Let's be real — the demand for compute is exploding.

AI adoption is growing faster than infrastructure can handle, and centralized systems are already showing cracks.

We're talking 10B+ petaFLOPs in training cost for some models — and it's only going up.

The real issue? Not just hardware scarcity. It's inefficiency — idle GPUs, high overhead, and poor allocation. That's the bottleneck no one likes to talk about.

That's why I think @ionet is onto something big.

Instead of trying to compete with giants like AWS or GCP head-on, they’re doing what Web3 does best: coordinating unused resources at scale. By pooling GPUs globally — then smartly orchestrating them with tools like Ray, K8s, and custom clustering — they're unlocking compute that was previously off the grid.

And here's where it gets even more interesting:

By rewarding supply with $IO, they're creating a cost-efficient flywheel — where compute buyers get access to cheaper, scalable infra without sacrificing performance. That's huge for anyone running serious AI workloads.

Tbh, this goes beyond decentralization for the sake of ideology. It's about making AI actually scalable, by tapping into what already exists but isn’t being used.

Feels like one of those rare use cases where crypto + AI actually makes sense.

Not hype. Real problem, real solution.