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⠀⠀⠀ ⠀⠀ ⋆ proofs : #vminfeeds ⠀ ⋆ mails : #vminhaul ⠀ ⋆ updates : #byvminkartz ⠀⠀ ╰╮ ᥫ᭡.

lara

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18,523 görüntüleme • 1 yıl önce •via X (Twitter)

#vminfeeds #vminhaul #byvminkartz

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ZKForge

24,207 görüntüleme • 8 ay önce

Why the S&P 500 Will Be Forced To Buy Bitcoin In this Swan Bitcoin presentation, Adam Livingston explains why passive index mechanics will force the S&P 500 to ingest Bitcoin exposure the moment Strategy qualifies for inclusion. This is not about taste or ideology, it is about rules, float, weights, and the blind math of passive flows. When the index updates the list, trillions in benchmark trackers and benchmark huggers follow, which pipes Bitcoin exposure into every 401k and pension that hugs the S&P. You will learn: - The exact checklist for S&P 500 inclusion and how Strategy now clears it - How passive funds like SPY and VOO are compelled to buy new entrants, not asked - Why a small initial weight can still trigger billions in forced purchases - How spot Bitcoin ETFs amplify the same flows with daily rebalancing - The reflexive loop that forms when Bitcoin rises, Strategy’s weight rises, and passive capital buys again - Real world proofs from prior inclusions that show how fast the index effect hits - Why miners, exchanges, and Bitcoin treasury companies create a second order wave of exposure - Why this is inevitability, not opinion Who this is for: - Finance pros who want the plumbing, not the memes - Bitcoiners who need a clean, shareable explanation for skeptics - CIOs, advisors, and analysts who live and die by benchmark risk Why it matters: - The passive system cannot ignore Bitcoin once the rules are triggered - Index mechanics will distribute Bitcoin exposure across global portfolios by default

Why the S&P 500 Will Be Forced To Buy Bitcoin In this Swan Bitcoin presentation, Adam Livingston explains why passive index mechanics will force the S&P 500 to ingest Bitcoin exposure the moment Strategy qualifies for inclusion. This is not about taste or ideology, it is about rules, float, weights, and the blind math of passive flows. When the index updates the list, trillions in benchmark trackers and benchmark huggers follow, which pipes Bitcoin exposure into every 401k and pension that hugs the S&P. You will learn: - The exact checklist for S&P 500 inclusion and how Strategy now clears it - How passive funds like SPY and VOO are compelled to buy new entrants, not asked - Why a small initial weight can still trigger billions in forced purchases - How spot Bitcoin ETFs amplify the same flows with daily rebalancing - The reflexive loop that forms when Bitcoin rises, Strategy’s weight rises, and passive capital buys again - Real world proofs from prior inclusions that show how fast the index effect hits - Why miners, exchanges, and Bitcoin treasury companies create a second order wave of exposure - Why this is inevitability, not opinion Who this is for: - Finance pros who want the plumbing, not the memes - Bitcoiners who need a clean, shareable explanation for skeptics - CIOs, advisors, and analysts who live and die by benchmark risk Why it matters: - The passive system cannot ignore Bitcoin once the rules are triggered - Index mechanics will distribute Bitcoin exposure across global portfolios by default

Swan

25,982 görüntüleme • 11 ay önce

🔥 Important Message to all Pioneers 🔥 If you’re listening to this and you know what I’m talking about — you’re already rich. Not today. Not tomorrow maybe. But 100% — in the end — you are rich. We showed the world the proofs. The updates. The partnerships. The recognition of Pi Network as the new system, the new standard. It’s not a dream anymore — it’s a reality in progress. And let me remind you: Pi was never “free money.” That’s in the disclaimer. What Dr. Nicolas Kokkalis gave us is a choice. 👉 Hold $Pi. 👉 Trust Pi Network. 👉 Build with the vision. That’s the contract between us and the founders. He didn’t stop us. He didn’t reject us. That silence is confirmation. Consensus is the path. Look around you — apps, utilities, communities in every country. People building, people transacting, people believing. This is not a game anymore. This is the new economy. So if you want to sell out for cents, that’s on you. But if you want to change your life — and the lives of millions — you hold. You trust. You build. Because Pi is worth what we make it worth. And together… we already decided. 💥 314,159 💥 The Global Consensus isn’t coming. It It’s already here. Pi is worth what we make it worth. And together, we’ve decided. Join now and be part of the future: 👉 my username odaixx as your invitation code. Sign up with your real name (copy it from your ID/Passport) to secure your bonus 1 Pi and build your security circle. This is the new economy. Don’t miss it.

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Pi King 👑 𝛑

18,497 görüntüleme • 10 ay önce

I see lots of people launching projects where their agents weigh and interact with information they are provided with via X through their X accounts. I've been experimenting with agent function and for long before it was popular on X, so, it had been made very clear to me long before that such automations and their functions are nothing but novel instances of surface level "interaction", yet it is hard to even call it that. The weighing of these instances is something that I find if stressed and iterated upon, could produce a more capable agentic framework. I've outlined how the depicted error and rewarding loop can be improved to make a better agent. I intend to move agentic function beyond theatrical loops of prompt and response by interrogating the optimization substrate itself. Rather than treating reward as a convenient scalar pat on the head, I frame agent behavior as a constrained variational problem over latent state transitions, where policy updates approximate inference under structured uncertainty. My approach draws less from corporate folklore and more from specific technical inflection points such as the reanalysis framework in Reanalyse: A Simple Way to Improve Sample Efficiency in RL by Julian Schrittwieser and colleagues, the planning architecture of Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm by David Silver et al., and the value decomposition insights in QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning by Tabish Rashid. What interests me is not their surface performance but the structural concessions they make to tractability. By embedding differentiable world models and amortized belief updates into the agentic loop, I treat interaction as recursive posterior refinement across partially observable manifolds, not as a parade of conditioned tokens but as an evolving distribution over trajectories. At a higher altitude, I see agentic improvement as a question of mathematical hygiene. How does one approximate optimal control in a non convex landscape without dissolving into instability under recursive self modification. The error reward cycle, so often romanticized, is in fact a delicate dynamical system whose gradient flows inhabit curved statistical manifolds. Insights from regret bounds in bandit theory, contraction mappings in dynamic programming, and spectral analysis of iterative operators suggest that coherence is less about clever prompting and more about fixed point behavior under perturbation. I am particularly preoccupied with the spectral radius of update operators, the existence and uniqueness of equilibria in combinatorial policy spaces, and the computational hardness that shadows long horizon planning. If the agent is to be more than an improviser with memory, its loop must satisfy constraints that are as much algebraic as empirical, grounded in proofs of convergence rather than optimism about scale. -I’m not the greatest performer, so please bear with my narration in the video!

I see lots of people launching projects where their agents weigh and interact with information they are provided with via X through their X accounts. I've been experimenting with agent function and for long before it was popular on X, so, it had been made very clear to me long before that such automations and their functions are nothing but novel instances of surface level "interaction", yet it is hard to even call it that. The weighing of these instances is something that I find if stressed and iterated upon, could produce a more capable agentic framework. I've outlined how the depicted error and rewarding loop can be improved to make a better agent. I intend to move agentic function beyond theatrical loops of prompt and response by interrogating the optimization substrate itself. Rather than treating reward as a convenient scalar pat on the head, I frame agent behavior as a constrained variational problem over latent state transitions, where policy updates approximate inference under structured uncertainty. My approach draws less from corporate folklore and more from specific technical inflection points such as the reanalysis framework in Reanalyse: A Simple Way to Improve Sample Efficiency in RL by Julian Schrittwieser and colleagues, the planning architecture of Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm by David Silver et al., and the value decomposition insights in QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning by Tabish Rashid. What interests me is not their surface performance but the structural concessions they make to tractability. By embedding differentiable world models and amortized belief updates into the agentic loop, I treat interaction as recursive posterior refinement across partially observable manifolds, not as a parade of conditioned tokens but as an evolving distribution over trajectories. At a higher altitude, I see agentic improvement as a question of mathematical hygiene. How does one approximate optimal control in a non convex landscape without dissolving into instability under recursive self modification. The error reward cycle, so often romanticized, is in fact a delicate dynamical system whose gradient flows inhabit curved statistical manifolds. Insights from regret bounds in bandit theory, contraction mappings in dynamic programming, and spectral analysis of iterative operators suggest that coherence is less about clever prompting and more about fixed point behavior under perturbation. I am particularly preoccupied with the spectral radius of update operators, the existence and uniqueness of equilibria in combinatorial policy spaces, and the computational hardness that shadows long horizon planning. If the agent is to be more than an improviser with memory, its loop must satisfy constraints that are as much algebraic as empirical, grounded in proofs of convergence rather than optimism about scale. -I’m not the greatest performer, so please bear with my narration in the video!

Caro

246,343 görüntüleme • 5 ay önce

🚀SEC’s Game-Changing Policy Fuels DeFi & RWA Revolution! The SEC’s Q2 2025 policy shift is setting Decentralized Finance (DeFi) on fire, with Real-World Assets (RWAs) leading the charge. Is a new DeFi Summer brewing? Join HTX to stay ahead! 🔥 Three SEC Moves Powering the Future: 1️⃣ Innovation Exemption: Highly decentralized protocols get temporary relief from registration requirements in pilot programs, cutting legal risks. 2️⃣ Functional Categorization Framework: Regulations now target on-chain operations and business logic, moving away from blanket “securities” labels for tokens. 3️⃣ Regulatory Sandbox for DAOs & RWAs: A safe space for testing DAOs and RWAs, blending cutting-edge innovation with compliance. 💡 Why RWAs Are Stealing the Show: 🔹 Easier Compliance: Tokenizing assets like real estate, bonds, or supply chain finance just got smoother, with fewer securities classification hurdles. 🔹Institutional Money Rush: The sandbox and transparency are pulling in big players. Ondo Finance’s OUSG issuance skyrocketed 40% post-policy, while Maple Finance and Centrifuge attract pension funds and asset managers. 💰 🔹Tech Breakthroughs: Zero-knowledge proofs (ZKPs), homomorphic encryption, and cross-chain solutions supercharge security, KYC/AML compliance, and multi-chain interoperability. 🔹 Market on Fire: DeFi’s TVL surged 17% (from $46B to $54B) in just one week! Governance tokens like UNI, AAVE, and MKR soared 25-60%, outpacing BTC and ETH. 📈 🔹DeFi Meets TradFi: RWAs bridge DeFi with traditional finance, unlocking tokenized real estate, invoice financing, and more for a seamless “on-chain + off-chain” ecosystem. 🌐 The Road Ahead: DeFi is shifting from “wild growth” to “compliant powerhouse.” New revenue models like protocol profit-sharing and asset management, plus hybrid governance (on-chain voting + off-chain legal frameworks), are reshaping the game. RWAs are poised to lead, with DeFi blue-chip tokens ready for a valuation reboot. The SEC’s pivot is a launchpad for institutional adoption and market maturity—#HTX is your front-row seat! 💭 My Take: The SEC’s policy is a massive win for DeFi, turbocharging RWAs and setting the stage for a potential bull run 🌸 Is the place to track this revolution! What’s your bet—will RWAs spark the next DeFi wave? 👉 Follow HTX for the hottest DeFi, RWA, and crypto updates! H.E. Justin Sun 👨‍🚀 🌞 HTX #TRX #TRONEcoStar

🚀SEC’s Game-Changing Policy Fuels DeFi & RWA Revolution! The SEC’s Q2 2025 policy shift is setting Decentralized Finance (DeFi) on fire, with Real-World Assets (RWAs) leading the charge. Is a new DeFi Summer brewing? Join HTX to stay ahead! 🔥 Three SEC Moves Powering the Future: 1️⃣ Innovation Exemption: Highly decentralized protocols get temporary relief from registration requirements in pilot programs, cutting legal risks. 2️⃣ Functional Categorization Framework: Regulations now target on-chain operations and business logic, moving away from blanket “securities” labels for tokens. 3️⃣ Regulatory Sandbox for DAOs & RWAs: A safe space for testing DAOs and RWAs, blending cutting-edge innovation with compliance. 💡 Why RWAs Are Stealing the Show: 🔹 Easier Compliance: Tokenizing assets like real estate, bonds, or supply chain finance just got smoother, with fewer securities classification hurdles. 🔹Institutional Money Rush: The sandbox and transparency are pulling in big players. Ondo Finance’s OUSG issuance skyrocketed 40% post-policy, while Maple Finance and Centrifuge attract pension funds and asset managers. 💰 🔹Tech Breakthroughs: Zero-knowledge proofs (ZKPs), homomorphic encryption, and cross-chain solutions supercharge security, KYC/AML compliance, and multi-chain interoperability. 🔹 Market on Fire: DeFi’s TVL surged 17% (from $46B to $54B) in just one week! Governance tokens like UNI, AAVE, and MKR soared 25-60%, outpacing BTC and ETH. 📈 🔹DeFi Meets TradFi: RWAs bridge DeFi with traditional finance, unlocking tokenized real estate, invoice financing, and more for a seamless “on-chain + off-chain” ecosystem. 🌐 The Road Ahead: DeFi is shifting from “wild growth” to “compliant powerhouse.” New revenue models like protocol profit-sharing and asset management, plus hybrid governance (on-chain voting + off-chain legal frameworks), are reshaping the game. RWAs are poised to lead, with DeFi blue-chip tokens ready for a valuation reboot. The SEC’s pivot is a launchpad for institutional adoption and market maturity—#HTX is your front-row seat! 💭 My Take: The SEC’s policy is a massive win for DeFi, turbocharging RWAs and setting the stage for a potential bull run 🌸 Is the place to track this revolution! What’s your bet—will RWAs spark the next DeFi wave? 👉 Follow HTX for the hottest DeFi, RWA, and crypto updates! H.E. Justin Sun 👨‍🚀 🌞 HTX #TRX #TRONEcoStar

Hồng Ngọc | Ruby💎| EarnHTX

25,942 görüntüleme • 1 yıl önce