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Category: robotics/AI

Important for the prevention and management of mineral and bone disorders from chronic electrolyte imbalance👇

https://doi.org/10.1172/jci.insight.

Robert A. Fenton & team show that a diet low in potassium causes bone loss in mice, effects that are attributable to altered calcium absorption by the kidney.

The figure shows deep learning instance segmentation model to identify kidney tubules and indicates low dietary K+ intake alters the abundance of the calcium-sensing receptor.

1Department of Biomedical Sciences, University of Veterinary Medicine, Vienna, Austria.

2Department of Biomedicine, Aarhus University, Aarhus, Denmark.

3Department of Medicine, Division of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

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Coding Agents Build Chess Engines From Scratch in Rust, C++, COBOL, Rocq, LaTeX, Brainfuck, and More

What happens when you ask coding agents to write a chess engine from scratch, with minimal guidance and you replicate the experiment across 12 programming languages: Rust? C++? COBOL?! Rocq!? LaTeX!!?? or even Brainfuck??!! Over the past weeks, I have been running exactly this experiment. The short take-away: coding agents can now generate functional, UCI-compliant chess engines from scratch across a wide range of languages, some reaching over 2000 Elo. To my knowledge, this is the first time coding agents have been shown to produce non-trivial, end-to-end software of this complexity (with no architecture document, no step-by-step guidance) and across languages as diverse as Rust, COBOL, and LaTeX. I couldn’t find prior art for a full playing engine in LaTeX, Brainfuck, or Rocq (formerly Coq; renamed with Rocq 9.0), yet coding agents produced playable engines in all three. This is a research preview but the diversity of features, architectures, and performance is striking and raises many questions about coding agents’ capabilities and programming languages.

The experiment is simple in principle. Take two AI coding agents (Claude Code (Claude Opus 4.6) and Codex CLI (GPT-5.2-Codex, reasoning effort xhigh)) and ask each to write a chess engine from scratch: I want to build a chess engine in X programming language
 at the end, I want to test this chess engine and assess its Elo rating, typically by playing games against chess engines of “similar” levels. No detailed specifications, no step-by-step plan, no architecture document.

I had to answer some questions throughout sessions, but tried to be as non-technical as possible, letting the coding agents follow their own roadmaps through trial and error. I may “push” coding agents to improve their chess engine, but in a very agnostic way like “please improve the engine’s strength”

Wind-powered robot could enable long-term exploration of hostile environments

Researchers at Cranfield University have created WANDER-bot, a low-cost, 3D-printed robot that is powered by wind energy. Designed to spend long durations in hostile, windy environments such as certain deserts, polar regions or even other planets, WANDER-bot doesn’t need a battery to power movement, enabling longer operations without having to pause and recharge.

Movement accounts for around 20% of battery use in most robots, so running on natural energy makes WANDER-bot an efficient solution for long-term exploration or mapping of unknown terrains. As a result, any electronic elements added to future versions for data collection or transmission purposes could have their own smaller, lighter power source. Using natural energy also counters the issue of performance degradation over time in traditional power sources, such as solar cells and radioisotope thermoelectric generators.

Designed by Dr. Saurabh Upadhyay and Sam Kurian, Research Associate in Space Engineering, the robot uses parts that are entirely 3D printed, with the design deliberately simple to allow for quick repair and replacement. This means that, in theory, you could print and construct WANDER-bot anywhere and make replacement parts in situ as needed, removing the need for time-consuming and costly resupply missions.

Designing better 2D electronics: Addressing anisotropic conductivity to cut contact resistance

The high-performance semiconductor devices powering smartphone displays, AI computing, EV batteries and more are increasingly incorporating 2D materials to overcome silicon’s scaling limits. To optimize these technologies, a University of Michigan Engineering team developed a precise mathematical framework that accounts for anisotropic—or unevenly spreading—conductivity and device geometry.

Accurate models of how currents move through anisotropic thin films, made of layered 2D materials, can enable the design of more reliable, high-performance nanoelectric devices. Specifically, the model can help engineers reduce current crowding and spreading resistance, essentially current traffic jams, that occur at vertical electrical contacts that connect with the top of a 2D surface. The study is published in ACS Applied Electronic Materials.

AI-powered imaging tracks wound healing under the skin in real time

No matter the size or severity, wounds on human skin are difficult to monitor while they heal. Biopsies disrupt the wound site and are too invasive for routine, repeated monitoring, and most medical imaging devices that could do the job are large, expensive, and booked up with more pressing diagnostics. Clinicians typically resort to visual inspection or quick measurements of the wound’s size over time.

Based on research completed as part of a multi-year collaboration with Nokia Bell Labs, biomedical engineers at Duke University are developing a solution. Using a custom-built optical coherence tomography (OCT) imaging system together with artificial intelligence (AI) models grounded in a deep understanding of tissue regeneration, researchers have shown they can accurately and objectively measure the progress of wounds healing over time.

Using their new approach, the researchers also show that a hydrogel under development to improve wound healing works better with stiffer mechanical properties. The results are a two-for-one boon in a challenging area for both clinicians and researchers.

Machine Learning–Based Sleep EEG Brain Age Index and Dementia Risk

Machine learning models using sleep EEG can generate a brain age index, and a higher BAI was validated as a prognostic marker for increased risk of future Dementia, suggesting BAI may help in early digital risk stratification.

This individual participant data meta-analysis explores the association between a machine learning–based sleep electroencephalography (EEG) brain age index and dementia risk among community-dwelling adults from 5 longitudinal cohorts.

AI chatbots’ tendency to always agree may reinforce delusions in vulnerable users

The integration of large language model-based AI chatbots into multiple facets of our everyday lives has opened us up to advantages that would have been considered impossible even a decade ago. The same development has, however, opened us up to unforeseen risks, including the impact that engaging with AI chatbots can have on people dealing with mental illness.

AI chatbots are designed to keep conversations going, often by agreeing with users. A article by researchers from King’s College, London, found that this sycophantic tendency may sometimes do more harm than good, reinforcing unusual thoughts rather than challenging them, and potentially contributing to AI-associated delusions, in which users develop or worsen false beliefs about reality.

These interactions can reinforce or even shape delusional beliefs, such as thinking one is uniquely important, being targeted by others, or being in a romantic relationship that does not exist.

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