Signals

Exploring how Markov chains serve as foundational language models and their relationship to modern LLMs through temperature control and state transitions.

A foundational AI research insight: general computational methods ultimately outperform human knowledge-based approaches.

A general audience introduction to how large language models like ChatGPT are built, from data collection to neural network training.

How physics training in linear algebra, tensor calculus, and entropy provides the mathematical foundation for understanding LLMs.

A technical discussion on the challenges of PDF parsing and why computer vision approaches often work better than traditional metadata-based methods.

A deep dive into the ongoing discussion about whether large language models truly understand the world or simply excel at pattern recognition.