The Bittensor Bull Thesis with James Ross and Mog

For today's episode, we dive deep into the the intersection of AI and crypto, and discuss how this sector has produced more hype than results (so far).

While both fields promise decentralization, combining them effectively has proven challenging. Most projects either centralize AI decision-making or create token systems without clear utility.

Bittensor is taking a different approach to this problem by creating a network where AI models compete for rewards through market incentives. This system lets token holders decide which models receive rewards based on measurable performance, rather than promises or marketing.

Their recent update shifted voting power from validators to token holders, aiming to align incentives more directly with utility. One project testing this approach is Mode, with their new subnet Synth, an AI model competing to predict market volatility.

The Synth subnet is live, with data scientists building rival prediction models. Models face off in open competition with market-driven feedback, creating natural selection—strong performers earn more rewards, while weaker ones get filtered out.

Let’s dive into what this means, how Synth is applying it, and what’s next for onchain AI.

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𝗗𝗜𝗦𝗖𝗟𝗔𝗜𝗠𝗘𝗥: 𝘐𝘯𝘷𝘦𝘴𝘵𝘪𝘯𝘨 𝘪𝘯 𝘤𝘳𝘺𝘱𝘵𝘰𝘤𝘶𝘳𝘳𝘦𝘯𝘤𝘺 𝘢𝘯𝘥 𝘋𝘦𝘍𝘪 𝘱𝘭𝘢𝘵𝘧𝘰𝘳𝘮𝘴 𝘤𝘰𝘮𝘦𝘴 𝘸𝘪𝘵𝘩 𝘪𝘯𝘩𝘦𝘳𝘦𝘯𝘵 𝘳𝘪𝘴𝘬𝘴 𝘪𝘯𝘤𝘭𝘶𝘥𝘪𝘯𝘨 𝘵𝘦𝘤𝘩𝘯𝘪𝘤𝘢𝘭 𝘳𝘪𝘴𝘬, 𝘩𝘶𝘮𝘢𝘯 𝘦𝘳𝘳𝘰𝘳, 𝘱𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘧𝘢𝘪𝘭𝘶𝘳𝘦 𝘢𝘯𝘥 𝘮𝘰𝘳𝘦. 𝘈𝘵 𝘤𝘦𝘳𝘵𝘢𝘪𝘯 𝘱𝘰𝘪𝘯𝘵𝘴 𝘵𝘩𝘳𝘰𝘶𝘨𝘩𝘰𝘶𝘵 𝘵𝘩𝘪𝘴 𝘤𝘩𝘢𝘯𝘯𝘦𝘭, 𝘸𝘦 𝘮𝘢𝘺 𝘦𝘢𝘳𝘯 𝘢 𝘤𝘰𝘮𝘮𝘪𝘴𝘴𝘪𝘰𝘯 𝘰𝘳 𝘧𝘦𝘦 𝘢𝘴 𝘢 𝘴𝘱𝘰𝘯𝘴𝘰𝘳𝘴𝘩𝘪𝘱, 𝘪𝘧 𝘵𝘩𝘪𝘴 𝘪𝘴 𝘵𝘩𝘦 𝘤𝘢𝘴𝘦 𝘸𝘦 𝘸𝘪𝘭𝘭 𝘢𝘭𝘸𝘢𝘺𝘴 𝘮𝘢𝘬𝘦 𝘴𝘶𝘳𝘦 𝘪𝘵 𝘪𝘴 𝘤𝘭𝘦𝘢𝘳. 𝘞𝘦 𝘢𝘳𝘦 𝘴𝘵𝘳𝘪𝘤𝘵𝘭𝘺 𝘢𝘯 𝘦𝘥𝘶𝘤𝘢𝘵𝘪𝘰𝘯𝘢𝘭 𝘤𝘰𝘯𝘵𝘦𝘯𝘵 𝘱𝘭𝘢𝘵𝘧𝘰𝘳𝘮, 𝘯𝘰𝘵𝘩𝘪𝘯𝘨 𝘸𝘦 𝘰𝘧𝘧𝘦𝘳 𝘪𝘴 𝘧𝘪𝘯𝘢𝘯𝘤𝘪𝘢𝘭 𝘢𝘥𝘷𝘪𝘤𝘦. 𝘞𝘦 𝘢𝘳𝘦 𝘯𝘰𝘵 𝘱𝘳𝘰𝘧𝘦𝘴𝘴𝘪𝘰𝘯𝘢𝘭𝘴 𝘰𝘳 𝘭𝘪𝘤𝘦𝘯𝘴𝘦𝘥 𝘢𝘥𝘷𝘪𝘴𝘰𝘳𝘴.