Cohere Research Blog
One of my favorite AI research labs with excelent resources to learn AI at all levels. See their research papers if you want to go deeper.
Resources that I like and keep coming back to.
One of my favorite AI research labs with excelent resources to learn AI at all levels. See their research papers if you want to go deeper.
To my Eyes, the AI Evals GOAT. Hands-on, opinionated pieces on LLM evals, fine-tuning, and shipping real AI products. Heavy on what actually works in practice.
On evaluating and iterating on AI products — useful for anyone trying to measure whether their LLM app is actually getting better.
The Langfuse team on LLM observability, tracing, and evals — practical reading if you're putting LLM apps into production.
Some of the clearest writing on ML systems and AI engineering — production-grade and low on hype. Her books are a natural next step.
Anthropic's research hub — interpretability, alignment, and safety work alongside the model releases. Strong on the "why," not just the "what."
OpenAI's research releases and publications, straight from the source. Good for tracking where frontier model capabilities are heading.
A newsletter on AI, product, and strategy — digestible takes on where the field is heading and what it means for builders.
Applied ML and LLM systems explained with a practitioner's eye — recsys, evals, and design patterns you can put to use.
Writing at the intersection of AI, security, and human meaning. Big-picture takes plus practical tooling; his newsletter is a regular read.