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Novel memristor wafer integration technology paves the way for brain-like AI chips

A research team led by Professor Sanghyeon Choi from the Department of Electrical Engineering and Computer Science at DGIST has successfully developed a memristor, which is gaining recognition as a next-generation semiconductor device, through mass-integration at the wafer scale.

The study, published in the journal Nature Communications, proposes a new technological platform for implementing a highly integrated AI semiconductor replicating the , overcoming the limitations of conventional semiconductors.

The human brain contains about 100 billion neurons and around 100 trillion synapses, allowing it to store and process enormous amounts of information within a compact space.

Human-centric photo dataset aims to help spot AI biases responsibly

A database of more than 10,000 human images to evaluate biases in artificial intelligence (AI) models for human-centric computer vision is presented in Nature this week. The Fair Human-Centric Image Benchmark (FHIBE), developed by Sony AI, is an ethically sourced, consent-based dataset that can be used to evaluate human-centric computer vision tasks to identify and correct biases and stereotypes.

Computer vision covers a range of applications, from autonomous vehicles to facial recognition technology. Many AI models used in were developed using flawed datasets that may have been collected without consent, often taken from large-scale image scraping from the web. AI models have also been known to reflect that may perpetuate sexist, racist, or other stereotypes.

Alice Xiang and colleagues present an image dataset that implements for a number of factors, including consent, diversity, and privacy. FHIBE includes 10,318 images of 1,981 people from 81 distinct countries or regions. The database includes comprehensive annotations of demographic and physical attributes, including age, pronoun category, ancestry, and hair and skin color.

Xpeng’s Robot Revolution: Mass-Producing Humanoids by 2026

Xpeng Motors has accelerated its humanoid robot ambitions, unveiling the advanced IRON model with solid-state batteries and aiming for mass production by end-2026. Paralleling Tesla, the Chinese EV maker is also launching robotaxis, blending automotive and robotics tech for future dominance. This move signals a transformative shift in AI and automation.

Therapeutic brain implants that travel through blood defy the need for surgery

What if clinicians could place tiny electronic chips in the brain that electrically stimulate a precise target, through a simple injection in the arm? This may someday help treat deadly or debilitating brain diseases, while eliminating surgery-related risks and costs.

MIT researchers have taken a major step toward making this scenario a reality. They developed microscopic, wireless bioelectronics that could travel through the body’s circulatory system and autonomously self-implant in a target region of the brain, where they would provide focused treatment.

In a study on mice, the researchers showed that after injection, these minuscule implants can identify and travel to a specific brain region without the need for human guidance. Once there, they can be wirelessly powered to provide electrical stimulation to the precise area. Such stimulation, known as neuromodulation, has shown promise as a way to treat and diseases like Alzheimer’s and multiple sclerosis.

CRISPR Screening Made Easy with the Revvity Dharmacon™ All-in-One Lentiviral Platform

Revvity’s Dharmacon All-in-one lentiviral platform has expanded to include whole-genome library options for CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa). Like the individual All-in-one reagents, the whole-genome libraries utilize a single vector lentiviral system with all components necessary for CRISPRko, CRISPRa, and CRISPRi whole-genome pooled screening.

The Quantum Dance: Discovery of Polarons Solves a Decades-Old Mystery in Condensed Matter Physics

In a breakthrough that reshapes our understanding of quantum materials, an international team of physicists has finally solved a decades-old mystery about how certain materials suddenly lose their ability to conduct electricity. The answer lies in an elusive quantum phenomenon known as a polaron — a quasiparticle formed when an electron becomes tightly coupled to the vibrations of the surrounding crystal lattice. This subtle “dance” between electrons and atoms can transform a good conductor into a perfect insulator.

The discovery, made by researchers from Kiel University and the DESY research center in Germany, including Professor Kai Rossnagel and Dr. Chul-Hee Min, provides the first direct evidence of polarons in a rare-earth compound composed of thulium, selenium, and tellurium (TmSe1–x Tex). Their findings, published in Physical Review Letters, illuminate one of quantum physics’ most puzzling phenomena: how subtle atomic vibrations can “kill” electrical conductivity.

Stellar Giants Forged the Chemical Diversity of Ancient Clusters

“Extremely massive stars may have played a key role in the formation of the first galaxies,” said Dr. Paolo Padoan.

How did the extremely massive stars (EMS) in the early universe help form the oldest star clusters? This is what a recent study published in the Monthly Notices of the Royal Astronomical Society hopes to address as an international team of scientists investigated the role that EMS played in not only forming globular clusters (GCs), but how the latter were responsible for forming the first black holes. This study has the potential to help scientists better understand the conditions of the early universe and what this could mean to better understanding our existence.

For the study, the researchers presented a new computational model to help explain how EMS contributed to GC formation with bodies celestial objects being between 1,000 to 10,000 times as massive as our Sun and containing hundreds of thousands to millions of stars, respectively. Given the massive sizes and short lifetimes of EMS, they go supernova when they die, and the new model postulates they become black holes while releasing massive amounts of chemical and hydrogen that mixes with surrounding gas and dust, resulting in the formation of GCs. Additionally, data obtained from NASA’s James Webb Space Telescope (JWST) discovered nitrogen-rich galaxies had chemical signatures obtained from GCs.

Micron-resolution fiber mapping in histology independent of sample preparation

To understand brain diseases, neuroscientists try to understand the intricate maze of nerve fibers in our brains. For analysis under a microscope, brain tissue is often immersed in paraffin wax to create high-quality slices. But until now, it has been impossible to precisely trace the densely packed nerves in these slices. Researchers from Delft, Stanford, Jülich, and Rotterdam have achieved a milestone: using the ComSLI technique, they can now map the fibers in any tissue sample with micrometer precision. The research is published in Nature Communications.

Micron-resolution fiber mapping in histology independent of sample preparation.

Georgiadis and colleagues conduct micron-resolution fibre mapping on multiple histological tissue sections. Their light-scattering technique works across different sample preparations and tissue types, including formalin-fixed paraffin-embedded brain sections.

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