All modelsOpenAI O1 Preview
The o1 series of large language models are designed to perform advanced reasoning through reinforcement learning. These models engage in deep internal thought processes before delivering responses, enabling them to handle complex queries. o1 preview is designed to reason about hard problems using broad general knowledge about the world.
Performance
Human raters compared o1-preview to GPT-4o on challenging, open-ended prompts across various domains to assess performance and accuracy in different types of tasks. As seen from the graph above, o-1 preview is optimized for STEM related tasks.
Limitations
Optimization for STEM Knowledge: o1-preview is not optimized for tasks requiring non-STEM factual knowledge, which may result in less accurate responses when handling queries outside of technical or scientific domains.
Domain Preference: o1-preview is preferred to GPT-4o in reasoning-heavy domains, but is not preferred to GPT-4o in language-focused domains, where linguistic nuance and fluency are more critical.
Context: May struggle with maintaining context over extended conversations, leading to inconsistencies in long interactions.
Bias: As it is trained on a large corpus of internet text, it may inadvertently reflect and perpetuate biases present in the training data.
Creativity Boundaries: While capable of creative outputs, it may not always meet specific creative standards or expectations for novel and nuanced content.
Ethical Concerns: Can be used to generate misleading information, offensive content, or be exploited for harmful purposes if not properly moderated.
Comprehension: Might not fully understand or accurately interpret highly technical or domain-specific content, especially if it involves recent developments post-training data cutoff.
Dependence on Prompt Quality: The quality and relevance of the output are highly dependent on the clarity and specificity of the input prompts provided by the user.
Citation
https://openai.com/index/introducing-openai-o1-preview/