I recently browsed the Chinese-speaking forums and noticed that there weren't many discussions about TAO, but the English-speaking forums were consistently buzzing with discussion. I spent the last couple of days systematically learning about TAO/Bittensor and have compiled a simplified explanation to help everyone quickly understand what it's all about. 1⃣What is TAO/Bittensor? Simply put, TAO aims to turn AI into an open network like Bitcoin. Currently, AI is largely controlled by a few companies, such as OpenAI, Google, and Anthropic. Models, computing power, data, and pricing are almost all controlled by a small number of companies. Bittensor aims to change this. It uses a mechanism called Proof of Intelligence (Proof of Intelligence) to allow anyone to participate in the AI network: You can provide models, computing power, data, and inference capabilities. As long as your AI output is valuable, you can earn TAO rewards. 2⃣How does the TAO network work? The entire Bittensor network is composed of subnets. This can be understood as: one subnet = one AI track For example, text generation, image processing, translation, search, inference computation, model training, and secure computation. Each subnet focuses on a specific direction. Currently, the network has approximately 128 subnets, with a future goal of expanding to 256. However, only about 20%-30% of the subnets are truly mature, the so-called blue-chip subnets. This is actually very similar to the early internet or the early Ethereum ecosystem: Many experimental projects, a few that succeeded Ultimately forming the core infrastructure TAO's total supply is 21 million, the same as Bitcoin, and it also has a halving mechanism. This naturally gives it a "AI Bitcoin" narrative. 3⃣ Why has TAO suddenly started to attract market attention? First: Dynamic TAO (dTAO) upgrade This is the most important upgrade in 2025. After the upgrade, subnets can be directly invested in, forming alpha tokens. TAO holders can allocate funds to different subnets, supporting high-performance subnets to earn more rewards. The result is: good subnets receive more resources, poor subnets are eliminated, network efficiency is significantly improved, and the ecosystem begins to move from narrative to actual products. Second: The first halving will occur in December 2025. Similar to Bitcoin. The daily issuance of TAO will decrease from approximately 7200 to 3600. The supply will be directly reduced. With continuously increasing demand, the halving will naturally become a long-term positive factor. Third: Decentralized large-scale model training is validated. This is a key technological breakthrough. The Templar subnet successfully trained a 72-parameter model on a distributed network. Using ordinary hardware, more than 70 independent nodes, and without a super cluster, a competitive large-scale model was ultimately trained. Fourth: NVIDIA CEO publicly acknowledges. In March 2026, Jensen Huang publicly praised Bittensor's distributed training, considering it a remarkable technological achievement. Fifth: Institutional Entries Grayscale launches Bittensor Trust, Bitwise submits related application TAO ETP products appear in Europe, major exchanges begin listing 4⃣ Which TAO subnets have real applications? 1. SN3: Templar (Templar) – The King of Decentralized Large-Scale Model Training Business Positioning: Distributed LLM pre-training platform, focusing on large-scale model training (using innovative compression algorithms such as SparseLoCo). Core Achievements: Successfully trained Covenant-72B (72B parameters, 1.1 trillion tokens), entirely on distributed ordinary hardware (70+ independent nodes), without the need for a super cluster. Ecosystem Significance: Proves that "decentralized training" is no longer just theory, breaking the centralized monopoly of OpenAI. Subnet revenue is used to repurchase Alpha, forming a positive feedback loop; it is the flagship representative of TAO's "intelligent production layer," driving the entire network towards "collective intelligence." 2. SN64: Chutes – The King of Serverless AI Inference Adoption (Highest Actual Usage) Business Positioning: Serverless GPU computing platform; developers can upload models/containers to deploy AI services (text generation, image/video generation, etc.) with one click. Core Achievements: Processed a cumulative total of 9.1 billion tokens, serving 400,000+ users (including 100,000+ API users), with a peak daily request volume exceeding 50 million. Pricing is 85% lower than AWS and 10-50% lower than Together AI, making it a top inference provider for OpenRouter. Performance of some models surpasses that of some centralized competitors. Ecosystem Significance: The subnet closest to "Real Product-Market Fit" (PMF), proving that decentralized AI can generate cash flow and massive adoption. Revenue automatically repurchases Alpha+ rewards for miners, forming a closed-loop economy; it is the underlying computing infrastructure for the Agent Economy. 3. SN4: Targon – A Representative of Enterprise-Level Confidential Secure Computing Business Positioning: A decentralized confidential GPU computing platform focusing on privacy-preserving AI inference and training. Core Achievements: Partners with Intel to provide enterprise-grade secure computing, serving over 4 million users. Supports platforms like Dippy, completing millions of real-world AI calls. Completed a $10.5 million Series A funding round in 2025. Ecosystem Significance: Solves AI privacy and compliance pain points (difficult to address with traditional cloud services), attracting institutions and enterprises. Complementing computing layers like Render/Akash, it's a key step in TAO's transformation towards "production-grade AI." Wait... When the market is down, instead of frequent trading and chasing trends, it's better to calmly research the next alpha. Real opportunities often appear before most people even start discussing them. There aren't many people researching TAO in the Chinese-speaking world yet; this is just a personal study note. Welcome to add your opinions and share different perspectives!