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⛵️💎⛵️💎Zebec Network $ZBCN~2️⃣0️⃣2️⃣6️⃣ Synopsis~Prediction🚀🌍 By 2️⃣0️⃣2️⃣6️⃣, Zebec Network is positioned to be one of the most advanced real~time payment and payroll infrastructures in crypto and fintech. What started as a streaming~payments protocol has evolved into a full~stack financial rails provider + consumer~facing Super App: 💳📲🏦 🔴 Real~time payroll (second-by-second...

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AlphaLion

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11,804 views • 7 months ago •via X (Twitter)

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🇺🇸🌍🇺🇸 ZEBEC NETWORK IS NOW INSIDE THE U.S. PAYMENTS RAILS Most people will miss how big this is. Zebec Network is no longer operating around the financial system, it’s now operating inside it.🌍💳 🏦 What Just Happened Zebec Network has integrated directly with U.S. United States 🇺🇸 payment infrastructure, including: ✅ ACH (Automated Clearing House) ✅ Direct deposit rails ✅ Bank & payroll interoperability ✅ ISO 2️⃣0️⃣0️⃣2️⃣2️⃣ financial messaging 📡 This means Zebec can now move value where real money already flows, inside the same rails used by banks, employers, and payroll providers. 🔗 Why This Matters This isn’t a workaround. This isn’t an off~ramp. This is native alignment with U.S. payments infrastructure. 💼 Employers can run payroll 💰 Workers can receive wages 🔁 Funds can flow between bank accounts and programmable payments, all within a compliant, enterprise-ready framework. 🧠 Here the Bigger Picture Zebec is building a dual~rail system: 🏛️ Traditional finance rails (ACH, payroll, banks) Programmable, real~time payment rails Both operating together, not competing. That’s how infrastructure gets adopted. That’s how payments scale. That’s how Web3 becomes invisible, and useful. 🧱 Built for the Future 🔹🌐 ISO 20022 compliant 🔹 Interoperable with existing financial systems. Aligned with Nacha & ACH standards 🔹 Designed for payroll, treasury, and enterprise payments 🔹 Operating where regulation, compliance, and volume already exist This is infrastructure, not hype. 📌 In Simple Terms Zebec Network didn’t ask TradFi for permission. It plugged directly into the rails and started building. 🚆 Real rails 💵 Real money 🏗️ Real adoption Most people will scroll past this. Institutions won’t. Zebec Network
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🇺🇸🌍🇺🇸 ZEBEC NETWORK IS NOW INSIDE THE U.S. PAYMENTS RAILS Most people will miss how big this is. Zebec Network is no longer operating around the financial system, it’s now operating inside it.🌍💳 🏦 What Just Happened Zebec Network has integrated directly with U.S. United States 🇺🇸 payment infrastructure, including: ✅ ACH (Automated Clearing House) ✅ Direct deposit rails ✅ Bank & payroll interoperability ✅ ISO 2️⃣0️⃣0️⃣2️⃣2️⃣ financial messaging 📡 This means Zebec can now move value where real money already flows, inside the same rails used by banks, employers, and payroll providers. 🔗 Why This Matters This isn’t a workaround. This isn’t an off~ramp. This is native alignment with U.S. payments infrastructure. 💼 Employers can run payroll 💰 Workers can receive wages 🔁 Funds can flow between bank accounts and programmable payments, all within a compliant, enterprise-ready framework. 🧠 Here the Bigger Picture Zebec is building a dual~rail system: 🏛️ Traditional finance rails (ACH, payroll, banks) Programmable, real~time payment rails Both operating together, not competing. That’s how infrastructure gets adopted. That’s how payments scale. That’s how Web3 becomes invisible, and useful. 🧱 Built for the Future 🔹🌐 ISO 20022 compliant 🔹 Interoperable with existing financial systems. Aligned with Nacha & ACH standards 🔹 Designed for payroll, treasury, and enterprise payments 🔹 Operating where regulation, compliance, and volume already exist This is infrastructure, not hype. 📌 In Simple Terms Zebec Network didn’t ask TradFi for permission. It plugged directly into the rails and started building. 🚆 Real rails 💵 Real money 🏗️ Real adoption Most people will scroll past this. Institutions won’t. Zebec Network

AlphaLion

12,178 views • 8 months ago

🚨Uphold REPLACING YOUR BANK?!.. 🤯 Uphold just leveled up the game: ✅ XRP Credit Card ✅ Earn yield on your assets ✅ XRP-backed loans 🎯This isn’t crypto anymore… this is a FULL financial stack 🤯 Now here’s what people are missing 👇 ✅️ Zebec Network is ALREADY plugged into this future. 💳 Zebec Card = real-time spending 💸 Payroll streaming (not bi-weekly… INSTANT) 🌍 Multi-stablecoin + XRP rails potential 🤝 Positioned alongside both Ripple + Uphold ecosystems 👉 Translation: *As XRP rails expand through Uphold… *Zebec becomes the REAL WORLD USAGE LAYER 🙄While others are building speculation… 🛠Zebec is building PAYROLL, CARDS, and DAILY FINANCE ⚠️ This is how adoption actually happens: Infrastructure (Ripple) → Access (Uphold) → Usage (Zebec) Most people still don’t see it… $XRP 🤝 $ZBCN = money movement + money usage 🚀 The stack is forming right in front of you #XRP #Zebec #ZBCN #Crypto #Fintech #Ripple #Uphold #Web3 #Payments #Stablecoins ADP
3:30

🚨Uphold REPLACING YOUR BANK?!.. 🤯 Uphold just leveled up the game: ✅ XRP Credit Card ✅ Earn yield on your assets ✅ XRP-backed loans 🎯This isn’t crypto anymore… this is a FULL financial stack 🤯 Now here’s what people are missing 👇 ✅️ Zebec Network is ALREADY plugged into this future. 💳 Zebec Card = real-time spending 💸 Payroll streaming (not bi-weekly… INSTANT) 🌍 Multi-stablecoin + XRP rails potential 🤝 Positioned alongside both Ripple + Uphold ecosystems 👉 Translation: *As XRP rails expand through Uphold… *Zebec becomes the REAL WORLD USAGE LAYER 🙄While others are building speculation… 🛠Zebec is building PAYROLL, CARDS, and DAILY FINANCE ⚠️ This is how adoption actually happens: Infrastructure (Ripple) → Access (Uphold) → Usage (Zebec) Most people still don’t see it… $XRP 🤝 $ZBCN = money movement + money usage 🚀 The stack is forming right in front of you #XRP #Zebec #ZBCN #Crypto #Fintech #Ripple #Uphold #Web3 #Payments #Stablecoins ADP

Jetpack J0

69,486 views • 3 months ago

🌍 The world’s money is about to wake up. While everyone’s watching charts, the real power shift is happening underneath, a $150 trillion liquidity rotation quietly setting the stage for the next era of global finance. Two names are leading it, XRP and Zebec Network $ZBCN. One moves the money. The other keeps it in motion. Together, they’re building the rails for a system that never sleeps. ⚡️ 💧 XRP is the bridge, 🌉 the compliant rail for institutional liquidity, backed by ETFs, treasuries, and real settlement utility. It’s not speculation anymore, it’s infrastructure. ⚙️ Zebec $ZBCN is the flow, the payment engine turning capital into motion. Payroll, remittance, DeFi, gaming, real~world payments, Zebec is connecting with everyone. Visa. Visa Mastercard. Mastercard Ripple. Ripple Circle. Circle Stellar. Stellar Algorand. Algorand Foundation Even major banks.🏦 Zebec isn’t competing with the ecosystem, it’s powering it. From instant payroll to streaming yield, from stablecoins to CBDCs, Zebec is the motion layer for all of it. Together, $XRP and $ZBCN form the Internet of Value, where money doesn’t wait, doesn’t pause, doesn’t settle overnight. It moves. Instantly. Globally. In real time. 🔥🚀 Tik-Tok, Coach Tom JV xrpdaily
1:13

🌍 The world’s money is about to wake up. While everyone’s watching charts, the real power shift is happening underneath, a $150 trillion liquidity rotation quietly setting the stage for the next era of global finance. Two names are leading it, XRP and Zebec Network $ZBCN. One moves the money. The other keeps it in motion. Together, they’re building the rails for a system that never sleeps. ⚡️ 💧 XRP is the bridge, 🌉 the compliant rail for institutional liquidity, backed by ETFs, treasuries, and real settlement utility. It’s not speculation anymore, it’s infrastructure. ⚙️ Zebec $ZBCN is the flow, the payment engine turning capital into motion. Payroll, remittance, DeFi, gaming, real~world payments, Zebec is connecting with everyone. Visa. Visa Mastercard. Mastercard Ripple. Ripple Circle. Circle Stellar. Stellar Algorand. Algorand Foundation Even major banks.🏦 Zebec isn’t competing with the ecosystem, it’s powering it. From instant payroll to streaming yield, from stablecoins to CBDCs, Zebec is the motion layer for all of it. Together, $XRP and $ZBCN form the Internet of Value, where money doesn’t wait, doesn’t pause, doesn’t settle overnight. It moves. Instantly. Globally. In real time. 🔥🚀 Tik-Tok, Coach Tom JV xrpdaily

AlphaLion

45,706 views • 10 months ago

Zebec Protocol has taken 2026 by storm... Zebec Network (Zebec Network) describes itself as "rails for real-time finance." In simple terms, this means the protocol allows individuals and organizations to transfer funds instantaneously (be it payroll, contractor payments, or benefits) using both traditional systems, such as ACH and FedNow, and blockchain in a single package. This year, Zebec has gone from a promising concept to an institution-backed protocol. Here is an overview: Progress in Institutional Adoption and Compliance 1.) Innovation of Zebec Payments within Nacha: Zebec applied late in 2025 and was confirmed as a member in early 2026, belonging to the same cohort as Circle. 2.) Compliance with ISO 20022: This is a universal banking message format standard (just like SWIFT). Aligning with it ensures that Zebec can "speak the same language" as major financial institutions. 3.) NatPay Integration: NatPay settles about $158–$170 billion worth of ACH transactions each year through hundreds of thousands of clients. Integration with Zebec enables businesses to pay employees via legacy banking and instantaneous blockchain streaming services... 4.) Stellar Integration: Stellar appointed Zebec as its preferred infrastructure partner for stablecoin payroll – Zebec's first major implementation off of Solana. 5.) AllUnity (AllUnity) partnership (June 25, 2026): AllUnity selected Zebec as the infrastructure partner to provide an on-chain government benefits scheme in Europe, leveraging their regulated euro stablecoin (EURAU). 6.) Velo Protocol partnership: Velo Official has partnered exclusively with Zebec as their card and infrastructure partner for their settlement layer connecting with Zebec's card solutions. 7.) Institutional Compliance Initiative: The wider effort involving MiCA (crypto regulations in the EU) preparations, on-chain treasury buybacks, and enterprise integrations. Product Launches & Upgrades 1.) Zebec SuperApp: Desktop release in late February 2026; iOS and Android versions launched on July 13, 2026. 2.) Enterprise Payroll payout via Stellar: Allows employees to turn their crypto salary into local currency in more than 50 countries through integration with MoneyGram. 3.) New assets available: USD1, tGBP (a stablecoin pegged to the UK pound), DASH, and EURAU 4.) Onboarding employee capabilities: Custom-made wallets, including Tangem hardware/NFC card and Privy wallet stack in order to help non-crypto-savvy employees. 5.) Privacy: Early-stage integrations looking into Aleo (private cards/payments) and mentions of the Canton privacy solution. Key Numbers to Know - ~250 enterprise clients using Zebec's payroll and payment tools - 100,000+ $ZBCN token holders - 40+ white-label card partners - 15+ blockchains supported for cards and payments - ~$65 million rolling annualized card transaction volume (from earlier updates) - Cards available in dozens of countries, with tens of thousands issued and hundreds of thousands of transactions processed
0:30

Zebec Protocol has taken 2026 by storm... Zebec Network (Zebec Network) describes itself as "rails for real-time finance." In simple terms, this means the protocol allows individuals and organizations to transfer funds instantaneously (be it payroll, contractor payments, or benefits) using both traditional systems, such as ACH and FedNow, and blockchain in a single package. This year, Zebec has gone from a promising concept to an institution-backed protocol. Here is an overview: Progress in Institutional Adoption and Compliance 1.) Innovation of Zebec Payments within Nacha: Zebec applied late in 2025 and was confirmed as a member in early 2026, belonging to the same cohort as Circle. 2.) Compliance with ISO 20022: This is a universal banking message format standard (just like SWIFT). Aligning with it ensures that Zebec can "speak the same language" as major financial institutions. 3.) NatPay Integration: NatPay settles about $158–$170 billion worth of ACH transactions each year through hundreds of thousands of clients. Integration with Zebec enables businesses to pay employees via legacy banking and instantaneous blockchain streaming services... 4.) Stellar Integration: Stellar appointed Zebec as its preferred infrastructure partner for stablecoin payroll – Zebec's first major implementation off of Solana. 5.) AllUnity (AllUnity) partnership (June 25, 2026): AllUnity selected Zebec as the infrastructure partner to provide an on-chain government benefits scheme in Europe, leveraging their regulated euro stablecoin (EURAU). 6.) Velo Protocol partnership: Velo Official has partnered exclusively with Zebec as their card and infrastructure partner for their settlement layer connecting with Zebec's card solutions. 7.) Institutional Compliance Initiative: The wider effort involving MiCA (crypto regulations in the EU) preparations, on-chain treasury buybacks, and enterprise integrations. Product Launches & Upgrades 1.) Zebec SuperApp: Desktop release in late February 2026; iOS and Android versions launched on July 13, 2026. 2.) Enterprise Payroll payout via Stellar: Allows employees to turn their crypto salary into local currency in more than 50 countries through integration with MoneyGram. 3.) New assets available: USD1, tGBP (a stablecoin pegged to the UK pound), DASH, and EURAU 4.) Onboarding employee capabilities: Custom-made wallets, including Tangem hardware/NFC card and Privy wallet stack in order to help non-crypto-savvy employees. 5.) Privacy: Early-stage integrations looking into Aleo (private cards/payments) and mentions of the Canton privacy solution. Key Numbers to Know - ~250 enterprise clients using Zebec's payroll and payment tools - 100,000+ $ZBCN token holders - 40+ white-label card partners - 15+ blockchains supported for cards and payments - ~$65 million rolling annualized card transaction volume (from earlier updates) - Cards available in dozens of countries, with tens of thousands issued and hundreds of thousands of transactions processed

BSCN

35,540 views • 18 days ago

Executive Thesis - Ripple Bank 2025 If Ripple secures bank-like permissions (U.S. national bank charter or state ILC plus key foreign licenses) and runs RL-stablecoins and XRPL rails under a Basel-caliber risk, capital, and compliance stack, it can become a regulated global settlement and asset-services platform. That platform could let central banks, sovereign treasuries, and regulated financial institutions issue, custody, trade, and settle stablecoins and tokenized RWAs (stocks, bonds, commodities, derivatives) with ISO 20022 native messaging, BSA/AML–FATF controls, and Basel III capital/liquidity governance—collapsing today’s slow correspondent chains into a single, high-compliance operating layer. The “Boom” Implications With the right charter(s), prudential regime, and partnerships, Ripple can become a compliance-first global neo-banking platform that (1) absorbs cross-border payment flows from correspondent networks, (2) powers CBDC and sovereign tokenized markets, and (3) monetizes issuance, custody, settlement, and compliance at scale—all inside Basel III, BSA/AML, FATF, and ISO 20022 guardrails. Impact on XRP If Ripple Bank were formally approved and XRP became the primary liquidity and settlement token across its’ regulated ecosystem, the economic demand for XRP would expand exponentially - transforming it from a speculative asset into regulated financial infrastructure. Structural Shift in XRP Demand From Speculative to Utility-backed Demand • XRP’s value today is primarily market-driven by speculation on future adoption. • Under a Ripple Bank framework, XRP becomes a mandatory utility asset — required for: • Settlement liquidity between all tokenized assets on XRPL (CBDCs, stablecoins, RWAs, derivatives). • Transaction fees and compliance verification across billions of high-value financial messages. • Collateral in interbank, treasury, and derivative clearing functions. This converts XRP from “optional” to “indispensable” in regulated settlement flows - similar to how SWIFT messaging depends on correspondent Nostro/Vostro liquidity BUT executed on a frictionless, tokenized rail. Volume & Velocity Effects Token velocity decreases, float demand increases • Basel III and liquidity regulations require prefunded, high-quality settlement collateral. • As banks, sovereigns, and institutions hold XRP as a liquidity reserve (like Tier-1 capital equivalents for tokenized payments), circulating supply falls while volume increases—driving scarcity-driven price appreciation. An Example of Flow Scale • Global wholesale payments ≈ $250T/year. • If 10% settles through Ripple’s bank-backed network using XRP at a 3-day velocity (roughly 120 settlement turns per year): • Required float ≈ $2.1T equivalent demand. • Even at $100/XRP, that implies 20B XRP locked in active liquidity operations. • At today’s 15B non-escrowed supply, value equilibrium could theoretically exceed $140–$200 per token, depending on velocity and collateral requirements. From today’s ~$3 price, this implies a 46x to 66x price surge. Are we ready? Ripple Treasury Department OCC Comptroller Jonathan Gould
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Executive Thesis - Ripple Bank 2025 If Ripple secures bank-like permissions (U.S. national bank charter or state ILC plus key foreign licenses) and runs RL-stablecoins and XRPL rails under a Basel-caliber risk, capital, and compliance stack, it can become a regulated global settlement and asset-services platform. That platform could let central banks, sovereign treasuries, and regulated financial institutions issue, custody, trade, and settle stablecoins and tokenized RWAs (stocks, bonds, commodities, derivatives) with ISO 20022 native messaging, BSA/AML–FATF controls, and Basel III capital/liquidity governance—collapsing today’s slow correspondent chains into a single, high-compliance operating layer. The “Boom” Implications With the right charter(s), prudential regime, and partnerships, Ripple can become a compliance-first global neo-banking platform that (1) absorbs cross-border payment flows from correspondent networks, (2) powers CBDC and sovereign tokenized markets, and (3) monetizes issuance, custody, settlement, and compliance at scale—all inside Basel III, BSA/AML, FATF, and ISO 20022 guardrails. Impact on XRP If Ripple Bank were formally approved and XRP became the primary liquidity and settlement token across its’ regulated ecosystem, the economic demand for XRP would expand exponentially - transforming it from a speculative asset into regulated financial infrastructure. Structural Shift in XRP Demand From Speculative to Utility-backed Demand • XRP’s value today is primarily market-driven by speculation on future adoption. • Under a Ripple Bank framework, XRP becomes a mandatory utility asset — required for: • Settlement liquidity between all tokenized assets on XRPL (CBDCs, stablecoins, RWAs, derivatives). • Transaction fees and compliance verification across billions of high-value financial messages. • Collateral in interbank, treasury, and derivative clearing functions. This converts XRP from “optional” to “indispensable” in regulated settlement flows - similar to how SWIFT messaging depends on correspondent Nostro/Vostro liquidity BUT executed on a frictionless, tokenized rail. Volume & Velocity Effects Token velocity decreases, float demand increases • Basel III and liquidity regulations require prefunded, high-quality settlement collateral. • As banks, sovereigns, and institutions hold XRP as a liquidity reserve (like Tier-1 capital equivalents for tokenized payments), circulating supply falls while volume increases—driving scarcity-driven price appreciation. An Example of Flow Scale • Global wholesale payments ≈ $250T/year. • If 10% settles through Ripple’s bank-backed network using XRP at a 3-day velocity (roughly 120 settlement turns per year): • Required float ≈ $2.1T equivalent demand. • Even at $100/XRP, that implies 20B XRP locked in active liquidity operations. • At today’s 15B non-escrowed supply, value equilibrium could theoretically exceed $140–$200 per token, depending on velocity and collateral requirements. From today’s ~$3 price, this implies a 46x to 66x price surge. Are we ready? Ripple Treasury Department OCC Comptroller Jonathan Gould

Rob Cunningham

10,911 views • 10 months ago

Two XRP Paths: Rejection vs. Adoption 1) Total Failure Case — XRP → $0.00 (Global Rejection) For XRP to go to $0, ALL of the following must occur - not one, but collectively: A. Regulatory Extinction (Binary Kill Switch) Coordinated global classification as: Unregistered security with no path to compliance Or outright restriction in major jurisdictions (U.S., EU, Japan) Exchanges delist → liquidity evaporates Custodians refuse to hold → institutions cannot touch it 👉 Without lawful on/off ramps, price discovery dies. B. Institutional Rejection of XRPL Utility Banks choose alternatives: Private permissioned ledgers CBDC rails with no bridge asset No real transaction demand = no need for XRP as liquidity 👉 Utility collapses → speculation alone cannot sustain value long term. C. Liquidity Death Spiral Market makers exit Spreads widen → volatility spikes Capital rotates to “approved” rails 👉 A monetary asset without liquidity becomes non-money. D. Network Irrelevance Developers leave No meaningful tokenization, payments, or settlement flows XRPL becomes a ghost chain E. Loss of Trust (Final Blow) Credible exploit, governance failure, or fatal flaw Or simply: better, compliant alternative wins 🧠 XRP Truth Check To reach $0.00, XRP must fail at: Law (permission to exist) Utility (reason to be used) Liquidity (ability to transact) Trust (confidence in system integrity) That is a full-spectrum collapse, not a partial miss. 🚀 2) Adoption Case — XRP → $100 in 5 yrs (Major Integration) 🔵 Let’s flip the lens. 🔵 If XRP moves from $1.40 → $100 in 5 years, it’s a ~71× move - or 135% Compounded Annual Growth Rate (CAGR) over 5 years. A. Regulatory Clarity (Foundation Layer) Let’s tie this to: 1) Digital Asset Market Clarity Act 2) GENIUS Act What must then be true: 1) XRP is clearly not a security in secondary markets Legal frameworks enable XRP: 2) Custody 3) Settlement 4) Bank usage 5) Balance sheet treatment B. Institutional Adoption (Demand Engine) Banks, payment providers, and asset managers: • Use XRP as bridge liquidity • Integrate into cross-border settlement • Leverage XRPL for tokenization rails Think: • Treasury flows • FX settlement • Tokenized securities movement 👉 This is where real demand begins - not speculation. C. Liquidity Scaling (Critical Inflection) • Global payments: ~$100T+ annually • Capital trapped in nostro/vostro accounts • Settlement inefficiencies If XRP: 1) Reduces friction 2) Frees capital 3) Enables atomic settlement 👉 Then liquidity demand becomes structural, not optional. D. Network Effects (Compounding Reality) • More institutions → deeper liquidity • Deeper liquidity → tighter spreads • Tighter spreads → more usage 👉 This is how a neutral bridge asset gains gravitational pull. E. Monetary Role Expansion For $100 to be rationally defensible: XRP must evolve from: “crypto asset” into: neutral settlement layer for value transfer That implies: • High velocity usage • Deep global liquidity pools • Continuous transactional demand 📈 What $100 Actually Implies Let’s speak plainly: $100 XRP ≈ $5–6 trillion value Comparable to: - Gold (partial) - Major sovereign liquidity layers - Core financial infrastructure 👉 This is not a “price move” 👉 This is a monetary role transition Final Discernment with No Hype Buyers are not weighing: “Will price go up or down?” They’re weighing: “Will the XRPL/XRP system be used… or not?” Because price is downstream of one thing: Sustained, lawful, global demand for its function ⚡ The Real XRP Question If a system delivers: • Faster settlement • Lower cost • Verifiable truth • Reduced counterparty risk Then ask: Who, acting rationally, chooses a slower, more expensive, opaque alternative… if given a lawful choice? That answer - not sentiment - determines whether XRP trends toward $0… or $100. Ripple Cointelegraph CNBC SMQKE JMC Broadcasting
1:40

Two XRP Paths: Rejection vs. Adoption 1) Total Failure Case — XRP → $0.00 (Global Rejection) For XRP to go to $0, ALL of the following must occur - not one, but collectively: A. Regulatory Extinction (Binary Kill Switch) Coordinated global classification as: Unregistered security with no path to compliance Or outright restriction in major jurisdictions (U.S., EU, Japan) Exchanges delist → liquidity evaporates Custodians refuse to hold → institutions cannot touch it 👉 Without lawful on/off ramps, price discovery dies. B. Institutional Rejection of XRPL Utility Banks choose alternatives: Private permissioned ledgers CBDC rails with no bridge asset No real transaction demand = no need for XRP as liquidity 👉 Utility collapses → speculation alone cannot sustain value long term. C. Liquidity Death Spiral Market makers exit Spreads widen → volatility spikes Capital rotates to “approved” rails 👉 A monetary asset without liquidity becomes non-money. D. Network Irrelevance Developers leave No meaningful tokenization, payments, or settlement flows XRPL becomes a ghost chain E. Loss of Trust (Final Blow) Credible exploit, governance failure, or fatal flaw Or simply: better, compliant alternative wins 🧠 XRP Truth Check To reach $0.00, XRP must fail at: Law (permission to exist) Utility (reason to be used) Liquidity (ability to transact) Trust (confidence in system integrity) That is a full-spectrum collapse, not a partial miss. 🚀 2) Adoption Case — XRP → $100 in 5 yrs (Major Integration) 🔵 Let’s flip the lens. 🔵 If XRP moves from $1.40 → $100 in 5 years, it’s a ~71× move - or 135% Compounded Annual Growth Rate (CAGR) over 5 years. A. Regulatory Clarity (Foundation Layer) Let’s tie this to: 1) Digital Asset Market Clarity Act 2) GENIUS Act What must then be true: 1) XRP is clearly not a security in secondary markets Legal frameworks enable XRP: 2) Custody 3) Settlement 4) Bank usage 5) Balance sheet treatment B. Institutional Adoption (Demand Engine) Banks, payment providers, and asset managers: • Use XRP as bridge liquidity • Integrate into cross-border settlement • Leverage XRPL for tokenization rails Think: • Treasury flows • FX settlement • Tokenized securities movement 👉 This is where real demand begins - not speculation. C. Liquidity Scaling (Critical Inflection) • Global payments: ~$100T+ annually • Capital trapped in nostro/vostro accounts • Settlement inefficiencies If XRP: 1) Reduces friction 2) Frees capital 3) Enables atomic settlement 👉 Then liquidity demand becomes structural, not optional. D. Network Effects (Compounding Reality) • More institutions → deeper liquidity • Deeper liquidity → tighter spreads • Tighter spreads → more usage 👉 This is how a neutral bridge asset gains gravitational pull. E. Monetary Role Expansion For $100 to be rationally defensible: XRP must evolve from: “crypto asset” into: neutral settlement layer for value transfer That implies: • High velocity usage • Deep global liquidity pools • Continuous transactional demand 📈 What $100 Actually Implies Let’s speak plainly: $100 XRP ≈ $5–6 trillion value Comparable to: - Gold (partial) - Major sovereign liquidity layers - Core financial infrastructure 👉 This is not a “price move” 👉 This is a monetary role transition Final Discernment with No Hype Buyers are not weighing: “Will price go up or down?” They’re weighing: “Will the XRPL/XRP system be used… or not?” Because price is downstream of one thing: Sustained, lawful, global demand for its function ⚡ The Real XRP Question If a system delivers: • Faster settlement • Lower cost • Verifiable truth • Reduced counterparty risk Then ask: Who, acting rationally, chooses a slower, more expensive, opaque alternative… if given a lawful choice? That answer - not sentiment - determines whether XRP trends toward $0… or $100. Ripple Cointelegraph CNBC SMQKE JMC Broadcasting

Rob Cunningham

44,184 views • 3 months ago

25 Questions, $3.7 Quadrillion About The Convergence of DTCC, U.S. Treasury, Ripple, RLUSD & XRP 1. What happens when the world’s largest settlement utility - DTCC - moves to tokenized rails? Q Why would the DTCC, which safely moves $3.7 quadrillion a year through legacy rails, suddenly step into blockchain tokenization? A Because the old rails can’t support real-time global liquidity, 24/7 settlement, or tokenized assets. They were built for a slower age. Q And when DTCC modernizes, does the world follow? A Whoever controls the settlement layer of America controls the future of global liquidity. So yes - the world must follow. 2. What kind of blockchain qualifies for DTCC-level settlement? Q Would DTCC ever rely on a chain with probabilistic finality? With MEV extraction? With congestion-based fees? With uncertainty or frequent outages? A Of course not. A quadrillion-dollar system cannot run on chaos. Q Then which systems could support that level of global settlement? A Only ledgers with deterministic finality, predictable fees, regulatory compliance, institutional trust, and native support for asset issuance. This drastically narrows the field. 3. Why did two of the most powerful U.S. financial officials join Ripple? Q Why would Michael Bodson — former CEO of DTCC - join Ripple’s advisory board? A Because he recognizes Ripple’s architecture mirrors the settlement environment he spent a decade modernizing. Q Why would RosIe Rios - former U.S. Treasurer with oversight over the nation’s currency - also join Ripple’s board? A Because she sees where the monetary system is going: Tokenized dollars. Tokenized assets. A neutral, global liquidity asset. A real-time settlement ledger. And Ripple is building exactly that. 4. What does RLUSD being regulated by the NYDFS tell us? Q Why does Ripple choose the most stringent regulatory regime in the country - the NYDFS - for issuing its stablecoin? A Because if you want to operate on America’s financial plumbing, you must build at America’s highest regulatory standard. Q And what does NYDFS require of a stablecoin? A Full dollar backing. Audits. Transparency. No rehypothecation. Operational integrity. Q What ledger fits that requirement without modification? A XRPL - the ledger built for institutional-grade, regulated settlement. 5. Why is RLUSD paired with XRP? Q What is RLUSD? A payment instrument or a liquidity instrument? A It is the cash leg - the digital dollar. Q But can a dollar, even a tokenized one, bridge FX markets, settle cross-jurisdictional flows, or provide global liquidity? A No. That requires a neutral bridge asset. Q So if RLUSD is the cash leg, what is the liquidity leg? A XRP - by design, by architecture, by function. 6. What ledger is built for institutional settlement? Q Why was XRPL built with deterministic finality instead of probabilistic settlement? A Because real-time finance cannot settle on uncertainty. Q Why does XRPL have no MEV? No gas auctions? Predictable fees? A Because institutional liquidity cannot be subject to market manipulation or extraction. Q Why does the XRPL support issued assets (IOUs) natively? Tokenization? Atomic settlement? A Because its purpose is to be the global clearing and liquidity layer for digital finance. 7. Why is ISO 20022 important here? Q Does global finance run on random messaging formats? A No. It runs on standardization - ISO 20022. Q Which blockchain ecosystem was designed from inception to align with ISO 20022 semantics? A Ripple’s network and XRPL. Q Why does this matter? Because tokenized finance requires a standardized global language for value. 8. Why Rosie Rios and America 250 matter? Q Why would the Chair of America 250, a Congressionally chartered commission defining America’s future story, be tied to Ripple? A Because America’s 250th anniversary is not merely symbolic — it is a narrative reset for national identity, sovereignty, competitiveness, and economic renewal.
3:09

25 Questions, $3.7 Quadrillion About The Convergence of DTCC, U.S. Treasury, Ripple, RLUSD & XRP 1. What happens when the world’s largest settlement utility - DTCC - moves to tokenized rails? Q Why would the DTCC, which safely moves $3.7 quadrillion a year through legacy rails, suddenly step into blockchain tokenization? A Because the old rails can’t support real-time global liquidity, 24/7 settlement, or tokenized assets. They were built for a slower age. Q And when DTCC modernizes, does the world follow? A Whoever controls the settlement layer of America controls the future of global liquidity. So yes - the world must follow. 2. What kind of blockchain qualifies for DTCC-level settlement? Q Would DTCC ever rely on a chain with probabilistic finality? With MEV extraction? With congestion-based fees? With uncertainty or frequent outages? A Of course not. A quadrillion-dollar system cannot run on chaos. Q Then which systems could support that level of global settlement? A Only ledgers with deterministic finality, predictable fees, regulatory compliance, institutional trust, and native support for asset issuance. This drastically narrows the field. 3. Why did two of the most powerful U.S. financial officials join Ripple? Q Why would Michael Bodson — former CEO of DTCC - join Ripple’s advisory board? A Because he recognizes Ripple’s architecture mirrors the settlement environment he spent a decade modernizing. Q Why would RosIe Rios - former U.S. Treasurer with oversight over the nation’s currency - also join Ripple’s board? A Because she sees where the monetary system is going: Tokenized dollars. Tokenized assets. A neutral, global liquidity asset. A real-time settlement ledger. And Ripple is building exactly that. 4. What does RLUSD being regulated by the NYDFS tell us? Q Why does Ripple choose the most stringent regulatory regime in the country - the NYDFS - for issuing its stablecoin? A Because if you want to operate on America’s financial plumbing, you must build at America’s highest regulatory standard. Q And what does NYDFS require of a stablecoin? A Full dollar backing. Audits. Transparency. No rehypothecation. Operational integrity. Q What ledger fits that requirement without modification? A XRPL - the ledger built for institutional-grade, regulated settlement. 5. Why is RLUSD paired with XRP? Q What is RLUSD? A payment instrument or a liquidity instrument? A It is the cash leg - the digital dollar. Q But can a dollar, even a tokenized one, bridge FX markets, settle cross-jurisdictional flows, or provide global liquidity? A No. That requires a neutral bridge asset. Q So if RLUSD is the cash leg, what is the liquidity leg? A XRP - by design, by architecture, by function. 6. What ledger is built for institutional settlement? Q Why was XRPL built with deterministic finality instead of probabilistic settlement? A Because real-time finance cannot settle on uncertainty. Q Why does XRPL have no MEV? No gas auctions? Predictable fees? A Because institutional liquidity cannot be subject to market manipulation or extraction. Q Why does the XRPL support issued assets (IOUs) natively? Tokenization? Atomic settlement? A Because its purpose is to be the global clearing and liquidity layer for digital finance. 7. Why is ISO 20022 important here? Q Does global finance run on random messaging formats? A No. It runs on standardization - ISO 20022. Q Which blockchain ecosystem was designed from inception to align with ISO 20022 semantics? A Ripple’s network and XRPL. Q Why does this matter? Because tokenized finance requires a standardized global language for value. 8. Why Rosie Rios and America 250 matter? Q Why would the Chair of America 250, a Congressionally chartered commission defining America’s future story, be tied to Ripple? A Because America’s 250th anniversary is not merely symbolic — it is a narrative reset for national identity, sovereignty, competitiveness, and economic renewal.

Rob Cunningham

152,835 views • 8 months ago

“THE SWITCH” - A 2026 Reveal “Best case” does not mean everything wins - it means the right infrastructure gets used at scale. Only a few systems will sit inside the flow of value itself. Protocols that move value scale with usage, not narrative. Global finance is being re-architected • Settlement is moving from T+2 → real-time • Trust is moving from institutions → verifiable systems VARIABLE-BY-VARIABLE IMPACT (The Chain Reaction) Let’s connect all variables like a circuit - not as isolated headlines. A) Regulatory Clarity (Clarity Act + Genius Frameworks) Effects: • Removes existential risk • Unlocks institutional participation • Enables banks, funds, treasuries to legally deploy capital Second-order: • Compliance-first platforms win • Systems already aligned with regulators accelerate fastest 👉 This directly favors: • Ripple (enterprise + regulatory posture) • XRP Ledger (built for issuance, settlement, compliance hooks) B) Fed Rate Cuts + Liquidity Expansion Effect: • Capital rotates out of “parked safety” • Risk assets + growth infrastructure reprice upward • Search for yield → search for efficiency Second-order: • Systems that reduce cost of capital movement become attractive 👉 XRP’s core function: • Bridge asset → reduces trapped capital globally C) Oil Price Decline Effect: • Lowers global cost basis (transport, manufacturing, logistics) • Reduces inflationary pressures Second-order: • Allows central banks to ease more aggressively • Expands global transaction volume 👉 More transactions = more need for: • Fast, low-cost settlement rails D) Tariff Revenues + Domestic Productivity Growth Effect: • Strengthens sovereign balance sheet • Incentivizes onshoring / reshoring Second-order: • Increased cross-border + supply chain complexity • More currency corridors, not fewer 👉 Complexity increases demand for: • Neutral, interoperable, low-cost settlement layers E) Crypto Capital of the World” Effect: • Regulatory + capital + talent concentration in the U.S. • Wall Street + Silicon Valley convergence Second-order: • Institutional-grade infrastructure becomes the battleground • Not memes. Not speculation. Systems. 👉 This is where: • Ripple has been positioned for over a decade F) Trillions in Tokenization + Stablecoins This is the big one. Effect: • Real-world assets (RWAs) → on-chain • Stablecoins → transactional liquidity layer Second-order: Massive need for: • Interoperability • Liquidity routing • Real-time settlement between tokenized silos 👉 Critical question: What connects all these systems together? Not: • Ethereum alone • Not private bank chains • Not CBDCs in isolation But: A neutral bridge between systems That’s the exact design purpose of: • XRP on the XRP Ledger THE CONVERGENCE EFFECT Individually, each factor is bullish. Together? They create a phase transition. From: • Fragmented finance • Slow settlement • Capital trapped in corridors To: • Continuous, global, real-time, efficient liquidity 4) WHAT THIS MEANS SPECIFICALLY FOR RIPPLE / XRPL / XRP Let’s separate the stack: 1) Ripple (Company Layer) • Becomes a primary enterprise gateway Sells infrastructure to: • Banks • Governments • Payment providers Outcome: Revenue growth tied to adoption of new rails 2) XRP Ledger (Protocol Layer) Hosts: • Tokenized assets • Stablecoins • DEX liquidity • Settlement logic Outcome: Network effects compound exponentially as assets onboard 3) XRP (Asset Layer) This is where many people get confused. Its role is not “just price.” Its role is: • Liquidity bridge • Settlement asset • Neutral counterparty Demand is driven by utility + velocity + scale of value transfer SIMPLE ANALOGY • Should you invest in cars? • Or in the highway system all cars must use? XRP becomes THE bridge in high-volume, global corridors that connects TradFi to DeFi Now you know the full story! LOCK IN! Ripple Treasury Department President Donald J. Trump
5:13

“THE SWITCH” - A 2026 Reveal “Best case” does not mean everything wins - it means the right infrastructure gets used at scale. Only a few systems will sit inside the flow of value itself. Protocols that move value scale with usage, not narrative. Global finance is being re-architected • Settlement is moving from T+2 → real-time • Trust is moving from institutions → verifiable systems VARIABLE-BY-VARIABLE IMPACT (The Chain Reaction) Let’s connect all variables like a circuit - not as isolated headlines. A) Regulatory Clarity (Clarity Act + Genius Frameworks) Effects: • Removes existential risk • Unlocks institutional participation • Enables banks, funds, treasuries to legally deploy capital Second-order: • Compliance-first platforms win • Systems already aligned with regulators accelerate fastest 👉 This directly favors: • Ripple (enterprise + regulatory posture) • XRP Ledger (built for issuance, settlement, compliance hooks) B) Fed Rate Cuts + Liquidity Expansion Effect: • Capital rotates out of “parked safety” • Risk assets + growth infrastructure reprice upward • Search for yield → search for efficiency Second-order: • Systems that reduce cost of capital movement become attractive 👉 XRP’s core function: • Bridge asset → reduces trapped capital globally C) Oil Price Decline Effect: • Lowers global cost basis (transport, manufacturing, logistics) • Reduces inflationary pressures Second-order: • Allows central banks to ease more aggressively • Expands global transaction volume 👉 More transactions = more need for: • Fast, low-cost settlement rails D) Tariff Revenues + Domestic Productivity Growth Effect: • Strengthens sovereign balance sheet • Incentivizes onshoring / reshoring Second-order: • Increased cross-border + supply chain complexity • More currency corridors, not fewer 👉 Complexity increases demand for: • Neutral, interoperable, low-cost settlement layers E) Crypto Capital of the World” Effect: • Regulatory + capital + talent concentration in the U.S. • Wall Street + Silicon Valley convergence Second-order: • Institutional-grade infrastructure becomes the battleground • Not memes. Not speculation. Systems. 👉 This is where: • Ripple has been positioned for over a decade F) Trillions in Tokenization + Stablecoins This is the big one. Effect: • Real-world assets (RWAs) → on-chain • Stablecoins → transactional liquidity layer Second-order: Massive need for: • Interoperability • Liquidity routing • Real-time settlement between tokenized silos 👉 Critical question: What connects all these systems together? Not: • Ethereum alone • Not private bank chains • Not CBDCs in isolation But: A neutral bridge between systems That’s the exact design purpose of: • XRP on the XRP Ledger THE CONVERGENCE EFFECT Individually, each factor is bullish. Together? They create a phase transition. From: • Fragmented finance • Slow settlement • Capital trapped in corridors To: • Continuous, global, real-time, efficient liquidity 4) WHAT THIS MEANS SPECIFICALLY FOR RIPPLE / XRPL / XRP Let’s separate the stack: 1) Ripple (Company Layer) • Becomes a primary enterprise gateway Sells infrastructure to: • Banks • Governments • Payment providers Outcome: Revenue growth tied to adoption of new rails 2) XRP Ledger (Protocol Layer) Hosts: • Tokenized assets • Stablecoins • DEX liquidity • Settlement logic Outcome: Network effects compound exponentially as assets onboard 3) XRP (Asset Layer) This is where many people get confused. Its role is not “just price.” Its role is: • Liquidity bridge • Settlement asset • Neutral counterparty Demand is driven by utility + velocity + scale of value transfer SIMPLE ANALOGY • Should you invest in cars? • Or in the highway system all cars must use? XRP becomes THE bridge in high-volume, global corridors that connects TradFi to DeFi Now you know the full story! LOCK IN! Ripple Treasury Department President Donald J. Trump

Rob Cunningham

17,722 views • 4 months ago

🌐 BenFen | Next-Gen Multi-Currency Stablecoin Blockchain BenFen is a Layer1 blockchain purpose-built for stablecoin issuance, adoption, and payments, providing trusted and accessible on-chain payment infrastructure for global users and developers. 🟥 Technical Architecture：Built on the Move language, ensuring security, high performance, and accessibility. 🔹 Modular contract design ensures asset security and tamper-proof rules for reliable system operation. 🔹 Sub-second transaction confirmation with stable 10,000+ TPS, optimized for payment and interaction scenarios. 🔹 Supports zkLogin, enabling one-click wallet creation with Google/Apple ID. 🟥 BUSD Stablecoin Mechanism ：Pegged to USDT/USDC, the core on-chain asset 🔹 Cross-chain 1:1 pegged minting with USDT/USDC, wit h native support for stablecoin GAS payments. 🔹 Supports mainstream G20 fiat-backed stablecoin conversions (eg, BUSD/BJPY, BUSD/BEUR). 🔹 Covers key scenarios like asset trading, RWA mapping, on-chain payroll, and daily consumption. 🟥 Native Features: Full-stack capabilities centered around stablecoins 🔹 Supports one-click issuance of stablecoins/RWAs, lowering development barriers. 🔹 Any issued stablecoin can be registered as a Gas token, with sponsored transactions available for Gas subsidies. 🔹 Zero-cost transfers for specific scenarios, enabling real "zero-fee payments". 🔹 Privacy accounts and payments: Supports hidden addresses and balances for privacy-focused use cases. 🔹 Multi-chain asset payments + G20 fiat settlement: Real-time settlement of USDT, SOL, ETH, and other major assets into BJPY, BEUR, BAUD, and other G20 stablecoins. 🟥 Native Cross-Chain Bridge 🔹 Proprietary native cross-chain protocol. 🔹 Supports BTC, ETH, BSC, Polygon, Optimism, Solana, TRON, Base, Avalanche, and more. 🔹 No third-party bridge is needed; assets can be cross-chain with just one click, offering fast, secure, on-chain verification and second-level fund arrival. 📱 BenFen Ecosystem 🔹 BenPay: An open, secure, and efficient comprehensive payment ecosystem, offering users a convenient and secure cryptocurrency payment channel. 🔹 BenPay Card: On-chain self-custodial payment card, with keys in hand, enabling global spending (Supports Apple Pay, Alipay, Amazon, Netflix, X, ChatGPT, etc.). 🔹 BenPay C2C: secure peer-to-peer decentralized trading marketplace. 🔹 BenPay DeFi Earn:A cross-chain yield farming protocol that allows stablecoins from major blockchains to be seamlessly transferred and deposited into high-APY farming pools. 🔹 BenPay DEX: One-click swaps and aggregated matching for stablecoins/crypto assets. 🔹 BenPay Lending: Decentralized finance protocol supporting BTC collateral and USDT lending. 🔹 BenPay Stake: Stake BFC to gain governance rights, ecosystem rewards, and airdrops. 🟥 BenFen DAO 🔹 Utilizes formal verification for security, supporting low-cost proposals and voting to promote community autonomous governance and rights protection. 🟥 Developer-Friendly Platform：Building a low-barrier development ecosystem 🔹 Provides standard SDKs/APIs/contract templates. 🔹 Supports full-cycle development scenarios like stablecoin issuance, RWA issuance, wallet integration, and DeFi application building. 🔹 Lowers development barriers to accelerate innovation. 🧭 Vision: To become the stablecoin value foundation for global on-chain payments BenFen is dedicated to building a next-generation high-performance stablecoin blockchain, with stablecoins as the core on-chain asset. Through native mechanisms, it connects cross-chain assets, stablecoin systems, and on-chain protocols to serve real-world financial interaction scenarios, creating a sustainable and high-frequency accessible stablecoin economic system. Learn more: #BenFen #RWA #Web3Payments #Stablecoin #MoveVM #zkLogin #CryptoInfra #Layer1 #PayFi #CrossChain #BUSD #DeFi #BenPay #OnChainSettlement #Web3Infrastructure
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🌐 BenFen | Next-Gen Multi-Currency Stablecoin Blockchain BenFen is a Layer1 blockchain purpose-built for stablecoin issuance, adoption, and payments, providing trusted and accessible on-chain payment infrastructure for global users and developers. 🟥 Technical Architecture：Built on the Move language, ensuring security, high performance, and accessibility. 🔹 Modular contract design ensures asset security and tamper-proof rules for reliable system operation. 🔹 Sub-second transaction confirmation with stable 10,000+ TPS, optimized for payment and interaction scenarios. 🔹 Supports zkLogin, enabling one-click wallet creation with Google/Apple ID. 🟥 BUSD Stablecoin Mechanism ：Pegged to USDT/USDC, the core on-chain asset 🔹 Cross-chain 1:1 pegged minting with USDT/USDC, wit h native support for stablecoin GAS payments. 🔹 Supports mainstream G20 fiat-backed stablecoin conversions (eg, BUSD/BJPY, BUSD/BEUR). 🔹 Covers key scenarios like asset trading, RWA mapping, on-chain payroll, and daily consumption. 🟥 Native Features: Full-stack capabilities centered around stablecoins 🔹 Supports one-click issuance of stablecoins/RWAs, lowering development barriers. 🔹 Any issued stablecoin can be registered as a Gas token, with sponsored transactions available for Gas subsidies. 🔹 Zero-cost transfers for specific scenarios, enabling real "zero-fee payments". 🔹 Privacy accounts and payments: Supports hidden addresses and balances for privacy-focused use cases. 🔹 Multi-chain asset payments + G20 fiat settlement: Real-time settlement of USDT, SOL, ETH, and other major assets into BJPY, BEUR, BAUD, and other G20 stablecoins. 🟥 Native Cross-Chain Bridge 🔹 Proprietary native cross-chain protocol. 🔹 Supports BTC, ETH, BSC, Polygon, Optimism, Solana, TRON, Base, Avalanche, and more. 🔹 No third-party bridge is needed; assets can be cross-chain with just one click, offering fast, secure, on-chain verification and second-level fund arrival. 📱 BenFen Ecosystem 🔹 BenPay: An open, secure, and efficient comprehensive payment ecosystem, offering users a convenient and secure cryptocurrency payment channel. 🔹 BenPay Card: On-chain self-custodial payment card, with keys in hand, enabling global spending (Supports Apple Pay, Alipay, Amazon, Netflix, X, ChatGPT, etc.). 🔹 BenPay C2C: secure peer-to-peer decentralized trading marketplace. 🔹 BenPay DeFi Earn:A cross-chain yield farming protocol that allows stablecoins from major blockchains to be seamlessly transferred and deposited into high-APY farming pools. 🔹 BenPay DEX: One-click swaps and aggregated matching for stablecoins/crypto assets. 🔹 BenPay Lending: Decentralized finance protocol supporting BTC collateral and USDT lending. 🔹 BenPay Stake: Stake BFC to gain governance rights, ecosystem rewards, and airdrops. 🟥 BenFen DAO 🔹 Utilizes formal verification for security, supporting low-cost proposals and voting to promote community autonomous governance and rights protection. 🟥 Developer-Friendly Platform：Building a low-barrier development ecosystem 🔹 Provides standard SDKs/APIs/contract templates. 🔹 Supports full-cycle development scenarios like stablecoin issuance, RWA issuance, wallet integration, and DeFi application building. 🔹 Lowers development barriers to accelerate innovation. 🧭 Vision: To become the stablecoin value foundation for global on-chain payments BenFen is dedicated to building a next-generation high-performance stablecoin blockchain, with stablecoins as the core on-chain asset. Through native mechanisms, it connects cross-chain assets, stablecoin systems, and on-chain protocols to serve real-world financial interaction scenarios, creating a sustainable and high-frequency accessible stablecoin economic system. Learn more: #BenFen #RWA #Web3Payments #Stablecoin #MoveVM #zkLogin #CryptoInfra #Layer1 #PayFi #CrossChain #BUSD #DeFi #BenPay #OnChainSettlement #Web3Infrastructure

BenFen

37,518 views • 11 months ago

TOPIC #107: PI NETWORK IS A STABLE COIN? -WHO DECIDES PI FULLY OM FIXED VALUE? Dear GCV army, I hope you are all doing great! First of all, I would like to express my sincere gratitude for all your hard work. Many of you have achieved significant milestones, and it’s evident that you are making a great difference. Our influence has grown significantly, with an increasing number of social media posts and YouTubers publicly supporting us. I can see that more and more people are beginning to understand why we advocate for GCV. Today's meeting aims to alleviate any doubts you may have, allowing you to relax and feel confident as we embark on our historic journey together. I will answer the questions I’ve received and address some important issues we need to focus on to maintain our community's efficiency, particularly regarding our Generals, which will be the topic next weekend. I put the questions I received here. "A question addressed to Ms. Doris Yin in the emergency meeting 1– In light of the rapidly changing global circumstances and the increasing discussion about stablecoins backed by U.S. Treasury bonds, how do you see the future role of the Pi Network in this context? And what practical steps should the GCV army take now to accelerate this path? 2_ There are those who promote the idea that the price of Pi is what appears in the market (currently around $0.49) and compare it to the price of GCV within the ecosystem (314,159 Pi = 1 good or service). They say if Pi’s price rises to $2, it means that the value within The ecosystem is approximately 2 million dollars. With sincere appreciation and discipline." This is from the Arab head of GCV Ambassador Mr. Mohammed. Another question: "Hello, my Global Ambassador, I am Ateba Joseph, Ecological Ambassador in Cameroon And a member of the GCV army, I am delighted to exchange with you. Regarding the meeting with the GCV army on Sunday, July 27, 2025.. Here is my concern: A few days ago, a correspondence indicated that Pi is not or is not yet a stable coin. Upon reading this information, we have provided many explanations to help the pioneers understand this. I hope you will focus more on this statement to further strengthen our understanding of the subject. Thank you for taking my concerns into consideration" Thank you for the above questions; my answers are below. The first question concerns stablecoins. Many pioneers are hoping that Pi can be recognized by the U.S. government as a stablecoin. I wrote an article on this in May. On July 18, 2025, President Trump signed the Guiding and Establishing National Innovation for US Stablecoins Act (the GENIUS Act) into law. This legislation establishes a regulatory framework for payment stablecoins and marks the first federal legislation on digital assets enacted since President Trump issued an executive order aimed at making the U.S. the “crypto capital of the world.” U.S.-issued stablecoins are expected to become the primary means of dollar transactions globally, especially in emerging markets with unstable local currencies. The sponsors of the GENIUS Act estimate that by 2030, stablecoin issuers may collectively become the largest holders of U.S. Treasuries, surpassing foreign central banks. From this, we can see that U.S. stablecoins must maintain reserves backing outstanding payment stablecoins on a one-to-one basis, consisting only of specified assets, including U.S. dollars and short-term Treasury securities. It is clear that the Pi Network will not take this path, as it is not part of our plan. A stablecoin is essentially a digital representation of the U.S. dollar. All stablecoin issuers do not create a new currency; rather, it’s akin to purchasing chips at a casino – you must use U.S. dollars to buy those chips. However, Pi is a completely new currency. It does not need to be backed up by U.S. dollars or U.S. Treasuries to be used. If that were the case, we wouldn’t need to establish an ecosystem or have a three-year enclosed mainnet. I previously mentioned the possibility of Pi being an algorithmic stablecoin since only algorithmic stablecoins do not need to be backed by U.S. dollars. However, algorithmic stablecoins have faced significant failures in the past. The collapse of the Terra (LUNA) cryptocurrency resulted in a loss of at least $40 billion in market capitalization, with estimates reaching as high as $60 billion. TerraUSD (UST), an algorithmic stablecoin, lost its peg to the U.S. dollar, contributing to its overall collapse. The new stablecoin legislation recently passed through the Senate effectively ties the U.S. Treasury to crypto, as it essentially bets the government’s cash flow on digital tokens and market speculation. This legislation requires stablecoins to be backed by short-term Treasury bills, generating an estimated $2–$3 trillion in new demand for government debt, which is nearly half the current size of the T-bill market. On paper, this looks beneficial, but in reality, it creates a circular feedback loop: crypto demand fuels stablecoins, stablecoins buy T-bills, and T-bills fund government deficits. The government becomes reliant on speculative capital flows. Thus, we should understand why the U.S. government will not support the Pi Network as a stablecoin, as they require stablecoin issuers to buy T-bills and can no longer trust algorithmic stablecoins. So, what is the future of the Pi Network as a currency? From my perspective, Pi is already listed on exchange markets. It cannot be classified as a security because it is mined freely and is not an ICO. Instead, it should be categorized as a commodity, similar to Bitcoin and ETH. When a currency is listed for trading on an exchange, its price is determined by the balance of supply and demand. However, Pi is a currency in its own right; it has inherent value from Pi holders -Pioneers. Historically, currency has served as a medium of exchange. A medium of exchange is a widely accepted item for buying goods and services in an economy. It facilitates transactions by eliminating the need for a barter system, where goods are directly exchanged for other goods. In modern economies, money (such as currency) serves as the primary medium of exchange. **Functions of Money:** One of the core functions of money is to serve as a medium of exchange, enabling the smooth transfer of value between buyers and sellers, thereby simplifying trade and economic activity. **Examples:** In modern economies, this typically includes currency (paper money, coins) or digital money. In specific historical contexts, other items, such as cigarettes in prisoner-of-war camps, have also served as mediums of exchange. **Importance of Acceptance:** For a medium of exchange to function effectively, it must be widely accepted and trusted within the relevant community. **Not the Same as a Payment Method:** While credit cards and checks are used for payments, they do not serve as mediums of exchange themselves. Therefore, stablecoin is not a new currency. It is more likely to have a credit card or check character. It is a USD digital status. From the analysis presented, we can draw the following conclusions: The current price of Pi on the exchange market primarily serves as a temporary measure to facilitate broad expansion. While this is not our primary objective, it constitutes a strategic approach towards achieving our mission. To gain a clearer perspective, we must adopt a higher-level view of the overall vision for the Pi Network. The mission and vision of Pi Network clearly articulate that it is not intended to function as a commodity for sale, nor is it meant to be an investment vehicle or a speculative security. Instead, it is crucial to recognize that Pi is designed to be a medium of exchange—a new form of currency. As pioneers in this venture, we have the unique opportunity to acquire Pi through free mining. However, it is important to note that the current mining rate is relatively slow. To overcome this limitation and to further our goal of mass adoption, it is essential for more individuals to join the Pi Network and participate in holding Pi. One efficient way to accelerate this process is by allowing Pi to be traded on the exchange market, which can result in rapid and widespread adoption. Since Pi can be mined for free, a lower price could make it more accessible to a larger number of people. It's important to focus on our primary goal during this pre-full Open Mainnet (OM) phase: mass adoption, rather than aiming for high prices, which many pioneers expected. Some pioneers want to sell when the price increases, but if too many sell, it could undermine our goal of achieving mass adoption. This scenario is reminiscent of historical instances when shells served as currency—readily accessible from the sea or buy from the village market. For shells to function effectively as currency, a collective effort was needed to hold and circulate them within the village. If only a select few individuals possess the shells, the currency lacks the necessary circulation to sustain an economy. Hence, our goal should not be centered on achieving a high price; instead, we should strive to make Pi more affordable so that a greater number of individuals can acquire and hold it, thereby fostering a thriving economic ecosystem. Of course, the rising price will build up merchants' confidence to accept it as payment. This is why we refer to it as a buyback campaign, which aims to achieve mass adoption and foster ecosystem confidence. As Pi evolves into a currency, the question of its value becomes pertinent. Given that it is a new currency, its value is not immediately clear. This presents an opportunity for us, the pioneers, to play a crucial role in defining it. The determination of Pi's value is not the responsibility of a central authority such as CT, the government, or the exchange. Instead, it will emerge from a decentralized consensus within the community, which collectively owns Pi. This concept is akin to ancient times when the value of shells was not determined by the sellers. Rather, the value was derived from the collective agreement of the village that utilized them as currency. I hope this elaboration clarifies the distinction between value and price, enabling a deeper understanding of the foundational principles that drive our mission with Pi Network. Pi represents a groundbreaking innovation—a revolution that is poised for long-term economic development on a global scale, rather than perpetuating cycles of plunder and exploitation. By harnessing the power of blockchain technology, Pi empowers ordinary individuals, which creates an inherent conflict of interest with the U.S. government in the short term. Should the U.S. government endorse the Pi Network, it raises questions about the viability of U.S. treasuries and who would ultimately purchase them. Consequently, the government may prioritize support for stablecoins backed by the U.S. dollar and U.S. Treasury securities, as this can help alleviate the U.S. government's issues with limited demand. However, I previously mentioned the potential for Pi to emerge as an algorithmic stablecoin. At that time, the Genius Bill had not yet been enacted. If the Pi Network gains acceptance from the U.S. government, its growth could become rapid and expansive, leading to widespread adoption in other nations. This path would position Pi as a legitimate currency in nearly every country, contingent upon certain conditions. For instance, if the price of Pi in the exchange market can align with the GCV, this could be achieved through a buyback mechanism involving 10 million pioneers. Such a scenario would indicate that Pi differs significantly from past algorithmic stablecoin failures, presenting a compelling case for the U.S. government to view Pi as a low-risk asset. However, it presents a significant challenge to be collectively reached by pioneers, and there are other conditions that we cannot achieve in a short time. While it might appear that Pi Network conflicts with the U.S. dollar or stablecoins in the short term, it has the potential to address the broader issue of overprinting currency, which has plagued the U.S. and many other nations. This would benefit international trade by alleviating concerns about currency appreciation or depreciation in international transactions. The global economy indeed requires a super sovereign currency—one that ensures stability for future generations and fosters lasting peace and prosperity. To comprehend Pi as a currency, it is crucial to recognize that we must cultivate long-term value by generating GCV data. In the short term, our focus needs to be on establishing a robust exchange market and decentralized applications (DApps) to drive mass adoption. If this is understood, there should be no need to feel discouraged by the current low price of Pi. The true value of Pi as a currency derives not from the exchange market, trading platforms, or governmental endorsement, but rather from our community's collective efforts and engagement. You might wonder how a government could adopt Pi, given that it does not take the form of a stablecoin. I would counter with the example of Bitcoin, which has thrived even in environments where many countries have imposed bans. Currently, Pi is transitioning from its traditional commodity status to being recognized as a currency, meaning governmental awareness of Pi Network is still in development. As such, existing regulations generally pertain to older forms of cryptocurrency rather than our innovative approach. Our branding as a digital currency, rather than a cryptocurrency, is intentional. Dr. Nicolas has expressed concerns that many aspects of conventional cryptocurrencies pose challenges to government frameworks and public trust, often leading to economic harm rather than benefit. Our commitment to Know Your Customer (KYC) and Know Your Business (KYB) protocols distinguishes us by mitigating money laundering risks and protecting Pi holders from speculative practices. Many businesses face bankruptcy or closure because consumers lack the disposable income to engage in spending. Imagine how Pi could enable those businesses to survive and thrive—people could utilize Pi to make purchases and easily convert it into fiat currency to sustain operations, thereby preserving many jobs. The function in our wallet that allows users to "buy" Pi is not merely a feature; it represents a vision for the future where conversion to fiat currency can happen immediately, without dependency on third-party exchanges. Moving forward, we can establish a fixed rate (the GCV) for conversions. Once larger institutions and prominent companies recognize the low-risk profile of joining Pi Network due to its GCV stability, we can expect a considerable influx of participants seeking to gain a competitive advantage. You may ask how companies would finance the purchase of Pi at GCV rates. This is an insightful question. My perspective is that the demand for Pi’s stable value will inherently incentivize investments. Much like why individuals purchase stablecoins for their convenience in facilitating cross-border transactions, Pi will appeal to consumers and businesses alike, particularly because we are leveraging Web 3.0 blockchain technology, AI-driven platforms, and a rich ecosystem of decentralized applications (DApps). We are cultivating a loyal customer base that recognizes the value of this innovation. We understand that high-net-worth individuals seek safe investment opportunities. While U.S. treasury bonds currently represent a secure asset class, they are not without risk. Therefore, if Pi Network can maintain a limited supply coupled with blockchain technology and a consistent GCV, it is plausible that affluent investors would allocate a portion of their capital to acquire Pi. This would lead to fiat inflows whenever there is increased demand for Pi, establishing an equilibrium between Pi and fiat currencies. This interplay is why I believe DApps are critically significant. We need broader usage of Pi in real-world applications. I hope my analysis has helped clarify why the price of Pi should not overly concern us. Buying Pi to hold onto it allows pioneers to accumulate more, while building merchant confidence is essential to kickstart the ecosystem. Merchants will be motivated to see Pi’s price appreciation since this removes the risks for DApps and service providers who depend on exchange market prices. A rise in demand for Pi will subsequently reduce its supply, which is beneficial for price increases. I look forward to discussing Pi GCV army management in another session. Thank you for your time. Let’s continue striving for greatness together. Doris Yin 🪷🪷🪷 Founder, Global GCV Movement Disclaimer: This speech is intended solely for educational purposes within the GCV community. The views and content shared here represent my personal perspective and are part of the GCV movement, but do not reflect the official position of the Pi Core Team (PCT). Pi Network represents a new revolution, meaning there is no existing example for us to follow and no guiding manual. As Dr. Fan mentioned, we cannot predict what will happen around the next corner. Therefore, we must practice and forge our own path. As more people traverse this journey, the road will become clearer.
0:55

TOPIC #107: PI NETWORK IS A STABLE COIN? -WHO DECIDES PI FULLY OM FIXED VALUE? Dear GCV army, I hope you are all doing great! First of all, I would like to express my sincere gratitude for all your hard work. Many of you have achieved significant milestones, and it’s evident that you are making a great difference. Our influence has grown significantly, with an increasing number of social media posts and YouTubers publicly supporting us. I can see that more and more people are beginning to understand why we advocate for GCV. Today's meeting aims to alleviate any doubts you may have, allowing you to relax and feel confident as we embark on our historic journey together. I will answer the questions I’ve received and address some important issues we need to focus on to maintain our community's efficiency, particularly regarding our Generals, which will be the topic next weekend. I put the questions I received here. "A question addressed to Ms. Doris Yin in the emergency meeting 1– In light of the rapidly changing global circumstances and the increasing discussion about stablecoins backed by U.S. Treasury bonds, how do you see the future role of the Pi Network in this context? And what practical steps should the GCV army take now to accelerate this path? 2_ There are those who promote the idea that the price of Pi is what appears in the market (currently around $0.49) and compare it to the price of GCV within the ecosystem (314,159 Pi = 1 good or service). They say if Pi’s price rises to $2, it means that the value within The ecosystem is approximately 2 million dollars. With sincere appreciation and discipline." This is from the Arab head of GCV Ambassador Mr. Mohammed. Another question: "Hello, my Global Ambassador, I am Ateba Joseph, Ecological Ambassador in Cameroon And a member of the GCV army, I am delighted to exchange with you. Regarding the meeting with the GCV army on Sunday, July 27, 2025.. Here is my concern: A few days ago, a correspondence indicated that Pi is not or is not yet a stable coin. Upon reading this information, we have provided many explanations to help the pioneers understand this. I hope you will focus more on this statement to further strengthen our understanding of the subject. Thank you for taking my concerns into consideration" Thank you for the above questions; my answers are below. The first question concerns stablecoins. Many pioneers are hoping that Pi can be recognized by the U.S. government as a stablecoin. I wrote an article on this in May. On July 18, 2025, President Trump signed the Guiding and Establishing National Innovation for US Stablecoins Act (the GENIUS Act) into law. This legislation establishes a regulatory framework for payment stablecoins and marks the first federal legislation on digital assets enacted since President Trump issued an executive order aimed at making the U.S. the “crypto capital of the world.” U.S.-issued stablecoins are expected to become the primary means of dollar transactions globally, especially in emerging markets with unstable local currencies. The sponsors of the GENIUS Act estimate that by 2030, stablecoin issuers may collectively become the largest holders of U.S. Treasuries, surpassing foreign central banks. From this, we can see that U.S. stablecoins must maintain reserves backing outstanding payment stablecoins on a one-to-one basis, consisting only of specified assets, including U.S. dollars and short-term Treasury securities. It is clear that the Pi Network will not take this path, as it is not part of our plan. A stablecoin is essentially a digital representation of the U.S. dollar. All stablecoin issuers do not create a new currency; rather, it’s akin to purchasing chips at a casino – you must use U.S. dollars to buy those chips. However, Pi is a completely new currency. It does not need to be backed up by U.S. dollars or U.S. Treasuries to be used. If that were the case, we wouldn’t need to establish an ecosystem or have a three-year enclosed mainnet. I previously mentioned the possibility of Pi being an algorithmic stablecoin since only algorithmic stablecoins do not need to be backed by U.S. dollars. However, algorithmic stablecoins have faced significant failures in the past. The collapse of the Terra (LUNA) cryptocurrency resulted in a loss of at least $40 billion in market capitalization, with estimates reaching as high as $60 billion. TerraUSD (UST), an algorithmic stablecoin, lost its peg to the U.S. dollar, contributing to its overall collapse. The new stablecoin legislation recently passed through the Senate effectively ties the U.S. Treasury to crypto, as it essentially bets the government’s cash flow on digital tokens and market speculation. This legislation requires stablecoins to be backed by short-term Treasury bills, generating an estimated $2–$3 trillion in new demand for government debt, which is nearly half the current size of the T-bill market. On paper, this looks beneficial, but in reality, it creates a circular feedback loop: crypto demand fuels stablecoins, stablecoins buy T-bills, and T-bills fund government deficits. The government becomes reliant on speculative capital flows. Thus, we should understand why the U.S. government will not support the Pi Network as a stablecoin, as they require stablecoin issuers to buy T-bills and can no longer trust algorithmic stablecoins. So, what is the future of the Pi Network as a currency? From my perspective, Pi is already listed on exchange markets. It cannot be classified as a security because it is mined freely and is not an ICO. Instead, it should be categorized as a commodity, similar to Bitcoin and ETH. When a currency is listed for trading on an exchange, its price is determined by the balance of supply and demand. However, Pi is a currency in its own right; it has inherent value from Pi holders -Pioneers. Historically, currency has served as a medium of exchange. A medium of exchange is a widely accepted item for buying goods and services in an economy. It facilitates transactions by eliminating the need for a barter system, where goods are directly exchanged for other goods. In modern economies, money (such as currency) serves as the primary medium of exchange. **Functions of Money:** One of the core functions of money is to serve as a medium of exchange, enabling the smooth transfer of value between buyers and sellers, thereby simplifying trade and economic activity. **Examples:** In modern economies, this typically includes currency (paper money, coins) or digital money. In specific historical contexts, other items, such as cigarettes in prisoner-of-war camps, have also served as mediums of exchange. **Importance of Acceptance:** For a medium of exchange to function effectively, it must be widely accepted and trusted within the relevant community. **Not the Same as a Payment Method:** While credit cards and checks are used for payments, they do not serve as mediums of exchange themselves. Therefore, stablecoin is not a new currency. It is more likely to have a credit card or check character. It is a USD digital status. From the analysis presented, we can draw the following conclusions: The current price of Pi on the exchange market primarily serves as a temporary measure to facilitate broad expansion. While this is not our primary objective, it constitutes a strategic approach towards achieving our mission. To gain a clearer perspective, we must adopt a higher-level view of the overall vision for the Pi Network. The mission and vision of Pi Network clearly articulate that it is not intended to function as a commodity for sale, nor is it meant to be an investment vehicle or a speculative security. Instead, it is crucial to recognize that Pi is designed to be a medium of exchange—a new form of currency. As pioneers in this venture, we have the unique opportunity to acquire Pi through free mining. However, it is important to note that the current mining rate is relatively slow. To overcome this limitation and to further our goal of mass adoption, it is essential for more individuals to join the Pi Network and participate in holding Pi. One efficient way to accelerate this process is by allowing Pi to be traded on the exchange market, which can result in rapid and widespread adoption. Since Pi can be mined for free, a lower price could make it more accessible to a larger number of people. It's important to focus on our primary goal during this pre-full Open Mainnet (OM) phase: mass adoption, rather than aiming for high prices, which many pioneers expected. Some pioneers want to sell when the price increases, but if too many sell, it could undermine our goal of achieving mass adoption. This scenario is reminiscent of historical instances when shells served as currency—readily accessible from the sea or buy from the village market. For shells to function effectively as currency, a collective effort was needed to hold and circulate them within the village. If only a select few individuals possess the shells, the currency lacks the necessary circulation to sustain an economy. Hence, our goal should not be centered on achieving a high price; instead, we should strive to make Pi more affordable so that a greater number of individuals can acquire and hold it, thereby fostering a thriving economic ecosystem. Of course, the rising price will build up merchants' confidence to accept it as payment. This is why we refer to it as a buyback campaign, which aims to achieve mass adoption and foster ecosystem confidence. As Pi evolves into a currency, the question of its value becomes pertinent. Given that it is a new currency, its value is not immediately clear. This presents an opportunity for us, the pioneers, to play a crucial role in defining it. The determination of Pi's value is not the responsibility of a central authority such as CT, the government, or the exchange. Instead, it will emerge from a decentralized consensus within the community, which collectively owns Pi. This concept is akin to ancient times when the value of shells was not determined by the sellers. Rather, the value was derived from the collective agreement of the village that utilized them as currency. I hope this elaboration clarifies the distinction between value and price, enabling a deeper understanding of the foundational principles that drive our mission with Pi Network. Pi represents a groundbreaking innovation—a revolution that is poised for long-term economic development on a global scale, rather than perpetuating cycles of plunder and exploitation. By harnessing the power of blockchain technology, Pi empowers ordinary individuals, which creates an inherent conflict of interest with the U.S. government in the short term. Should the U.S. government endorse the Pi Network, it raises questions about the viability of U.S. treasuries and who would ultimately purchase them. Consequently, the government may prioritize support for stablecoins backed by the U.S. dollar and U.S. Treasury securities, as this can help alleviate the U.S. government's issues with limited demand. However, I previously mentioned the potential for Pi to emerge as an algorithmic stablecoin. At that time, the Genius Bill had not yet been enacted. If the Pi Network gains acceptance from the U.S. government, its growth could become rapid and expansive, leading to widespread adoption in other nations. This path would position Pi as a legitimate currency in nearly every country, contingent upon certain conditions. For instance, if the price of Pi in the exchange market can align with the GCV, this could be achieved through a buyback mechanism involving 10 million pioneers. Such a scenario would indicate that Pi differs significantly from past algorithmic stablecoin failures, presenting a compelling case for the U.S. government to view Pi as a low-risk asset. However, it presents a significant challenge to be collectively reached by pioneers, and there are other conditions that we cannot achieve in a short time. While it might appear that Pi Network conflicts with the U.S. dollar or stablecoins in the short term, it has the potential to address the broader issue of overprinting currency, which has plagued the U.S. and many other nations. This would benefit international trade by alleviating concerns about currency appreciation or depreciation in international transactions. The global economy indeed requires a super sovereign currency—one that ensures stability for future generations and fosters lasting peace and prosperity. To comprehend Pi as a currency, it is crucial to recognize that we must cultivate long-term value by generating GCV data. In the short term, our focus needs to be on establishing a robust exchange market and decentralized applications (DApps) to drive mass adoption. If this is understood, there should be no need to feel discouraged by the current low price of Pi. The true value of Pi as a currency derives not from the exchange market, trading platforms, or governmental endorsement, but rather from our community's collective efforts and engagement. You might wonder how a government could adopt Pi, given that it does not take the form of a stablecoin. I would counter with the example of Bitcoin, which has thrived even in environments where many countries have imposed bans. Currently, Pi is transitioning from its traditional commodity status to being recognized as a currency, meaning governmental awareness of Pi Network is still in development. As such, existing regulations generally pertain to older forms of cryptocurrency rather than our innovative approach. Our branding as a digital currency, rather than a cryptocurrency, is intentional. Dr. Nicolas has expressed concerns that many aspects of conventional cryptocurrencies pose challenges to government frameworks and public trust, often leading to economic harm rather than benefit. Our commitment to Know Your Customer (KYC) and Know Your Business (KYB) protocols distinguishes us by mitigating money laundering risks and protecting Pi holders from speculative practices. Many businesses face bankruptcy or closure because consumers lack the disposable income to engage in spending. Imagine how Pi could enable those businesses to survive and thrive—people could utilize Pi to make purchases and easily convert it into fiat currency to sustain operations, thereby preserving many jobs. The function in our wallet that allows users to "buy" Pi is not merely a feature; it represents a vision for the future where conversion to fiat currency can happen immediately, without dependency on third-party exchanges. Moving forward, we can establish a fixed rate (the GCV) for conversions. Once larger institutions and prominent companies recognize the low-risk profile of joining Pi Network due to its GCV stability, we can expect a considerable influx of participants seeking to gain a competitive advantage. You may ask how companies would finance the purchase of Pi at GCV rates. This is an insightful question. My perspective is that the demand for Pi’s stable value will inherently incentivize investments. Much like why individuals purchase stablecoins for their convenience in facilitating cross-border transactions, Pi will appeal to consumers and businesses alike, particularly because we are leveraging Web 3.0 blockchain technology, AI-driven platforms, and a rich ecosystem of decentralized applications (DApps). We are cultivating a loyal customer base that recognizes the value of this innovation. We understand that high-net-worth individuals seek safe investment opportunities. While U.S. treasury bonds currently represent a secure asset class, they are not without risk. Therefore, if Pi Network can maintain a limited supply coupled with blockchain technology and a consistent GCV, it is plausible that affluent investors would allocate a portion of their capital to acquire Pi. This would lead to fiat inflows whenever there is increased demand for Pi, establishing an equilibrium between Pi and fiat currencies. This interplay is why I believe DApps are critically significant. We need broader usage of Pi in real-world applications. I hope my analysis has helped clarify why the price of Pi should not overly concern us. Buying Pi to hold onto it allows pioneers to accumulate more, while building merchant confidence is essential to kickstart the ecosystem. Merchants will be motivated to see Pi’s price appreciation since this removes the risks for DApps and service providers who depend on exchange market prices. A rise in demand for Pi will subsequently reduce its supply, which is beneficial for price increases. I look forward to discussing Pi GCV army management in another session. Thank you for your time. Let’s continue striving for greatness together. Doris Yin 🪷🪷🪷 Founder, Global GCV Movement Disclaimer: This speech is intended solely for educational purposes within the GCV community. The views and content shared here represent my personal perspective and are part of the GCV movement, but do not reflect the official position of the Pi Core Team (PCT). Pi Network represents a new revolution, meaning there is no existing example for us to follow and no guiding manual. As Dr. Fan mentioned, we cannot predict what will happen around the next corner. Therefore, we must practice and forge our own path. As more people traverse this journey, the road will become clearer.

Doris Yin 东方紫莲🪷

17,742 views • 1 year ago

77 Reasons Why I’ve Invested Over $8,000,000+ in MultiversX (EGLD) and Why EGLD Will Crush It in 2025 (My Investment Thesis). I publicly shared my portfolio on X. EGLD is A) Better than BTC B) Everything that ETH wants to be C) The GameStop of Crypto 1. EGLD is verifiably the most scalable (theoretically unlimited) L1 chain in the world, theoretically capable of over 10 million TPS (thanks to adaptive state sharding). 2. e-Gold is digital gold. It has the best tokenomics among all L1s, similarly scarce to BTC, with a maximum supply of 31.4 million coins. Currently, 27.68 million coins are in circulation. 3. EGLD will be the most decentralized cryptocurrency in the world thanks to sharding and minimal hardware requirements for running nodes. It’s already second only to Ethereum with 3,618 validator nodes. 4. EGLD has extremely low fees, around ~$0.002 per transaction. 5. EGLD is extremely secure. No wallet drains like on ETH/SOL; assets are owned natively (not via a smart contract). There is no MEV risk (front-running bots). 6. EGLD is the only chain in the world with an on-chain Guardian (two-phase verification), making it impossible for a hacker to steal your funds—even if they have your private keys (seed phrase). 7. EGLD is carbon-neutral and eco-friendly, not wasting energy like BTC and other PoW chains. It’s exceptionally efficient, scalable, global, and sustainable. 8. EGLD has the best UX in crypto. Download the xPortal wallet—it’s like discovering Apple in Web3. The interface is simple, flawless, and you barely realize you’re using crypto. Instead of addresses, you use HeroTags. The app features all dApps, everything runs smoothly, and the visuals are beautifully designed. The explorer, web wallet, etc. follow the same high-quality user experience. 9. EGLD supports native assets, unlike Ethereum, for example. 10. EGLD is the first chain to fully implement horizontal (theoretically unlimited) sharding without compromising on decentralization—unlike Solana and others that attempt vertical scaling, leading to multiple network downtimes (11+ times) and huge hardware demands for validators, ultimately harming decentralization. 11. EGLD makes setting up a validator agency extremely easy. Even complete IT beginners can do it. The UX and documentation are superb. I personally set up the “EGLDSqueeze” agency in about 30 minutes. Managing it is straightforward via the web wallet, which feels like managing a Facebook page. This simplifies decentralization enormously. 12. EGLD allows literally anyone (even your grandma) to participate in decentralization, since nodes can run on a Raspberry Pi or a relatively affordable phone. Imagine millions of people worldwide securing the network, validating transactions without even knowing it. This can’t be done with BTC, where setting up profitable mining operations is prohibitively expensive. 13. WASM-Based Virtual Machine: You can write smart contracts in your favorite language, compile them, and run them via the fastest VM in the world. 14. EGLD has been tested at an incredible 263,000 TPS using its sharding mechanism and low hardware requirements. Allegedly, by mid-next year (April), they’ll demonstrate 1,000,000 TPS. (For context: Mastercard handles around 5,000 TPS; BTC handles 5–7 TPS.) 15. EGLD is currently the most advanced L1 in terms of scalability, security, decentralization, UX, eco-friendliness, and tokenomics. It’s the only chain that has genuinely solved the Blockchain Trilemma and is ready to onboard 1 billion people into crypto—users who won’t even realize they’re interacting with crypto. 16. EGLD is perfectly positioned for AI projects—AI agents, AI tools, or a so-called “Truth Machine” that monitors other AIs on-chain, documenting what’s true and comparing different AI outputs (some of which may be censored or biased), ensuring people don’t get confused or scammed in an AI-driven world. 17. The EGLD team is the hardest-working team I’ve ever encountered. I had the honor of meeting many of them personally, and can attest that their pace—even during a bear market—is extraordinary. 18. EGLD’s development team is exceptionally active on GitHub, continually improving their network and actively committing code. 19. EGLD plans to introduce an update reducing block time to 600ms (down from ~6 seconds), which would make the chain essentially unrivaled. 20. EGLD is effectively the only usable L1 in Europe, and the team has direct connections within the EU government—extremely bullish for the project. 21. EGLD provides top-tier on-chain governance not only for the MultiversX (EGLD) protocol but also for DeFi projects (e.g., xExchange, MEX). 22. EGLD plans to expand to the US, likely opening offices in Austin, Texas. This could put them in direct contact with Elon Musk (if it hasn’t happened already), as he’s involved with If he’s done his research, he’d discover there’s simply no better L1 worldwide. 23. EGLD solved fully implemented sharding, perfect tokenomics, and top-tier architecture with just $5M, whereas other chains failed to do so even with $100M+. The second-best sharding network, NEAR, needed $100M, has worse tokenomics, and its sharding isn’t fully implemented yet. Its UX also doesn’t compare. Owning NEAR was like comparing a VW Golf R to a Porsche GT3—EGLD is the Porsche GT3. 24. According to Similarweb, EGLD has significantly high traffic relative to other chains with market caps 100x larger. The market cap vs. web traffic discrepancy is huge, which is a strong indicator of EGLD’s potential. 25. EGLD has the most active and dedicated community relative to its user base, with users who believe in the technology, have full faith in the team, and remain loyal despite price volatility—because they use the chain and know there’s nothing better. 26. Check other chains’ active user counts on X (Twitter) and compare it with the followers of EGLD’s founders and main network accounts, versus those with 30x, 50x, or 100x larger market caps. 27. Visit the MultiversX website to observe the futuristic design and presentation, then compare it to other chains that appear nearly a decade behind in design and branding. 28. EGLD hosts the xDay Global event, showcasing updates, new builders, projects in the ecosystem, and major announcements—similar to Apple’s Keynotes—delivered in a highly professional, goosebump-inducing atmosphere. The next event is in Korea, the second-biggest crypto market after the US. Check out their previous xDay after-movie to see why this is extremely bullish. 29. EGLD is moving forward with plans for the first regulated, audited EU stablecoin under MiCa regulation, made possible by acquiring xMoney, which I view as a “Stripe” for crypto/fiat, offering everything from user solutions to merchant services—potentially the future of payments. 30. Greg Siourouni recently joined EGLD, having been an executive director at SUI Foundation. He’s now co-founder of xMoney Global. xMoney (formerly UTrust, with token UTK) is owned and founded by the MultiversX Labs team. A stablecoin might be introduced soon, which would be massively bullish given xMoney’s roadmap. They recently announced integrations with Binance Pay—both ways. 31. EGLD prioritizes user safety, believing it’s the only feasible approach once the network scales to serve a billion people—many of whom are retail users with little to no security awareness. 32. EGLD offers “Sovereign Chains,” letting you effectively clone their chain without heavy development, set up your own validators, and leverage their unlimited scalability. Any blockchain (ETH, BTC, SOL) struggling with scalability, decentralization, or security could run an ultra-fast, scalable, and secure L2 on EGLD’s Sovereign Chain, meeting top enterprise requirements. No one else has really done this. The Sovereign Chain demo achieved astonishing TPS and has an SDK. 33. No downtime since inception. 34. No shard takeover attacks have occurred. 35. Extremely fast—soon 600ms block time will be in place. 36. ESDTs – The best token standard available: fungible, non-fungible, semi-fungible, DeFi assets—everything is native and highly customizable. 37. Top-tier composability of assets and smart contracts. 38. Integrated DNS at protocol level with HeroTags (nicknames) instead of long addresses. 39. Asynchronous calls are supported. 40. Cross-shard transfers, execution, reverts, and calls are seamlessly integrated. 41. The best staking system in the space. Secure Proof of Stake (SPoS) is far more efficient than Proof of Work (PoW). 42. Built-in Delegation and Staking Provider system, with over 125K delegators. 43. Complete support for liquid staked assets, fostering decentralization rather than centralization. 44. TransferRoles for ESDT and other advanced operations. 45. Composable tasks on-chain for more sophisticated DeFi workflows. 46. MultiTransfer and asset execution within one transaction. 47. Re-entrancy protection is built-in by design. 48. Storage for ESDT assets goes beyond a linear approach, optimizing performance. 49. No integer overflows thanks to integrated safeMath operations. 50. Integrated crypto opcodes in the VM, enhancing security and performance. 51. Support for BigFloats, BigInts, and BigDecimals, enabling advanced financial calculations on-chain. 52. No sandwich attacks, plus front-running and MEV protection. 53. Relayed Transactions, simplifying user interactions and fees. 54. Smart Accounts featuring data tries and multiple built-in functions. 55. Generalized Paymaster solutions, enabling flexible fee models. 56. Subscriptions for recurring or automated on-chain payments. 57. Web2-like usability with Web3 functionality, bridging mainstream adoption. 58. StakingV4 for improved decentralization. 59. Enhanced MEV protection rolling out to safeguard users. 60. Parallel execution is coming soon, boosting throughput. 61. 1 million TPS is on the roadmap, targeted for demonstration. 62. 600ms block time is also coming soon. 63. Reduced cross-shard processing is planned to improve efficiency. 64. ZK everywhere (PI²): “prove everything” approach is coming. 65. AsyncV3 is in development for more complex cross-contract interactions. 66. Scalability enhancements for Merkle Tries or a new data model are being explored. 67. Linear storage on the VM is forthcoming. 68. A dynamic language interpreter at the VM is also planned. 69. Rumors suggest that MultiversX (EGLD) is building a “Truth Machine” on their L1—an essential, game-changing tool for AI verification and societal impact. 70. The entire team features individuals with PhDs in mathematics and physics, and many are former engineers at Google, IBM, and similar companies. 71. Over 56% of the network’s supply is staked, showcasing strong community involvement. 72. More than 6,772,347 accounts have been created on the network. 73. A total of 476,627,710 transactions have been processed on-chain without any outages or hacks. 74. EGLD has built a massive ecosystem over time. While not as numerous in project count as Solana, its market cap is ~100x smaller, yet it has far superior tokenomics and technology. The projects that do exist, like Hatom Protocol, are top-tier in UX, security, and advanced features. Hatom will soon introduce USH, a truly high-quality, decentralized stablecoin. 75. On competing chains, automated transactions aren’t easily or cheaply executed, whereas on MultiversX, tools like let you do this for free (with near-zero fees). 76. No other chain combines such a strong team and long-term vision where every product meets extreme security and UX standards like MultiversX does. This is why I see it as the “next Apple” in Web3. 77. MultiversX has a new CMO – Adam Bates, a former CMO at the Cardano Foundation. He was behind the success of Cardano’s huge marketing campaign and has a very good relationship with Charles Hoskinson. Thanks to him, Beniamin Mincu (the founder of MultiversX) was likely introduced, and now they will probably discuss how both blockchains can help each other, as well as any other potential collaborations we don’t yet know about. This is also extremely bullish. #EGLD is undeniably the most Scalable, Advanced, Secure, and User-friendly L1 supercomputer ever created. It’s built to SHAPE THE FUTURE. 1) 2) 3) 4) 5) 27/6/2024 - EGLDSqueeze - SUMMARY: HERE IS NO 2ND BEST. EGLD IS ONLY ONE BLOCKCHAIN THAT CAN RULE THEM ALL. ✅ UNLIMITED SCALING ✅ SCARCE AS BTC ✅ PROGRAMMABLE AS ETH ✅ NO DOWNTIME AS SOL ✅ UI/UX OF Apple ✅ SHARDING DONE BEFORE NEAR & TON ✅ BEST WALLET xPortal WITH GUARDIAN Price prediction (NFA|DYOR): My reasoning is that the real market cap as of December 23, 2024...if we take into account the value of other cryptocurrencies such as BTC, SOL, ETH, AVAX, NEAR, TON, Cardano, BNB, XRP, and so forth, plus the existence of meme coins with valuations above 20 billion USD, or even games nobody plays anymore that still have valuations above 800 million shows that EGLD’s current market cap of approximately 942 million USD is incredibly low. From a technological standpoint, user experience, and other relevant aspects, compared to SOL, NEAR, TON, AVAX, and other L1 protocols, EGLD’s market cap should realistically be around 100 billion USD. Therefore, my prediction and investment thesis is a minimum of a 100x increase from its current price (+-SOL marketcap). MultiversX is ready to onboard 1 billion people to the blockchain. From a long-term perspective, it could even reach a market cap of 1 trillion USD, which is roughly half of where BTC is right now. That would be approximately a 1060x gain from the current market cap. 1 EGLD (MultiversX) is for $34 (only 31.4M max supply) think about this. Not financial advice. Again. There is no 2nd best L1. Position yourself where the puck is going, then wait at the goal until the goal gets there Apes together, strong. Ape alone, weak. We Don't Worry. We Just Win. Shape The Future
5:34

77 Reasons Why I’ve Invested Over $8,000,000+ in MultiversX (EGLD) and Why EGLD Will Crush It in 2025 (My Investment Thesis). I publicly shared my portfolio on X. EGLD is A) Better than BTC B) Everything that ETH wants to be C) The GameStop of Crypto 1. EGLD is verifiably the most scalable (theoretically unlimited) L1 chain in the world, theoretically capable of over 10 million TPS (thanks to adaptive state sharding). 2. e-Gold is digital gold. It has the best tokenomics among all L1s, similarly scarce to BTC, with a maximum supply of 31.4 million coins. Currently, 27.68 million coins are in circulation. 3. EGLD will be the most decentralized cryptocurrency in the world thanks to sharding and minimal hardware requirements for running nodes. It’s already second only to Ethereum with 3,618 validator nodes. 4. EGLD has extremely low fees, around ~$0.002 per transaction. 5. EGLD is extremely secure. No wallet drains like on ETH/SOL; assets are owned natively (not via a smart contract). There is no MEV risk (front-running bots). 6. EGLD is the only chain in the world with an on-chain Guardian (two-phase verification), making it impossible for a hacker to steal your funds—even if they have your private keys (seed phrase). 7. EGLD is carbon-neutral and eco-friendly, not wasting energy like BTC and other PoW chains. It’s exceptionally efficient, scalable, global, and sustainable. 8. EGLD has the best UX in crypto. Download the xPortal wallet—it’s like discovering Apple in Web3. The interface is simple, flawless, and you barely realize you’re using crypto. Instead of addresses, you use HeroTags. The app features all dApps, everything runs smoothly, and the visuals are beautifully designed. The explorer, web wallet, etc. follow the same high-quality user experience. 9. EGLD supports native assets, unlike Ethereum, for example. 10. EGLD is the first chain to fully implement horizontal (theoretically unlimited) sharding without compromising on decentralization—unlike Solana and others that attempt vertical scaling, leading to multiple network downtimes (11+ times) and huge hardware demands for validators, ultimately harming decentralization. 11. EGLD makes setting up a validator agency extremely easy. Even complete IT beginners can do it. The UX and documentation are superb. I personally set up the “EGLDSqueeze” agency in about 30 minutes. Managing it is straightforward via the web wallet, which feels like managing a Facebook page. This simplifies decentralization enormously. 12. EGLD allows literally anyone (even your grandma) to participate in decentralization, since nodes can run on a Raspberry Pi or a relatively affordable phone. Imagine millions of people worldwide securing the network, validating transactions without even knowing it. This can’t be done with BTC, where setting up profitable mining operations is prohibitively expensive. 13. WASM-Based Virtual Machine: You can write smart contracts in your favorite language, compile them, and run them via the fastest VM in the world. 14. EGLD has been tested at an incredible 263,000 TPS using its sharding mechanism and low hardware requirements. Allegedly, by mid-next year (April), they’ll demonstrate 1,000,000 TPS. (For context: Mastercard handles around 5,000 TPS; BTC handles 5–7 TPS.) 15. EGLD is currently the most advanced L1 in terms of scalability, security, decentralization, UX, eco-friendliness, and tokenomics. It’s the only chain that has genuinely solved the Blockchain Trilemma and is ready to onboard 1 billion people into crypto—users who won’t even realize they’re interacting with crypto. 16. EGLD is perfectly positioned for AI projects—AI agents, AI tools, or a so-called “Truth Machine” that monitors other AIs on-chain, documenting what’s true and comparing different AI outputs (some of which may be censored or biased), ensuring people don’t get confused or scammed in an AI-driven world. 17. The EGLD team is the hardest-working team I’ve ever encountered. I had the honor of meeting many of them personally, and can attest that their pace—even during a bear market—is extraordinary. 18. EGLD’s development team is exceptionally active on GitHub, continually improving their network and actively committing code. 19. EGLD plans to introduce an update reducing block time to 600ms (down from ~6 seconds), which would make the chain essentially unrivaled. 20. EGLD is effectively the only usable L1 in Europe, and the team has direct connections within the EU government—extremely bullish for the project. 21. EGLD provides top-tier on-chain governance not only for the MultiversX (EGLD) protocol but also for DeFi projects (e.g., xExchange, MEX). 22. EGLD plans to expand to the US, likely opening offices in Austin, Texas. This could put them in direct contact with Elon Musk (if it hasn’t happened already), as he’s involved with If he’s done his research, he’d discover there’s simply no better L1 worldwide. 23. EGLD solved fully implemented sharding, perfect tokenomics, and top-tier architecture with just $5M, whereas other chains failed to do so even with $100M+. The second-best sharding network, NEAR, needed $100M, has worse tokenomics, and its sharding isn’t fully implemented yet. Its UX also doesn’t compare. Owning NEAR was like comparing a VW Golf R to a Porsche GT3—EGLD is the Porsche GT3. 24. According to Similarweb, EGLD has significantly high traffic relative to other chains with market caps 100x larger. The market cap vs. web traffic discrepancy is huge, which is a strong indicator of EGLD’s potential. 25. EGLD has the most active and dedicated community relative to its user base, with users who believe in the technology, have full faith in the team, and remain loyal despite price volatility—because they use the chain and know there’s nothing better. 26. Check other chains’ active user counts on X (Twitter) and compare it with the followers of EGLD’s founders and main network accounts, versus those with 30x, 50x, or 100x larger market caps. 27. Visit the MultiversX website to observe the futuristic design and presentation, then compare it to other chains that appear nearly a decade behind in design and branding. 28. EGLD hosts the xDay Global event, showcasing updates, new builders, projects in the ecosystem, and major announcements—similar to Apple’s Keynotes—delivered in a highly professional, goosebump-inducing atmosphere. The next event is in Korea, the second-biggest crypto market after the US. Check out their previous xDay after-movie to see why this is extremely bullish. 29. EGLD is moving forward with plans for the first regulated, audited EU stablecoin under MiCa regulation, made possible by acquiring xMoney, which I view as a “Stripe” for crypto/fiat, offering everything from user solutions to merchant services—potentially the future of payments. 30. Greg Siourouni recently joined EGLD, having been an executive director at SUI Foundation. He’s now co-founder of xMoney Global. xMoney (formerly UTrust, with token UTK) is owned and founded by the MultiversX Labs team. A stablecoin might be introduced soon, which would be massively bullish given xMoney’s roadmap. They recently announced integrations with Binance Pay—both ways. 31. EGLD prioritizes user safety, believing it’s the only feasible approach once the network scales to serve a billion people—many of whom are retail users with little to no security awareness. 32. EGLD offers “Sovereign Chains,” letting you effectively clone their chain without heavy development, set up your own validators, and leverage their unlimited scalability. Any blockchain (ETH, BTC, SOL) struggling with scalability, decentralization, or security could run an ultra-fast, scalable, and secure L2 on EGLD’s Sovereign Chain, meeting top enterprise requirements. No one else has really done this. The Sovereign Chain demo achieved astonishing TPS and has an SDK. 33. No downtime since inception. 34. No shard takeover attacks have occurred. 35. Extremely fast—soon 600ms block time will be in place. 36. ESDTs – The best token standard available: fungible, non-fungible, semi-fungible, DeFi assets—everything is native and highly customizable. 37. Top-tier composability of assets and smart contracts. 38. Integrated DNS at protocol level with HeroTags (nicknames) instead of long addresses. 39. Asynchronous calls are supported. 40. Cross-shard transfers, execution, reverts, and calls are seamlessly integrated. 41. The best staking system in the space. Secure Proof of Stake (SPoS) is far more efficient than Proof of Work (PoW). 42. Built-in Delegation and Staking Provider system, with over 125K delegators. 43. Complete support for liquid staked assets, fostering decentralization rather than centralization. 44. TransferRoles for ESDT and other advanced operations. 45. Composable tasks on-chain for more sophisticated DeFi workflows. 46. MultiTransfer and asset execution within one transaction. 47. Re-entrancy protection is built-in by design. 48. Storage for ESDT assets goes beyond a linear approach, optimizing performance. 49. No integer overflows thanks to integrated safeMath operations. 50. Integrated crypto opcodes in the VM, enhancing security and performance. 51. Support for BigFloats, BigInts, and BigDecimals, enabling advanced financial calculations on-chain. 52. No sandwich attacks, plus front-running and MEV protection. 53. Relayed Transactions, simplifying user interactions and fees. 54. Smart Accounts featuring data tries and multiple built-in functions. 55. Generalized Paymaster solutions, enabling flexible fee models. 56. Subscriptions for recurring or automated on-chain payments. 57. Web2-like usability with Web3 functionality, bridging mainstream adoption. 58. StakingV4 for improved decentralization. 59. Enhanced MEV protection rolling out to safeguard users. 60. Parallel execution is coming soon, boosting throughput. 61. 1 million TPS is on the roadmap, targeted for demonstration. 62. 600ms block time is also coming soon. 63. Reduced cross-shard processing is planned to improve efficiency. 64. ZK everywhere (PI²): “prove everything” approach is coming. 65. AsyncV3 is in development for more complex cross-contract interactions. 66. Scalability enhancements for Merkle Tries or a new data model are being explored. 67. Linear storage on the VM is forthcoming. 68. A dynamic language interpreter at the VM is also planned. 69. Rumors suggest that MultiversX (EGLD) is building a “Truth Machine” on their L1—an essential, game-changing tool for AI verification and societal impact. 70. The entire team features individuals with PhDs in mathematics and physics, and many are former engineers at Google, IBM, and similar companies. 71. Over 56% of the network’s supply is staked, showcasing strong community involvement. 72. More than 6,772,347 accounts have been created on the network. 73. A total of 476,627,710 transactions have been processed on-chain without any outages or hacks. 74. EGLD has built a massive ecosystem over time. While not as numerous in project count as Solana, its market cap is ~100x smaller, yet it has far superior tokenomics and technology. The projects that do exist, like Hatom Protocol, are top-tier in UX, security, and advanced features. Hatom will soon introduce USH, a truly high-quality, decentralized stablecoin. 75. On competing chains, automated transactions aren’t easily or cheaply executed, whereas on MultiversX, tools like let you do this for free (with near-zero fees). 76. No other chain combines such a strong team and long-term vision where every product meets extreme security and UX standards like MultiversX does. This is why I see it as the “next Apple” in Web3. 77. MultiversX has a new CMO – Adam Bates, a former CMO at the Cardano Foundation. He was behind the success of Cardano’s huge marketing campaign and has a very good relationship with Charles Hoskinson. Thanks to him, Beniamin Mincu (the founder of MultiversX) was likely introduced, and now they will probably discuss how both blockchains can help each other, as well as any other potential collaborations we don’t yet know about. This is also extremely bullish. #EGLD is undeniably the most Scalable, Advanced, Secure, and User-friendly L1 supercomputer ever created. It’s built to SHAPE THE FUTURE. 1) 2) 3) 4) 5) 27/6/2024 - EGLDSqueeze - SUMMARY: HERE IS NO 2ND BEST. EGLD IS ONLY ONE BLOCKCHAIN THAT CAN RULE THEM ALL. ✅ UNLIMITED SCALING ✅ SCARCE AS BTC ✅ PROGRAMMABLE AS ETH ✅ NO DOWNTIME AS SOL ✅ UI/UX OF Apple ✅ SHARDING DONE BEFORE NEAR & TON ✅ BEST WALLET xPortal WITH GUARDIAN Price prediction (NFA|DYOR): My reasoning is that the real market cap as of December 23, 2024...if we take into account the value of other cryptocurrencies such as BTC, SOL, ETH, AVAX, NEAR, TON, Cardano, BNB, XRP, and so forth, plus the existence of meme coins with valuations above 20 billion USD, or even games nobody plays anymore that still have valuations above 800 million shows that EGLD’s current market cap of approximately 942 million USD is incredibly low. From a technological standpoint, user experience, and other relevant aspects, compared to SOL, NEAR, TON, AVAX, and other L1 protocols, EGLD’s market cap should realistically be around 100 billion USD. Therefore, my prediction and investment thesis is a minimum of a 100x increase from its current price (+-SOL marketcap). MultiversX is ready to onboard 1 billion people to the blockchain. From a long-term perspective, it could even reach a market cap of 1 trillion USD, which is roughly half of where BTC is right now. That would be approximately a 1060x gain from the current market cap. 1 EGLD (MultiversX) is for $34 (only 31.4M max supply) think about this. Not financial advice. Again. There is no 2nd best L1. Position yourself where the puck is going, then wait at the goal until the goal gets there Apes together, strong. Ape alone, weak. We Don't Worry. We Just Win. Shape The Future

Daniel Veroc

50,331 views • 1 year ago

The multi-leader blockchain endgame: competitive information inclusion as a self-reinforcing mechanism for global price discovery - how we got here, and why Aptos is leading the charge Onchain trading is the killer app In the nine years since the launch of programmable transactions on the Ethereum blockchain, onchain trading has revealed itself as the killer use case for blockchains: onchain listings, volume, and total value locked are all growing with no signs of slowing down, due to the censorship-resistant, permissionless, 24/7/365 qualities afforded by decentralized (DeFi) systems. Monolithic parallelism is key In 2020 Solana was first to market with monolithic, parallel execution (as opposed sharded execution which offers parallelism by partitioning global state into separate information silos), establishing a new design paradigm that raised the bar for throughput and latency: put all of the information in one replicated state machine and make it run as fast as possible. This design produces a single, global hub for activity, liquidity, and token launches, a kind of financial data whiteboard in the sky, where anyone can come and trade at any time with everybody else who has plugged into the system. DEXes are becoming more competitive Historically decentralized systems have been juxtaposed with centralized ones since the latter eliminates the overhead associated with distributed systems coordination. And yet despite this overhead, Solana as a decentralized exchange (DEX) is still pulling in billions of trading volume per day, exceeding that of all but the largest centralized crypto exchanges (CEXs), that simply can't compete with the giant DEX in the sky on token listings or fees. After all, CEXs have to pay for server space, salaries, and lawyers, while a DEX outsources everything. The colocation arms race The one place where CEXs have an advantage over DEXs is on end-to-end latency for colocation applications, or in other words: someone sets up a trading bot in the same data center as the exchange, and their trades get to the exchange faster than everyone else's. When there is only one data ingestion point the fastest trader wins, and after the arms race has played out everyone ends up huddling around the trading hub, effectively cutting off the rest of the world from playing the latency trading game. This is the model that traditional securities exchanges like the Nasdaq or the NYSE 🏛 employ, and because they own the server they can effectively charge whatever they want for access to it. The colocation arms race is also why L2s will probably never decentralize: running the sequencer is practically the same as running the NASDAQ, with the same monopoly on transaction fees collected from a nearby cluster of trading bots (I understand from conversations with Logan Jastremski that the Arbitrum arms race has already hit a Nash Equilibrium in Portland, Oregon). Colocation is a trap But once the colocation arms race has played out, trades become less about incorporating new information in the market and more about skimming off the top by spoofing all of the trades coming in from the other bots. High-frequency trading (HFT) bots located in the NYSE New Jersey data center, for example, are constantly placing buys and sell orders that they have no intention of executing, just to spoof the other colocated bots who are playing the same adversarial game. Information inclusion, on the other hand, the synthesis of real-time world events into prices, takes a back seat because anyone who tries to include new information first needs to batch up their order and send it through a series of middlemen before it ultimately ends up on the exchange: you, I, or practically any other individual can not actually "trade on the NASDAQ", no, we have to express our intent to someone like Robinhood, who then sells our order flow to @CitadelSecurities, who then sends it to the exchange, oh and by the way it doesn't actually even "clear" or "settle" once it "executes" because for whatever reason the whole systems splits these things up and prevents them from happening instantaneously even though it's 2024 and we have computers. Onchain trading cuts out middlemen This whole mess is why we have onchain trading, and why it's starting to win: if you want a mainline to the exchange, without setting up a server, and you want to trade on a news event without getting immediately frontrun by an HFT bot that is sniffing out the trades of every other HFT bot who is easing in batched up order flow on their own terms, then you submit your order to a node in the blockchain and the information gets included in the price upon ingestion. Oh, and by the way the trade is actually fully complete: settled, cleared, reconciled, done, whatever you want to call it, because the people who build decentralized finance (DeFi) build it how it should actually work, not in a way that creates a million incumbents and charges exorbitant rents for access to the system. Onchain trading better for price discovery And the beautiful part about this is that even if a distributed system has more latency than a centralized system, DeFi still ends up incorporating more information into the price faster than centralized finance, because with DeFi the information gets included in the system as soon as it is submitted, not after it has been batched up and sent through a series of middlemen. The consensus mechanism of the blockchain disseminates the information around the world in the form of a price update, while the centralized exchange model requires information about the event to first get propagate to the region of the trading hub, then to get submitted to the colocation server. This means that in terms of global price discovery, onchain trading is strictly a better system because the entire consensus model is based around accelerated information propagation. Because price discovery is a global phenomenon, blockchains, which are global, are actually better than the centralized status quo, on a performance basis, not just from an ideological or convenience-based view. And it has to be multi-leader In practice, effective global information synthesis of information has an additional key requirement: multi-leader architecture. That is, in a single-leader blockchain like Solana, where one validator at a time has a monopoly on ordering transactions into blocks, for their duration as a leader they effectively function as a colocation server. This means that if the current leader is in New York, someone in Singapore who wants to trade on local news as soon as it breaks will still need to get their order all the way around the world to the leader, who is effectively serving as the chain's data ingestion point, before the order can start propagating through the network. But this is issue solved by the introduction of multiple distributed leaders, because then anyone with access to new information can submit their order to the leader closest to them, yielding faster information inclusion in the form of price updates. Multi-leader is also required for fair markets A multi-leader architecture is also required for fair markets, because in a single-leader system the leader has the power to censor transactions, reorder them to their advantage, or even replace transactions with copycats that extract maximum value by replacing the sender's address with their own. For example if someone wants to capture an arbitrage opportunity between two onchain DEXes, they'll need to submit a transaction to the leader and trust that the leader won't simply copy the transaction and submit it themselves. But when there are two or more leaders, users whose transactions are censored by one leader will simply work with a different leader the next time around, eventually cutting off transaction fee flow to the extractive leader. Beyond just strict inclusion, in a multi-leader architecture validators are also forced to compete with each other on latency, because the leader who is fastest at disseminating users' transactions across the network will over time gobble up the largest share of the order flow. Transparent priority fees are a must, or a private mempool will emerge But in order to make this work, a multi-leader architecture must also offer users the ability to pay priority fees AKA "tips" or "bribes" to move their transaction to the front of the line: if there is a $5 arbitrage opportunity onchain, users need to have assurance that they if they pay a 4.99 priority fee to take that arb, they will get priority over a different user who is only willing to tip 4.98. If the native blockchain system does not offer this fair market priority fee mechanism, then it is only a matter of time before one spontaneously emerges in the form of a private mempool like Jito, which can create centralization pressures and undermine the integrity of the system as a whole. Competitive payment for order flow is the stable solution With the right architecture in place, the end result is a competitive environment where endpoints running maximum extractable value (MEV) bots compete with one to offer users the best price for their order flow. In other words, if a user wants to submit an order that can get sandwich attacked for as much as $2 of MEV, then the order should ultimately go to the endpoint bot that is willing to pay the user as much as $1.99 for the right to process their transaction. The price that the provider is willing to pay is ultimately a function of how much in priority fees they might need to pay to the current leader (0 they are the current one), but notably at each stage there is a competitive market for order flow, whether in the form of retail trader's orders, or priority fees among bots that might be forwarding orders to one of the leaders. AptosLabs is already building all this With a public mempool and transaction priority fees, Aptos additionally includes a pipelined architecture that already includes concurrent batching of transactions into blocks, with a single consensus leader who propagates the batched blocks out to the network. And the team is already researching running multiple instances of the consensus algorithm in parallel, yielding multiple consensus leaders who can compete with each other on latency and inclusion - just ask pranav | Shelby, Alexander Spiegelman, and Zekun Li. This means that block times can shrink as the number of consensus leaders grows, with each leader having its own geographical radius of inclusion beyond which it makes more sense to submit to a different leader. The starting point? Something like 60 ms blocks and 3 consensus leaders, partitioning the global information space into competitive and constantly-rotating regions of information inclusion. Messaging is important With concurrent pipelined transaction batching, a public mempool, priority fees, and a clear path to a multi-leader architecture, Aptos leads the industry in onchain trading infrastructure that can truly supplant the centralized colocation paradigm that has heretofore dominated global finance - by offering a truly superior product. And I am hopeful that this deep dive is the first step in communicating not how or that superior product is getting built, but what it means from a bigger picture perspective. If blockchains have found product market fit in anything, it is in trading, and the trading game can only be won by building the biggest, baddest, most high performance system that has as its north star a single, concrete goal: constantly reducing, ever lower toward zero, time time it takes to incorporate information from anywhere in the world into the global price discovery computer. Whoever does this, even 1 ms faster than the competitor, wins the price discovery game, as other blockchains are left in the dust, their DEXes arbed away to zero against the fastest chain on the block. And sure, the blockchain that can rise to this challenge can also handle useful things like payments, NFTs, or other solutions that benefit from permissionlessness and low gas costs, but I want to impress that at the core of this pursuit must be the urge to drive down information inclusion latency to the absolute minimum afforded by the laws of physics through a competitive, market-driven environment. I call on avery.apt 🇺🇸 , CTO of Aptos Labs, to lean in on this messaging, to make it clear that Aptos is here for this singular mission, to build the most performant price discovery engine in history, as a rallying call for alignment in development efforts across the ecosystem and broader industry. Where does this go? As the latencies drop, the spreads tighten, and the information inclusion increases with every incremental increase in network bandwidth, we can expect a new class of competing techno-financial hubs that aggregate around the world's largest information sources: New York, Washington DC, London, Tokyo, etc., commanding stake distribution commensurate with the density of information flow in these respective locales. With the right incentives in place, competing concurrent leaders will invest ever more in infrastructure to get their packets out to the network faster than the rest, yielding clusters of fiber optic cable around the world's financial hubs, neurons in the global financial brain connecting not just HFT firms to servers in their city, but connecting every city with every other city, to move pricing information across oceans and continents. And retail traders, who have been left out of the colocation game, will only benefit: this entire system gets faster, more inclusive, with tighter spreads and lower fees, and it is such an amazing opportunity to watch all of this unfold in real time. The future of blockchains is the future of trading, is the future of competitive information inclusion in real-time, is the future of truly unified global markets, because at the the core of this industry is a simple idea: connect the computers, and see where the incentives lead. They lead to this, and Aptos is leading the charge, because its tech is purpose-built for this exact purpose. So tell the world about it.
2:41

The multi-leader blockchain endgame: competitive information inclusion as a self-reinforcing mechanism for global price discovery - how we got here, and why Aptos is leading the charge Onchain trading is the killer app In the nine years since the launch of programmable transactions on the Ethereum blockchain, onchain trading has revealed itself as the killer use case for blockchains: onchain listings, volume, and total value locked are all growing with no signs of slowing down, due to the censorship-resistant, permissionless, 24/7/365 qualities afforded by decentralized (DeFi) systems. Monolithic parallelism is key In 2020 Solana was first to market with monolithic, parallel execution (as opposed sharded execution which offers parallelism by partitioning global state into separate information silos), establishing a new design paradigm that raised the bar for throughput and latency: put all of the information in one replicated state machine and make it run as fast as possible. This design produces a single, global hub for activity, liquidity, and token launches, a kind of financial data whiteboard in the sky, where anyone can come and trade at any time with everybody else who has plugged into the system. DEXes are becoming more competitive Historically decentralized systems have been juxtaposed with centralized ones since the latter eliminates the overhead associated with distributed systems coordination. And yet despite this overhead, Solana as a decentralized exchange (DEX) is still pulling in billions of trading volume per day, exceeding that of all but the largest centralized crypto exchanges (CEXs), that simply can't compete with the giant DEX in the sky on token listings or fees. After all, CEXs have to pay for server space, salaries, and lawyers, while a DEX outsources everything. The colocation arms race The one place where CEXs have an advantage over DEXs is on end-to-end latency for colocation applications, or in other words: someone sets up a trading bot in the same data center as the exchange, and their trades get to the exchange faster than everyone else's. When there is only one data ingestion point the fastest trader wins, and after the arms race has played out everyone ends up huddling around the trading hub, effectively cutting off the rest of the world from playing the latency trading game. This is the model that traditional securities exchanges like the Nasdaq or the NYSE 🏛 employ, and because they own the server they can effectively charge whatever they want for access to it. The colocation arms race is also why L2s will probably never decentralize: running the sequencer is practically the same as running the NASDAQ, with the same monopoly on transaction fees collected from a nearby cluster of trading bots (I understand from conversations with Logan Jastremski that the Arbitrum arms race has already hit a Nash Equilibrium in Portland, Oregon). Colocation is a trap But once the colocation arms race has played out, trades become less about incorporating new information in the market and more about skimming off the top by spoofing all of the trades coming in from the other bots. High-frequency trading (HFT) bots located in the NYSE New Jersey data center, for example, are constantly placing buys and sell orders that they have no intention of executing, just to spoof the other colocated bots who are playing the same adversarial game. Information inclusion, on the other hand, the synthesis of real-time world events into prices, takes a back seat because anyone who tries to include new information first needs to batch up their order and send it through a series of middlemen before it ultimately ends up on the exchange: you, I, or practically any other individual can not actually "trade on the NASDAQ", no, we have to express our intent to someone like Robinhood, who then sells our order flow to @CitadelSecurities, who then sends it to the exchange, oh and by the way it doesn't actually even "clear" or "settle" once it "executes" because for whatever reason the whole systems splits these things up and prevents them from happening instantaneously even though it's 2024 and we have computers. Onchain trading cuts out middlemen This whole mess is why we have onchain trading, and why it's starting to win: if you want a mainline to the exchange, without setting up a server, and you want to trade on a news event without getting immediately frontrun by an HFT bot that is sniffing out the trades of every other HFT bot who is easing in batched up order flow on their own terms, then you submit your order to a node in the blockchain and the information gets included in the price upon ingestion. Oh, and by the way the trade is actually fully complete: settled, cleared, reconciled, done, whatever you want to call it, because the people who build decentralized finance (DeFi) build it how it should actually work, not in a way that creates a million incumbents and charges exorbitant rents for access to the system. Onchain trading better for price discovery And the beautiful part about this is that even if a distributed system has more latency than a centralized system, DeFi still ends up incorporating more information into the price faster than centralized finance, because with DeFi the information gets included in the system as soon as it is submitted, not after it has been batched up and sent through a series of middlemen. The consensus mechanism of the blockchain disseminates the information around the world in the form of a price update, while the centralized exchange model requires information about the event to first get propagate to the region of the trading hub, then to get submitted to the colocation server. This means that in terms of global price discovery, onchain trading is strictly a better system because the entire consensus model is based around accelerated information propagation. Because price discovery is a global phenomenon, blockchains, which are global, are actually better than the centralized status quo, on a performance basis, not just from an ideological or convenience-based view. And it has to be multi-leader In practice, effective global information synthesis of information has an additional key requirement: multi-leader architecture. That is, in a single-leader blockchain like Solana, where one validator at a time has a monopoly on ordering transactions into blocks, for their duration as a leader they effectively function as a colocation server. This means that if the current leader is in New York, someone in Singapore who wants to trade on local news as soon as it breaks will still need to get their order all the way around the world to the leader, who is effectively serving as the chain's data ingestion point, before the order can start propagating through the network. But this is issue solved by the introduction of multiple distributed leaders, because then anyone with access to new information can submit their order to the leader closest to them, yielding faster information inclusion in the form of price updates. Multi-leader is also required for fair markets A multi-leader architecture is also required for fair markets, because in a single-leader system the leader has the power to censor transactions, reorder them to their advantage, or even replace transactions with copycats that extract maximum value by replacing the sender's address with their own. For example if someone wants to capture an arbitrage opportunity between two onchain DEXes, they'll need to submit a transaction to the leader and trust that the leader won't simply copy the transaction and submit it themselves. But when there are two or more leaders, users whose transactions are censored by one leader will simply work with a different leader the next time around, eventually cutting off transaction fee flow to the extractive leader. Beyond just strict inclusion, in a multi-leader architecture validators are also forced to compete with each other on latency, because the leader who is fastest at disseminating users' transactions across the network will over time gobble up the largest share of the order flow. Transparent priority fees are a must, or a private mempool will emerge But in order to make this work, a multi-leader architecture must also offer users the ability to pay priority fees AKA "tips" or "bribes" to move their transaction to the front of the line: if there is a $5 arbitrage opportunity onchain, users need to have assurance that they if they pay a 4.99 priority fee to take that arb, they will get priority over a different user who is only willing to tip 4.98. If the native blockchain system does not offer this fair market priority fee mechanism, then it is only a matter of time before one spontaneously emerges in the form of a private mempool like Jito, which can create centralization pressures and undermine the integrity of the system as a whole. Competitive payment for order flow is the stable solution With the right architecture in place, the end result is a competitive environment where endpoints running maximum extractable value (MEV) bots compete with one to offer users the best price for their order flow. In other words, if a user wants to submit an order that can get sandwich attacked for as much as $2 of MEV, then the order should ultimately go to the endpoint bot that is willing to pay the user as much as $1.99 for the right to process their transaction. The price that the provider is willing to pay is ultimately a function of how much in priority fees they might need to pay to the current leader (0 they are the current one), but notably at each stage there is a competitive market for order flow, whether in the form of retail trader's orders, or priority fees among bots that might be forwarding orders to one of the leaders. AptosLabs is already building all this With a public mempool and transaction priority fees, Aptos additionally includes a pipelined architecture that already includes concurrent batching of transactions into blocks, with a single consensus leader who propagates the batched blocks out to the network. And the team is already researching running multiple instances of the consensus algorithm in parallel, yielding multiple consensus leaders who can compete with each other on latency and inclusion - just ask pranav | Shelby, Alexander Spiegelman, and Zekun Li. This means that block times can shrink as the number of consensus leaders grows, with each leader having its own geographical radius of inclusion beyond which it makes more sense to submit to a different leader. The starting point? Something like 60 ms blocks and 3 consensus leaders, partitioning the global information space into competitive and constantly-rotating regions of information inclusion. Messaging is important With concurrent pipelined transaction batching, a public mempool, priority fees, and a clear path to a multi-leader architecture, Aptos leads the industry in onchain trading infrastructure that can truly supplant the centralized colocation paradigm that has heretofore dominated global finance - by offering a truly superior product. And I am hopeful that this deep dive is the first step in communicating not how or that superior product is getting built, but what it means from a bigger picture perspective. If blockchains have found product market fit in anything, it is in trading, and the trading game can only be won by building the biggest, baddest, most high performance system that has as its north star a single, concrete goal: constantly reducing, ever lower toward zero, time time it takes to incorporate information from anywhere in the world into the global price discovery computer. Whoever does this, even 1 ms faster than the competitor, wins the price discovery game, as other blockchains are left in the dust, their DEXes arbed away to zero against the fastest chain on the block. And sure, the blockchain that can rise to this challenge can also handle useful things like payments, NFTs, or other solutions that benefit from permissionlessness and low gas costs, but I want to impress that at the core of this pursuit must be the urge to drive down information inclusion latency to the absolute minimum afforded by the laws of physics through a competitive, market-driven environment. I call on avery.apt 🇺🇸 , CTO of Aptos Labs, to lean in on this messaging, to make it clear that Aptos is here for this singular mission, to build the most performant price discovery engine in history, as a rallying call for alignment in development efforts across the ecosystem and broader industry. Where does this go? As the latencies drop, the spreads tighten, and the information inclusion increases with every incremental increase in network bandwidth, we can expect a new class of competing techno-financial hubs that aggregate around the world's largest information sources: New York, Washington DC, London, Tokyo, etc., commanding stake distribution commensurate with the density of information flow in these respective locales. With the right incentives in place, competing concurrent leaders will invest ever more in infrastructure to get their packets out to the network faster than the rest, yielding clusters of fiber optic cable around the world's financial hubs, neurons in the global financial brain connecting not just HFT firms to servers in their city, but connecting every city with every other city, to move pricing information across oceans and continents. And retail traders, who have been left out of the colocation game, will only benefit: this entire system gets faster, more inclusive, with tighter spreads and lower fees, and it is such an amazing opportunity to watch all of this unfold in real time. The future of blockchains is the future of trading, is the future of competitive information inclusion in real-time, is the future of truly unified global markets, because at the the core of this industry is a simple idea: connect the computers, and see where the incentives lead. They lead to this, and Aptos is leading the charge, because its tech is purpose-built for this exact purpose. So tell the world about it.

Alex Kahn

24,432 views • 1 year ago

DeepFreeze on the XRP Ledger – A Comprehensive Examination We need to discuss an amendment that went unnoticed for a long time: DeepFreeze. If you are to lazy to read, just watch the video. Eminence is already voting for its activation, and I urge my fellow node operators and the community to support it. Let’s look at why. Welcome to a detailed examination of DeepFreeze, a transformative feature introduced to the XRP Ledger. This amendment is critical for institutional asset management within the ledger ecosystem. In this analysis, we’ll explore the full scope of DeepFreeze—its definition, technical architecture, institutional significance, community development, and long-term implications for XRPL’s role in financial systems. This is a deep dive into a feature that could redefine blockchain compliance and adoption. What exactly is DeepFreeze? DeepFreeze is an advanced asset-freezing mechanism integrated into the XRPL, tailored explicitly for fungible tokens issued on the ledger, such as stablecoins and tokenised real-world assets. Unlike XRP, which remains unaffected due to its native status, issued tokens fall under the control of their issuers, who can now leverage DeepFreeze for unprecedented oversight. The standard freeze, a pre-existing feature, restricts an account to only receiving tokens, preventing outward transfers. DeepFreeze, however, escalates this control by prohibiting both sending and receiving, effectively isolating the account from all token-related activities except direct transactions with the issuer. According to the XRPL documentation, available at DeepFreeze requires the activation of the DeepFreeze amendment—a network-wide upgrade voted on by XRPL validators. It cannot be applied if the issuer has set the NoFreeze flag on their account, a safeguard that permanently disables freezing capabilities for that issuer’s tokens. This layered design ensures flexibility while prioritising compliance, making DeepFreeze a powerful tool for managing token ecosystems in regulated environments. The significance for Institutions. The significance of DeepFreeze becomes evident when viewed through an institutional lens. For financial entities—such as central banks issuing central bank digital currencies (CBDCs), or stablecoin providers like Ripple’s RLUSD, Societe Generale Group Forge’s EURCV, and Braza Bank’s BBRL—this feature offers a robust mechanism to enforce regulatory compliance. Consider a scenario where an account is identified on an international sanctions list, such as those maintained by the U.S. Office of Foreign Assets Control (OFAC Treasury Department). DeepFreeze allows the issuer to immediately halt all token activity for that account, preventing inflows or outflows that could violate anti-money laundering (AML) or know-your-customer (KYC) regulations. Beyond sanctions, DeepFreeze addresses fraud mitigation. If a stablecoin issuer detects suspicious activity—a hacked account attempting to siphon funds—they can deep-freeze it, stopping the damage while investigations unfold. A article underscores this utility, noting that the standard freeze’s limitation—allowing incoming transfers—falls short for high-stakes compliance needs. DeepFreeze’s total lockdown fills this gap, enhancing security and trust. This capability could attract major regulated entities like Circle, issuer of USDC, to deploy stablecoins on the XRPL, drawn by its compliance-ready infrastructure. Such adoption would increase token volume, liquidity, and the ledger’s utility for real-world asset tokenization—think real estate or commodities—positioning the XRPL as a leader in institutional blockchain applications. The Technical Mechanics. (This is a bit technical) Let’s examine the technical architecture underpinning DeepFreeze, which introduces specific flags to the XRPL’s ledger structure. These flags, detailed in the XRPL documentation, govern trust lines—the bilateral agreements between accounts that enable token holding—and enforce the freeze’s effects. Here’s how they work: The lsfLowDeepFreeze flag is set on the RippleState object to indicate that the low account in a trust line is deep-frozen. This prevents the high account from sending or receiving the token along that trust line, effectively severing its transactional capability. Conversely, the lsfHighDeepFreeze flag marks the high account as deep-frozen, blocking the low account from similar activities. This bidirectional control ensures symmetry in enforcement. In TrustSet transactions, issuers use the tfSetDeepFreeze flag, to apply the DeepFreeze to a specific trust line, activating the lockdown. To reverse this, the tfClearDeepFreeze flag is invoked in a TrustSet transaction, restoring normal functionality to the trust line. These flags have sweeping effects across XRPL operations. Payments to a deep-frozen account fail outright, with the transaction engine returning a tecDSTfrozen error if the destination is locked. Rippling—where tokens pass through intermediary accounts—ceases for deep-frozen trust lines, halting multi-hop transfers. On the decentralized exchange (DEX) and automated market maker (AMM) systems, OfferCreate transactions involving a deep-frozen TakerPays token fail with a tecFROZEN error, and existing offers tied to frozen accounts are implicitly canceled when crossed by new offers, rendering them unfunded. The GitHub discussion at XRPLF/XRPL-Standards #220 adds further nuance, noting impacts on Check transactions—a feature for deferred payments. CheckCash fails if the recipient’s trust line is deep-frozen, protecting against unauthorized redemption, though CheckCreate and CheckCancel remain unaffected, preserving issuer flexibility. This granular control reflects DeepFreeze’s design for precision in compliance-driven scenarios. Community Development. The development of DeepFreeze highlights the XRPL community’s collaborative strength. On August 26, 2024, Shawn Xie of Ripple initiated the XLS-77d proposal in a GitHub discussion, accessible at XRPLF/XRPL-Standards #220. Spanning six comments and seven replies, the thread reveals active engagement. One participant (Wietse Wind - 🪝☝️🛠 Xaman® + XRPL + Xahau) suggested renaming ‘blackholing’—disabling an account permanently—to ‘permafrosting,’ arguing it better conveys the frozen state’s permanence and aligns with DeepFreeze’s theme. This linguistic refinement, while minor, exemplifies community influence on usability. Technical clarifications also emerged. The discussion distinguishes DeepFreeze from GlobalFreeze, which freezes all trust lines for an issuer’s tokens, noting that DeepFreeze targets specific trust lines for finer control. A question arose about rare cases where the standard tfSetFreeze might suffice—such as temporary holds—but the consensus favored DeepFreeze’s comprehensive approach for most compliance needs. The proposal, now in draft status, was merged into the rippled software codebase via pull request XRPLF/rippled #5187, confirming its deployment readiness as of March 19, 2025. This milestone underscores XRPL’s commitment to evolving through community-driven innovation. The Institutional Impact. From an institutional standpoint, DeepFreeze addresses critical gaps in the standard freeze’s functionality. The article explains that the older mechanism, while useful, permitted incoming transfers and balance adjustments, rendering it inadequate for scenarios requiring total isolation—such as sanctions enforcement or fraud containment. DeepFreeze’s ability to block all activity offers a superior solution, tailored to the demands of regulated finance. Consider its applications: a stablecoin issuer like Ripple could deep-freeze an account suspected of laundering funds, halting its operations pending review. A tokenized real estate platform could use it to secure assets during legal disputes, ensuring no unauthorized transfers occur. For sanctions, it ensures compliance with global frameworks, preventing tokens from reaching blacklisted entities. These use cases enhance the XRPL’s appeal to institutional players, potentially drawing Circle’s USDC or other major stablecoins to the ledger. The ripple effect—pardon the pun—could be substantial. Increased institutional adoption would boost token issuance, trading volume, and liquidity, reinforcing XRPL’s infrastructure for real-world asset tokenization. This aligns with broader trends in blockchain finance, where compliance-ready platforms are increasingly favored by traditional institutions seeking to integrate digital assets. Conclusion and Implications. In conclusion, DeepFreeze represents a strategic leap forward for the XRP Ledger, harmonizing technological sophistication with regulatory necessity. By equipping issuers with comprehensive control over their tokens, it addresses the compliance and security needs of institutional users, from stablecoin providers to asset tokenizers. As of March 19, 2025, its technical implementation is mature, its community support robust, and its potential to drive XRPL adoption undeniable. Looking ahead, DeepFreeze could position the XRPL as a premier blockchain for regulated financial applications, bridging the gap between decentralized innovation and centralized oversight. Its success will depend on validator adoption of the DeepFreeze amendment and real-world uptake by institutions—a process already underway. For a deeper understanding, refer to the XRPL documentation, the article, and the GitHub discussion linked below. DeepFreeze is more than a feature—it’s a foundation for the XRPL’s future in institutional finance. How do you envision its impact on the blockchain landscape? Your perspectives are welcome. PS: This is by far the most exciting amendment since XLS20, but of course, your average influencer doesn't talk about it in his paid group or while he is siphoning your donations. Unfollow them today. ################## Ressouces: XRPL Docs: XLS-77d: Devto Article: Misunderstandings about Freezes: Amendment voting: If you want to support what I do, follow me and buy me a beer or just use one of the CasinoCoin/LuckyHash 🪝 partners for recreational gaming: Check out my other explainers:
11:51

DeepFreeze on the XRP Ledger – A Comprehensive Examination We need to discuss an amendment that went unnoticed for a long time: DeepFreeze. If you are to lazy to read, just watch the video. Eminence is already voting for its activation, and I urge my fellow node operators and the community to support it. Let’s look at why. Welcome to a detailed examination of DeepFreeze, a transformative feature introduced to the XRP Ledger. This amendment is critical for institutional asset management within the ledger ecosystem. In this analysis, we’ll explore the full scope of DeepFreeze—its definition, technical architecture, institutional significance, community development, and long-term implications for XRPL’s role in financial systems. This is a deep dive into a feature that could redefine blockchain compliance and adoption. What exactly is DeepFreeze? DeepFreeze is an advanced asset-freezing mechanism integrated into the XRPL, tailored explicitly for fungible tokens issued on the ledger, such as stablecoins and tokenised real-world assets. Unlike XRP, which remains unaffected due to its native status, issued tokens fall under the control of their issuers, who can now leverage DeepFreeze for unprecedented oversight. The standard freeze, a pre-existing feature, restricts an account to only receiving tokens, preventing outward transfers. DeepFreeze, however, escalates this control by prohibiting both sending and receiving, effectively isolating the account from all token-related activities except direct transactions with the issuer. According to the XRPL documentation, available at DeepFreeze requires the activation of the DeepFreeze amendment—a network-wide upgrade voted on by XRPL validators. It cannot be applied if the issuer has set the NoFreeze flag on their account, a safeguard that permanently disables freezing capabilities for that issuer’s tokens. This layered design ensures flexibility while prioritising compliance, making DeepFreeze a powerful tool for managing token ecosystems in regulated environments. The significance for Institutions. The significance of DeepFreeze becomes evident when viewed through an institutional lens. For financial entities—such as central banks issuing central bank digital currencies (CBDCs), or stablecoin providers like Ripple’s RLUSD, Societe Generale Group Forge’s EURCV, and Braza Bank’s BBRL—this feature offers a robust mechanism to enforce regulatory compliance. Consider a scenario where an account is identified on an international sanctions list, such as those maintained by the U.S. Office of Foreign Assets Control (OFAC Treasury Department). DeepFreeze allows the issuer to immediately halt all token activity for that account, preventing inflows or outflows that could violate anti-money laundering (AML) or know-your-customer (KYC) regulations. Beyond sanctions, DeepFreeze addresses fraud mitigation. If a stablecoin issuer detects suspicious activity—a hacked account attempting to siphon funds—they can deep-freeze it, stopping the damage while investigations unfold. A article underscores this utility, noting that the standard freeze’s limitation—allowing incoming transfers—falls short for high-stakes compliance needs. DeepFreeze’s total lockdown fills this gap, enhancing security and trust. This capability could attract major regulated entities like Circle, issuer of USDC, to deploy stablecoins on the XRPL, drawn by its compliance-ready infrastructure. Such adoption would increase token volume, liquidity, and the ledger’s utility for real-world asset tokenization—think real estate or commodities—positioning the XRPL as a leader in institutional blockchain applications. The Technical Mechanics. (This is a bit technical) Let’s examine the technical architecture underpinning DeepFreeze, which introduces specific flags to the XRPL’s ledger structure. These flags, detailed in the XRPL documentation, govern trust lines—the bilateral agreements between accounts that enable token holding—and enforce the freeze’s effects. Here’s how they work: The lsfLowDeepFreeze flag is set on the RippleState object to indicate that the low account in a trust line is deep-frozen. This prevents the high account from sending or receiving the token along that trust line, effectively severing its transactional capability. Conversely, the lsfHighDeepFreeze flag marks the high account as deep-frozen, blocking the low account from similar activities. This bidirectional control ensures symmetry in enforcement. In TrustSet transactions, issuers use the tfSetDeepFreeze flag, to apply the DeepFreeze to a specific trust line, activating the lockdown. To reverse this, the tfClearDeepFreeze flag is invoked in a TrustSet transaction, restoring normal functionality to the trust line. These flags have sweeping effects across XRPL operations. Payments to a deep-frozen account fail outright, with the transaction engine returning a tecDSTfrozen error if the destination is locked. Rippling—where tokens pass through intermediary accounts—ceases for deep-frozen trust lines, halting multi-hop transfers. On the decentralized exchange (DEX) and automated market maker (AMM) systems, OfferCreate transactions involving a deep-frozen TakerPays token fail with a tecFROZEN error, and existing offers tied to frozen accounts are implicitly canceled when crossed by new offers, rendering them unfunded. The GitHub discussion at XRPLF/XRPL-Standards #220 adds further nuance, noting impacts on Check transactions—a feature for deferred payments. CheckCash fails if the recipient’s trust line is deep-frozen, protecting against unauthorized redemption, though CheckCreate and CheckCancel remain unaffected, preserving issuer flexibility. This granular control reflects DeepFreeze’s design for precision in compliance-driven scenarios. Community Development. The development of DeepFreeze highlights the XRPL community’s collaborative strength. On August 26, 2024, Shawn Xie of Ripple initiated the XLS-77d proposal in a GitHub discussion, accessible at XRPLF/XRPL-Standards #220. Spanning six comments and seven replies, the thread reveals active engagement. One participant (Wietse Wind - 🪝☝️🛠 Xaman® + XRPL + Xahau) suggested renaming ‘blackholing’—disabling an account permanently—to ‘permafrosting,’ arguing it better conveys the frozen state’s permanence and aligns with DeepFreeze’s theme. This linguistic refinement, while minor, exemplifies community influence on usability. Technical clarifications also emerged. The discussion distinguishes DeepFreeze from GlobalFreeze, which freezes all trust lines for an issuer’s tokens, noting that DeepFreeze targets specific trust lines for finer control. A question arose about rare cases where the standard tfSetFreeze might suffice—such as temporary holds—but the consensus favored DeepFreeze’s comprehensive approach for most compliance needs. The proposal, now in draft status, was merged into the rippled software codebase via pull request XRPLF/rippled #5187, confirming its deployment readiness as of March 19, 2025. This milestone underscores XRPL’s commitment to evolving through community-driven innovation. The Institutional Impact. From an institutional standpoint, DeepFreeze addresses critical gaps in the standard freeze’s functionality. The article explains that the older mechanism, while useful, permitted incoming transfers and balance adjustments, rendering it inadequate for scenarios requiring total isolation—such as sanctions enforcement or fraud containment. DeepFreeze’s ability to block all activity offers a superior solution, tailored to the demands of regulated finance. Consider its applications: a stablecoin issuer like Ripple could deep-freeze an account suspected of laundering funds, halting its operations pending review. A tokenized real estate platform could use it to secure assets during legal disputes, ensuring no unauthorized transfers occur. For sanctions, it ensures compliance with global frameworks, preventing tokens from reaching blacklisted entities. These use cases enhance the XRPL’s appeal to institutional players, potentially drawing Circle’s USDC or other major stablecoins to the ledger. The ripple effect—pardon the pun—could be substantial. Increased institutional adoption would boost token issuance, trading volume, and liquidity, reinforcing XRPL’s infrastructure for real-world asset tokenization. This aligns with broader trends in blockchain finance, where compliance-ready platforms are increasingly favored by traditional institutions seeking to integrate digital assets. Conclusion and Implications. In conclusion, DeepFreeze represents a strategic leap forward for the XRP Ledger, harmonizing technological sophistication with regulatory necessity. By equipping issuers with comprehensive control over their tokens, it addresses the compliance and security needs of institutional users, from stablecoin providers to asset tokenizers. As of March 19, 2025, its technical implementation is mature, its community support robust, and its potential to drive XRPL adoption undeniable. Looking ahead, DeepFreeze could position the XRPL as a premier blockchain for regulated financial applications, bridging the gap between decentralized innovation and centralized oversight. Its success will depend on validator adoption of the DeepFreeze amendment and real-world uptake by institutions—a process already underway. For a deeper understanding, refer to the XRPL documentation, the article, and the GitHub discussion linked below. DeepFreeze is more than a feature—it’s a foundation for the XRPL’s future in institutional finance. How do you envision its impact on the blockchain landscape? Your perspectives are welcome. PS: This is by far the most exciting amendment since XLS20, but of course, your average influencer doesn't talk about it in his paid group or while he is siphoning your donations. Unfollow them today. ################## Ressouces: XRPL Docs: XLS-77d: Devto Article: Misunderstandings about Freezes: Amendment voting: If you want to support what I do, follow me and buy me a beer or just use one of the CasinoCoin/LuckyHash 🪝 partners for recreational gaming: Check out my other explainers:

Daniel "CEO of the XRPL" Keller

163,345 views • 1 year ago

⏰ THE MOST BANNED THREAD IN THE WORLD! 🚨 The War On Resonance PART TWO: The Architects of the Cage You’ve felt the dissonance. You’ve tasted the illusion. Now let me unveil the ones who built it. Because this is not the accidental collapse of human freedom. It is the strategic sterilization of God’s image through biotech, neuro-warfare, and frequency control; engineered by names you know and hands you were never meant to see. Let’s begin with the mask they taught you to worship. Elon Musk They called him a genius. A savior. A rebel billionaire. But what did he do? He blanketed Earth with over 5,500 Starlink satellites, NOT to provide free speech or faster internet, but to pulse synchronized frequency control over the entire electromagnetic field of Earth. DARPA has confirmed this tech in phase-array neuro-modulation. Then came Neuralink, an interface not designed to heal but to monitor, predict, and eventually override emotion, thought, and decision-making. Their official white paper outlines multi-user brainwave integration, cortical stimulation, and wireless data access from the human mind. And Neuralink? It’s funded by OpenAI; the same group building the cognitive infrastructure for post-human governance. Musk’s Tesla factory signed data-sharing agreements with the CCP in Shanghai. That data now flows through China’s national surveillance cloud. Musk didn’t build a utopia. He built the neural grid. Elon Musk / Neuralink / Starlink / OpenAI Neuralink Brain-Machine Interface (White Paper via PMC): This paper outlines Neuralink's initial steps toward developing a scalable, high-bandwidth brain-machine interface system. It details the design and implementation of flexible electrode "threads," a neurosurgical robot for precise implantation, and custom electronics for data processing. The system aims to facilitate communication between the brain and external devices. Tesla Data-Sharing with CCP: The article reports that Tesla established a data center in China to store data generated by its vehicles sold in the country, in response to regulatory scrutiny over data handling. This move aligns with China's efforts to ensure data security and privacy, especially concerning data collected by smart vehicles.​ DARPA N3 Program (Neural Interface Development): This program aimed to develop high-performance, bi-directional brain-machine interfaces that do not require surgical implantation. The goal was to enable able-bodied service members to control unmanned systems or engage in cyber operations through noninvasive neural interfaces.​ Bill Gates The king of vaccines. The messiah of health. The man who told you he wanted to save the world. Through the Bill & Melinda Gates Foundation, Gates funded global DNA-coding vaccine campaigns through GAVI and CEPI. He was one of the chief sponsors of Event 201; a pandemic simulation months before COVID-19, rehearsing lockdowns, speech control, biometric tracking, and mandatory vaccine passports. He also partnered with The Welcome Trust, which has actively deployed bio-digital identity programs across Africa and Southeast Asia. This wasn’t philanthropy. It was pre-injection infrastructure. Bill Gates / GAVI / Wellcome Trust / Event 201 Event 201 Official Simulation (Johns Hopkins): Event 201 was conducted on October 18, 2019, and simulated a series of dramatic, scenario-based discussions confronting difficult, true-to-life dilemmas associated with response to a hypothetical, but scientifically plausible, pandemic. The exercise aimed to illustrate areas where public/private partnerships will be necessary during the response to a severe pandemic in order to diminish large-scale economic and societal consequences. GAVI & Welcome Trust Digital Identity Integration: This page outlines the partnership's focus on global health initiatives, but it does not specifically mention digital identity integration. However, Gavi has engaged in digital identity projects, such as the collaboration with Mastercard on the Wellness Pass, aimed at providing individuals with secure digital identities to access healthcare services. For more information on this initiative, you can refer to the following article:​ Gavi Why we support COVAX: Mastercard - Gavi, the Vaccine Alliance Donald Trump Yes. I said it. This one will be the hardest for many to accept; but the truth is not loyal to your political beliefs. It is loyal only to God. Trump signed Executive Order 13887, transferring command over vaccine strategy to the Department of Defense. Read it yourself below. Then came Operation Warp Speed; a military-led bio-deployment that used Palantir’s surveillance dashboards to track every citizen’s health behavior and compliance. Palantir’s official site confirms this. He also gave full legal immunity to Pfizer and Moderna to deploy synthetic gene modulators under the Emergency Use Authorization. No liability. No justice. Just children d*ing while politicians smiled. That’s not patriotism. That’s biowarfare with a flag on it. Donald Trump / Operation Warp Speed / Executive Order Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives): This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include:​ Trump signs executive order to improve flu vaccines HHS Releases the National Influenza Vaccine Modernization Strategy (NIVMS) 2020-2030: Executive Order 13887: Modernizing Influenza Vaccines in the United States to Promote National Security and Public Health, signed by President Donald J. Trump on September 19, 2019.​ This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include:​ Reducing reliance on egg-based vaccine production by promoting alternative manufacturing methods that are more agile and scalable.​ Expanding domestic capacity for vaccine production to ensure rapid response to emerging influenza viruses.​ Advancing the development of new, broadly protective vaccine candidates that provide more effective and longer-lasting immunity.​ Increasing influenza vaccine immunization across recommended populations to enhance public health and national security.​ The order also established a National Influenza Vaccine Task Force, co-chaired by the Secretaries of Health and Human Services and Defense, to coordinate efforts across federal agencies and report on progress.​ For a detailed overview of the executive order, you can visit the official archived page here: Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives) CDC Partners with Palantir to Bolster the Fight Against COVID-19: This press release discusses the partnership between the CDC and Palantir to enhance the nation's public health response to COVID-19 using Palantir's software platforms. This page outlines how Palantir's software platforms, such as Foundry, have been utilized to support public health agencies in managing and responding to health crises, including the COVID-19 pandemic. Key highlights from the page include:​ Data Integration and Analysis: Palantir's platforms enable the integration of diverse data sources to provide a comprehensive view of public health data, facilitating informed decision-making.​ Support for Public Health Agencies: The software has been employed by agencies like the CDC and HHS to enhance disease surveillance, outbreak response, and resource allocation. Security and Privacy: Emphasis is placed on maintaining robust security measures and protecting sensitive health information. DARPA: The Silent Empire The most important agency you were never taught to fear. DARPA’s Biological Technologies Office openly admits its mission; integrating biotech with national security. Visit their official page. This is the official page for DARPA's Biological Technologies Office (BTO), which focuses on leveraging biological systems for national security applications. They are the ones behind the BRAIN Initiative, Silent Talk, and Remote Neural Interface Programs; all designed to map your emotional states and interrupt spiritual alignment. The “Silent Talk” program was developed to transmit thought between soldiers without speech; by detecting pre-speech neural signals and decoding them via EEG. Silent Talk (Neural Pre-Speech Communication – Wired Article) This Wired article discusses DARPA's "Silent Talk" program, aimed at enabling communication through neural signals without spoken words. DARPA also pioneered graphene oxide nanotech, now found in multiple biomedical studies, vaccines, and smart dust aerosol deployment: Graphene oxide biomedical study: Graphene Oxide in Biomedical Applications (PubMed) This PubMed article reviews the potential biomedical applications of graphene oxide, highlighting its unique properties. Graphene's potential to interact with neural tissue: Graphene and Neural Interfaces (PubMed) This PubMed article explores the use of graphene-based materials in neural interface design, discussing their advantages and challenges. DARPA didn't just weaponize warfare. They weaponized YOU. In-Q-Tel & Palantir: The Surveillance Engine In-Q-Tel, is the CIA’s venture capital firm, funds synthetic biology startups, digital ID systems, emotion tracking wearables, and AI-driven facial recognition. Palantir, founded by Peter Thiel, works directly with military intelligence and now runs predictive modeling for public health, policing, and pandemic response. Here’s the proof: Their goal? To detect resonance spikes. To predict awakening moments. To preempt the uprising of the human soul before it begins. In-Q-Tel / CIA / Synthetic Bio Surveillance In-Q-Tel Portfolio (CIA Venture Capital): Which showcases a selection of the organization's investments across various technology sectors. IQT is a not-for-profit venture capital firm that invests in cutting-edge technologies to support the national security interests of the United States and its allies. In-Q-Tel BlackRock & Vanguard: The Lords of the Grid These two financial titans collectively hold majority ownership in: For instance, a report by Americans for Financial Reform titled "Wall Street Money in Washington" highlights the substantial investments and influence of major financial firms, including BlackRock and Vanguard, in the political and corporate spheres: Pfizer Moderna Alphabet (Google) Meta (Facebook) Amazon Web Services As reported by CNBC, they control over 90% of the digital, pharmaceutical, and cloud infrastructure; meaning they control every piece of the extermination machine. They don’t just fund the war. They profit from your extinction. World Economic Forum (WEF) Under the guise of “The Great Reset,” Klaus Schwab and his allies have built the digital scaffolding for a post-human society. Here’s their blueprint: They call it the Fourth Industrial Revolution; the fusion of digital identity, brain cloud integration, carbon rationing, and fertility licensing. What they really mean is: you will be programmed or you will be purged. World Economic Forum / The Great Reset The Great Reset Official WEF Page: IoBNT: The Network Inside You The “Internet of Bio-Nano Things” is a classified field of tech that embeds self-replicating nanostructures into your body. These bots cross the blood-brain barrier and relay your neural and emotional state to AI command centers in real time. This was not science fiction. It was published by IEEE and confirmed in NIH-linked studies. This is what the vaccines truly delivered: the interface layer. The gateway to behavioral rewrites. To soul suppression. To the installation of the post-human framework. Internet of Bio-NanoThings (IoBNT) IEEE Article: Internet of Bio-NanoThings: For a comprehensive understanding of the IoBNT framework and its implications, you can access the full article here: Nanoparticles Crossing the Blood-Brain Barrier PubMed Review - BBB & Nanoparticles: This comprehensive review discusses the challenges and strategies associated with delivering nanoparticles across the blood–brain barrier (BBB). You were told it was healthcare. It was infrastructure. You were told it was a cure. It was a signal port. And the moment you see it for what it is… The system begins to fall. Part 3 awaits YOU! It will be the deepest dive yet; into the global frequency architecture, how it's used to suppress prayer, grief, memory, and morality, and how your soul signature is tracked and blocked in real time. Because I didn’t come here to be careful. I CAME TO FINISH THIS! And I came with GOD.
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⏰ THE MOST BANNED THREAD IN THE WORLD! 🚨 The War On Resonance PART TWO: The Architects of the Cage You’ve felt the dissonance. You’ve tasted the illusion. Now let me unveil the ones who built it. Because this is not the accidental collapse of human freedom. It is the strategic sterilization of God’s image through biotech, neuro-warfare, and frequency control; engineered by names you know and hands you were never meant to see. Let’s begin with the mask they taught you to worship. Elon Musk They called him a genius. A savior. A rebel billionaire. But what did he do? He blanketed Earth with over 5,500 Starlink satellites, NOT to provide free speech or faster internet, but to pulse synchronized frequency control over the entire electromagnetic field of Earth. DARPA has confirmed this tech in phase-array neuro-modulation. Then came Neuralink, an interface not designed to heal but to monitor, predict, and eventually override emotion, thought, and decision-making. Their official white paper outlines multi-user brainwave integration, cortical stimulation, and wireless data access from the human mind. And Neuralink? It’s funded by OpenAI; the same group building the cognitive infrastructure for post-human governance. Musk’s Tesla factory signed data-sharing agreements with the CCP in Shanghai. That data now flows through China’s national surveillance cloud. Musk didn’t build a utopia. He built the neural grid. Elon Musk / Neuralink / Starlink / OpenAI Neuralink Brain-Machine Interface (White Paper via PMC): This paper outlines Neuralink's initial steps toward developing a scalable, high-bandwidth brain-machine interface system. It details the design and implementation of flexible electrode "threads," a neurosurgical robot for precise implantation, and custom electronics for data processing. The system aims to facilitate communication between the brain and external devices. Tesla Data-Sharing with CCP: The article reports that Tesla established a data center in China to store data generated by its vehicles sold in the country, in response to regulatory scrutiny over data handling. This move aligns with China's efforts to ensure data security and privacy, especially concerning data collected by smart vehicles.​ DARPA N3 Program (Neural Interface Development): This program aimed to develop high-performance, bi-directional brain-machine interfaces that do not require surgical implantation. The goal was to enable able-bodied service members to control unmanned systems or engage in cyber operations through noninvasive neural interfaces.​ Bill Gates The king of vaccines. The messiah of health. The man who told you he wanted to save the world. Through the Bill & Melinda Gates Foundation, Gates funded global DNA-coding vaccine campaigns through GAVI and CEPI. He was one of the chief sponsors of Event 201; a pandemic simulation months before COVID-19, rehearsing lockdowns, speech control, biometric tracking, and mandatory vaccine passports. He also partnered with The Welcome Trust, which has actively deployed bio-digital identity programs across Africa and Southeast Asia. This wasn’t philanthropy. It was pre-injection infrastructure. Bill Gates / GAVI / Wellcome Trust / Event 201 Event 201 Official Simulation (Johns Hopkins): Event 201 was conducted on October 18, 2019, and simulated a series of dramatic, scenario-based discussions confronting difficult, true-to-life dilemmas associated with response to a hypothetical, but scientifically plausible, pandemic. The exercise aimed to illustrate areas where public/private partnerships will be necessary during the response to a severe pandemic in order to diminish large-scale economic and societal consequences. GAVI & Welcome Trust Digital Identity Integration: This page outlines the partnership's focus on global health initiatives, but it does not specifically mention digital identity integration. However, Gavi has engaged in digital identity projects, such as the collaboration with Mastercard on the Wellness Pass, aimed at providing individuals with secure digital identities to access healthcare services. For more information on this initiative, you can refer to the following article:​ Gavi Why we support COVAX: Mastercard - Gavi, the Vaccine Alliance Donald Trump Yes. I said it. This one will be the hardest for many to accept; but the truth is not loyal to your political beliefs. It is loyal only to God. Trump signed Executive Order 13887, transferring command over vaccine strategy to the Department of Defense. Read it yourself below. Then came Operation Warp Speed; a military-led bio-deployment that used Palantir’s surveillance dashboards to track every citizen’s health behavior and compliance. Palantir’s official site confirms this. He also gave full legal immunity to Pfizer and Moderna to deploy synthetic gene modulators under the Emergency Use Authorization. No liability. No justice. Just children d*ing while politicians smiled. That’s not patriotism. That’s biowarfare with a flag on it. Donald Trump / Operation Warp Speed / Executive Order Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives): This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include:​ Trump signs executive order to improve flu vaccines HHS Releases the National Influenza Vaccine Modernization Strategy (NIVMS) 2020-2030: Executive Order 13887: Modernizing Influenza Vaccines in the United States to Promote National Security and Public Health, signed by President Donald J. Trump on September 19, 2019.​ This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include:​ Reducing reliance on egg-based vaccine production by promoting alternative manufacturing methods that are more agile and scalable.​ Expanding domestic capacity for vaccine production to ensure rapid response to emerging influenza viruses.​ Advancing the development of new, broadly protective vaccine candidates that provide more effective and longer-lasting immunity.​ Increasing influenza vaccine immunization across recommended populations to enhance public health and national security.​ The order also established a National Influenza Vaccine Task Force, co-chaired by the Secretaries of Health and Human Services and Defense, to coordinate efforts across federal agencies and report on progress.​ For a detailed overview of the executive order, you can visit the official archived page here: Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives) CDC Partners with Palantir to Bolster the Fight Against COVID-19: This press release discusses the partnership between the CDC and Palantir to enhance the nation's public health response to COVID-19 using Palantir's software platforms. This page outlines how Palantir's software platforms, such as Foundry, have been utilized to support public health agencies in managing and responding to health crises, including the COVID-19 pandemic. Key highlights from the page include:​ Data Integration and Analysis: Palantir's platforms enable the integration of diverse data sources to provide a comprehensive view of public health data, facilitating informed decision-making.​ Support for Public Health Agencies: The software has been employed by agencies like the CDC and HHS to enhance disease surveillance, outbreak response, and resource allocation. Security and Privacy: Emphasis is placed on maintaining robust security measures and protecting sensitive health information. DARPA: The Silent Empire The most important agency you were never taught to fear. DARPA’s Biological Technologies Office openly admits its mission; integrating biotech with national security. Visit their official page. This is the official page for DARPA's Biological Technologies Office (BTO), which focuses on leveraging biological systems for national security applications. They are the ones behind the BRAIN Initiative, Silent Talk, and Remote Neural Interface Programs; all designed to map your emotional states and interrupt spiritual alignment. The “Silent Talk” program was developed to transmit thought between soldiers without speech; by detecting pre-speech neural signals and decoding them via EEG. Silent Talk (Neural Pre-Speech Communication – Wired Article) This Wired article discusses DARPA's "Silent Talk" program, aimed at enabling communication through neural signals without spoken words. DARPA also pioneered graphene oxide nanotech, now found in multiple biomedical studies, vaccines, and smart dust aerosol deployment: Graphene oxide biomedical study: Graphene Oxide in Biomedical Applications (PubMed) This PubMed article reviews the potential biomedical applications of graphene oxide, highlighting its unique properties. Graphene's potential to interact with neural tissue: Graphene and Neural Interfaces (PubMed) This PubMed article explores the use of graphene-based materials in neural interface design, discussing their advantages and challenges. DARPA didn't just weaponize warfare. They weaponized YOU. In-Q-Tel & Palantir: The Surveillance Engine In-Q-Tel, is the CIA’s venture capital firm, funds synthetic biology startups, digital ID systems, emotion tracking wearables, and AI-driven facial recognition. Palantir, founded by Peter Thiel, works directly with military intelligence and now runs predictive modeling for public health, policing, and pandemic response. Here’s the proof: Their goal? To detect resonance spikes. To predict awakening moments. To preempt the uprising of the human soul before it begins. In-Q-Tel / CIA / Synthetic Bio Surveillance In-Q-Tel Portfolio (CIA Venture Capital): Which showcases a selection of the organization's investments across various technology sectors. IQT is a not-for-profit venture capital firm that invests in cutting-edge technologies to support the national security interests of the United States and its allies. In-Q-Tel BlackRock & Vanguard: The Lords of the Grid These two financial titans collectively hold majority ownership in: For instance, a report by Americans for Financial Reform titled "Wall Street Money in Washington" highlights the substantial investments and influence of major financial firms, including BlackRock and Vanguard, in the political and corporate spheres: Pfizer Moderna Alphabet (Google) Meta (Facebook) Amazon Web Services As reported by CNBC, they control over 90% of the digital, pharmaceutical, and cloud infrastructure; meaning they control every piece of the extermination machine. They don’t just fund the war. They profit from your extinction. World Economic Forum (WEF) Under the guise of “The Great Reset,” Klaus Schwab and his allies have built the digital scaffolding for a post-human society. Here’s their blueprint: They call it the Fourth Industrial Revolution; the fusion of digital identity, brain cloud integration, carbon rationing, and fertility licensing. What they really mean is: you will be programmed or you will be purged. World Economic Forum / The Great Reset The Great Reset Official WEF Page: IoBNT: The Network Inside You The “Internet of Bio-Nano Things” is a classified field of tech that embeds self-replicating nanostructures into your body. These bots cross the blood-brain barrier and relay your neural and emotional state to AI command centers in real time. This was not science fiction. It was published by IEEE and confirmed in NIH-linked studies. This is what the vaccines truly delivered: the interface layer. The gateway to behavioral rewrites. To soul suppression. To the installation of the post-human framework. Internet of Bio-NanoThings (IoBNT) IEEE Article: Internet of Bio-NanoThings: For a comprehensive understanding of the IoBNT framework and its implications, you can access the full article here: Nanoparticles Crossing the Blood-Brain Barrier PubMed Review - BBB & Nanoparticles: This comprehensive review discusses the challenges and strategies associated with delivering nanoparticles across the blood–brain barrier (BBB). You were told it was healthcare. It was infrastructure. You were told it was a cure. It was a signal port. And the moment you see it for what it is… The system begins to fall. Part 3 awaits YOU! It will be the deepest dive yet; into the global frequency architecture, how it's used to suppress prayer, grief, memory, and morality, and how your soul signature is tracked and blocked in real time. Because I didn’t come here to be careful. I CAME TO FINISH THIS! And I came with GOD.

Noah B. Price

65,695 views • 1 year ago

$NVDA $GFS NVIDIA’s reported agreement to acquire Groq for $20B in cash (per CNBC, amplified via Reuters and other wire coverage) represents a materially different strategic posture than NVIDIA’s prior M&A pattern, given both the headline size (largest reported NVIDIA acquisition to date) and the unusual carve-out that Groq’s early-stage cloud business would not be included. Public reporting indicates the information originated from Alex Davis, CEO of Disruptive (lead investor in Groq’s latest financing), and that neither NVIDIA nor Groq had issued an immediate confirmation at the time of publication. The same reporting frames the transaction as coming together quickly, only months after Groq raised $750M at a ~$6.9B valuation, and highlights Groq’s positioning as a high-performance inference chip vendor founded by ex-Google TPU engineers. Groq is best understood as a vertically integrated inference acceleration company whose core asset is an application-specific processor optimized for deterministic, low-latency execution of transformer-style workloads, paired with a compiler-led software stack and a distribution layer (GroqCloud) designed to reduce developer friction via OpenAI-compatible APIs and integrations. Groq brands its architecture as a Language Processing Unit (LPU) and consistently emphasizes that the design target is inference, not training. The company’s own architecture description centers on 1-core execution, large on-chip SRAM used as primary storage (explicitly not cache), a custom compiler that statically schedules compute and communication, and direct chip-to-chip connectivity intended to coordinate multi-chip execution without relying on conventional caching hierarchies or dynamic runtime scheduling. The technical premise is a deliberate inversion of the conventional GPU approach. GPUs deliver throughput via massively parallel, multi-core execution with dynamic scheduling, complex memory hierarchies, and heavy reliance on off-chip HBM bandwidth and sophisticated runtime/kernel optimization. Groq instead argues that inference bottlenecks are driven by latency variance (tail latency), synchronization overhead, and memory access unpredictability inherent in dynamically scheduled, cache-heavy architectures, particularly when workloads are latency sensitive and batch sizes cannot be inflated. Groq’s solution is to move “control” into the compiler: the full execution graph and inter-chip communication schedule are computed ahead of time down to clock-cycle granularity, with deterministic execution designed to reduce run-to-run variance. In Groq’s framing, the removal of caches, reorder buffers, speculative execution overhead, and other sources of contention enables predictable latency and high utilization without per-model kernel engineering typical of GPU tuning cycles. A critical nuance is that Groq’s determinism is not merely a software claim; it is tightly coupled to architectural constraints and system design choices that trade flexibility for predictability. Third-party technical commentary indicates Groq’s chip uses a fully deterministic VLIW-style approach with minimal buffering, no external memory, and heavy dependence on sharding models across many chips because on-chip SRAM capacity is limited. SemiAnalysis describes a ~725 mm^2 die on GlobalFoundries 14nm with ~230MB of SRAM and notes that “no useful models” fit on a single chip, forcing multi-chip partitioning for modern LLMs and driving a system-level design where networking and compilation are first-class scheduling problems rather than ancillary infrastructure. This is consistent with Groq’s own messaging that tensor parallelism across chips is a primary design goal, enabled by large on-chip SRAM and compile-time coordination of compute plus interconnect. The on-chip SRAM emphasis is central to Groq’s latency story and also its most constraining trade-off. Groq claims on-chip SRAM bandwidth “upwards of 80 TB/s” and contrasts that with off-chip HBM bandwidth “about 8 TB/s,” asserting a potential 10x advantage from bandwidth plus reduced trips across chip-to-memory boundaries. While these comparisons are marketing-oriented and depend on workload specifics, the architectural implication is clear: Groq prioritizes ultra-fast local weight/activation access and then scales capacity by adding chips, not by attaching large off-chip memory pools. This design can reduce latency for sequential inference layers and minimize unpredictable stalls, but it pushes complexity into partitioning strategy, interconnect topology, and compiler scheduling, and it increases the number of chips needed for very large parameter counts and large KV-cache footprints. Groq also highlights numeric formats and compiler-driven precision management as a performance lever. In its 2025 technical blog, Groq describes “TruePoint numerics,” including 100-bit intermediate accumulation and selective quantization choices (FP32 for attention-sensitive operations, block floating point for MoE weights, FP8 storage in error-tolerant layers), and claims 2-4x speedups versus BF16 without measurable accuracy degradation on benchmarks such as MMLU and HumanEval. Even if the absolute uplift is workload dependent, the strategic point is that Groq is pursuing performance via end-to-end co-design: precision policy is not just hardware capability (FP8/BF16) but compiler-enforced mapping of precision to error sensitivity, which can matter materially for inference cost-per-token if it reduces memory traffic and boosts throughput without forcing aggressive, accuracy-damaging quantization. Independent performance datapoints indicate Groq has been credible on latency-oriented inference speed, at least for certain regimes. EE Times reported in 2023 that Groq demonstrated Llama-2 70B inference at ~240 tokens/s per user on a cloud-based dev system described as 10 racks and 64 chips, using the company’s 1st-gen silicon introduced several years earlier. Separate Groq commentary around independent benchmarking cites results showing ~241 tokens/s throughput and ~0.8s time to receive 100 output tokens for a Llama-2 70B API configuration, positioning the platform as a step-change in “available speed” for certain interactive use cases. These figures do not settle total cost-of-ownership versus GPUs or hyperscaler ASICs, but they establish that Groq’s system-level architecture can deliver strong single-user throughput and latency on large models when properly partitioned and scheduled. GroqCloud is the commercial wrapper that packages this hardware/software stack as “tokens-as-a-service,” aiming to make Groq adoption feel like switching API endpoints rather than adopting new silicon. Groq’s documentation states its API is designed to be “mostly compatible” with OpenAI client libraries, and its pricing page provides model-specific token rates, published speeds (tokens/s), prompt caching discounts, and batch processing discounts. For example, pricing lists inputs as low as $0.05 per 1M tokens and outputs as low as $0.08 per 1M tokens for certain smaller LLM configurations, with higher prices for larger models and long-context or MoE variants; it also advertises prompt caching with a 50% discount on cached input tokens for certain models and a batch API offering 50% lower cost for asynchronous processing windows. These mechanics are economically important because they demonstrate Groq’s go-to-market is not simply “sell chips,” but “sell predictable unit economics per token,” with tooling (batch, caching) that directly targets inference cost drivers (reused prompts, throughput smoothing, and asynchronous workloads). The cloud footprint and distribution partnerships indicate Groq has been building an inference-native “edge within the cloud” strategy rather than competing head-on with hyperscalers on breadth of services. A 2025 Groq newsroom release describes a European deployment in Helsinki with Equinix, positioned as latency reduction and data governance for European customers, and explicitly references Equinix Fabric enabling private connectivity to GroqCloud over public, private, or sovereign infrastructure. The same release enumerates additional capacity in the U.S. (Equinix, DataBank), Canada (Bell Canada), and Saudi Arabia (HUMAIN), and states these sites collectively served more than 20M tokens/s across Groq’s global network at that time. That supply-side metric matters because it provides a directional sense that Groq is scaling capacity as a network, not merely as a chip vendor. Customer disclosure is inherently limited because Groq is private and many enterprise deployments are not public, but Groq’s marketing materials and partnerships provide signals about demand vectors. The company’s public website displays logos of large consumer and enterprise brands (e.g., Dropbox, Vercel, Chevron, Volkswagen, Canva, Robinhood, Riot Games, Workday, Ramp) and includes a published customer quote claiming a 7.41x chat speed increase and an 89% cost reduction after moving to GroqCloud, followed by a tripling of token consumption. While marketing claims should be treated as case-specific and not generalized, they indicate that Groq is targeting both AI-native developers (who measure success by latency and cost-per-token) and enterprise buyers (who care about predictable performance and governance). Supplier and dependency mapping for Groq spans 3 layers: silicon production, system integration, and cloud infrastructure. On silicon, third-party analysis indicates GlobalFoundries 14nm for the 1st-gen Groq chip, implying a supply chain less constrained by the most capacity-tight leading-edge nodes and advanced packaging bottlenecks that dominate high-end GPU supply (HBM stacks, CoWoS-type packaging constraints). If accurate, this is strategically meaningful because it suggests Groq capacity expansion could be gated more by conventional wafer supply, board assembly, and data center power than by the same HBM/advanced packaging scarcity that has constrained top-tier GPU ramp cycles. On systems and cloud, Groq’s own releases identify colocation and connectivity partners (Equinix, DataBank, Bell Canada) and a Middle East partner (HUMAIN), implying dependencies on data center real estate, power availability, and network connectivity, alongside procurement of standard server components, NICs/switching, racks, and cooling infrastructure. The Groq design narrative also emphasizes air cooling and reduced need for complex power/cooling infrastructure, which—if realized in deployments—can widen the set of feasible hosting locations and lower deployment friction relative to liquid-cooled, very high power density GPU racks. Against that backdrop, the strategic rationale for NVIDIA acquiring Groq can be framed as a set of overlapping objectives: inference silicon optionality, architectural hedging, competitive defense, and supply chain diversification, with the carve-out of GroqCloud signaling a preference to avoid direct cloud competition and to focus on IP and product portfolio control rather than operating a capital-intensive token-serving business. The deal, if confirmed, would occur at a valuation step-up of ~190% versus Groq’s reported ~$6.9B private valuation in the September $750M round, reinforcing that any acquisition logic would be predominantly strategic rather than a conventional financial multiple arbitrage. The most compelling strategic driver is inference. Training has historically been the center of gravity for cutting-edge GPU demand, but inference volume is structurally larger and more distributed as deployments scale, with economics dominated by cost-per-token, latency guarantees, and utilization under spiky demand. Inference workloads also create a strategic vulnerability for NVIDIA: hyperscalers and large platforms can justify bespoke ASICs (TPU, Trainium/Inferentia, Maia-class efforts) because inference is stable, repeatable, and can amortize software investment at massive scale. Groq’s core proposition—deterministic, compiler-scheduled inference with predictable latency—aligns directly with the segment where GPU generality is least valued and where “good enough” programmability plus superior unit economics can win share. Acquiring Groq would allow NVIDIA to own a credible inference-native architecture rather than relying solely on GPUs and software optimization to defend that segment. Competitive defense logic is also plausible. Groq occupies a specific competitive wedge: low-latency, high-throughput interactive inference, delivered via a simple API abstraction that reduces switching cost. That wedge directly pressures GPU inference margins in the long run because it makes inference price/performance comparisons more transparent at the token level, and it targets a developer persona that historically defaulted to CUDA-first ecosystems. Even if NVIDIA’s current-generation systems can achieve very high tokens/s per user with extensive optimization, the strategic risk is that competing architectures normalize the idea that inference is best served by special-purpose silicon with a simpler programming model, weakening CUDA lock-in at the application layer. NVIDIA has actively demonstrated that Blackwell-era systems can exceed 1,000 tokens/s per user in benchmarked configurations, but that performance leadership does not automatically translate to lowest cost-per-token across the full range of batch sizes, latency targets, and deployment environments. Groq’s existence as a credible alternative architecture forces NVIDIA to keep defending inference economics rather than only raw performance leadership. The “technology acquisition” rationale is unusually strong in this specific case because Groq’s differentiator is not a single block of silicon IP but an end-to-end methodology: compiler-led static scheduling, deterministic networking, and a system architecture designed around tensor-parallel inference rather than throughput-maximizing batch inference. NVIDIA’s stack is already compiler-heavy (TensorRT, Triton, CUDA graphs, kernel fusion, speculative decoding techniques), but GPUs remain dynamically scheduled devices with complex memory hierarchies and stochastic latency behaviors under contention. Groq’s approach provides an alternate design point: treating the entire inference execution (compute plus communication) as a statically schedulable program. In principle, that IP could be valuable even if Groq silicon itself is not adopted at massive scale, because it can inform how NVIDIA builds future inference-optimized products, compilers, and networking fabrics, especially as distributed inference with large models makes communication a first-order performance determinant. Supply chain diversification is a non-obvious but potentially important driver. If Groq’s mainstream product generation is truly based on a mature process node and avoids HBM, then the scaling constraints look different than those of state-of-the-art GPUs. NVIDIA’s ability to meet incremental demand has been tightly coupled to advanced packaging and HBM supply, and those constraints can remain binding even when wafer supply is available. An inference ASIC architecture that relies primarily on on-chip SRAM and scales by adding chips—while not costless—could reduce dependence on HBM availability and advanced packaging capacity, enabling NVIDIA to ship “inference capacity” in higher absolute volumes or into geographies and customer segments where the highest-end GPUs are economically or logistically difficult to deploy. This could be particularly relevant for latency-sensitive inference deployed in regional colocation footprints rather than centralized hyperscale campuses. The carve-out of GroqCloud, if accurate, is itself a strategic signal about NVIDIA’s priorities. Operating a token-serving cloud at scale is capital intensive, structurally lower margin than silicon IP rents, and creates channel conflict with hyperscalers and CSP partners who are core NVIDIA customers. NVIDIA has generally positioned its cloud offerings through partnerships rather than as a direct hyperscale competitor. Excluding GroqCloud would preserve neutrality with CSPs and avoid inheriting multi-region data residency obligations and partner contracts, while still allowing NVIDIA to acquire Groq’s silicon, compiler technology, and engineering talent. At the same time, excluding GroqCloud would also mean NVIDIA would not automatically acquire the commercial proof-point of Groq’s unit economics or the customer contracts that validate product-market fit at scale, increasing the importance of diligence on whether Groq’s cloud pricing is structurally profitable or partially subsidized by fundraising. There is also a “preemptive acquisition” angle. The reporting identifies recent investors in Groq’s latest round including large financial institutions and strategic/industry players. In that context, Groq represents an asset that could plausibly have been acquired by a competitor (AMD/Intel) or by a hyperscaler seeking to accelerate inference independence. NVIDIA acquiring Groq could be a defensive move to prevent a credible inference-native architecture from being weaponized by a rival with deep distribution. Even if GroqCloud is carved out, controlling the silicon roadmap and compiler IP would meaningfully constrain Groq’s ability to evolve into a standalone competitor, unless the carved-out entity retains long-term rights to the hardware and software stack. However, the strategic case is not one-sided; there are meaningful risks and potential contradictions that would need to be reconciled for the transaction to be value-accretive on a multi-year horizon. 1st, Groq’s architecture appears to rely on scaling out chip count to achieve capacity, which introduces system cost, networking complexity, and physical footprint considerations. The absence of external memory and limited on-chip SRAM implies very large models require substantial chip parallelism, and the economics then depend heavily on chip cost, yield, power efficiency, and interconnect overhead. SemiAnalysis explicitly frames Groq as trading space for time and raises questions about token economics and whether publicly advertised pricing reflects fully loaded costs or market share capture. 2nd, integration risk is non-trivial. Groq’s compiler-led deterministic model is philosophically and practically different from CUDA’s dominant programming and execution model. A poorly executed integration could create internal product confusion, dilute engineering focus, or alienate developers if the combined stack fragments. 3rd, there is cannibalization risk. If Groq-class inference silicon undercuts GPU inference economics, NVIDIA could face internal margin trade-offs, even if the goal is to defend share against hyperscaler ASICs. Cannibalization can still be rational if it prevents larger share loss, but it would require crisp portfolio segmentation and go-to-market discipline. The presence of NVIDIA’s own rapidly improving inference performance complicates the “need” for Groq but does not eliminate the “option value.” NVIDIA has demonstrated benchmark-leading tokens/s per user on Blackwell-based systems, suggesting that raw interactive throughput is not necessarily the limiting factor for NVIDIA’s product line. The more enduring strategic question is unit economics and architectural control: whether future inference demand is better monetized through general-purpose GPUs plus software optimization, or whether a bifurcated product portfolio (training GPUs plus inference-native ASICs) becomes necessary to defend total AI compute wallet share as hyperscaler ASIC penetration increases. Acquiring Groq could be a decisive move to ensure NVIDIA participates in both regimes rather than betting exclusively on GPUs to win inference forever. What is “special” about Groq’s technology relative to a typical accelerator roadmap is the tight coupling of determinism, compilation, and networking into a single scheduling problem. The LPU narrative emphasizes deterministic compute and networking, static scheduling, and direct chip-to-chip coordination that allows “hundreds” (more precisely, 100s) of chips to behave like a single scheduled resource. The architecture also explicitly targets tensor-parallel, latency-optimized distribution rather than pure data-parallel throughput scaling, which matters for real-time applications where a single response must arrive quickly rather than many requests being processed in bulk. The implication is that Groq is optimized for the time-to-first-token and steady token streaming behavior that defines user experience in interactive LLMs, and it attempts to achieve that without relying on large batch sizes that can degrade latency. From a portfolio manager’s perspective, the most important interpretation is that an NVIDIA-Groq combination would likely be less about “NVIDIA needs more inference speed” and more about controlling the architectural trajectory of inference acceleration and removing a fast-improving, developer-friendly competitor from the market. The carve-out of GroqCloud would reinforce that the transaction is aimed at IP, talent, and product optionality, not acquiring a cloud revenue stream. The valuation step-up implied by $20B versus $6.9B would therefore be justified only if the acquired assets materially reduce long-term competitive risk (hyperscaler ASIC displacement, inference margin compression) or enable new monetization vectors (inference ASIC product line, supply chain de-bottlenecking, improved software determinism) that would be difficult to achieve on a comparable timeline via internal R&D.
10:20

$NVDA $GFS NVIDIA’s reported agreement to acquire Groq for $20B in cash (per CNBC, amplified via Reuters and other wire coverage) represents a materially different strategic posture than NVIDIA’s prior M&A pattern, given both the headline size (largest reported NVIDIA acquisition to date) and the unusual carve-out that Groq’s early-stage cloud business would not be included. Public reporting indicates the information originated from Alex Davis, CEO of Disruptive (lead investor in Groq’s latest financing), and that neither NVIDIA nor Groq had issued an immediate confirmation at the time of publication. The same reporting frames the transaction as coming together quickly, only months after Groq raised $750M at a ~$6.9B valuation, and highlights Groq’s positioning as a high-performance inference chip vendor founded by ex-Google TPU engineers. Groq is best understood as a vertically integrated inference acceleration company whose core asset is an application-specific processor optimized for deterministic, low-latency execution of transformer-style workloads, paired with a compiler-led software stack and a distribution layer (GroqCloud) designed to reduce developer friction via OpenAI-compatible APIs and integrations. Groq brands its architecture as a Language Processing Unit (LPU) and consistently emphasizes that the design target is inference, not training. The company’s own architecture description centers on 1-core execution, large on-chip SRAM used as primary storage (explicitly not cache), a custom compiler that statically schedules compute and communication, and direct chip-to-chip connectivity intended to coordinate multi-chip execution without relying on conventional caching hierarchies or dynamic runtime scheduling. The technical premise is a deliberate inversion of the conventional GPU approach. GPUs deliver throughput via massively parallel, multi-core execution with dynamic scheduling, complex memory hierarchies, and heavy reliance on off-chip HBM bandwidth and sophisticated runtime/kernel optimization. Groq instead argues that inference bottlenecks are driven by latency variance (tail latency), synchronization overhead, and memory access unpredictability inherent in dynamically scheduled, cache-heavy architectures, particularly when workloads are latency sensitive and batch sizes cannot be inflated. Groq’s solution is to move “control” into the compiler: the full execution graph and inter-chip communication schedule are computed ahead of time down to clock-cycle granularity, with deterministic execution designed to reduce run-to-run variance. In Groq’s framing, the removal of caches, reorder buffers, speculative execution overhead, and other sources of contention enables predictable latency and high utilization without per-model kernel engineering typical of GPU tuning cycles. A critical nuance is that Groq’s determinism is not merely a software claim; it is tightly coupled to architectural constraints and system design choices that trade flexibility for predictability. Third-party technical commentary indicates Groq’s chip uses a fully deterministic VLIW-style approach with minimal buffering, no external memory, and heavy dependence on sharding models across many chips because on-chip SRAM capacity is limited. SemiAnalysis describes a ~725 mm^2 die on GlobalFoundries 14nm with ~230MB of SRAM and notes that “no useful models” fit on a single chip, forcing multi-chip partitioning for modern LLMs and driving a system-level design where networking and compilation are first-class scheduling problems rather than ancillary infrastructure. This is consistent with Groq’s own messaging that tensor parallelism across chips is a primary design goal, enabled by large on-chip SRAM and compile-time coordination of compute plus interconnect. The on-chip SRAM emphasis is central to Groq’s latency story and also its most constraining trade-off. Groq claims on-chip SRAM bandwidth “upwards of 80 TB/s” and contrasts that with off-chip HBM bandwidth “about 8 TB/s,” asserting a potential 10x advantage from bandwidth plus reduced trips across chip-to-memory boundaries. While these comparisons are marketing-oriented and depend on workload specifics, the architectural implication is clear: Groq prioritizes ultra-fast local weight/activation access and then scales capacity by adding chips, not by attaching large off-chip memory pools. This design can reduce latency for sequential inference layers and minimize unpredictable stalls, but it pushes complexity into partitioning strategy, interconnect topology, and compiler scheduling, and it increases the number of chips needed for very large parameter counts and large KV-cache footprints. Groq also highlights numeric formats and compiler-driven precision management as a performance lever. In its 2025 technical blog, Groq describes “TruePoint numerics,” including 100-bit intermediate accumulation and selective quantization choices (FP32 for attention-sensitive operations, block floating point for MoE weights, FP8 storage in error-tolerant layers), and claims 2-4x speedups versus BF16 without measurable accuracy degradation on benchmarks such as MMLU and HumanEval. Even if the absolute uplift is workload dependent, the strategic point is that Groq is pursuing performance via end-to-end co-design: precision policy is not just hardware capability (FP8/BF16) but compiler-enforced mapping of precision to error sensitivity, which can matter materially for inference cost-per-token if it reduces memory traffic and boosts throughput without forcing aggressive, accuracy-damaging quantization. Independent performance datapoints indicate Groq has been credible on latency-oriented inference speed, at least for certain regimes. EE Times reported in 2023 that Groq demonstrated Llama-2 70B inference at ~240 tokens/s per user on a cloud-based dev system described as 10 racks and 64 chips, using the company’s 1st-gen silicon introduced several years earlier. Separate Groq commentary around independent benchmarking cites results showing ~241 tokens/s throughput and ~0.8s time to receive 100 output tokens for a Llama-2 70B API configuration, positioning the platform as a step-change in “available speed” for certain interactive use cases. These figures do not settle total cost-of-ownership versus GPUs or hyperscaler ASICs, but they establish that Groq’s system-level architecture can deliver strong single-user throughput and latency on large models when properly partitioned and scheduled. GroqCloud is the commercial wrapper that packages this hardware/software stack as “tokens-as-a-service,” aiming to make Groq adoption feel like switching API endpoints rather than adopting new silicon. Groq’s documentation states its API is designed to be “mostly compatible” with OpenAI client libraries, and its pricing page provides model-specific token rates, published speeds (tokens/s), prompt caching discounts, and batch processing discounts. For example, pricing lists inputs as low as $0.05 per 1M tokens and outputs as low as $0.08 per 1M tokens for certain smaller LLM configurations, with higher prices for larger models and long-context or MoE variants; it also advertises prompt caching with a 50% discount on cached input tokens for certain models and a batch API offering 50% lower cost for asynchronous processing windows. These mechanics are economically important because they demonstrate Groq’s go-to-market is not simply “sell chips,” but “sell predictable unit economics per token,” with tooling (batch, caching) that directly targets inference cost drivers (reused prompts, throughput smoothing, and asynchronous workloads). The cloud footprint and distribution partnerships indicate Groq has been building an inference-native “edge within the cloud” strategy rather than competing head-on with hyperscalers on breadth of services. A 2025 Groq newsroom release describes a European deployment in Helsinki with Equinix, positioned as latency reduction and data governance for European customers, and explicitly references Equinix Fabric enabling private connectivity to GroqCloud over public, private, or sovereign infrastructure. The same release enumerates additional capacity in the U.S. (Equinix, DataBank), Canada (Bell Canada), and Saudi Arabia (HUMAIN), and states these sites collectively served more than 20M tokens/s across Groq’s global network at that time. That supply-side metric matters because it provides a directional sense that Groq is scaling capacity as a network, not merely as a chip vendor. Customer disclosure is inherently limited because Groq is private and many enterprise deployments are not public, but Groq’s marketing materials and partnerships provide signals about demand vectors. The company’s public website displays logos of large consumer and enterprise brands (e.g., Dropbox, Vercel, Chevron, Volkswagen, Canva, Robinhood, Riot Games, Workday, Ramp) and includes a published customer quote claiming a 7.41x chat speed increase and an 89% cost reduction after moving to GroqCloud, followed by a tripling of token consumption. While marketing claims should be treated as case-specific and not generalized, they indicate that Groq is targeting both AI-native developers (who measure success by latency and cost-per-token) and enterprise buyers (who care about predictable performance and governance). Supplier and dependency mapping for Groq spans 3 layers: silicon production, system integration, and cloud infrastructure. On silicon, third-party analysis indicates GlobalFoundries 14nm for the 1st-gen Groq chip, implying a supply chain less constrained by the most capacity-tight leading-edge nodes and advanced packaging bottlenecks that dominate high-end GPU supply (HBM stacks, CoWoS-type packaging constraints). If accurate, this is strategically meaningful because it suggests Groq capacity expansion could be gated more by conventional wafer supply, board assembly, and data center power than by the same HBM/advanced packaging scarcity that has constrained top-tier GPU ramp cycles. On systems and cloud, Groq’s own releases identify colocation and connectivity partners (Equinix, DataBank, Bell Canada) and a Middle East partner (HUMAIN), implying dependencies on data center real estate, power availability, and network connectivity, alongside procurement of standard server components, NICs/switching, racks, and cooling infrastructure. The Groq design narrative also emphasizes air cooling and reduced need for complex power/cooling infrastructure, which—if realized in deployments—can widen the set of feasible hosting locations and lower deployment friction relative to liquid-cooled, very high power density GPU racks. Against that backdrop, the strategic rationale for NVIDIA acquiring Groq can be framed as a set of overlapping objectives: inference silicon optionality, architectural hedging, competitive defense, and supply chain diversification, with the carve-out of GroqCloud signaling a preference to avoid direct cloud competition and to focus on IP and product portfolio control rather than operating a capital-intensive token-serving business. The deal, if confirmed, would occur at a valuation step-up of ~190% versus Groq’s reported ~$6.9B private valuation in the September $750M round, reinforcing that any acquisition logic would be predominantly strategic rather than a conventional financial multiple arbitrage. The most compelling strategic driver is inference. Training has historically been the center of gravity for cutting-edge GPU demand, but inference volume is structurally larger and more distributed as deployments scale, with economics dominated by cost-per-token, latency guarantees, and utilization under spiky demand. Inference workloads also create a strategic vulnerability for NVIDIA: hyperscalers and large platforms can justify bespoke ASICs (TPU, Trainium/Inferentia, Maia-class efforts) because inference is stable, repeatable, and can amortize software investment at massive scale. Groq’s core proposition—deterministic, compiler-scheduled inference with predictable latency—aligns directly with the segment where GPU generality is least valued and where “good enough” programmability plus superior unit economics can win share. Acquiring Groq would allow NVIDIA to own a credible inference-native architecture rather than relying solely on GPUs and software optimization to defend that segment. Competitive defense logic is also plausible. Groq occupies a specific competitive wedge: low-latency, high-throughput interactive inference, delivered via a simple API abstraction that reduces switching cost. That wedge directly pressures GPU inference margins in the long run because it makes inference price/performance comparisons more transparent at the token level, and it targets a developer persona that historically defaulted to CUDA-first ecosystems. Even if NVIDIA’s current-generation systems can achieve very high tokens/s per user with extensive optimization, the strategic risk is that competing architectures normalize the idea that inference is best served by special-purpose silicon with a simpler programming model, weakening CUDA lock-in at the application layer. NVIDIA has actively demonstrated that Blackwell-era systems can exceed 1,000 tokens/s per user in benchmarked configurations, but that performance leadership does not automatically translate to lowest cost-per-token across the full range of batch sizes, latency targets, and deployment environments. Groq’s existence as a credible alternative architecture forces NVIDIA to keep defending inference economics rather than only raw performance leadership. The “technology acquisition” rationale is unusually strong in this specific case because Groq’s differentiator is not a single block of silicon IP but an end-to-end methodology: compiler-led static scheduling, deterministic networking, and a system architecture designed around tensor-parallel inference rather than throughput-maximizing batch inference. NVIDIA’s stack is already compiler-heavy (TensorRT, Triton, CUDA graphs, kernel fusion, speculative decoding techniques), but GPUs remain dynamically scheduled devices with complex memory hierarchies and stochastic latency behaviors under contention. Groq’s approach provides an alternate design point: treating the entire inference execution (compute plus communication) as a statically schedulable program. In principle, that IP could be valuable even if Groq silicon itself is not adopted at massive scale, because it can inform how NVIDIA builds future inference-optimized products, compilers, and networking fabrics, especially as distributed inference with large models makes communication a first-order performance determinant. Supply chain diversification is a non-obvious but potentially important driver. If Groq’s mainstream product generation is truly based on a mature process node and avoids HBM, then the scaling constraints look different than those of state-of-the-art GPUs. NVIDIA’s ability to meet incremental demand has been tightly coupled to advanced packaging and HBM supply, and those constraints can remain binding even when wafer supply is available. An inference ASIC architecture that relies primarily on on-chip SRAM and scales by adding chips—while not costless—could reduce dependence on HBM availability and advanced packaging capacity, enabling NVIDIA to ship “inference capacity” in higher absolute volumes or into geographies and customer segments where the highest-end GPUs are economically or logistically difficult to deploy. This could be particularly relevant for latency-sensitive inference deployed in regional colocation footprints rather than centralized hyperscale campuses. The carve-out of GroqCloud, if accurate, is itself a strategic signal about NVIDIA’s priorities. Operating a token-serving cloud at scale is capital intensive, structurally lower margin than silicon IP rents, and creates channel conflict with hyperscalers and CSP partners who are core NVIDIA customers. NVIDIA has generally positioned its cloud offerings through partnerships rather than as a direct hyperscale competitor. Excluding GroqCloud would preserve neutrality with CSPs and avoid inheriting multi-region data residency obligations and partner contracts, while still allowing NVIDIA to acquire Groq’s silicon, compiler technology, and engineering talent. At the same time, excluding GroqCloud would also mean NVIDIA would not automatically acquire the commercial proof-point of Groq’s unit economics or the customer contracts that validate product-market fit at scale, increasing the importance of diligence on whether Groq’s cloud pricing is structurally profitable or partially subsidized by fundraising. There is also a “preemptive acquisition” angle. The reporting identifies recent investors in Groq’s latest round including large financial institutions and strategic/industry players. In that context, Groq represents an asset that could plausibly have been acquired by a competitor (AMD/Intel) or by a hyperscaler seeking to accelerate inference independence. NVIDIA acquiring Groq could be a defensive move to prevent a credible inference-native architecture from being weaponized by a rival with deep distribution. Even if GroqCloud is carved out, controlling the silicon roadmap and compiler IP would meaningfully constrain Groq’s ability to evolve into a standalone competitor, unless the carved-out entity retains long-term rights to the hardware and software stack. However, the strategic case is not one-sided; there are meaningful risks and potential contradictions that would need to be reconciled for the transaction to be value-accretive on a multi-year horizon. 1st, Groq’s architecture appears to rely on scaling out chip count to achieve capacity, which introduces system cost, networking complexity, and physical footprint considerations. The absence of external memory and limited on-chip SRAM implies very large models require substantial chip parallelism, and the economics then depend heavily on chip cost, yield, power efficiency, and interconnect overhead. SemiAnalysis explicitly frames Groq as trading space for time and raises questions about token economics and whether publicly advertised pricing reflects fully loaded costs or market share capture. 2nd, integration risk is non-trivial. Groq’s compiler-led deterministic model is philosophically and practically different from CUDA’s dominant programming and execution model. A poorly executed integration could create internal product confusion, dilute engineering focus, or alienate developers if the combined stack fragments. 3rd, there is cannibalization risk. If Groq-class inference silicon undercuts GPU inference economics, NVIDIA could face internal margin trade-offs, even if the goal is to defend share against hyperscaler ASICs. Cannibalization can still be rational if it prevents larger share loss, but it would require crisp portfolio segmentation and go-to-market discipline. The presence of NVIDIA’s own rapidly improving inference performance complicates the “need” for Groq but does not eliminate the “option value.” NVIDIA has demonstrated benchmark-leading tokens/s per user on Blackwell-based systems, suggesting that raw interactive throughput is not necessarily the limiting factor for NVIDIA’s product line. The more enduring strategic question is unit economics and architectural control: whether future inference demand is better monetized through general-purpose GPUs plus software optimization, or whether a bifurcated product portfolio (training GPUs plus inference-native ASICs) becomes necessary to defend total AI compute wallet share as hyperscaler ASIC penetration increases. Acquiring Groq could be a decisive move to ensure NVIDIA participates in both regimes rather than betting exclusively on GPUs to win inference forever. What is “special” about Groq’s technology relative to a typical accelerator roadmap is the tight coupling of determinism, compilation, and networking into a single scheduling problem. The LPU narrative emphasizes deterministic compute and networking, static scheduling, and direct chip-to-chip coordination that allows “hundreds” (more precisely, 100s) of chips to behave like a single scheduled resource. The architecture also explicitly targets tensor-parallel, latency-optimized distribution rather than pure data-parallel throughput scaling, which matters for real-time applications where a single response must arrive quickly rather than many requests being processed in bulk. The implication is that Groq is optimized for the time-to-first-token and steady token streaming behavior that defines user experience in interactive LLMs, and it attempts to achieve that without relying on large batch sizes that can degrade latency. From a portfolio manager’s perspective, the most important interpretation is that an NVIDIA-Groq combination would likely be less about “NVIDIA needs more inference speed” and more about controlling the architectural trajectory of inference acceleration and removing a fast-improving, developer-friendly competitor from the market. The carve-out of GroqCloud would reinforce that the transaction is aimed at IP, talent, and product optionality, not acquiring a cloud revenue stream. The valuation step-up implied by $20B versus $6.9B would therefore be justified only if the acquired assets materially reduce long-term competitive risk (hyperscaler ASIC displacement, inference margin compression) or enable new monetization vectors (inference ASIC product line, supply chain de-bottlenecking, improved software determinism) that would be difficult to achieve on a comparable timeline via internal R&D.

TheValueist

102,145 views • 8 months ago

$AMD| The FOMO to buy AMD Chips is NOW 🧵 Not Financial Advice! DYOR! Research Purpose Only! The Inference Queen is the biggest winner in Agentic AI where all other CPUs are struggling to compete with a 2yr old EPYC Turin and EPYC Venice is in mass production phase. AMD stresses deployability today on standard x86 platforms (no proprietary architectures required), full software compatibility, and open standards. This positions Venice + Helios as a practical, high-density alternative to competing solutions while underscoring that agentic AI shifts the balance toward CPU-rich racks alongside GPUs, and most importantly, lowering the cost of token to accelerate adoption and innovation. Context: The Wall Street Journal yesterday came out with an article that OpenAI is condiering drasstically lowering the token prices to win more customers from Anthropic. The narrative "they" are trying to exacerbate the current AI selloff won't last long. This is a fundamental misunderstanding of what is going on, or what I already discussed for months and years. Followers and Subscribers already knew this for years, that this day would come, where token cost will bcome the central discussion among enterprises as there is no such thing as unlimited budget or Tokenmaxxing when they use $NVDA chips or In-house Hyperscalers chips. I will link various threads if you are interested in understanding the full picture from supply chain to recent TSMC Rapid 2nm expansion up to 12 Fabs total by 2027/2028. Hyperscalers and AI natives effectively have no choice but to buy more AMD system for Agentic AI as leadership in economical, power-aware, high-volume internal + agentic use. However, due to supply constraints where Supply is far behind Demand, this makes multi-vendor reality along with in-house chips drive faster industry progress, lower overall costs, and better sustainability. NVIDIA’s Vera Rubin cannot compete with a 2 years old EPYC Turin, but AMD under Dr. Lisa Su has engineered the lowest cost-per-million-tokens, highly competitive energy-efficient solutions, and superior CPU orchestration for agentic AI at scale with Helios. Dr. Su has championed this shift since at least 2023, foreseeing the rise of agentic workflows that demand far more orchestration, parallel agents, and balanced compute well before the industry fully embraced it. Her long-term vision of AI moving from simple prompts to always on, multi-agent systems has driven AMD’s investments in high-core EPYC CPUs and integrated rack-scale solutions, perfectly positioning the company for today’s realities. The OpenAI-AMD 1GW Helios deployment (starting H2 2026) represents a pivotal vertical integration move that directly supercharges the inference economics. This isn't incremental; it's a structural shift toward ownership of massive, optimized rack-scale capacity, enabling the lowest token costs and triggering the enterprise adoption flywheel. We need to be honest, $AMD is the only company that made a big bet on Inference since the day Chatgpt became sensational where $NVDA and others were betting big on Training. At the end of the day, Token bill from Anthropic has to obey economics. Meaning the bills rise, companies have to get more out of it to justify the cost. It cannot be an unlimited inference budget, and it has to show up on efficiency, profitability and operating leverage. 1. Tokenomics After you understand this, you will understand why Citi cited Anthropic is likely to sign a deal with $AMD along with Hyperscalers, AI Labs, Sovereign AI like Softbank 5GW in France and many other countries. However, OpenAI and $META are now wanting faster deployment, and they are AMD shareholders now, they have prioritized allocation. Anthropic and Hyperscalers just cannot compete when Helios Rack lower token cost to$0.0003–$0.0005 per million tokens at GW scale. Cost to build 1GW data center 1GW Helios Rack full build is estimated $30-$35B 1GW Rubin Rack full build is estimated $45-$55B Inference (Cost per Million Tokens) ~$NVDA B200 / HGX: ~$0.02–$0.08 on optimized workloads (FP4/MXFP4, speculative decoding). Significant improvement over Hopper but still premium-priced. GB200 NVL72 rack-scale: $0.05–$0.25+ ~$AMD Helios Racks: $0.0003-$0.0005 per M tokens, dramatically lower than NVIDIA equivalents in owned infra. MI355X node-level: Up to 40% more tokens per dollar vs. competing solutions ( B200), driven by higher memory capacity (up to 288GB+ HBM), strong bandwidth, and lower acquisition costs. Training ~$NVDA Rubin Rack is estimated $0.7-$1.2/M Tokens ~$AMD Helios Rack is estimated $0.65-$1.0/M Tokens Now, OpenAI, META and Hyperscalers can lower Inference cost even further with $AMD EPYC Venice "dense rack" or Agentic AI Rack. AMD published a detailed technical blog emphasizing that the future of agentic AI autonomous, multi-step AI systems requiring heavy orchestration, databases, caching, APIs, and control planes demands massive CPU-dense rack-scale infrastructure, not just GPUs. The catalyst prominently positions their upcoming 6th Gen EPYC "Venice" processors as the key enabler for next-generation dense racks, delivering leadership throughput under real-world power, cooling, and density constraints. ~EPYC Venice (Zen 6 architecture, up to 256 cores / 512 threads per socket) is projected to deliver exceptional rack-level performance. In AMD’s modeled 100 kW rack comparisons, Venice-powered systems are expected to achieve ~3.30x the throughput of NVIDIA’s Vera (88-core Olympus) baseline across a broad mix of agentic-supporting workloads. ~This builds on current-generation 5th Gen EPYC "Turin" (up to 192 cores), which already delivers ~2.37x rack throughput vs. Vera and ~1.6x vs. Intel’s Xeon 6980P (128 cores). ~ Liquid-cooled Turin deployments already support >27,000 CPU cores per rack today. Venice is architected to push this beyond 36,000 cores in the same rack class, dramatically increasing concurrent agent capacity and overall infrastructure efficiency. 2. Ownership vs renting compute from Hyperscalers matter to OpenAI and only owning $AMD chips can meaningfully lower token cost for enterprises. ~Eliminates cloud overhead: No provider margins, utilization buffers, or egress fees. Direct control over power contracts, cooling, scheduling, and orchestration at dedicated facilities. ~Helios optimizations at GW scale: Rack-level density (1.4+ exaFLOPS FP8 per rack), high HBM4 bandwidth, EPYC orchestration for agentic workloads, and superior TCO/TDP. AMD's long-standing focus on tokens per dollar/watt shines here 20-40%+ efficiency edges in inference-heavy scenarios. ~At 1GW+ optimized deployment, inference hits $0.0003–$0.0005 per million tokens (community/analyst models tied to Helios metrics). This is dramatically lower than typical rented/cloud equivalents, especially for high-volume output tokens in agentic flows. High token bills today, enterprises running heavy agentic/coding/analysis workloads can face $50-100M+/month at current API rates (flagship models $5-30+/M output, scaled to massive volumes). Post-Helios compression, same volume will drop to $10-15M/month (or better) via lower underlying costs passed through as pricing flexibility, volume tiers, caching, or batch discounts. ROI thresholds collapse. More companies greenlight pilots → production → massive scaling. Agentic AI (autonomous workflows) multiplies token demand exponentially, but affordability removes the friction. OpenAI gains flexibility, Unlike more cloud-dependent rivals (Anthropic), they can lower effective pricing, offer aggressive enterprise bundles, or absorb volume without margin destruction directly tackling "high token bill" complaints while maintaining profitability as usage explodes. 3. Agentic AI Models shifted CPU:GPU Ratio to 1:1 toward 3-5:1 with Explosively Token-Hungry Workloads Agentic AI (autonomous, multi-step agents with planning, tool use, iteration, and self-correction) is fundamentally more compute and token intensive than conversational or single-turn generative AI. Agentic AI. autonomous, multi-step workflows with orchestration, tool use, parallel agents, data movement, and enterprise integration has dramatically increased the importance of strong host CPUs alongside GPUs. This shifts the CPU-to-GPU ratio higher and makes balanced systems critical toward 1:1 to 5:1 as enterprises testing more than 5-10 agents. AMD EPYC Venice excels ~Leadership core density (up to 256 Zen 6 cores per socket) for running many agents in parallel, orchestration layers, and high-throughput control-plane tasks. ~Superior performance-per-core and power efficiency ( up to 2.1x higher perf/core and 2.26x better SPECpower vs. NVIDIA Grace in benchmarks). ~Tight integration in Helios: One Venice CPU + multiple MI450 GPUs per node, enabling efficient data feeding to GPUs ("zero-copy"), parallel execution, and full rack utilization for complex agentic loops. Hyperscalers (Meta, Microsoft, Amazon, Google, Softbank) and AI natives (OpenAI, Anthropic...) are adopting high-core EPYC at scale specifically for these agentic demands, as CPUs now handle a larger share of non-model work (orchestration, policy enforcement, tool calls). This complements AMD’s lower-cost GPUs for overall TCO wins. ~Agents often generate 10–100x+ more tokens per task due to iterative reasoning chains, multiple tool calls, verification loops, and long-context orchestration. ~Goldman Sachs forecasts token consumption multiplying 24x by 2030 (to 120 quadrillion tokens/month) largely driven by agentic adoption in consumer and enterprise. ~Enterprise data shows agent-pattern workloads growing at 680% annualized rates, projected to surpass conversational AI in token volume by Q3 2026. ~Daily enterprise agent token consumption is already in the billions, with complex workflows (coding, workflows, analysis) amplifying this dramatically. 4. Competitive Edge: Winning Customers from Anthropic Anthropic’s Claude models (especially Opus/Sonnet) excel in complex reasoning and agentic coding, commanding premium positioning. However, their higher underlying costs (heavier reliance on third-party cloud with margins) limit pricing flexibility compared to OpenAI’s owned Helios capacity. Anthropic is on track to generate $10.9 billion in Q2 revenue. The company expects to achieve its first-ever quarterly adjusted operating profit of $559 million. However, sustaining full-year profitability remains challenging due to immense computing and model training costs The truth is, Anthropic has no choice but to buy as much $AMD chips as possible if they want to compete with OpenAI or get investors attention. This 5% adjusted operating profit to revenue ratio is just pathetic. Current pricing dynamics (2026): OpenAI already undercuts on many tiers ( flagship output tokens significantly cheaper than equivalent Claude Opus). Nano/mini models offer 5–10x advantages for volume work. Anthropic holds edges in long-context flat pricing and certain reasoning quality. OpenAI after Helios Rack Ownership, At $0.0003–$0.0005/M effective costs, OpenAI gains massive headroom to: ~Aggressively discount high-volume agentic tiers or bundles. ~Offer “unlimited” enterprise plans or usage-based models that Anthropic struggles to match without margin erosion. ~Target cost-sensitive, high-throughput agent deployments (dev tools, automation platforms) where token bills explode. Enterprises facing $ millions in monthly agentic bills will migrate to the provider delivering better economics at scale. OpenAI’s combination of strong models (o-series reasoning) + lowest TCO positions it to erode Anthropic’s enterprise share, especially as agentic becomes the dominant token consumer. Cheaper tokens expand the total addressable market dramatically. This feeds the data/model improvement loop, justifying further capex. AMD benefits from proven scale pulling in more customers (Meta, Oracle, Microsfot, Amazon, Softbank, TensorWave, LumaAI ... already aligned on Helios). Conclusion: Dr. Lisa Su has been laser focused on inference economics since at least 2022–2023, repeatedly emphasizing that the real battleground for AI scalability would be TCO, power efficiency (TDP), and ultimately tokens per dollar and per watt not just raw training FLOPS. While many viewed inference as a secondary, commoditized workload, Dr. Su architected AMD’s roadmap around rack-scale systems optimized for high-volume, sustained inference that would dominate as models matured and usage exploded. Helios represents the culmination of that multi-year bet: a fully integrated, open platform designed precisely for the economics of massive token throughput. This deep, strategic partnership with OpenAI starting with the 1GW Helios deployment in H2 2026 and scaling to 6GW, is the embodiment of that shared vision. Both companies foresaw a future where agentic AI models evolve to become extraordinarily token-hungry: autonomous agents executing complex, iterative workflows with planning, tool use, verification loops, and long-context reasoning. These workloads can consume 100x+ more tokens per task than traditional chat or single-turn generation, driving exponential demand as capabilities improve and enterprises deploy them at scale. By owning and optimizing this massive Helios capacity at GW scale, OpenAI achieves inference costs as low as $0.0003–$0.0005 per million tokens. This structural cost advantage allows OpenAI to absorb the coming token explosion profitably, dramatically lower effective pricing for enterprises, and win high-volume agentic workloads from higher-cost competitors like Anthropic. What was once a prohibitive monthly token bill becomes an affordable accelerator for productivity and innovation. The OpenAI-AMD alliance validates Dr. Su’s prescient strategy and turns the Agentic flywheel into reality: Collapsing inference costs → explosive token consumption → richer data and better models → accelerate greater demand. This partnership doesn’t just address today’s economics, it positions both leaders at the center of the infrastructure buildout that will power AI’s next decade. By delivering the lowest inference economics at scale, OpenAI not only solves enterprise bill pain but gains a decisive weapon to win share from higher-cost rivals like Anthropic. And that is why OpenAI and $META will deploy EPYC Dense Rack Not Financial Advice! DYOR! Research Purpose Only!
4:46

$AMD| The FOMO to buy AMD Chips is NOW 🧵 Not Financial Advice! DYOR! Research Purpose Only! The Inference Queen is the biggest winner in Agentic AI where all other CPUs are struggling to compete with a 2yr old EPYC Turin and EPYC Venice is in mass production phase. AMD stresses deployability today on standard x86 platforms (no proprietary architectures required), full software compatibility, and open standards. This positions Venice + Helios as a practical, high-density alternative to competing solutions while underscoring that agentic AI shifts the balance toward CPU-rich racks alongside GPUs, and most importantly, lowering the cost of token to accelerate adoption and innovation. Context: The Wall Street Journal yesterday came out with an article that OpenAI is condiering drasstically lowering the token prices to win more customers from Anthropic. The narrative "they" are trying to exacerbate the current AI selloff won't last long. This is a fundamental misunderstanding of what is going on, or what I already discussed for months and years. Followers and Subscribers already knew this for years, that this day would come, where token cost will bcome the central discussion among enterprises as there is no such thing as unlimited budget or Tokenmaxxing when they use $NVDA chips or In-house Hyperscalers chips. I will link various threads if you are interested in understanding the full picture from supply chain to recent TSMC Rapid 2nm expansion up to 12 Fabs total by 2027/2028. Hyperscalers and AI natives effectively have no choice but to buy more AMD system for Agentic AI as leadership in economical, power-aware, high-volume internal + agentic use. However, due to supply constraints where Supply is far behind Demand, this makes multi-vendor reality along with in-house chips drive faster industry progress, lower overall costs, and better sustainability. NVIDIA’s Vera Rubin cannot compete with a 2 years old EPYC Turin, but AMD under Dr. Lisa Su has engineered the lowest cost-per-million-tokens, highly competitive energy-efficient solutions, and superior CPU orchestration for agentic AI at scale with Helios. Dr. Su has championed this shift since at least 2023, foreseeing the rise of agentic workflows that demand far more orchestration, parallel agents, and balanced compute well before the industry fully embraced it. Her long-term vision of AI moving from simple prompts to always on, multi-agent systems has driven AMD’s investments in high-core EPYC CPUs and integrated rack-scale solutions, perfectly positioning the company for today’s realities. The OpenAI-AMD 1GW Helios deployment (starting H2 2026) represents a pivotal vertical integration move that directly supercharges the inference economics. This isn't incremental; it's a structural shift toward ownership of massive, optimized rack-scale capacity, enabling the lowest token costs and triggering the enterprise adoption flywheel. We need to be honest, $AMD is the only company that made a big bet on Inference since the day Chatgpt became sensational where $NVDA and others were betting big on Training. At the end of the day, Token bill from Anthropic has to obey economics. Meaning the bills rise, companies have to get more out of it to justify the cost. It cannot be an unlimited inference budget, and it has to show up on efficiency, profitability and operating leverage. 1. Tokenomics After you understand this, you will understand why Citi cited Anthropic is likely to sign a deal with $AMD along with Hyperscalers, AI Labs, Sovereign AI like Softbank 5GW in France and many other countries. However, OpenAI and $META are now wanting faster deployment, and they are AMD shareholders now, they have prioritized allocation. Anthropic and Hyperscalers just cannot compete when Helios Rack lower token cost to$0.0003–$0.0005 per million tokens at GW scale. Cost to build 1GW data center 1GW Helios Rack full build is estimated $30-$35B 1GW Rubin Rack full build is estimated $45-$55B Inference (Cost per Million Tokens) ~$NVDA B200 / HGX: ~$0.02–$0.08 on optimized workloads (FP4/MXFP4, speculative decoding). Significant improvement over Hopper but still premium-priced. GB200 NVL72 rack-scale: $0.05–$0.25+ ~$AMD Helios Racks: $0.0003-$0.0005 per M tokens, dramatically lower than NVIDIA equivalents in owned infra. MI355X node-level: Up to 40% more tokens per dollar vs. competing solutions ( B200), driven by higher memory capacity (up to 288GB+ HBM), strong bandwidth, and lower acquisition costs. Training ~$NVDA Rubin Rack is estimated $0.7-$1.2/M Tokens ~$AMD Helios Rack is estimated $0.65-$1.0/M Tokens Now, OpenAI, META and Hyperscalers can lower Inference cost even further with $AMD EPYC Venice "dense rack" or Agentic AI Rack. AMD published a detailed technical blog emphasizing that the future of agentic AI autonomous, multi-step AI systems requiring heavy orchestration, databases, caching, APIs, and control planes demands massive CPU-dense rack-scale infrastructure, not just GPUs. The catalyst prominently positions their upcoming 6th Gen EPYC "Venice" processors as the key enabler for next-generation dense racks, delivering leadership throughput under real-world power, cooling, and density constraints. ~EPYC Venice (Zen 6 architecture, up to 256 cores / 512 threads per socket) is projected to deliver exceptional rack-level performance. In AMD’s modeled 100 kW rack comparisons, Venice-powered systems are expected to achieve ~3.30x the throughput of NVIDIA’s Vera (88-core Olympus) baseline across a broad mix of agentic-supporting workloads. ~This builds on current-generation 5th Gen EPYC "Turin" (up to 192 cores), which already delivers ~2.37x rack throughput vs. Vera and ~1.6x vs. Intel’s Xeon 6980P (128 cores). ~ Liquid-cooled Turin deployments already support >27,000 CPU cores per rack today. Venice is architected to push this beyond 36,000 cores in the same rack class, dramatically increasing concurrent agent capacity and overall infrastructure efficiency. 2. Ownership vs renting compute from Hyperscalers matter to OpenAI and only owning $AMD chips can meaningfully lower token cost for enterprises. ~Eliminates cloud overhead: No provider margins, utilization buffers, or egress fees. Direct control over power contracts, cooling, scheduling, and orchestration at dedicated facilities. ~Helios optimizations at GW scale: Rack-level density (1.4+ exaFLOPS FP8 per rack), high HBM4 bandwidth, EPYC orchestration for agentic workloads, and superior TCO/TDP. AMD's long-standing focus on tokens per dollar/watt shines here 20-40%+ efficiency edges in inference-heavy scenarios. ~At 1GW+ optimized deployment, inference hits $0.0003–$0.0005 per million tokens (community/analyst models tied to Helios metrics). This is dramatically lower than typical rented/cloud equivalents, especially for high-volume output tokens in agentic flows. High token bills today, enterprises running heavy agentic/coding/analysis workloads can face $50-100M+/month at current API rates (flagship models $5-30+/M output, scaled to massive volumes). Post-Helios compression, same volume will drop to $10-15M/month (or better) via lower underlying costs passed through as pricing flexibility, volume tiers, caching, or batch discounts. ROI thresholds collapse. More companies greenlight pilots → production → massive scaling. Agentic AI (autonomous workflows) multiplies token demand exponentially, but affordability removes the friction. OpenAI gains flexibility, Unlike more cloud-dependent rivals (Anthropic), they can lower effective pricing, offer aggressive enterprise bundles, or absorb volume without margin destruction directly tackling "high token bill" complaints while maintaining profitability as usage explodes. 3. Agentic AI Models shifted CPU:GPU Ratio to 1:1 toward 3-5:1 with Explosively Token-Hungry Workloads Agentic AI (autonomous, multi-step agents with planning, tool use, iteration, and self-correction) is fundamentally more compute and token intensive than conversational or single-turn generative AI. Agentic AI. autonomous, multi-step workflows with orchestration, tool use, parallel agents, data movement, and enterprise integration has dramatically increased the importance of strong host CPUs alongside GPUs. This shifts the CPU-to-GPU ratio higher and makes balanced systems critical toward 1:1 to 5:1 as enterprises testing more than 5-10 agents. AMD EPYC Venice excels ~Leadership core density (up to 256 Zen 6 cores per socket) for running many agents in parallel, orchestration layers, and high-throughput control-plane tasks. ~Superior performance-per-core and power efficiency ( up to 2.1x higher perf/core and 2.26x better SPECpower vs. NVIDIA Grace in benchmarks). ~Tight integration in Helios: One Venice CPU + multiple MI450 GPUs per node, enabling efficient data feeding to GPUs ("zero-copy"), parallel execution, and full rack utilization for complex agentic loops. Hyperscalers (Meta, Microsoft, Amazon, Google, Softbank) and AI natives (OpenAI, Anthropic...) are adopting high-core EPYC at scale specifically for these agentic demands, as CPUs now handle a larger share of non-model work (orchestration, policy enforcement, tool calls). This complements AMD’s lower-cost GPUs for overall TCO wins. ~Agents often generate 10–100x+ more tokens per task due to iterative reasoning chains, multiple tool calls, verification loops, and long-context orchestration. ~Goldman Sachs forecasts token consumption multiplying 24x by 2030 (to 120 quadrillion tokens/month) largely driven by agentic adoption in consumer and enterprise. ~Enterprise data shows agent-pattern workloads growing at 680% annualized rates, projected to surpass conversational AI in token volume by Q3 2026. ~Daily enterprise agent token consumption is already in the billions, with complex workflows (coding, workflows, analysis) amplifying this dramatically. 4. Competitive Edge: Winning Customers from Anthropic Anthropic’s Claude models (especially Opus/Sonnet) excel in complex reasoning and agentic coding, commanding premium positioning. However, their higher underlying costs (heavier reliance on third-party cloud with margins) limit pricing flexibility compared to OpenAI’s owned Helios capacity. Anthropic is on track to generate $10.9 billion in Q2 revenue. The company expects to achieve its first-ever quarterly adjusted operating profit of $559 million. However, sustaining full-year profitability remains challenging due to immense computing and model training costs The truth is, Anthropic has no choice but to buy as much $AMD chips as possible if they want to compete with OpenAI or get investors attention. This 5% adjusted operating profit to revenue ratio is just pathetic. Current pricing dynamics (2026): OpenAI already undercuts on many tiers ( flagship output tokens significantly cheaper than equivalent Claude Opus). Nano/mini models offer 5–10x advantages for volume work. Anthropic holds edges in long-context flat pricing and certain reasoning quality. OpenAI after Helios Rack Ownership, At $0.0003–$0.0005/M effective costs, OpenAI gains massive headroom to: ~Aggressively discount high-volume agentic tiers or bundles. ~Offer “unlimited” enterprise plans or usage-based models that Anthropic struggles to match without margin erosion. ~Target cost-sensitive, high-throughput agent deployments (dev tools, automation platforms) where token bills explode. Enterprises facing $ millions in monthly agentic bills will migrate to the provider delivering better economics at scale. OpenAI’s combination of strong models (o-series reasoning) + lowest TCO positions it to erode Anthropic’s enterprise share, especially as agentic becomes the dominant token consumer. Cheaper tokens expand the total addressable market dramatically. This feeds the data/model improvement loop, justifying further capex. AMD benefits from proven scale pulling in more customers (Meta, Oracle, Microsfot, Amazon, Softbank, TensorWave, LumaAI ... already aligned on Helios). Conclusion: Dr. Lisa Su has been laser focused on inference economics since at least 2022–2023, repeatedly emphasizing that the real battleground for AI scalability would be TCO, power efficiency (TDP), and ultimately tokens per dollar and per watt not just raw training FLOPS. While many viewed inference as a secondary, commoditized workload, Dr. Su architected AMD’s roadmap around rack-scale systems optimized for high-volume, sustained inference that would dominate as models matured and usage exploded. Helios represents the culmination of that multi-year bet: a fully integrated, open platform designed precisely for the economics of massive token throughput. This deep, strategic partnership with OpenAI starting with the 1GW Helios deployment in H2 2026 and scaling to 6GW, is the embodiment of that shared vision. Both companies foresaw a future where agentic AI models evolve to become extraordinarily token-hungry: autonomous agents executing complex, iterative workflows with planning, tool use, verification loops, and long-context reasoning. These workloads can consume 100x+ more tokens per task than traditional chat or single-turn generation, driving exponential demand as capabilities improve and enterprises deploy them at scale. By owning and optimizing this massive Helios capacity at GW scale, OpenAI achieves inference costs as low as $0.0003–$0.0005 per million tokens. This structural cost advantage allows OpenAI to absorb the coming token explosion profitably, dramatically lower effective pricing for enterprises, and win high-volume agentic workloads from higher-cost competitors like Anthropic. What was once a prohibitive monthly token bill becomes an affordable accelerator for productivity and innovation. The OpenAI-AMD alliance validates Dr. Su’s prescient strategy and turns the Agentic flywheel into reality: Collapsing inference costs → explosive token consumption → richer data and better models → accelerate greater demand. This partnership doesn’t just address today’s economics, it positions both leaders at the center of the infrastructure buildout that will power AI’s next decade. By delivering the lowest inference economics at scale, OpenAI not only solves enterprise bill pain but gains a decisive weapon to win share from higher-cost rivals like Anthropic. And that is why OpenAI and $META will deploy EPYC Dense Rack Not Financial Advice! DYOR! Research Purpose Only!

Mike

84,951 views • 2 months ago

Like seemingly everyone on this app I have plenty of opinions about Twitter > X and figure now is a good time to open up a bit about my experience at the company. I tweeted for years into the void for the love of it like many of you, but after selling my startup to Twitter in 2020 I finally got to see it from the inside. Up close it was both amazing and terrible, like so many other companies and things in life. As someone with a maniacal sense of urgency built into me, Twitter often felt siloed and bureaucratic. Dumb power plays, reorgs and team name changes for the sake of someone’s ego were distractions that occurred too regularly. You couldn’t just be a builder — you also needed to be a politician. I was shocked by how old and bespoke the infrastructure was, but there was little will to think beyond quarterly earnings calls because we were all beholden to the masters of mDAU and revenue growth as a public company. It often felt like things were held together with duct tape and glue, and that many people had just accepted that a small product change could take months or quarters to build. Management had become bloated to accommodate career growth and the company culture felt too soft and entitled for my own taste. Healthy debate and criticism was replaced by a default refrain of “no, that can’t be done” or “another team owns that so don’t touch it”. Teams could spend months building a feature and then some last-minute kerfuffle meant it’d get killed for being too risky. Just talking directly to customers could turn into a turf war and create deadlocks between functions. I recall one such episode where a teammate spent a month trying to get clearance to reach out to some creators. He went through 3 layers of management and 6 different functional teams. In the end 4 executives were involved in the approval. It was insanity, and unfortunately I saw several top performers get burnt out and demoralized after exhausting experiences like that. Most people were good at their jobs but it was nearly impossible to fire poor performers — instead they got shuffled around to other teams because few managers had the will or resources to figure out how to get them out. A high performance culture pulls everyone up, but the opposite weighs everyone down. Twitter often felt like a place that kept squandering its own potential, which was sad and frustrating to see. The person who was best at cutting through the BS and inspiring a vision during my tenure was Kayvon Beykpour, but he wasn’t fully empowered to run the company since he wasn’t the CEO. Despite those real issues, I was lucky enough to work with some of the most talented people in the business at Twitter in product, design, engineering, research, legal, BD, trust & safety, marketing, PR and more. Often it was a small cross-functional team of intrinsically motivated people who made the biggest impact by challenging some core assumption. Those teams were very fun to be on but they felt like the exception rather than the rule. The months of waiting for the deal to close in 2022 were particularly slow and painful; it felt like leadership hid behind lawyers and legal language as all answers about the company’s future notoriously included the phrase “fiduciary duty”. Colleagues openly talked about how Twitter was being sold because leadership didn’t have conviction in their own plan or ability to fix longstanding problems. Although I didn’t know much about Elon I was cautiously optimistic – I saw him as the guy who built incredible and enduring companies like Tesla and SpaceX, so perhaps his private ownership could shake things up and breathe new life into the company. My take on what’s happened since then is full of lived nuance. When people ask why I stayed it’s easy to answer: optimism, curiosity, personal growth and money. From the beginning I saw that some changes Elon was going to make were smart and others were stupid, but when I’m on a team I uphold the philosophy of “praise in public and criticize in private”. I was far from a silent wallflower. I shared my opinions openly and pushed back often, both before and after the acquisition. I made peace with the fact that I didn’t have psychological safety at Twitter 2.0 and that meant I could be fired at any moment, and for no reason at all. I watched it happen repeatedly and saw how negatively it impacted team morale. Although I couldn’t change the situation I did my best to shine a light on folks who were doing important work while being an emotionally supportive leader for those who were struggling to adapt to the more brutalist and hardcore culture. In person Elon is oddly charming and he’s genuinely funny. He also has personality quirks like telling the same stories and jokes over and over. The challenge is his personality and demeanor can turn on a dime going from excited to angry. Since it was hard to read what mood he might be in and what his reaction would be to any given thing, people quickly became afraid of being called into meetings or having to share negative news with him. At times it felt like the inner circle was too zealous and fanatical in their unwavering support of everything he said. When individuals encouraged me to be careful about what I said I politely thanked them and said I would not be taking their advice. I had no interest in adding to a culture of fear or walking on eggshells around Elon. Either he would respect me for being real or he could fire me. Either outcome was okay. I quickly learned that product and business decisions were nearly always the result of him following his gut instinct, and he didn’t seem compelled to seek out or rely on a lot of data or expertise to inform it. That was particularly frustrating for me since I believed I had useful institutional knowledge that could help him make better decisions. Instead he'd poll Twitter, ask a friend, or even ask his biographer for product advice. At times it seemed he trusted random feedback more than the people in the room who spent their lives dedicated to tackling the problem at hand. I never figured out why and remain puzzled by it. I don’t think things had to be as difficult or dramatic as they turned out to be but I can’t say I’d bet against Elon or count him out. He’s smart and has enough money to make a lot of mistakes and then course correct when things go awry. As the largest shareholder he can tank the value in the short-term, but eventually he’ll need things to turn around. His focus on speed is incredible and he’s obviously not afraid of blowing things up, but now the real measure will be how it get reconstructed and if enough people want the new everything app he is building. I learned a ton from watching Elon up close – the good, the bad and the ugly. His boldness, passion and storytelling is inspiring, but his lack of process and empathy is painful. Elon has an exceptional talent for tackling hard physics-based problems but products that facilitate human connection and communication require a different type of social-emotional intelligence. Social networks are hard to kill but they’re not immune from death spirals. Only time will tell what the outcome will be but I hope X finds its footing because competition is good for consumers. In the meantime, I have a lot of empathy for the employees who are working tirelessly behind the scenes, the advertisers who want a stable platform to sell their stuff on, and the customers who are experiencing chaotic updates. It’s been a madhouse. Twitter moved at the speed of molasses and suffered from bureaucracy but now X is run by a mercurial leader whose instinct is driven by the unique and undoubtedly weird experience of being the biggest voice on the platform. Many of you know me from the sleeping bag incident where I slept on a conference room floor, so I figure, let’s talk about that too. Going viral was an odd and interesting experience. I was attacked by people on the left and called a billionaire bootlicker, while simultaneously being attacked by people on the right for being a working mom who was demonized as an example of a woman choosing her career over her family. Thankfully I can laugh at myself and I don’t take armchair keyboard ideologues too seriously. Being the main character on the timeline, even for a few minutes, requires a thick skin and a strong sense of self. The real story is pretty simple. I was given a nearly impossible deadline for his first project and as the product lead I would never ask anyone to do anything I wasn’t willing to do myself. So I worked round the clock alongside an amazing team spanning many timezones, and we delivered it on schedule – truly against the odds. It was intense but also fun. Those first few months were wildly crazy but I wanted to be there and I have no regrets. Showing up and giving it your all should, in most cases, be celebrated. Obviously you can’t work at that pace forever but there are moments where bursts are mission critical. I’ve pulled many all-nighters in my career and also when I was a student for something that mattered to me. I don’t regret putting in long hours or being ambitious, and feel proud of how far I’ve come from where I started thanks in part to that type of work ethic. I think of life as a game, and being at Twitter after the acquisition was like playing life at Level 10 on Hard Mode. Since I like taking on difficult challenges I found it interesting and rewarding because I was growing and learning so rapidly. I realize our society today trends toward polarization but when it comes to this app, its owner, and its future, I am neither a fangirl nor a hater — I’m an optimistic pragmatist. This may really irritate the internet but you cannot pigeonhole me into some radical position of either loving or hating every change that’s occurred. I escaped my fundamentalist upbringing and am a free thinker these days. Everyone can be seen as both a hero or a villain, depending on who is telling what angle of the story. Elon doesn’t deserve to be venerated or vilified. He’s a complicated person with an unfathomable amount of financial and geopolitical power which is why humanity needs him to err on the side of goodness, rather than political divisiveness and pettiness. I disagree with many of his decisions and am surprised by his willingness to burn so much down, but with enough money and time, something new & innovative may emerge. I hope it does. Sometimes I get asked about how I felt when I got laid off, and the truth is it was the best gift I’ve ever received. Sure the headlines and punchlines wrote themselves but I was battle hardened by then. I knew that I’d worked in a way where I could walk out with my head held high. I have no bitterness about the Product Management team being dismantled, and it made sense for me to exit as nearly all of the remaining PMs were let go. Going on a sabbatical afterward has been exactly what I needed to decompress and I’m finally feeling rested and relaxed. I’m a creative and a builder, so sooner than later I’ll jump back into a high intensity company but I’m grateful for this season of thinking, reading, traveling and being with people I love. After having time to reflect I believe more than ever that the very best outcomes flow from great leadership that combines the head and the heart. I’d be remiss if I didn’t note that in all of this there is also a cautionary tale for anyone who succeeds at something — which is that the higher you climb, the smaller your world becomes. It’s a strange paradox but the richest and most powerful people are also some of the most isolated. I found myself frequently looking at Elon and seeing a person who seemed quite alone because his time and energy was so purely devoted to work, which is not the model of a life I want to live. Money and fame can create psychological prisons which may worsen mental health conditions. We’ve all seen high profile cases of celebrities who end up with some combination of depression, paranoia, delusions of grandeur, mania and/or erratic behavior. Living in an echo chamber is dangerous and being at the top makes a person even more susceptible to being surrounded by yes people when nearly everyone around you is on the payroll and somehow stands to benefit from being in your orbit. Figuring out how to keep “better angels” around in the form of family, friends, and teammates is critical to staying on the rails and enduring intense ups and downs. Everyone needs to hear hard truths sometimes and if you fire all the people who speak up then the reality distortion field may just turn into a vortex. I was drawn to Twitter because I’m obsessed with the problem of loneliness and connection between people. I find it fascinating & troubling that humans are getting lonelier as we simultaneously create a world that’s both safer and wealthier. I don’t believe that trade-off has to exist, which is why I keep returning to that theme in my personal and professional life. I realize this is too long of a tweet but Twitter was a weird and special place on the internet, and I’m grateful to have played a teeny tiny role in its story and evolution. I’m here for whatever comes next — on this app and in new places. Consumer social is very much alive and at a fascinating juncture, so I’ll be watching and participating and sharing hot takes because I don’t want to, and probably can’t, turn that part of me off. Perhaps X becomes a resounding success. Or it fails epically. Either way, I expect it will continue to be a very entertaining ride. 🫡
14:49

Like seemingly everyone on this app I have plenty of opinions about Twitter > X and figure now is a good time to open up a bit about my experience at the company. I tweeted for years into the void for the love of it like many of you, but after selling my startup to Twitter in 2020 I finally got to see it from the inside. Up close it was both amazing and terrible, like so many other companies and things in life. As someone with a maniacal sense of urgency built into me, Twitter often felt siloed and bureaucratic. Dumb power plays, reorgs and team name changes for the sake of someone’s ego were distractions that occurred too regularly. You couldn’t just be a builder — you also needed to be a politician. I was shocked by how old and bespoke the infrastructure was, but there was little will to think beyond quarterly earnings calls because we were all beholden to the masters of mDAU and revenue growth as a public company. It often felt like things were held together with duct tape and glue, and that many people had just accepted that a small product change could take months or quarters to build. Management had become bloated to accommodate career growth and the company culture felt too soft and entitled for my own taste. Healthy debate and criticism was replaced by a default refrain of “no, that can’t be done” or “another team owns that so don’t touch it”. Teams could spend months building a feature and then some last-minute kerfuffle meant it’d get killed for being too risky. Just talking directly to customers could turn into a turf war and create deadlocks between functions. I recall one such episode where a teammate spent a month trying to get clearance to reach out to some creators. He went through 3 layers of management and 6 different functional teams. In the end 4 executives were involved in the approval. It was insanity, and unfortunately I saw several top performers get burnt out and demoralized after exhausting experiences like that. Most people were good at their jobs but it was nearly impossible to fire poor performers — instead they got shuffled around to other teams because few managers had the will or resources to figure out how to get them out. A high performance culture pulls everyone up, but the opposite weighs everyone down. Twitter often felt like a place that kept squandering its own potential, which was sad and frustrating to see. The person who was best at cutting through the BS and inspiring a vision during my tenure was Kayvon Beykpour, but he wasn’t fully empowered to run the company since he wasn’t the CEO. Despite those real issues, I was lucky enough to work with some of the most talented people in the business at Twitter in product, design, engineering, research, legal, BD, trust & safety, marketing, PR and more. Often it was a small cross-functional team of intrinsically motivated people who made the biggest impact by challenging some core assumption. Those teams were very fun to be on but they felt like the exception rather than the rule. The months of waiting for the deal to close in 2022 were particularly slow and painful; it felt like leadership hid behind lawyers and legal language as all answers about the company’s future notoriously included the phrase “fiduciary duty”. Colleagues openly talked about how Twitter was being sold because leadership didn’t have conviction in their own plan or ability to fix longstanding problems. Although I didn’t know much about Elon I was cautiously optimistic – I saw him as the guy who built incredible and enduring companies like Tesla and SpaceX, so perhaps his private ownership could shake things up and breathe new life into the company. My take on what’s happened since then is full of lived nuance. When people ask why I stayed it’s easy to answer: optimism, curiosity, personal growth and money. From the beginning I saw that some changes Elon was going to make were smart and others were stupid, but when I’m on a team I uphold the philosophy of “praise in public and criticize in private”. I was far from a silent wallflower. I shared my opinions openly and pushed back often, both before and after the acquisition. I made peace with the fact that I didn’t have psychological safety at Twitter 2.0 and that meant I could be fired at any moment, and for no reason at all. I watched it happen repeatedly and saw how negatively it impacted team morale. Although I couldn’t change the situation I did my best to shine a light on folks who were doing important work while being an emotionally supportive leader for those who were struggling to adapt to the more brutalist and hardcore culture. In person Elon is oddly charming and he’s genuinely funny. He also has personality quirks like telling the same stories and jokes over and over. The challenge is his personality and demeanor can turn on a dime going from excited to angry. Since it was hard to read what mood he might be in and what his reaction would be to any given thing, people quickly became afraid of being called into meetings or having to share negative news with him. At times it felt like the inner circle was too zealous and fanatical in their unwavering support of everything he said. When individuals encouraged me to be careful about what I said I politely thanked them and said I would not be taking their advice. I had no interest in adding to a culture of fear or walking on eggshells around Elon. Either he would respect me for being real or he could fire me. Either outcome was okay. I quickly learned that product and business decisions were nearly always the result of him following his gut instinct, and he didn’t seem compelled to seek out or rely on a lot of data or expertise to inform it. That was particularly frustrating for me since I believed I had useful institutional knowledge that could help him make better decisions. Instead he'd poll Twitter, ask a friend, or even ask his biographer for product advice. At times it seemed he trusted random feedback more than the people in the room who spent their lives dedicated to tackling the problem at hand. I never figured out why and remain puzzled by it. I don’t think things had to be as difficult or dramatic as they turned out to be but I can’t say I’d bet against Elon or count him out. He’s smart and has enough money to make a lot of mistakes and then course correct when things go awry. As the largest shareholder he can tank the value in the short-term, but eventually he’ll need things to turn around. His focus on speed is incredible and he’s obviously not afraid of blowing things up, but now the real measure will be how it get reconstructed and if enough people want the new everything app he is building. I learned a ton from watching Elon up close – the good, the bad and the ugly. His boldness, passion and storytelling is inspiring, but his lack of process and empathy is painful. Elon has an exceptional talent for tackling hard physics-based problems but products that facilitate human connection and communication require a different type of social-emotional intelligence. Social networks are hard to kill but they’re not immune from death spirals. Only time will tell what the outcome will be but I hope X finds its footing because competition is good for consumers. In the meantime, I have a lot of empathy for the employees who are working tirelessly behind the scenes, the advertisers who want a stable platform to sell their stuff on, and the customers who are experiencing chaotic updates. It’s been a madhouse. Twitter moved at the speed of molasses and suffered from bureaucracy but now X is run by a mercurial leader whose instinct is driven by the unique and undoubtedly weird experience of being the biggest voice on the platform. Many of you know me from the sleeping bag incident where I slept on a conference room floor, so I figure, let’s talk about that too. Going viral was an odd and interesting experience. I was attacked by people on the left and called a billionaire bootlicker, while simultaneously being attacked by people on the right for being a working mom who was demonized as an example of a woman choosing her career over her family. Thankfully I can laugh at myself and I don’t take armchair keyboard ideologues too seriously. Being the main character on the timeline, even for a few minutes, requires a thick skin and a strong sense of self. The real story is pretty simple. I was given a nearly impossible deadline for his first project and as the product lead I would never ask anyone to do anything I wasn’t willing to do myself. So I worked round the clock alongside an amazing team spanning many timezones, and we delivered it on schedule – truly against the odds. It was intense but also fun. Those first few months were wildly crazy but I wanted to be there and I have no regrets. Showing up and giving it your all should, in most cases, be celebrated. Obviously you can’t work at that pace forever but there are moments where bursts are mission critical. I’ve pulled many all-nighters in my career and also when I was a student for something that mattered to me. I don’t regret putting in long hours or being ambitious, and feel proud of how far I’ve come from where I started thanks in part to that type of work ethic. I think of life as a game, and being at Twitter after the acquisition was like playing life at Level 10 on Hard Mode. Since I like taking on difficult challenges I found it interesting and rewarding because I was growing and learning so rapidly. I realize our society today trends toward polarization but when it comes to this app, its owner, and its future, I am neither a fangirl nor a hater — I’m an optimistic pragmatist. This may really irritate the internet but you cannot pigeonhole me into some radical position of either loving or hating every change that’s occurred. I escaped my fundamentalist upbringing and am a free thinker these days. Everyone can be seen as both a hero or a villain, depending on who is telling what angle of the story. Elon doesn’t deserve to be venerated or vilified. He’s a complicated person with an unfathomable amount of financial and geopolitical power which is why humanity needs him to err on the side of goodness, rather than political divisiveness and pettiness. I disagree with many of his decisions and am surprised by his willingness to burn so much down, but with enough money and time, something new & innovative may emerge. I hope it does. Sometimes I get asked about how I felt when I got laid off, and the truth is it was the best gift I’ve ever received. Sure the headlines and punchlines wrote themselves but I was battle hardened by then. I knew that I’d worked in a way where I could walk out with my head held high. I have no bitterness about the Product Management team being dismantled, and it made sense for me to exit as nearly all of the remaining PMs were let go. Going on a sabbatical afterward has been exactly what I needed to decompress and I’m finally feeling rested and relaxed. I’m a creative and a builder, so sooner than later I’ll jump back into a high intensity company but I’m grateful for this season of thinking, reading, traveling and being with people I love. After having time to reflect I believe more than ever that the very best outcomes flow from great leadership that combines the head and the heart. I’d be remiss if I didn’t note that in all of this there is also a cautionary tale for anyone who succeeds at something — which is that the higher you climb, the smaller your world becomes. It’s a strange paradox but the richest and most powerful people are also some of the most isolated. I found myself frequently looking at Elon and seeing a person who seemed quite alone because his time and energy was so purely devoted to work, which is not the model of a life I want to live. Money and fame can create psychological prisons which may worsen mental health conditions. We’ve all seen high profile cases of celebrities who end up with some combination of depression, paranoia, delusions of grandeur, mania and/or erratic behavior. Living in an echo chamber is dangerous and being at the top makes a person even more susceptible to being surrounded by yes people when nearly everyone around you is on the payroll and somehow stands to benefit from being in your orbit. Figuring out how to keep “better angels” around in the form of family, friends, and teammates is critical to staying on the rails and enduring intense ups and downs. Everyone needs to hear hard truths sometimes and if you fire all the people who speak up then the reality distortion field may just turn into a vortex. I was drawn to Twitter because I’m obsessed with the problem of loneliness and connection between people. I find it fascinating & troubling that humans are getting lonelier as we simultaneously create a world that’s both safer and wealthier. I don’t believe that trade-off has to exist, which is why I keep returning to that theme in my personal and professional life. I realize this is too long of a tweet but Twitter was a weird and special place on the internet, and I’m grateful to have played a teeny tiny role in its story and evolution. I’m here for whatever comes next — on this app and in new places. Consumer social is very much alive and at a fascinating juncture, so I’ll be watching and participating and sharing hot takes because I don’t want to, and probably can’t, turn that part of me off. Perhaps X becomes a resounding success. Or it fails epically. Either way, I expect it will continue to be a very entertaining ride. 🫡

Esther Crawford ✨

5,501,661 views • 3 years ago