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: Hendrix , Researcher at Web3Caff Research
Cover: Logo from this project, Typography by Web3Caff Research
Word count: 2800+ words in total
Current centralized AI service providers generally face issues with model authenticity and computational integrity. This deficiency has spurred the continuous pursuit of zero-knowledge learning (zkML) technology in the Web3 domain for computationally intensive tasks. This zkML technology applies ZK techniques to machine learning inference, allowing verification of the authenticity and integrity of inference computations without exposing sensitive model data. However, most of these zkML frameworks are still in the experimental stage. They typically require complex customization for different tasks, demanding engineers to design proof circuits at the hardware level, yet still yielding results with enormous proof costs. Inference Labs recently launched two new products, DSperse and JSTProve, to address the pain points of zkML's difficulty in practical application, hoping to pave the way for the practical and large-scale application of zkML in computationally intensive tasks.
