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The intelligent stack for powering AI workloads | io.cloud: decentralized GPUs | io.intelligence: inference & agents | t.me/io_net

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io.net
@ionet
Jun 11
The future of AI compute doesn't run on hype. It runs on real utility, real burns, and a network that gets stronger every time it's used. The Incentive Dynamic Engine (IDE) is now live! io.net/blog/a-new-tok…
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io.net
@ionet
2h
The cheapest GPU isn't always the cheapest GPU. The GPU market has fragmented across hyperscalers, neoclouds, and decentralized networks. A cheap hourly rate can quickly become expensive when you factor in SLAs, security requirements, data residency, and the cost of getting
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io.net
@ionet
23h
Daily token usage in China went from 100B to 140T in 14 months. Beijing's response: - 100,000 GPUs - $532B in infrastructure investment - 9,800 EFLOPS by 2030 The AI race is a compute race. Access to GPUs will define who competes. Governments and hyperscalers are solving this
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io.net
@ionet
Sep 9
Compute got decentralized first. Trust is next. The infrastructure layer has been moving fast. The verification layer hasn't caught up yet. Catch @Gaurav_ionet, io.net CEO, on closing that gap. Thursday, 1PM UTC.
Humanity
@Humanityprot
Sep 8
X SPACE: Compute is decentralizing. Credentials aren't, yet. We're sitting down with @shubhamb126 and @Gaurav_ionet of @ionet on trusting infrastructure and agents you can't see, Thursday 10 September, 1PM UTC. Set your reminders 👇
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io.net
@ionet
Sep 8
38GW. That's the US data center power shortfall through 2028. The hyperscaler solution is to build more data centers, substations, and power generation. Then wait 4-7 years for it. Meanwhile, millions of GPUs are already powered, cooled, connected, and underutilized. AI
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