A research team has demonstrated that thin films of ruthenium dioxide (RuO₂) exhibit altermagnetism—the defining property of what is now recognized as the third fundamental class of magnetic materials.
Category: robotics/AI
A new family of barium-based crystals reveals rules for structural changes
The ultimate goal of materials scientists is to design and create materials with precise structures and tailored properties. Predictive technologies have advanced significantly with the rise of AI, yet the delicate nature of chemistry, where even the smallest change can alter a material’s behavior, remains a challenge for building truly chemically intuitive frameworks.
In a recent study, a team of researchers from the US presented a homologous series of barium-based crystals, where the family of materials was built from the same molecular building blocks and capable of forming an infinite range of structures. The only differences among the versions are the size and the arrangement of the blocks, brought about by slight changes in the ratio of the two elements with different electron affinities.
What makes this set of materials unique is that knowing one member of a sequence allows you to predict the next. The researchers believe that understanding the relationship between small changes and a material’s overall chemistry can help improve AI frameworks for predicting and synthesizing new materials.
Brain implant helps man with paralysis regain movement
A brain implant used for the first time is helping a patient with paralysis regain use of his limbs. The use of artificial intelligence is helping in the process, also making it possible for the man to feel objects again. NBC News’ Sam Brock reports.
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Advanced neuromorphic engineering approaches for restoring… : Regenerative Medicine Reports
Isting gap in neuromorphic engineering by mimicking biological neuron dynamics and realizing effective clinical applications to promote functional recovery and quality of life enhancement in patients with brain injury. The novel neuromorphic engineering approaches leverage the dynamic behavior of brain neurons, incorporating electronic circuits that emulate neuronal dynamics. A basic configuration involves a neural model designed to mimic the dynamics of a living neuron, with the potential to replace damaged brain tissue when implanted, thus restoring signal propagation. An enhanced configuration integrates a closed-loop system, wherein the feedback signal from biological neurons synchronizes the artificial neuron with its living counterpart, allowing continuous self-adjustment of system parameters and promoting a neuro-autogenerative regime.
Transcutaneous Peripheral Nerve Stimulation for Essential Tremor: A Randomized Clinical Trial
Essential tremor (ET), the most common upper limb tremor, can impair daily activities. In a multicenter RCT, an artificial intelligence–driven transcutaneous peripheral nerve stimulation (TPNS) device reduced mADL scores by 6.9 points at 90 days, compared with a 2.7-point reduction in the sham group.
Question Is an artificial intelligence (AI)–driven TPNS device superior to a sham device in reducing essential tremor?
Findings In this randomized clinical trial that included 125 adults with essential tremor, use of the TPNS device reduced the modified Activities of Daily Living score of the Essential Tremor Rating Assessment Scale by a clinically meaningful 6.9 points at 90 days, significantly more than the 2.7-point reduction seen in the sham-treated group.
Meaning The TPNS device improved activities related to upper limb tremor at 90 days and could be an effective noninvasive treatment for essential tremor.
Math, Inc.
The Math Inc. team is excited to introduce Gauss, a first-of-its-kind autoformalization agent for assisting human expert mathematicians at formal verification. Using Gauss, we have completed a challenge set by Fields Medallist Terence Tao and Alex Kontorovich in January 2024 to formalize the strong Prime Number Theorem (PNT) in Lean (GitHub).
The translation of human mathematics into verifiable machine code has long been a grand challenge. However, the cost of doing so is prohibitive, requiring scarce human expertise. In particular, after 18 months, Tao and Kontorovich recently announced intermediate progress in July 2025 toward their goal, obstructed by core difficulties in the field of complex analysis.
In light of such difficulties, we are pleased to announce that with Gauss, we have completed the project after three weeks of effort. Gauss can work autonomously for hours, dramatically compressing the labor previously reserved for top formalization experts. Along the way, Gauss formalized the key missing results in complex analysis, which opens up future initiatives previously considered unapproachable.
Nvidia unveils new open-source AI models amid boom in Chinese offerings
Nvidia on Monday revealed the third generation of its “Nemotron” large-language models aimed at writing, coding and other tasks. The smallest of the models, called Nemotron 3 Nano, was being released Monday, with two other, larger versions coming in the first half of 2026.
Nvidia, which has become the world’s most valuable listed company, said that Nemotron 3 Nano was more efficient than its predecessor — meaning it would be cheaper to run — and would do better at long tasks with multiple steps.
Nvidia is releasing the models as open-source offerings from Chinese tech firms such as DeepSeek, Moonshot AI and Alibaba Group Holdings are becoming widely used in the tech industry, with companies such as Airbnb disclosing use of Alibaba’s Qwen open-source model.
AI helps explain how covert attention works and uncovers new neuron types
Shifting focus on a visual scene without moving our eyes—think driving, or reading a room for the reaction to your joke—is a behavior known as covert attention. We do it all the time, but little is known about its neurophysiological foundation.
Now, using convolutional neural networks (CNNs), UC Santa Barbara researchers Sudhanshu Srivastava, Miguel Eckstein and William Wang have uncovered the underpinnings of covert attention, and in the process, have found new, emergent neuron types, which they confirmed in real life using data from mouse brain studies.
“This is a clear case of AI advancing neuroscience, cognitive sciences and psychology,” said Srivastava, a former graduate student in the lab of Eckstein, now a postdoctoral researcher at UC San Diego.