Salvato in:
Dettagli Bibliografici
Autori principali: deVadoss, John, Artzt, Matthias
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:https://arxiv.org/abs/2504.14668
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Sommario:
  • Ensuring that an AI system behaves reliably and as intended, especially in the presence of unexpected faults or adversarial conditions, is a complex challenge. Inspired by the field of Byzantine Fault Tolerance (BFT) from distributed computing, we explore a fault tolerance architecture for AI safety. By drawing an analogy between unreliable, corrupt, misbehaving or malicious AI artifacts and Byzantine nodes in a distributed system, we propose an architecture that leverages consensus mechanisms to enhance AI safety and reliability.