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In the current rapid development of artificial intelligence, many people are following the competition among various large models, such as Sora or GPT-5. However, the real value may not lie in these models themselves, but in the data sources they rely on.
In this context, on-chain data, due to its transparency and authenticity, is becoming a key nutrient for AI development. In this field, Chainbase is quietly rising to become an important player in the supply of on-chain data.
The uniqueness of Chainbase lies in the fact that it is not a common AI tool, a new type of L2 solution, or a visualization platform. Instead, it is an infrastructure that provides structured on-chain data for AI, intelligent agents, and various projects. This positioning, while not glamorous, contains immense commercial potential.
Compared to other data platforms, Chainbase has obvious advantages: it is not limited to graph-structured data reading like The Graph, nor does it require complex SQL queries like Dune. More importantly, the data it provides is both structured and verifiable, which platforms like Arkham cannot match.
Large tech companies like Google have also realized the importance of on-chain data and are starting to make moves in this field. However, Chainbase has gone further down this path: it has not only achieved data structuring and verifiability, but also proposed the innovative concept of "data as an asset."
In the era of AI, whoever can provide the highest quality and most reliable data holds the key to future development. Chainbase is precisely targeting this critical point and is expected to occupy an important position in the future wave of integration between AI and Web3.
With the continuous advancement of AI technology, the demand for high-quality data will only grow. In this trend, data infrastructure providers like Chainbase are likely to become one of the biggest beneficiaries in the entire ecosystem. Although they are not as eye-catching as front-end AI applications, they play a crucial role behind the scenes.