The Significance of OpenAI O1 and the Scaling Law in Reinforcement Learning

OpenAI o1 is a major leap in logical reasoning for large models, surpassing GPT-4o by improving complex problem-solving and scaling abilities.

OpenAI o1: A Major Leap in Large Models

I believe OpenAI's o1 is the biggest advancement in large models since GPT-4. Its improvements in logical reasoning surpassed expectations. While GPT-4o and o1 are different development paths, o1 is more fundamental and far more important. Here's why.

Why is o1 More Important than GPT-4o?

These are two distinct directions for large model development. Honestly, when GPT-4o was released, I was a bit disappointed. I expected OpenAI to prioritize the o1 approach, but GPT-4o came first.

GPT-4o focuses on integrating different modalities, but this doesn't significantly boost the intelligence of large models. o1, on the other hand, explores how far large models can go toward AGI and what their limitations are. Clearly, the second issue is more critical.

The problem with GPT-4o is that the model's intelligence isn't advanced enough to handle complex tasks. Simply relying on new modalities like images and videos won’t dramatically improve its intelligence. These data types enhance the model's perception of the multimodal world but don't increase its cognitive abilities.

Improving cognitive abilities mainly relies on LLM text models, and enhancing an LLM's reasoning ability is key to increasing its cognitive skills.

The stronger an LLM's reasoning skills, the more complex applications it can unlock. The ceiling for large model applications rises accordingly. So, improving the model's logical reasoning should be the top priority.

If o1 continues to improve, it can enhance multimodal models like GPT-4o by either replacing GPT-4o's base model, generating synthetic data for reasoning, or distilling knowledge. This would enable GPT-4o to solve more complex tasks and unlock advanced multimodal scenarios.

OpenAI’s future strategy seems to involve two lines: o1 and GPT-4o. The logic is likely that o1 enhances the base model's reasoning, and this ability can be transferred to the multimodal GPT-4o.