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Researchers use artificial intelligence to boost image quality of metalens camera

Researchers have leveraged deep learning techniques to enhance the image quality of a metalens camera. The new approach uses artificial intelligence to turn low-quality images into high-quality ones, which could make these cameras viable for a multitude of imaging tasks including intricate microscopy applications and mobile devices.

Potential power and pitfalls of harnessing artificial intelligence for sleep medicine

A new article highlights how artificial intelligence stands on the threshold of making monumental contributions to the field of sleep medicine. Through a strategic analysis, researchers examined advancements in AI within sleep medicine and spotlighted its potential in revolutionizing care in three critical areas: clinical applications, lifestyle management, and population health. The committee also reviewed barriers and challenges associated with using AI-enabled technologies.

Generative AI that imitates human motion

Walking and running is notoriously difficult to recreate in robots. Now, a group of researchers has overcome some of these challenges by creating an innovative method that employs central pattern generators -- neural circuits located in the spinal cord that generate rhythmic patterns of muscle activity -- with deep reinforcement learning. The method not only imitates walking and running motions but also generates movements for frequencies where motion data is absent, enables smooth transition movements from walking to running, and allows for adapting to environments with unstable surfaces.

Researchers use foundation models to discover new cancer imaging biomarkers

Researchers have harnessed the technology behind foundation models, which power tools like ChatGPT, to discover new cancer imaging biomarkers that could transform how patterns are identified from radiological images. Improved identification of such patterns can greatly impact the early detection and treatment of cancer.

Built-in bionic computing

The use of pliable soft materials to collaborate with humans and work in disaster areashas drawn much recent attention. However, controlling soft dynamics for practical applications has remained a significant challenge. Researchers developed a method to control pneumatic artificial muscles, which are soft robotic actuators. Rich dynamics of these drive components can be exploited as a computational resource.
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