Artificial intelligence

Researchers at MIT and elsewhere have used artificial intelligence to develop a new antibiotic to combat Acinetobacter baumannii, a challenging bacteria known to become resistant to antibiotics, reports Hannah Kuchler for the Financial Times. “It took just an hour and a half — a long lunch — for the AI to serve up a potential new antibiotic, an offering to a world contending with the rise of so-called superbugs: bacteria, viruses, fungi and parasites that have mutated and no longer respond to the drugs we have available,” writes Kuchler.

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.”

Principal Research Scientist Kalyan Veeramachaneni speaks with Fast Company reporter Sam Becker about his work in developing the Synthetic Data Vault, which is helpful for creating synthetic data sets, reports Sam Becker for Fast Company. “Fake data is randomly generated,” says Veeramachaneni. “While synthetic data is trying to create data from a machine learning model that looks very realistic.”

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."

Undergraduate student Isabella Struckman and Sofie Kupiec ’23 reached out to the first hundred signatories of the Future of Life Institute’s open letting calling for a pause on AI development to learn more about their motivations and concerns, reports Will Knight for Wired. “The duo’s write-up of their findings reveals a broad array of perspectives among those who put their name to the document,” writes Knight. “Despite the letter’s public reception, relatively few were actually worried about AI posing a looming threat to humanity.”

Prof. Daniela Rus, director of CSAIL, speaks with TechCrunch reporter Brain Heater about liquid neural networks and how this emerging technology could impact robotics. “The reason we started thinking about liquid networks has to do with some of the limitations of today’s AI systems,” says Rus, “which prevent them from being very effective for safety, critical systems and robotics. Most of the robotics applications are safety critical.”

MIT researchers have developed a new tool called “PhotoGuard” that can help protect images from AI manipulation, reports Ross Cristantiello for Boston.com. The tool “is designed to make real images resistant to advanced models that can generate new images, such as DALL-E and Midjourney,” writes Cristantiello.

A working paper co-authored by Prof. John Horton and graduate students Emma van Inwegen and Zanele Munyikwa has found that “AI has the potential to level the playing field for non-native English speakers applying for jobs by helping them better present themselves to English-speaking employers,” reports Medora Lee for USA Today. “Between June 8 and July 14, 2021, [Inwegen] studied 480,948 job seekers, who applied for jobs that require English to be spoken but who mostly lived in nations where English is not the native language,” explains Lee. “Of those who used AI, 7.8% were more likely to be hired.”

Researchers at MIT have developed “PhotoGuard,” a tool that can be used to protect images from AI manipulation, reports Catherine Thorbecke for CNN. The tool “puts an invisible ‘immunization’ over images that stops AI models from being able to manipulate the picture,” writes Thorbecke.

Boston Globe reporter Aaron Pressman speaks with alumnus Jeremy Wertheimer, co-founder of ITA Software, about the state of AI innovation in the Greater Boston area, reports Aaron Pressman for The Boston Globe. “Back in the day, we called it good old-fashioned AI,” says Wertheimer. “But the future is to forget all that clever coding. You want to have an incredibly simple program with enough data and enough computing power.”

A number of MIT alumni including Elaheh Ahmadi, Alexander Amini, and Jose Amich have been named to the Forbes 30 Under 30 Local Boston list.

Prof. David Autor speaks with Delphine Strauss of the Financial Times about the risks AI poses to jobs and job quality, but also the technology’s potential to help rebuild middle-class jobs. “The good case for AI is where it enables people with foundational expertise or judgment to do more expert work with less expertise,” says Autor. He adds, “My hope is that we can use AI to reinstate the value of skills held by people without as high a degree of formal education.”

Prof. Daron Acemoglu speaks with Boston Globe reporters Alex Kantrowitz and Douglas Gorman about how to address the advance of AI in the workplace. “We know from many areas that have rapidly automated that they don’t deliver the types of returns that they promised,” says Acemoglu. “Humans are underrated.”