MIT Schwarzman College of Computing

Auto Added by WPeMatico

Katie Spivakovsky wins 2026 Churchill Scholarship

MIT senior Katie Spivakovsky has been selected as a 2026-27 Churchill Scholar and will undertake an MPhil in biological sciences at the Wellcome Sanger Institute at Cambridge University in the U.K. this fall.Spivakovsky, who is double-majoring in biological engineering and artificial intelligence, with minors in mathematics and biology, aims to integrate computation and bioengineering in […]

Katie Spivakovsky wins 2026 Churchill Scholarship Read More »

The philosophical puzzle of rational artificial intelligence

To what extent can an artificial system be rational?A new MIT course, 6.S044/24.S00 (AI and Rationality), doesn’t seek to answer this question. Instead, it challenges students to explore this and other philosophical problems through the lens of AI research. For the next generation of scholars, concepts of rationality and agency could prove integral in AI

The philosophical puzzle of rational artificial intelligence Read More »

Why it’s critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting.“We demonstrate that even when you train models on large amounts of data, and choose the

Why it’s critical to move beyond overly aggregated machine-learning metrics Read More »

Generative AI tool helps 3D print personal items that sustain daily use

Generative artificial intelligence models have left such an indelible impact on digital content creation that it’s getting harder to recall what the internet was like before it. You can call on these AI tools for clever projects such as videos and photos — but their flair for the creative hasn’t quite crossed over into the

Generative AI tool helps 3D print personal items that sustain daily use Read More »

At MIT, a continued commitment to understanding intelligence

The MIT Siegel Family Quest for Intelligence (SQI), a research unit in the MIT Schwarzman College of Computing, brings together researchers from across MIT who combine their diverse expertise to understand intelligence through tightly coupled scientific inquiry and rigorous engineering. These researchers engage in collaborative efforts spanning science, engineering, the humanities, and more. SQI seeks to

At MIT, a continued commitment to understanding intelligence Read More »

3 Questions: How AI could optimize the power grid

Artificial intelligence has captured headlines recently for its rapidly growing energy demands, and particularly the surging electricity usage of data centers that enable the training and deployment of the latest generative AI models. But it’s not all bad news — some AI tools have the potential to reduce some forms of energy consumption and enable cleaner grids.One

3 Questions: How AI could optimize the power grid Read More »

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

MIT scientists investigate memorization risk in the age of clinical AI Read More »

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

MIT in the media: 2025 in review Read More »

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

Guided learning lets “untrainable” neural networks realize their potential Read More »

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

A new way to increase the capabilities of large language models Read More »