Comment by ttul

Pasting from my Perplexity page on the topic:

The core innovation [1] of o1 lies in its ability to generate and refine internal chains of thought before producing a final output [2]. Unlike traditional LLMs that primarily focus on next-token prediction, o1 learns to:

1. Recognize and correct mistakes 2. Break down complex steps into simpler ones 3. Try alternative approaches when initial strategies fail

This process allows o1 to tackle more complex, multi-step problems, particularly in STEM fields.

OpenAI reports observing new "scaling laws" with o1 [5]:

1. Train-time compute: Performance improves with more extensive reinforcement learning during training. 2. Test-time compute: Accuracy increases when the model is allowed more time to "think" during inference.

This suggests a trade-off between inference speed and accuracy.

Sources [1] Introducing OpenAI o1 https://medium.com/%40sriramramakrishnan.aiexpert/openais-o1... [2] Learning to Reason with LLMs | OpenAI https://openai.com/index/learning-to-reason-with-llms/ [3] OpenAI o1 models - FAQ [ChatGPT Enterprise and Edu] https://help.openai.com/en/articles/9855712-openai-o1-models... [4] OpenAI releases new o1 reasoning model - The Verge https://www.theverge.com/2024/9/12/24242439/openai-o1-model-... [5] 9 things you need to know about OpenAI's powerful new AI model o1 https://fortune.com/2024/09/13/openai-o1-strawberry-model-9-... [6] Notes on OpenAI's new o1 chain-of-thought models https://simonwillison.net/2024/Sep/12/openai-o1/ [7] OpenAI just dropped o1 Model that can 'reason' through complex ... https://www.tomsguide.com/ai/openais-o1-model-takes-ai-to-a-... [8] Models - OpenAI API https://platform.openai.com/docs/models [9] OpenAI Unveils O1 - 10 Key Facts About Its Advanced AI Models https://www.forbes.com/sites/janakirammsv/2024/09/13/openai-...