Singapore-MIT Alliance for Research and Technology’s (SMART) Mens, Manus & Machina (M3S) interdisciplinary research group, and National University of Singapore (NUS), alongside collaborators from Massachusetts Institute of Technology (MIT) and Nanyang Technological University (NTU Singapore), have developed an AI control system that enables soft robotic arms to learn a wide repertoire of motions and tasks once, then adjust to new scenarios on the fly without needing retraining or sacrificing functionality. This breakthrough brings soft robotics closer to human-like adaptability for real-world applications, such as in assistive robotics, rehabilitation robots, and wearable or medical soft robots, by making them more intelligent, versatile and safe.
A firm that wants to use a large language model (LLM) to summarize sales reports or triage customer inquiries can choose between hundreds of unique LLMs with dozens of model variations, each with slightly different performance.
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.
Whether you’re a scientist brainstorming research ideas or a CEO hoping to automate a task in human resources or finance, you’ll find that artificial intelligence (AI) tools are becoming the assistants you didn’t know you needed. In particular, many professionals are tapping into the talents of semi-autonomous software systems called AI agents, which can call on AI at specific points to solve problems and complete tasks.
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.
