AI Flash News

The approach could help engineers tackle extremely complex design problems, from power grid optimization to vehicle design.

Lincoln Laboratory intern Ivy Mahncke developed and tested algorithms to help human divers and robots navigate underwater.

By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.

To help generative AI models create durable, real-world accessories and decor, the PhysiOpt system runs physics simulations and makes subtle tweaks to its 3D blueprints.

By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.

As millions turn to ChatGPT and other AI chatbots for therapy-style advice, new research from Brown University raises a serious red flag: even when instructed to act like trained therapists, these systems routinely break core ethical standards of mental health care. In side-by-side evaluations with peer counselors and licensed psychologists, researchers uncovered 15 distinct ethical risks — from mishandling crisis situations and reinforcing harmful beliefs to showing biased responses and offering “deceptive empathy” that mimics care without real understanding.

Qubits, the heart of quantum computers, can change performance in fractions of a second — but until now, scientists couldn’t see it happening. Researchers at NBI have built a real-time monitoring system that tracks these rapid fluctuations about 100 times faster than previous methods. Using fast FPGA-based control hardware, they can instantly identify when a qubit shifts from “good” to “bad.” The discovery opens a new path toward stabilizing and scaling future quantum processors.

Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The breakthrough could lead to powerful, low-energy supercomputers while revealing new secrets about how our brains process information.

Researchers at the University of Michigan have created an AI system that can interpret brain MRI scans in just seconds, accurately identifying a wide range of neurological conditions and determining which cases need urgent care. Trained on hundreds of thousands of real-world scans along with patient histories, the model achieved accuracy as high as 97.5% and outperformed other advanced AI tools.