Matei Zaharia says combining GEPA with RL yields improved learning from feedback

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13.05.2026

Matei Zaharia says combining GEPA with RL yields improved learning from feedback — GEPA and RL integration advances learning

A novel approach merging Generalized Empirical Policy Approximation (GEPA) with Reinforcement Learning (RL) is being explored to enhance the quality of machine learning models. According to Matei Zaharia, the integration aims to harness beneficial aspects from both methods, allowing algorithms to reflect on complex feedback and update their parameters more effectively. The research underscores the ongoing innovation in reinforcement learning, which remains a core area of artificial intelligence development.

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Zaharia previously announced that GPT 5.5 and Codex are available on Databricks, enabling enterprise management via the Unity AI Gateway, according to a recent update. He also reported that Genie has delivered a threefold increase in data agent accuracy for Databricks workflows, as noted in a separate release. The ongoing work highlights continued advances in machine learning infrastructure and tools.

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