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.
Researchers create a trajectory-planning system that enables drones working together in the same airspace to always choose a safe path forward.
Annual award honors early-career researchers for creativity, innovation, and research accomplishments.
A new experiential learning opportunity challenges undergraduates across the Greater Boston area to apply their AI skills to a range of industry projects.
MIT researchers are discovering which parts of the brain are engaged when a person evaluates a computer program.
New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.
Researchers make headway in solving a longstanding problem of balancing curious “exploration” versus “exploitation” of known pathways in reinforcement learning.
A new technique enables AI models to continually learn from new data on intelligent edge devices like smartphones and sensors, reducing energy costs and privacy risks.
A machine-learning method finds patterns of health decline in ALS, informing future clinical trial designs and mechanism discovery. The technique also extends to Alzheimer’s and Parkinson’s.
On its own, a new machine-learning model discovers linguistic rules that often match up with those created by human experts.
Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.
Recent MEng graduates reflect on their application-focused research as affiliates of the MIT-IBM Watson AI Lab.
Studying a powerful type of cyberattack, researchers identified a flaw in how it’s been analyzed before, then developed new techniques that stop it in its tracks.
A machine-learning method imagines what a sentence visually looks like, to situate and ground its semantics in the real world, improving translation, like humans can.
A machine-learning model can identify the action in a video clip and label it, without the help of humans.
A new neural network approach captures the characteristics of a physical system’s dynamic motion from video, regardless of rendering configuration or image differences.