On one hand, Meta spent $14.8 billion to acquire nearly half of Scale AI's equity, and the entire Silicon Valley is exclaiming that the giant is repricing the price of "data annotation" at a sky high price; On the other hand, @ SaharaLabsAI, which is about to undergo TGE, is still trapped under the Web3 AI bias label of "rubbing concepts and unable to prove themselves". What has the market overlooked behind this huge contrast? Firstly, data annotation is a more valuable track than decentralized computing power aggregation. The story of challenging cloud computing giants with idle GPUs is indeed exciting, but computing power is essentially a standardized commodity, with differences mainly in price and availability. Price advantage may seem to find a gap in the monopoly of giants, but accessibility is limited by geographical distribution, network latency, and insufficient user incentives. Once giants reduce prices or increase supply, this advantage will be instantly erased. Data annotation is completely different - it is a differentiated field that requires human intelligence and professional judgment. Every high-quality annotation carries unique professional knowledge, cultural background, cognitive experience, and so on, which cannot be "standardized" and replicated like GPU computing power. A precise cancer imaging diagnosis label requires the professional intuition of a senior oncologist; A seasoned financial market sentiment analysis cannot do without the practical experience of Wall Street traders. This natural scarcity and irreplaceability give "data annotation" a moat depth that computing power can never match. On June 10th, Meta officially announced the acquisition of a 49% stake in data annotation company Scale AI for $14.8 billion, making it the largest single investment in the AI field this year. More noteworthy is that Alexandre Wang, founder and CEO of Scale AI, will also serve as the head of Meta's newly established "Super Intelligence" research laboratory. This 25-year-old Chinese entrepreneur founded Scale AI in 2016 while still a dropout from Stanford University, and now his company is valued at $30 billion. The customer list of Scale AI can be called the "all-star lineup" of the AI industry: OpenAI, Tesla, Microsoft, the Ministry of Defense, and others are its long-term partners. The company specializes in providing high-quality data annotation services for AI model training, with over 300000 professionally trained annotators. You see, while everyone is still arguing about which model has a higher score, the real players have quietly shifted the battlefield to the data source. A 'dark battle' about the future control of AI has begun. The success of Scale AI has exposed an overlooked truth: computing power is no longer scarce, model architecture tends to be homogeneous, and it is the carefully "tuned" data that truly determines the upper limit of AI intelligence. Meta bought not an outsourcing company at a sky high price, but the "oil extraction rights" of the AI era. The story of monopoly always has rebels. Just as cloud computing aggregation platforms attempt to disrupt centralized cloud computing services, Sahara AI is attempting to completely rewrite the value allocation rules for data annotation using blockchain. The fatal flaw of traditional data annotation models is not a technical issue, but rather an incentive design problem. A doctor who spends a few hours annotating medical images may receive tens of dollars in labor fees, while the AI models trained on this data are worth billions of dollars, but the doctor does not receive a penny. This extreme unfairness in value distribution seriously suppresses the willingness to supply high-quality data. With the catalysis of the web3 token incentive mechanism, they are no longer cheap data "migrant workers", but true "shareholders" of the AI LLM network. Obviously, the advantages of web3 in transforming production relations are more suitable for data annotation scenarios than computing power. It is interesting that Sahara AI happened to acquire TGE at Meta's sky high price, is it a coincidence or carefully planned? In my opinion, this actually reflects a turning point in the market: both Web3 AI and Web2 AI have moved from "computing power" to the crossroads of "data quality". While traditional giants are building data barriers with money, Web3 is using tokenomics to construct a larger experiment of 'data democratization'.