Theta Labs Partners with Peking University to Advance AI Research
Theta Labs has made significant strides in the realm of AI and blockchain research by announcing Peking University as a new customer for its EdgeCloud AI platform. Peking University, a prestigious institution ranked among the top 10 globally in computer science, will utilize Theta’s hybrid cloud GPU infrastructure to enhance its research capabilities. This collaboration is part of Theta’s broader initiative to support advanced AI research across various academic institutions, including notable universities in the US and Korea, such as the University of Oregon and KAIST. The addition of corporate clients like Liner and Jamcoding further underscores Theta’s growing influence in the AI sector.
Professor Zhen Xiao, a leading figure in distributed systems and AI at Peking University, has been pivotal in this partnership. With a Ph.D. from Cornell University and a robust publication record, Professor Xiao’s research spans multiple domains, including deep learning and blockchain. His involvement with Theta began in 2022 when he joined the Theta Advisory Board, contributing to the development of the EdgeCloud platform. The collaboration has already yielded several joint research papers presented at prestigious conferences, showcasing advancements in adaptive defense mechanisms for AI models and scalable blockchain frameworks.
The integration of EdgeCloud’s hybrid cloud GPU infrastructure is set to revolutionize AI research at Peking University. Professor Xiao expressed enthusiasm about the potential of EdgeCloud to facilitate large-scale distributed AI projects, stating that it represents one of the most complex hybrid GPU systems he has encountered. This partnership not only enhances research capabilities at Peking University but also positions Theta as a leader in decentralized GPU platforms for academia in Asia, with aspirations for global expansion. The future of AI innovation is likely to be driven by infrastructure companies like Theta that effectively harness distributed computation and GPU resources.