Within the past few years, models that can predict the structure or function of proteins have been widely used for a variety of biological applications, such as identifying drug targets and designing new therapeutic antibodies. These models, which are based on large language models (LLMs), can make very accurate predictions of a protein’s suitability for a given application. However, there’s no way to determine how these models make their predictions or which protein features play the most important role in those decisions. In a new study, MIT researchers have used a novel technique to open up that “black box” and […]

In 1943, while the world’s brightest physicists split atoms for the Manhattan Project, the American psychologist B.F. Skinner led his own secret government project to win World War II.  Skinner did not aim to build a new class of larger, more destructive weapons. Rather, he wanted to make conventional bombs more precise. The idea struck him as he gazed out the window of his train on the way to an academic conference. “I saw a flock of birds lifting and wheeling in formation as they flew alongside the train,” he wrote. “Suddenly I saw them as ‘devices’ with excellent vision […]

Prompted in part by Apple’s paper about the limits of large language models (“The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity”), I spent some time playing with Tower of Hanoi. It’s a problem I solved some 50 years ago when I was in college, and I haven’t felt the desire or need to revisit it since. Now, of course, “We Can Haz AI,” and all that means. Of course, I didn’t want to write the code myself. I confess, I don’t like recursive solutions. But there was Qwen3-30B, a “reasoning […]