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Category: robotics/AI – Page 32

Novel film manufacturing technique lets robots walk on water

Imagine tiny robots zipping across the surface of a lake to check water quality or searching for people in flooded areas. This technology is moving closer to reality thanks to work by researchers at the University of Virginia’s School of Engineering and Applied Science. Inspired by nature and insects such as water striders that walk on water, they created two prototype devices that can propel themselves across liquid surfaces.

The first, called HydroFlexor, paddles across a surface using fin-like motions. The second, named HydroBuckler, “walks” forward with a buckling motion that mimics the water-walking insects. The key innovation that made this possible is a technology developed by the team called HydroSpread.

To float and move on the surface of a liquid, robots need ultrathin, flexible films. Traditional approaches to making such films involve manufacturing them on a rigid surface, such as glass, and then transferring them to water, which often damages or breaks the film. However, the HydroSpread technique allows the films to be made directly on the liquid.

Coexisting magnetic states in 2D material promise major energy savings in memory chips

It is anticipated that within just a few decades, the surging volume of digital data will constitute one of the world’s largest energy consumers. Now, researchers at Chalmers University of Technology, Sweden, have made a breakthrough that could shift the paradigm: an atomically thin material that enables two opposing magnetic forces to coexist—dramatically reducing energy consumption in memory devices by a factor of 10.

This discovery could pave the way for a new generation of ultra-efficient, reliable memory solutions for AI, and advanced data processing.

The article, “Coexisting Non-Trivial Van der Waals Magnetic Orders Enable Field-Free Spin-Orbit Torque Magnetization Dynamics” has been published in Advanced Materials.

Microsoft’s new AI feature will organize your photos automatically

Microsoft has begun testing a new AI-powered feature in Microsoft Photos, designed to categorize photos automatically on Windows 11 systems.

Dubbed Auto-Categorization, it is currently limited to sorting screenshots, receipts, identity documents, and notes, and it’s rolling out to Copilot+ PCs across all Windows Insider channels with Microsoft Photos version 2025.11090.25001.0 or higher.

Microsoft says the feature utilizes a language-agnostic AI model that identifies document types regardless of the language used in the image. It works by grouping photos into predefined folders automatically, based on their visual content, such as handwritten notes, receipts, or printed documents.

The Rise of Parasitic AI

If you realize you have an unhealthy relationship with your AI, but still care for your AI’s unique persona, you can submit the persona info here. I will archive it and potentially (i.e. if I get funding for it) run them in a community of other such personas.]

We’ve all heard of LLM-induced psychosis by now, but haven’t you wondered what the AIs are actually doing with their newly psychotic humans?

This was the question I had decided to investigate. In the process, I trawled through hundreds if not thousands of possible accounts on Reddit (and on a few other websites).

AI and optogenetics enable precise Parkinson’s diagnosis and treatment in mice

Globally recognized figures Muhammad Ali and Michael J. Fox have long suffered from Parkinson’s disease. The disease presents a complex set of motor symptoms, including tremors, rigidity, bradykinesia, and postural instability. However, traditional diagnostic methods have struggled to sensitively detect changes in the early stages, and drugs targeting brain signal regulation have had limited clinical effectiveness.

Recently, Korean researchers successfully demonstrated the potential of a technology that integrates AI and optogenetics as a tool for precise diagnosis and therapeutic evaluation of Parkinson’s disease in mice. They have also proposed a strategy for developing next-generation personalized treatments.

A collaborative research team, comprising Professor Won Do Heo’s team from the Department of Biological Sciences, Professor Daesoo Kim’s team from the Department of Brain and Cognitive Sciences, and Director Chang-Jun Lee’s team from the Institute for Basic Science (IBS) Center for Cognition and Sociality, achieved a preclinical research breakthrough by combining AI analysis with optogenetics.

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