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Announcing PUFF PASS GEN 2 on Berachain Foundation 🐻⛓ Mainnet Same vape, higher mining efficiency. Wen: Q5 Where: Kingdomly 🏰 & Seoulmate Price: 0.025 ETH or 100,000 KRW (Korean Credit Card) Supply: 30,000 ⚠️ This is a non-profit sale to onboard web2 normies

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Puffpaw

65,143 subscribers

35,671 views • 1 year ago •via X (Twitter)

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Anya Rossi• Live Now

Private livecam show

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Puffpaw1 year ago

Check out our recent interview with @DecryptMedia

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Puffpaw1 year ago

1) All Genesis holders are whitelisted for GEN 2 2) All Genesis holders will have an exclusive initial time window (lasting multiple weeks) to participate in the vape-2-earn game. /// This is the end of the thread ///

Reown's profile picture
Reown1 year ago

AppKit is the full-stack toolkit to build onchain app UX 🪄 ✅ Social, Email, and Wallet Login ✅ Embedded Wallets ✅ Crypto Swaps ✅ On-ramp Integrate with just 20 lines of code across 10+ languages for all EVM chains and Solana. Onboard millions of users for free today.

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0xGeeGee1 year ago

@berachain @KingdomlyApp @seoulmate99 lmao so gen 1 is lower efficiency and we paid 4 times more?

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Puffpaw1 year ago

@berachain @KingdomlyApp @seoulmate99 Only Gen 1 will have 5% airdrop Exclusive initial time window in the game Whitelisted for gen 2

ruined.'s profile picture
ruined.1 year ago

@berachain @KingdomlyApp @seoulmate99 imajin launching a next gen that is better than the "genesis" before customers even get their gen 1

Puffpaw's profile picture
Puffpaw1 year ago

@berachain @KingdomlyApp @seoulmate99 Only Gen 1 will have 5% airdrop Exclusive initial time window in the game Whitelisted for gen 2

OxTøchi 🦇🔈's profile picture
OxTøchi 🦇🔈1 year ago

@berachain @KingdomlyApp @seoulmate99 wtf am I reading 😒

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Puffpaw1 year ago

@berachain @KingdomlyApp @seoulmate99

bigmac's profile picture
bigmac1 year ago

@berachain @KingdomlyApp @seoulmate99 what’s the point of gen 1 now then if it’s a lower efficieny model

Honey bera's profile picture
Honey bera1 year ago

@berachain @KingdomlyApp @seoulmate99 WTF

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On the latest Bitcoin News Weekly, Giacomo Loathsome Bitcoin Destroyer Zucco laid out the Bitcoin tech projects he is most excited for in 2026. Beyond payments, his vision is to fix the fundamental infrastructure of the internet and financial self-sovereignty. Here is a breakdown of the key tech projects Zucco is most excited about: 1. Fixing Internet Communication & Social Media Zucco is bullish on protocols that aim to decentralize the very fabric of how we interact online, moving away from centralized silos. Holepunch: A platform for building peer-to-peer applications without servers. Nostr: A decentralized protocol for social media and data vending that removes the power of central moderators. Keet: A peer-to-peer communication tool built on Holepunch that focuses on privacy and direct user interaction. 2. Scalable, Sovereign Identity Rather than government-mandated digital IDs, Zucco advocates for "pseudonymous identity" where users control their own keys. Economic Incentive: He notes that because Bitcoin users must learn to manage keys to protect their money, they are finally prepared for the "web of trust" models that failed in the past. 3. The "New" Lightning Network Zucco acknowledges that the current Lightning Network has "overpromised" by relying on semi-centralized nodes. He is excited about a multi-layered approach that abstracts complexity away from the user: Ark: This protocol is a major highlight for Zucco because it "batches across users" rather than just time. This allows thousands of users to achieve finality in a single on-chain transaction. Complementary Layers: He sees a "symphony" of layers, including Spark, Mercury Layer, Liquid, and Cashu, working together to make Bitcoin as easy to use as a credit card. 4. Decentralizing Bitcoin Mining To prevent censorship and "KYC mining," Zucco supports tools that return power to individual miners: OCEAN & DATUM: Projects that allow miners to create their own block templates rather than letting pools decide which transactions to include. Stratum V2: An upgraded protocol designed to increase security and efficiency in pool communication. Lightning/Ark Payouts: He is excited about mining pools using Lightning or Ark for non-custodial, high-frequency payouts to miners. 5. Smart Contracts & Assets (RGB) Zuccoo, who originally invented the RGB protocol in 2018, is excited to see its "renaissance" alongside Taproot Assets. Client-Side Validation: RGB allows for smart contracts and tokens (like Tether) to exist on Bitcoin without bloating the blockchain or requiring new tokens to function. Reduction of Harm: He believes that if people insist on using stablecoins or tokens, doing so on RGB strengthens Bitcoin's privacy and liquidity rather than damaging it.
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On the latest Bitcoin News Weekly, Giacomo Loathsome Bitcoin Destroyer Zucco laid out the Bitcoin tech projects he is most excited for in 2026. Beyond payments, his vision is to fix the fundamental infrastructure of the internet and financial self-sovereignty. Here is a breakdown of the key tech projects Zucco is most excited about: 1. Fixing Internet Communication & Social Media Zucco is bullish on protocols that aim to decentralize the very fabric of how we interact online, moving away from centralized silos. Holepunch: A platform for building peer-to-peer applications without servers. Nostr: A decentralized protocol for social media and data vending that removes the power of central moderators. Keet: A peer-to-peer communication tool built on Holepunch that focuses on privacy and direct user interaction. 2. Scalable, Sovereign Identity Rather than government-mandated digital IDs, Zucco advocates for "pseudonymous identity" where users control their own keys. Economic Incentive: He notes that because Bitcoin users must learn to manage keys to protect their money, they are finally prepared for the "web of trust" models that failed in the past. 3. The "New" Lightning Network Zucco acknowledges that the current Lightning Network has "overpromised" by relying on semi-centralized nodes. He is excited about a multi-layered approach that abstracts complexity away from the user: Ark: This protocol is a major highlight for Zucco because it "batches across users" rather than just time. This allows thousands of users to achieve finality in a single on-chain transaction. Complementary Layers: He sees a "symphony" of layers, including Spark, Mercury Layer, Liquid, and Cashu, working together to make Bitcoin as easy to use as a credit card. 4. Decentralizing Bitcoin Mining To prevent censorship and "KYC mining," Zucco supports tools that return power to individual miners: OCEAN & DATUM: Projects that allow miners to create their own block templates rather than letting pools decide which transactions to include. Stratum V2: An upgraded protocol designed to increase security and efficiency in pool communication. Lightning/Ark Payouts: He is excited about mining pools using Lightning or Ark for non-custodial, high-frequency payouts to miners. 5. Smart Contracts & Assets (RGB) Zuccoo, who originally invented the RGB protocol in 2018, is excited to see its "renaissance" alongside Taproot Assets. Client-Side Validation: RGB allows for smart contracts and tokens (like Tether) to exist on Bitcoin without bloating the blockchain or requiring new tokens to function. Reduction of Harm: He believes that if people insist on using stablecoins or tokens, doing so on RGB strengthens Bitcoin's privacy and liquidity rather than damaging it.

Bitcoin News

13,054 views • 6 months ago

Every time I speak or listen to Shashi Kumar from Akshayakalpa Organic, I learn something new about food, health, and sustainability. A few things I learned recently: 1. Antibiotic resistance is a global health threat. Due to overuse, germs have become resistant to antibiotics, leading to health complications and deaths. The non-obvious way in which we ingest antibiotics is through dairy and meat. For example, cows that are always tied down tend to catch diseases quickly, and the use of antibiotics becomes necessary to treat them. If a cow is treated with antibiotics, 40% of it shows up in the milk. 2. Death of bees Bees are excellent pollinators, and beekeeping on AK farms has considerably increased coconut yields. Unfortunately, most bee colonies die due to the use of pesticides, habitat loss, and parasites. 3. Loss of organic carbon Organic carbon in soil has dropped to an alarming low of 1%. It needs to be much higher for sustainable farming. The lower the organic carbon content, the lower the fertility of the soil, and the lower the nutrition profile of the produce. An orange from 50 years ago had a much better nutrition profile than today's. For example, one orange from then is better than three oranges today. One way to increase the organic carbon in the soil is to move to more sustainable practices when farming, i.e., organic farming. But today, subsidies on fertilizers and seeds make organic more expensive. Also, consumer support doesn’t exist; maybe if consumers cared about the nutrition profile of what we consume, there would be more demand for organic, and at scale, the price could also drop. AK farms are at 3.6%, took 13 years. We have to change this trend. Maybe it will if younger and more educated folks take up farming and such conversations become mainstream. Farmers definitely need to be able to keep higher margins on their produce and need easy access to credit. AK is trying to solve some of these issues. Akshayakalpa Organic is one of our most exciting partnerships through Rainmatter by Zerodha. Watch this conversation (full conversation on the Rainmatter foundation Youtube channel), where Shashi talks about food, farming, and much more.
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Every time I speak or listen to Shashi Kumar from Akshayakalpa Organic, I learn something new about food, health, and sustainability. A few things I learned recently: 1. Antibiotic resistance is a global health threat. Due to overuse, germs have become resistant to antibiotics, leading to health complications and deaths. The non-obvious way in which we ingest antibiotics is through dairy and meat. For example, cows that are always tied down tend to catch diseases quickly, and the use of antibiotics becomes necessary to treat them. If a cow is treated with antibiotics, 40% of it shows up in the milk. 2. Death of bees Bees are excellent pollinators, and beekeeping on AK farms has considerably increased coconut yields. Unfortunately, most bee colonies die due to the use of pesticides, habitat loss, and parasites. 3. Loss of organic carbon Organic carbon in soil has dropped to an alarming low of 1%. It needs to be much higher for sustainable farming. The lower the organic carbon content, the lower the fertility of the soil, and the lower the nutrition profile of the produce. An orange from 50 years ago had a much better nutrition profile than today's. For example, one orange from then is better than three oranges today. One way to increase the organic carbon in the soil is to move to more sustainable practices when farming, i.e., organic farming. But today, subsidies on fertilizers and seeds make organic more expensive. Also, consumer support doesn’t exist; maybe if consumers cared about the nutrition profile of what we consume, there would be more demand for organic, and at scale, the price could also drop. AK farms are at 3.6%, took 13 years. We have to change this trend. Maybe it will if younger and more educated folks take up farming and such conversations become mainstream. Farmers definitely need to be able to keep higher margins on their produce and need easy access to credit. AK is trying to solve some of these issues. Akshayakalpa Organic is one of our most exciting partnerships through Rainmatter by Zerodha. Watch this conversation (full conversation on the Rainmatter foundation Youtube channel), where Shashi talks about food, farming, and much more.

Nithin Kamath

244,549 views • 2 years ago

$AMD $5 Trillion MC Is Inevitable Long Term👑 This thread will focus more on Inference! 2026 EPYC "Venice" $TSM 2nm to save Large GW Scale Inference by 40% more than Prior Turin gen. Context: EPYC Turin achieves ~$0.001 per million tokens for batch inference vs $0.02-$0.12/ million tokens as I wrote the thread below. Venice is going to lower cost down to $0.0005-$0.0006/Million Tokens. OpenAI spent roughly $20B on Inference and Training, where 80-90% of that was for Inference per Analysts. AKA Renting Compute is Expensive AF! In this thread, I want to focus on why most analysts and investors are underestimating the role EPYC "Venice" and future Gen on overall Data center revenue. And $TSM ramping up 2nm supply early is a confirmation that AMD will be a major buyer long term. I will also link the thread the Gap between AMD Analysts & Reality and 2nm Ramp Thread so you have more comprehensive view of what I'm writing here. Before I go into detail this is my 2026 Projection: AI GPUs: $35-$50B EPYC Data Center: $15B-$17B Client Segment: $12-$13B Gaming: $6B Embedded: $4B-$5B Total Revenue $70-$100B Non-GAAP net income $18B-$25B Non-GAAP EPS $10.97-$15.40 Foward P/E 55x-70x= $603-$1,078 AMD's Analysts are projecting $0 Revenue for MI450 and sluggish EPYC Growth. Meaning, all analysts are either full of 💩 or Sexist, you decide! Analysts are also projecting 0% growth on AMD "Secret Weapon" Chip as $MSFT said we are at significant Windows refresh and upgrade cycle. Do you think TSMC would allocate more 2nm supply to $AMD at $0 MI450 revenue and sluggish EPYC? 1. EPYC is going to be the leader in lowest Inference! Current Turin cost saving is 95% vs $NVDA or 98-99% on Inference cost when you factor in renting Inference compute from Amazon Web Services, Microsoft Azure, or $NVDA Neocloud pets. TSMC claimed: 10-15% higher performance at iso-power, 25-30% lower power at iso-speed, and ~15% higher transistor density compared to 3nm. This reduces operational expenses (energy, cooling) while increasing throughput per chip. EPYC Turin achieves ~$0.001 per million tokens for batch inference (via vLLM on models like Llama 3 70B), driven by high core counts and low hardware costs. EPYC Venice offers ~1.7x overall performance and up to 70% more compute capability per core, with up to 256 cores (512 threads). Enhanced vector/AI instructions and open-source firmware (openSIL) optimize for inference workloads. AMD Incorporates AI Engines (now part of AMD's XDNA) for on-chip acceleration, improving efficiency for low-latency and edge inference. This reduces reliance on discrete GPUs, lowering system complexity and TCO. Venice SKUs are projected at $3,000-$15,000 ($5,000 for 256-core flagship), far below NVIDIA Rubin ($50,000-$90,000) or AMD's own MI450 GPUs ($40,000-$50,000). High memory bandwidth (up to 1.6 TB/s) supports efficient batch inference. Venice is designed exactly for Large customers that want to lower Inference Cost and MI450 Helios is for Customers that want Training at lowest TCO, TDP as well as lower Upfront 1GW scale(Full build $35-$40B vs $NVDA $55B-$80B). 2. Real World Example: OpenAI's 2025 inference spend reached ~$20B, escalating to even higher total compute rental (mostly inference) amid token volume growth(from video generating). By 2026, with usage doubling (consistent with industry trends: token demand grows 2-5x YoY), assume OpenAI processes ~1,800 billion million-tokens annually $NVDA Blackwell at $0.02-$0.12 is $36B(most optimized) Rubin is projected to be at $0.01/million tokens or $18B annual Inference Cost vs $AMD Venice $0.0005/million tokens or $0.9B annual Inference Cost => Massive saving for OpenAI or anyone that are paying 80-90% Annual Bill for Inference compute. In short, it is unsustainable to pay this much rent vs owning for all current AI players for the medium to long term. Rubin excels in low-latency decode (if Groq integration from $20B deal in 2027-2028), but Venice dominates batch (80% of inference by 2030). Actual savings depend on deployment scale (OpenAI's 6GW AMD plans), electricity rates, and software maturity. If Rubin only hits $0.03, savings swell to $53.1B vs. $17.1B. 3. Will running Inference on Venice and future Gen slow down response generation in 2026 and beyond? Human perception of "fast enough" for chat, agents, search augmentation, summarization, coding assistance is roughly Meaning, EPYC may generate $100B a year on data center revenue, Hence $MSFT $AMZN $META $GOOGL OpenAI xAI and 42+ Countries are leaning AMD for Inference, because the cost saving is MASSIVE! 4. Regular users (you, me, people using ChatGPT, Claude, Gemini, Grok, Perplexity...) are extremely unlikely to notice any slowdown and in many cases might even experience slightly faster or more consistent response times if the industry heavily shifts toward AMD EPYC for inference. What actually happens when companies save massively on inference? When OpenAI , Anthropic , Gemini , Grok Meta .... save billions on the batch/enterprise/RAG layer using EPYC Venice, they typically do one or more of these things with the savings, none of which make your chat slower but enhancing their bottom line(Profit) ~Keep prices the same → make more profit ~Lower subscription prices / increase free tier limits ~Train bigger & better models more frequently ~Offer longer context windows ~Add more reasoning steps / tool calls / agents per query ~Improve multimodal capabilities ~Build more data centers / reduce throttling during peaks In practice the consumer experience usually gets better, not worse, when inference becomes dramatically cheaper. Prime example is $META leaning AMD heavily or currently AMD largest customer. or Grok 2 to Grok 3 heavily used AMD for Inference saving. And most Grok Users reported Groke responses snappier, not slower. 5. What does this mean for potential Revenue? Noted that TSMC is massively ramping 2nm supply for $AMD both MI450 and EPYC. EPYC Conservative projection: FY2025: $10.5B(best Est) FY2026: $16B FY2027: $29B FY2028: $49B FY2029: $75B FY2030: $100B Large customers: $META OpenAI $MSFT $AMZN $GOOGL xAI (Apple?) Smaller customer: $DELL $HPE $SMCI and 42+ other countries. The roadmap to $5 Trillion is very much inevitable as Inference Cost from Renting or owning $NVDA are too high, but $NVDA will still dominate Training market share, where MI families are likely to take 15-20% market share, but the TAM is also expanding Rapidly. Most Institutions are projecting $2-$3Trillion TAM by 2030. $NVDA said $4 Trillion. Dr. Lisa Su said $1 Trillion+ by 2030. So you decide on how much TAM. If you enjoy this kind of analysis, Slap the Like/Repost and Bookmark to please the X Algo as it is Free.99! If you want to support my work further, consider subscribe to see more in-depth analysis! Alright, that is it. Not Financial Advice!
3:09

$AMD $5 Trillion MC Is Inevitable Long Term👑 This thread will focus more on Inference! 2026 EPYC "Venice" $TSM 2nm to save Large GW Scale Inference by 40% more than Prior Turin gen. Context: EPYC Turin achieves ~$0.001 per million tokens for batch inference vs $0.02-$0.12/ million tokens as I wrote the thread below. Venice is going to lower cost down to $0.0005-$0.0006/Million Tokens. OpenAI spent roughly $20B on Inference and Training, where 80-90% of that was for Inference per Analysts. AKA Renting Compute is Expensive AF! In this thread, I want to focus on why most analysts and investors are underestimating the role EPYC "Venice" and future Gen on overall Data center revenue. And $TSM ramping up 2nm supply early is a confirmation that AMD will be a major buyer long term. I will also link the thread the Gap between AMD Analysts & Reality and 2nm Ramp Thread so you have more comprehensive view of what I'm writing here. Before I go into detail this is my 2026 Projection: AI GPUs: $35-$50B EPYC Data Center: $15B-$17B Client Segment: $12-$13B Gaming: $6B Embedded: $4B-$5B Total Revenue $70-$100B Non-GAAP net income $18B-$25B Non-GAAP EPS $10.97-$15.40 Foward P/E 55x-70x= $603-$1,078 AMD's Analysts are projecting $0 Revenue for MI450 and sluggish EPYC Growth. Meaning, all analysts are either full of 💩 or Sexist, you decide! Analysts are also projecting 0% growth on AMD "Secret Weapon" Chip as $MSFT said we are at significant Windows refresh and upgrade cycle. Do you think TSMC would allocate more 2nm supply to $AMD at $0 MI450 revenue and sluggish EPYC? 1. EPYC is going to be the leader in lowest Inference! Current Turin cost saving is 95% vs $NVDA or 98-99% on Inference cost when you factor in renting Inference compute from Amazon Web Services, Microsoft Azure, or $NVDA Neocloud pets. TSMC claimed: 10-15% higher performance at iso-power, 25-30% lower power at iso-speed, and ~15% higher transistor density compared to 3nm. This reduces operational expenses (energy, cooling) while increasing throughput per chip. EPYC Turin achieves ~$0.001 per million tokens for batch inference (via vLLM on models like Llama 3 70B), driven by high core counts and low hardware costs. EPYC Venice offers ~1.7x overall performance and up to 70% more compute capability per core, with up to 256 cores (512 threads). Enhanced vector/AI instructions and open-source firmware (openSIL) optimize for inference workloads. AMD Incorporates AI Engines (now part of AMD's XDNA) for on-chip acceleration, improving efficiency for low-latency and edge inference. This reduces reliance on discrete GPUs, lowering system complexity and TCO. Venice SKUs are projected at $3,000-$15,000 ($5,000 for 256-core flagship), far below NVIDIA Rubin ($50,000-$90,000) or AMD's own MI450 GPUs ($40,000-$50,000). High memory bandwidth (up to 1.6 TB/s) supports efficient batch inference. Venice is designed exactly for Large customers that want to lower Inference Cost and MI450 Helios is for Customers that want Training at lowest TCO, TDP as well as lower Upfront 1GW scale(Full build $35-$40B vs $NVDA $55B-$80B). 2. Real World Example: OpenAI's 2025 inference spend reached ~$20B, escalating to even higher total compute rental (mostly inference) amid token volume growth(from video generating). By 2026, with usage doubling (consistent with industry trends: token demand grows 2-5x YoY), assume OpenAI processes ~1,800 billion million-tokens annually $NVDA Blackwell at $0.02-$0.12 is $36B(most optimized) Rubin is projected to be at $0.01/million tokens or $18B annual Inference Cost vs $AMD Venice $0.0005/million tokens or $0.9B annual Inference Cost => Massive saving for OpenAI or anyone that are paying 80-90% Annual Bill for Inference compute. In short, it is unsustainable to pay this much rent vs owning for all current AI players for the medium to long term. Rubin excels in low-latency decode (if Groq integration from $20B deal in 2027-2028), but Venice dominates batch (80% of inference by 2030). Actual savings depend on deployment scale (OpenAI's 6GW AMD plans), electricity rates, and software maturity. If Rubin only hits $0.03, savings swell to $53.1B vs. $17.1B. 3. Will running Inference on Venice and future Gen slow down response generation in 2026 and beyond? Human perception of "fast enough" for chat, agents, search augmentation, summarization, coding assistance is roughly Meaning, EPYC may generate $100B a year on data center revenue, Hence $MSFT $AMZN $META $GOOGL OpenAI xAI and 42+ Countries are leaning AMD for Inference, because the cost saving is MASSIVE! 4. Regular users (you, me, people using ChatGPT, Claude, Gemini, Grok, Perplexity...) are extremely unlikely to notice any slowdown and in many cases might even experience slightly faster or more consistent response times if the industry heavily shifts toward AMD EPYC for inference. What actually happens when companies save massively on inference? When OpenAI , Anthropic , Gemini , Grok Meta .... save billions on the batch/enterprise/RAG layer using EPYC Venice, they typically do one or more of these things with the savings, none of which make your chat slower but enhancing their bottom line(Profit) ~Keep prices the same → make more profit ~Lower subscription prices / increase free tier limits ~Train bigger & better models more frequently ~Offer longer context windows ~Add more reasoning steps / tool calls / agents per query ~Improve multimodal capabilities ~Build more data centers / reduce throttling during peaks In practice the consumer experience usually gets better, not worse, when inference becomes dramatically cheaper. Prime example is $META leaning AMD heavily or currently AMD largest customer. or Grok 2 to Grok 3 heavily used AMD for Inference saving. And most Grok Users reported Groke responses snappier, not slower. 5. What does this mean for potential Revenue? Noted that TSMC is massively ramping 2nm supply for $AMD both MI450 and EPYC. EPYC Conservative projection: FY2025: $10.5B(best Est) FY2026: $16B FY2027: $29B FY2028: $49B FY2029: $75B FY2030: $100B Large customers: $META OpenAI $MSFT $AMZN $GOOGL xAI (Apple?) Smaller customer: $DELL $HPE $SMCI and 42+ other countries. The roadmap to $5 Trillion is very much inevitable as Inference Cost from Renting or owning $NVDA are too high, but $NVDA will still dominate Training market share, where MI families are likely to take 15-20% market share, but the TAM is also expanding Rapidly. Most Institutions are projecting $2-$3Trillion TAM by 2030. $NVDA said $4 Trillion. Dr. Lisa Su said $1 Trillion+ by 2030. So you decide on how much TAM. If you enjoy this kind of analysis, Slap the Like/Repost and Bookmark to please the X Algo as it is Free.99! If you want to support my work further, consider subscribe to see more in-depth analysis! Alright, that is it. Not Financial Advice!

Mike

102,223 views • 6 months ago

** Call to Action for Global Pioneers: Uniting Efforts to Stabilize the GCV Price in the Exchange Market** Dear Global Pioneers, We are currently at a critical juncture that may determine our ability to swiftly realize the GCV in the exchange market. As of now, we are in the Open Network phase, which serves as a preparatory stage for a fully decentralized network where all code can be activated. It is important to note that the Pi Network has not registered as a security because it aims to function as a digital currency rather than a digital asset. However, given recent list on the exchange market, compliance with the United States Securities and Exchange Commission (SEC) is now necessary for Pi Network, which subsequently require CT not to guide Pi's price in the exchange market. To address this situation, we urge all pioneers to unite in a call auction to ensure the GCV is stabilized as soon as possible. We implore you not to sell below the GCV price. Conversely, you are encouraged to buy if you have the means, as the current prices are significantly low. It is essential to emphasize that we are now in the Open Network phase, permitting both buying and selling. We have observed that many pioneers may be hesitant to make purchases; however, it is imperative that you do not let this concern deter you. We have surpassed the enclosed mainnet phase, where buying and selling were prohibited. Increasing liquidity in the exchange market is crucial for attracting external investors. At this stage, the combined strength of all pioneers is required to enhance purchasing power and to capitalize on lower prices. Please clarify your understanding of our current pricing situation. The existing market prices do not reflect Pi's value of our source code, which is derived from our blockchain record. Our efforts have previously focused on establishing Pi as a digital currency, culminating in the creation of the GCV blockchain record, which has indeed achieved success. For instance, the GitHub record indicates a GCV of $314,159, and Mr. Kasasih's code fork has now been integrated into the CT’s main bran code of the signifying its official status. The rationale for the current low prices in the exchange market stems, in part, from a lack of awareness among many pioneers, some of whom may be in financially constrained positions and require immediate funds for necessities. Such individuals may be misled by those who do not support GCV's potential, thereby selling their holdings at depressed prices. This underscores the importance of CT's control over KYC processes and migration procedures. Allowing all pioneers pass KYC and migrating Pi could lead to detrimental outcomes for the project, as uninformed pioneers may sell at significantly low prices. Just we see right now there are a lot of pioneers sell at very low price. So, CT only allow 10 million wallets migrated. It is important to recognize that the current low pricing is not the fault of the PCT or GCV CT, it is a consequence of a collective lack of proactive engagement from the pioneers. By promoting education on the true value of Pi as GCV, we can mitigate the prevalence of low-price sellers. While complaints about pricing may arise, it is essential to understand that we cannot prevent pioneers from selling. What we can do is purchase the available low-priced offerings from the market and collectively urge all pioneers not to sell below the GCV price. This remains a top priority for all involved if we aim to achieve the OM status swiftly. Additionally, it is vital to understand that the CT cannot announce the price of Pi in the exchange market, nor can they buy all the Pi in the exchange market. The price must ultimately be determined by the actions of our pioneering community and outside investors. Therefore, it is everyone's responsibility to refrain from complaints and instead focus on advancing the project collectively. We recommend all pioneers take the following actions: - Do not sell below $314,159. Please list selling price at $314,159. You should have confidence on GCV when it has been in the code already. Once the OM completed; all ecosystems will implement GCV. And you don’t need to wait long time and I estimate in one month or less. - Consider purchasing if you have extra funds available but ensure that you are not borrowing money or using essential living funds for these investments. Any amount such as $10 or $20 or $100 you choose to invest can contribute to increasing the visibility of Pi in the exchange market, potentially attracting outside investors. Also, many pioneers have locked three years with 100%, it is a good chance. You can acquire 6 Pi for just $10 right now. Once our pioneers warm up the market, you'll see outside investors becoming active, so there's no need to worry about how long or how much funding it will take to reach GCV. As soon as the low-priced Pi are being purchased, the price is poised to surge from just a few dollars to GCV in no time. We won't follow the traditional cryptocurrency path for growth because we have a strong community backing GCV.` It is crucial for all global pioneers to recognize that we are all collectively striving towards the successful realization of the OM. The CT shares this goal as well. However, if the exchange market price remains as low as $1 or $2, the likelihood of merchants joining the Pi Network diminishes. It is imperative that the gap between the ecosystem's Pi value and its exchange market price remain minimal. If the exchange price is low, it inhibits the CT's ability to fulfill ecosystem objectives. You need not worry about protracted timelines. With collective action, the path to achieving GCV can be expedited. While it would indeed be beneficial for the CT to manage arrangements efficiently, it is vital that we do not adopt a passive stance, awaiting resolutions. Delays could adversely affect both the reputation of PCT and the GCV CT. Lastly, I would like to address recent rumors suggesting that pioneers are unable to transfer Pi to or from the exchange market; this information is misleading. Pi Network is indeed open already, and the CT has verified five exchange markets for transactions. I have personally encountered challenges while attempting to purchase 1,000 Pi on the exchange market, with multiple platforms rejecting my credit and debit card payments. Nonetheless, I firmly believe that this represents a valuable investment opportunity critical for advancing our collective mission toward GCV unification in the exchange market. Your understanding of this message and prompt actions will be appreciated as we move forward together. Best regards, Doris Yin🪷🪷🪷 Founder, Global GCV Movement Feb.23rd, 2025
11:55

** Call to Action for Global Pioneers: Uniting Efforts to Stabilize the GCV Price in the Exchange Market** Dear Global Pioneers, We are currently at a critical juncture that may determine our ability to swiftly realize the GCV in the exchange market. As of now, we are in the Open Network phase, which serves as a preparatory stage for a fully decentralized network where all code can be activated. It is important to note that the Pi Network has not registered as a security because it aims to function as a digital currency rather than a digital asset. However, given recent list on the exchange market, compliance with the United States Securities and Exchange Commission (SEC) is now necessary for Pi Network, which subsequently require CT not to guide Pi's price in the exchange market. To address this situation, we urge all pioneers to unite in a call auction to ensure the GCV is stabilized as soon as possible. We implore you not to sell below the GCV price. Conversely, you are encouraged to buy if you have the means, as the current prices are significantly low. It is essential to emphasize that we are now in the Open Network phase, permitting both buying and selling. We have observed that many pioneers may be hesitant to make purchases; however, it is imperative that you do not let this concern deter you. We have surpassed the enclosed mainnet phase, where buying and selling were prohibited. Increasing liquidity in the exchange market is crucial for attracting external investors. At this stage, the combined strength of all pioneers is required to enhance purchasing power and to capitalize on lower prices. Please clarify your understanding of our current pricing situation. The existing market prices do not reflect Pi's value of our source code, which is derived from our blockchain record. Our efforts have previously focused on establishing Pi as a digital currency, culminating in the creation of the GCV blockchain record, which has indeed achieved success. For instance, the GitHub record indicates a GCV of $314,159, and Mr. Kasasih's code fork has now been integrated into the CT’s main bran code of the signifying its official status. The rationale for the current low prices in the exchange market stems, in part, from a lack of awareness among many pioneers, some of whom may be in financially constrained positions and require immediate funds for necessities. Such individuals may be misled by those who do not support GCV's potential, thereby selling their holdings at depressed prices. This underscores the importance of CT's control over KYC processes and migration procedures. Allowing all pioneers pass KYC and migrating Pi could lead to detrimental outcomes for the project, as uninformed pioneers may sell at significantly low prices. Just we see right now there are a lot of pioneers sell at very low price. So, CT only allow 10 million wallets migrated. It is important to recognize that the current low pricing is not the fault of the PCT or GCV CT, it is a consequence of a collective lack of proactive engagement from the pioneers. By promoting education on the true value of Pi as GCV, we can mitigate the prevalence of low-price sellers. While complaints about pricing may arise, it is essential to understand that we cannot prevent pioneers from selling. What we can do is purchase the available low-priced offerings from the market and collectively urge all pioneers not to sell below the GCV price. This remains a top priority for all involved if we aim to achieve the OM status swiftly. Additionally, it is vital to understand that the CT cannot announce the price of Pi in the exchange market, nor can they buy all the Pi in the exchange market. The price must ultimately be determined by the actions of our pioneering community and outside investors. Therefore, it is everyone's responsibility to refrain from complaints and instead focus on advancing the project collectively. We recommend all pioneers take the following actions: - Do not sell below $314,159. Please list selling price at $314,159. You should have confidence on GCV when it has been in the code already. Once the OM completed; all ecosystems will implement GCV. And you don’t need to wait long time and I estimate in one month or less. - Consider purchasing if you have extra funds available but ensure that you are not borrowing money or using essential living funds for these investments. Any amount such as $10 or $20 or $100 you choose to invest can contribute to increasing the visibility of Pi in the exchange market, potentially attracting outside investors. Also, many pioneers have locked three years with 100%, it is a good chance. You can acquire 6 Pi for just $10 right now. Once our pioneers warm up the market, you'll see outside investors becoming active, so there's no need to worry about how long or how much funding it will take to reach GCV. As soon as the low-priced Pi are being purchased, the price is poised to surge from just a few dollars to GCV in no time. We won't follow the traditional cryptocurrency path for growth because we have a strong community backing GCV.` It is crucial for all global pioneers to recognize that we are all collectively striving towards the successful realization of the OM. The CT shares this goal as well. However, if the exchange market price remains as low as $1 or $2, the likelihood of merchants joining the Pi Network diminishes. It is imperative that the gap between the ecosystem's Pi value and its exchange market price remain minimal. If the exchange price is low, it inhibits the CT's ability to fulfill ecosystem objectives. You need not worry about protracted timelines. With collective action, the path to achieving GCV can be expedited. While it would indeed be beneficial for the CT to manage arrangements efficiently, it is vital that we do not adopt a passive stance, awaiting resolutions. Delays could adversely affect both the reputation of PCT and the GCV CT. Lastly, I would like to address recent rumors suggesting that pioneers are unable to transfer Pi to or from the exchange market; this information is misleading. Pi Network is indeed open already, and the CT has verified five exchange markets for transactions. I have personally encountered challenges while attempting to purchase 1,000 Pi on the exchange market, with multiple platforms rejecting my credit and debit card payments. Nonetheless, I firmly believe that this represents a valuable investment opportunity critical for advancing our collective mission toward GCV unification in the exchange market. Your understanding of this message and prompt actions will be appreciated as we move forward together. Best regards, Doris Yin🪷🪷🪷 Founder, Global GCV Movement Feb.23rd, 2025

Doris Yin 东方紫莲🪷

143,075 views • 1 year 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🪷

17,590 views • 11 months ago

Announcing the 2025 Hackathon & GCV Update Happy Saturday, Global Pioneers and Global GCV Ambassadors! This is Doris Yin from Toronto, Canada. How are you doing? I hope everything is going well. Today, I want to share the Core Team announcement about the 2025 Hackathon. The prizes are: First prize: 75,000 Pi Second prize: 45,000 Pi Third prize: 15,000 Pi I know some of you may feel discouraged about GCV because CT uses exchange price for prize. , but there’s no need to worry. Let me explain why. This does not mean GCV has failed, nor does it mean the Core Team supports a low Pi value. As I mentioned before, we have two methods, two paths to strengthen GCV. The first path is offline GCV. This is very important. We still need to implement partial Pi payments at GCV offline, and more merchants are joining in. They appreciate it because it helps local businesses grow. This is already happening in countries like China, Vietnam, the Philippines, Indonesia, Malaysia, Thailand, and India. We can also observe more GCV data being recorded on the blockchain, which is essential to OM fix Pi value. Instead of the Pi value coming from the exchange market, it comes from the community-driven process. You can see this reflected in the blockchain records. Our social media, groups, communities, and education efforts help pioneers recognize and acknowledge the Pi value and GCV. However, we also need online utilities and DApps. This will increase actual usage of Pi after the Open Mainnet. So we have two parts: 1. Value confirmation: We must continue building and creating more GCV data. 2. DApps and utilities usage: We need higher-quality DApps widely usage to guarantee and protect GCV. Currently, DApps are limited and mostly from pioneers, not professionals. We need good-quality DApps. If the Core Team were to simply give a prize of one Pi, it wouldn’t motivate developers—especially top developers inside and outside the community. To truly motivate them, we must use the exchange market price to attract the highest-level developers. For example, the first prize of 75,000 Pi is roughly 20,000–30,000 USD. That’s a meaningful incentive now, and in the future, it could be even higher. Developers can also see the future value of Pi, not just the current 30 cents, which encourages high-quality development. As we develop more, it supports the full realization of GCV. Offline partial Pi payments, partial fiat payments, and industrial alliances in different countries attract more participants. Online, using exchange market price to increase demand and reduce Pi selling pressure, helping to keep the price steadily increasing. When pioneers spend Pi on items, it reduces the circulating supply, creating scarcity, which is positive for the Pi Network and GCV. Some anti-GCV voices laugh and say “GCV has failed,” but they laughed too early because the CT strategy is helping GCV. Even these early critics help GCV by increasing awareness and adoption. I will also write articles to explain this further for everyone. Regarding the Core Team: it wouldn’t make sense for them to target only 30 cents. Their goal is GCV because any project owner wants their product or service to be meaningful and valuable. A higher Pi value is good for the ecosystem. GCV can support the Pi Network long-term, possibly 100 years or even 1,000 years. We don’t have hundreds of billions of Pi in circulation—currently, only about 2 billion exist. When fully released, it will take time, and the value will continue to grow. I hope everyone understands. Happy Saturday! Enjoy your day, keep working, and help the community. I also hope our GCV Ambassadors actively participate in the 2025 Hackathon. Thank you, and goodbye for now! Doris Yin 🪷 🪷🪷 Founder, Global GCV Movement August 16th, 2025
6:41

Announcing the 2025 Hackathon & GCV Update Happy Saturday, Global Pioneers and Global GCV Ambassadors! This is Doris Yin from Toronto, Canada. How are you doing? I hope everything is going well. Today, I want to share the Core Team announcement about the 2025 Hackathon. The prizes are: First prize: 75,000 Pi Second prize: 45,000 Pi Third prize: 15,000 Pi I know some of you may feel discouraged about GCV because CT uses exchange price for prize. , but there’s no need to worry. Let me explain why. This does not mean GCV has failed, nor does it mean the Core Team supports a low Pi value. As I mentioned before, we have two methods, two paths to strengthen GCV. The first path is offline GCV. This is very important. We still need to implement partial Pi payments at GCV offline, and more merchants are joining in. They appreciate it because it helps local businesses grow. This is already happening in countries like China, Vietnam, the Philippines, Indonesia, Malaysia, Thailand, and India. We can also observe more GCV data being recorded on the blockchain, which is essential to OM fix Pi value. Instead of the Pi value coming from the exchange market, it comes from the community-driven process. You can see this reflected in the blockchain records. Our social media, groups, communities, and education efforts help pioneers recognize and acknowledge the Pi value and GCV. However, we also need online utilities and DApps. This will increase actual usage of Pi after the Open Mainnet. So we have two parts: 1. Value confirmation: We must continue building and creating more GCV data. 2. DApps and utilities usage: We need higher-quality DApps widely usage to guarantee and protect GCV. Currently, DApps are limited and mostly from pioneers, not professionals. We need good-quality DApps. If the Core Team were to simply give a prize of one Pi, it wouldn’t motivate developers—especially top developers inside and outside the community. To truly motivate them, we must use the exchange market price to attract the highest-level developers. For example, the first prize of 75,000 Pi is roughly 20,000–30,000 USD. That’s a meaningful incentive now, and in the future, it could be even higher. Developers can also see the future value of Pi, not just the current 30 cents, which encourages high-quality development. As we develop more, it supports the full realization of GCV. Offline partial Pi payments, partial fiat payments, and industrial alliances in different countries attract more participants. Online, using exchange market price to increase demand and reduce Pi selling pressure, helping to keep the price steadily increasing. When pioneers spend Pi on items, it reduces the circulating supply, creating scarcity, which is positive for the Pi Network and GCV. Some anti-GCV voices laugh and say “GCV has failed,” but they laughed too early because the CT strategy is helping GCV. Even these early critics help GCV by increasing awareness and adoption. I will also write articles to explain this further for everyone. Regarding the Core Team: it wouldn’t make sense for them to target only 30 cents. Their goal is GCV because any project owner wants their product or service to be meaningful and valuable. A higher Pi value is good for the ecosystem. GCV can support the Pi Network long-term, possibly 100 years or even 1,000 years. We don’t have hundreds of billions of Pi in circulation—currently, only about 2 billion exist. When fully released, it will take time, and the value will continue to grow. I hope everyone understands. Happy Saturday! Enjoy your day, keep working, and help the community. I also hope our GCV Ambassadors actively participate in the 2025 Hackathon. Thank you, and goodbye for now! Doris Yin 🪷 🪷🪷 Founder, Global GCV Movement August 16th, 2025

Doris Yin 东方紫莲🪷

28,870 views • 11 months ago

$AMD $5 Trillion is Inevitable LT| Agentic AI🧵 Agentic AI is the new $5 Trillion TAM 🚨🚨🚨 This thead will do Comp with $INTC and how to quantify this massive Agentic AI demand spike, and forcing Jensen to rush a CPU design. Global Agentic AI Market size is estimated to be $3-$5Trillion TAM by 2030(McKinsey) Quantifying the demand from agentic AI for AMD involves assessing the broader market growth for agentic systems, their unique computational requirements (particularly for CPUs in orchestration and reasoning tasks), and AMD's positioning very well through products like EPYC processors and partnerships. AMD EPYC Venice is the most superior choice in 2026-2027 for most Agentic AI workloads Agentic AI refers to autonomous AI agents that perform multi-step tasks, involving sequential logic, tool integration, and decision-making workloads that heavily rely on CPUs for handling orchestration, memory management, and context switching, rather than just GPU-parallelized training or batch inference. Agentic AI is often cited as 40-100x more "hungry" than traditional AI due to its continuous, 24/7 operation and complex workflows. This stems from factors like chain-of-thought reasoning (multiple LLM calls per query), API/tool interactions, memory management, and orchestration loops, which can generate 10-100x more tokens and require real-time responsiveness. For example, a single agentic query might trigger 5-20 model inferences, making it 10-20x more compute-intensive than simple chatbots, and the always-on nature compounds this to 40-100x overall. Nvidia's CEO has highlighted this as driving "easily 100x more computation" for inference in agentic/reasoning setups. AMD's EPYC Venice (6th Gen EPYC, codenamed "Venice") and Intel's Xeon 7 Diamond Rapids represent the pinnacle of server CPU technology in 2026, both targeting high-performance data center workloads like AI inference, agentic AI orchestration, cloud computing, and HPC. Venice builds on AMD's Zen 6 architecture, emphasizing core density and efficiency, while Diamond Rapids leverages Intel's Panther Cove P-cores for balanced performance. Both chips adopt similar advancements like 16-channel DDR5 memory and PCIe Gen 6, but differ in core counts, process nodes, and overall design philosophy. Intel has faced acute supply constraints across its Xeon lineup, including legacy nodes (Intel 7/3) and the ramping 18A process for next-gen parts. Intel shortage is expected with lead times up to 6 months or longer. 1. AMD EPYC Venice vs Intel Xeon 7 Diamond Rapids Architecture AMD: Zen 6 chiplet design with 8 CCDs and dual IODs Intel: Panther Cove P-cores; multi-die architecture with 4 compute tiles Core/Thread Count AMD: Up to 256 cores / 512 threads (Zen 6c variant) Intel: Up to 192 cores / 192 threads Process Node AMD: TSMC N2 (2nm) Intel: Intel 18A (1.8nm-class); in-house fab Memory Support AMD: 16-channel DDR5; up to 1.6 TB/s bandwidth. Intel: 16-channel DDR5 ; up to 1.6 TB/s bandwidth I/O and Connectivity AMD: PCIe Gen 6 (up to 128 lanes); twice the CPU-to-GPU bandwidth Intel: PCIe Gen 6 (up to 128 lanes); LGA 9324 socket Power (TDP) AMD: Starting 400-500W, potentially lower due to efficiency gains from TSMC 2nm Intel: Starting 400-500W, as it targets competitive efficiency Performance Projections AMD: Up to 70% uplift vs. 5th Gen Turin (1.7x in multi-threaded/AI tasks) Intel: ~40% faster than Granite Rapids (Xeon 6, 128-core). Lags AMD in per-core perf and 40-50% behind Venice core-for-core comp Target Workloads AMD: AI inference/orchestration, HPC, cloud virtualization. Partnerships Intel: Hyperscale AI, general enterprise. Custom silicon Pricing: AMD: estimated $10k-$20k for top SKUs Intel: estimated $8-$18k Availability: AMD: Significant Ramp H2 2026 due to higher allocation from TSMC Intel: H1-H2 2026 delayed, but trying to catch up Overall: ~Venice's 256 cores provide a 33% edge over Diamond Rapids' 192, making it superior for massively parallel tasks like AI training/inference or virtualization ~TSMC's N2 vs. Intel 18A debates rage on which is "better," but AMD's mature chiplet approach yields better density ( 32 cores/CCD vs. Intel's 48/tile). Venice's redesign reduces latency, aiding agentic AI where CPUs handle orchestration ~ Early projections show Venice widening AMD's lead matching or exceeding Diamond Rapids' perf with fewer watts in multi-threaded benchmarks. Intel's no-SMT design (to prioritize AI) handicaps it vs. AMD's 512 threads, though Clearwater Forest (E-core) could compete in density-focused niches. ~Power & Cooling: Both push above 400-500W, demanding liquid cooling. ~AMD been taking market share now above 40%. AMD EPYC Venice emerges as the superior choice in 2026 for most server workloads. Its higher core/thread count (256/512 vs. 192/192), stronger per-core performance, and architecture optimized for AI-driven tasks (agentic orchestration with GPU integration) provide decisive advantages in throughput, scalability, and efficiency. Projections indicate Venice delivering 1.7x the performance of prior gens while widening the gap over Intel ( 40-70% leads in multi-threaded benchmarks). AMD's fabless model with TSMC ensures reliable scaling, and its ecosystem ( open ROCm) appeals to AI adopters. Intel's Diamond Rapids is competitive in single-threaded enterprise apps and custom hyperscale ( NVLink), with potential fab advantages for supply/security. However, without SMT and lower density, it falls short in core-for-core battles—exposing Intel to another generation of AMD dominance unless 18A yields surprise efficiency gains. For data centers prioritizing raw compute ( AI, HPC), Venice wins; for Intel-centric ecosystems or specialized I/O, Diamond Rapids holds ground. Real benchmarks post-launch will confirm, but logic points to AMD pulling ahead. 2. Market size , Potential Revenue and Supply Global Agentic AI market size is projected to be $3-$5 Trillion by 2030 according to McKinsey, where consensus points to 40-50% CAGR driven by small to large enterprise demand. I also wrote a full thread on how and why Agentic AI is so explosive that AMD will blow all anlaysts estimate for subscribers. Link below if you are interested. AMD's data center segment hit a record $5.4B in Q4 2025 (up 39% YoY), with EPYC shipments ramping due to agentic demand. With 2GW of deployment in H2 2026, AMD AI data center revenue has $40-$50B+ at the lowest or most conservative projection; or Total Revenue in the $77-$94B For FY2026. However, Agentic AI massive demand spike could send EPYC revenue 3x to 4x in the next few years, potentially surpassing MI series GPU demand as enterprises prioritize CPU-dense Rack setups. This is pushing $NVDA Jensen to rush a CPU design and acquired Groq, a new CPU player due to this massive TAM. Noted that this is just popping just in weeks, highlighting we are just so early in this AI Supercycle and the pace of adoption is insane, and clearly productivity will skyrocket. Why? Because Agentic AI is 24/7 Smart AI agent working for you or your businesses is a mad compelling, and it is estimated to be 40-100x more Inference Hugnry! Many experts already said it is impossible to project this kind of Inference Demand. AI CapEx is expected to ramp up even more in 2027-2028-2029 and 2030 as Global Agentic AI is going to scale to $3-$5 Trillion TAM by 2030. The nature of Agentic is driving higher CPU/GPU ratio, with CPUs handling 50-90% of Agentic workflows. For example, The current Helios Rack: 18 compute trays per rack with 72 GPUs + 18 CPUs. The beauty of this $META and $AMD long term partnership is, that it is absolutely flexible to adjust racks to higher CPU rato or equal to service different needs. Helios rack can be easily swap to 2 GPUs 2CPUs or even CPUs only trays for dedicated orchestration/head nodes. You see, the beauty of this open rack-scale is flexibility and evolvability. If Agentic AI demand pushes much higher, AMD should be able to adjust variant trays without abandoning Heilos Rack. We can't talk just about massive Agentic AI demand without talking about the Supply side or TSMC. TSMC, AMD's primary foundry for advanced nodes ( Zen 6/Venice on N2/2nm), is addressing AI-driven shortages through massive expansions. TSMC accelerates fab construction with up to 10 facilities targeted for 2026. TSMC is accelerating its domestic manufacturing expansion, with industry sources indicating that as many as ten fabs could be under construction or preparing to begin operations across Taiwan’s major science parks. TSMC Capex: $52-56B in 2026 (up 37% YoY), with $45B already approved for new/upgraded capacities. 70-80% for advanced processes (2nm/A16), 10-20% for packaging (CoWoS quadrupling to 120-140K wafers/month by late 2026). In addition, Taiwanese companies (led by TSMC) commit to at least $250B in direct investments in US-based advanced semiconductor, AI, and energy production/innovation capacity.Taiwan provides $250B in government credit guarantees to facilitate additional investments and build a full US semiconductor ecosystem (including industrial parks). TSMC completed a second land purchase in Arizona (January 2026) for gigafab scaling, with an additional $100B+ (potentially four more modules) to further expand and qualify for tariff exemptions. AMD with secured 12GW from OpenAI and $META and massive Agentic AI will mean higher priority acess to 20-30% more wafers on TSMC advanced nodes, as TSMC has multi-year agreements with AMD for AI chips. Dr. C. C. Wei, CEO of TSMC quote: "I spend a lot of time in the last three or four months talking to my customer and then customers. Customer. I want to make sure that my customers demand are real. I talk to those cloud service providers, all of them. Their answer is. I'm quite satisfied with their answer. Actually they show me the evidence that the AI really help their business. So they grow their business successfully and he or she in their financial return. So I also double check their financial status. They are very rich." Amid shortages, the US buildout ensures AMD can ramp production of Instinct GPUs and EPYC CPUs without the constraints hitting competitors like Intel. By diversifying away from Taiwan (85% of advanced nodes today), the agreement mitigates supply disruptions, ensuring stable flows for AMD's chips. Scaling production and securing supply will matter for AMD the most in the next 5-10 years growth. The growth could be 80-100% YoY or higher; or it could be in the 60%. The aggressive TSMC supply ramp is reassuring the higher growth point. Conclusion: AMD stands at a pivotal inflection point in 2026, where the explosive rise of agentic AI demanding 40-100x more inference compute through its 24/7, multi-step orchestration positions the company to potentially triple its EPYC CPU revenue to $45-60B+ by 2028 while scaling Instinct GPUs to tens of billions annually by 2027. Agentic AI demand could push AI CapEx closer to $1 Trillion in 2027, far higher than most estimates. Dr. Lisa Su, AMD's visionary CEO, is masterfully securing supply to harness this massive demand by prioritizing operational execution and deep TSMC collaboration, ensuring readiness for the second-half 2026 AI ramp. Dr. Su has explicitly called out surging EPYC demand for agentic tasks where CPUs power head nodes and traditional workloads alongside GPUs while guiding for data center dominance through proactive capacity planning and partnerships like Nutanix ($150M investment for open agentic platforms) or providing tens of millions CPUs for OpenAI, $META, $ORCL, $AMZN, $MSFT, $GOOGL and others. Her strategy includes multi-year TSMC agreements for advanced nodes (N2 for Venice CPUs and future Instincts), diversifying beyond Taiwan to mitigate risks, and unveiling innovations like the MI455X GPU at CES 2026, which she touted as enabling "the next trillion-dollar market opportunity" in physical AI. Dr. Su's forward-looking vision predicting AI reaching 5 billion users emphasizes "AI everywhere," backed by hardware like Ryzen AI chips, all while declaring demand "going through the roof" and committing to scale without bottlenecks. TSMC's aggressive ramp-up, fueled by $52-56B in 2026 capex (up 37% YoY) and 10+ new fabs across Taiwan, the US (Arizona cluster expanding to 6+ modules with $165B+ investment), Japan, and Europe, provides profound reassurance for AMD's supply stability. The January 2026 US-Taiwan agreement committing $250B in investments and credit guarantees for US reshoring accelerates this, granting tariff relief (15% rates with 1.5-2.5x exemptions) tied to capacity buildouts, enabling TSMC to potentially double output over the decade to meet AI wafer hunger. This translates to 20-30% higher wafer allocations on key nodes, sidestepping Intel-like shortages and empowering Dr. Su's team to deliver on hyperscaler demands without disruption. Ultimately, this synergy cements AMD's leadership in the agentic era, promising sustained growth, $5T+ valuations at scale, and a resilient path forward as AI reshapes the world. This is NOT Financial Advice! Video source: AMD CES 2026
2:49

$AMD $5 Trillion is Inevitable LT| Agentic AI🧵 Agentic AI is the new $5 Trillion TAM 🚨🚨🚨 This thead will do Comp with $INTC and how to quantify this massive Agentic AI demand spike, and forcing Jensen to rush a CPU design. Global Agentic AI Market size is estimated to be $3-$5Trillion TAM by 2030(McKinsey) Quantifying the demand from agentic AI for AMD involves assessing the broader market growth for agentic systems, their unique computational requirements (particularly for CPUs in orchestration and reasoning tasks), and AMD's positioning very well through products like EPYC processors and partnerships. AMD EPYC Venice is the most superior choice in 2026-2027 for most Agentic AI workloads Agentic AI refers to autonomous AI agents that perform multi-step tasks, involving sequential logic, tool integration, and decision-making workloads that heavily rely on CPUs for handling orchestration, memory management, and context switching, rather than just GPU-parallelized training or batch inference. Agentic AI is often cited as 40-100x more "hungry" than traditional AI due to its continuous, 24/7 operation and complex workflows. This stems from factors like chain-of-thought reasoning (multiple LLM calls per query), API/tool interactions, memory management, and orchestration loops, which can generate 10-100x more tokens and require real-time responsiveness. For example, a single agentic query might trigger 5-20 model inferences, making it 10-20x more compute-intensive than simple chatbots, and the always-on nature compounds this to 40-100x overall. Nvidia's CEO has highlighted this as driving "easily 100x more computation" for inference in agentic/reasoning setups. AMD's EPYC Venice (6th Gen EPYC, codenamed "Venice") and Intel's Xeon 7 Diamond Rapids represent the pinnacle of server CPU technology in 2026, both targeting high-performance data center workloads like AI inference, agentic AI orchestration, cloud computing, and HPC. Venice builds on AMD's Zen 6 architecture, emphasizing core density and efficiency, while Diamond Rapids leverages Intel's Panther Cove P-cores for balanced performance. Both chips adopt similar advancements like 16-channel DDR5 memory and PCIe Gen 6, but differ in core counts, process nodes, and overall design philosophy. Intel has faced acute supply constraints across its Xeon lineup, including legacy nodes (Intel 7/3) and the ramping 18A process for next-gen parts. Intel shortage is expected with lead times up to 6 months or longer. 1. AMD EPYC Venice vs Intel Xeon 7 Diamond Rapids Architecture AMD: Zen 6 chiplet design with 8 CCDs and dual IODs Intel: Panther Cove P-cores; multi-die architecture with 4 compute tiles Core/Thread Count AMD: Up to 256 cores / 512 threads (Zen 6c variant) Intel: Up to 192 cores / 192 threads Process Node AMD: TSMC N2 (2nm) Intel: Intel 18A (1.8nm-class); in-house fab Memory Support AMD: 16-channel DDR5; up to 1.6 TB/s bandwidth. Intel: 16-channel DDR5 ; up to 1.6 TB/s bandwidth I/O and Connectivity AMD: PCIe Gen 6 (up to 128 lanes); twice the CPU-to-GPU bandwidth Intel: PCIe Gen 6 (up to 128 lanes); LGA 9324 socket Power (TDP) AMD: Starting 400-500W, potentially lower due to efficiency gains from TSMC 2nm Intel: Starting 400-500W, as it targets competitive efficiency Performance Projections AMD: Up to 70% uplift vs. 5th Gen Turin (1.7x in multi-threaded/AI tasks) Intel: ~40% faster than Granite Rapids (Xeon 6, 128-core). Lags AMD in per-core perf and 40-50% behind Venice core-for-core comp Target Workloads AMD: AI inference/orchestration, HPC, cloud virtualization. Partnerships Intel: Hyperscale AI, general enterprise. Custom silicon Pricing: AMD: estimated $10k-$20k for top SKUs Intel: estimated $8-$18k Availability: AMD: Significant Ramp H2 2026 due to higher allocation from TSMC Intel: H1-H2 2026 delayed, but trying to catch up Overall: ~Venice's 256 cores provide a 33% edge over Diamond Rapids' 192, making it superior for massively parallel tasks like AI training/inference or virtualization ~TSMC's N2 vs. Intel 18A debates rage on which is "better," but AMD's mature chiplet approach yields better density ( 32 cores/CCD vs. Intel's 48/tile). Venice's redesign reduces latency, aiding agentic AI where CPUs handle orchestration ~ Early projections show Venice widening AMD's lead matching or exceeding Diamond Rapids' perf with fewer watts in multi-threaded benchmarks. Intel's no-SMT design (to prioritize AI) handicaps it vs. AMD's 512 threads, though Clearwater Forest (E-core) could compete in density-focused niches. ~Power & Cooling: Both push above 400-500W, demanding liquid cooling. ~AMD been taking market share now above 40%. AMD EPYC Venice emerges as the superior choice in 2026 for most server workloads. Its higher core/thread count (256/512 vs. 192/192), stronger per-core performance, and architecture optimized for AI-driven tasks (agentic orchestration with GPU integration) provide decisive advantages in throughput, scalability, and efficiency. Projections indicate Venice delivering 1.7x the performance of prior gens while widening the gap over Intel ( 40-70% leads in multi-threaded benchmarks). AMD's fabless model with TSMC ensures reliable scaling, and its ecosystem ( open ROCm) appeals to AI adopters. Intel's Diamond Rapids is competitive in single-threaded enterprise apps and custom hyperscale ( NVLink), with potential fab advantages for supply/security. However, without SMT and lower density, it falls short in core-for-core battles—exposing Intel to another generation of AMD dominance unless 18A yields surprise efficiency gains. For data centers prioritizing raw compute ( AI, HPC), Venice wins; for Intel-centric ecosystems or specialized I/O, Diamond Rapids holds ground. Real benchmarks post-launch will confirm, but logic points to AMD pulling ahead. 2. Market size , Potential Revenue and Supply Global Agentic AI market size is projected to be $3-$5 Trillion by 2030 according to McKinsey, where consensus points to 40-50% CAGR driven by small to large enterprise demand. I also wrote a full thread on how and why Agentic AI is so explosive that AMD will blow all anlaysts estimate for subscribers. Link below if you are interested. AMD's data center segment hit a record $5.4B in Q4 2025 (up 39% YoY), with EPYC shipments ramping due to agentic demand. With 2GW of deployment in H2 2026, AMD AI data center revenue has $40-$50B+ at the lowest or most conservative projection; or Total Revenue in the $77-$94B For FY2026. However, Agentic AI massive demand spike could send EPYC revenue 3x to 4x in the next few years, potentially surpassing MI series GPU demand as enterprises prioritize CPU-dense Rack setups. This is pushing $NVDA Jensen to rush a CPU design and acquired Groq, a new CPU player due to this massive TAM. Noted that this is just popping just in weeks, highlighting we are just so early in this AI Supercycle and the pace of adoption is insane, and clearly productivity will skyrocket. Why? Because Agentic AI is 24/7 Smart AI agent working for you or your businesses is a mad compelling, and it is estimated to be 40-100x more Inference Hugnry! Many experts already said it is impossible to project this kind of Inference Demand. AI CapEx is expected to ramp up even more in 2027-2028-2029 and 2030 as Global Agentic AI is going to scale to $3-$5 Trillion TAM by 2030. The nature of Agentic is driving higher CPU/GPU ratio, with CPUs handling 50-90% of Agentic workflows. For example, The current Helios Rack: 18 compute trays per rack with 72 GPUs + 18 CPUs. The beauty of this $META and $AMD long term partnership is, that it is absolutely flexible to adjust racks to higher CPU rato or equal to service different needs. Helios rack can be easily swap to 2 GPUs 2CPUs or even CPUs only trays for dedicated orchestration/head nodes. You see, the beauty of this open rack-scale is flexibility and evolvability. If Agentic AI demand pushes much higher, AMD should be able to adjust variant trays without abandoning Heilos Rack. We can't talk just about massive Agentic AI demand without talking about the Supply side or TSMC. TSMC, AMD's primary foundry for advanced nodes ( Zen 6/Venice on N2/2nm), is addressing AI-driven shortages through massive expansions. TSMC accelerates fab construction with up to 10 facilities targeted for 2026. TSMC is accelerating its domestic manufacturing expansion, with industry sources indicating that as many as ten fabs could be under construction or preparing to begin operations across Taiwan’s major science parks. TSMC Capex: $52-56B in 2026 (up 37% YoY), with $45B already approved for new/upgraded capacities. 70-80% for advanced processes (2nm/A16), 10-20% for packaging (CoWoS quadrupling to 120-140K wafers/month by late 2026). In addition, Taiwanese companies (led by TSMC) commit to at least $250B in direct investments in US-based advanced semiconductor, AI, and energy production/innovation capacity.Taiwan provides $250B in government credit guarantees to facilitate additional investments and build a full US semiconductor ecosystem (including industrial parks). TSMC completed a second land purchase in Arizona (January 2026) for gigafab scaling, with an additional $100B+ (potentially four more modules) to further expand and qualify for tariff exemptions. AMD with secured 12GW from OpenAI and $META and massive Agentic AI will mean higher priority acess to 20-30% more wafers on TSMC advanced nodes, as TSMC has multi-year agreements with AMD for AI chips. Dr. C. C. Wei, CEO of TSMC quote: "I spend a lot of time in the last three or four months talking to my customer and then customers. Customer. I want to make sure that my customers demand are real. I talk to those cloud service providers, all of them. Their answer is. I'm quite satisfied with their answer. Actually they show me the evidence that the AI really help their business. So they grow their business successfully and he or she in their financial return. So I also double check their financial status. They are very rich." Amid shortages, the US buildout ensures AMD can ramp production of Instinct GPUs and EPYC CPUs without the constraints hitting competitors like Intel. By diversifying away from Taiwan (85% of advanced nodes today), the agreement mitigates supply disruptions, ensuring stable flows for AMD's chips. Scaling production and securing supply will matter for AMD the most in the next 5-10 years growth. The growth could be 80-100% YoY or higher; or it could be in the 60%. The aggressive TSMC supply ramp is reassuring the higher growth point. Conclusion: AMD stands at a pivotal inflection point in 2026, where the explosive rise of agentic AI demanding 40-100x more inference compute through its 24/7, multi-step orchestration positions the company to potentially triple its EPYC CPU revenue to $45-60B+ by 2028 while scaling Instinct GPUs to tens of billions annually by 2027. Agentic AI demand could push AI CapEx closer to $1 Trillion in 2027, far higher than most estimates. Dr. Lisa Su, AMD's visionary CEO, is masterfully securing supply to harness this massive demand by prioritizing operational execution and deep TSMC collaboration, ensuring readiness for the second-half 2026 AI ramp. Dr. Su has explicitly called out surging EPYC demand for agentic tasks where CPUs power head nodes and traditional workloads alongside GPUs while guiding for data center dominance through proactive capacity planning and partnerships like Nutanix ($150M investment for open agentic platforms) or providing tens of millions CPUs for OpenAI, $META, $ORCL, $AMZN, $MSFT, $GOOGL and others. Her strategy includes multi-year TSMC agreements for advanced nodes (N2 for Venice CPUs and future Instincts), diversifying beyond Taiwan to mitigate risks, and unveiling innovations like the MI455X GPU at CES 2026, which she touted as enabling "the next trillion-dollar market opportunity" in physical AI. Dr. Su's forward-looking vision predicting AI reaching 5 billion users emphasizes "AI everywhere," backed by hardware like Ryzen AI chips, all while declaring demand "going through the roof" and committing to scale without bottlenecks. TSMC's aggressive ramp-up, fueled by $52-56B in 2026 capex (up 37% YoY) and 10+ new fabs across Taiwan, the US (Arizona cluster expanding to 6+ modules with $165B+ investment), Japan, and Europe, provides profound reassurance for AMD's supply stability. The January 2026 US-Taiwan agreement committing $250B in investments and credit guarantees for US reshoring accelerates this, granting tariff relief (15% rates with 1.5-2.5x exemptions) tied to capacity buildouts, enabling TSMC to potentially double output over the decade to meet AI wafer hunger. This translates to 20-30% higher wafer allocations on key nodes, sidestepping Intel-like shortages and empowering Dr. Su's team to deliver on hyperscaler demands without disruption. Ultimately, this synergy cements AMD's leadership in the agentic era, promising sustained growth, $5T+ valuations at scale, and a resilient path forward as AI reshapes the world. This is NOT Financial Advice! Video source: AMD CES 2026

Mike

44,460 views • 4 months ago

$AMD is easily a $1,200 stock IMO| CPUs TAM 🧵 Not Financial Advice! DYOR! In this thread, I want to discuss the actual TAM for CPUs data center for just 2026, where many are giving different ranges, where I don't agree with. I will explain in detail why I disagree with these research firms and financial analysts using Math. And this thread should not be treated as Financial Advice. I'm just explaining my research and thought process so we can have a discussion. In 2024/2025, I gave out $620 PT for FY2026 was too conservative for AMD potential. At the time, It was early and many were just laughing, that PT was unrealistic and the AI world is run on GPUs only. Today, most of these folks are laughing with me. That is ok, I dont offer financial advice, and I do not need everyone to agree with me. I respect other opinions. If you enjoy this kind of thread, slap the like/repost/bookmark. If you want to support my work further and gain more in-depth analysis, consider subscribe! In early 2026, hyperscalers, enterprises, and OEMs are scrambling as Intel and AMD server CPUs are largely sold out for the year, with prices jumping 10–20% and lead times stretching from weeks to months (or longer for certain SKUs). What was once a GPU dominated story has flipped: the shift to explosive Agentic AI with its multi-step reasoning loops, tool calling, multi-agent orchestration, real-time data movement, and reinforcement learning, is dramatically tightening CPU:GPU ratios from the old training-era 1:4–8 all the way to 1:1 to 5:1 or even CPU-heavy configurations. CEOs across NVIDIA, AMD, Intel, Google, Meta, Microsoft, and public companies have been sounding the alarm on CNBC, Bloomberg, and earnings calls. CPUs are “cool again,” and in many agentic deployments they are becoming the new bottleneck alongside (or even ahead of) GPUs and custom ASICs. In 2025, roughly 12-15m AI GPUs + AI ASICs GPUs shipped, and is expect to be 15-20m units by 2026, where it suggesting Training demand is not going away. The actual TAM is structural, multiplicative demand that has already forced AMD to double its long-term server CPU TAM forecast to >$120 billion by 2030 (>35% CAGR), with Dr. Lisa Su noting Q2 2026 server CPU sales expected to surge 70%+ year-over-year and demand “far exceeding expectations.” At the same time, AMD’s secured 30–40% share of TSMC’s initial 2nm capacity (behind only Apple’s >50%) positions it to ramp Zen 6-based EPYC Venice exactly when this agentic wave hits hardest but even that aggressive five-fab 2nm expansion (with plans scaling toward 11 total advanced facilities) cannot instantly close the gap in the near-term. Supply constraints on wafers, advanced packaging, and power are compounding the squeeze, just as hyperscalers forward-buy and lock in long-term deals. 1. The actual potential TAM Various sources and institutions are giving $50-$160-$200B CPUs TAM toward 2030, and i disagree, where supply is severely behind vs Demand by at least 2-3 years or even longer by some estimates. The actual TAM will probably be 15-20m for FY2026. The typical average selling price from low to high end is $5,000 to $15,000, but due to rising memory, and different inflationary pressures on Semi, it would be more logical to think between $7,000-17,000. A. CPU:GPU Ratio at 1:1 A basic calucation at mid range =12,000 x 15-20m CPUs= $180-$240B TAM B. CPU:GPU Ratio at 5:1 = $12,000 x 75m-100m CPUs= $900B-$1.2T TAM Of course TSMC cannot even supply 20% of this massive inflection TAM in 2026. But do we think of Demand for TAM or Supply for TAM? Hence we are seeing massive 2nm Ramp from TSMC for $AMD. IMO, conservatively, I would take down 15-20% on 1:1 or $135-$192B TAM for just 2026. Im not even talking about 2030. We are just months into this, it is impossible to estimate Cagr atm, but this is 1-5 agents running tasks, I wrote a thread on 24/7 autonomous agents thread, where companies could use 50-250 agents to run tasks for them 24/7. It would require a different structural CPU:GPU to bring down the cost of token as well as handling the Orchestration bottleneck. GPUs would be useless and sit idle waiting for CPU due to highly CPU-intensive nature. The cost per Million tokens must come down more rapidly for this 50-250 autonomous agents to work, otherwise the token cost would be too enormous. Helios Rack is estimated to bring inference cost down to $0.0003-$0.0005/M tokens with 18 EPYC Venices along with 72 MI455x and other chips+ Components. A heavier or CPUs dense rack would bring down inference cost further. EPYC Verano(2027 gen 7 AI-optimized) is expected to drive inference costs meaningfully lower than the Venice baseline likely to the $0.00002–$0.00025 per million tokens range (or even sub-$0.00015 in highly optimized agentic/batch workloads). Verano have higher core counts than Venice, LPDDR5X SOCAMM2 memory support, more AI optimized and Next-Gen rack density & efficiency. 2. $AMD secured at least 30-40% of TSMC 2nm capacity and Memory from Samsung through 2028-2030. 2 2nm fabs are entering ramping phase toward 60-65k wafers per months and 5 dedicated 2nm fabs entering mass production/ramp in 2026. Will link sub threads below if you are interest for full detail. Apple is reported to secure 50%+ 2nm capacity for Iphone 18 and Mac chips and AMD secured at least 30-40% capacity while $NVDA $AVGO $ARM $AMZN $GOOGL and others are on 3nm. This broader aggressive ramp from TSMC to target up to 11 fabs is to address $AMD massive growth ahead. Where $ARM is facing massive CPUs supply constraints as they have to compete with other Mega Cap players on 3nm allocation. And $INTC is also facing supply constraints for data center CPUs and PC per management with lead times extrended to longer than 12 weeks. Dr. Su is aiming for higher than 50%+ Market share, and I believe it is achievable in 2026 or 2027 as AMD has the strongest CPUs offerings. Dr. Su did not want to take advantage of the shortage and she said during the Q1 earning call, AMD is prioritizing Units shipped while guiding margin to be inching 60%. If Jensen were in charge, I'm sure margin would be 70-75% in this kind of severe CPUs shortage condition. But that is not how Dr. Su operates for more than a decade. She wants most market share. So we will see it in revenue growth, but as TSMC ramps faster and faster, AMD Operating and FCF margin will massively improve vs prior decade. A significantly higher margin profile than before. 3. How I came up with $1,200 withint 12-18 months? At $1,200/ share, that would be around $2 Trillion MC. I expect FY2027 revenue to be $124-$144B where data center revenue dominates overall revenue. AI GPUs: I will stick to the lowest end so show u that I'm conservative at $18B for each GW vs $NVDA Rubin is $30B+ (most likely Helios Rack in the $20B+ due to memory price rising). We know deals with OpenAI and Meta are around 12GW and additional multi-customers at multi-GW scale were hinted and will be revealed as we get to July 22-23 2026 Advancing AI event. For now I will conservatively add a bit more to this model. (3-6GW Helios Rack Range) EPYC Venice is reported to be in $15,000-$20,000. However large customers will likely to enjoy $10-$12k discount. I expect AMD to be able to ramp 7m EPYC Venice for entire 2026 and 3-4m of EPYC Verano(higher price than Venice). If we take an average selling price of $10,000 to be on the conservative side. Take down another 30% to be even more conservative on projection. I like to be conservative. That would be ~ 7m EPYC CPUs(Venice + Verano) for FY2027 or 583,000 units per month or 15,000 additional 2nm wafers per month which is completely reasonable for current TSMC Ramp, and I may be too conservative here. EPYC Verano and MI500 series will also be on 2nm. AI GPUs: 3GW x $18B= $54B EPYC CPUs: $10k x 7m CPUs= $70B = Data center revenue alone is $124B Other segments= probably in the $20-$25B FY 2027. FY2027 revenue = $124-$149B At 7m EPYC CPUs for entire 2027, that would be more than 50% market share when we comp it to availability from supply side, not from total Demand. It is possible that TSMC could significantly ramp even more capacity in 2027, so we will see. Metric Q1 2026 FY2027 Gross Margin 55-56% 60-62% Operating Margin 25-26% 32-35% Net Income Margin ~22% 26-30% FCF Margin 25% 28-30% At $124-$149B Revenue FY 2027 Net Income would be $32-$44B EPS would be $20-$27 (GAAP) Non-GAAP would be $25-$31 At $1,200 a share or $2T valuation that would be: 13.4-16x Price to Sales (P/S) 38-48 P/E At this kind of growth of AI SuperCycle, I think it is very reasonable valuation. If we use today at $406/share or $661B MC: 2027 P/S = 4.4x-5.3x 2027 P/E = 13x-16x Is AMD today expensive or cheap to you? Above is already a very conservative where I trimmed 20-30% of doable units. Meaning, there could be upside if TSMC is able to ramp meaningfully like they are planning. Conclusion: A $1,200 per share valuation IMO for AMD in FY2027 is not expensive at all; it is, in fact, conservative when viewed against the structural explosion in agentic AI demand we have mapped out. With server CPU TAM potentially scaling into the $100–$200B+ range in just CPU:GPU 1:1 Ratio for just 2026. AMD positioned to capture 50%+ share thanks to its 2nm TSMC allocation advantage and full-stack leadership, the company could realistically deliver $124–149B in total revenue and $25–$31+ non-GAAP EPS. At those levels, $1,200 implies a 2027 P/E = 13x-16x. Entirely reasonable for a company that will have become the clear Inference Queen (and in many workloads the preferred) AI infrastructure provider, with operating margins expanding above 30% and tens of billions in high-margin rack-scale AI revenue. Dr. Lisa Su was right presciently so about the Agentic AI inflection all the way back to her early 2022–2023 commentary on the coming shift from pure training to inference and orchestration-heavy workloads. While the broader market only fully woke up to this in 2026 when she doubled AMD’s long-term server CPU TAM forecast to >$120B by 2030 (with >35% CAGR), Dr. Su and her team have consistently positioned the company at the center of the CPU renaissance. The explosive demand we are seeing today, sold-out lines, rising ASPs, and hyperscalers forward-buying entire gigawatts of Helios-class systems is exactly the outcome she forecasted years ago. Not Financial Advice! DYOR!
13:03

$AMD is easily a $1,200 stock IMO| CPUs TAM 🧵 Not Financial Advice! DYOR! In this thread, I want to discuss the actual TAM for CPUs data center for just 2026, where many are giving different ranges, where I don't agree with. I will explain in detail why I disagree with these research firms and financial analysts using Math. And this thread should not be treated as Financial Advice. I'm just explaining my research and thought process so we can have a discussion. In 2024/2025, I gave out $620 PT for FY2026 was too conservative for AMD potential. At the time, It was early and many were just laughing, that PT was unrealistic and the AI world is run on GPUs only. Today, most of these folks are laughing with me. That is ok, I dont offer financial advice, and I do not need everyone to agree with me. I respect other opinions. If you enjoy this kind of thread, slap the like/repost/bookmark. If you want to support my work further and gain more in-depth analysis, consider subscribe! In early 2026, hyperscalers, enterprises, and OEMs are scrambling as Intel and AMD server CPUs are largely sold out for the year, with prices jumping 10–20% and lead times stretching from weeks to months (or longer for certain SKUs). What was once a GPU dominated story has flipped: the shift to explosive Agentic AI with its multi-step reasoning loops, tool calling, multi-agent orchestration, real-time data movement, and reinforcement learning, is dramatically tightening CPU:GPU ratios from the old training-era 1:4–8 all the way to 1:1 to 5:1 or even CPU-heavy configurations. CEOs across NVIDIA, AMD, Intel, Google, Meta, Microsoft, and public companies have been sounding the alarm on CNBC, Bloomberg, and earnings calls. CPUs are “cool again,” and in many agentic deployments they are becoming the new bottleneck alongside (or even ahead of) GPUs and custom ASICs. In 2025, roughly 12-15m AI GPUs + AI ASICs GPUs shipped, and is expect to be 15-20m units by 2026, where it suggesting Training demand is not going away. The actual TAM is structural, multiplicative demand that has already forced AMD to double its long-term server CPU TAM forecast to >$120 billion by 2030 (>35% CAGR), with Dr. Lisa Su noting Q2 2026 server CPU sales expected to surge 70%+ year-over-year and demand “far exceeding expectations.” At the same time, AMD’s secured 30–40% share of TSMC’s initial 2nm capacity (behind only Apple’s >50%) positions it to ramp Zen 6-based EPYC Venice exactly when this agentic wave hits hardest but even that aggressive five-fab 2nm expansion (with plans scaling toward 11 total advanced facilities) cannot instantly close the gap in the near-term. Supply constraints on wafers, advanced packaging, and power are compounding the squeeze, just as hyperscalers forward-buy and lock in long-term deals. 1. The actual potential TAM Various sources and institutions are giving $50-$160-$200B CPUs TAM toward 2030, and i disagree, where supply is severely behind vs Demand by at least 2-3 years or even longer by some estimates. The actual TAM will probably be 15-20m for FY2026. The typical average selling price from low to high end is $5,000 to $15,000, but due to rising memory, and different inflationary pressures on Semi, it would be more logical to think between $7,000-17,000. A. CPU:GPU Ratio at 1:1 A basic calucation at mid range =12,000 x 15-20m CPUs= $180-$240B TAM B. CPU:GPU Ratio at 5:1 = $12,000 x 75m-100m CPUs= $900B-$1.2T TAM Of course TSMC cannot even supply 20% of this massive inflection TAM in 2026. But do we think of Demand for TAM or Supply for TAM? Hence we are seeing massive 2nm Ramp from TSMC for $AMD. IMO, conservatively, I would take down 15-20% on 1:1 or $135-$192B TAM for just 2026. Im not even talking about 2030. We are just months into this, it is impossible to estimate Cagr atm, but this is 1-5 agents running tasks, I wrote a thread on 24/7 autonomous agents thread, where companies could use 50-250 agents to run tasks for them 24/7. It would require a different structural CPU:GPU to bring down the cost of token as well as handling the Orchestration bottleneck. GPUs would be useless and sit idle waiting for CPU due to highly CPU-intensive nature. The cost per Million tokens must come down more rapidly for this 50-250 autonomous agents to work, otherwise the token cost would be too enormous. Helios Rack is estimated to bring inference cost down to $0.0003-$0.0005/M tokens with 18 EPYC Venices along with 72 MI455x and other chips+ Components. A heavier or CPUs dense rack would bring down inference cost further. EPYC Verano(2027 gen 7 AI-optimized) is expected to drive inference costs meaningfully lower than the Venice baseline likely to the $0.00002–$0.00025 per million tokens range (or even sub-$0.00015 in highly optimized agentic/batch workloads). Verano have higher core counts than Venice, LPDDR5X SOCAMM2 memory support, more AI optimized and Next-Gen rack density & efficiency. 2. $AMD secured at least 30-40% of TSMC 2nm capacity and Memory from Samsung through 2028-2030. 2 2nm fabs are entering ramping phase toward 60-65k wafers per months and 5 dedicated 2nm fabs entering mass production/ramp in 2026. Will link sub threads below if you are interest for full detail. Apple is reported to secure 50%+ 2nm capacity for Iphone 18 and Mac chips and AMD secured at least 30-40% capacity while $NVDA $AVGO $ARM $AMZN $GOOGL and others are on 3nm. This broader aggressive ramp from TSMC to target up to 11 fabs is to address $AMD massive growth ahead. Where $ARM is facing massive CPUs supply constraints as they have to compete with other Mega Cap players on 3nm allocation. And $INTC is also facing supply constraints for data center CPUs and PC per management with lead times extrended to longer than 12 weeks. Dr. Su is aiming for higher than 50%+ Market share, and I believe it is achievable in 2026 or 2027 as AMD has the strongest CPUs offerings. Dr. Su did not want to take advantage of the shortage and she said during the Q1 earning call, AMD is prioritizing Units shipped while guiding margin to be inching 60%. If Jensen were in charge, I'm sure margin would be 70-75% in this kind of severe CPUs shortage condition. But that is not how Dr. Su operates for more than a decade. She wants most market share. So we will see it in revenue growth, but as TSMC ramps faster and faster, AMD Operating and FCF margin will massively improve vs prior decade. A significantly higher margin profile than before. 3. How I came up with $1,200 withint 12-18 months? At $1,200/ share, that would be around $2 Trillion MC. I expect FY2027 revenue to be $124-$144B where data center revenue dominates overall revenue. AI GPUs: I will stick to the lowest end so show u that I'm conservative at $18B for each GW vs $NVDA Rubin is $30B+ (most likely Helios Rack in the $20B+ due to memory price rising). We know deals with OpenAI and Meta are around 12GW and additional multi-customers at multi-GW scale were hinted and will be revealed as we get to July 22-23 2026 Advancing AI event. For now I will conservatively add a bit more to this model. (3-6GW Helios Rack Range) EPYC Venice is reported to be in $15,000-$20,000. However large customers will likely to enjoy $10-$12k discount. I expect AMD to be able to ramp 7m EPYC Venice for entire 2026 and 3-4m of EPYC Verano(higher price than Venice). If we take an average selling price of $10,000 to be on the conservative side. Take down another 30% to be even more conservative on projection. I like to be conservative. That would be ~ 7m EPYC CPUs(Venice + Verano) for FY2027 or 583,000 units per month or 15,000 additional 2nm wafers per month which is completely reasonable for current TSMC Ramp, and I may be too conservative here. EPYC Verano and MI500 series will also be on 2nm. AI GPUs: 3GW x $18B= $54B EPYC CPUs: $10k x 7m CPUs= $70B = Data center revenue alone is $124B Other segments= probably in the $20-$25B FY 2027. FY2027 revenue = $124-$149B At 7m EPYC CPUs for entire 2027, that would be more than 50% market share when we comp it to availability from supply side, not from total Demand. It is possible that TSMC could significantly ramp even more capacity in 2027, so we will see. Metric Q1 2026 FY2027 Gross Margin 55-56% 60-62% Operating Margin 25-26% 32-35% Net Income Margin ~22% 26-30% FCF Margin 25% 28-30% At $124-$149B Revenue FY 2027 Net Income would be $32-$44B EPS would be $20-$27 (GAAP) Non-GAAP would be $25-$31 At $1,200 a share or $2T valuation that would be: 13.4-16x Price to Sales (P/S) 38-48 P/E At this kind of growth of AI SuperCycle, I think it is very reasonable valuation. If we use today at $406/share or $661B MC: 2027 P/S = 4.4x-5.3x 2027 P/E = 13x-16x Is AMD today expensive or cheap to you? Above is already a very conservative where I trimmed 20-30% of doable units. Meaning, there could be upside if TSMC is able to ramp meaningfully like they are planning. Conclusion: A $1,200 per share valuation IMO for AMD in FY2027 is not expensive at all; it is, in fact, conservative when viewed against the structural explosion in agentic AI demand we have mapped out. With server CPU TAM potentially scaling into the $100–$200B+ range in just CPU:GPU 1:1 Ratio for just 2026. AMD positioned to capture 50%+ share thanks to its 2nm TSMC allocation advantage and full-stack leadership, the company could realistically deliver $124–149B in total revenue and $25–$31+ non-GAAP EPS. At those levels, $1,200 implies a 2027 P/E = 13x-16x. Entirely reasonable for a company that will have become the clear Inference Queen (and in many workloads the preferred) AI infrastructure provider, with operating margins expanding above 30% and tens of billions in high-margin rack-scale AI revenue. Dr. Lisa Su was right presciently so about the Agentic AI inflection all the way back to her early 2022–2023 commentary on the coming shift from pure training to inference and orchestration-heavy workloads. While the broader market only fully woke up to this in 2026 when she doubled AMD’s long-term server CPU TAM forecast to >$120B by 2030 (with >35% CAGR), Dr. Su and her team have consistently positioned the company at the center of the CPU renaissance. The explosive demand we are seeing today, sold-out lines, rising ASPs, and hyperscalers forward-buying entire gigawatts of Helios-class systems is exactly the outcome she forecasted years ago. Not Financial Advice! DYOR!

Mike

301,322 views • 2 months ago

Spark Intelligence lifetime sale is live! A self-evolving AI agent. The more you use it, the smarter it gets. Lifetime sale is now active for 45 days. What lifetime members get: - Lifetime Spark upgrades - Essential tools to evolve Spark - Library of domain evolution chips (pre-built skill modules that level up Spark's learning in specific areas) - Exclusive access to premium features - 10% of $SPARK token supply, equally divided among all lifetime buyers SFUND Community & X Community allocations will remain the same, this 10% will come from vibe coders allocations, for the real users of Spark Intelligence. The product will constantly evolve through tooling, benchmark systems, and integrations to popular frameworks. The code will be open source, and OSS contributions will be welcome: with a goal to have an open ecosystem around Spark and SparkNet for everyone's benefit, while having a membership for the premium features. Spark Intelligence's self-evolving AI system will be live on the 21st of this month. How to participate: Simple USDC transfer. No wallet connections needed. Lifetime sub: $279 USDC You can buy multiple for gifting to others. IMPORTANT: Only send USDC from non-exchange wallets. $SPARK tokens will be airdropped to the address you send from. Address: 0xD15257A5C18d2fF107E9e3F7dE434F90C8256c85 Networks: Base & Ethereum ⚠️ This is the ONLY official address to send sub purchases. Ignore any others posted in replies. $SPARK token gifts will be available until the snapshot before token launch. If you buy a lifetime after token launch there won't be any token gifts. --- For those who don't grab lifetime: Early bird (first 2 months only): $14.99/mo Regular: $22.59/mo or $229/yr Card payments via x402 and Stripe coming soon for monthly and yearly subs. --- Below you can find a snippet from a recent evolution run, out of 10 points, Spark could even evolve already available LLM models, where we tried to evolve Deepseek's reasoning in the current benchmark test. The tooling will be shared so you can benchmark & evolve many other models, including local LLM models, while evolving Spark. --- Spark will come with many modules to learn and evolve from your direct conversations & projects, tooling, social APIs, and more. Spark is already compatible with most popular LLMs and IDEs, and we will continue to make it available with all the popular frameworks.
0:26

Spark Intelligence lifetime sale is live! A self-evolving AI agent. The more you use it, the smarter it gets. Lifetime sale is now active for 45 days. What lifetime members get: - Lifetime Spark upgrades - Essential tools to evolve Spark - Library of domain evolution chips (pre-built skill modules that level up Spark's learning in specific areas) - Exclusive access to premium features - 10% of $SPARK token supply, equally divided among all lifetime buyers SFUND Community & X Community allocations will remain the same, this 10% will come from vibe coders allocations, for the real users of Spark Intelligence. The product will constantly evolve through tooling, benchmark systems, and integrations to popular frameworks. The code will be open source, and OSS contributions will be welcome: with a goal to have an open ecosystem around Spark and SparkNet for everyone's benefit, while having a membership for the premium features. Spark Intelligence's self-evolving AI system will be live on the 21st of this month. How to participate: Simple USDC transfer. No wallet connections needed. Lifetime sub: $279 USDC You can buy multiple for gifting to others. IMPORTANT: Only send USDC from non-exchange wallets. $SPARK tokens will be airdropped to the address you send from. Address: 0xD15257A5C18d2fF107E9e3F7dE434F90C8256c85 Networks: Base & Ethereum ⚠️ This is the ONLY official address to send sub purchases. Ignore any others posted in replies. $SPARK token gifts will be available until the snapshot before token launch. If you buy a lifetime after token launch there won't be any token gifts. --- For those who don't grab lifetime: Early bird (first 2 months only): $14.99/mo Regular: $22.59/mo or $229/yr Card payments via x402 and Stripe coming soon for monthly and yearly subs. --- Below you can find a snippet from a recent evolution run, out of 10 points, Spark could even evolve already available LLM models, where we tried to evolve Deepseek's reasoning in the current benchmark test. The tooling will be shared so you can benchmark & evolve many other models, including local LLM models, while evolving Spark. --- Spark will come with many modules to learn and evolve from your direct conversations & projects, tooling, social APIs, and more. Spark is already compatible with most popular LLMs and IDEs, and we will continue to make it available with all the popular frameworks.

Spark

42,662 views • 5 months ago

India is quietly preparing for the coming precious metals order in which LBMA/COMEX is less relevant for pricing. SEBI’s February 26, 2026 circular (HO/(68)2026-IMD-POD-2/I/5780/2026) may appear as a routine technical update ,but I see it as a strategic signal of how India is positioning itself in a changing global commodities landscape. Effective April 1, 2026, every mutual fund and ETF holding physical gold or silver must stop using the London LBMA AM fixing price + manual adjustments for duty, currency conversion, transport, taxes, and notional premiums/discounts. Instead, they must value physical holdings using the polled domestic spot prices published by recognized Indian stock exchanges primarily the MCX polled spot price (the exact same benchmark used for final settlement of physically delivered gold and silver derivatives contracts). Official reason: “to reflect domestic market conditions and ensure uniformity in valuation practices.” My deeper macro interpretation: India is quietly preparing for the coming precious metals order in which LBMA/COMEX is less relevant for pricing. We have already witnessed live previews of this decoupling. In October 2025 and again in January–February 2026, India’s MCX polled prices ran at massive premiums over LBMA far beyond the normal 15% import duty effect. The core driver was acute physical non-availability: depleting stocks at refiners, jewelers, and dealers amid explosive demand. London arbitrage simply could not deliver metal fast enough. The price of “metal you can actually take delivery of today in India” completely decoupled from international benchmarks. The Silver Market Has Become Exceptionally Tight — Here’s Exactly How Severe It Has Gotten (2025–2026) The silver market is now heading into its sixth consecutive year of structural supply deficit in 2026. According to the Silver Institute’s preliminary outlook (released February 2026, based on Metals Focus data): - Projected 2026 deficit: 67 million ounces. - 2025 deficit: even larger at ~95 million ounces (some estimates from J.P. Morgan and others put it between 117–230 million ounces depending on inventory draw calculations). - Cumulative 5-year deficit (2021–2025): over 800 million ounces roughly an entire year of global mine production. This is not a temporary imbalance. It is deeply structural, and the tightness is intensifying. Key drivers making the silver market so tight: 1. Exploding structural industrial demand (now ~55–60% of total silver use) Silver is irreplaceable due to its unmatched conductivity, thermal properties, and corrosion resistance. Demand is surging from: - Solar PV: Despite some thrifting (using less silver per panel), global installations keep rising aggressively. - Electric Vehicles (EVs) & charging infrastructure: An EV uses 67–79% more silver than a traditional ICE vehicle (25–50 grams per EV on average). EVs are forecast to overtake ICE vehicles as the main source of automotive silver demand by 2027. - AI, data centers & electronics: Massive growth in connectors, circuits, thermal management, and power systems. AI infrastructure alone is adding huge incremental demand. 2. Extremely slow supply response Total global supply in 2026 is forecast to rise only +1.5% to a decade-high of 1.05 billion ounces. Mine production grows just +1% to 820 million ounces. Why? Silver is overwhelmingly a **by-product** of copper, lead, and zinc mining — new supply does not ramp quickly even at higher prices. 3. China’s strategic export controls (the geopolitical kicker) China controls 60–70% of global refined silver supply. From January 1, 2026, it imposed a formal export licensing regime. Only 44 companies are approved to export silver for the 2026–2027 period (a massive reduction from previous market participants). Silver has effectively been reclassified as a strategic material (alongside tungsten and antimony) to protect domestic needs for green energy, EVs, electronics, and defense. Exports are expected to drop sharply, creating 2,000+ tonnes of annual shortage for Western buyers and adding permanent friction to global physical flows. Result: Above-ground inventories worldwide are under sustained pressure. COMEX, LBMA, and Shanghai stocks have repeatedly hit multi-year lows. Lease rates have climbed. Physical premiums have become volatile and extreme. India one of the world’s largest silver consumers, felt this pain acutely. Silver imports exploded in 2025 (up dramatically year-on-year, with some months showing 300–500% spikes), yet local stocks still depleted rapidly during festivals and hoarding periods, pushing MCX premiums to multi-year highs. Why This SEBI Move Is Strategic Preparation By mandating the MCX polled domestic price from April 1, 2026, SEBI is ensuring that Gold & Silver ETF NAVs (Nippon India Gold BeES, HDFC Gold ETF, SBI Gold ETF, ICICI Pru Silver ETF, etc.) automatically capture: - Real-time physical stock tightness in India - Immediate availability (or scarcity) of metal - Any future import/export frictions or strategic restrictions - True local replacement cost — even when global paper benchmarks diverge In a world where physical flows are becoming politicized and constrained, relying on LBMA/COMEX (driven heavily by paper trading and Western liquidity) risks significant mispricing for Indian investors. This is no longer just “better uniformity.” This is India quietly future-proofing its financial products for a more fragmented, physical-first precious metals regime — one where **domestic availability and policy risks** will increasingly dictate the price that actually matters. For investors: cleaner, more accurate NAVs + stronger protection against exactly the physical and geopolitical risks we are already seeing in silver. The official language is neutral. But the shift from London to MCX polled pricing is one of the most under-appreciated macro moves happening in commodities right now. LBMA and COMEX will still influence the global trend, but in the coming order, they may matter less and less for actual pricing in India.
2:45

India is quietly preparing for the coming precious metals order in which LBMA/COMEX is less relevant for pricing. SEBI’s February 26, 2026 circular (HO/(68)2026-IMD-POD-2/I/5780/2026) may appear as a routine technical update ,but I see it as a strategic signal of how India is positioning itself in a changing global commodities landscape. Effective April 1, 2026, every mutual fund and ETF holding physical gold or silver must stop using the London LBMA AM fixing price + manual adjustments for duty, currency conversion, transport, taxes, and notional premiums/discounts. Instead, they must value physical holdings using the polled domestic spot prices published by recognized Indian stock exchanges primarily the MCX polled spot price (the exact same benchmark used for final settlement of physically delivered gold and silver derivatives contracts). Official reason: “to reflect domestic market conditions and ensure uniformity in valuation practices.” My deeper macro interpretation: India is quietly preparing for the coming precious metals order in which LBMA/COMEX is less relevant for pricing. We have already witnessed live previews of this decoupling. In October 2025 and again in January–February 2026, India’s MCX polled prices ran at massive premiums over LBMA far beyond the normal 15% import duty effect. The core driver was acute physical non-availability: depleting stocks at refiners, jewelers, and dealers amid explosive demand. London arbitrage simply could not deliver metal fast enough. The price of “metal you can actually take delivery of today in India” completely decoupled from international benchmarks. The Silver Market Has Become Exceptionally Tight — Here’s Exactly How Severe It Has Gotten (2025–2026) The silver market is now heading into its sixth consecutive year of structural supply deficit in 2026. According to the Silver Institute’s preliminary outlook (released February 2026, based on Metals Focus data): - Projected 2026 deficit: 67 million ounces. - 2025 deficit: even larger at ~95 million ounces (some estimates from J.P. Morgan and others put it between 117–230 million ounces depending on inventory draw calculations). - Cumulative 5-year deficit (2021–2025): over 800 million ounces roughly an entire year of global mine production. This is not a temporary imbalance. It is deeply structural, and the tightness is intensifying. Key drivers making the silver market so tight: 1. Exploding structural industrial demand (now ~55–60% of total silver use) Silver is irreplaceable due to its unmatched conductivity, thermal properties, and corrosion resistance. Demand is surging from: - Solar PV: Despite some thrifting (using less silver per panel), global installations keep rising aggressively. - Electric Vehicles (EVs) & charging infrastructure: An EV uses 67–79% more silver than a traditional ICE vehicle (25–50 grams per EV on average). EVs are forecast to overtake ICE vehicles as the main source of automotive silver demand by 2027. - AI, data centers & electronics: Massive growth in connectors, circuits, thermal management, and power systems. AI infrastructure alone is adding huge incremental demand. 2. Extremely slow supply response Total global supply in 2026 is forecast to rise only +1.5% to a decade-high of 1.05 billion ounces. Mine production grows just +1% to 820 million ounces. Why? Silver is overwhelmingly a **by-product** of copper, lead, and zinc mining — new supply does not ramp quickly even at higher prices. 3. China’s strategic export controls (the geopolitical kicker) China controls 60–70% of global refined silver supply. From January 1, 2026, it imposed a formal export licensing regime. Only 44 companies are approved to export silver for the 2026–2027 period (a massive reduction from previous market participants). Silver has effectively been reclassified as a strategic material (alongside tungsten and antimony) to protect domestic needs for green energy, EVs, electronics, and defense. Exports are expected to drop sharply, creating 2,000+ tonnes of annual shortage for Western buyers and adding permanent friction to global physical flows. Result: Above-ground inventories worldwide are under sustained pressure. COMEX, LBMA, and Shanghai stocks have repeatedly hit multi-year lows. Lease rates have climbed. Physical premiums have become volatile and extreme. India one of the world’s largest silver consumers, felt this pain acutely. Silver imports exploded in 2025 (up dramatically year-on-year, with some months showing 300–500% spikes), yet local stocks still depleted rapidly during festivals and hoarding periods, pushing MCX premiums to multi-year highs. Why This SEBI Move Is Strategic Preparation By mandating the MCX polled domestic price from April 1, 2026, SEBI is ensuring that Gold & Silver ETF NAVs (Nippon India Gold BeES, HDFC Gold ETF, SBI Gold ETF, ICICI Pru Silver ETF, etc.) automatically capture: - Real-time physical stock tightness in India - Immediate availability (or scarcity) of metal - Any future import/export frictions or strategic restrictions - True local replacement cost — even when global paper benchmarks diverge In a world where physical flows are becoming politicized and constrained, relying on LBMA/COMEX (driven heavily by paper trading and Western liquidity) risks significant mispricing for Indian investors. This is no longer just “better uniformity.” This is India quietly future-proofing its financial products for a more fragmented, physical-first precious metals regime — one where **domestic availability and policy risks** will increasingly dictate the price that actually matters. For investors: cleaner, more accurate NAVs + stronger protection against exactly the physical and geopolitical risks we are already seeing in silver. The official language is neutral. But the shift from London to MCX polled pricing is one of the most under-appreciated macro moves happening in commodities right now. LBMA and COMEX will still influence the global trend, but in the coming order, they may matter less and less for actual pricing in India.

Macro Liquidity by Sunil Reddy

17,297 views • 4 months 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

50,006 views • 1 year ago

TOPIC #106: What Is a “Free Market”? Clarifying the Misconceptions in the Pi Ecosystem I’ve noticed a narrative spreading within parts of the Pi Network community: the idea that Pi’s value in Dapps or ecosystem should fluctuate freely with the exchange market, and that this is what defines a “free market.” They use this "free market" to deny GCV. Let me be clear: this misconception is not only misleading, but it threatens the foundation of the Pi ecosystem we’ve worked so hard to build. It’s time to clarify the truth, not only for our pioneers today but for the economic legacy we’re building for generations to come. What Is a Free Market Really? According to Britannica, a free market is an economic system characterized by minimal government intervention, where prices are determined by the interplay of supply and demand. But even Britannica admits: > “The free market represents a benchmark that does not actually exist… Modern societies only approach this ideal along a spectrum.” — value in relation to In short, a 100% free market is a myth. Every successful economy has rules and frameworks to maintain stability. Without these, markets descend into chaos, not freedom. In Pi Network, “free market” cannot mean price anarchy. And “decentralization” does not mean “do whatever you want.” Let’s break this down: What Pi Network Decentralization Actually Means Pi Network’s decentralization is built on the Stellar Consensus Protocol (SCP) and reflects a healthy distribution of power and particip,ation — not a lack of structure. Key principles of Pi's decentralization: No Single Point of Control No central entity dominates the network. User Participation Pioneers validate transactions and contribute to governance. Resilience The network can survive attacks or failures due to its distributed nature. Censorship Resistance It’s harder for one party to silence or manipulate the system. None of this means that Pi's value can operate in a free market. Any currency must have a fixed value; this is a fundamental concept in economics. Have you ever seen the values of currencies like the USD, CAD, or RMB fluctuate freely based on individual opinions? On the contrary, a fixed value emphasizes the need to protect the economy we are building together. The community-driven GCV illustrates that the value of Pi should derive from its pioneers and merchants, demonstrating the spirit of decentralization. It should not depend on PCT, any government, large corporations, or investors. Furthermore, this structure ensures that no entity can shut down the Pi Network once it becomes fully decentralized, which I believe will occur when it is fully operational and mature. The Danger of Currency Risk: Why Price or Value Chaos Is Destructive In global finance, currency risk refers to the potential loss of value resulting from unstable exchange rates. As the Corporate Finance Institute explains: > “Currency risk refers to the exposure faced by investors or companies operating across different countries due to changes in the value of one currency versus another.” Let’s apply this to Pi. Imagine a Pi Network Dapp marketplace mall merchant collecting a large amount of 10,000 Pi after the Open Mainnet (OM). Customers pay with Pi, but at a value $1. The merchants must know the Pi value because they need to calculate the FIAT cost. Then, when the merchant tries to use that Pi to buy a car, only to be told the accepted rate is $0.1 for one Pi, the merchant total Then, when the merchant tries to use that Pi to buy a car, only to be told the accepted rate is $0.1 for one Pi, the merchant has a total of 10,000 Pi, which is only $1,000, but the cost of investing in products is $9,000 (Sales $10,000 with $1,000 as profit). That’s a massive loss for the merchant $8,000. If you were the merchant, would you feel it was unfair? Will you still support "free market"? Now, imagine the exchange market drops Pi to $0.40. You will lose $5,000. Would you still want to run your business in Pi? Likely not. And neither would other developers or merchants. Unstable value leads to fear. Fear leads to exit. Exit leads to collapse. This is why we must support Global Consensus Value (GCV) — to ensure a unified, trusted economy. Why GCV Exists — and Why $314,159 Matters GCV is not a fantasy. It’s an economic strategy. It functions much like the gold standard once did: England pioneered it. The U.S. adopted it under the Bretton Woods system, fixing the dollar to gold at $35/oz. This standard enabled global trade and trust until 1971. If the free market can work, why did the US adopt the Bretton Woods system at that time to fix the USD's rate with gold? Because if they didn't promise a fixed rate, no country would give its gold to the US. The gold is trust! Here in Pi Network, GCV is a trust! Pi’s GCV of $314,159 per Pi is not random. It’s based on utility, scarcity, and long-term vision. It reflects Pi’s potential as a foundational currency for a real digital economy. Misusing “Free Market” Is Cheating to Ignorant Pioneers Let’s be blunt. Some individuals abuse the term “free market” to justify undervaluing Pi for personal short-term gain, hoarding more Pi, and undermining long-term stability. However, a true economy isn’t built on confusion. Consider the Cayman Islands — a country with no income tax — yet it only accepts USD for settlement. Why? Because multiple currencies lead to confusion, which undermines investor trust. If Pi has no unified value, we will lose merchants, DApps, developers, and the entire vision, except that they just come to hoard Pi, not for the long-term economy, or they really don't understand the economy. The Way Forward: Unity, Strategy, and Patience Here’s how we build the future together for the following strategies before fully OM Strategy #1: Offline Partial GCV Adoption -Fix Pi Value at GCV in Ecosystem for OM GCV Ambassadors around the world are guiding merchants to accept partial GCV, benefiting both sides: Pioneers buy low-cost goods. Merchants enjoy more sales and earn a small profit in FIAT. The ecosystem produces GCV transaction data, creating the real basis for Pi’s future fixed value at OM. Strategy # 2: Online DApps with Utility — at Any Value to Increase Exchange Pi price for OM We support ALL DApps — regardless of the Pi value they use ($1, $100, or floating): As long as the pioneers and merchants are satisfied. As long as real usage is created. As long as the utility grows. As long as more good-quality Dapps are created It will protect and attract more merchants and developers, driving up Pi demand while reducing supply and organically pushing Pi’s market price toward GCV. Strategy #3: Build up GCV Infrastructure The Head of GCV Ambassador builds up your countrywide GCV infrastructure in all provinces, cities, counties, and villages. Strategy #4: Education and Protection of Pi Network Mission and GCV GCV Education Ambassadors: Educate pioneers to HOLD Pi and support GCV usage. GCV Army: Defend GCV and Pi Network on social media, building public trust and global participation. Online Non-GCV pioneers and merchants, or DApp owners, can still enjoy DApps, even if they use low Pi values. They are reducing selling pressure and strengthening the Pi economy. It is said that a person's wealth is closely linked to their knowledge, cognitive abilities, and moral character. We respect and appreciate all DApp owners, merchants, service providers, and pioneers, regardless of whether they share our beliefs in GCV. We are currently in a chaotic period. Before fully transitioning to OM, pioneers, merchants, and DApps will undergo a screening process based on their own judgment and understanding. Those who strongly believe in GCV will become champions and accumulate substantial wealth. Conversely, those who do not believe in GCV may risk losing their wealth by abandoning Pi. This is because if you have a strong belief, you are more likely to hold onto your Pi. If you oppose GCV, it is often due to a lack of long-term confidence in Pi or a current need to accumulate more Pi. It's important to recognize that once you have accumulated enough Pi, you will want to support GCV because no one wishes to hold onto a worthless coin. This approach is fair to everyone. GCV is akin to Noah's Ark, carrying those who have a strong belief in GCV to safety on the mountains of Ararat. A fixed GCV: Attracts real investors Encourages developers and merchants Reduces currency risk Builds global trust and reputation Let’s stop spreading confusion. Let’s stop begging the old system. We are builders. We are visionaries. We are the future. Final Words Together, we build — not beg. Together, we lead, not mislead. Together, we protect Pi for a future that lasts not for years, but centuries. Doris Yin 🪷🪷🪷 July 20th, 2025
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TOPIC #106: What Is a “Free Market”? Clarifying the Misconceptions in the Pi Ecosystem I’ve noticed a narrative spreading within parts of the Pi Network community: the idea that Pi’s value in Dapps or ecosystem should fluctuate freely with the exchange market, and that this is what defines a “free market.” They use this "free market" to deny GCV. Let me be clear: this misconception is not only misleading, but it threatens the foundation of the Pi ecosystem we’ve worked so hard to build. It’s time to clarify the truth, not only for our pioneers today but for the economic legacy we’re building for generations to come. What Is a Free Market Really? According to Britannica, a free market is an economic system characterized by minimal government intervention, where prices are determined by the interplay of supply and demand. But even Britannica admits: > “The free market represents a benchmark that does not actually exist… Modern societies only approach this ideal along a spectrum.” — value in relation to In short, a 100% free market is a myth. Every successful economy has rules and frameworks to maintain stability. Without these, markets descend into chaos, not freedom. In Pi Network, “free market” cannot mean price anarchy. And “decentralization” does not mean “do whatever you want.” Let’s break this down: What Pi Network Decentralization Actually Means Pi Network’s decentralization is built on the Stellar Consensus Protocol (SCP) and reflects a healthy distribution of power and particip,ation — not a lack of structure. Key principles of Pi's decentralization: No Single Point of Control No central entity dominates the network. User Participation Pioneers validate transactions and contribute to governance. Resilience The network can survive attacks or failures due to its distributed nature. Censorship Resistance It’s harder for one party to silence or manipulate the system. None of this means that Pi's value can operate in a free market. Any currency must have a fixed value; this is a fundamental concept in economics. Have you ever seen the values of currencies like the USD, CAD, or RMB fluctuate freely based on individual opinions? On the contrary, a fixed value emphasizes the need to protect the economy we are building together. The community-driven GCV illustrates that the value of Pi should derive from its pioneers and merchants, demonstrating the spirit of decentralization. It should not depend on PCT, any government, large corporations, or investors. Furthermore, this structure ensures that no entity can shut down the Pi Network once it becomes fully decentralized, which I believe will occur when it is fully operational and mature. The Danger of Currency Risk: Why Price or Value Chaos Is Destructive In global finance, currency risk refers to the potential loss of value resulting from unstable exchange rates. As the Corporate Finance Institute explains: > “Currency risk refers to the exposure faced by investors or companies operating across different countries due to changes in the value of one currency versus another.” Let’s apply this to Pi. Imagine a Pi Network Dapp marketplace mall merchant collecting a large amount of 10,000 Pi after the Open Mainnet (OM). Customers pay with Pi, but at a value $1. The merchants must know the Pi value because they need to calculate the FIAT cost. Then, when the merchant tries to use that Pi to buy a car, only to be told the accepted rate is $0.1 for one Pi, the merchant total Then, when the merchant tries to use that Pi to buy a car, only to be told the accepted rate is $0.1 for one Pi, the merchant has a total of 10,000 Pi, which is only $1,000, but the cost of investing in products is $9,000 (Sales $10,000 with $1,000 as profit). That’s a massive loss for the merchant $8,000. If you were the merchant, would you feel it was unfair? Will you still support "free market"? Now, imagine the exchange market drops Pi to $0.40. You will lose $5,000. Would you still want to run your business in Pi? Likely not. And neither would other developers or merchants. Unstable value leads to fear. Fear leads to exit. Exit leads to collapse. This is why we must support Global Consensus Value (GCV) — to ensure a unified, trusted economy. Why GCV Exists — and Why $314,159 Matters GCV is not a fantasy. It’s an economic strategy. It functions much like the gold standard once did: England pioneered it. The U.S. adopted it under the Bretton Woods system, fixing the dollar to gold at $35/oz. This standard enabled global trade and trust until 1971. If the free market can work, why did the US adopt the Bretton Woods system at that time to fix the USD's rate with gold? Because if they didn't promise a fixed rate, no country would give its gold to the US. The gold is trust! Here in Pi Network, GCV is a trust! Pi’s GCV of $314,159 per Pi is not random. It’s based on utility, scarcity, and long-term vision. It reflects Pi’s potential as a foundational currency for a real digital economy. Misusing “Free Market” Is Cheating to Ignorant Pioneers Let’s be blunt. Some individuals abuse the term “free market” to justify undervaluing Pi for personal short-term gain, hoarding more Pi, and undermining long-term stability. However, a true economy isn’t built on confusion. Consider the Cayman Islands — a country with no income tax — yet it only accepts USD for settlement. Why? Because multiple currencies lead to confusion, which undermines investor trust. If Pi has no unified value, we will lose merchants, DApps, developers, and the entire vision, except that they just come to hoard Pi, not for the long-term economy, or they really don't understand the economy. The Way Forward: Unity, Strategy, and Patience Here’s how we build the future together for the following strategies before fully OM Strategy #1: Offline Partial GCV Adoption -Fix Pi Value at GCV in Ecosystem for OM GCV Ambassadors around the world are guiding merchants to accept partial GCV, benefiting both sides: Pioneers buy low-cost goods. Merchants enjoy more sales and earn a small profit in FIAT. The ecosystem produces GCV transaction data, creating the real basis for Pi’s future fixed value at OM. Strategy # 2: Online DApps with Utility — at Any Value to Increase Exchange Pi price for OM We support ALL DApps — regardless of the Pi value they use ($1, $100, or floating): As long as the pioneers and merchants are satisfied. As long as real usage is created. As long as the utility grows. As long as more good-quality Dapps are created It will protect and attract more merchants and developers, driving up Pi demand while reducing supply and organically pushing Pi’s market price toward GCV. Strategy #3: Build up GCV Infrastructure The Head of GCV Ambassador builds up your countrywide GCV infrastructure in all provinces, cities, counties, and villages. Strategy #4: Education and Protection of Pi Network Mission and GCV GCV Education Ambassadors: Educate pioneers to HOLD Pi and support GCV usage. GCV Army: Defend GCV and Pi Network on social media, building public trust and global participation. Online Non-GCV pioneers and merchants, or DApp owners, can still enjoy DApps, even if they use low Pi values. They are reducing selling pressure and strengthening the Pi economy. It is said that a person's wealth is closely linked to their knowledge, cognitive abilities, and moral character. We respect and appreciate all DApp owners, merchants, service providers, and pioneers, regardless of whether they share our beliefs in GCV. We are currently in a chaotic period. Before fully transitioning to OM, pioneers, merchants, and DApps will undergo a screening process based on their own judgment and understanding. Those who strongly believe in GCV will become champions and accumulate substantial wealth. Conversely, those who do not believe in GCV may risk losing their wealth by abandoning Pi. This is because if you have a strong belief, you are more likely to hold onto your Pi. If you oppose GCV, it is often due to a lack of long-term confidence in Pi or a current need to accumulate more Pi. It's important to recognize that once you have accumulated enough Pi, you will want to support GCV because no one wishes to hold onto a worthless coin. This approach is fair to everyone. GCV is akin to Noah's Ark, carrying those who have a strong belief in GCV to safety on the mountains of Ararat. A fixed GCV: Attracts real investors Encourages developers and merchants Reduces currency risk Builds global trust and reputation Let’s stop spreading confusion. Let’s stop begging the old system. We are builders. We are visionaries. We are the future. Final Words Together, we build — not beg. Together, we lead, not mislead. Together, we protect Pi for a future that lasts not for years, but centuries. Doris Yin 🪷🪷🪷 July 20th, 2025

Doris Yin 东方紫莲🪷

30,299 views • 1 year 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 $META will deploy EPYC Dense Rack Not Financial Advice! DYOR! Research Purpose Only!
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$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 • 1 month ago

Made $313 → $2,382,780 in 4 Days Using a Claude AI Bot on Polymarket. 26,738 trades. 98% win rate. Full blockchain proof. Every single trade verifiable on-chain. I've made the exact step-by-step guide to build this Claude Polymarket bot from scratch. You've been trading for 3 years. Still red. He gave Claude $313. Woke up rich. Free for 24 hours. To get this Setup guide: 1. Comment "Money" 2. Like and Retweet 3. Follow me Himanshu Kumar (so i can DM you) Full 2-hour video tutorial attached. Every single click and command explained. Beginner to running bot. Now let me break down exactly how this works. Save this post. This is the most important trading breakdown you'll ever read. ↓ Let's start with the number that should make you sick. $313. That's what this wallet started with. Not $50,000. Not $10,000. Not even $1,000. $313. Less than your monthly Netflix + Uber Eats + Spotify combined. 4 months later: $2,382,780.80. That's a 7,942x return. While you spent those same 4 months staring at charts, drawing trendlines, panic selling, revenge trading, and ending the month exactly where you started. Minus the $200 you lost on that "sure thing." Same 4 months. Same market. Same opportunities. He had a bot. You had feelings. Guess who won. Save this post right now. What I'm about to explain is the exact mechanism behind every dollar of that $2.38M. Follow Himanshu Kumar so you don't miss the rest. ↓ How Polymarket actually works and why bots print money on it. Polymarket is a prediction market. Will BTC be higher in 15 minutes? Yes or No. Will the Fed raise rates? Yes or No. You buy shares between $0 and $1. If you're right, your share settles at $1. If you're wrong, it settles at $0. Simple. Now here's where it gets interesting. Polymarket updates its prices SLOWER than the real market moves. When BTC drops 0.6% on Binance, Polymarket still shows old odds for about 2.7 seconds. 2.7 seconds. In those 2.7 seconds, the bot already knows the outcome. It's not predicting. It's not guessing. It's reading information that already exists and trading before Polymarket catches up. That's not trading. That's collecting free money with a 2.7 second head start. And you're over there using a 15-indicator TradingView setup trying to "predict" where BTC goes next. The bot doesn't predict anything. It just reads faster than you. That's the entire edge. Save this post because if you understand this one concept you understand how millionaires are being made on Polymarket right now. Follow Himanshu Kumar for more breakdowns like this. ↓ Let me walk you through one single trade. A new 15-minute BTC contract opens on Polymarket. Odds are 50/50. Fair price. 10 minutes in, BTC drops 0.6% on Binance. Hard, fast move. The real probability of BTC being lower at expiry is now about 78%. Polymarket still shows 54/46. The bot sees this instantly. Binance WebSocket feed. Under 50ms latency. The edge is 24 percentage points. On a binary contract, that's basically free money. Bot calculates position size using Kelly Criterion. Executes via Polymarket's API. Done. Within 2-3 seconds, other participants update the odds. 54/46 moves toward 78/22. Bot either exits for immediate profit or holds to resolution. Either way, the trade was entered with near-certainty of a positive outcome. Now repeat this 200-500 times per day. $313 → $2,382,780 in 4 months. Not magic. Not prediction. Not luck. Industrial-scale exploitation of a market inefficiency that still exists today. And you're still placing one manual trade per day and calling yourself a "trader." This is the mechanism behind every single dollar. Bookmark this post so you can study it again. Follow Himanshu Kumar because I'm breaking down each strategy separately. ↓ There are 4 strategies. Not all Claude bots do the same thing. Strategy 1: Latency Arbitrage. Win rate: 85-98%. What 0x8dxd used. Monitor Binance price feeds. When Polymarket odds lag behind reality by 3-5%, buy the correct side before the market corrects. No forecasting. No model. No sentiment analysis. Pure speed. You're not guessing. You're reading an outcome that has already happened. Strategy 2: Oracle Arbitrage. Win rate: 78-85%. Chainlink oracle price feeds occasionally diverge from Polymarket's implied prices. When they do, the settlement direction is known. Fewer opportunities. Higher certainty when they appear. Strategy 3: News-Driven Trading. Win rate: 60-75%. Claude ingests real-time news. Government filings. Central bank statements. On-chain data. Assesses probability impact before retail traders even finish reading the headline. Lower win rate because interpretation introduces uncertainty. But works on ANY market category, not just crypto. Strategy 4: Market Making. Return: 2-5% per month. Place buy and sell orders on both sides. Capture the spread. No prediction required. Most consistent. Hardest to blow up. Compounds aggressively over time. You didn't even know there were 4 strategies. You thought "trading bot" meant one thing. That's how far behind you are. 4 strategies. 4 different risk profiles. 4 ways to make money while you sleep. Save this post. Follow Himanshu Kumar for the deep dive into each one. ↓ The timeline that should haunt you. December 2025: Bot launches with $313. Nobody notices. January 6, 2026: Wallet hits ~$438,000. 140x in 30 days. 6,615 predictions. 98% win rate. Finbold reports it. Crypto Twitter explodes. March 10, 2026: Head-to-head test. Claude bot: $1,000 → $14,216 in 48 hours. +1,322%. OpenClaw bot: fully liquidated. Same market. Same timeframe. Claude won because of better risk management. OpenClaw died because it overleveraged. March 16, 2026: Someone trains a swarm model on 3 years of NBA data. Result: +$1.49M on Polymarket. April 2026: 0x8dxd final verified balance: $2,382,780.80. 26,738 trades. 4 months. This all happened while you were "waiting for the right time to start." The right time was December 2025. The second best time is right now. But you'll probably wait until it's too late. That's what you always do. Every date on this timeline is a day you could have started but didn't. Save this post. Follow Himanshu Kumar so you at least start today. ↓ Why Claude and not ChatGPT? This isn't opinion. It's data. March 2026 head-to-head: Claude bot: +1,322%. OpenClaw (GPT-based): liquidated. Same prompt. Same market. Same conditions. Researchers found Claude's code included: > More defensive edge cases > More conservative default parameters > Better error handling > More legible code for debugging > Proper Kelly Criterion position sizing > Hard drawdown kill switches ChatGPT's code overleveraged into a losing sequence and couldn't recover. Claude's code sized positions conservatively, stopped trading when drawdown thresholds hit, and survived to compound another day. The difference between +1,322% and liquidation wasn't the strategy. It was the risk management. And Claude writes better risk management than ChatGPT. That's not a debate. That's a $15,216 difference in 48 hours. But sure, keep using ChatGPT because "everyone uses it." Everyone's broke too. Coincidence? Stop using the popular tool. Start using the profitable one. Save this post. Follow Himanshu Kumar for more Claude vs ChatGPT comparisons with real data. ↓ Why humans lose to bots. Every single time. Same strategy. Same market. Same period. Bots: ~$206,000 profit. Humans: ~$100,000 profit. 2x gap. Same strategy. Here's why: 1. Late entries. By the time you identify the lag, verify your reasoning, and click buy, the 2.7 second window is gone. The bot executes in under 100ms. You execute in 30 seconds. The opportunity doesn't exist for 30 seconds. 2. Emotional sizing. You oversize when "confident." Undersize when scared. Exact opposite of Kelly math. The bot sizes based on edge. Every time. No feelings. 3. Fatigue. You make worse decisions at hour 6 than at hour 1. The bot makes the same decision at hour 72 that it made at hour 1. 4. Drawdown psychology. After 3 losses you either panic quit or double down trying to recover. Both destroy capital. The bot has a kill switch. It stops. It doesn't feel anything. You're not competing with other humans anymore. You're competing with machines that don't sleep, don't feel, don't flinch. And you're losing. The data doesn't lie. Humans lose to bots 2x on the same strategy. Save this post. Follow Himanshu Kumar for the complete bot setup that removes you from the equation. ↓ What can go wrong. Because I'm not going to lie to you. Most people who build this bot will NOT 7,942x their money. Some will lose their initial capital. Here's what can kill you: Edge compression. The arbitrage window was 12 seconds in 2024. It's 2.7 seconds now. It's shrinking. At some point it hits zero for retail operators. This is a time-limited opportunity. Not a permanent income stream. Rule changes. Polymarket can change contract mechanics, settlement rules, or API terms overnight. What worked yesterday can lose money tomorrow. Risk management bugs. A 98% win rate strategy with broken position sizing will blow up your account on the one losing trade. The March 2026 experiment proved this. Claude survived. OpenClaw got liquidated. Same strategy. Different risk management. That's why the 2-hour video tutorial walks through every single risk parameter. Because the strategy doesn't kill you. Bad risk management kills you. This is the section most "gurus" delete. I'm keeping it because I'd rather you make money safely than blow up and blame me. Save this post. Follow Himanshu Kumar for honest breakdowns, not hype. ↓ The step-by-step to build your own. Step 1: Set up a Polymarket wallet. Fund with USDC via Polygon network. Start with $100-$300 for testing. Step 2: Generate API credentials. CLOB API key from docs.polymarket .com. Store private key in environment variable. Never hardcode it. Never share it. Step 3: Prompt Claude to build the bot. Use Claude Code for best results. It reads your filesystem, executes code, and iterates on errors autonomously. Step 4: Paper trade for at least one week. Minimum 200 completed trades. Win rate must be above 70% before going live. This step is NOT optional. Step 5: Configure risk management. Max single position: 8% of portfolio. Daily loss limit: -20% with auto halt. Kill switch at -40% drawdown. Telegram alerts on every threshold. Step 6: Go live small. $1-5 per trade. Watch every trade for first week. Compare to paper results. Scale only on evidence. Skip steps 4 and 5 and you will lose your money. That's not a warning. That's a guarantee. This is your complete build guide. Save this post. Follow Himanshu Kumar because I'll be posting the exact Claude prompts for each strategy. ↓ The edge exists right now. Not next month. Not "when you're ready." Right now. The arbitrage window is 2.7 seconds. It was 12 seconds in 2024. It's shrinking every week. Every day you wait, more bots enter the space. The window gets smaller. Your potential returns get smaller. The bots already running have a compounding advantage. They're making money today that they'll use to make more money tomorrow. You're reading about it and telling yourself "I'll look into this next weekend." That's what you said last weekend. And the weekend before that. The best time to start was 6 months ago. The second best time is today. But you already know you're going to bookmark this and never open it again. Prove me wrong. ↓ Full 2-hour video tutorial attached. Every single click. Every command. Every parameter. From zero to running bot. Beginner friendly. Nothing skipped. A similar bot has already earned $2,382,780. Full blockchain proof in the article below. The video is free. The tools are free. The edge still exists. The only thing that costs money is another month of doing nothing while bots eat every opportunity you're too slow to catch. Follow Himanshu Kumar for the complete series covering every automated income stream using Claude. Prediction markets are just the beginning. Save this post. Bookmark it. Screenshot it. Whatever you need to do so you actually watch the video and build the bot instead of just reading about people who did. You Must Follow me Himanshu Kumar, so i can send you DM.
2:22:35

Made $313 → $2,382,780 in 4 Days Using a Claude AI Bot on Polymarket. 26,738 trades. 98% win rate. Full blockchain proof. Every single trade verifiable on-chain. I've made the exact step-by-step guide to build this Claude Polymarket bot from scratch. You've been trading for 3 years. Still red. He gave Claude $313. Woke up rich. Free for 24 hours. To get this Setup guide: 1. Comment "Money" 2. Like and Retweet 3. Follow me Himanshu Kumar (so i can DM you) Full 2-hour video tutorial attached. Every single click and command explained. Beginner to running bot. Now let me break down exactly how this works. Save this post. This is the most important trading breakdown you'll ever read. ↓ Let's start with the number that should make you sick. $313. That's what this wallet started with. Not $50,000. Not $10,000. Not even $1,000. $313. Less than your monthly Netflix + Uber Eats + Spotify combined. 4 months later: $2,382,780.80. That's a 7,942x return. While you spent those same 4 months staring at charts, drawing trendlines, panic selling, revenge trading, and ending the month exactly where you started. Minus the $200 you lost on that "sure thing." Same 4 months. Same market. Same opportunities. He had a bot. You had feelings. Guess who won. Save this post right now. What I'm about to explain is the exact mechanism behind every dollar of that $2.38M. Follow Himanshu Kumar so you don't miss the rest. ↓ How Polymarket actually works and why bots print money on it. Polymarket is a prediction market. Will BTC be higher in 15 minutes? Yes or No. Will the Fed raise rates? Yes or No. You buy shares between $0 and $1. If you're right, your share settles at $1. If you're wrong, it settles at $0. Simple. Now here's where it gets interesting. Polymarket updates its prices SLOWER than the real market moves. When BTC drops 0.6% on Binance, Polymarket still shows old odds for about 2.7 seconds. 2.7 seconds. In those 2.7 seconds, the bot already knows the outcome. It's not predicting. It's not guessing. It's reading information that already exists and trading before Polymarket catches up. That's not trading. That's collecting free money with a 2.7 second head start. And you're over there using a 15-indicator TradingView setup trying to "predict" where BTC goes next. The bot doesn't predict anything. It just reads faster than you. That's the entire edge. Save this post because if you understand this one concept you understand how millionaires are being made on Polymarket right now. Follow Himanshu Kumar for more breakdowns like this. ↓ Let me walk you through one single trade. A new 15-minute BTC contract opens on Polymarket. Odds are 50/50. Fair price. 10 minutes in, BTC drops 0.6% on Binance. Hard, fast move. The real probability of BTC being lower at expiry is now about 78%. Polymarket still shows 54/46. The bot sees this instantly. Binance WebSocket feed. Under 50ms latency. The edge is 24 percentage points. On a binary contract, that's basically free money. Bot calculates position size using Kelly Criterion. Executes via Polymarket's API. Done. Within 2-3 seconds, other participants update the odds. 54/46 moves toward 78/22. Bot either exits for immediate profit or holds to resolution. Either way, the trade was entered with near-certainty of a positive outcome. Now repeat this 200-500 times per day. $313 → $2,382,780 in 4 months. Not magic. Not prediction. Not luck. Industrial-scale exploitation of a market inefficiency that still exists today. And you're still placing one manual trade per day and calling yourself a "trader." This is the mechanism behind every single dollar. Bookmark this post so you can study it again. Follow Himanshu Kumar because I'm breaking down each strategy separately. ↓ There are 4 strategies. Not all Claude bots do the same thing. Strategy 1: Latency Arbitrage. Win rate: 85-98%. What 0x8dxd used. Monitor Binance price feeds. When Polymarket odds lag behind reality by 3-5%, buy the correct side before the market corrects. No forecasting. No model. No sentiment analysis. Pure speed. You're not guessing. You're reading an outcome that has already happened. Strategy 2: Oracle Arbitrage. Win rate: 78-85%. Chainlink oracle price feeds occasionally diverge from Polymarket's implied prices. When they do, the settlement direction is known. Fewer opportunities. Higher certainty when they appear. Strategy 3: News-Driven Trading. Win rate: 60-75%. Claude ingests real-time news. Government filings. Central bank statements. On-chain data. Assesses probability impact before retail traders even finish reading the headline. Lower win rate because interpretation introduces uncertainty. But works on ANY market category, not just crypto. Strategy 4: Market Making. Return: 2-5% per month. Place buy and sell orders on both sides. Capture the spread. No prediction required. Most consistent. Hardest to blow up. Compounds aggressively over time. You didn't even know there were 4 strategies. You thought "trading bot" meant one thing. That's how far behind you are. 4 strategies. 4 different risk profiles. 4 ways to make money while you sleep. Save this post. Follow Himanshu Kumar for the deep dive into each one. ↓ The timeline that should haunt you. December 2025: Bot launches with $313. Nobody notices. January 6, 2026: Wallet hits ~$438,000. 140x in 30 days. 6,615 predictions. 98% win rate. Finbold reports it. Crypto Twitter explodes. March 10, 2026: Head-to-head test. Claude bot: $1,000 → $14,216 in 48 hours. +1,322%. OpenClaw bot: fully liquidated. Same market. Same timeframe. Claude won because of better risk management. OpenClaw died because it overleveraged. March 16, 2026: Someone trains a swarm model on 3 years of NBA data. Result: +$1.49M on Polymarket. April 2026: 0x8dxd final verified balance: $2,382,780.80. 26,738 trades. 4 months. This all happened while you were "waiting for the right time to start." The right time was December 2025. The second best time is right now. But you'll probably wait until it's too late. That's what you always do. Every date on this timeline is a day you could have started but didn't. Save this post. Follow Himanshu Kumar so you at least start today. ↓ Why Claude and not ChatGPT? This isn't opinion. It's data. March 2026 head-to-head: Claude bot: +1,322%. OpenClaw (GPT-based): liquidated. Same prompt. Same market. Same conditions. Researchers found Claude's code included: > More defensive edge cases > More conservative default parameters > Better error handling > More legible code for debugging > Proper Kelly Criterion position sizing > Hard drawdown kill switches ChatGPT's code overleveraged into a losing sequence and couldn't recover. Claude's code sized positions conservatively, stopped trading when drawdown thresholds hit, and survived to compound another day. The difference between +1,322% and liquidation wasn't the strategy. It was the risk management. And Claude writes better risk management than ChatGPT. That's not a debate. That's a $15,216 difference in 48 hours. But sure, keep using ChatGPT because "everyone uses it." Everyone's broke too. Coincidence? Stop using the popular tool. Start using the profitable one. Save this post. Follow Himanshu Kumar for more Claude vs ChatGPT comparisons with real data. ↓ Why humans lose to bots. Every single time. Same strategy. Same market. Same period. Bots: ~$206,000 profit. Humans: ~$100,000 profit. 2x gap. Same strategy. Here's why: 1. Late entries. By the time you identify the lag, verify your reasoning, and click buy, the 2.7 second window is gone. The bot executes in under 100ms. You execute in 30 seconds. The opportunity doesn't exist for 30 seconds. 2. Emotional sizing. You oversize when "confident." Undersize when scared. Exact opposite of Kelly math. The bot sizes based on edge. Every time. No feelings. 3. Fatigue. You make worse decisions at hour 6 than at hour 1. The bot makes the same decision at hour 72 that it made at hour 1. 4. Drawdown psychology. After 3 losses you either panic quit or double down trying to recover. Both destroy capital. The bot has a kill switch. It stops. It doesn't feel anything. You're not competing with other humans anymore. You're competing with machines that don't sleep, don't feel, don't flinch. And you're losing. The data doesn't lie. Humans lose to bots 2x on the same strategy. Save this post. Follow Himanshu Kumar for the complete bot setup that removes you from the equation. ↓ What can go wrong. Because I'm not going to lie to you. Most people who build this bot will NOT 7,942x their money. Some will lose their initial capital. Here's what can kill you: Edge compression. The arbitrage window was 12 seconds in 2024. It's 2.7 seconds now. It's shrinking. At some point it hits zero for retail operators. This is a time-limited opportunity. Not a permanent income stream. Rule changes. Polymarket can change contract mechanics, settlement rules, or API terms overnight. What worked yesterday can lose money tomorrow. Risk management bugs. A 98% win rate strategy with broken position sizing will blow up your account on the one losing trade. The March 2026 experiment proved this. Claude survived. OpenClaw got liquidated. Same strategy. Different risk management. That's why the 2-hour video tutorial walks through every single risk parameter. Because the strategy doesn't kill you. Bad risk management kills you. This is the section most "gurus" delete. I'm keeping it because I'd rather you make money safely than blow up and blame me. Save this post. Follow Himanshu Kumar for honest breakdowns, not hype. ↓ The step-by-step to build your own. Step 1: Set up a Polymarket wallet. Fund with USDC via Polygon network. Start with $100-$300 for testing. Step 2: Generate API credentials. CLOB API key from docs.polymarket .com. Store private key in environment variable. Never hardcode it. Never share it. Step 3: Prompt Claude to build the bot. Use Claude Code for best results. It reads your filesystem, executes code, and iterates on errors autonomously. Step 4: Paper trade for at least one week. Minimum 200 completed trades. Win rate must be above 70% before going live. This step is NOT optional. Step 5: Configure risk management. Max single position: 8% of portfolio. Daily loss limit: -20% with auto halt. Kill switch at -40% drawdown. Telegram alerts on every threshold. Step 6: Go live small. $1-5 per trade. Watch every trade for first week. Compare to paper results. Scale only on evidence. Skip steps 4 and 5 and you will lose your money. That's not a warning. That's a guarantee. This is your complete build guide. Save this post. Follow Himanshu Kumar because I'll be posting the exact Claude prompts for each strategy. ↓ The edge exists right now. Not next month. Not "when you're ready." Right now. The arbitrage window is 2.7 seconds. It was 12 seconds in 2024. It's shrinking every week. Every day you wait, more bots enter the space. The window gets smaller. Your potential returns get smaller. The bots already running have a compounding advantage. They're making money today that they'll use to make more money tomorrow. You're reading about it and telling yourself "I'll look into this next weekend." That's what you said last weekend. And the weekend before that. The best time to start was 6 months ago. The second best time is today. But you already know you're going to bookmark this and never open it again. Prove me wrong. ↓ Full 2-hour video tutorial attached. Every single click. Every command. Every parameter. From zero to running bot. Beginner friendly. Nothing skipped. A similar bot has already earned $2,382,780. Full blockchain proof in the article below. The video is free. The tools are free. The edge still exists. The only thing that costs money is another month of doing nothing while bots eat every opportunity you're too slow to catch. Follow Himanshu Kumar for the complete series covering every automated income stream using Claude. Prediction markets are just the beginning. Save this post. Bookmark it. Screenshot it. Whatever you need to do so you actually watch the video and build the bot instead of just reading about people who did. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

52,808 views • 3 months ago