AI Flash News

While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.

With the help of AI, MIT Research Scientist Judah Cohen is reshaping subseasonal forecasting, with the goal of extending the lead time for predicting impactful weather.

Recent launch event for the center featured discussions on pro-worker AI, wealth inequality, and the future of liberal democracy.

New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.

MIT graduate student C Jacob Payne reimagines historic architecture and invents new possibilities at the intersection of AI and design.

Stanford researchers have developed an AI that can predict future disease risk using data from just one night of sleep. The system analyzes detailed physiological signals, looking for hidden patterns across the brain, heart, and breathing. It successfully forecast risks for conditions like cancer, dementia, and heart disease. The results suggest sleep contains early health warnings doctors have largely overlooked.

Researchers have created microscopic robots so small they’re barely visible, yet smart enough to sense, decide, and move completely on their own. Powered by light and equipped with tiny computers, the robots swim by manipulating electric fields rather than using moving parts. They can detect temperature changes, follow programmed paths, and even work together in groups. The breakthrough marks the first truly autonomous robots at this microscopic scale.

Researchers have built a new platform that produces ultrashort UV-C laser pulses and detects them at room temperature using atom-thin materials. The light flashes last just femtoseconds and can be used to send encoded messages through open space. The system relies on efficient laser generation and highly responsive sensors that scale well for manufacturing. Together, these advances could accelerate the development of next-generation photonic technologies.

New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers redesigned AI systems to better resemble biological brains, some models produced brain-like activity without any training at all. This challenges today’s data-hungry approach to AI development. The work suggests smarter design could dramatically speed up learning while slashing costs and energy use.