A smarter way to develop new drugs

Pharmaceutical companies are using artificial intelligence to streamline the process of discovering new medicines. Machine-learning models can propose new molecules that have specific properties which could fight certain diseases, doing in minutes what might take humans months to achieve manually. But there’s a major hurdle that holds these systems back: The models often suggest new […]

Estimating the informativeness of data

Not all data are created equal. But how much information is any piece of data likely to contain? This question is central to medical testing, designing scientific experiments, and even to everyday human learning and thinking. MIT researchers have developed a new way to solve this problem, opening up new applications in medicine, scientific discovery, […]

An easier way to teach robots new skills

With e-commerce orders pouring in, a warehouse robot picks mugs off a shelf and places them into boxes for shipping. Everything is humming along, until the warehouse processes a change and the robot must now grasp taller, narrower mugs that are stored upside down. Reprogramming that robot involves hand-labeling thousands of images that show it […]

Anticipating others’ behavior on the road

Humans may be one of the biggest roadblocks keeping fully autonomous vehicles off city streets. If a robot is going to navigate a vehicle safely through downtown Boston, it must be able to predict what nearby drivers, cyclists, and pedestrians are going to do next. Behavior prediction is a tough problem, however, and current artificial […]

Learning to think critically about machine learning

Students in the MIT course 6.036 (Introduction to Machine Learning) study the principles behind powerful models that help physicians diagnose disease or aid recruiters in screening job candidates. Now, thanks to the Social and Ethical Responsibilities of Computing (SERC) framework, these students will also stop to ponder the implications of these artificial intelligence tools, which […]

Three from MIT awarded 2022 Paul and Daisy Soros Fellowships for New Americans

MIT graduate student Fernanda De La Torre, alumna Trang Luu ’18, SM ’20, and senior Syamantak Payra are recipients of the 2022 Paul and Daisy Soros Fellowships for New Americans. De La Torre, Luu, and Payra are among 30 New Americans selected from a pool of over 1,800 applicants. The fellowship honors the contributions of immigrants […]

MIT Schwarzman College of Computing unveils Break Through Tech AI

Aimed at driving diversity and inclusion in artificial intelligence, the MIT Stephen A. Schwarzman College of Computing is launching Break Through Tech AI, a new program to bridge the talent gap for women and underrepresented genders in AI positions in industry. Break Through Tech AI will provide skills-based training, industry-relevant portfolios, and mentoring to qualified […]

MIT’s FutureMakers programs help kids get their minds around — and hands on — AI

As she was looking for a camp last summer, Yabesra Ewnetu, who’d just finished eighth grade, found a reference to MIT’s FutureMakers Create-a-thon. Ewnetu had heard that it’s hard to detect bias in artificial intelligence because AI algorithms are so complex, but this didn’t make sense to her. “I was like, well, we’re the ones […]

An optimized solution for face recognition

The human brain seems to care a lot about faces. It’s dedicated a specific area to identifying them, and the neurons there are so good at their job that most of us can readily recognize thousands of individuals. With artificial intelligence, computers can now recognize faces with a similar efficiency — and neuroscientists at MIT’s […]

Does this artificial intelligence think like a human?

In machine learning, understanding why a model makes certain decisions is often just as important as whether those decisions are correct. For instance, a machine-learning model might correctly predict that a skin lesion is cancerous, but it could have done so using an unrelated blip on a clinical photo. While tools exist to help experts […]

Dan Huttenlocher ponders our human future in an age of artificial intelligence

What does it mean to be human in an age where artificial intelligence agents make decisions that shape human actions? That’s a deep question with no easy answers, and it’s been on the mind of Dan Huttenlocher SM ’84, PhD ’88, dean of the MIT Schwarzman College of Computing, for the past few years. “Advances […]

Featured video: L. Rafael Reif on the power of education

MIT President L. Rafael Reif recently joined Raúl Rodríguez, associate vice president of internationalization at Tecnológico de Monterrey, for a wide-ranging fireside chat about the power of education and its impact in addressing global issues, even more so in a post pandemic world.  “When I was younger, my parents used to always tell me and my […]

Solving the challenges of robotic pizza-making

Imagine a pizza maker working with a ball of dough. She might use a spatula to lift the dough onto a cutting board then use a rolling pin to flatten it into a circle. Easy, right? Not if this pizza maker is a robot. For a robot, working with a deformable object like dough is […]

When it comes to AI, can we ditch the datasets?

Huge amounts of data are needed to train machine-learning models to perform image classification tasks, such as identifying damage in satellite photos following a natural disaster. However, these data are not always easy to come by. Datasets may cost millions of dollars to generate, if usable data exist in the first place, and even the […]

Computational modeling guides development of new materials

Metal-organic frameworks, a class of materials with porous molecular structures, have a variety of possible applications, such as capturing harmful gases and catalyzing chemical reactions. Made of metal atoms linked by organic molecules, they can be configured in hundreds of thousands of different ways. To help researchers sift through all of the possible metal-organic framework […]

The benefits of peripheral vision for machines

Perhaps computer vision and human vision have more in common than meets the eye? Research from MIT suggests that a certain type of robust computer-vision model perceives visual representations similarly to the way humans do using peripheral vision. These models, known as adversarially robust models, are designed to overcome subtle bits of noise that have […]

Injecting fairness into machine-learning models

If a machine-learning model is trained using an unbalanced dataset, such as one that contains far more images of people with lighter skin than people with darker skin, there is serious risk the model’s predictions will be unfair when it is deployed in the real world. But this is only one part of the problem. […]

Using artificial intelligence to find anomalies hiding in massive datasets

Identifying a malfunction in the nation’s power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated sensors spread across the U.S. capture data on electric current, voltage, and other critical information in real time, often taking multiple recordings per second. Researchers at the MIT-IBM Watson AI […]

More sensitive X-ray imaging

Scintillators are materials that emit light when bombarded with high-energy particles or X-rays. In medical or dental X-ray systems, they convert incoming X-ray radiation into visible light that can then be captured using film or photosensors. They’re also used for night-vision systems and for research, such as in particle detectors or electron microscopes. Researchers at […]

Can machine-learning models overcome biased datasets?

Artificial intelligence systems may be able to complete tasks quickly, but that doesn’t mean they always do so fairly. If the datasets used to train machine-learning models contain biased data, it is likely the system could exhibit that same bias when it makes decisions in practice. For instance, if a dataset contains mostly images of […]

Toward a stronger defense of personal data

A heart attack patient, recently discharged from the hospital, is using a smartwatch to help monitor his electrocardiogram signals. The smartwatch may seem secure, but the neural network processing that health information is using private data that could still be stolen by a malicious agent through a side-channel attack. A side-channel attack seeks to gather […]