A four-legged robotic system for playing soccer on various terrains
“DribbleBot” can maneuver a soccer ball on landscapes such as sand, gravel, mud, and snow, using reinforcement learning to adapt to varying ball dynamics.
Speeding up drug discovery with diffusion generative models
MIT researchers built DiffDock, a model that may one day be able to find new drugs faster than traditional methods and reduce the potential for adverse side effects.
New algorithm keeps drones from colliding in midair
Researchers create a trajectory-planning system that enables drones working together in the same airspace to always choose a safe path forward.
Strengthening trust in machine-learning models
Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where confidence in the results of a data analysis might break down.
Learning to grow machine-learning models
New LiGO technique accelerates training of large machine-learning models, reducing the monetary and environmental cost of developing AI applications.
New “traffic cop” algorithm helps a drone swarm stay on task
By keeping data fresh, the system could help robots inspect buildings or search disaster zones.
New method accelerates data retrieval in huge databases
Researchers used machine learning to build faster and more efficient hash functions, which are a key component of databases.
It’s a weird, weird quantum world
In MIT’s 2023 Killian Lecture, Peter Shor shares a brief history of quantum computing from a personal viewpoint.
Large language models are biased. Can logic help save them?
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.
Integrating humans with AI in structural design
A process that seeks feedback from human specialists proves more effective at optimization than automated systems working alone.
Report: CHIPS Act just the first step in addressing threats to US leadership in advanced computing
The Advanced Computing Users Survey, sampling sentiments from 120 top-tier universities, national labs, federal agencies, and private firms, finds the decline in America’s advanced computing lead spans many areas.
Phiala Shanahan is seeking fundamental answers about our physical world
With supercomputers and machine learning, the physicist aims to illuminate the structure of everyday particles and uncover signs of dark matter.
MIT-Takeda Program heads into fourth year with crop of 10 new projects
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
A new chip for decoding data transmissions demonstrates record-breaking energy efficiency
The chip, which can decipher any encoded signal, could enable lower-cost devices that perform better while requiring less hardware.
Efficient technique improves machine-learning models’ reliability
The method enables a model to determine its confidence in a prediction, while using no additional data and far fewer computing resources than other methods.