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.”
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.”
Writing for Financial Times, economist Ann Harrison spotlights research by Prof. Daron Acemoglu, Pascual Restrepo PhD '16 and Prof. David Autor, that explores the impact of automation on jobs in the United States. Acemoglu and Restrepo have “calculated that each additional robot in the US eliminates 3.3 workers” and that “most of the increase in inequality is due to workers who perform routine tasks being hit by automation,” writes Harrison.
Javier Ramos '12, SM '14, co-founder of InkBit, and his colleagues have developed a, “3D inkjet printer that uses contact-free computer vision feedback to print hybrid objects with a broad range of new functional chemistries,” reports Ed Brown for Tech Briefs. “Our vision for Inkbit is to reshape how the world thinks about production, from design to execution and make our technology readily available,” says Ramos. “The big opportunity with 3D printing is how to disrupt the world of manufacturing — that’s what we're focused on.”
Writing for Wired, research scientist Kate Darling highlights the importance of addressing the fundamentally human behaviors that have been incorporated into AI chatbots. “Research in human-computer and human-robot interaction shows that we love to anthropomorphize—attribute humanlike qualities, behaviors, and emotions to—the nonhuman agents we interact with, especially if they mimic cues we recognize,” writes Darling. “And, thanks to recent advances in conversational AI, our machines are suddenly very skilled at one of those cues: language.”
Prof. Julie Shah speaks with Wall Street Journal reporter Lauren Weber about the implementation of automation in the work force. According to Shah, “when companies adopt automation successfully, they end up adding workers as they become more productive and fill more orders,” writes Weber. “And machines’ lack of flexibility has often resulted in what Shah calls ‘zero-sum automation,’ where gains in productivity are canceled out by the need for people to fix or reprogram robots and compensate for their drawbacks.”
Researchers from MIT have developed, “nanoelectronics they hope can one day enter the brain and treat conditions like Alzheimer’s by monitoring some of these brain patterns,” reports Elizabeth Hlavinka for Salon. “Their device, which they call Cell Rover, serves as a sort of antenna that can help external devices monitor cells.”
Researchers from MIT and elsewhere have developed a new AI technique for teaching robots to pack items into a limited space while adhering to a range of constraints, reports Nick Hilden for Scientific American. “We want to have a learning-based method to solve constraints quickly because learning-based [AI] will solve faster, compared to traditional methods,” says graduate student Zhutian “Skye” Yang.
Four faculty members from across MIT - Professors Song Han, Simon Johnson, Yoon Kim and Rosalind Picard - speak with Curiosity Stream about the opportunities and risks posed by the rapid advancements in the field of AI. “We do want to think about which human capabilities we treasure,” says Picard. She adds that during the Covid-19 pandemic, “we saw a lot of loss of people's ability to communicate with one another face-to-face when their world moved online. I think we need to be thoughtful and intentional about what we're building with the technology and whether it's diminishing who we are or enhancing it.”
Prof. Russ Tedrake and Max Bajracharya '21 MEng '21 speak with TechCrunch reporter Brian Heater about the impact of generative AI on the future of robotics. “Generative AI has the potential to bring revolutionary new capabilities to robotics,” says Tedrake. “Not only are we able to communicate with robots in natural language, but connecting to internet-scale language and image data is giving robots a much more robust understanding and reasoning about the world.”
Researchers from MIT and elsewhere have developed a new 3D printing process that “allows users to create more elastic materials along with rigid ones using slow-curing polymers,” reports Tony Ho Tran for the Daily Beast. The researchers used the system to create a, “3D printed hand complete with bones, ligaments, and tendons. The new process also utilizes a laser sensor array developed by researchers at MIT that allows the printer to actually ‘see’ what it’s creating as it creates it.”
Prof. Arnaud Costinot and Prof. Iván Werning speak with TechCrunch reporter Brian Heater about their research examining the potential impact of a robot tax on automation and jobs. “The potential wages people can earn may become more unequal with new technologies and the idea is that the tax can mitigate these effects,” Costinot and Werning explain. “In a sense, one can think of this as pre-distribution, affecting earnings before taxes, instead of redistribution.”