Episode notes
Google DeepMind has come up with an interesting idea: using language models as optimizers. They call this approach Optimization by PROmpting, or OPRO for short. Instead of relying on traditional optimization methods, DeepMind's models are trained to generate new solutions by understanding natural language descriptions of the problem at hand and using previous solutions as a basis. This concept has been tested on a range of problems, including linear regression, traveling salesman problems, and prompt optimization tasks. The results are pretty impressive. The prompts optimized by OPRO have outperformed prompts designed by humans by up to 8% on the GSM8K dataset, and up to a whopping 50% on the Big-Bench Hard tasks dataset. So why is this significa ...