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Regina Barzilay (left) and James Collins are the recipients of this year’s 2026 Pritzker Prize for AI in Science Research Excellence, which is jointly awarded by the University of Chicago and Caltech (Credits: Photos: Max Rousseau (Barzilay) and M. Scott Brauer (Collins)).
CSAIL article

Regina Barzilay, MIT’s School of Engineering Distinguished Professor of AI and Health, and James Collins, MIT’s Termeer Professor of Medical Engineering and Science, are the recipients of the 2026 Pritzker Prize for AI in Science Research Excellence. 

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CSAIL article

As a theoretical cryptographer, Kalai deals with questions like: how do you prove you know something without revealing what it is? What does it mean to know something at all? How can we verify AI answers are good, not just correct? And, in a world increasingly run by systems we don't fully understand, what do we owe each other in the name of safety? 

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An MRI scan of a fetal brain (outlined in yellow) in the sagittal position. E(3)-Pose is a model that helps track movement in an MRI of the fetus’s brain. The model could help clinicians make earlier and more accurate diagnoses of developmental anomalies (Credits: Courtesy of the MIT Jameel Clinic and the researchers).
CSAIL article

Despite millions of years of evolution, the development of the human fetus remains a complex process that is vulnerable to genetic, environmental, and metabolic disruptions. These disruptions could result in developmental abnormalities, starting with one of the first organs to begin developing in the fetus that continues to develop after birth: the brain.

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McGovern Institute researchers show that it's possible for an artificial neural network to build its own learning machinery (Credits: iStock)
CSAIL article

As artificial intelligence becomes more and more powerful, its ability to handle human-like tasks is undeniable. Artificial neural networks can learn to recognize images, use language, or write computer code. Like the brain’s circuits, they reorganize themselves as they learn, adjusting the strengths of their connections to improve their performance.

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Please join this TechTalk from Google, a CSAIL Alliances member

The rapid evolution of the optical layer has profoundly shaped and differentiated compute infrastructure. Optical interconnects have been crucial in supporting the immense growth of networking bandwidth for machine learning, successfully scaling with electrical I/O while simultaneously improving power efficiency and cost. Consequently, machine learning networks have become the primary driver for business and technological advancements in fiber optic communications.