Sane + 🌶️ takes in an insane AI world... AI capabilities researcher: co-created RLHF/ChatGPT @ @openai now trying to right the wrong 🤭 (ceo @typesafeai)

We all know intelligence is spikey/jagged - but do we know _why_ it is? TL;DR is everyone is cheating in AI (and because we're releasing 🤫 soon, we're making precommitments to do better 💪)
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Lies, Damned Lies, and Benchmarks

As the famously misattributed quote goes: “There are three kinds of lies: lies, damned lies, and statistics.” There is now a fourth kind: AI benchmarks. Benchmarks got us to incredibly smart AI. What

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Sutton's bitter lesson is roughly: scale > algorithms Sharing the wisdom that anyone who has made ML useful knows: neither scaling nor algorithms is the be-all and end-all
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The Bitterest Lesson

TL;DR: Compute drives progress in AI, but what good is progress if you are not doing the right task! Rich Sutton's bitter lesson states that compute beats algorithms. Researchers want to encode their

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Wrote about the incredibly important KV cache: - Why are people spending so much on agents - How is inference so profitable all of a sudden (+ why it won't last) - Why routing doesn't work P.S. they also constrain the design space for coding agents A LOT
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(KV) Cache Rules Everything Around Me

TL;DR: The biggest cost to devs of an agent is re-reading its own context, which costs the provider close to nothing to serve. Background Pop quiz: what's the most important cost when running an

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