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Flexible printed devices produce realistic signals that activate real neurons and point toward efficient brain-inspired computing.

MIT chemists have found a new way to predict 3D genomic structures using AI, which is much faster than old methods.

Researchers have suggested new LLM training strategies where AI learns by talking with others in a real-world setting.

New world model generates diverse, real-time environments from text prompts for navigation and learning, advancing AI research and creativity.

Custom deep-learning system uncovers early clues that predict how starving bacteria form complex structures.

The U.S. Food and Drug Administration (FDA) is rapidly integrating AI into its regulatory processes, aiming to enhance efficiency and reduce review times across all centers.

AI scientists in Japan have developed a new LLM with about 172 billion parameters and shared parameters and training data with the public.

Algorithms were trained on already-published data, making them cost-effective