Galactic gravity can dramatically impact wide binary stars, pushing them towards unexpected mergers or collisions.
The detection of gravitational waves.
Gravitational waves are distortions or ripples in the fabric of space and time. They were first detected in 2015 by the Advanced LIGO detectors and are produced by catastrophic events such as colliding black holes, supernovae, or merging neutron stars.
A New Phenomenon in Markarian 817
Astronomers have observed a supermassive black hole in the galaxy Markarian 817 (Mrk 817), located 430 million light-years away in the constellation Draco, unleashing ultra-fast winds that are disrupting its host galaxy. Detected using ESA’s XMM-Newton space telescope, this discovery marks the first instance of such winds emerging from a moderately feeding black hole, defying previous expectations.
That’s the word from a new set of predictions for the decade ahead issued by Accenture, which highlights how our future is being shaped by AI-powered autonomy. By 2030, agents — not people — will be the “primary users of most enterprises’ internal digital systems,” the study’s co-authors state. By 2032, “interacting with agents surpasses apps in average consumer time spent on smart devices.”
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This heralds a moment of transition, what the report’s primary author, Accenture CTO Karthik Narain, calls the Binary Big Bang. “When foundation models cracked the natural language barrier,” writes Narain, “they kickstarted a shift in our technology systems: how we design them, use them, and how they operate.”
Researchers led by Nanyang Technological University, Singapore (NTU Singapore) have developed a breakthrough technique that could lay the foundations for detecting the universe’s “dark matter” and bring scientists closer than before to uncovering the secrets of the cosmos.
The things we can see on Earth and in space— visible matter like rocks and stars—make up only a small portion of the universe, as scientists believe that 85% of matter in the cosmos comprises invisible dark matter. This mysterious substance is said to be the invisible glue holding galaxies together. Finding it could help us understand cosmic phenomena that cannot be explained solely by the matter we see.
But proving the existence of dark matter is a herculean task. As its name suggests, dark matter is “dark,” meaning it does not normally emit or reflect light, carries no electric charge and interacts extremely weakly with normal matter, making it undetectable with conventional scientific instruments.
In October 2022, scientists detected the explosive death of a star 2.4 billion light-years away that was brighter than any ever recorded.
As the star’s core collapsed down into a black hole, the gamma-ray burst emitted by the star – an event named GRB 221009A – erupted with energies of up to 18 teraelectronvolts. Gamma-ray bursts are already the brightest explosions our Universe can produce; but GRB 221009A was an absolute record-smasher, earning it the moniker “the BOAT” – Brightest Of All Time.
There is, however, something wrong with the picture, according to a team of astrophysicists led by Giorgio Galanti of the National Institute for Astrophysics (INAF) in Italy. Based on cutting-edge models of the Universe, we shouldn’t be able to see photons more powerful than 10 teraelectronvolts in data from the Large High Altitude Air Shower Observatory (LHAASO) that made the detection.
The enigmatic galaxy AGC 114,905 spans vast distances but contains 100 times fewer stars than the Milky Way.
The AI behavior models controlling how robots interact with the physical world haven’t been advancing at the crazy pace that GPT-style language models have – but new multiverse ‘world simulators’ from Nvidia and Google could change that rapidly.
There’s a chicken-and-egg issue slowing things down for AI robotics; large language model (LLM) AIs have enjoyed the benefit of massive troves of data to train from, since the Internet already holds an extraordinary wealth of text, image, video and audio data.
But there’s far less data for large behavior model (LBM) AIs to train on. Robots and autonomous vehicles are expensive and annoyingly physical, so data around 3D representations of real-world physical situations is taking a lot longer to collect and incorporate into AI models.
The LUX ZEPLIN (LZ) Dark Matter experiment is a large research effort involving over 200 scientists and engineers at 40 institutions worldwide. Its key objective is to search for weakly interacting massive particles (WIMPs) by analyzing data collected by the LZ detector, situated at the Sanford Underground Research Facility in South Dakota.
The LZ Collaboration recently released the results of the first experimental run of the LZ dark matter experiment. These results, published in Physical Review Letters, set new constraints on the interactions between dark matter and other particles, which could inform future searches for weakly-interacting dark matter candidates.
“There is no reason to believe that dark matter will interact with regular matter in the simplest way, so it is important to consider more complex interactions,” Sam Eriksen, co-author of the paper, told Phys.org.
