[Market Trends] OpenAI's o1 model: How good is it? | Lex Clips
📌 Is OpenAI's o1 the Secret to Smarter AI?
This video discusses OpenAI's o1 model and its role in programming, specifically in relation to "test time compute" systems. These systems allow models to compute more efficiently at inference time rather than solely relying on larger pre-trained models. The speaker highlights that traditional scaling of model size has hit a limit, making test time compute a promising alternative to improve performance without excessively large models. They explore the potential of using test time compute to handle only the most complex queries, while smaller models manage simpler tasks, reducing computational waste. The conversation also touches on the challenges of dynamically deciding when to use smaller models versus more powerful ones like o1, and discusses the idea of "process reward models" for grading decision-making steps within AI. However, there is still much uncertainty about how these techniques work, especially outside of major labs like OpenAI.
