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Researchers at MIT have developed a new method for “training home robots in simulation,” reports Brain Heater for TechCrunch. “Simulation has become a bedrock element of robot training in recent decades,” explains Heater. “It allows robots to try and fail at tasks thousands — or even millions — of times in the same amount of time it would take to do it once in the real world.”
Prof. Armando Solar-Lezama speaks with The Wall Street Journal reporter Isabelle Bousquette about large language models (LLMs) in academia. Instead of building LLMs from scratch, Solar-Lezama suggests “students and researchers are focused on developing applications and even creating synthetic data that could be used to train LLMs,” writes Bousquette.
MIT scientists have created RoboGrocery, a robot prototype that can pack a bag of standard groceries, reports Mack DeGeurin for Popular Science. Using an RGB-D camera equipped with computer vision technology and grippers with pressure sensors, RoboGrocery’s “ability to assess items, determine their delicacy, and pack efficiently without causing damage sets it apart from conventional robotic packers,” explains Prof. Daniela Rus.
New York Times reporter Siobhan Roberts highlights the various MIT faculty and students who have contributed to the “serious recreational mathematics” behind the Rubik’s Cube phenomenon. Various mathematicians, including Prof. Erik Demaine, organized a two-day special session to celebrate the 50th anniversary of the Rubik’s Cube.
Using multimodal sensing and a soft robotic manipulator, MIT scientists have developed an automated system, called RoboGrocery, that can pack groceries of different sizes and weights, reports Brian Heater for TechCrunch. Heater explains that as the soft robotic gripper touches an item, “pressure sensors in the fingers determine that they are, in fact, delicate and therefore should not go at the bottom of the bag — something many of us no doubt learned the hard way. Next, it notes that the soup can is a more rigid structure and sticks it in the bottom of the bag.”
Prof. Yoon Kim speaks with Vox reporter Adam Clark Estes on how to address hallucinations and misinformation within large language models. “I don't think we'll ever be at a stage where we can guarantee that hallucinations won't exist,” says Kim. “But I think there's been a lot of advancements in reducing these hallucinations, and I think we'll get to a point where they'll become good enough to use.”
Researchers from MIT have developed RoboGrocery, a soft robotic system that “can determine how to pack a grocery item based on its weight, size and shape without causing damage to the item,” reports Jennifer Kite-Powell for Forbes. “This is more than just automation—it's a paradigm shift that enhances precision, reduces waste and adapts seamlessly to the diverse needs of modern retail logistics,” says Prof. Daniela Rus, director of CSAIL.
MIT scientists have developed a “four-fingered robotic hand which is capable of rotating balls and toys in any direction and orientation,” reports Maisie Lillywhite for BBC News. “The improvement in dexterity could have significant implications for automating tasks such as handling goods for supermarkets or sorting through waste for recycling,” Lillywhite writes.
Prof. Dylan Hadfield-Menell is interviewed by Wired’s Will Knight about CriticGPT, a new tool developed by OpenAI that will assist human trainers in developing AI. “It might lead to big jumps in individual capabilities, and it might be a stepping stone towards sort of more effective feedback in the long run,” Hadfield-Menell says.
Research Scientist Neil Thompson speaks with New York Times reporter Hank Sanders about the economic and social impact of AI technology in the fast-food industry. Thompson explains that “voice A.I. is inaccurate often enough that it requires some level of human oversight, which decreases cost savings,” writes Hank.
MIT researchers have improved upon the diffusion models used in AI image generation, reports Alok Jha for The Economist. Working with electrically charged particles, the team created “Poisson flow generative models,” which “generate images of equal or better quality than state-of-the-art diffusion models, while being less error-prone and requiring between ten and 20 times fewer computational steps,” Jha explains.
Prof. Regina Barzilay spoke at The Futurist Summit: The Age of AI – an event hosted by The Washington Post – about the influence of AI in medicine. “When we're thinking today how many years it takes to bring new technologies [to market], sometimes it's decades if we’re thinking about drugs, and very, very slow,” Barzilay explains. “With AI technologies, you've seen how fast the technology that you're using today is changing.”
MIT researchers used tools of computational complexity and mathematical concepts to prove that no analysis of the Super Mario Bros video game level “can say for sure whether or not it can ever be completed,” reports Matthew Sparkes for New Scientist. “The idea is that you’ll be able to solve this Mario level only if this particular computation will terminate, and we know that there’s no way to determine that, and so there’s no way to determine whether you can solve the level,” says Prof. Erik Demaine.
Prof. Regina Barzilay joins The Economist’s “Babbage” podcast to discuss how artificial intelligence could enable health care providers to understand and treat diseases in new ways. Host Alok Jha notes that Barzilay is determined to “overcome those challenges that are standing in the way of getting AI models to become useful in health care.” Barzilay explains: “I think we really need to change our mindset and think how we can solve the many problems for which human experts were unable to find a way forward.”
On NPR’s Short Wave, climate correspondent Lauren Sommer reports on MIT researchers using artificial intelligence to decode the secret language of sperm whales. Prof. Daniela Rus says, “it really turned out that sperm whale communication was indeed not random or simplistic but rather structured in a very complex, combinatorial manner.”