OpenAI ：2024年OpenAI o1大模型技术报告（英文版）（42页）.pdf

1、OpenAI o1 System CardOpenAISept 12,20241IntroductionThe o1 model series is trained with large-scale reinforcement learning to reason using chain ofthought.These advanced reasoning capabilities provide new avenues for improving the safety androbustness of our models.In particular,our models can reaso

2、n about our safety policies in contextwhen responding to potentially unsafe prompts.This leads to state-of-the-art performance oncertain benchmarks for risks such as generating illicit advice,choosing stereotyped responses,and succumbing to known jailbreaks.Training models to incorporate a chain of

3、thought beforeanswering has the potential to unlock substantial benefits,while also increasing potential risks thatstem from heightened intelligence.Our results underscore the need for building robust alignmentmethods,extensively stress-testing their efficacy,and maintaining meticulous risk manageme

4、ntprotocols.This report outlines the safety work carried out for the OpenAI o1-preview and OpenAIo1-mini models,including safety evaluations,external red teaming,and Preparedness Frameworkevaluations.2Model data and trainingThe o1 large language model family is trained with reinforcement learning to

5、 perform complexreasoning.o1 thinks before it answersit can produce a long chain of thought before respondingto the user.OpenAI o1-preview is the early version of this model,while OpenAI o1-mini isa faster version of this model that is particularly effective at coding.Through training,themodels lear

6、n to refine their thinking process,try different strategies,and recognize their mistakes.Reasoning allows o1 models to follow specific guidelines and model policies weve set,ensuringthey act in line with our safety expectations.This means they are better at providing helpfulanswers and resisting att