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Thesis14 Jul 2025Why DeAI matters across the AI stack: seven layers from incentives to computeMaps seven layers where decentralization matters for AI: open innovation incentives, verifiable inference, decentralized training, private MPC compute, GPU networks, user-owned models and onchain agent payments. Also frames VLAs as lacking a LangChain-style framework that Codec is building.Map13 Jul 2025Six post-TGE AI plays to watch: TAO, NEAR, TIG, IO, NIL, CODECDescribes six live AI tokens without Kaito leaderboards: Bittensor subnets as digital commodity markets, NEAR as AI-native L1, TIG for algorithm IP co-ownership, io.net GPU clustering, Nillion blind compute and Codec's VLA framework.Breakdown24 Jun 2025TIG: Optimisable Proof of Work and tokenized algorithmic innovationSummarizes TIG's thesis: replacing PoW mining with Optimisable Proof of Work so researchers submit algorithms, with commercial licensing linking adoption to token value. Frames algorithms as a crypto-native asset class.
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