New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.
MIT researchers discovered a hidden atomic order that persists in metals even after extreme processing.
Assistant Professor Priya Donti’s research applies machine learning to optimize renewable energy.
The approach combines physics and machine learning to avoid damaging disruptions when powering down tokamak fusion machines.
Incorporating machine learning, MIT engineers developed a way to 3D print alloys that are much stronger than conventionally manufactured versions.
MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.
Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.
The new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.
At the inaugural MIT Generative AI Impact Consortium Symposium, researchers and business leaders discussed potential advancements centered on this powerful technology.
MIT-IBM Watson AI Lab researchers have developed a universal guide for estimating how large language models will perform based on smaller models in the same family.
MIT CSAIL researchers developed a tool that can model the shape and movements of fetuses in 3D, potentially assisting doctors in finding abnormalities and making diagnoses.
The research center, sponsored by the DOE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.
Popular mechanical engineering course applies machine learning and AI theory to real-world engineering design.