Ritual Blockchain: Unlocking New Economic and Governance Paradigms with Native Precompiles Ritual is often dismissed as “just another chain with precompiles,” but that view misses the transformative potential of its built‑in primitives By exposing low‑level, gas‑efficient modules directly to smart contracts, @ritualnet enables architectural patterns that are either impossible or prohibitively expensive on other major L1 The result is a platform where sovereign agents, identity markets, private multimodal interfaces, agent‑native companies, and machine‑centric market structures can be built natively, without the heavy‑handed workarounds that dominate today’s ecosystem

Analysis: The new “constructive strategic stability” paradigm between the U.S. and China requires balancing active cooperation with careful risk management, setting a cautious but optimistic long-term trajectory for the two superpowers.

Privacy is the next inevitable paradigm of Web3. Blockchain’s first decade chased full transparency. but now, on-chain privacy has become the core demand for institutions, businesses and regular users. We’re thrilled to launch OpenBuild × Aleo Bootcamp @AleoHQ @Aleo_Asia @Aleo_CH Aleo 101: Build Your First Privacy App From Scratch 🗓 Starts: May 8 ✅ No cryptography background required ✅ Master Leo v4.0 & ZK fundamentals ✅ Full hands-on: setup → coding → deployment ✅ Build & launch your real privacy dApp ✅ Access Aleo ecosystem resources & bounty opportunities Solidity / Rust basic knowledge is all you need to join. Secure your spot now and become a builder in the privacy Web3 era👇

The Underpriced Truth: Agentic AI Is a Paradigm Shift Centered on Memory 1/ The market will slowly realize: Agentic AI is memory-centric, not compute-centric. The new hardware stack is: ① Memory — HBM / DRAM / NAND ② Parallel compute — GPU / ASIC ③ Coordinator — CPU CPUs stopped doing the heavy lifting a long time ago. This isn't a cycle. It's a paradigm. 🧵👇 2/ First principles Humanity's ultimate pursuit of intelligence has always been two things: Infinite memory + infinite compute. When we say someone is smart, we mean two things: "good memory" + "fast thinking." Machine intelligence is walking the exact same path. 3/ The story the market already understands: HBM LLM inference's decode stage is a textbook memory-bound workload. Every token generated → drag the entire KV cache across memory. Bandwidth too low → expensive GPUs sit idle. That's why every new GPU generation ships with more HBM bandwidth and capacity. 4/ The story the market is missing The "1M context" you keep hearing about? It is not assembled inside the GPU inference cluster. So where is it actually built? 5/ It's built on the traditional servers running the agentic system Those CPU + huge-DRAM servers are quietly doing the heaviest lifting: • loading user long-term & short-term memory • loading the agent's system spec / prompt • loading skill / tool / subagent definitions • compressing the context once it overflows 1M tokens All of this lives in DRAM, not HBM. 6/ Compare this to the previous era In the web / mobile era, we barely stored any user context at all. Only search / recsys / ads kept a small user profile — maybe 1/20, even 1/100 of the data volume an agentic system needs today. That asymmetry is the real overlooked inflection point. 7/ The supply chain is already telling this story Server CPU : DRAM ratio is climbing fast: • Web / Mobile era: 1 core : 4 GB • Agentic AI today: 1 core : 16 GB • Deep agentic future: 1 core : 64 GB and beyond 8/ And it's NOT just "4x more memory" Under agentic workloads, a single CPU serves a fraction of the users it used to. When the entire IT stack migrates to agentic: • CPU count grows several-fold to ~10x • DRAM total grows tens-fold to ~100x That's the part nobody is pricing in. 9/ The conclusion Agentic AI is a paradigm shift centered on storage + parallel compute. The software paradigm changed. The hardware paradigm changed with it. Only those who deeply understand the technology will see it: This isn't a memory cycle. It's a memory paradigm. 10/ Time horizon Given how early we still are on: • user adoption rate • depth of usage per user We are at least 5 years away from the cyclical top of this memory wave. (Zoom out far enough and everything is a cycle — but this one is nowhere near peak.) $MU $DRAM $SNDK

🥇Crypto VC Tier List for 2026 • S: @a16zcrypto • A: @cbventures • B: @paradigm, @ARKInvest, @galaxyhq, @sequoia, @dragonfly_xyz 📌 The ranking is based on funds’ presence in this year’s crypto funding market: access to major rounds, deal activity, and lead participation. Overall Retail ROI is used as a secondary track record metric.