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Continue reading “Microsoft CEO: “Agents Will Replace ALL Software”” | >

Artificial neural networks, central to deep learning, are powerful but energy-consuming and prone to overfitting. The authors propose a network design inspired by biological dendrites, which offers better robustness and efficiency, using fewer trainable parameters, thus enhancing precision and resilience in artificial neural networks.

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The chemical composition of a material alone sometimes reveals little about its properties. The decisive factor is often the arrangement of the molecules in the atomic lattice structure or on the surface of the material. Materials science utilizes this factor to create certain properties by applying individual atoms and molecules to surfaces with the aid of high-performance microscopes. This is still extremely time-consuming and the constructed nanostructures are comparatively simple.

Using , a research group at TU Graz now wants to take the construction of nanostructures to a new level. Their paper is published in the journal Computer Physics Communications.

“We want to develop a self-learning AI system that positions individual molecules quickly, specifically and in the right orientation, and all this completely autonomously,” says Oliver Hofmann from the Institute of Solid State Physics, who heads the research group. This should make it possible to build highly complex molecular structures, including logic circuits in the nanometer range.

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Scientists have built an artificial motor capable of mimicking the natural mechanisms that power life.

The finding, from The University of Manchester and the University of Strasbourg, published in the journal Nature, provides new insights into the fundamental processes that drive life at the molecular level and could open doors for applications in medicine, energy storage, and nanotechnology.

Professor David Leigh, lead researcher from The University of Manchester, said: Biology uses chemically powered molecular machines for every biological process, such as transporting chemicals around the cell, information processing or reproduction.

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New research shows somatic mutations drive epigenetic changes tied to aging. This discovery reshapes our understanding of aging and challenges current anti-aging strategies.

Summary: A new study has uncovered a direct link between somatic mutations and epigenetic modifications, challenging established views on aging. Researchers found that random genetic mutations drive predictable changes in DNA methylation, offering new insights into the relationship between mutation accumulation and epigenetic clocks.

This suggests that epigenetic changes may track, rather than cause, aging, making it harder to reverse aging than previously thought. These findings redefine our understanding of aging at the molecular level and hold significant implications for future anti-aging therapies.

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In a groundbreaking study published in Nature, researchers from the University of British Columbia, the University of Washington, and Johns Hopkins University have identified a new class of quantum states in a specially engineered graphene structure. They found topological electronic crystals in twisted bilayer–tilayer graphene, made by stacking and twisting two-dimensional graphene layers.

Graphene, composed of carbon atoms arranged in a honeycomb structure, has unique electrical properties due to the way electrons hop between the carbon atoms.

Prof. Joshua Folk from UBC explains that stacking two graphene flakes with a slight twist creates a geometric interference effect known as a moiré pattern, changing how electrons move, slowing them down, and twisting their motion.

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