Electrical engineering and computer science (EECS)

MIT researchers have developed a machine-learning accelerator chip to make health-monitoring apps more secure, reports Aman Tripathi for Interesting Engineering. “The researchers subjected this new chip to intensive testing, simulating real-world hacking attempts, and the results were impressive,” explains Tripathi. “Even after millions of attempts, they were unable to recover any private information. In contrast, stealing data from an unprotected chip took only a few thousand samples.”

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.”

Doug Ricket '01, MEng '02 co-founded PayJoy, a startup that aims to “provide a fair and responsible entry point for individuals in emerging markets to enter the modern financial system, build credit, achieve economic freedom, and access digital connectivity,” reports Mary Ann Azevedo for TechCrunch. “PayJoy is applying a buy now, pay-as-you-go model to the estimated 3 billion adults globally who don’t have credit by allowing them to purchase smartphones and pay weekly for a 3- to 12-month period. The phones themselves are used as collateral for the loan,” explains Azevedo.

Prof. Roger Levy, Prof. Tracy Slatyer and Prof. Martin Wainwright are among the 2024 John Simon Guggenheim Foundation Fellowship recipients, reports Michael T. Nietzel for Forbes. “The new fellows represent 52 scholarly disciplines and artistic fields and are affiliated with 84 academic institutions,” writes Nietzel.

Prof. Roger Levy, Prof. Tracy Slatyer and Prof. Martin Wainwright have been awarded John Simon Guggenheim Foundation Fellowships, reports Mark Feeney for The Boston Globe. A Guggenheim fellowship “is one of the most sought-after honors in academe, the arts, and culture,” explains Feeney. “It helps underwrite a proposed art or scholarly project.”

Fast Company reporter AJ Hess spotlights “Slow Productivity: The Lost Art of Accomplishments Without Burnout,” a new book by Cal Newport SM '06, PhD '09. The book “traces the history of measuring workers’ output and the rise of knowledge workers’ stress and burnout,” explains Hess. “As an antidote, Newport proposes what some may argue is an oversimplified solution: simply do less.”

U.S. News & World Report reporter Cole Claybourn spotlights Amar Gopal Bose '51, SM '52 ScD '56, a former MIT faculty member, as one of fifteen famous Fulbright scholars. Bose, founder of Bose Corporation, “studied at the Massachusetts Institute of Technology on a full scholarship, earning his bachelor’s, master’s and doctoral degrees in electrical engineering,” writes Claybourn.

Researchers at MIT have found that large language models mimic intelligence using linear functions, reports Kyle Wiggers for TechCrunch. “Even though these models are really complicated, nonlinear functions that are trained on lots of data and are very hard to understand, there are sometimes really simple mechanisms working inside them,” writes Wiggers. 

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." 

Bloomer Tech, a health tech startup founded by Alicia Chong Rodriguez SM ‘17, SM ’18, is working to “address the gender gap in health care, which has led to less clinical trial representation and fewer resources to diagnose and treat women with various diseases,” reports Steph Solis for Axios. The startup is prepared “to launch a clinical trial for bras that could help detect heart irregularities and other conditions that can lead to heart disease,” writes Solis.

Harry Rein '15, MEng '16 and Chris Tinsley MBA '20 co-founded ShopMy, a marketing platform designed to connect content creators with brands and monetize their content, reports Laruen Forristal for TechCrunch. “ShopMy’s marketing platform equips creators with the tools they need to earn from their product recommendations, like building digital storefronts, accessing a catalog of millions of products, making commissionable links and chatting directly with companies via mobile app,” explains Forristal.

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.”

Prof. Mike Stonebraker co-founded DBOS, a serverless software platform, that aims to “put a database system at the bottom of the technology stack as close to the bare metal as possible where the operating system usually sits,” reports Ron Miller for TechCrunch. “Bare metal is a term used to describe the pure hardware layer where no software exists. Flipping the OS and the database is a bold and revolutionary idea,” explains Miller.

Prof. Thomas Malone speaks with Poets & Quants for Executives reporter Alison Damast about the executive education course he teaches with Prof. Daniela Rus that aims to provide senior-level managers with a better sense of how AI works. “We are certainly not trying to teach people to understand the details of how to write AI programs, though some of those in the course may know that already,” Malone says. “What we are trying to do is give them a sense of when it is easy and when it is hard to use AI technology at various times for different kinds of business applications.”

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.”