AI Flash News

With $25 million investment from the Commonwealth of Massachusetts, MIT to build a new shared-use facility to serve as a statewide quantum toolbox.

A new study of the postwar U.S. shows which kinds of workers historically filled new tech-enabled jobs.

Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.

MIT faculty member in electrical engineering and computer science to focus on innovation in engineering education and new pedagogical approaches.

The prestigious fellowship funds graduate studies at Stanford University.

Researchers at Penn have created a hybrid light-matter particle that could dramatically speed up AI computing while using far less energy. The breakthrough may help replace some electronic computing processes with ultra-efficient light-based technology.

NASA is testing a next-generation space computer chip that could give spacecraft the ability to operate far more independently in deep space. The radiation-hardened processor is showing performance levels hundreds of times beyond current spaceflight computers while surviving punishing tests designed to mimic the harsh conditions of space. The technology could enable AI-powered spacecraft, faster scientific discoveries, and smarter missions to the Moon and Mars.

A new quantum-inspired algorithm has cracked a problem so massive that conventional supercomputers struggle to even approach it. Researchers used the method to simulate extraordinarily complex quantum materials known as quasicrystals, opening the door to powerful new quantum devices and ultra-efficient electronics. The work could help scientists design advanced topological qubits and materials for future quantum computers.

The little pauses, “ums,” and moments when you struggle to find the right word may reveal far more about your brain than anyone realized. Researchers discovered that everyday speech patterns are closely tied to executive function — the mental system that powers memory, planning, focus, and flexible thinking. By using AI to analyze natural conversations, the team found they could predict cognitive performance with surprising accuracy, potentially opening the door to simple speech-based tools that could detect early signs of dementia long before traditional testing does.