In a video for CNN, graduate student Alex Kachkine explains his work developing a method using AI to create a reversible polymer film that could be used to restore damaged oil paintings, making the process faster than manual restoration. Kachkine explains that he hopes his work helps “get more paintings out of storage and into public view as there are many paintings that are damaged that I would love to see and it’s a real shame that there aren’t the resources necessary to restore them.”
Graduate student Alex Kachkine speaks with New York Times reporter Ephrat Livni about his work creating a new AI technique for restoring paintings, and how his research on microchips helped inspire the development. Microchips “require very high degrees of precision,” Kachkine explains. “And it turns out a lot of the techniques we use to achieve that level of precision are applicable to art restoration.” Kachkine adds that he hopes conservators will be able to “leverage the benefits” of the techniques he gleaned from engineering to preserve “really valuable cultural heritage.”
Writing for The Guardian, Prof. Carlo Ratti highlights his work using “AI to compare footage of public spaces from the 1970s with recent video” from the same locations in Boston, New York and Philadelphia. “The findings are striking: people walk faster, linger less, and are less likely to meet up,” explains Ratti. “By using AI to study urban public spaces, we can gather data, pick out patterns and test new designs that could help us rethink, for our time, our modern versions of the agora– the market and main public gathering place of Athens.”
Prof. Philip Isola speaks with Fast Company reporter Victor Dey about the impact and use of agentic AI. “In some domains we truly have automatic verification that we can trust, like theorem proving in formal systems. In other domains, human judgment is still crucial,” says Isola. “If we use an AI as the critic for self-improvement, and if the AI is wrong, the system could go off the rails.”
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."
A study by researchers at MIT has found that “pedestrians are walking 15 percent faster and stopping to linger 14 percent less than they used to,” reports Rima Sabina Aouf for Dezeen. “Using computer vision and artificial intelligence to analyze videos of four public spaces across three American cities, the study found that walking speeds rose notably between 1980 and 2010, while instances of people lingering or interacting with others fell,” writes Aouf.
Researchers at MIT have found that “pedestrians in three major northeastern U.S. cities – Boston, New York and Philadelphia —are moving 15 percent faster than they did in 1980,” reports Lucy Notarantonio for Newsweek. Notarantonio explains that: “The researchers hope their work will inform how cities design and redesign public areas — especially at a time when digital polarization is reshaping how people connect in real life.”
Graduate student Alex Kachkine has developed a new technique that “uses AI-generated polymer films to physically restore damaged paintings in hours,” reports Benj Edwards for Ars Technica. “Kachkine's method works by printing a transparent ‘mask’ containing thousands of precisely color-matched regions that conservators can apply directly to an original artwork,” explains Edwards. “Unlike traditional restoration, which permanently alters the painting, these masks can reportedly be removed whenever needed. So it's a reversible process that does not permanently change a painting.”
Guardian reporter Ian Sample highlights how graduate student Alex Kachkine has developed a new approach to restoring age-damaged artwork in hours. “The technique draws on artificial intelligence and other computer tools to create a digital reconstruction of the damaged painting,” explains Sample. “This is then printed on to a transparent polymer sheet that is carefully laid over the work.”
Graduate student Alex Kachkine speaks with Nature reporter Amanda Heidt about his work developing a new restoration method for restoring damaged artwork. The method uses “digital tools to create a ‘mask’ of pigments that can be printed and varnished onto damaged paintings,” explains Heidt. The method “reduces both the cost and time associated with art restoration and could one day give new life to many of the paintings held in institutional collections — perhaps as many as 70% — that remain hidden from public view owing to damage.”
Nature spotlights graduate student Alex Kachkine – an engineer, art collector and art conservator – on his quest to develop a new AI-powered, art restoration method, reports Geoff Marsh for Nature. “My hope is that conservators around the planet will be able to use these techniques to restore paintings that have never been seen by the general public,” says Kachkine. “Many institutions have paintings that arrived at them a century ago, have never been shown because they are so damaged and there are no resources to restore them. And hopefully this technique means we will be able to see more of those publicly.”
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.”
Researchers at MIT have developed “Clio,” a new technique that “enables robots to make intuitive, task-relevant decisions,” reports Jennifer Kite-Powell for Forbes. The team’s new approach allows “a robot to quickly map a scene and identify the items they need to complete a given set of tasks,” writes Kite-Powell.
Researchers at MIT have developed a new method that “enables robots to intuitively identify relevant areas of a scene based on specific tasks,” reports Baba Tamim for Interesting Engineering. “The tech adopts a distinctive strategy to make robots effective and efficient at sorting a cluttered environment, such as finding a specific brand of mustard on a messy kitchen counter,” explains Tamim.