Optimize Anything Launches Omni Meta-Optimizer Combining LLM Algorithms
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Many LLM-based optimization algorithms have been proposed recently. We find that GEPA, AutoResearch, and Meta-Harness each win on different tasks and no single LLM optimizer wins everywhere. How do we leverage the complementary performance profiles of these optimization algorithms? Today, we release optimize_anything omni: a meta-optimizer that leverages the best of each optimizer. At a matched budget, omni beats every standalone optimizer. (thread)
AI-based research and engineering is one of the main topics we're researching in the STAR Lab at Berkeley, and something I'm seeing used in industry more and more too. This is nice work from my grad students packaging multiple AI-based "autoresearch" algorithms into one API in the GEPA package so you can mix-and-match them to get the best results. These can be used for anything from writing prompts to designing agents to optimizing code.
Many LLM-based optimization algorithms have been proposed recently. We find that GEPA, AutoResearch, and Meta-Harness each win on different tasks and no single LLM optimizer wins everywhere. How do we leverage the complementary performance profiles of these optimization algorithms? Today, we release optimize_anything omni: a meta-optimizer that leverages the best of each optimizer. At a matched budget, omni beats every standalone optimizer. (thread)