Computer science and technology

Maria Telleria ’08, SM’10, PhD ’13 speaks with Forbes contributor Stuart Anderson about her experience immigrating to the U.S. as a teenager, earning her PhD at MIT, and co-founding a company. “I don’t think I would have had these opportunities if I could not have come to the United States,” said Telleria. “I think it helped me grow by being exposed to two cultures. When you have had to think in two different ways, I think it makes you better understand other people and why they’re different. Coming to America has been an amazing opportunity.”

MIT was named to the number two spot in U.S. News & World Report’s ranking of the top universities, reports WBZ.

MIT has been ranked one of the top universities in the world by U.S. News & World Report, writes Emily Sweeney for The Boston Globe. Sweeney writes that the ranking “looked at approximately 1,500 colleges and universities and evaluated them on 19 measures of academic quality — this year changing its methodology to put more emphasis on social mobility and the outcomes of graduating students.”

Prof. Regina Barzilay speaks with The Economist about how AI can help advance medicine in areas such as uncovering new drugs. With AI, “the type of questions that we will be asking will be very different from what we’re asking today,” says Barzilay.

A new study by MIT researchers demonstrates how “machine-learning systems designed to spot someone breaking a policy rule—a dress code, for example—will be harsher or more lenient depending on minuscule-seeming differences in how humans annotated data that were used to train the system,” reports Ananya for Scientific American. “This is an important warning for a field where datasets are often used without close examination of labeling practices, and [it] underscores the need for caution in automated decision systems—particularly in contexts where compliance with societal rules is essential,” says Prof. Marzyeh Ghassemi.

Prof. Regina Barzilay writes for CNN about how AI can impact health care. “Smart AI algorithms, which are trained on large-scale medical data and equipped with powerful computing, can go beyond what is humanly possible, eliminate care delays and reduce the cost of health care,” writes Barzilay.

Forbes reporter Rob Toews spotlights Prof. Daniela Rus, director of CSAIL, and research affiliate Ramin Hasani and their work with liquid neural networks. “The ‘liquid’ in the name refers to the fact that the model’s weights are probabilistic rather than constant, allowing them to vary fluidly depending on the inputs the model is exposed to,” writes Toews.

Prof. Tod Machover speaks with Boston Globe reporter A.Z. Madonna about the restaging of his opera ‘VALIS’ at MIT, which features an AI-assisted musical instrument developed by Nina Masuelli ’23.  “In all my career, I’ve never seen anything change as fast as AI is changing right now, period,” said Machover. “So to figure out how to steer it towards something productive and useful is a really important question right now.”

Prof. Simon Johnson speaks with Freakonomics guest host Adam Davidson about his new book, economic history, and why new technologies impact people differently. “What do people creating technology, deploying technology— what exactly are they seeking to achieve? If they’re seeking to replace people, then that’s what they’re going to be doing,” says Johnson. “But if they’re seeking to make people individually more productive, more creative, enable them to design and carry out new tasks — let’s push the vision more in that direction. And that’s a naturally more inclusive version of the market economy. And I think we will get better outcomes for more people.”

Nature contributor David Chandler writes about the late Prof. Edward Fredkin and his impact on computer science and physics. “Fredkin took things even further, concluding that the whole Universe could actually be seen as a kind of computer,” explains Chandler. “In his view, it was a ‘cellular automaton’: a collection of computational bits, or cells, that can flip states according to a defined set of rules determined by the states of the cells around them. Over time, these simple rules can give rise to all the complexities of the cosmos — even life.”

Prof. Yoon Kim speaks with Popular Science reporter Charlotte Hu about how large language models like ChatGPT operate. “You can think of [chatbots] as algorithms with little knobs on them,” says Kim. “These knobs basically learn on data that you see out in the wild,” allowing the software to create “probabilities over the entire English vocab.”

Graduate students Martin Nisser and Marisa Gaetz co-founded Brave Behind Bars, a program designed to provide incarcerated individuals with coding and digital literacy skills to better prepare them for life after prison, reports Morgan Radford for MSNBC. Computers and coding skills “are really kind of paramount for fostering success in the modern workplace,” says Nisser.

Researchers from MIT and Harvard have explored astrocytes, a group of brain cells, from a computational perspective and developed a mathematical model that shows how they can be used to build a biological transformer, reports Kyle Wiggers for TechCrunch. “The brain is far superior to even the best artificial neural networks that we have developed, but we don’t really know exactly how the brain works,” says research staff member Dmitry Krotov. “There is scientific value in thinking about connections between biological hardware and large-scale artificial intelligence networks. This is neuroscience for AI and AI for neuroscience.

Prof. Mark Tegmark speaks with The Wall Street Journal reporter Emily Bobrow about the importance of companies and governments working together to mitigate the risks of new AI technologies. Tegmark “recommends the creation of something like a Food and Drug Administration for AI, which would force companies to prove their products are safe before releasing them to the public,” writes Bobrow.

Prof. D. Fox Harrell writes for The Guardian about the importance of ensuring AI systems are designed to “reflect the ethically positive culture we truly want.” Harrell emphasizes that: “We need to be aware of, and thoughtfully design, the cultural values that AI is based on. With care, we can build systems based on multiple worldviews – and address key ethical issues in design such as transparency and intelligibility."