A single photograph offers glimpses into the creator’s world — their interests and feelings about a subject or space. But what about creators behind the technologies that help to make those images possible?  MIT Department of Electrical Engineering and Computer Science Associate Professor Jonathan Ragan-Kelley is one such person, who has designed everything from tools for visual effects in movies to the Halide programming language that’s widely used in industry for photo editing and processing. As a researcher with the MIT-IBM Watson AI Lab and the Computer Science and Artificial Intellig ..read more

The recent ransomware attack on ChangeHealthcare, which severed the network connecting health care providers, pharmacies, and hospitals with health insurance companies, demonstrates just how disruptive supply chain attacks can be. In this case, it hindered the ability of those providing medical services to submit insurance claims and receive payments. This sort of attack and other forms of data theft are becoming increasingly common and often target large, multinational corporations through the small and mid-sized vendors in their corporate supply chains, enabling breaks in these enormous sys ..read more

Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions — essentially, high-level representations of complex concepts that skip less-important details — and thus sputter when asked to do more sophisticated tasks. Luckily, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have found a treasure trove of abstractions within na ..read more

The return of spring in the Northern Hemisphere touches off tornado season. A tornado's twisting funnel of dust and debris seems an unmistakable sight. But that sight can be obscured to radar, the tool of meteorologists. It's hard to know exactly when a tornado has formed, or even why. A new dataset could hold answers. It contains radar returns from thousands of tornadoes that have hit the United States in the past 10 years. Storms that spawned tornadoes are flanked by other severe storms, some with nearly identical conditions, that never did. MIT Lincoln Laboratory researchers who curated the ..read more

How can MIT’s community leverage generative AI to support learning and work on campus and beyond? At MIT’s Festival of Learning 2024, faculty and instructors, students, staff, and alumni exchanged perspectives about the digital tools and innovations they’re experimenting with in the classroom. Panelists agreed that generative AI should be used to scaffold — not replace — learning experiences. This annual event, co-sponsored by MIT Open Learning and the Office of the Vice Chancellor, celebrates teaching and learning innovations. When introducing new teaching and learning technologies, panelists ..read more

Julie Shah ’04, SM ’06, PhD ’11, the H.N. Slater Professor in Aeronautics and Astronautics, has been named the new head of the Department of Aeronautics and Astronautics (AeroAstro), effective May 1. “Julie brings an exceptional record of visionary and interdisciplinary leadership to this role. She has made substantial technical contributions in the field of robotics and AI, particularly as it relates to the future of work, and has bridged important gaps in the social, ethical, and economic implications of AI and computing,” says Anantha Chandrakasan, MIT’s chief innovation and strategy office ..read more

For nearly a decade, a team of MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have been seeking to uncover why certain images persist in a people's minds, while many others fade. To do this, they set out to map the spatio-temporal brain dynamics involved in recognizing a visual image. And now for the first time, scientists harnessed the combined strengths of magnetoencephalography (MEG), which captures the timing of brain activity, and functional magnetic resonance imaging (fMRI), which identifies active brain regions, to precisely determine when and where the ..read more

This article was updated on April 23 to reflect the promotion of Gosha Geogdzhayev from alternate to winner of the Gates Cambridge Scholarship. MIT seniors Gosha Geogdzhayev and Sadhana Lolla have won the prestigious Gates Cambridge Scholarship, which offers students an opportunity to pursue graduate study in the field of their choice at Cambridge University in the U.K. Established in 2000, Gates Cambridge offers full-cost post-graduate scholarships to outstanding applicants from countries outside of the U.K. The mission of Gates Cambridge is to build a global network of future leaders committ ..read more

Health-monitoring apps can help people manage chronic diseases or stay on track with fitness goals, using nothing more than a smartphone. However, these apps can be slow and energy-inefficient because the vast machine-learning models that power them must be shuttled between a smartphone and a central memory server. Engineers often speed things up using hardware that reduces the need to move so much data back and forth. While these machine-learning accelerators can streamline computation, they are susceptible to attackers who can steal secret information. To reduce this vulnerability, researche ..read more

To build AI systems that can collaborate effectively with humans, it helps to have a good model of human behavior to start with. But humans tend to behave suboptimally when making decisions. This irrationality, which is especially difficult to model, often boils down to computational constraints. A human can’t spend decades thinking about the ideal solution to a single problem. Researchers at MIT and the University of Washington developed a way to model the behavior of an agent, whether human or machine, that accounts for the unknown computational constraints that may hamper the agent’s proble ..read more