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Sapien is a gamefi, Ai training solution. Raised $5M Join waitlist here..!

AI + Web3: Towers and Squares TL;DR 1. Web3 projects with AI concepts have become targets for capital attraction in both primary and secondary markets. 2. The opportunities of Web3 in the AI industry are mainly reflected in: utilizing distributed incentives to coordinate long-tail potential supplies ( across data, storage, and computing ); while establishing a decentralized market for open-source models and AI Agents. 3. AI is mainly applied in the Web3 industry for on-chain finance (, cryptocurrency payments, trading, data analysis ), and assisting development. 4. The utility of AI+Web3 is reflected in the complementary nature of both: Web3 is expected to counteract AI centralization, and AI is expected to help Web3 break out of its niche. Introduction In the past two years, AI has developed rapidly, and the emergence of ChatGPT has opened a new era of generative artificial intelligence, also sparking a wave in the Web3 field. With the support of AI concepts, the financing of Web3 projects has been significantly boosted.

📌 How can we ensure the quality of "training data" when the speed of AI development far exceeds regulation and ethical construction? @JoinSapien proposed a potentially more binding solution: reconstructing the data contributor ecosystem with a staking + reputation system. This model is not complex, but very "Web3": 1️⃣ Tokens need to be staked before task execution → Take responsibility before contributing 2️⃣ Completed peer review by peers in the community → Decentralized quality verification 3️⃣ Result affects contributor's reputation → Reputation binds task permissions and benefits There are several noteworthy systemic variables behind this mechanism: 🔹Data quality is automatically adjusted through a penalty mechanism rather than relying on a centralized review system. 🔹The incentive structure is strongly linked to "participant credibility", effectively preventing rug pulls/bot flooding. 🔹All contribution processes are traceable on-chain, ensuring that subsequent AI models can verify their training paths. 📊 As of now: 🔹1.8 million+ participants 🔹185 million+ tag tasks 🔹Covering multiple vertical scenarios such as healthcare, education, and autonomous driving In the current situation where both "AI computing power" and "AI models" are excessively competitive, the quality control system for training data has instead become a scarce resource. Sapien does not attempt to replace OpenAI-style large models, but instead chooses to take a different approach—enhancing the credibility of "human knowledge" in the AI system through rules, responsibilities, and incentives. Perhaps this mechanism is the key piece of the next stage. It's not about "what can be done", but rather "how accurately it can be done" and "whether it is correct". Quality is not shouted out as a slogan; it is enforced through rules. @cookiedotfuncn @cookiedotfun #PlaySapien #CookieSnaps #Sapien #SapienSnaps

Notice National migration to Australia! The island nation of Tuvalu may be submerged in 25 years, with its highest point not exceeding 5 meters above sea level. Over 80% of residents have applied for Australian climate visas and it may become the world's first digital nation! Sharp turn 90 degrees At the end of this week, our advisory board welcomed an important member: welcome Zhang Tonghao, the head of data and platform products at ByteDance. 🛠️ 1. The "data foundation" of Byte has got an experienced master. Zhang Tonghao is not someone who handles data by coding or making charts; rather, he is like an old craftsman who understands the grain of every piece of wood. During the heavy rains in Southeast Asia, he led a team using tricycles to mark flood levels for AI training, reducing the delivery delay prediction error to below 3%; The ambiguity of Filipino dialects led him to decide to involve tribal teachers, stopping AI from translating "ulipon" (servant) into a discriminatory term; German hospital CT annotation, he insists that doctors' hourly wage should be doubled: "If the tumor margin is off by one pixel, a life could be lost by ten years." "Other people's data is oil, while he treats it like living water - he has to ask the source before taking a scoop." —— The on-chain resume of Yunnan annotator Sister Li is the "anti-pit" policy she advocates: companies should check data fingerprints before hiring. 🌏 2. The advisory seat adds "Preventing the Giant's Scythe" Zhang Tonghao joining is crucial because it provides ordinary people with three self-defense shovels: Strong Pricing Power: Previously, companies wanted to cut the price by 30% for the bundled million medical images, but now he can bring annotators to vote for a 15% increase - "The nights that Berlin doctors Mark and others worked must be exchanged for their children's tuition." Ethical Red Light Rights: A nurse in the Philippines found that the recruitment AI labeled "nurse" with a female tag, so he directly froze the task and completed 30% of male nurse data in 7 days. Continuous cooking offline: Typhoon weather causing internet outages? The cache annotation package he promotes allows farmers to map and store on their phones, and settle online in seconds—The heavier the rain, the higher the price. "Used to be data laborers, now data shareholders - he knows how much our calluses are worth." ——The tricycle driver in Cagayan relied on the heavy rain surcharge he set to support his daughter in completing nursing school. 🤝 Three, why him? Because he is willing to squat in the mud and listen to the breathing. Other consultants love to talk about algorithm iterations, but he leads his team to delve into the wrinkles of the human experience: Singapore warehouse: After two weeks of hard work alongside the e-commerce operations team, we pushed the LG vacuum cleaner to the top three in sales on Shopee. Dai bamboo house: Discovered that AI misclassified elderly people's coughs as "cursing," immediately added dialect protection vocabulary, and rewarded an extra 0.5 yuan for each recording; Field Hospital: During the power outage in Ukraine, he changed the SMS marking system, allowing doctors to exchange one emergency CT for a bag of plasma. In the chess game of bytes, he exclusively takes the path on the side of the "ren" character: Data is not floating in the cloud; it is earned through people risking their lives, enduring sleepless nights, and betting their dignity. 🚀 Conclusion: The advisory role is not just a title, it's about taking responsibility. When the coral bleaching data marked by Palawan fishermen obstructs the reclamation project of the resort; When the Iloilo teacher teaches the dialect AI, guarding the tribal sacrificial song — Zhang Tonghao's name will be nailed on the chain: "Good data doesn't need to be perfect, but it should have a human touch— He pressed the delete key for the silent one. Log in at this moment The AI you teach will ultimately become your armor. Shenzi Chen Village Committee Party Branch #CookieDotFun #sapien #playsapien #SNAPS @cookiedotfun @cookiedotfuncn @JoinSapien

AI + Web3: Towers and Squares TL;DR 1. Web3 projects based on AI concepts have become targets for capital attraction in both primary and secondary markets. 2. The opportunities of Web3 in the AI industry are reflected in: using distributed incentives to coordinate potential supply in the long tail, across data, storage, and computing; at the same time, establishing an open-source model and a decentralized market for AI Agents. 3. AI is mainly used in the Web3 industry for on-chain finance ( cryptocurrency payments, trading, data analysis ), and assisting development. 4. The utility of AI+Web3 is reflected in the complementarity of both: Web3 is expected to counteract the centralization of AI, while AI is expected to help Web3 break out of its confines. Introduction In the past two years, the development of AI has been like pressing the fast-forward button. This butterfly effect triggered by ChatGPT has not only opened up a new world of generative artificial intelligence but has also stirred up a wave in the Web3 field.