MIT Schwarzman College of Computing

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MIT scientists investigate memorization risk in the age of clinical AI

What is patient privacy for? The Hippocratic Oath, thought to be one of the earliest and most widely known medical ethics texts in the world, reads: “Whatever I see or hear in the lives of my patients, whether in connection with my professional practice or not, which ought not to be spoken of outside, I […]

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MIT in the media: 2025 in review

“At MIT, innovation ranges from awe-inspiring technology to down-to-Earth creativity,” noted Chronicle, during a campus visit this year for an episode of the program. In 2025, MIT researchers made headlines across print publications, podcasts, and video platforms for key scientific advances, from breakthroughs in quantum and artificial intelligence to new efforts aimed at improving pediatric health

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Guided learning lets “untrainable” neural networks realize their potential

Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks.Their findings

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A new way to increase the capabilities of large language models

Most languages use word position and sentence structure to extract meaning. For example, “The cat sat on the box,” is not the same as “The box was on the cat.” Over a long text, like a financial document or a novel, the syntax of these words likely evolves. Similarly, a person might be tracking variables in

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3 Questions: Using computation to study the world’s best single-celled chemists

Today, out of an estimated 1 trillion species on Earth, 99.999 percent are considered microbial — bacteria, archaea, viruses, and single-celled eukaryotes. For much of our planet’s history, microbes ruled the Earth, able to live and thrive in the most extreme of environments. Researchers have only just begun in the last few decades to contend

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Enabling small language models to solve complex reasoning tasks

As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that human-like reasoning is around the corner. In reality, they still trail us by a wide margin on complex tasks. Try playing Sudoku with one, for instance, where you fill in numbers one through nine in such

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New MIT program to train military leaders for the AI age

Artificial intelligence can enhance decision-making and enable action with reduced risk and greater precision, making it a critical tool for national security. A new program offered jointly by the MIT departments of Mechanical Engineering (Course 2, MechE) and Electrical Engineering and Computer Science (Course 6, EECS) will provide breadth and depth in technical studies for

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New method improves the reliability of statistical estimations

Let’s say an environmental scientist is studying whether exposure to air pollution is associated with lower birth weights in a particular county.They might train a machine-learning model to estimate the magnitude of this association, since machine-learning methods are especially good at learning complex relationships.Standard machine-learning methods excel at making predictions and sometimes provide uncertainties, like

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New materials could boost the energy efficiency of microelectronics

MIT researchers have developed a new fabrication method that could enable the production of more energy efficient electronics by stacking multiple functional components on top of one existing circuit.In traditional circuits, logic devices that perform computation, like transistors, and memory devices that store data are built as separate components, forcing data to travel back and

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MIT affiliates named 2025 Schmidt Sciences AI2050 Fellows

Two current MIT affiliates and seven additional alumni are among those named to the 2025 cohort of AI2050 Fellows.  Zongyi Li, a postdoc in the MIT Computer Science and Artificial Intelligence Lab, and Tess Smidt ’12, an associate professor of electrical engineering and computer science (EECS), were both named as AI2050 Early Career Fellows. Seven additional MIT

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