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A proposal to pair recurrent memory with dense attention in language models for AI agents
A post sharing @a1zhang’s blog describes an alternative to fitting an AI agent’s harness around a decoder-only Transformer: change the model’s input and output shape to fit the agent.
TLDR
A post sharing @a1zhang’s blog says the proposal would use recurrent memory for older history while dense attention handles recent context. The blog suggests this could reduce the need for manual compaction in AI agents.
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