HN user
Nice presentation of the list!
I'd recommend watching a few of his talks/podcasts before during reading these to get the overview and how all the bits in these works tie together.
https://www.dwarkesh.com/p/ilya-sutskever
https://simons.berkeley.edu/talks/ilya-sutskever-openai-2023...
The author discussed this here four days ago
With the benefit of hindsight, perhaps much of this was Claude Mythos? The model was deployed internally since Feb
Agreed. LLMs have helped me achieve much deeper reading, _when directed to do so_. Asking an LLM to “Teach me Socratically about this paper/code. One question at a time”, usually allows me to get a much deeper reading of the material than I would otherwise.
Each of these models has a thinking/reasoning variant and a default non-thinking variant. I would expect the reasoning variants (o3 or “GPT5 Thinking”, Gemini DeepThink, Claude with Extended Thinking, etc) to do better at this. I think there is also some chance that in their reasoning traces they may display something you might see as closer to world modelling. In particular, you might find them explicitly tracking positions of pieces and checking validity.
As far as I can tell they don’t say which LLM they used which is kind of a shame as there is a huge range of capabilities even in newly released LLMs (e.g. reasoning vs not).
They fix the temperature at T=0.6 for all k for all models, even though their own Figure 10 shows that RL model benefits from higher temperatures. I would buy the overall claim much more if they swept of temperature parameter for each k and model like they did in the Codex paper [1].