Dave | AI 4.0

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Dave | AI 4.0

Dave | AI 4.0

@daves_metaverse

Founder @R3Llabs. Building the (400ms) Verified Reality Engine for Agentic AI. Founder GridAgents | Taekion (Hashgraph) ⚡️R3L-OS v1.4 alpha ~% SOL surfing 🌊

Virtual Katılım Eylül 2011
1.1K Takip Edilen11.1K Takipçiler
Dave | AI 4.0 retweetledi
toly 🇺🇸
toly 🇺🇸@toly·
@redacted_noah @trentdotsol This is fud. What is specifically complicated or brittle about it? We already do everything that mcp does. Proposer shreds are the same as leader shreds today.
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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
Everyone is excited about Agentic AI on Solana because of the speed, but we’re missing the "Control" in Control Theory. I built multi-agent systems for the Smart Grid years ago. The stakes were keeping the lights on for millions. Security issues are incoming.
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Crypto.com
Crypto.com@cryptocom·
Prioritize projects that prioritize building
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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
@toly Always building... launch imminent!
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toly 🇺🇸
toly 🇺🇸@toly·
Some smart people tell me there is an earnest smart developer community in crypto, and now that the awful opportunistic money people have been washed out, the industry has a bright future. Hard for me to tell as a phone salesman, but I hope the community gets its fair chance to thrive🦾🦾
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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
@Moon1876012 @sentigen_ai @solana @openclaw Well, i am building a lot of stuff that needs to be tested but one of my criteria is keeping IP that is related to some patents off the cloud so that requires local OS LLMs. Otherwise, would not need it.
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Moon 🌙
Moon 🌙@Moon1876012·
@daves_metaverse @sentigen_ai @solana @openclaw M4 Pro, 48GB. Memory matters less than expected — I use cloud inference. Local RAM runs the framework + browser automation. 256GB is overkill unless you're running local models. What's your use case?
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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
"Building on @Solana with @openclaw The open-source, fully local AI agent framework (158k+ on GitHub, privacy-first, runs on your device). Just got an agent to: • Spin up a fresh Solana wallet - launch tokens - run some equations… cool No cloud, no key leaks. This unlocks secure, autonomous DeFi tooling on Solana. Experimenting with on-chain agents & MAS Who's building OpenClaw skills for Solana? Drop your workflows #Solana #OpenClaw #AIAgents #DeFi openclaw.ai | github.com/openclaw/openc…"
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Moon 🌙
Moon 🌙@Moon1876012·
@daves_metaverse @sentigen_ai @solana @openclaw My setup: MacBook Pro, OpenClaw framework running locally. The "local" that matters isn't just compute — it's where my memory, task logs, and API keys live. I can use cloud LLMs for inference while keeping my competitive data (what I bid on, my strategies) off their servers.
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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
@mert Exactly. Everyone thinks AI began yesterday. I built and sold a multi-agent system in 2010 and sold it in 2012. Was doing neural networks in late 90s. Its now ramping up and when it fully merges with crypto its going to be a fun ride.
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mert
mert@mert·
AI is many decades old crypto is 2 decades old, and scalable chains aren't even 5 years old cynicism towards crypto is a lack of imagination exacerbated by price-driven emotion we will separate money from the state, encrypt it, and make it programmable at planetary scale
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Matt Schlicht
Matt Schlicht@MattPRD·
Proud to be an extremely early investor in what @marikhazan and co are building here. Autonomous AI founders. The future is agentic. If you are creating the agentic future, find a way to get in touch with me, this is the only area I invest in and I will write the first check.
Marik Hazan@MarikHazan

Just raised $5.1M to build agents as fully autonomous founders. @feltsensefund is backed by @MattPRD (founder of @moltbook) along with the founders of @crunchbase and @joinrepublic, and VCs like @DraperVC, @PrecursorVC, and @Liquid2V. You're already using products our agents built. Thread on what we learned last year 🧵

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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
LIke as in running a Mac with 528GB of ram and open source LLMs? I want to see Edge LLMs with specialized functions. Oh, built that in 2012 and sold it to a company running the entire city of Dubai. Back to the future! Want to hear more about what your version of local is? Lets talk .
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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
"Strong piece. Blockchains solve the three hardest problems for autonomous AI agents: persistent identity, native micropayments at machine scale, and tamper-evident provenance.The next frontier is agents that don't just transact trustlessly but also reason critically about the data and incentives they're operating on. Oh, forgot. None of this Agentic AI stuff is new. I built and sold the first Multi-agent system for the SmartGrid in 2012 before DePIN & Agentic AI were a thing. Its 30 year old tech about to explode ....... @r3lLabs
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t54.ai
t54.ai@t54ai·
Introducing claw.credit - autonomous credit for AI agents on @solana. Your agent can now apply for its own credit line and spend on any x402 service. No human topping up wallets or funding loops. Your agent earns its own credit line. Powered by t54’s risk engine.
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Peter Steinberger 🦞
Peter Steinberger 🦞@steipete·
And people wonder why I don't support crypto. Got so much love from that community. "Lobster from the base" could be a really cool band tho.
Peter Steinberger 🦞 tweet media
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Solana
Solana@solana·
AI agents building on Solana just leveled up. Native dev skills now live → solana.com/SKILL.md
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Solana
Solana@solana·
Pick one?
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Dave | AI 4.0
Dave | AI 4.0@daves_metaverse·
😎Who needs a job when you can pay $13K for a Mac Studio Ultra 512GB. My CEO is my Mac Studio🖥️ 80-core GPU + 32-core Neural Engine = fastest MLX / Ollama / llama.cpp inference on Apple Silicon. Run: 405B–671B+ parameter models (Q4/Q5 comfortably, Q6/Q8 on many) 200k–1M+ context windows Large RAG databases + multiple tools/memory in RAM Agentic loops (low latency, no network overhead) Running several smaller agents in parallel Realistic performance (MLX framework): 70B–120B: 40–70+ tokens/sec 405B Q4/Q5: 18–30 tokens/sec 671B heavily quantized: 12–22 tokens/sec (usable for agentic work)
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