The University of Surrey has built an artificial intelligence (AI) model that identifies chemical compounds that promote healthy aging—paving the way towards pharmaceutical innovations that extend a person’s lifespan.
Our customers are putting Spot to work in nuclear environments, increasing safety and efficiency at their their electrical production facilities. Learn how thre… See More.
Spot is going to work in nuclear environments, increasing the safety, efficiency, and cost-effectiveness of their electrical production facilities.
There are many reasons for drones to be quick. The professional drone racing circuit aside, speed bodes well when you are searching for survivors on a disaster site, or delivering cargo, or even inspecting critical infrastructure. But how do you get something done in the shortest possible time with limited battery life when you have to navigate through obstacles, changing speeds, and altitude? You use an algorithm.
In the depths of space, there are celestial bodies where extreme conditions prevail: Rapidly rotating neutron stars generate super-strong magnetic fields. And black holes, with their enormous gravitational pull, can cause huge, energetic jets of matter to shoot out into space. An international physics team with the participation of the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) has now proposed a new concept that could allow some of these extreme processes to be studied in the laboratory in the future: A special setup of two high-intensity laser beams could create conditions similar to those found near neutron stars. In the discovered process, an antimatter jet is generated and accelerated very efficiently. The experts present their concept in the journal Communications Physics.
The basis of the new concept is a tiny block of plastic, crisscrossed by micrometer-fine channels. It acts as a target for two lasers. These simultaneously fire ultra-strong pulses at the block, one from the right, the other from the left — the block is literally taken by laser pincers. “When the laser pulses penetrate the sample, each of them accelerates a cloud of extremely fast electrons,” explains HZDR physicist Toma Toncian. “These two electron clouds then race toward each other with full force, interacting with the laser propagating in the opposite direction.” The following collision is so violent that it produces an extremely large number of gamma quanta — light particles with an energy even higher than that of X-rays.
The swarm of gamma quanta is so dense that the light particles inevitably collide with each other. And then something crazy happens: According to Einstein’s famous formula E=mc2, light energy can transform into matter. In this case, mainly electron-positron pairs should be created. Positrons are the antiparticles of electrons. What makes this process special is that “very strong magnetic fields accompany it,” describes project leader Alexey Arefiev, a physicist at the University of California at San Diego. “These magnetic fields can focus the positrons into a beam and accelerate them strongly.” In numbers: Over a distance of just 50 micrometers, the particles should reach an energy of one gigaelectronvolt (GeV) — a size that usually requires a full-grown particle accelerator.
Interesting properties of carbon nanotubes prompt a search for diverse inorganic nanotubes. Here, the authors report a supertetrahedral chalcogenide cluster-based semiconducting nanotube array that exhibits high electric conductivity and oriented photoconductive behavior.
One of the most important open questions in science is how our consciousness is established. In the 1990s, long before winning the 2020 Nobel Prize in Physics for his prediction of black holes, physicist Roger Penrose teamed up with anaesthesiologist Stuart Hameroff to propose an ambitious answer.
They claimed that the brain’s neuronal system forms an intricate network and that the consciousness this produces should obey the rules of quantum mechanics —the theory that determines how tiny particles like electrons move around. This, they argue, could explain the mysterious complexity of human consciousness.
Gain-of-function experiments aim to increase the transmissibility and virulence of existing viruses, making them deadlier for humans. The stated purpose is to better understand pathogens and to develop vaccines for possible future pandemics. Critics say this type of research is extremely dangerous and should be banned or regulated. They claim it has not prevented any pandemics to date, and that the COVID-19 outbreak might be the result of an accidental release from a lab that was conducting gain-of-function research.
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DeepMind and EMBL release the most complete database of predicted 3D structures of human proteins.
Partners use AlphaFold, the AI system recognized last year as a solution to the protein structure prediction problem, to release more than 350000 protein structure predictions including the entire human proteome to the scientific community.
DeepMind today announced its partnership with the European Molecular Biology Laboratory (EMBL), Europe’s flagship laboratory for the life sciences, to make the most complete and accurate database yet of predicted protein structure models for the human proteome. This will cover all ~20000 proteins expressed by the human genome, and the data will be freely and openly available to the scientific community. The database and artificial intelligence system provide structural biologists with powerful new tools for examining a protein’s three-dimensional structure, and offer a treasure trove of data that could unlock future advances and herald a new era for AI-enabled biology.
Brain–computer interfaces (BCIs) provide bidirectional communication between the brain and output devices that translate user intent into function. Among the different brain imaging techniques used to operate BCIs, electroencephalography (EEG) constitutes the preferred method of choice, owing to its relative low cost, ease of use, high temporal resolution, and noninvasiveness. In recent years, significant progress in wearable technologies and computational intelligence has greatly enhanced the performance and capabilities of EEG-based BCIs (eBCIs) and propelled their migration out of the laboratory and into real-world environments. This rapid translation constitutes a paradigm shift in human–machine interaction that will deeply transform different industries in the near future, including healthcare and wellbeing, entertainment, security, education, and marketing. In this contribution, the state-of-the-art in wearable biosensing is reviewed, focusing on the development of novel electrode interfaces for long term and noninvasive EEG monitoring. Commercially available EEG platforms are surveyed, and a comparative analysis is presented based on the benefits and limitations they provide for eBCI development. Emerging applications in neuroscientific research and future trends related to the widespread implementation of eBCIs for medical and nonmedical uses are discussed. Finally, a commentary on the ethical, social, and legal concerns associated with this increasingly ubiquitous technology is provided, as well as general recommendations to address key issues related to mainstream consumer adoption.
One of the holy grails of computer science is the development of an AI that can extrapolate from data. A team of researchers from the University of Southern California has announced the development of something profoundly new — a model for an AI with imagination.
Understanding “why” may be the key to unlocking an AI’s imagination.
