The Ledger
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LLMs favor CLI tools over APIs due to massive pre-training data volumes
“I think that in pre-training, there's just an enormous amount of command line data. Like even let's ignore, let's like, let's ignore RL. Like you're doing no harness post training. Just the amount of like CLI versus API documentation for just like navigating t…”
NVIDIA uses 'Speed of Light' framework to define minimum viable goals
“SOL is a term that NVIDIA is used to sort of like instigate a compelling event. You say, this is done. How do we get there? What is the minimum, as much as necessary, as little as possible thing that it takes for us to get exactly here? And it helps you just b…”
Local document pre-fill with global sequence decode solves transformer quadratic scaling
“If pre-fill becomes local and decode is, is still global, you solve that pre-fill quadratic scaling problem because you have a bunch of like small chunks that you pre-fill independently.”
LLM prefill remains compute-bound while decoding phases are strictly memory-bound
“So prefill typically, and this changes as model architecture changes, prefill is right now compute bound. Most of the time. If the sequence is sufficiently long, it's compute bound on the decode side because you're doing a full pass over all the weights and th…”