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0xPrismatic
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We’ve been tracking the Bittensor metrics that ma
t
ter (h/t @taoapp_)
The data tells a story most people haven’t caught up to yet... 👇
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This is quite cool: SpaceX mirror token. Questions in my mind are: - how much liquidity will there be - what legal claims will token holders have
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Decentralized training in practice: Compute, data, and validation are all done by separate actors, each earning tokens or micropayments. Correctness is often enforced through some form of cryptoeconomics: cheat, and you get slashed. Play fair, and you get paid.
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Open weights ≠ open systems. Most “free” AI models today were trained by large AI research labs with strategic reasons to release them. But what happens when that stops? Tokenized AI may be the way out. 🧵
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Would be very interesting to see where today’s decentralized compute networks land on this AI supercomputer performance chart. h/t @EpochAIResearch
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You can solve coordination. You can solve verification. You can even make it fast. But without incentives, decentralized training doesn’t work. Why would anyone burn compute for free? Let’s talk about why incentive design is the final boss. 🧵
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