Nadav

@nadav

25 Following

842 Followers

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What is the most thorough and up to date research writing on what accounts for stablecoin volumes?

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what tools do people use for AI dictation? I sometimes want to ramble to dictate high level thoughts to eg chatgpt or claude and then have it translate that to a PRD or RFC or spec, but the audio tools in those products are too optimized to the conversational use case — I don't want a back n forth, just listen to me and do what I say

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Succinct non interactive arguments of *reasoning* to the rescue. Only half kidding…

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say you had to measure your organization's effective usage of AI as a KPI. how would you do it? particularly for engineers

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What are good frameworks or tools for building your own agents — not for posting on Twitter, but for useful knowledge work (eg sorting through email daily)

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we're looking to hire a cracked brand designer. who's the best out there or who should I talk to that knows that person?

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what is the most sober high-signal piece of writing about AI agents in the context of crypto

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𝚐𝔪𝟾𝚡𝚡𝟾 pfp

𝚐𝔪𝟾𝚡𝚡𝟾

INTELLECT-1, the first 10B model trained via a decentralized framework, is now officially released. The release includes the base model, checkpoints, post-trained models, datasets, technical report, and training framework. Another w for open source! This demonstrates the potential of decentralized deep learning to collaboratively build large-scale models. https://www.primeintellect.ai/blog/intellect-1-release

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determinism without provability is probably under researched, though not sure if that’s remotely feasible given floats are non deterministic

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@remco from Worldcoin had a cool talk on this in Devcon from a few years ago and prob best source for practical knowledge on zkML / zk neural nets. AFAIK for any model reasonably large or useful by modern standards though TEEs are the closest you can get today — cool stuff from Nous research here

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what is the state of art for how wallets are determining ERC20 token lists nowadays?

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In other words, I always thought “decentralized AI” was maybe a little bit of a solution looking for a problem because of OSS models like Llama. But that might no longer be the case

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The emergence of a test-time compute overhang in scaling reasoning models implies a surprising importance to decentralized inference. If the most useful and insightful things AIs can do require enormous amounts of inference compute, it means the highest leverage work output in the world is censorable (or worse, abusable) by an incredibly small number of people.

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anyone know if they're on FC?

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love Nous. should we get those guys in here?

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https://huggingface.co/papers/2411.04905

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https://huggingface.co/papers/2411.10440

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interesting result from @danrobinson https://www.paradigm.xyz/2024/11/pm-amm

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