Prof. Stuart Madnick speaks with Wailin Wong and Cooper Katz McKim of Planet Money about the growing problem of data breaches in the U.S., noting how AI is feeding into the problem. “We've seen several examples of how cyber attacks have been greatly accelerated due to AI tools,” Madnick explains.
Prof. Steve Leeb and graduate student Daniel Monagle speak with Tech Briefs reporter Edward Brown about their work “designing an energy management interface between an energy harvesting source and a sensor load that will give the best possible results.” Monagle notes that in the future they hope to make the system “smaller so that it can fit in tight places like inside a motor terminal box. But beyond that we want to take advantage of AI tools to design techniques for minimizing the energy used by the system.”
Noman Bashir, a fellow with MIT’s Climate and Sustainability Consortium, speaks with Smithsonian Magazine reporter Amber X. Chen about the impact of AI data centers on the country’s electric grid and infrastructure. Bashir notes “that the industry’s environmental impacts can also be seen farther up the supply chain,” writes Chen. “The GPUs that power A.I. data centers are made with rare earth elements, the extraction of which Bashir notes is resource intensive and can cause environmental degradation.”
Vana, an MIT startup, is developing an app “that works like a wallet for personal data that can be used to train AI,” reports Megan Morrone for Axios. “Vana hopes people will use the app to control and pool their own data with others, shape how it’s used and share in the value it creates,” writes Morrone.
Writing for Nature, Prof. Danielle Wood makes the case that both public and commercial satellite missions are needed to understand and protect the environment. “Although commercial companies have much to offer, the public sector must still lead the design, operation and management of satellites, and remain committed to tracking changes on Earth comprehensively, openly and transparently,” Wood writes.
Noman Bashir, a fellow with MIT's Climate and Sustainability Consortium, speaks with AP reporter Caleigh Wells about how new AI data centers are impacting the country’s energy grid. “Since we are trying to build data centers at a pace where we cannot integrate more renewable energy resources into the grid, most of the new data centers are being powered by fossil fuels,” says Bashir.
Interesting Engineering reporter Saoirse Kerrigan spotlights a number of MIT research projects from the past decade. MIT has “long been a hub of innovation and ingenuity across multiple industries and disciplines,” writes Kerrigan. “Every year, the school’s best and brightest debut projects that push the boundaries of science and technology. From vehicles and furniture to exciting new breakthroughs in electricity generation, the school’s projects have tackled an impressive variety of subjects.”
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.”
A study by Prof. Noelle Selin has found that climate change will impact our ability to curb smoke and smog pollutants, reports Vivian La for WBUR. The researchers “used computer models to predict how air pollution will develop in the Eastern United States over the next few decades,” explains La. Selin underscored the importance of policies that reduce air pollution noting that: “what we’re doing to the atmosphere has impacts and it’s important not to roll these back.”
Wall Street Journal reporter Dominique Mosbergen spotlights how Prof. James Collins and his lab have built their “own algorithms to trawl chemical databases, such as those of existing pharmaceutical drugs, for potential antibacterial compounds.” Collins’ His lab is “also experimenting with using generative AI to design completely new molecules that could kill bacteria,” writes Mosbergen.
Researchers from MIT and other institutions have uncovered new pathways, along with identifying genes, that may contribute to the development of a new class of drugs to treat Alzheimer’s disease, reports John R. Ellement for The Boston Globe. “The drugs currently approved to treat Alzheimer’s have not been as successful as hoped,” Ellement explains. “Those drugs tend to target amyloid plaques in the brain, but the new research suggests other areas to target.”
Principal Research Scientist Kalyan Veeramachaneni speaks with WBUR On Point host Meghna Chakrabarti about the benefits and risks of training AI on synthetic data. “I think the AI that we have as of today and we are using is largely very small; I don't mean that as in size, but in the tasks that it can do,” says Veeramachaneni. “And as days go by, we are asking more and more of it… that requires us to provide more data, train more models that are much more efficient in reasoning, and can solve problems that we haven't thought of solving.”
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.”
Mohamed Elrefaie speaks with Automotive World reporter Will Girling about his work developing an open-source dataset of 8,000 car designs, including their aerodynamic characteristics, which could be used to develop novel car designs in a more efficient manner. “If an automaker wants to reduce drag and improve performance, it can guide the GenAI model to produce those specific designs,” Elrefaie explains. “The standard development cycle for a design using legacy tools can take anywhere from three to five years, as it requires collaboration between many specialized departments. With AI, you could validate up to 600 designs in just one or two minutes.”
Ars Technica reporter Jacek Krywko spotlights how MIT researchers have developed a new photonic chip that that can “compute the entire deep neural net, including both linear and non-linear operations, using photons.” Visiting scientist Saumil Bandyopadhyay '17, MEng '18, PhD '23 explains that: “We’re focused on a very specific metric here, which is latency. We aim for applications where what matters the most is how fast you can produce a solution. That’s why we are interested in systems where we’re able to do all the computations optically.”