A new AI framework inspired by human memory could make machines more efficient, adaptive, and capable of reasoning. A recent paper published in the journal Engineering presents a novel approach to artificial intelligence by modeling it after how human memory functions. The research aims to overco
Physicists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and Stony Brook University (SBU) have shown that particles produced in collimated sprays called jets retain information about their origins in subatomic particle smashups. The study was recently published as an Editor’s Suggestion in the journal Physical Review Letters.
“Despite extensive research, the connection between a jet’s initial conditions and its final particle distribution has remained elusive,” said Charles Joseph Naim, a research associate at the Center for Frontiers in Nuclear Science (CFNS) in SBU’s Department of Physics and Astronomy. “This study, for the first time, establishes a direct connection between the ‘entanglement entropy’ at the earliest stage of jet formation and the particles that emerge as a jet evolves.”
The evidence comes from an analysis of jet particles emerging from proton-proton collisions captured by the ATLAS experiment at the Large Hadron Collider, a 17-mile-circumference circular collider located at CERN, the European Organization for Nuclear Research. In these powerful collisions, the individual building blocks of the colliding protons, known as quarks and gluons, scatter off one another and sometimes get knocked free with enormous amounts of energy. But quarks can’t stay free for long. They and the gluons that normally hold them together immediately begin to split and reconnect through a branching process called fragmentation. The result is the formation of many new composite particles made of pairs or triplicates of quarks—collectively known as hadrons—that spray out of the collision in a coordinated way, that is, as a jet.
When exploring their surroundings, communicating with others and expressing themselves, humans can perform a wide range of body motions. The ability to realistically replicate these motions, applying them to human and humanoid characters, could be highly valuable for the development of video games and the creation of animations, content that can be viewed using virtual reality (VR) headsets and training videos for professionals.
Researchers at Peking University’s Institute for Artificial Intelligence (AI) and the State Key Laboratory of General AI recently introduced new models that could simplify the generation of realistic motions for human characters or avatars. The work is published on the arXiv preprint server.
Their proposed approach for the generation of human motions, outlined in a paper presented at CVPR 2025, relies on a data augmentation technique called MotionCutMix and a diffusion model called MotionReFit.
A combined team of metallurgists, materials scientists and engineers from the Chinese Academy of Sciences, Shandong University and the Georgia Institute of Technology has developed a way to make stainless steel more resistant to metal fatigue. In their study published in the journal Science, the group developed a new twisting technique that functions as an “anti-crash wall” in the steel, giving it much more strength and resistance to cyclic creep.
Metal can experience fatigue when bent many times, leading to breaking. When this occurs in critical applications, it can result in catastrophic accidents such as bridge failures. Because of that, scientists have for many years been working to reduce or prevent stress levels in metals. In this new effort, the researchers found a way to dramatically improve the strength of a type of stainless steel while also boosting its resistance to what is known as cycle creep, where fatigue occurs due to ratcheting, a form of repeated bending.
The new technique involved repeatedly twisting a sample of 304 austenitic stainless steel in a machine in certain ways. This led to spatially grading the cells that made up the metal, resulting in the build-up of what the team describes as a submicron-scale, three-dimensional, anti-crash wall. Under a microscope, the researchers found an ultra-fine, sub-10 nanometer, coherent lamellar structure that slowed dislocation by preventing stacking faults.
A photonic processor capable of running advanced artificial intelligence models with near-electronic precision is introduced, marking a substantial step towards post-transistor computing technologies.
Marines with 7th Communication Battalion are conducting tests with the new free space optics communications system at Camp Hansen, Okinawa, Japan. The highly secured FSO system employs an infrared
Colossal Biosciences CEO Ben Lamm says the critics who call his dire wolves designer dogs are missing the point: ‘It’s a stupid argument.’
Here in this video today we will explore something that has been demanded by viewers of the channel for quite sometime, the Xeelee rings, one of the largest megastructures in fiction. We first have to take a look at the universe we are discussing about. So, The Xeelee Sequence is a series of science fiction novels and short stories by British author Stephen Baxter, exploring the grand scale of the universe from the Big Bang to its ultimate end. The series follows humanity’s evolution over billions of years, its conflicts with alien species, and the mysterious, hyper-advanced Xeelee, who are engaged in a cosmic war against the enigmatic dark matter entities known as the Photino Birds. The books blend hard science fiction with cosmic wonder, delving into themes of time travel, black hole physics, alternate universes, and the limits of human potential. Major works in the series include \.
To grow, cancer tumors must hijack the immune system for their needs. One of the main tricks that most tumors use is to manipulate a type of immune cell called a macrophage, causing it to protect the tumor from the rest of the immune system, recruit blood vessels and help the cancer spread to other tissues.
Now researchers in Prof. Ido Amit’s lab at the Weizmann Institute of Science have used state-of-the-art gene editing and single-cell and AI technologies to identify a master switch that turns macrophages into cancer helpers.
Based on this discovery, the team developed a new therapy that was shown to be effective in mice with bladder tumors, one of the most common types of cancer in humans and one for which only limited therapeutic innovations are currently available. The discovery is presented in a paper published in the journal Cancer Cell.
