Episode
Titans: Neural Long-Term Memory for LLMs, with author Ali Behrouz
- Published
- May 15, 2025
- Duration seconds
- 7705
- Processing state
processed- Canonical source
- https://www.cognitiverevolution.ai
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Summary
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. SPONSORS: ElevenLabs: ElevenLabs gives your app a natural voice. Pick from 5,000+ voices in 31 languages, or clone your own, and launch lifelike agents for support, scheduling, learning, and games. Full server and client SDKs, dynamic tools, and monitoring keep you in control. Start free at https://elevenlabs.io/cognitive-revolution Oracle Cloud Infrastructure (OCI): Oracle Cloud Infrastructure offers next-generation cloud solutions that cut costs and boost performance. With OCI, you can run AI projects and applications faster and more securely for less. New U.S. customers can save 50% on compute, 70% on storage, and 80% on networking by switching to OCI before May 31, 2024. See if you qualify at https://oracle.com/cognitive The AGNTCY: The AGNTCY is an open-source collective dedicated to building the Internet of Agents, enabling AI agents to communicate and collaborate seamlessly across frameworks. Join a community of engineers foc…