How can you easily grasp the current market trends, technological developments, ecosystem progress, and governance dynamics in the Web3 industry? Web3Caff Research's "Market Trend Insights" column delves into the front lines to identify and select current hot topics, providing valuable interpretations, commentary, and fundamental analysis. See through the phenomena to the essence; follow us now to quickly capture the forefront of the Web3 market.
Author: Shirley Li , Researcher at Web3Caff Research
Cover: Logo from this project, Typography by Web3Caff Research
Word count: Approximately 3600+ words in total
With the rapid development of AI technology, some potential contradictions have begun to emerge. For example, the underlying data and computing power in the current AI field are controlled by a few entities, and the training, inference, and evaluation processes of AI models are mostly in a "black box" state, lacking transparency. At the same time, the training and inference of AI models rely on abundant data. Although publicly available data is relatively easy to obtain, its quality varies greatly, making it difficult for AI models to quickly establish an advantage in market competition. Therefore, high-quality private or copyrighted data has become a crucial asset. However, due to the opaque operation of centralized AI platforms, the process of how data is used and how its value is generated is difficult to trace. This makes it difficult for data contributors and model developers to confidently share their data, and they also find it difficult to obtain fair and verifiable economic rewards based on their contributions.
Against this backdrop, the Metis team is dedicated to building a high-performance blockchain ecosystem for AI-native applications. Previously, Metis launched its AI-native Layer 2 network, Hyperion, and recently, another AI service framework built by Metis, LazAI, also officially launched its Alpha mainnet .
LazAI is an on-chain AI infrastructure layer. Its core concept is to break data monopolies through the decentralization, transparency, and incentive mechanisms of blockchain technology, enabling data contributors, model developers, and users to participate and benefit fairly, thus forming a new generation of AI ecosystem. To this end, LazAI attempts to address the issues mentioned at the beginning from the following three aspects:
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