Chatbots like ChatGPT and Claude have experienced a meteoric rise in usage over the past three years because they can help you with a wide range of tasks. Whether you’re writing Shakespearean sonnets, debugging code, or need an answer to an obscure trivia question, artificial intelligence (AI) systems seem to have you covered. The source of this versatility? Billions or even trillions of textual data points across the Internet.

A global cohort of eight scientists and engineers working in a variety of disciplines were named Schmidt Polymaths and will each receive up to $2.5 million over five years to pursue research in new disciplines or using new methodologies, Schmidt Sciences announced today. 

The artificial intelligence models that turn text into images are also useful for generating new materials. Over the last few years, generative materials models from companies like Google, Microsoft, and Meta have drawn on their training data to help researchers design tens of millions of new materials.

In 1968, MIT Professor Stephen Benton transformed holography by making three-dimensional images viewable under white light. Over fifty years later, holography’s legacy is inspiring new directions at MIT CSAIL, where the Human-Computer Interaction Engineering (HCIE) group, led by Professor Stefanie Mueller, is pioneering programmable color — a future in which light and material appearance can be dynamically controlled.

3D printing has come a long way since its invention in 1983 by Chuck Hull, who pioneered stereolithography, a technique that solidifies liquid resin into solid objects using ultraviolet lasers. Over the decades, 3D printers have evolved from experimental curiosities into tools capable of producing everything from custom prosthetics to complex food designs, architectural models, and even functioning human organs. 

If your hand lotion is a bit runnier than usual coming out of the bottle, it might have something to do with the goop’s “mechanical memory.”

When the IEEE International Conference on Robotics and Automation (ICRA) first convened 40 years ago, the robotics community shared a clear vision: robots would one day combine elegant mathematical models with advanced computation to handle complex tasks. Four decades later, the community is divided over how to reach that goal. That divide was on full display this May in Atlanta, where ICRA marked its anniversary with a unique closing keynote: a live Oxford-style debate on whether “data will solve robotics and automation.”

MIT researchers have developed a reconfigurable antenna that dynamically adjusts its frequency range by changing its physical shape, making it more versatile for communications and sensing than static antennas.

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In computer science parlance, the molecule is “symmetric,” meaning the fundamental structure of that molecule remains the same if it undergoes certain transformations, like rotation.