Meet the 2022-23 Accenture Fellows
This year's fellows will work across research areas including telemonitoring, human-computer interactions, operations research, AI-mediated socialization, and chemical transformations.
Large language models help decipher clinical notes
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.
MIT researchers use quantum computing to observe entanglement
Researchers at the Center for Theoretical Physics lead work on testing quantum gravity on a quantum processor.
Ushering in a new era of computing
Dan Huttenlocher is a professor of electrical engineering and computer science and the inaugural dean at MIT Schwarzman College of Computing.
Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs
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.
Breaking the scaling limits of analog computing
New technique could diminish errors that hamper the performance of super-fast analog optical neural networks.
The task of magnetic classification suddenly looks easier
MIT undergraduate researchers Helena Merker, Harry Heiberger, and Linh Nguyen, and PhD student Tongtong Liu, exploit machine-learning techniques to determine the magnetic structure of materials.
Teresa Gao named 2024 Mitchell Scholar
The MIT senior will pursue postgraduate studies in computer science in Ireland.
A simpler path to better computer vision
New research reveals a scalable technique that uses synthetic data to improve the accuracy of AI models that recognize images.
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.