A far-sighted approach to machine learning
New system can teach a group of cooperative or competitive AI agents to find an optimal long-term solution.
From LGO to PhD
For some MIT Leaders for Global Operations graduates, a research passion becomes a full-time career.
Solving brain dynamics gives rise to flexible machine-learning models
MIT CSAIL researchers solve a differential equation behind the interaction of two neurons through synapses to unlock a new type of speedy and efficient AI algorithm.
Ensuring AI works with the right dose of curiosity
Researchers make headway in solving a longstanding problem of balancing curious “exploration” versus “exploitation” of known pathways in reinforcement learning.
In machine learning, synthetic data can offer real performance improvements
Models trained on synthetic data can be more accurate than other models in some cases, which could eliminate some privacy, copyright, and ethical concerns from using real data.
Study urges caution when comparing neural networks to the brain
Computing systems that appear to generate brain-like activity may be the result of researchers guiding them to a specific outcome.
Machine learning facilitates “turbulence tracking” in fusion reactors
A new approach sheds light on the behavior of turbulent structures that can affect the energy generated during fusion reactions, with implications for reactor design.
Using sound to model the world
This machine-learning system can simulate how a listener would hear a sound from any point in a room.
3 Questions: How AI image generators could help robots
Yilun Du, a PhD student and MIT CSAIL affiliate, discusses the potential applications of generative art beyond the explosion of images that put the web into creative hysterics.
A faster experiment to find and study topological materials
Using machine learning and simple X-ray spectra, researchers can uncover compounds that might enable next-generation computer chips or quantum devices.
Deep learning with light
A new method uses optics to accelerate machine-learning computations on smart speakers and other low-power connected devices.
A factory for FrEDs at MIT
Graduate students create on-campus assembly factory for fiber extrusion devices.
Learning on the edge
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.
Neurodegenerative disease can progress in newly identified patterns
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.
New program to support translational research in AI, data science, and machine learning
The MIT-Pillar AI Collective will cultivate prospective entrepreneurs and drive innovation.