Meet the 2022-23 Accenture Fellows

Launched in October 2020, the MIT and Accenture Convergence Initiative for Industry and Technology underscores the ways in which industry and technology can collaborate to spur innovation. The five-year initiative aims to achieve its mission through research, education, and fellowships. …

Large language models help decipher clinical notes

Electronic health records (EHRs) need a new public relations manager. Ten years ago, the U.S. government passed a law that strongly encouraged the adoption of electronic health records with the intent of improving and streamlining care. The enormous amount of information in these …

Ushering in a new era of computing

As a graduate student doing his master’s thesis on speech recognition at the MIT AI Lab (now the MIT Computer Science and Artificial Intelligence Laboratory), Dan Huttenlocher worked closely with Professor Victor Zue. Well known for pioneering the development of …

Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs

Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy grids, and molecular interactions. As researchers collect more data and build out these …

Breaking the scaling limits of analog computing

As machine-learning models become larger and more complex, they require faster and more energy-efficient hardware to perform computations. Conventional digital computers are struggling to keep up.

An analog optical neural network could perform the same tasks as a digital one, …

Teresa Gao named 2024 Mitchell Scholar

MIT senior Teresa Gao has been named one of the 12 winners of the George J. Mitchell Scholarship’s Class of 2024. After graduating next spring with a double major in computer science and engineering as well as brain and cognitive …

A simpler path to better computer vision

Before a machine-learning model can complete a task, such as identifying cancer in medical images, the model must be trained. Training image classification models typically involves showing the model millions of example images gathered into a massive dataset.

However, using …

A far-sighted approach to machine learning

Picture two teams squaring off on a football field. The players can cooperate to achieve an objective, and compete against other players with conflicting interests. That’s how the game works.

Creating artificial intelligence agents that can learn to compete and …

Solving brain dynamics gives rise to flexible machine-learning models

Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world …

Ensuring AI works with the right dose of curiosity

It’s a dilemma as old as time. Friday night has rolled around, and you’re trying to pick a restaurant for dinner. Should you visit your most beloved watering hole or try a new establishment, in the hopes of discovering something …

In machine learning, synthetic data can offer real performance improvements

Teaching a machine to recognize human actions has many potential applications, such as automatically detecting workers who fall at a construction site or enabling a smart home robot to interpret a user’s gestures.

To do this, researchers train machine-learning models …

Machine learning facilitates “turbulence tracking” in fusion reactors

Fusion, which promises practically unlimited, carbon-free energy using the same processes that power the sun, is at the heart of a worldwide research effort that could help mitigate climate change.

A multidisciplinary team of researchers is now bringing tools and …

Using sound to model the world

Imagine the booming chords from a pipe organ echoing through the cavernous sanctuary of a massive, stone cathedral.

The sound a cathedral-goer will hear is affected by many factors, including the location of the organ, where the listener is standing, …

Deep learning with light

Ask a smart home device for the weather forecast, and it takes several seconds for the device to respond. One reason this latency occurs is because connected devices don’t have enough memory or power to store and run the enormous …

Learning on the edge

Microcontrollers, miniature computers that can run simple commands, are the basis for billions of connected devices, from internet-of-things (IoT) devices to sensors in automobiles. But cheap, low-power microcontrollers have extremely limited memory and no operating system, making it challenging to …

New program to support translational research in AI, data science, and machine learning

The MIT School of Engineering and Pillar VC today announced the MIT-Pillar AI Collective, a one-year pilot program funded by a gift from Pillar VC that will provide seed grants for projects in artificial intelligence, machine learning, and data science …

Q&A: Global challenges surrounding the deployment of AI

The AI Policy Forum (AIPF) is an initiative of the MIT Schwarzman College of Computing to move the global conversation about the impact of artificial intelligence from principles to practical policy implementation. Formed in late 2020, AIPF brings together leaders

In-home wireless device tracks disease progression in Parkinson’s patients

Parkinson’s disease is the fastest-growing neurological disease, now affecting more than 10 million people worldwide, yet clinicians still face huge challenges in tracking its severity and progression.

Clinicians typically evaluate patients by testing their motor skills and cognitive functions during …

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