Terrible name (with a terrible reason, that this ‘resets the counter’ on AI capability to 1, and ‘o’ as in OpenAI when they previously used o for Omni, very confusing). Impressive new capabilities in many ways. Less impressive in many others, at least relative to its hype.

Clearly this is an important capabilities improvement. However, it is not a 5-level model, and in important senses the ‘raw G’ underlying the system hasn’t improved.

GPT-o1 seems to get its new capabilities by taking (effectively) GPT-4o, and then using extensive Chain of Thought (CoT) and quite a lot of tokens. Thus that unlocks (a lot of) what that can unlock. We did not previously know how to usefully do that. Now we do. It gets much better at formal logic and reasoning, things in the ‘system 2’ bucket. That matters a lot for many tasks, if not as much [...]

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Outline:

(01:26) Introducing GPT-o1

(05:05) Evals

(07:55) Chain of Thought

(08:57) Coding

(11:08) Human Preference Evaluation

(11:37) What Is It?

(20:24) Doing Math Without Terrance Tao

(25:02) Doing Real Math with Terence Tao

(30:04) Positive Examples

(38:51) Skeptical Reactions

(42:32) Report from Janus World

(45:30) Same Old Silly Examples

(53:47) Latency

(55:14) Paths Forward Unrelated to Safety

(59:17) Safety Last

(01:07:06) Deception

(01:10:50) External Red Teaming

(01:11:23) Apollo's Red Teaming Finds Deceptive Alignment

(01:22:17) Preparedness Testing Finds Reward Hacking

(01:26:43) METR's Red Teaming

(01:29:52) What Are the Safety and Policy Implications?

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