Our State of Bittensor 2024 report is live! Alongside the report, we're releasing a recording with the authors of the report, interviewed by our co-founder @dlawee and @brodydotai from Outpost. We discuss: > David's past experience as an executive at Google and as the founder of Alphabet's growth equity fund > The history of Bittensor and what makes it unique > Standout subnets > Dynamic TAO's implications > Our 2025 Thesis

Final Thought: Will This Work? 🤔 DTAO is one of the biggest changes to Bittensor and could revolutionize decentralized AI networks. By using AMMs instead of validator votes, only the best subnets win. 💬 What do you think? Will this make Bittensor more fair and efficient?

The AMM Ensures Fair Market Pricing 🔄 After this sell: • The price drops slightly: 104.27 ─────── = 0.01087 TAO per Alpha 9,090.91 Summary: ✅ Buying Alpha increases its price ✅ Selling Alpha decreases its price ✅ Subnet token price is purely market-driven, NOT set by validators

Someone Sells Alpha Tokens 📉 Now, another user sells 500 Alpha tokens back to the pool to get TAO. 1️⃣ Before the trade: • TAO in pool = 110 • Alpha in pool = 9,090.91 • k = 1,000,000 2️⃣ After the user adds 500 Alpha: • New Alpha in pool = 9,590.91 • Solve for new TAO amount: After this trade, the new price of 1 Alpha token is: 1,000,000 ─────── = 104.27 9,090.91 So: • New TAO in pool = 104.27 • The user gets: 110 - 104.27 = 5.73 TAO

Someone Buys Alpha Tokens 💰 A user buys 10 TAO worth of Alpha tokens from the pool. 1️⃣ Before the trade: • TAO in pool = 100 • Alpha in pool = 10,000 • k = 1,000,000 2️⃣ After the user adds 10 TAO: • New TAO in pool = 110 • Since k must stay constant, solve for new Alpha amount: 1,000,000 ─────── =9,090.91 110 So: • New Alpha in pool = 9,090.91 • The user gets: 10,000 - 9,090.91 = 909.09 Alpha

The Core AMM Formula: Constant Product DTAO uses an AMM model to determine the price of subnet tokens (Alpha) in TAO. The rule is simple: x × y = k where: x = amount of TAO in the subnet pool y = amount of subnet token (Alpha) k = constant product (stays the same after every trade) This ensures the price always adjusts as people buy or sell tokens.

@dlawee @brodydotai Check out the full report here:

For more, check out the full State of Bittensor 2024 report here:

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We got @bloomberg_seth dropping alpha right now for FREE

Sneak peek at a key thesis from our upcoming Bittensor report: The future of AI agents depends on infrastructure that enables self-improvement. The market's missing this Bittensor is already building every component needed—from data collection to training to inference

Looking back on 2024, we’re genuinely impressed by the progress Bittensor has made and the challenges it has overcome. We're super excited to share this report soon.

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