io.net

AI infrastructure has been running in the dark. Controlled by a handful of players, the industry has been held back by hidden pricing, secretive deals, and locked doors. We built io.net to change that. Distributed compute. Transparent pricing. Open access. For everyone. Everywhere. For over two years we have been working to bring light to the dark. Today with the launch of our new brand design, we are giving form to the idea. The lights are on. io.net

Centralized clouds are facing a “power wall”, with new data centers taking 3-5 years to build. This has a massive impact on growing AI projects Startups often can't get access to the compute they need, and if they do it's at a price they can't afford it. You see this with centralized clouds like Together AI, where “Instant Clusters” frequently top out at 64 GPUs. Anything beyond that and you get locked behind sales conversions, long-term reserve contracts, and Institutional delays. We built @ionet to be different. We avoid bottlenecks by aggregating existing data centers into a global mesh. This porvides instant access to thousands of GPUs and savings of up to 70% vs centralized clouds. Read the full breakdown: io.net/blog/io-vs-tog…

Utility. That's what the Incentive Dynamic Engine (IDE) is all about. When DePIN moves away from speculation and to real utility, it opens the possibility of building resilient, sustainable networks that are true alternatives to hyperscalers. That's exactly what we're doing. Want a short overview of how the IDE works and why it matters? Check you our quick guide: io.net/blog/the-quick…

Hyperscalers will soon control 2/3 of global data center capacity. This will allow them to further control access and set terms and prices that exclude all but the largest companies. Except when they can't. @ionet is pushing back by offering affordable and accessible compute to everyone, everywhere. No backroom deals. No hidden costs. No gatekeeping. Transparency. Access. And prices that are 70% less. The future of AI isn't for the few, it's for the many. @ionet is turning on the lights. ciodive.com/news/hyperscal…

Haven't gotten a chance to read full the @ionet tokenomics litepaper yet? No problem, here's the lowdown. The IDE: → Replaces fixed, inflationary token emissions with a dynamic, demand driven model → Provides GPU supplier income in USD-targeted payouts to remove token price volatility → Burns at least 50% of remaining emissions supply over time, creating real scarcity tied to real usage → Introduces a dual-vault system that protects suppliers in downturns, absorbing surplus in upturns Find out more: io.net/tokenomics

AI infrastructure was built for the few, not the many. Private deals are negotiated behind closed doors. The biggest players pay less. Everyone else gets in line. And most of us are left in the dark. But there is a better way. AI shouldn't be a private club few people can afford. It should be an open network everyone can access. Bold ideas are born in the light. Limiting ideas are born in darkness. When we build in the open, we make space for creativity, collaboration, and innovation. The lights are on. Read more about it here: io.net/blog/io-net-is…

Some more big news on a big news day! @zai_lab just released GLM 5.1 and we are excited to be one of the earliest providers for this flagship, next-gen model for agentic engineering! Z.ai is an open source power house. io.net is the leader in decentralized compute. Incredible things can happen when you bring them together.

The final io.net tokenomics litepaper is now live! After releasing our initial proposal in December, we spent weeks talking to our community and gathering feedback from builders, suppliers, and token holders. The verdict? Overwhelmingly positive. Creating a sustainable, utility driven network is exactly what the AI industry needs. And the Incentive Dynamic Engine (IDE) is the way to get there. Check out the final version of the litepaper here: io.net/tokenomics The IDE will go live in Q2 2026!

OpenAI expects to spend $121 billion on computing power for AI research in 2028. Yes, that says billion. While most AI developers are struggling to get access to the compute power they need to create sustainable businesses, AI giants will be spending hundreds of billions of dollars. Oh, and that's at an $85 billion operational loss for OpenAI. These numbers are staggering. And they are are proof of why decentralized compute is so important for both growing AI projects and the future of AI. If you don't have billions, there's @ionet wsj.com/tech/ai/openai…

Your AI training job is moving at a snail's pace. And your AWS bill is skyrocketing. It's your infrastructure. Not your model. The right GPU cluster can turns weeks into hours. The wrong setup burns time and money. In our beginner's guide to GPU clusters, we break down what clusters are, how to understand cloud pricing, and when it makes sense to rent vs buy. If you're building an AI project and need accessible, scalable, and affordable compute io.net can help. io.net/blog/what-is-a…

@OpenAINewsroom @gdb @alexkantrowitz @BigTechPod Oh wait, we have an idea. If you want to empower everyone, take your $122 billion investment and give it to AI startups. More projects, more voices, more empowerment. Seems pretty simple.

OpenAI Co-founder and President @gdb sits down with @alexkantrowitz on @BigTechPod to talk AI and how it can empower everyone.

AI infra controlled by a few giant companies isn't just a pricing problem. It's a single point of failure for anyone building in AI. Political, economic, and energy crisis can unexpectedly take down data centralized centers. And when they do: → GPU access dries up → Compute costs spike → Critical systems go dark → Projects stall → Users lose access Decentralized compute isn't just about cost. It's infrastructure resilience. @ionet CEO Gaurav Sharma breaks it down: supplychainbrain.com/blogs/1-think-…

If we really want to expand AI's benefits we need to make it accessible to everyone, everywhere. That won't happen by giving $122 billion to one company and trust they will do the right thing. That money could have funded 5,000+ AI startups, run 250,000 tuition free developer bootcamps, or cover average inference costs for 1 million startups for a year. This just isn't right. AI is meant for the many not the few. That's why we make compute immediately accessible at costs that are 70% less than hyperscalers. Find out more at io.net