AI Flash News

MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.

By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.

A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.

Mariano Salcedo ’25, a master’s student in the new Music Technology and Computation Graduate Program, is designing an AI to visualize and express music and other sounds.

An AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.

DNA robots are emerging as tiny programmable machines that could one day deliver drugs, hunt viruses, and build molecular-scale devices. By borrowing ideas from traditional robotics and combining them with DNA folding techniques, scientists are creating structures that can move and act with precision. These robots can be guided using chemical reactions or external signals like light and magnetic fields.

A new tomato-picking robot is learning to think before it acts. Instead of simply identifying ripe fruit, it predicts how easy each tomato will be to harvest and adjusts its approach accordingly. This smarter strategy boosted success rates to 81%, with the robot even switching angles when needed. The breakthrough could pave the way for farms where robots and humans work side by side.

Artificial intelligence is often portrayed as a tool that replaces human work, but new research from Swansea University suggests a far more exciting role: creative collaborator. In a large study with more than 800 participants designing virtual cars, researchers found that AI-generated design galleries sparked deeper engagement, longer exploration, and better results.

As AI systems began acing traditional tests, researchers realized those benchmarks were no longer tough enough. In response, nearly 1,000 experts created Humanity’s Last Exam, a massive 2,500-question challenge covering highly specialized topics across many fields. The exam was engineered so that any question solvable by current AI models was removed. Early results show even the most advanced systems still struggle — revealing a surprisingly large gap between AI performance and true expert-level knowledge.