Foundations of Large Language Models

Large language models originated from natural language processing, but they have undoubtedly become one of the most revolutionary technological advancements in the field of artificial intelligence in recent years.

I hope that, with the release of DeepSeek R1, and its proven capabilities to beat ChatGPT on many tasks, we will go back to using deep research to continue to make LLMs better, instead of hyping it up with superficial buzzwords.

🔸Here’s an awesome openbook from Tong Xiao and Jingbo Zhu that I think will help people leverage First Principle Thinking to breakdown complex problems that exist today with LLMs, into smaller digestible gaps, so they can redesign or rebuild from the ground up.

🔸This is what makes AI cheaper long-term and more accessible to everyone. Race to the bottom is a natural course of technology.

Foundations of Large Language Models explores basics concepts of LLMs such as:

🔹Pre-Training methods and model architectures

🔹Building models and scaling to train

🔹Prompting strategies, like chain-of-thought

🔹Alignment methods, like RLHF

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