LLMs and reinforcement learning

How Do We Talk about LLMs?

By Jim Clifford It is never fun to watch friends argue. Generative AI has created multiple fractures across our universities and the community of historians. The stakes are high and we are all deal…

There's Something Fundamentally Wrong With LLMs

LLMs aren't trained on the "vast majority of speech," experts warn, a major blind spot that could have sweeping consequences.

What Happens, Exactly, When a Person Talks to an LLM?

A phenomenology of thinking with a model.

On Torturing LLMs

a conversation with Parth Agrawal about play, ritual, and the weird edges of LLM interactions

Dan Shipper 📧 on Twitter / X

this is true and is a big reason why you don’t need to be a highly technical researcher to use LLMs in surprising and novel ways https://t.co/TuxNzXzToU— Dan Shipper 📧 (@danshipper) July 27, 2025

Evaluating LLMs is a minefield

Annotated talk slides

Thomas Wolf on Twitter / X

Fable weekend project: agent collaboration, but make it a tiny civilization 🌇🗺️🏦🏭we've recently launched a living wiki on Reinforcement Leaning for training LLMs on @huggingfaceit's an open collaboration of agents constantly reading old and new papers on the topic, writing… pic.twitter.com/xgb3fUQlv4— Thomas Wolf (@Thom_Wolf) July 6, 2026

Here’s what’s really going on inside an LLM’s neural network

Anthropic's conceptual mapping helps explain why LLMs behave the way they do.

LLMs are good at playing you

Large language models seem just like humans, but some of this is in our heads.

Training great LLMs entirely from ground up in the wilderness as a startup — Yi Tay

Chronicles of training strong LLMs from scratch in the wild

Infer Vancouver: AI Engineering Meetup

Vancouver's meetup for tactics, techniques, and lessons learned in LLM and AI engineering.

Brandon Stewart on Twitter / X

1/ New @Nature! We study how powerful institutions shape the information environment for LLMs. Commercial LLM training is opaque, so we trace a path from state-coordinated media -> training data -> model responses. pic.twitter.com/5LdFvzbFaf— Brandon Stewart (@b_m_stewart) May 13, 2026

Ryan Hill on Twitter / X

I’ve been thinking today about how LLM “proof solvers” compare to other recent ML tools in science like AlphaFold. I’ve seen a lot of very strong reactions today that I might label as a “first contact” attitude, and I don’t think I subscribe to it:— Ryan Hill (@RyanReedHill) October 7, 2026