In an MIT classroom, a professor lectures while students diligently write down notes they will reread later to study and internalize key information ahead of an exam.

What can we learn about human intelligence by studying how machines “think?” Can we better understand ourselves if we better understand the artificial intelligence systems that are becoming a more significant part of our everyday lives?

Pulkit Agrawal, MIT EECS Associate Professor and CSAIL principal investigator, has received the Toshio Fukuda Young Professional Award from the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) for his work in “robot learning, self-supervised and sim-to-real policy learning, agile locomotion, and dexterous manipulation,” according to the organization.

The degree to which someone trusts the information depicted in a chart can depend on their assumptions about who made the data visualization, according to a pair of studies by MIT researchers.

It’s hard to keep up with the ever-changing trends of the fashion world. What’s “in” one minute is often out of style the next season, potentially causing you to re-evaluate your wardrobe.

Say a person takes their French Bulldog, Bowser, to the dog park. Identifying Bowser as he plays among the other canines is easy for the dog-owner to do while onsite.

Say a local concert venue wants to engage its community by giving social media followers an easy way to share and comment on new music from emerging artists. Rather than working within the constraints of existing social platforms, the venue might want to create its own social app with the functionality that would be best for its community. But building a new social app from scratch involves many complicated programming steps, and even if the venue can create a customized app, the organization’s followers may be unwilling to join the new platform because it could mean leaving their connections and data behind.

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.