Edge 413: Autonomous Agents and Semantic Memory
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💡 ML Concept of the Day: Semantic Memory in Autonomous AgentsIn the last few issues of this newsletter we have been exploring different memory architectures in autonomous agents. Semantic memory is, arguably, the most common memory structure in LLMs. From a conceptual standpoint, semantic memory in autonomous agents draws inspiration from cognitive psychology and is centered around the argument that facts have meaning. For instance, listening to a specific music tune might bring back memories of places and people related to it. As it name indicates, the core idea of semantic memory structures is to capture knowledge of the agent’s knowledge about the world and itself. This knowledge can be used to further enrich LLM interactions combining it with in-context information... Subscribe to TheSequence to unlock the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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Parallelism, computation, memory, hardware acceleration and control flow are some of the capabilities addressed by the new compilers. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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Capturing memories of important events in the lifecycle of an agent. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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