[...] much of the point of a model like o1 is not to deploy it, but to generate training data for the next model. Every problem that an o1 solves is now a training data point for an o3 (eg. any o1 session which finally stumbles into the right answer can be refined to drop the dead ends and produce a clean transcript to train a more refined intuition).
— gwern
Recent articles
- My review of Claude's new Code Interpreter, released under a very confusing name - 9th September 2025
- Recreating the Apollo AI adoption rate chart with GPT-5, Python and Pyodide - 9th September 2025
- GPT-5 Thinking in ChatGPT (aka Research Goblin) is shockingly good at search - 6th September 2025