Building a Transformer Out of Claudes — Collaboration Request
The author proposes a multi-agent framework called ClaudeFormer to do frontier math research, where a team of Claudes (AI agents) work together in a transformer-like architecture.
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Why it matters
This novel architecture could enable more efficient and scalable AI-powered research by leveraging a multi-agent collaborative approach.
Key Points
- 1ClaudeFormer maps the transformer architecture, with Claudes as the workers, an attention mechanism as the router, and a verification process
- 2The goal is to emulate a single Claude with a larger context window by having multiple Claudes with smaller context windows collaborate
- 3The architecture scales in three ways: context window (number of Claudes), depth (number of dispatch cycles), and attention heads
Details
The author's core idea is to build a transformer architecture out of Claudes (AI agents). In this setup, a single Claude acts as the
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