Researchers at MIT and elsewhere have developed a machine-learning model that can identify which drugs should not be taken together, reports Politico. “The researchers built a model to measure how intestinal tissue absorbed certain commonly used drugs,” they write. “They then trained a machine-learning algorithm based on their new data and existing drug databases, teaching the new algorithm to predict which drugs would interact with which transporter proteins.”
MIT researchers have developed a new technique “that could allow most large language models (LLMs) like ChatGPT to retain memory and boost performance,” reports Tony Ho Tran for the Daily Beast. “The process is called StreamingLLM and it allows for chatbots to perform optimally even after a conversation goes on for more than 4 million words,” explains Tran.
Prof. David Rand speaks with VOA News about the potential impact of adding watermarks to AI generated materials. “My concern is if you label as AI-generated, everything that’s AI-generated regardless of whether it’s misleading or not, people essentially are going to stop really paying attention to it,” says Rand.
Researchers at MIT and elsewhere have found that while AI systems could help doctors come to the right diagnosis more often, the diagnostic gains aren’t always distributed evenly, with more improvements tied to patients with lighter skin, report Daniel Payne, Erin Schumaker, and Ruth Reader for Politico. “AI could be a powerful tool to improve care and potentially offer providers a check on their blindspots," they write. "But that doesn’t mean AI will reduce bias. In fact, the study suggests, AI could cause greater disparities in care.”
Graduate student Lauren “Ren” Ramlan programmed Doom, an iD software video game, to run on a display made from E.coli cells, reports Andrew Paul for Popular Science. For the project to work, “Ramlan first grew cells within a 32×48 1-bit well plate, then connected the makeshift screen to a controller capable of processing and translating binary code into the ‘addition or omission of a repressor controlling the fluorescence of the cells,’” writes Paul. “Basically, Ramlan swapped a traditional screen’s tiny light diodes for glowing bacterial cells."
A more than $40 million investment to add advanced nano-fabrication equipment and capabilities to MIT.nano will significantly expand the center’s nanofabrication capabilities, reports Jon Chesto for The Boston Globe. The new equipment, which will also be available to scientists outside MIT, will allow “startups and students access to wafer-making equipment used by larger companies. These tools will allow its researchers to make prototypes of an array of microelectronic devices.”
Jared Sadoian ’10 speaks with Boston Globe reporter Kara Baskin about his work as director of operations for Cambridge Street Hospitality. “My day consists of email and spreadsheets, and budgeting and planning and analysis,” says Sadoian. “At the same time, it’s very firmly rooted in guest-facing hospitality that most readers might be more familiar with: talking to guests and taking reservations and making sure that folks are happy in the restaurants, and solving problems. Maybe it’s making a drink. This job is all-encompassing, and I love it for that reason, because I ran away from the office life.”
Researchers from MIT have developed liquid metal printing, a new technique that can be used to quickly 3D print large-scale objects such as furniture, reports Designboom. The researchers say this technique can enable 3D printing, “ten times faster than a comparable metal additive manufacturing process, and the process of melting the metal may be more efficient than some other methods, given that metal is also more accessible with the abundance of scraps that can be recycled,” writes Designboom.
MIT researchers have developed a 3D printing technique called liquid metal printing (LMP) that capable of printing large aluminum parts at least 10 times faster than a comparable metal additive manufacturing process, reports Brian Heater for TechCrunch. LMP “utilizes a bed of 100-micron glass beads to create a structure into which molten aluminum is deposited — a process not entirely dissimilar from injection molding,” explains Heater. “The beads are capable of standing up to the intense temperature, while allowing the heat to quickly dissipate as the metal solidifies.”
New York Times opinion writer Peter Coy spotlights the MIT Shaping the Future of Work Initiative, a new effort aimed at analyzing the forces that are eroding job quality for non-college workers and identifying ways to move the economy onto a more equitable trajectory. Nothing is “inexorable,” said Prof. Daron Acemoglu during the project’s kickoff event. “The answer in most cases is, AI will do whatever we choose it to do.”
Researchers from MIT and elsewhere have developed an AI model that is capable of identifying 3 ½ times more people who are at high-risk for developing pancreatic cancer than current standards, reports Felice J. Freyer for The Boston Globe. “This work has the potential to enlarge the group of pancreatic cancer patients who can benefit from screening from 10 percent to 35 percent,” explains Freyer. “The group hopes its model will eventually help detect risk of other hard-to-find cancers, like ovarian.”
In a new study examining the potential impact of AI on jobs that employ computer vision, MIT researchers found, “a vast majority of jobs previously identified as vulnerable to AI are not economically beneficial for employers to automate at this time,” reports Catherine Thorbecke for CNN. “In many cases, humans are the more cost-effective way, and a more economically attractive way, to do work right now,” says Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL. “What we’re seeing is that while there is a lot of potential for AI to replace tasks, it’s not going to happen immediately.”
A new working paper by MIT researchers finds that artificial intelligence is not currently a cost-effective replacement in jobs where computer vision is employed, reports Saritha Rai for Bloomberg. “Our study examines the usage of computer vision across the economy, examining its applicability to each occupation across nearly every industry and sector,” explains Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL. “We show that there will be more automation in retail and healthcare, and less in areas like construction, mining or real estate.”
Undark reporter Sarah Scoles spotlights Matt Jacobs '02 for his work with many California SAR (search and rescue) teams. “In 2015, Jacobs published a paper that took another look at the incident information in the large ISRID database (International Search & Rescue Incident Database),” writes Scoles. “Taking the largest ISRID categories – hikers, hunters, and gatherers – he tried to see how the terrain affected their choices.”
A new working paper by MIT researchers focuses on whether human work, including vision tasks, are worth replacing with AI computer vision, reports Jeremy Hsu for New Scientist. “There are lots of tasks that you can imagine AI applying to, but actually cost-wise you just wouldn’t want to do it,” says Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL.