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How does OpenAI's o1 exactly work? Part 2. Here is a list of papers & summaries on LLM reasoning that I've recently read. All learning-based. 0) STaR: Self-Taught Reasoner https://t.co/ZVu3ky248Y Ground Zero. Instead of always having to CoT prompt, bake that into the default… https://t.co/jqBvz351ZG
How does OpenAI's o1 exactly work? Here is a list of papers & summaries on LLM reasoning that I've recently read. I'll split them into 2 categories: 1) prompt-based - enforce step by step reasoning & self-correcting flow purely using prompts 2) learning-based - bake in the… https://t.co/0uuTJbdjnq
On The Planning Abilities of OpenAI's o1 Models This work reports that o1-preview is particularly strong in self-evaluation and constraint-following. They also mention that these o1 models demonstrate bottlenecks in decision-making and memory management, which are more… https://t.co/sazTsszL9f
OpenAI's latest AI model, o1, represents a significant advancement in AI reasoning by focusing on optimizing test-time compute rather than merely increasing parameters. This new approach aims to enhance model responses and offers insights into the future of AI performance. The o1 model, particularly the o1-preview, is noted for its strong self-evaluation and constraint-following abilities. However, it also faces bottlenecks in decision-making and memory management. Unlike its predecessors, such as GPT-2, GPT-3, and GPT-4, the o1 model does not rely on increased scale but rather on innovative methods to improve AI reasoning. Additionally, Google's AlphaProof is another significant development in AI reasoning.
