What truly stands out is not simply mixing AI and zero-knowledge proofs, but how to make zkML truly land from the experimental stage into usable infrastructure.

The key lies in the distributed proof generation scheme. Distributing the computational load across multiple nodes addresses the fundamental scalability and speed bottlenecks, rather than just stacking hardware performance. In other words, this is an architectural breakthrough rather than a mere hardware optimization.

Coupled with a distributed proof framework, the entire system's throughput and response time are elevated to a new level. This is the critical step for zkML to move from theory to practical application — it's not about how clever the algorithm is, but whether it can handle real-world traffic and latency requirements.