Episode 109 — io.net — The Decentralised GPU Network

EPISODE 109 — io.net — The Decentralised GPU Network

The GPU shortage of 2023 exposed a fundamental problem in the AI industry: the infrastructure for training and running artificial intelligence models is controlled by a tiny number of companies — Amazon, Google, and Microsoft — and when demand exceeds their capacity, there is no meaningful alternative. NVIDIA H100 processors had waiting lists measured in months. AI teams were paying $4-5 per chip-hour when they could access capacity at all. Meanwhile, millions of high-performance GPUs sat idle in gaming computers, retired mining rigs, and underutilised data centres. io.net built the marketplace that connects idle GPUs to AI teams that need them — using blockchain economics to coordinate what no centralised company could organise from scratch.

In this episode of Crypto for Beginners, we explain io.net and the decentralised compute model in full. We cover DePIN — Decentralised Physical Infrastructure Networks — and why using token incentives to coordinate distributed hardware can create cost advantages that centralised ownership cannot match, particularly when the hardware already exists and sits idle. We explain how io.net aggregates GPU supply: how individual providers register hardware, how the protocol matches jobs to available machines, and how the Ray-based distributed computing framework enables complex AI workloads to run across hundreds of machines in multiple locations simultaneously.

We explain IO Cloud — the interface for AI developers to request GPU clusters — and IO Intelligence, which adds pre-trained model access and AI agent frameworks on top of raw compute. We cover the IO token: its supply structure, the IDE dynamic emission model that ties token issuance to actual compute demand, and what realistic provider earnings look like in 2026. We cover the competitive landscape — io.net versus Render, Akash, and Aethir — and we are honest about the challenges: enterprise trust certification, competition from hyperscale cloud providers, and the volatility of provider incentives when token prices fluctuate.

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