MIT Schwarzman College of Computing

Alzheimer’s disease affects more than 6 million people in the United States, and there are very few FDA-approved treatments that can slow the progression of the disease. In hopes of discovering new targets for potential Alzheimer’s treatments, MIT researchers have performed the broadest analysis yet of the genomic, epigenomic, and transcriptomic changes that occur in every cell type in the …

Generative AI, which is currently riding a crest of popular discourse, promises a world where the simple transforms into the complex — where a simple distribution evolves into intricate patterns of images, sounds, or text, rendering the artificial startlingly real. The realms of imagination no longer remain as mere abstractions, as researchers from MIT's Computer Science and Artificial Intelligence Laboratory …

Five MIT professors have been selected to receive the 2023 Simons Investigators awards from the Simons Foundation. Virginia Vassilevska Williams and Vinod Vaikuntanathan are both professors in MIT’s Department of Electrical Engineering and Computer Science (EECS) and principal investigators in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). Aram Harrow and Leonid Mirny are professors in the Department of Physics, …

An age-old adage, often introduced to us during our formative years, is designed to nudge us beyond our self-centered, nascent minds: "Two heads are better than one." This proverb encourages collaborative thinking and highlights the potency of shared intellect. Fast forward to 2023, and we find that this wisdom holds true even in the realm of artificial intelligence: Multiple language …

Innovating at the intersection of chemistry, biology, and engineering, Professor Brad Pentelute and the Pentelute Lab at MIT invent new chemistry, platforms, and techniques that might revolutionize therapeutics. Their formula in brief: nature-inspired research that begins at the molecular level, infused with state-of-the-art machine learning and automation, aimed at solving real-world problems. Take, for example, biotechnology’s longstanding protein delivery problem. …

As 3D printers have become cheaper and more widely accessible, a rapidly growing community of novice makers are fabricating their own objects. To do this, many of these amateur artisans access free, open-source repositories of user-generated 3D models that they download and fabricate on their 3D printer. But adding custom design elements to these models poses a steep challenge for …

The classic computer science adage “garbage in, garbage out” lacks nuance when it comes to understanding biased medical data, argue computer science and bioethics professors from MIT, Johns Hopkins University, and the Alan Turing Institute in a new opinion piece published in a recent edition of the New England Journal of Medicine (NEJM). The rising popularity of artificial intelligence has …

Whether you are a new employee, a gymnast, or a bendy straw manufacturer, one trait is ideal across the board: flexibility. The same can now be said about prototyping electronic devices. While designers typically test out their designs on “breadboards,” or thin plastic boards that can hold together electronic components, they are often stiff and slow. With the rigidity of …

In computer graphics and computer-aided design (CAD), 3D objects are often represented by the contours of their outer surfaces. Computers store these shapes as “thin shells,” which model the contours of the skin of an animated character but not the flesh underneath. This modeling decision makes it efficient to store and manipulate 3D shapes, but it can lead to unexpected …

Imagine you’re enjoying a picnic by a riverbank on a windy day. A gust of wind accidentally catches your paper napkin and lands on the water’s surface, quickly drifting away from you. You grab a nearby stick and carefully agitate the water to retrieve it, creating a series of small waves. These waves eventually push the napkin back toward the …

Powerful machine-learning algorithms known as vision and language models, which learn to match text with images, have shown remarkable results when asked to generate captions or summarize videos. While these models excel at identifying objects, they often struggle to understand concepts, like object attributes or the arrangement of items in a scene. For instance, a vision and language model might …

Computing is at an inflection point. Moore’s Law, which predicts that the number of transistors on an electronic chip will double each year, is slowing down due to the physical limits of fitting more transistors on affordable microchips. These increases in computer power are slowing down as the demand grows for high-performance computers that can support increasingly complex artificial intelligence …

Someone learning to play tennis might hire a teacher to help them learn faster. Because this teacher is (hopefully) a great tennis player, there are times when trying to exactly mimic the teacher won’t help the student learn. Perhaps the teacher leaps high into the air to deftly return a volley. The student, unable to copy that, might instead try …

On April 24, MIT celebrated outstanding students and employees at the annual Change-Maker Awards for their diligent work to eradicate sexual misconduct and support survivors. These architects of positive change exemplify one of MIT’s core values: striving to make our community a more humane and welcoming place where all can thrive. Hosted by MIT Violence Prevention and Response (VPR) and …

Socrates once said: “It is not the size of a thing, but the quality that truly matters. For it is in the nature of substance, not its volume, that true value is found.” Does size always matter for large language models (LLMs)? In a technological landscape bedazzled by LLMs taking center stage, a team of MIT Computer Science and Artificial …

Huge libraries of drug compounds may hold potential treatments for a variety of diseases, such as cancer or heart disease. Ideally, scientists would like to experimentally test each of these compounds against all possible targets, but doing that kind of screen is prohibitively time-consuming. In recent years, researchers have begun using computational methods to screen those libraries in hopes of …

There has been a remarkable surge in the use of algorithms and artificial intelligence to address a wide range of problems and challenges. While their adoption, particularly with the rise of AI, is reshaping nearly every industry sector, discipline, and area of research, such innovations often expose unexpected consequences that involve new norms, new expectations, and new rules and laws. …

When interacting with another person, you likely spend part of your time trying to anticipate how they will feel about what you’re saying or doing. This task requires a cognitive skill called theory of mind, which helps us to infer other people’s beliefs, desires, intentions, and emotions. MIT neuroscientists have now designed a computational model that can predict other people’s …

When machine-learning models are deployed in real-world situations, perhaps to flag potential disease in X-rays for a radiologist to review, human users need to know when to trust the model’s predictions. But machine-learning models are so large and complex that even the scientists who design them don’t understand exactly how the models make predictions. So, they create techniques known as …

Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of machine-learning models used in applications like speech recognition and object detection. The work, for the first time, combines two architectures of self-supervised learning, contrastive learning and masked data modeling, in …