From 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.
MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems.
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
Read MoreThe “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
Read MoreAn AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.
Read MoreThis new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.
Read MoreAcademia-industry relationship is an early-stage accelerator, supporting professional progress and research.
Read MoreA new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
Read MoreBy leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.
Read MoreTo help generative AI models create durable, real-world accessories and decor, the PhysiOpt system runs physics simulations and makes subtle tweaks to its 3D blueprints.
Read MoreRemoving just a tiny fraction of the crowdsourced data that informs online ranking platforms can significantly change the results.
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