$TAO Lately, performance has been very strong. One interesting phenomenon is that every time the parent token rises, liquidity gradually diffuses into the Alpha subnet markets.
Bittensor now has 100+ subnets, and each one is working on a different part of the AI industry chain. Here are a few representative examples:
1️⃣ SN51 Lithium: a decentralized GPU market, targeting H100/A100 clusters, supporting hourly rental.
2️⃣ SN64 Chutes: serverless AI inference—quickly deploy open-source models and pay based on actual compute resources.
3️⃣ SN4 Colossus: decentralized, confidential computing that solves security issues for AI workloads running on untrusted hardware.
4️⃣ SN44 Score: AI sports analytics and computer vision, with real-time tracking of games, players, and targets.
5️⃣ SN120 Affine: focuses on inference model evaluation—selects better models based on real inference performance.
6️⃣ SN53 EfficientFrontier: AI investment and trading strategies, competing with Vanta in the trading-strategy contest track.
7️⃣ SN3 Templar: decentralized LLM training; it previously trained Covenant 72B, and is now operated by a new team.
8️⃣ SN8 Vanta: AI trading strategies, scoring based on real-time performance rather than just backtesting.
9️⃣ SN9 Iota: distributed LLM training—build an unpermissioned training cluster using existing hardware.
🔟 SN68 NOVA: AI drug discovery, attempting to push AI-selected compounds into robotic synthesis.
I think what’s truly interesting about Bittensor isn’t just $TAO itself, but the subnets behind it that keep evolving.
If, in the future, the Alpha market gradually matures and capital flows from $TAO into various subnets, the imagination space for the whole ecosystem may open up even further.
Bittensor now has 100+ subnets, and each one is working on a different part of the AI industry chain. Here are a few representative examples:
1️⃣ SN51 Lithium: a decentralized GPU market, targeting H100/A100 clusters, supporting hourly rental.
2️⃣ SN64 Chutes: serverless AI inference—quickly deploy open-source models and pay based on actual compute resources.
3️⃣ SN4 Colossus: decentralized, confidential computing that solves security issues for AI workloads running on untrusted hardware.
4️⃣ SN44 Score: AI sports analytics and computer vision, with real-time tracking of games, players, and targets.
5️⃣ SN120 Affine: focuses on inference model evaluation—selects better models based on real inference performance.
6️⃣ SN53 EfficientFrontier: AI investment and trading strategies, competing with Vanta in the trading-strategy contest track.
7️⃣ SN3 Templar: decentralized LLM training; it previously trained Covenant 72B, and is now operated by a new team.
8️⃣ SN8 Vanta: AI trading strategies, scoring based on real-time performance rather than just backtesting.
9️⃣ SN9 Iota: distributed LLM training—build an unpermissioned training cluster using existing hardware.
🔟 SN68 NOVA: AI drug discovery, attempting to push AI-selected compounds into robotic synthesis.
I think what’s truly interesting about Bittensor isn’t just $TAO itself, but the subnets behind it that keep evolving.
If, in the future, the Alpha market gradually matures and capital flows from $TAO into various subnets, the imagination space for the whole ecosystem may open up even further.
