#AI and #RWA are our most optimistic tracks this cycle, and the team has invested a lot of energy in research, during which I often ask the team a question: "What is the truly scarce #AI resource?" ” Some say it's computing power, some say it's algorithms. Through continuous consultation and communication, I realized more and more clearly that the real scarcity is high-quality human data. The recent release of #Vana #Playground AI data products has blown up my eyes, allowing truly high-quality human data to return to individuals and ushering in the era of data capital. In the past, data was basically divided into three categories: 1️⃣ Public scraping data: Tweets, Reddit crawling, there is a lot of such data, but it is shallow and lacks context. 2️⃣ Platform private data: Spotify, Telegram, ChatGPT interaction, this is the really valuable in-depth data, but it is locked by the big manufacturers. 3️⃣ Annotation datasets: Kaggle or crowdsourced annotation has limited quality, high cost, and is difficult to scale. What #Playground did was create a fourth type of data: data collectively owned by the community. This is amazing. Because it is neither a "glimpse" crawled for free nor a "black box monopoly" of the platform, but a "deep human data" actively contributed by users and aggregated by DAOs. When I watched the video demo of #VanaPlayground, I saw for the first time that I could preview the dataset architecture, download synthetic samples, and even connect with the DataDAO behind it in one interface, which really felt a bit like visiting a "data farmers' market". Compared with the past, buying data is like buying canned food, cold and unaware of the ingredients; Now it is a direct dialogue with farmers (communities) to see the origin and freshness. Why is #VanaPlayground important to #AI? Currently, training #AI models does not rely on more computing power, but on the depth and diversity of data. Let me use an analogy, for example, the interaction data of the #ChatGPT we use every day can reflect the real way humans think; For example, people use #Spotify listening data to describe user preferences and emotions. When community partners use #Telegram group chats, group chat data can map the real context of community interactions. These things are not given by crawls. They are the "fuel" needed for #AI personalization, #Agent interaction, next-generation applications. In #Playground, data is not a messy pile of JSON, but a structured sample with architecture, browsable, and measurable. This allows developers to design and test models faster, and buyers can "try it" before deciding whether to buy or not. Overall, I personally think #VanaPlayground has a big vision, not just a "data showroom" but a front office for a decentralized data economy. Today it makes datasets visible and explorable, tearing through the data gap of high-quality personal datasets; Tomorrow it will become an entrance to data trading. You can initiate data requests directly in the interface, allowing community data to directly participate in value distribution. In the future, this could be a global human data protocol, with user contributions → community aggregation → developers using → revenue to reflow communities. This model is very similar to the turning point of "land privatization" in history. In the past, the data belonged to the platform, and users could only "work". Now that data can be "confirmed", it is no longer a by-product, but capital. The impact of this on the entire #AI industry may be more far-reaching than simply improving computing power, and it is worth paying attention to and looking forward to! 🧐