Titans: Neural Long-Term Memory for LLMs, with author Ali Behrouz

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Titans: Neural Long-Term Memory for LLMs, with author Ali Behrouz

12h ago 2:11:25

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In this episode of The Cognitive Revolution, Ali Behrouz, a PhD student at Cornell University, delves into his research on enhancing memory mechanisms in large language models through his latest paper titled Titans. Behrouz discusses the limitations of current models in maintaining long-term coherence and introduces the concept of a neural network as a memory module. Highlighting architectures such as memory as context and memory as gate, he explains how these innovative approaches can significantly improve long-term memory retention in AI systems. The discussion also touches upon challenges such as catastrophic forgetting and the need for more effective models in reinforcement learning and decision-making tasks. This insightful conversation sheds light on the future directions and potential applications of advanced memory mechanisms in AI.

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