Using AI to mitigate the growing environmental threat of data centers
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
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Supercomputing researchers document evolution of AI hardware
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Read MoreMIT students gain a humanist lens on technical innovation in Tulsa, Oklahoma
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
Read MoreFrom MIT to IBM, expediting AI and quantum deployment
MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems.
Read MoreWhen AI art has no author: Study finds generated images often can’t be traced to training data
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
Read MoreHow a medical database developed at MIT evolved into a global standard of data-sharing
The visionary PhysioNet platform launched 25 years ago, based on a system developed at MIT in the 1970s. It has become one of the most comprehensive biomedical and clinical data repositories in existence.
Read More3 Questions: Neural transparency and the future of AI design
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI’s neural network before their chatbot ever says a word.
Read MoreHelping AI models to meet the real world
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
Read MoreJesse Thaler named director of the Laboratory for Nuclear Science
The professor of physics and inaugural director of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions will lead LNS and continue his research in particle physics.
Read MoreImproving the speed and energy-efficiency of AI agents
A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.
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