Reading
A running list of books, papers, and articles I'm currently reading or recently read.
Recent
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It is becoming clear that Small Language Models are marginally better when the underlying parameters are about the same. Results from this paper claim that the models generally have 1% deviation from each other in results.
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Bringing long-term memory to inference
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Great lectures by Andrew Ng and the Stanford team. Thank you to Stanford for making this available to the public.
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There is a general notion that LLMs are nondeterministic due to concurrency and floating points roundoff on the GPU. This paper revisits that idea that LLMs can become deterministic.