Unpacking the “black box” to build better AI models

When deep learning models are deployed in the real world, perhaps to detect financial fraud from credit card activity or identify cancer in medical images, they are often able to outperform humans.

But what exactly are these deep learning models …

Subtle biases in AI can influence emergency decisions

It’s no secret that people harbor biases — some unconscious, perhaps, and others painfully overt. The average person might suppose that computers — machines typically made of plastic, steel, glass, silicon, and various metals — are free of prejudice. While …

Machine learning and the arts: A creative continuum

Sketch a doodle of a drum or a saxophone to conjure a multi-instrumental composition. Look into a webcam, speak, and watch your mouth go bouncing across the screen — the input for a series of charmingly clunky chain reactions.

This …

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, …

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 …

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, …

3 Questions: How AI image generators could help robots

AI image generators, which create fantastical sights at the intersection of dreams and reality, bubble up on every corner of the web. Their entertainment value is demonstrated by an ever-expanding treasure trove of whimsical and random images serving as indirect

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 …

Neurodegenerative disease can progress in newly identified patterns

Neurodegenerative diseases — like amyotrophic lateral sclerosis (ALS, or Lou Gehrig's disease), Alzheimer’s, and Parkinson’s — are complicated, chronic ailments that can present with a variety of symptoms, worsen at different rates, and have many underlying genetic and environmental causes, …

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 …

Empowering Cambridge youth through data activism

For over 40 years, the Mayor's Summer Youth Employment Program (MSYEP, or the Mayor’s Program) in Cambridge, Massachusetts, has been providing teenagers with their first work experience, but 2022 brought a new offering. Collaborating with MIT’s Personal Robots research group (PRG) …

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