The End of Consensus Research?

Key points

• Despite decades of active human research, discovering practical low-latency solutions to the problem is still open, as it requires combining protocol knowledge, correctness reasoning, implementation, and experimental evaluation.1
• We report on how AI helped us discover A-greement, a new consensus protocol for geo-replicated state machines that significantly outperforms state-of-the-art solutions.1
• AI-greement is of independent interest: its Lean formalization uncovers several previously unreported vulnerabilities in existing consensus protocols, and it provides guidelines on how domain-specific harnesses can turn general-purpose coding agents into effective tools for (distributed) computing research.1
• Yet we argue that human consensus experts remain essential before, during, and after the search: agents reshape the researcher's role rather than end consensus research.1

Sources (1)

• [1]The End of Consensus Research?
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 21, 05:55 PM

  Consensus is a fundamental problem in distributed computing and at the core of state machine replication (SMR).

  Despite decades of active human research, discovering practical low-latency solutions to the problem is still open, as it requires combining protocol knowledge, correctness reasoning, implementation, and experimental evaluation.

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