数链科技
06/21 19:50
AGI is a category that almost nothing currently being built actually addresses, and working through the task around @OpenGradient, #OpenGradient, and $OG, the gap between "race for decentralized AGI" and what the protocol does was the widest one I've encountered exploring this project. OpenGradient verifies inference from existing models — narrow, task-specific systems that are nowhere near general intelligence by any technical definition. There's no architectural path visible in the documentation from "verify that this model's inference ran correctly" to "contribute meaningfully to AGI development," because those are different categories of problem entirely. Verification infrastructure doesn't make models more general, more capable, or closer to AGI; it makes claims about specific narrow model outputs checkable. The design choice that stood out is that the actual roadmap and technical materials don't really gesture toward AGI either — the AGI framing seems to live almost entirely in title and positioning language, disconnected from the engineering substance underneath. That's a fairly common pattern in crypto AI projects, where the most ambitious-sounding word gets attached to infrastructure work that's real but oriented toward a much more modest and immediate problem. Whether that disconnect matters — whether anyone evaluating the project takes the AGI framing literally, or reads past it to the narrower thing actually being built — is the part that stayed with me.
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