Computer Science and Artificial Intelligence Laboratory (CSAIL)

Fortune reporter Jeremy Kahn spotlights a study co-authored by Prof. Marzyeh Ghassemi exploring issues associated with “explainable” AI systems that are being applied in fields such as healthcare, finance and government. The researchers explain that those using such systems “might have misunderstood the capabilities of contemporary explainability techniques—they can produce broad descriptions of how the AI system works in a general sense but, for individual decisions, the explanations are unreliable or, in some instances, only offer superficial levels of explanation.”

In an article for The New York Times exploring whether humans are the only species able to comprehend geometry, Siobhan Roberts spotlights Prof. Josh Tenenbaum’s approach to exploring how humans can extract so much information from minimal data, time, and energy. “Instead of being inspired by simple mathematical ideas of what a neuron does, it’s inspired by simple mathematical ideas of what thinking is,” says Tenenbaum.

MIT researchers have created a new computer algorithm that has allowed the mini cheetah to maximize its speed across varying types of terrain, reports Shi En Kim for Popular Science. “What we are interested in is, given the robotic hardware, how fast can [a robot] go?” says Prof. Pulkit Agrawal. “We didn’t want to constrain the robot in arbitrary ways.”

MIT researchers have used a new reinforcement learning system to teach robots how to acclimate to complex landscapes at high speeds, reports Emmett Smith for Mashable. “After hours of simulation training, MIT’s mini-cheetah robot broke a record with its fastest run yet,” writes Smith.

CSAIL researchers developed a new machine learning system to teach the MIT mini cheetah to run, reports James Vincent for The Verge. “Using reinforcement learning, they were able to achieve a new top-speed for the robot of 3.9m/s, or roughly 8.7mph,” writes Vincent.

Gizmodo reporter Andrew Liszewski writes that CSAIL researchers developed a new AI system to teach the MIT mini cheetah how to adapt its gait, allowing it to learn to run. Using AI and simulations, “in just three hours’ time, the robot experienced 100 days worth of virtual adventures over a diverse variety of terrains,” writes Liszewski, “and learned countless new techniques for modifying its gait so that it can still effectively loco-mote from point A to point B no matter what might be underfoot.”

Popular Science reporter Tatyana Woodall writes that CSAIL researchers have developed electromagnetic bot blocks that can reconfigure into various shapes and could potentially help astronauts build in space. “The electromagnetic lining of the 3D printed frames allows cubes to seamlessly attract, repel, or even turn themselves off,” writes Wood. “One cube takes a little over an hour to make, and only costs 60 cents.”

STAT has named Noubar Afeyan ’87, Cornelia Bargmann PhD ’87, Prof. Regina Barzilay and Prof. Sangeeta N. Bhatia to their list of trailblazing researchers working in the life sciences. “Many of the STATUS List are well-known as change makers; others are largely unheralded heroes. But all have compelling stories to tell,” writes STAT.

A team of scientists from MIT and Facebook have created a new object tagging system called InfraredTags, reports Charlotte Hu for Popular Science. “InfraredTags uses infrared light-based barcodes and QR codes that embedded permanently into the bodies of 3D printed objects,” reports Hu.  

STAT reporters Katie Palmer and Casey Ross spotlight how Prof. Regina Barzilay has developed an AI tool called Mirai that can identify early signs of breast cancer from mammograms. “Mirai’s predictions were rolled into a screening tool called Tempo, which resulted in earlier detection compared to a standard annual screening,” writes Palmer and Ross.

In an article for The Wall Street Journal about next generation technologies that can create and quantify personal health data, Laura Cooper spotlights Prof. Dina Katabi’s work developing a noninvasive device that sits in a person’s home and can help track breathing, heart rate, movement, gait, time in bed and the length and quality of sleep. The device “could be used in the homes of seniors and others to help detect early signs of serious medical conditions, and as an alternative to wearables,” writes Cooper.

An international team of scholars, including MIT researchers, has published a new study exploring the history and use of letterlocking, reports William J. Broad for The New York Times. The researchers note that they hope their work prompts “novel kinds of archival research, and allows even very well-known artefacts to be examined anew.”

Prof. Regina Barzilay speaks with Good Morning America about her work developing a new AI tool that could “revolutionize early breast cancer detection” by identifying patients at high risk of developing the disease. “If this technology is used in a uniform way,” says Barzilay, “we can identify early who are high-risk patients and intervene.”

Washington Post reporter Steve Zeitchik spotlights Prof. Regina Barzilay and graduate student Adam Yala’s work developing a new AI system, called Mirai, that could transform how breast cancer is diagnosed, “an innovation that could seriously disrupt how we think about the disease.” Zeitchik writes: “Mirai could transform how mammograms are used, open up a whole new world of testing and prevention, allow patients to avoid aggressive treatments and even save the lives of countless people who get breast cancer.”

Prof. Erik Demaine speaks with Popular Mechanics reporter Sarah Wells about the surprisingly complex math behind wrapping a present. "If [the wrapping] is a square piece of paper, we know the best [way]," Demaine says. "[But] what if I gave you an eight-and-a-half by eleven rectangle? The answer turns out to be really complicated…And again, this is just wrapping a cube. If you're wrapping a general box, it's going to get even messier. Here, we don't even know the right answer."