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Center for Advanced AI, Accenture
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On-policy reinforcement learning with diffusion policies just got a whole lot easier thanks to a clever method that sidesteps expensive log-likelihood computations.
LLMs can now remember the past without forgetting the details: an indexed memory system lets agents selectively retrieve full-fidelity interactions from an external database, outperforming lossy summarization methods on long-horizon tasks.