A new generative AI approach to predicting chemical reactions

Many attempts have been made to harness the power of new artificial intelligence and large language models (LLMs) to try to predict the outcomes of new chemical reactions. These have had limited success, in part because until now they have not been grounded in an...

3 Questions: The pros and cons of synthetic data in AI

Synthetic data are artificially generated by algorithms to mimic the statistical properties of actual data, without containing any information from real-world sources. While concrete numbers are hard to pin down, some estimates suggest that more than 60 percent of...

3 Questions: On biology and medicine’s “data revolution”

Caroline Uhler is an Andrew (1956) and Erna Viterbi Professor of Engineering at MIT; a professor of electrical engineering and computer science in the Institute for Data, Science, and Society (IDSS); and director of the Eric and Wendy Schmidt Center at the Broad...

Simpler models can outperform deep learning at climate prediction

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in weather and climate, but a new study by MIT researchers shows that bigger models are not always better. The team demonstrates that, in certain...

Can large language models figure out the real world?

Back in the 17th century, German astronomer Johannes Kepler figured out the laws of motion that made it possible to accurately predict where our solar system’s planets would appear in the sky as they orbit the sun. But it wasn’t until decades later, when Isaac Newton...