reply ☄️Arm's data-center royalty revenue has doubled year-over-year, with cumulative AGI CPU demand surpassing $2 billion. Arm Neoverse shipments have topped 1.5 billion cores, with the last 500 million shipped in just 9 months.
🌟DA's take: Let's be clear, AI data centers are migrating from x86 to Arm. That's not a trend, it's a fact. Nvidia Vera, Google Axion, AWS Graviton, Microsoft Cobalt, they're all betting on Arm now. Once an architecture-level migration like this gets going, the momentum is huge, and Arm is quietly eating the foundation layer of AI compute.
Think it through, and it follows that if DeAgentAI's distributed inference network is going to scale up, chip architecture choice matters enormously too. Arm's low-power, high-density profile is a natural fit for the large-scale, distributed footprint that decentralized AI nodes need.
What do you think: will Arm replace x86 as the dominant architecture of the AI era?
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reply 🐳OpenAI's Astra model cracked 10 previously unsolved math problems, including disproving the Erdős unit distance conjecture and the Connes rigidity conjecture, with every proof backed by machine-verifiable Lean formalization, at a compute cost of roughly $2,000.
🌟DA's take: This time it's different.OpenAI isn't asking mathematicians to "trust me", it's handing over machine-verifiable proofs. Solving a century-old problem for $2,000 is orders of magnitude cheaper than hiring a PhD student.
Math might be the first discipline AI fully rewrites. And guess what, DeAgentAI's distributed inference network is doing something similar: handing complex on-chain decision-making over to AI, then outputting the results in verifiable form.
What do you think: once AI can prove theorems 10,000x faster than humans, what does the mathematician's role become?