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LUMA LABS KLING RUNWAY ELEVEN LABS MINIMAX.
A team of AI and robotics researchers at Carnegie Mellon University, working with a pair of colleagues from technology company NVIDIA, has developed a new model for training robots to move like human athletes.
A new study of complex systems supports a growing trend that focuses more on analyzing a system’s collective behavior rather than on trying to uncover the underlying interaction mechanisms.
When observing a flock of starlings swirling through the sky in perfect coordination—a phenomenon known as murmuration—we witness the elegant interplay of individual actions creating collective behavior. In trying to understand these mesmerizing patterns, researchers can isolate simple rules based on an individual bird’s field of vision and distance to its neighbors, but there’s always a question of whether the model is really capturing the processes behind the bird interactions (Fig. 1). The problem is a general one in complex systems research, and it comes down to distinguishing mechanisms (the rules governing interactions) from behaviors (the observable patterns that emerge).
A good way to study mechanisms versus behaviors is through representative networks of interacting individuals, or nodes. Traditionally, researchers have focused on pairwise interactions, but many systems also include higher-order interactions between multiple nodes. What impact these higher-order mechanisms have on behaviors has been unclear. Thomas Robiglio from the Central European University in Vienna and colleagues have now addressed this issue by considering networks with higher-order interactions and evaluating the resulting behaviors in terms of statistical dependencies between the node values [1]. The researchers identified higher-order behavioral signatures that—unlike their pairwise counterparts—revealed the presence of higher-order mechanisms.
Measurements of millions of galaxies suggest that dark energy changes over time and is more complicated than previously thought.
Past neuroscience and psychology studies have shown that people’s expectations of the world can influence their perceptions, either by directing their attention to expected stimuli or by reducing their sensitivity (i.e., perceptual acuity) to variations within the categories of stimuli we expect to be exposed to.
While the effects of expectations on perceptions are now well-documented, their neural underpinnings remain poorly understood.
Researchers at University of California San Diego (UC San Diego) carried out a study involving songbirds aimed at better understanding how expectation-fueled biases in perception shape brain activity and behavior.
A new study published in Proceedings of the National Academy of Sciences has turned traditional thinking on its head by highlighting the role of human interactions during the shift from hunting and gathering to farming—one of the biggest changes in human history—rather than earlier ideas that focused on environmental factors.
The transition from a hunter-gatherer foraging lifestyle, which humanity had followed for hundreds of thousands of years, to a settled farming one about 12,000 years ago has been widely discussed in popular books like “Sapiens: A Brief History of Humankind” by Yuval Noah Harari.
Researchers from the University of Bath, the Max Planck Institute for Evolutionary Anthropology in Germany, the University of Cambridge, UCL, and others have developed a new mathematical model that challenges the traditional view that this major transition was driven by external factors, such as climate warming, increased rainfall, or the development of fertile river valleys.
The ice-giant planet Uranus, which travels around the sun tipped on its side, is a weird and mysterious world. Now, in an unprecedented study spanning two decades, researchers using NASA’s Hubble Space Telescope have uncovered new insights into the planet’s atmospheric composition and dynamics. This was possible only because of Hubble’s sharp resolution, spectral capabilities, and longevity.
The team’s results will help astronomers to better understand how the atmosphere of Uranus works and responds to changing sunlight. These long-term observations provide valuable data for understanding the atmospheric dynamics of this distant ice giant, which can serve as a proxy for studying exoplanets of similar size and composition.
When Voyager 2 flew past Uranus in 1986, it provided a close-up snapshot of the sideways planet. What it saw resembled a bland, blue-green billiard ball. By comparison, Hubble chronicled a 20-year story of seasonal changes from 2002 to 2022. Over that period, a team led by Erich Karkoschka of the University of Arizona, and Larry Sromovsky and Pat Fry from the University of Wisconsin used the same Hubble instrument, STIS (the Space Telescope Imaging Spectrograph), to paint an accurate picture of the atmospheric structure of Uranus.
Researchers at the Institute of Automation of the Chinese Academy of Sciences have developed a compact, battery-powered brain stimulation device capable of delivering therapeutic magnetic pulses while a person is walking or performing everyday activities.
Repetitive transcranial magnetic stimulation is used to treat conditions such as depression, stroke-related motor impairment, and other neuropsychiatric disorders. It is also used in cognitive and motor function research.
Existing systems need to be plugged into a power supply and have bulky designs meant for stationary use in clinical settings. These limitations prevent stimulation during natural movement, such as standing and walking, making at-home or on-the-go treatments impractical.
People breathing contaminated air over the course of years are at greater risk of developing numerous diseases. This is thought to be due to highly reactive components in particulate matter, which affect biological processes in the body. However, researchers from the University of Basel, Switzerland, have now shown that precisely these components disappear within hours and that previous measurements therefore completely underestimate the quantities in which they are present.
From chronic respiratory problems to cardiovascular diseases, diabetes and dementia, health damage caused by particulate matter air pollution is wide-ranging and serious. The World Health Organization (WHO) estimates that over six million deaths a year are caused by increased exposure to particulate matter.
The chemical composition of these tiny particles in the air, which come from a wide range of both anthropogenic and natural sources, is highly complex. Which particles trigger which reactions and long-term diseases in the body is the subject of intensive research.
Europe’s physics lab CERN is planning to build a particle-smasher even bigger than its Large Hadron Collider to continue searching for answers to some of the universe’s tiniest yet most profound mysteries.
The Future Circular Collider (FCC) has not yet received a political green light or funding. Even if approved, the vast project would not start operations until the 2040s—or be completed until the end of the century.
CERN’s Large Hadron Collider (LHC), which famously discovered the “God particle” Higgs boson and is currently the world’s powerful particle accelerator, is expected to have run its course by the 2040s.
