The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
New dataset of 30,000-plus competition math problems from 47 countries gives AI researchers a harder test — and students worldwide a better training ground.
A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.
Researchers are developing hardware and algorithms to improve collaboration between divers and autonomous underwater vehicles engaged in maritime missions.
Researchers use control theory to shed unnecessary complexity from AI models during training, cutting compute costs without sacrificing performance.
Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.
Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.
By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.