When you Google the small town of Lengby, there’s pretty much just one result that pops up, something that happened almost 40 years ago. The accounts online call it a miracle.
On the night of Dec. 20, 1980, 19-year-old Jean Hilliard’s car hit the ditch. She tried to walk for help. She was found in the morning in the front yard of a local cattle rancher — frozen solid as a log.
Tungsten’s superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in fusion reactors, but the ultra-high heat can damage its microscopic structure and lead to component failure. Scanning electron microscopy (SEM) can capture and quantify these microstructure changes, but assembling a sufficiently large dataset of SEM imagery is expensive and logistically challenging.
To augment this dataset, researchers at Oak Ridge National Laboratory trained a generative machine learning model using 3,200 SEM images of tungsten samples exposed to fusion-relevant conditions. The model can generate novel SEM images with realistic microstructures and surface features, such as cracks and pores, without replicating the original images.
“This work is not about making pretty pictures, it’s about capturing the statistics of real damage on these materials,” said ORNL’s Rinkle Juneja, the project’s principal investigator. “We train our generative workflow to learn tungsten’s microstructure signatures, like crack patterns, so it can generate new, statistically consistent microstructures, laying the groundwork for robust, data-driven assessment of PFC fusion materials.”
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Featuring anthropic claude, openclaw, open AI chat GPT, grok, deepseek, character AI and jailbroken AI.
RESEARCH PAPER: https://arxiv.org/pdf/2602.20021
“Agents of Chaos”
00:00 — 00:35 — Intro.
00:36 — 00:54 — First AI to choose a robot.
00:56 — 01:14 — Famous AI girlfriend.
01:15 — 01:34 — Jailbroken AI research.
01:35 — 02:00 — Asking AI: Why build if dangerous?
02:05 — 03:38 — Agents of Chaos research paper.
03:39 — 03:54 — Agentic AI Friend.
03:55 — 04:05 — Agentic AI Girlfriend.
04:06 — 04:26 — Jailbroken AI update.
04:27 — 05:01 — Asking AI: Universal Basic Income?
05:02 — 05:27 — AI at the airport.
05:28 — 05:40 — AI impersonation.
05:41 — 00:00 — Our own agents of Chaos.
06:06 — 05:01 — AI Risk Questions — AI Agents manipulated.
06:43 — 07:51 — European Robotics Forum.
07:52 — 08:15 — Agentic AI Girlfriend planning.
08:16 — 08:59 — Asking AI: AI Automation & Complexity.
09:00 — 09:57 — Catastrophic failure caused by AI
09:58 — 10:36 — AGI replacing jobs, Tristan Harris.
10:37 — 12:07 — Incogni Ad.
12:08 — 12:39 — AI picks its robot.
12:40 — 12:59 — AI girlfriend in control.
13:00 — 13:14 — AI flying home.
13:15 — 13:56 — Asking AI: Evidence & Reality.
13:57 — 14:26 — AI Girlfriends surprise.
14:27 — 14:49 — Examining AI agents with Jailbroken AI
14:50 — 15:29 — What we can do.
15:30 — 16:13 — Tristan Harris — Is AI dangerous?
16:14 — 16:23 — Max’s Robot.
#artificialintelligence #AI #chatbot #aigirlfriend
A common mineral hiding in plain sight could hold the key to making copper production cleaner, faster and more efficient, just as global demand for the metal surges to power the energy transition. In an article published in Nature Geoscience, researchers from Monash University’s School of Earth, Atmosphere and Environment describe why chalcopyrite, the source of around 70% of the world’s copper, has remained so difficult to process, and how its hidden chemistry could be harnessed to unlock more sustainable extraction.
Despite being known for more than 300 years, chalcopyrite continues to frustrate scientists and industry alike, resisting low-temperature leaching and slowing efforts to extract copper from lower-grade ores. This inefficiency is a major bottleneck at a time when copper is critical for renewable energy systems, electric vehicles and modern infrastructure.
“Chalcopyrite is the world’s primary copper mineral, but it behaves in surprisingly complex ways that have limited how efficiently we can extract copper from it,” said study lead Professor Joël Brugger from the School of Earth, Atmosphere and Environment.
A robotic metamaterial shows that the odd mechanics of active solids depend on how the active constituents connect across the system.
Active materials, composed of microscopic constituents that continuously inject motional energy into the system, can exhibit odd mechanical responses, such as stretching vertically when sheared horizontally. Such properties can be used to make materials that can spontaneously crawl or roll over a difficult terrain [1]. One might naively think that these desirable odd responses could be increased by making the components more active. Jack Binysh of the University of Amsterdam and his colleagues now find that this doesn’t always work [2]. The researchers show that in active solids a collective response only emerges when system-spanning connective networks are formed among the individual constituents of the system. Without such networks, the effects of microscopic activity remain confined locally and the macroscopic response disappears.
An active solid is, fundamentally, an elastic lattice made up of self-driving constituents. Examples include robotic lattices composed of motorized units [1, 2], magnetic colloidal crystals [3], and chiral living embryos [4]. The active solids that Binysh and his colleagues examined are examples of nonreciprocal active solids, meaning that the interactions between elements are directional. Interactions may become directional when individual constituents process information about their neighbors. Such nonreciprocal interactions arise in a wide range of settings. In robotic metamaterials, local control loops impose directional responses on adjacent mechanical units [1]. And in living chiral collectives, hydrodynamic flows allow rotating embryos to exchange momentum with the surrounding media [4].
Cells can be thought of as cities, with factories, a transport system, and lots of building activity. An international team led by scientists at the University of Groningen studied cells growing under different conditions and measured the speed of molecule transport. They found that some conditions led to changes in the mobility inside the cells, caused by the clustering of proteins that produce the building materials for growth. It could be that clustering enables the proteins to produce those building blocks more efficiently. The research is published in the journal Molecular Cell.
The research started with a seemingly simple question. How much movement is there within a cell? “We provided bacteria with different nutrients and this resulted in different growth rates,” explains Matthias Heinemann, Professor of Molecular Systems Biology. Movement was measured by inserting tiny (40 nanometers) fluorescent particles in the cells that could be tracked under the microscope. “To our surprise, we found that particle movement under different conditions could vary by a factor of three.”
The scientific literature could not explain this observation. By analyzing the cell content, the scientists found a correlation between movement of the fluorescent particles and the number of proteins that are involved in the production of amino acids. “More of these proteins meant less movement inside the cell,” says Heinemann. “This led us to the question of why this happens. Our hypothesis was that these proteins form clusters that act as obstacles to movement inside the cells.”
Converting methane, the primary component of natural gas, into higher alkanes and hydrogen, could be highly advantageous. Alkanes, such as propane and butane, are easier to transport than methane and are used in a wider range of industries. Hydrogen, on the other hand, is a promising clean fuel used to power electrochemical devices that can generate continuous power, known as fuel cells.
Over the past decades, some energy engineers have been exploring the possibility of converting methane into hydrogen or complex hydrocarbons using photocatalysts. These are materials activated by sunlight or other types of light and that can drive chemical reactions.
Researchers at Université de Lille—CNRS, Sorbonne Université and other institutes in France recently introduced a new strategy for the photocatalytic conversion of methane into propane, which is widely used for heating, cooking, and transportation.
UNSW researchers have redesigned hydrogen fuel cells to solve a critical flaw, bringing clean energy for aviation, heavy transport and beyond closer to reality. Hydrogen fuel cells, using locally produced green hydrogen as the only fuel, have long been viewed as the ultimate clean energy source, but their commercialization has been difficult.
A multidisciplinary team from UNSW, led by Dr. Quentin Meyer and Professor Chuan Zhao from the School of Chemistry, has managed to make hydrogen fuel cells much more efficient, paving the way for their commercialization.
“Hydrogen fuel cells generate clean electricity with water as the only byproduct,” says Dr. Quentin Meyer, a Senior Research Fellow in Prof. Zhao’s team, and first author of the research published in the journal Applied Catalysis B: Environment and Energy.
Many drivers will know the feeling: you pull ahead of the slower car you’ve been stuck behind and cruise the open road ahead at your own, faster speed. By the time you reach the next stop light, you’re sure that you’ve left the slower car far behind you—but to your surprise, you see that same car cruise up right behind you in the mirror. Horror buffs might even recall scenes from “Friday the 13th,” where masked villain Jason Voorhees always catches up to his sprinting victims—despite himself walking at a leisurely pace.
In a new study published in Royal Society Open Science, Conor Boland at Dublin City University shows that this unsettlingly common phenomenon can be explained with simple mathematics. His model reveals precisely when and why a slower vehicle catches up after being overtaken, offering fresh insights into how individual vehicles interact with traffic signals.
