Intelligence in the Open

A MiniMax Research Night during SF Tech Week Intelligence in the Open is a recurring MiniMax research series bringing together AI researchers, engineers, technical founders, and investors for candid conversations about the work shaping the next generation of intelligent systems. For our SF Tech Week edition, we’re exploring one of the most consequential questions in AI: What happens when AI systems begin contributing to their own improvement? This edition will focus on recursive self-improvement (RSI) and the research paths leading toward it — from autonomous research and post-training to self-improving agents, synthetic data, verifiers, evaluation, and systems capable of running increasingly complete experimentation loops. We’ll bring together researchers working across areas including: Recursive self-improvement Autoresearch and autonomous experimentation AI-driven post-training Synthetic data and self-play Reinforcement learning Verifiers and automated evaluation Self-improving agents and coding systems Long-horizon agentic research One area we’ll explore comes directly from recent MiniMax research. In PostTrainBench, MiniMax M3 was given four pretrained base models and tasked with autonomously running the full data synthesis → training → evaluation → iteration process, deciding what data to generate, how to train the models, and how to adjust subsequent experiments based on evaluation results. The broader question goes beyond any single experiment: How close are we to AI systems that can meaningfully improve the systems that built them? Each researcher will present recent work in a focused 10–15 minute talk, followed by an open discussion connecting different approaches to self-improvement and autonomous research. Expect technical conversations, real experiments, open questions, food, and plenty of time to connect directly with researchers and builders working at the frontier. Speakers Speakers will be announced soon. We’re currently inviting…

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