io.net (@ionet)
@ionet
The intelligent stack for powering AI workloads | decentralized GPUs | io.intelligence: inference & agents |
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Centralized clouds charge you up to 70% more than you need to pay for GPU compute.
Not because their chips cost more. Because you're also paying for their electricity, cooling headaches, software bundles, and egress fees.
We broke down every option for GPU compute with the actual numbers.
Full guide:
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The future of AI depends on who controls compute.
@ionet CEO @Gaurav_ionet is joining leaders from @nosana_ai, @akashnet_, and @AethirCloud for a live panel on one of the biggest questions in AI infrastructure right now.
They'll tackle centralized vs decentralized compute, and what it means for builders, startups, enterprises, and autonomous agents.
GPU costs are rising, access is tightening, and the stakes couldn't be higher.
Sign up below 👇
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The question every AI builder is asking: centralized or decentralized compute?
We’re bringing together experts from @nosana_ai, @akashnet, @AethirCloud, and @ionet to dig into it live.
📆 June 2, 5PM CET
Register:
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It sounds like the beginning of a joke.
Gandalf and the Pope walk into an AI conference...
Except it isn't a joke.
The concentration of power among AI companies has become such a threat that even the Pope felt he needed to comment on it.
And use a quote from Lord of the Rings to do it.
But the problem isn't AI. It's that too few people control it.
AI needs to move beyond @OpenAI , @AnthropicAI , @Google, and the like to become a force for the many, not the few.
How do we get there? Affordable compute. Instant access. Open-source models.
That's @ionet
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It's only May, and @Uber has already burned through its entire AI budget for the year.
With costs as high as $2,000 per engineer per month, it's easy to understand why.
And they aren't alone.
Less than 1% of executives report 20%+ ROI from AI.
Overpriced infrastructure, soaring token usage, and runaway costs make AI almost unaffordable, even for the largest companies.
But you don't need an enterprise budget to build with AI. You need affordable compute and leading open-source models.
That's exactly what @ionet delivers.
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