The explosion of generative AI has driven global demand for GPU compute to unprecedented levels. At DePIN Day Denver 2024, Angela Yi from io.net presented how the project is tackling this challenge by aggregating underused GPU resources into a global, permissionless, decentralized cloud. With 25,000+ GPUs already on its network, io.net aims to become the go-to infrastructure for scalable, cost-effective AI computing. Here’s how they’re making it happen.
Why GPUs Are the New Oil
AI models are consuming compute at exponential rates. While AI compute demand increases 10x every 18 months, traditional cloud supply merely doubles. Startups and enterprises alike report spending up to 80% of their operational expenses on GPU compute. io.net addresses this bottleneck by aggregating unused GPU capacity from:
- Consumer devices (including Apple M-series chips)
- Crypto mining farms
- Independent data centers
Introducing io.net: The Decentralized GPU Network
io.net offers a permissionless GPU cloud where users can deploy compute clusters in 40 seconds. The core products include:
- io Cloud: For engineers to deploy AI workloads at scale
- io Worker: For contributors to earn from idle hardware
- io Explorer: For real-time visibility into clusters, devices, and inferences
Unlike traditional cloud providers, io.net offers:
- Up to 90% cheaper compute
- Support for clustered AI models (not just single GPU access)
- No KYC or waiting period to deploy clusters
The Power of GPU Clustering at Scale
io.net’s infrastructure goes beyond simple GPU rental. Its platform supports orchestration of distributed GPUs into powerful virtual clusters. Engineers can:
- Select from global GPU types, including RTX, A100, H100, and M-series
- Customize based on latency, speed, compliance, and location
- Deploy up to 20,000 GPUs in seconds
This makes io.net viable for anything from small experiments to full-scale enterprise AI operations.
Earning Through io Worker
Hardware owners can connect their GPUs, track performance, and earn significantly more than through traditional mining. Key features:
- Reputation system based on uptime and speed
- Real-time monitoring and payout tracking
- Up to 15x better returns than average GPU mining
Even individuals with laptops or MacBooks can contribute and earn.
End-to-End Infrastructure: From Training to Inference
io.net supports full lifecycle ML operations:
- Cluster deployment (Kubernetes, Ray, etc.)
- Secure and encrypted environments (SOC 2 options)
- Integrated dev tools (Jupyter, VSCode)
- Explorer for tracking real-time job history and earnings
They’ve also built a showcase app, BCH AI, a generative image tool powered entirely by the network.
The Bigger Vision: Permissionless AI Infrastructure
Angela highlighted io.net‘s future plans:
- Support for Apple silicon opens compute access to millions more users
- All cluster activity and inference prompts can be recorded on-chain
- A model marketplace is launching to let open-source AI builders monetize usage
With traction across 40 countries and growing demand, io.net is positioning itself as the core layer for decentralized AI compute.
Decentralizing the Future of AI Compute
By tapping into global GPU oversupply and enabling permissionless, clustered compute, io.net is creating a new backbone for AI infrastructure. Faster, cheaper, and decentralized, it offers a real alternative to cloud monopolies while rewarding contributors around the world. With its rapid growth and robust architecture, io.net may soon become the internet of GPUs.
