. @inference_labs is making a clear claim: distributed proving unlocks zkML at scale

AI scaled once inference moved from single machines to distributed clusters. Inference Labs applies the same logic to verifiable AI

The bottleneck in zkML comes from proving entire models at once

Their solution, DSperse, slices models into independent components and distributes proving across many nodes. More nodes lead to faster proofs, stable memory usage, and resilient execution

Combined with JSTprove, this architecture supports near–real-time verification and production-grade performance.

The impact is structural:
+ zkML becomes a scalable infrastructure
+ Proof generation turns fault-tolerant
+ Autonomous systems gain auditability and resilience

With hardware acceleration partners like Cysic, distributed proving pushes verifiable AI from research into real-world deployment.

This is a paradigm shift for zkML math-powered trust, delivered by networks