If you are looking for more detailed information on what o1 is and does and how it was trained then look no further
Highlights:
- The o1 model series is trained with large-scale reinforcement learning.
- It uses chain-of-thought reasoning to enhance advanced reasoning capabilities.
- These capabilities open new avenues for improving model safety and robustness.
- Models can reason about safety policies in context when responding to potentially unsafe prompts.
- This results in state-of-the-art performance on benchmarks for:
- Generating illicit advice.
- Choosing stereotyped responses.
- Succumbing to known jailbreaks.
- Training models to reason before answering could offer substantial benefits but also increase risks due to heightened intelligence.
- Results highlight the need for:
- Robust alignment methods.
- Extensive stress-testing of these methods.
- Meticulous risk management protocols.
- The report outlines safety work for the OpenAI o1-preview and o1-mini models.
- It includes safety evaluations, external red teaming, and Preparedness Framework evaluations.