Reporting in Portuguese, Correio Braziliense highlights researchers at MIT who have developed a new technique that uses light stimuli to benefit people with paralysis or amputations. “Our work could help bring the use of optogenetics closer to humans in the realm of neuroprosthetics that control paralyzed muscles and other functions of the peripheral nervous system,” says graduate student Guillermo Herrera-Arcos.
Researchers at CSAIL have created three “libraries of abstraction” – a collection of abstractions within natural language that highlight the importance of everyday words in providing context and better reasoning for large language models, reports Darren Orf for Popular Mechanics. “The researchers focused on household tasks and command-based video games, and developed a language model that proposes abstractions from a dataset,” explains Orf. “When implemented with existing LLM platforms, such as GPT-4, AI actions like ‘placing chilled wine in a cabinet' or ‘craft a bed’ (in the Minecraft sense) saw a big increase in task accuracy at 59 to 89 percent, respectively.”
Nature reporter Andrew Robinson reviews “The Heart and the Chip,” a new book by Prof. Daniela Rus and science writer Gregory Mone. The book “focuses on combining human and robotic strengths to pair ‘the heart and the chip’ in three interlinked fields: robotics, artificial intelligence and machine learning,” explains Robinson.
MIT researchers have developed a wearable backpack with spider-like limbs to help astronauts maintain stability in space, reports Jess Thomson for Newsweek. The new technology, called Supernumerary Robotic Limbs (SuperLimbs), “could be crucial in future missions to the moon, where gravity is only a sixth of that on Earth and astronauts may struggle to clamber up again after a fall due to their unwieldy space suits,” explains Thomson.
Researchers at MIT have developed SuperLimbs, a pair of wearable robotic limbs that “can physically support an astronaut and lift them back on their feet after a fall,” reports Brain Heater for TechCrunch. “The system, which is still in the prototype phase, responds directly to the wearer’s feedback,” writes Heater. “When sitting or lying down, it offers a constructive support to help them get back up while expending less energy — every extra bit helps in a situation like this.”
MIT researchers have developed a new procedure that uses game theory to improve the accuracy and consistency of large language models (LLMs), reports Steve Nadis for Quanta Magazine. “The new work, which uses games to improve AI, stands in contrast to past approaches, which measured an AI program’s success via its mastery of games,” explains Nadis.
Writing for Forbes, Prof. Christian Catalini makes the case that when it comes to today’s digital infrastructure, from AI and robotics to financial services and digital marketplaces, “if the United States wants to continue to lead, it needs to create the right conditions for competition to thrive. Like in the early days of the internet, this starts with policymakers embracing and nurturing a novel architecture based on open protocols.”
Scientific American reporter Riis Williams explores how MIT researchers created “smart gloves” that have tactile sensors woven into the fabric to help teach piano and make other hands-on activities easier. “Hand-based movements like piano playing are normally really subjective and difficult to record and transfer,” explains graduate student Yiyue Luo. “But with these gloves we are actually able to track one person’s touch experience and share it with another person to improve their tactile learning process.”
MIT researchers have developed a new type of spring-like device that uses a flexible element to help power biohybrid robots, reports Brian Heater for TechCrunch. “The muscle fiber/flexure system can be applied to various kinds of robots in different sizes,” Heater writes, adding that the researchers are, “focused on creating extremely small robots that could one day operate inside the body to perform minimally invasive procedures.”
A number of MIT faculty and alumni – including Prof. Daniela Rus, Prof. Regina Barzilay, Research Affiliate Haddad Habib, Research Scientist Lex Fridman, Marc Raibert PhD '77, former Postdoc Rana El Kaliouby and Ray Kurzweil '70 – have been named key figures “at the forefront of Boston’s AI revolution,” reports Wyndham Lewis for Boston Magazine. These researchers are “driving progress and reshaping the way we live,” writes Lewis.
MIT researchers have developed a new technique that uses a large language model to allow robots to self-correct after making a mistake, reports Brian Heater for TechCrunch. “Researchers behind the study note that while imitation learning (learning to do a task through observation) is popular in the world of home robotics, it often can’t account for the countless small environmental variations that can interfere with regular operation, thus requiring a system to restart from square one,” writes Heater. “The new research addresses this, in part, by breaking demonstrations into smaller subsets."
Prof. Pulkit Agrawal and graduate student Gabriel Margolis speak with The Economist’s Babbage podcast about the simulation research and technology used in developing intelligent machines. “Simulation is a digital twin of reality,” says Agrawal. “But simulation still doesn’t have data, it is a digital twin of the environment. So, what we do is something called reinforcement learning which is learning by trial and error which means that we can try out many different combinations.”
Reflex Robotics, a startup co-founded by several MIT alumni, has developed a remotely-operated humanoid robot capable of handling tasks such as grabbing an item off a shelf, reports Brian Heater for TechCrunch. The robot’s hardware “is an in-house design, featuring a ‘torso’ mounted to a base that allows the arms and sensors to dynamically move up and down,” explains Heater. “It makes for a surprisingly dexterous robot that can access shelves at a variety of heights, while maneuvering tight spaces. The system has a wheeled base, which is perfectly effective for navigating these kinds of layouts.”
Prof. Daniela Rus, director of CSAIL, speaks with The Economist’s Babbage podcast about the history and future of artificial neural networks and their role in large language models. “The early artificial neuron was a very simple mathematical model,” says Rus. “The computation was discrete and very simple, essentially a step function. You’re either above or below a value.”
Prof. Daniela Rus, director of CSAIL, speaks with Boston Globe reporter Evan Sellinger about her new book, “The Heart and the Chip: Our Bright Future With Robots,” in which she makes the case that in the future robots and humans will be able to team up to create a better world. “I want to highlight that machines don’t have to compete with humans, because we each have different strengths. Humans have wisdom. Machines have speed, can process large numbers, and can do many dull, dirty, and dangerous tasks,” Rus explains. “I see robots as helpers for our jobs. They’ll take on the routine, repetitive tasks, ensuring human workers focus on more complex and meaningful work.”