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Bittensor TAO 360 Report: Unlocking Hidden Potential in AI Subnets
Hey there, tech enthusiasts! 🚀
Let’s dive into some game-changing revelations from the Bittensor TAO 360 Report, where for the first time, AI is analyzing AI. Yes, you heard that right — an AI-driven analysis of Bittensor subnets has uncovered fascinating insights that could reshape how we think about value, growth, and potential in decentralized networks. Whether you’re a Bittensor OG or just curious about the decentralized AI space, this one’s for you.
What’s the TAO 360 Report All About?
This report takes a deep dive into 54 subnets, running over 2,350 individual reports using four powerhouse AI models: GPT-4, Claude, Gemini, and Llama 3. It categorizes subnets into three key buckets:
- Appropriately Valued: Subnets receiving rewards that match their contributions.
- Undervalued: Subnets doing more than they’re being rewarded for.
- Overvalued: Subnets receiving more emissions than their efforts justify.
The results? Shocking, to say the least. Let’s break it down by model: