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AI-Enabled Blockchain

I wanted to understand what changes when blockchain transactions carry executable ML work instead of only values. I built a Go master-peer network where peers run Python models, validate their outputs, compete on proof of work, and broadcast the winning block.

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What stayed with me

The useful lesson was not that AI makes a blockchain better. It was seeing where computation, validation, consensus, and cancellation meet when several peers can finish the same work at different times.

Core behavior

  1. 01Master-peer network that exchanges transactions and blocks over TCP
  2. 02ML-backed transactions whose Python outputs are recomputed and validated before mining
  3. 03Concurrent, cancellable miners that stop when a valid peer block arrives
GoTCPProof of WorkPythonDocker