Lifeboat Foundation

In a study published recently in Advanced Intelligent Systems, researchers from Queen Mary University of London have made significant advancements in the field of bionics with the development of a new type of electric variable-stiffness artificial muscle that possesses self-sensing capabilities. This innovative technology has the potential to revolutionize soft robotics and medical applications.

Muscle contraction hardening is not only essential for enhancing strength but also enables rapid reactions in living organisms. Taking inspiration from nature, the team of researchers at QMUL’s School of Engineering and Materials Science has successfully created an artificial muscle that seamlessly transitions between soft and hard states while also possessing the remarkable ability to sense forces and deformations.

Dr. Ketao Zhang, a Lecturer at Queen Mary and the lead researcher, explains the importance of variable stiffness technology in artificial muscle-like actuators. “Empowering robots, especially those made from flexible materials, with self-sensing capabilities is a pivotal step towards true bionic intelligence,” says Dr. Zhang.

New glasses use sonar sensing technology and AI to allow users to control devices via silent, mouthed commands.

A powerful 7.2-magnitude earthquake struck near the Alaska Peninsula late Saturday.

Preliminary data placed the quake about 55 miles southwest of Sand Point, Alaska, the National Weather Service said. It had initially been measured at a magnitude of 7.4, the United States Geological Survey said on Twitter.

It struck at about 10:48 p.m. local time. In Kodiak, Alaska, sirens sounded late at night, according to a video posted on social media.

Swiss-Mile, a Swiss cutting-edge startup, created a robot-transformer that can perform a variety of tasks on it’s own.

For many, the word “crystals” conjures images of shimmering suncatchers that create a prism of rainbow colors or semi-transparent stones thought to possess healing abilities. But in the realm of science and engineering, crystals take on a more technical definition. They’re perceived as materials whose components – be it atoms, molecules, or nanoparticles –are arranged regularly in space. In other words, crystals are defined by the regular arrangement of their constituents. Familiar examples include diamonds, table salt, and sugar cubes.

Astronomers at the University of Sydney have shown that a small, faint star is the coldest on record to produce emission at radio wavelength.

The ‘ultracool brown dwarf’ examined in the study is a ball of gas simmering at about 425 degrees centigrade—cooler than a typical campfire—without burning nuclear fuel.

By contrast, the surface temperature of the sun, a nuclear inferno, is about 5,600 degrees.

During today’s press conference in which Hollywood actors confirmed that they were going on strike, Duncan Crabtree-Ireland, SAG-AFTRA’s chief negotiator, revealed a proposal from Hollywood studios that sounds ripped right out of a Black Mirror episode.

In a statement about the strike, the Alliance of Motion Picture and Television Producers (AMPTP) said that its proposal included “a groundbreaking AI proposal that protects actors’ digital likenesses for SAG-AFTRA members.”

Gero, an AI-driven biotech focused on aging and longevity, has demonstrated the feasibility of applying quantum computing for drug design and generative chemistry, which now offers significant promise for the future of healthcare. The research, published in Scientific Reports, outlines how a hybrid quantum-classical machine-learning model was used to interface between classical and quantum computational devices with the goal of generating novel chemical structures for potential drugs—an industry first.

The research paper follows in the wake of recent advancements from Gero, which sparked vigorous discussion among longevity experts in the scientific community when a story was published in Popular Mechanics that asserted humans can stop—but not fully reverse—aging. Earlier this year, Gero announced a target discovery deal with Pfizer, whereby Gero’s machine-learning technology platform is being applied to discover potential therapeutic targets for fibrotic diseases using large-scale human data.

In this new line of research, the team explored whether a hybrid generative AI system—a deep neural network working in conjunction with commercially available quantum hardware—could suggest unique chemical structures that are synthetically feasible and possess drug-like properties.

We introduce a novel Natural Language Processing (NLP) task called guilt detection, which focuses on detecting guilt in text. We identify guilt as a complex and vital emotion that has not been previously studied in NLP, and we aim to provide a more fine-grained analysis of it. To address the lack of publicly available corpora for guilt detection, we created VIC, a dataset containing 4,622 texts from three existing emotion detection datasets that we binarized into guilt and no-guilt classes. We experimented with traditional machine learning methods using bag-of-words and term frequency-inverse document frequency features, achieving a 72% f1 score with the highest-performing model. Our study provides a first step towards understanding guilt in text and opens the door for future research in this area.