MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting.

Gemstones like precious opal are beautiful to look at and deceivingly complex. As you look at such gems from different angles, you’ll see a variety of tints glisten, causing you to question what color the rock actually is. It’s iridescent thanks to something called structural color — microscopic structures that reflect light to produce radiant hues.

Generative artificial intelligence models have left such an indelible impact on digital content creation that it’s getting harder to recall what the internet was like before it. You can call on these AI tools for clever projects such as videos and photos — but their flair for the creative hasn’t quite crossed over into the physical world just yet.

MIT researchers have developed a new method for designing 3D structures that can be transformed from a flat configuration into their curved, fully formed shape with only a single pull of a string.

Most languages use word position and sentence structure to extract meaning. For example, “The cat sat on the box,” is not the same as “The box was on the cat.” Over a long text, like a financial document or a novel, the syntax of these words likely evolves.

To innovate as a technologist, you need to be a polyglot—fluent in multiple languages of problem-solving, able to synthesize ideas across domains, reframing puzzles to visualize different outcomes, and revealing the questions that have yet to be asked.