https://www.interconnects.ai/p/building-on-evaluation-quicksand Building on evaluation quicksandNathan LambertOct 16, 2024 “In my article on “Big Tech’s LLM evals are just marketing,” I didn’t uncover the deeper reasons as to why can’t fully
What I Read: Transformers Inference Optimization
https://astralord.github.io/posts/transformer-inference-optimization-toolset Transformers Inference Optimization ToolsetAleksandr SamarinOct 1, 2024 “Large Language Models are pushing the boundaries of artificial intelligence, but their immense size poses significant computational challenges. As these models grow,
What I Read: LLMs, 2024
https://simonwillison.net/2024/Dec/31/llms-in-2024 Things we learned about LLMs in 2024Simon Willison31st December 2024 “A lot has happened in the world of Large Language Models over the course of 2024.”
What I Read: embedding models
https://unstructured.io/blog/understanding-embedding-models-make-an-informed-choice-for-your-rag Understanding embedding models: make an informed choice for your RAGMaria KhalusovaAug 13, 2024 “How do you choose a suitable embedding model for your RAG application?”
What I Watch: How LLMs store facts
How might LLMs store facts | Chapter 7, Deep Learning3Blue1BrownAug 31, 2024 “Unpacking the multilayer perceptrons in a transformer, and how they may store facts”