Stanford’s AI Research Laboratory for Use Theta EdgeCloud for LLM Model Studies

Stanford Lab, focused on AI survey, will use a decentralized calculation platform in the cloud EdgeCloud for its work at LLMS.

Decentralized cloud could be a solution for AI’s huge computer needs. 17. April Aunt Laboratories have been detected In order for AI Stanford University used theta (Theta) EdgeCloud in its work on large language models. The laboratory, led by Professor Ellen ViterCa, will use the platform for discrete optimization and algorithmic reasoning of LLMS.

Stanford joins the growing list of academic institutions using a decentralized exploration platform. According to Theta Laboratories, other EdgeCloud adoptive include Seoul National University University Korea, University of Oregon, Michigan State University and more.

Large technical and decentralized services compete for AI Compute

Large technological companies quickly spread investment in computer infrastructure, especially one directed towards the power supply ai. In 2024. Years Microsoft invested $ 3.3 billion In the Data Center in Visconsin, with the administration base Joe Bidenova.

At the same time, Amazon stated plans Spend 11 billion dollars about data centers in Indiana. Google, on the other hand, goes globally, invest in your data in Finland and construction of another one in Malaysia for $ 2 billion.

However, a large technical model is not the only one competing for AI workloads. Unlike most traditional LLM services, Theta EdgeCloud operates as a decentralized cloud computing platform. Its infrastructure is geographically distributed, which means that it does not rely on the mass centralized data data to obtain the calculation of power.

Instead, the platform uses Blocchain technology to reward less GPU providers based on income created by users. This allows Theta to work with lower capital expenditures and faster circumference. In turn, offers accessible infrastructure for users.

The Network is a blockage protocol that is originally designed for Decentralized video streaming. However, the network has been expanded from then to provide a decentralized cloud computing infrastructure, with a special focus on AI applications.