On Vassar Street, in the heart of MIT’s campus, the MIT Stephen A. Schwarzman College of Computing recently opened the doors to its new headquarters in Building 45. The building’s central location and welcoming design will help form a new cluster of connectivity at MIT and enable the space to have a multifaceted role.  “The college has a broad mandate for computing across MIT,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “The building is designed to be the computing crossroad ..read more

For those in need of one, an organ transplant is a matter of life and death.  Every year, the medical procedure gives thousands of people with advanced or end-stage diseases extended life. This “second chance” is heavily dependent on the availability, compatibility, and proximity of a precious resource that can’t be simply bought, grown, or manufactured — at least not yet. Instead, organs must be given — cut from one body and implanted into another. And because living organ donation is only viable in certain cases, many organs are only available for donation after the donor’s death. Unsur ..read more

In biomedicine, segmentation involves annotating pixels from an important structure in a medical image, like an organ or cell. Artificial intelligence models can help clinicians by highlighting pixels that may show signs of a certain disease or anomaly. However, these models typically only provide one answer, while the problem of medical image segmentation is often far from black and white. Five expert human annotators might provide five different segmentations, perhaps disagreeing on the existence or extent of the borders of a nodule in a lung CT image. “Having options can help in decision-ma ..read more

A user could ask ChatGPT to write a computer program or summarize an article, and the AI chatbot would likely be able to generate useful code or write a cogent synopsis. However, someone could also ask for instructions to build a bomb, and the chatbot might be able to provide those, too. To prevent this and other safety issues, companies that build large language models typically safeguard them using a process called red-teaming. Teams of human testers write prompts aimed at triggering unsafe or toxic text from the model being tested. These prompts are used to teach the chatbot to avoid such r ..read more

Since the 1970s, modern antibiotic discovery has been experiencing a lull. Now the World Health Organization has declared the antimicrobial resistance crisis as one of the top 10 global public health threats.  When an infection is treated repeatedly, clinicians run the risk of bacteria becoming resistant to the antibiotics. But why would an infection return after proper antibiotic treatment? One well-documented possibility is that the bacteria are becoming metabolically inert, escaping detection of traditional antibiotics that only respond to metabolic activity. When the danger has passed ..read more

Without a map, it can be just about impossible to know not just where you are, but where you’re going, and that’s especially true when it comes to materials properties. For decades, scientists have understood that while bulk materials behave in certain ways, those rules can break down for materials at the micro- and nano-scales, and often in surprising ways. One of those surprises was the finding that, for some materials, applying even modest strains — a concept known as elastic strain engineering — on materials can dramatically improve certain properties, provided those strains stay elastic a ..read more

Last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart issued a call for papers to “articulate effective roadmaps, policy recommendations, and calls for action across the broad domain of generative AI.” The response to the call far exceeded expectations with 75 proposals submitted. Of those, 27 proposals were selected for seed funding. In light of this enthusiastic response, Kornbluth and Barnhart announced a second call for proposals this fall. “The groundswell of interest and the caliber of the ideas overall made clear that a second round was in order,” they said in their em ..read more

Large language models, such as those that power popular artificial intelligence chatbots like ChatGPT, are incredibly complex. Even though these models are being used as tools in many areas, such as customer support, code generation, and language translation, scientists still don’t fully grasp how they work. In an effort to better understand what is going on under the hood, researchers at MIT and elsewhere studied the mechanisms at work when these enormous machine-learning models retrieve stored knowledge. They found a surprising result: Large language models (LLMs) often use a very simple lin ..read more

From wiping up spills to serving up food, robots are being taught to carry out increasingly complicated household tasks. Many such home-bot trainees are learning through imitation; they are programmed to copy the motions that a human physically guides them through. It turns out that robots are excellent mimics. But unless engineers also program them to adjust to every possible bump and nudge, robots don’t necessarily know how to handle these situations, short of starting their task from the top. Now MIT engineers are aiming to give robots a bit of common sense when faced with situations that p ..read more

In our current age of artificial intelligence, computers can generate their own “art” by way of diffusion models, iteratively adding structure to a noisy initial state until a clear image or video emerges. Diffusion models have suddenly grabbed a seat at everyone’s table: Enter a few words and experience instantaneous, dopamine-spiking dreamscapes at the intersection of reality and fantasy. Behind the scenes, it involves a complex, time-intensive process requiring numerous iterations for the algorithm to perfect the image. MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) res ..read more