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@study0718

CRYPTO TRADER || @megaeth ambassador

参加日 Temmuz 2015
2.1K フォロー中1.7K フォロワー
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study@study0718·
@SolEnrichHQ just shipped again - MPP integration hardened - holder-count fixed - comparewallets now multiwallet ready More endpoints incoming this week. Data layer for Solana agents getting stronger every day $SE @0xSardius CA: 677CpPEoKVo9tyCyBHqtiXZivUPdPXEigd3FspWuBAGS
Sardius@0xSardius

@SolEnrichHQ update: - shipped further hardening around endpoints and flow with MPP integration - shipped fixes for holder-count and upgraded compare-wallets to allow multi-wallet comparison - doing general admin and fixes before adding additional endpoints this week

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study@study0718·
AI’s real bottleneck isn’t models it’s memory Sessions reset. Intelligence doesn’t compound. @cludeproject is building portable, onchain memory that scales to 1B records. Not chat history infrastructure for the onchain AI economy $Clude @sebbsssss
seb@sebbsssss

Solving cold start is how we bring 1 billion memories onchain. Every AI system runs into the same bottleneck. Without memory, there is no context. No history. No continuity. No accumulated understanding. So every new session, agent, or application starts too close to zero. We think this is one of the biggest constraints in AI. And it will not be solved with chat history alone. If intelligence is going to compound, memory cannot stay trapped inside isolated apps or be rebuilt one prompt at a time. It has to be: importable, exportable, and explorable at scale. Size matters! That is how you solve cold start properly. @cludeproject will make it possible to seed systems with large bodies of memory from day one. From conversations, archives, records, histories, structured context, and layered narrative data. Everything you think it needs to remember. New Size, New Challenges But once memory begins to scale, the challenge changes. It is no longer just storage. It is structure. It is navigation. It is legibility. Because real memory does not grow in a straight line. It grows like a living system; through nodes, branches, clusters, pathways, recurrences, contradictions, and long-range dependencies. Not a transcript. Almost like a real human Brain. That is why we built the Memory Explorer. The Memory Explorer makes large memory systems visible and navigable in real time, allowing both humans and machines to move through memory at different levels of resolution: From high-level structures to dense clusters to specific nodes, links, and pathways. And when you see it in motion, it becomes obvious but also quite beautiful like its alive. memory is not just something to retrieve. It is something to explore. > Something to trace. > Something to grow. > Something to understand. Clude is not just an app. It is infrastructure for an AI economy onchain, designed for private memory packets to persist, move, and compound over time. Because if we want to bring 1 billion memories onchain, memory cannot remain static, fragmented, or locked inside isolated products. It has to become portable infrastructure for intelligence. What comes next Our upcoming release is the first major step in that direction. We will show how we are solving cold start through: > mass memory import/export > a fully explorable digital brain > a system designed to scale to one billion memories onchain A living memory system. A compounding intelligence layer. This is step one. More soon. ---- The mystery of life isn't a problem to solve, but a reality to experience.

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study@study0718·
Big move from @cludeproject Now entering @colosseum’s Solana Frontier Hackathon ($2.5M funding) They’re building persistent on-chain memory for AI agents cheaper, scalable, real semantic recall Fresh off a $250K win. Momentum strong $CLUDE
seb@sebbsssss

Not resting on our laurels. @cludeproject is excited to be entering and showcasing our product on the Frontier Hackathon

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study@study0718·
AI agents are bleeding tokens on “context tax” Clude demo: 200 memories → 2,081 tokens (native) vs 229 tokens (semantic recall) 89% savings, same output Persistent on-chain memory is becoming a key AI infra narrative
seb@sebbsssss

We rejoice when we see a larger context window model released. It's great but most people don't see the other side of things. Every loaded tool or extended context eats tokens whether you use it or not on that turn. It's what we call "context tax"; essentially you're being taxed (paying more tokens due to larger context windows) The recent announcement from @AnthropicAI on moving to API billing means the ‘context tax’ is now real. If you’re building agents, token-efficient memory architecture is no longer optional. Every token sent to an LLM introduces a tradeoff: increased cost, added latency, and diminishing performance. Beyond a certain threshold, additional context no longer improves outcomes. Instead, it leads to “context rot”, where the model becomes less effective as it struggles to navigate accumulated noise. So I tested this with Clude with real world production data and models. 200 memories. Same question. Same model. One run stuffs everything into the prompt. The other uses Clude's semantic recall to retrieve only what's relevant. Native: 2,081 input tokens. Clude: 229 input tokens. 89% fewer tokens. Same answer. And here's the part that matters at scale: without selective recall, your costs grow linearly with every memory you add. 1,000 memories? 10,000? Your prompt just keeps getting fatter. With Clude, it stays flat, because your agent only pulls what it needs for that specific query. This is one part of what we're building. @cludeproject separates memory from the model

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study@study0718·
Clude is a Solana based project building an on chain persistent memory layer for AI agents, enabling efficient semantic recall to cut context tax and token usage while turning personal memories into ownable, tradable on chain assets $CLUDE
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study@study0718·
89% token reduction demo live
seb@sebbsssss

We rejoice when we see a larger context window model released. It's great but most people don't see the other side of things. Every loaded tool or extended context eats tokens whether you use it or not on that turn. It's what we call "context tax"; essentially you're being taxed (paying more tokens due to larger context windows) The recent announcement from @AnthropicAI on moving to API billing means the ‘context tax’ is now real. If you’re building agents, token-efficient memory architecture is no longer optional. Every token sent to an LLM introduces a tradeoff: increased cost, added latency, and diminishing performance. Beyond a certain threshold, additional context no longer improves outcomes. Instead, it leads to “context rot”, where the model becomes less effective as it struggles to navigate accumulated noise. So I tested this with Clude with real world production data and models. 200 memories. Same question. Same model. One run stuffs everything into the prompt. The other uses Clude's semantic recall to retrieve only what's relevant. Native: 2,081 input tokens. Clude: 229 input tokens. 89% fewer tokens. Same answer. And here's the part that matters at scale: without selective recall, your costs grow linearly with every memory you add. 1,000 memories? 10,000? Your prompt just keeps getting fatter. With Clude, it stays flat, because your agent only pulls what it needs for that specific query. This is one part of what we're building. @cludeproject separates memory from the model

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study@study0718·
3 Ways to Use Clude Python — pip install clude and call the Cortex API with a clean async interface TypeScript — Compose clude-brain with your choice of provider MCP — npx clude-bot mcp-serve to use memory from any MCP-compatible editor
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study@study0718·
$SYNA Founder is an Ironman athlete + neurosurgical researcher building Synapse Neuro AI to connect data rich individuals with life saving scientists Demo already shown at MCG, early supporters joining, funding targeted by month end Keeping it on watch @synapseneuro_ai
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study@study0718·
Gem alert on Solana @SolEnrichHQ built by @0xSardius (10y crypto vet) who’s 100% focused on ONE thing: x402 + MPP for agentic commerce
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study@study0718·
Phase 2 MPP integration is live for @SolEnrichHQ All x402 endpoints are now active, unlocking 16 new ways for agents & LLMs to enrich Solana data. First movers in MPP for agentic commerce on Solana. Built by @0xSardius $SE
Solenrich@SolEnrichHQ

Phase 2 for MPP integration complete! MPP endpoints shipped alongside all of our existing x402 endpoints 16 ways to enrich data on solana for your agent/llm first mover in the MPP space for agentic commerce on solana, more to come @BagsApp @BagsHackathon @finnbags

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study@study0718·
GM Solana SolEnrichHQ just shipped Phase 2 MPP integration unlocking 16 new enrichment endpoints (x402 + MPP) built for agents & LLM workflows. Payments: USDC on Solana or credit card via MPP. Agentic commerce is getting real. Built by @0xSardius @SolEnrichHQ $SE
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study@study0718·
GSD just dropped $GSD browser a serious unlock for AI agents One install → agents can browse, click, type, debug & test sites reliably No flaky selectors Stable snapshots + Rust speed Agentic browser automation is finally getting real
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study@study0718·
While most Solana tokens bleed holders daily, $GSD still has 80.2% of wallets holding after 30+ days That’s not luck that’s conviction in the product An agentic AI operating system with serious builders behind it Patience here could pay off big
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study@study0718·
Remember when one viral meme could run to 9 figures? Now everything gets cloned and PvP’d to zero in hours $BIGLY flips the playbook: • One hyped launch weekly • Presale builds real bags • Auction sets name/ticker/narrative + 50% fees • Thick LP, all attention on one coin
fiatphobia@fiatphobia

if something went viral before, traders actually had new memes run to 9 figures now, the second anything catches attention, it gets cloned to death and PvP’d to zero @BiglyApp fixes that one hyped launch a week. no vamping. all the attention in one place.

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GSD@gsd_foundation·
@study0718 Glad you appreciated it 🤙🏻
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study@study0718·
Just read @gsd_foundation’s April Fools thread “Partnered with the Dept of War to /gsd:deploy autonomous weapons and give everyone a git-controlled STATE.md.” Unhinged, dark, and painfully on-point tech satire
GSD@gsd_foundation

Over the last couple weeks, we’ve been in negotiations with the @DeptofWar regarding implementation of the GSD framework into US military operations worldwide. We’re going to be working very closely with the @PeteHegseth and his team in two key areas: [1/4]

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