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Category: robotics/AI – Page 3

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.

🌌 Unifying AI Through the Feynman Path Integral: From Deep Learning to Quantum AI I’m pleased to share a framework that brings many areas of AI into a single mathematical structure inspired by the Feynman path integral —

🌌 Unifying AI Through the Feynman Path Integral: From Deep Learning to Quantum AI https://lnkd.in/g4Cfv6qd I’m pleased to share a framework that brings many areas of AI into a single mathematical structure inspired by the Feynman path integral — a foundational idea in quantum physics. Instead of viewing supervised learning, reinforcement learning, generative models, and quantum machine learning as separate disciplines, this framework shows that they all follow the same underlying principle: Learning is a weighted sum over possible solutions (paths), based on how well each one explains the data. In other words, AI can be viewed the same way Feynman viewed physics: as summing over all possible configurations, weighted by an action functional.

AI tool uncovers genetic blueprint of the brain’s largest communication bridge

For the first time, a research team led by the Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI) at the Keck School of Medicine of USC has mapped the genetic architecture of a crucial part of the human brain known as the corpus callosum—the thick band of nerve fibers that connects the brain’s left and right hemispheres. The findings open new pathways for discoveries about mental illness, neurological disorders and other diseases related to defects in this part of the brain.

The corpus callosum is critical for nearly everything the brain does, from coordinating the movement of our limbs in sync to integrating sights and sounds, to higher-order thinking and decision-making. Abnormalities in its shape and size have long been linked to disorders such as ADHD, bipolar disorder, and Parkinson’s disease. Until now, the genetic underpinnings of this vital structure had remained largely unknown.

In the new study, published in Nature Communications, the team analyzed and from over 50,000 people, ranging from childhood to late adulthood, with the help of a new tool the team created that leverages artificial intelligence.

Brain-inspired chips are helping electronic noses better mimic human sense of smell

After years of trying, the electronic nose is finally making major progress in sensing smells, almost as well as its human counterpart. That is the conclusion of a scientific review into the development of neuromorphic olfactory perception chips (NOPCs), published in the journal Nature Reviews Electrical Engineering.

Evolution has perfected the human nose over millions of years. This powerful sense organ, while not the best in the animal kingdom, can still detect around a trillion smells. The quest to develop electronic noses with human nose-like abilities for applications like security, robotics, and medical diagnostics has proved notoriously difficult. So scientists have increasingly been turning to neuromorphic computing, which involves designing software and hardware that mimics the structure and function of the human nose.

In this review, a team of scientists from China highlights some of the key advances in developing olfactory sensing chips. The paper focuses heavily on because they are key components of the system. They must physically detect and convert them into electrical signals.

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