Researchers have developed a new kind of nanoelectronic device that could dramatically cut the energy consumed by artificial intelligence hardware by mimicking the human brain. The researchers, led by the University of Cambridge, developed a form of hafnium oxide that acts as a highly stable, low-energy “memristor”—a component designed to mimic the efficient way neurons are connected in the brain. The results are reported in the journal Science Advances.
Current AI systems rely on conventional computer chips that shuttle data back and forth between memory and processing units. This constant movement consumes large amounts of electricity, and global demand is exploding as AI adoption expands across industries.
Brain-inspired, or neuromorphic, computing is an alternative way to process information that could reduce energy use by as much as 70% by storing and processing information in the same place, and doing so with extremely low power. Such a system would also be far more adaptable, in the same way our own brains are able to learn and adapt.
Humans excel at transmitting ideas, skills, and knowledge across generations, and at building on those competencies in a cumulative manner. James Rilling, Professor of Psychology at Emory University, explores how the transmission of our cumulative culture is assumed to depend on both language and mental perspective-taking, or theory of mind. If humans have specialized abilities in these domains, we must have neurobiological specializations to support them. Our research has used comparative primate neuroimaging to attempt to identify such specializations. The arcuate fasciculus is a white matter fiber tract that links Wernicke’s and Broca’s language areas. It is known to be involved in multiple, high level linguistic functions such as lexical semantics, complex syntax, and speech fluency. Using diffusion weighted imaging and tractography, we have demonstrated human specializations in the size and trajectory of the arcuate fasciculus that may partially explain human linguistic abilities. Theory of Mind depends on a set of cortical regions that belong to a neural network known as the default mode network that is functionally connected, highly active at rest, and deactivated by attention-demanding cognitive tasks. We and others have used functional neuroimaging to show that chimpanzees and other primates appear to have a default mode network that is similar to that of humans. However, the non-human primate default mode network seems to have weaker connectivity between certain key nodes, suggesting that these connections could play a role in human theory of mind specializations. Recorded on 02/27/2026. [3/2026] [Show ID: 41329]
Explore More Science & Technology on UCTV (https://www.uctv.tv/science) Science and technology continue to change our lives. University of California scientists are tackling the important questions like climate change, evolution, oceanography, neuroscience and the potential of stem cells.
UCTV is the broadcast and online media platform of the University of California, featuring programming from its ten campuses, three national labs and affiliated research institutions. UCTV explores a broad spectrum of subjects for a general audience, including science, health and medicine, public affairs, humanities, arts and music, business, education, and agriculture. Launched in January 2000, UCTV embraces the core missions of the University of California — teaching, research, and public service – by providing quality, in-depth television far beyond the campus borders to inquisitive viewers around the world.
Become a Big Think member to unlock expert classes, premium print issues, exclusive events and more: https://bigthink.com/membership/?utm_… “If science aims to describe everything, how can it not describe the simple fact of our existence?” On this episode of Dispatches, Kmele speaks with the scientists, mathematicians, and spiritual leaders trying to do just that:
This video is an episode from @The-Well, our publication about ideas that inspire a life well-lived, created with the @JohnTempletonFoundation
Watch the full podcast now ► • Dispatches from The Well.
In the newest episode of Dispatches from The Well, we’re diving deep into the “hard problem of consciousness.” Here, Kmele combines the perspectives of five different scientists, philosophers, and spiritual leaders to approach one of humanity’s most pressing questions: what is consciousness?
In the AI age, the question of consciousness is more prevalent than ever. Is every single thing in the universe self-aware? What does it actually mean to be conscious? Are our bodies really just a vessel for our thoughts? Kmele asks these questions, and many more, in the most thought-provoking episode yet. This is Dispatches from The Well.
Featuring: sir roger penrose, christof koch, melanie mitchell, reid hoffman, swami sarvapriyananda.
Recent reporting on SpaceX’s proposal to deploy up to one million satellites in low Earth orbit — paired with a vision of AI-enabled, autonomous orbital infrastructure — marks a decisive moment for the space community. Regardless of whether these numbers ultimately materialize, the direction is unmistakable: space is moving toward unprecedented scale, autonomy and strategic importance.
That reality demands a fundamental reassessment of what space awareness really means.
For decades, space situational awareness (SSA) focused on orbital mechanics: where an object is, where it will be and whether it might collide with something else. That model is now insufficient. Satellites are no longer passive nodes governed primarily by physics; they are software-defined, networked systems deeply integrated with terrestrial cyber infrastructure, global supply chains and increasingly AI-driven decision loops.
Dive deep into the fascinating mind of Philip K. Dick through The Exegesis of Philip K. Dick, a posthumous collection of the legendary science fiction author’s personal notes, philosophical musings, and reflections on reality, existence, and spirituality. In this video, we explore the core themes of the book, including Dick’s obsession with the nature of reality, his exploration of gnosticism, and his visionary ideas that foreshadowed concepts like simulated realities, later popularized by films such as The Matrix.
We’ll also delve into Dick’s personal struggles with mental illness, paranoia, and addiction, as well as his unrelenting pursuit of truth and spiritual enlightenment. Whether you’re a fan of his groundbreaking novels or curious about the mind behind them, this video offers an insightful look at the profound thoughts and challenges that shaped his work.
Join us as we unravel the complexities of The Exegesis and celebrate the legacy of one of the most influential thinkers and writers in science fiction history.
This video was created as a personal experiment of sorts, made from start to finish in one day using only AI tools, based upon my prompts.
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.
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”
What if immortality and god-like intelligence were just a few years away? Renowned futurist and former Google engineer Ray Kurzweil predicts that humanity is rapidly approaching a \.
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.
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.
