What happens when blockchain meets AI infrastructure at scale? In today's episode, I sit down with Tory Green from io.net to explore how a decentralized GPU network could reshape the future of machine learning, AI development, and compute accessibility.

io.net has grown rapidly over the past year. With more than 325,000 verified GPUs already in its decentralized network, it's offering an alternative to the high costs and limitations of traditional cloud compute. What caught my attention is the platform's ability to reduce GPU costs by up to 90 percent, giving startups and researchers access to performance that would otherwise be out of reach. In fact, over 73 partners have already integrated io.net's infrastructure, helping drive month-over-month network earnings growth of nearly 60 percent.

But this conversation goes far deeper than computing. Tory walks me through the vision of a more transparent, open, and incentive-driven AI development ecosystem. From its collaboration with OKX to power Web3 infrastructure for AI developers to enabling real-world applications like Zerebro AI agents, io.net is building a new paradigm for how infrastructure should work in the era of intelligent systems.

We also dive into the convergence of blockchain and AI, and why this isn't just a niche Web3 experiment. It's about creating real incentives for data sharing, enabling collaboration across models, and removing bottlenecks in how builders access the tools they need. Tory also shares how the company is evolving from a computing network into a full-stack AI development platform, including tools for no-code agent creation.

So what will the next generation of AI applications look like when they're powered by a global, decentralized network instead of a handful of cloud giants? And how can developers take advantage of this shift today?

3230: Inside io.net's On-Demand GPU Infrastructure

Tech Talks Daily

3230: Inside io.net's On-Demand GPU Infrastructure