Algorithms

A study by MIT researchers examining the carbon emissions of self-driving cars found that “the power required to run one billion driverless vehicles driving for one hour per day could consume as much energy as all existing data centers in the world,” reports Claire Brown for The New York Times. Graduate student Soumya Sudhakar explains that another big unknown is how autonomous vehicles could change the way people travel, adding to the uncertainty over the overall long-term emissions outlook for self-driving cars. 

Prof. Karrie Karahalios has been named to Fast Company’s 2025 “AI 20” list for her work empowering individuals and communities to take a stand against algorithmic overreach, reports Mark Sullivan for Fast Company. “As we build these systems, and they seem to be permeating our society right now, one of my big goals is not to ignore human intuition and not to have people give up agency,” says Karahalios. 

Prof. Caitlin Mueller has been named Innovator of the Year by Architectural Record for her work advancing a “vision for building design and construction that unites these disciplines with computation to create structure that are sustainable, high performing, and delightful,” reports Architectural Record. “Her group develops computational design and digital fabrication methods that integrate efficiency, performance, material circularity, and architectural expression,” Architectural Record notes. “This work spans robotic assembly of optimized trusses, fabrication of low-cost earthen and concrete systems, and algorithmic strategies for reusing salvaged wood and reassembled concrete parts.” 

Prof. Daniela Rus, director of CSAIL, speaks with CBS News reporter Tony Dokoupil about her work developing AI-powered robots. “AI and robots are tools,” says Rus. “They are tools created by the people, for the people. And like any other tools they’re not inherently good or bad; they are what we choose to do with them. And I believe we can choose to do extraordinary things.” 

Researchers at MIT have developed a new tool, called Meschers, that allows users to create detailed computer representations of mathematically impossible objects, reports Gayoung Lee for Gizmodo. “In addition to creating aesthetically quirky objects,” Lee explains, “Meschers could eventually assist in research across geometry, thermodynamics, and even art and architecture." 

Researchers at MIT have uncovered a variety of obstacles of AI in software development, reports Rob Wile for NBC News. They have found “the main obstacles come when AI programs are asked to develop code at scale, or with more complex logic,” writes Wile. 

Researchers at MIT have developed “a new imaging technique that could allow quality control robots in warehouses to peer into closed boxes,” reports Chris Young for Interesting Engineering. “Using this new technology, robots could peer into a cardboard shipping box and see that the handle of a mug is broken, for example,” explains Young. “This new method could revolutionize warehouse quality control and streamline the shipping and delivery process.”  

Forbes contributor Tanya Fileva spotlights how MIT CSAIL researchers have developed a system called Air-Guardian, an “AI-enabled copilot that monitors a pilot’s gaze and intervenes when their attention is lacking.” Fileva notes that “in tests, the system ‘reduced the risk level of flights and increased the success rate of navigating to target points’—demonstrating how AI copilots can enhance safety by assisting with real-time decision-making.”

Architect reporter Blaine Brownell spotlights Prof. Caitlin Mueller’s work repurposing “discarded tree forks from urban forestry projects [and] repurposing the nodes as structural joints in hybrid reclaimed-engineered wood constructions.” Mueller and her team have “developed computer programs to catalog 3D scans of the tree forks as well as determine the appropriate cuts for their intended structural applications,” explains Brownell. “An algorithm matches prepared tree forks to three-dimensional intersections in the intended structural framework, streamlining the design process.” 

Wall Street Journal reporter Angelina Torre spotlights “Letterlocking: The Hidden History of the Letter,” a new book by MIT Libraries Conservator Jana Dambrogio and King’s College London Senior Lecturer Daniel Smith that explores the history and art of “folding a letter so it serves as its own envelope.” The book “calls on scholars to ‘read the folds’ of written correspondence – to peer into the historical, social or personal circumstances that might not be explicitly stated,” explains Torre. 

Prof. Pulkit Agrawal speaks with Darian Woods and Geoff Brumfiel of NPR’s The Indicator from Planet Money about his work developing a simulator that can be used to train robots. “The power of simulation is that you can collect, you know, very large amounts of data,” explains Agrawal. “For example, in three hours', you know, worth of simulation, we can collect 100 days' worth of data.” 

Prof. Pulkit Agrawal speaks with NPR Short Wave host Regina Barber and science correspondent Geoff Brumfiel about his work developing a new technique that allows robots to train in simulations of scanned home environments. “The power of simulation is that we can collect very large amounts of data,” explains Agrawal. “For example, in three hours' worth of simulation, we can collect 100 days' worth of data.” 

[Originally in Spanish] MIT researchers have developed a new technique to educate robots by increasing human input, reports Uriel Bederman for TN Tecno.  “We can’t expect non-technical people to collect data and fine-tune a neural network model," explains graduate student Felix Yanwei Wang. "Consumers will expect the robot to work right out of the box, and if it doesn’t, they’ll want an intuitive way to customize it. That’s the challenge we’re addressing in this work."

Liquid AI, an MIT startup, is developing technology that “holds the same promise of writing, analyzing, and creating content as its rivals while using far less computing power,” reports Aaron Pressman for The Boston Globe. 

Researchers at MIT have developed a new AI model capable of assessing a patient’s risk of pancreatic cancer, reports Erez Meltzer for Forbes. “The model could potentially expand the group of patients who can benefit from early pancreatic cancer screening from 10% to 35%,” explains Meltzer. “These kinds of predictive capabilities open new avenues for preventive care.”