AI and # RWA are the most promising tracks for us this cycle. The team has invested a lot of energy in research, and during this time, I often ask the team one question: "What is the truly scarce # AI resource?"
Some say it's computing power, others say it's algorithms. Through continuous inquiry and communication, I have increasingly realized that the real scarcity is high-quality human data.
Recently, the #Vana released the #Playground AI data product, which impressed me. It brings high-quality human data back to individuals and opens the era of data capital!
In the past, data was generally divided into three categories:
1️⃣ Publicly scraped data: tweets, Reddit scraping. This type of data is abundant but shallow and lacks context.
2️⃣ Platform private data: interactions on Spotify, Telegram, ChatGPT. This is the truly valuable deep data, but it is tightly locked by large companies.
3️⃣ Labeled datasets: Kaggle or crowdsourced labeling, which have limited quality, high costs, and are difficult to scale.
What #Playground has done is create a fourth type of data: community collectively owned data. This is impressive because it is neither the "surface-level" data scraped for free nor the "black box monopoly" of platforms, but rather "deep human data" actively contributed by users and aggregated by a DAO.
After watching the video demonstration of #VanaPlayground, I felt like I was browsing a "data farmers' market" for the first time. I could preview the dataset structure, download synthetic samples, and even connect with the underlying DataDAO all in one interface. In contrast to the past, when buying data felt like purchasing canned food—cold and without knowing the ingredients—now I can directly converse with the farmers (community) and see the origin and freshness.
Why is #VanaPlayground so important for #AI?
Currently, training #AI models relies not on the amount of computing power but on the depth and diversity of data. For example, the interaction data we use daily with #ChatGPT reflects real human thinking patterns; similarly, the listening data from #Spotify can depict user preferences and emotions; and the group chat data from community members using #Telegram can map the real context of community interactions.
These elements cannot be provided by crawlers. They are the "fuel" necessary for #AI personalization, #Agent interactions, and next-generation applications. In #Playground, data is not just a pile of messy JSON but structured samples that are organized, browsable, and measurable. This allows developers to design models and conduct tests more quickly, while buyers can "sample" before deciding whether to purchase.
Overall, I personally believe that #VanaPlayground has a grand vision, not just as a "data showroom," but as the front end of a decentralized data economy. Today, it makes datasets visible and explorable, tearing down the data gap for high-quality personal datasets; tomorrow, it will become the entry point for data transactions. You can directly initiate data requests in the interface, allowing community data to participate directly in value distribution; in the future, this could become a global human data protocol: user contribution → community aggregation → developer use → revenue flowing back to the community. This model is very similar to the historical turning point of "land privatization." Previously, data belonged to platforms, and users could only "work." Now, data can be "certified," and it is no longer a byproduct but capital. The impact of this on the entire #AI industry may be more profound than simply enhancing computing power, and it is worth paying attention to and looking forward to! 🧐
免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。
