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If the first image of a black hole looked like a fuzzy doughnut, this one is a thin onion ring.

Using a machine learning technique, scientists have sharpened the portrait of the supermassive black hole at the center of galaxy M87, revealing a thinner halo of glowing gas than seen previously.

In 2019, scientists with the Event Horizon Telescope unveiled an image of M87s black hole (SN: 4/10/19). The picture was the first ever taken of a black hole and showed a blurry orange ring of swirling gas silhouetted by the dark behemoth. The new rings thickness is half that of the original, despite being based on the same data, researchers report April 13 in the Astrophysical Journal Letters.

The Event Horizon Telescope takes data using a network of telescopes across the globe. But that technique leaves holes in the data. Since we cant just cover the entire Earth in telescopes, what that means is that there is some missing information, says astrophysicist Lia Medeiros of the Institute for Advanced Study in Princeton, N.J. We need to have an algorithm that can fill in those gaps.

Previous analyses had used certain assumptions to fill in those gaps, such as preferring an image that is smooth. But the new technique uses machine learning to fill in those gaps based on over 30,000 simulated images of matter swirling around a black hole, creating a sharper image.

In the future, this technique could help scientists get a better handle on the black holes mass and perform improved tests of gravity and other studies of black hole physics.

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Physics writer Emily Conover has a Ph.D. in physics from the University of Chicago. She is a two-time winner of the D.C. Science Writers Association Newsbrief award.

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The first black hole portrait got sharper thanks to machine learning - Science News Magazine

Humanity'sfirst image of a black hole has gotten a makeover.

The iconic picture of the supermassive black hole at the center of Messier 87,a giantgalaxy sitting 53 million light-years from Earth in the "nearby" Virgocluster,was first released in 2019. The M87 black hole appeared as a flaming, fuzzy doughnut-like object emerging from a darkbackdrop but now we have a sharper look.

The new image,published Thursday in a Astrophysical Journal Lettersstudy,gives us a refined look at the black hole which now looks like a skinner, bright orange ring with a clearer dark center.

According to the study, the image was reconstructed using new machine-learningtechnology called PRIMO. Scientists relied on the same data that was used to create the 2019 image originally obtained by anEvent Horizon Telescope collaboration in 2017.

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In 2017, a network of radio telescopes around the world formed "an Earth-sized virtual telescope with the power and resolution capable of observing the 'shadow'of a black holes event horizon," the National Science Foundation's NOIRLab notes.

While this allowed scientists to see incredible details, gaps remained. PRIMO has helped fill in the missing pieces.

"Since we cannot study black holes up close, the detail in an image plays a critical role in our ability to understand its behavior,"Lia Medeiros, an astrophysicist at the Institute for Advanced Study inNew Jersey andlead author of Thursday's study, said in theNOIRLab press release.

"The width of the ring in the image is now smaller by about a factor of two, which will be a powerful constraint for our theoretical models and tests of gravity."

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The machine learning technique also brings the possibility of further work on other images of celestial objects, NOIRLab notes includingSagittarius A*,the black hole at the center of our Milky Way galaxy. Astronomers revealedan image ofSagittarius A* in May 2022, which was also captured usingEHT data.

"The 2019 image was just the beginning,"Medeiros said. "If a picture is worth a thousand words, the data underlying that image have many more stories to tell. PRIMO will continue to be a critical tool in extracting such insights."

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Contributing: Doyle Rice, USA TODAY. The Associated Press.

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Iconic first black hole picture is now sharper, thanks to new machine-learning tech - USA TODAY

NEW YORK (AP) The first image of a black hole captured four years ago revealed a fuzzy, fiery doughnut-shaped object. Now, researchers have used artificial intelligence to give that cosmic beauty shot a touch-up.

The updated picture, published Thursday in the Astrophysical Journal Letters, keeps the original shape, but with a skinnier ring and a sharper resolution.

The image released in 2019 gave a peek at the enormous black hole at the center of the M87 galaxy, 53 million light-years from Earth. A light-year is 5.8 trillion miles. It was made using data gathered by a network of radio telescopes around the world, showing swirling light and gas.

But even with many telescopes working together, gaps remained in the data. In the latest study, scientists relied on the same data and used machine learning to fill in the missing pieces.

The resulting picture looks similar to the original, but with a thinner doughnut and a darker center, researchers said.

For me, it feels like were really seeing it for the first time, said lead author Lia Medeiros, an astrophysicist at the Institute for Advanced Study in New Jersey.

By having a clearer picture, researchers hope to learn more about the black holes properties and gravity in future studies. And Medeiros said the team plans to use machine learning on other images of celestial objects, including possibly the black hole at the center of our Milky Way galaxy.

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The Associated Press Health and Science Department receives support from the Howard Hughes Medical Institutes Science and Educational Media Group. The AP is solely responsible for all content.

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First image of a black hole gets a makeover with AI - The Associated Press

A team of researchers has shown off a new machine-learning technique by enhancing the Event Horizon Telescope's images of a supermassive black hole at the center of a galaxy 55 million light-years from Earth. The technique, called PRIMO, enhances the fidelity and sharpness of radio interferometry images.

The Event Horizon Telescope (EHT), responsible for the original images, is an international collaboration capturing images of black holes using a virtual Earth-sized telescope. As incredible and iconic as the original images of the supermassive black hole at the center of Messier 87 were four years ago, they were still fuzzy in appearance. Researchers using PRIMO, which stands for principal-component interferometric modeling, have been able to give a bit of clarity to the original images.

Medeiros added the that width of the ring in the new image is smaller by around a factor of two, which she says will be "a powerful constraint" for theoretical models and tests of gravity.

By applying PRIMO to the original EHT images, computers scoured over 30,000 high-fidelity simulated images of gas accreting onto a black hole in order to find common patterns within the images. Those results were then "blended to provide a highly accurate representation of the EHT observations." The team then confirmed the newly rendered images were consistent with the EHT data and with theoretical expectations.

According to Medeiros, this is just the beginning for PRIMO. "If a picture is worth a thousand words, the data underlying that image have many many more stories to tell. PRIMO will continue to be a critical tool in extracting such insights."

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Fuzzy First Image Of A Supermassive Black Hole Gets A HIgh-Fidelity AI Makeover - Hot Hardware

Amazon President & CEO Andy Jassy attends the Los Angeles Premiere of Amazon Prime Video's "The Lord Of The Rings: The Rings Of Power" at The Culver Studios on August 15, 2022 in Culver City, California. (Photo by Kevin Winter/Getty Images)

Amazon CEO Andy Jassy signaled confidence that the company will get costs under control in his annual shareholder letter, where he also noted the tech giant was spending heavily on AI tools that have gained popularity in recent months.

In the letter, Jassy described 2022 as one of the harder macroeconomic years in recent memory and detailed the steps Amazon had taken to trim costs, such as shuttering its health care initiative Amazon Care and some stores across the country. The company had also slashed 27,000 corporate roles since the fall, marking the biggest rounds of layoffs in its history.

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There are a number of other changes that weve made over the last several months to streamline our overall costs, and like most leadership teams, well continue to evaluate what were seeing in our business and proceed adaptively, Jassy wrote.

The companys profitable cloud computing unit Amazon Web Services also faces short-term headwinds right now, despite growing 29% year-over-year in 2022 on a $62 billion revenue base, Jassy wrote. He noted challenges for the unit stem from companies spending more cautiously in the face of challenging current macroeconomic conditions.

Despite the cuts and turbulent times, Jassy said he strongly believes Amazon's best days are in front of us.

The Seattle company will continue to invest in specialized chips most used for machine learning, its advertising business as well as generative AI tools. The tools are part of a new generation of machine-learning systems that can converse, generate readable text on demand and produce novel images and video based on what theyve learned from a vast database of digital books and online text.

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Lets just say that LLMs and Generative AI are going to be a big deal for customers, our shareholders, and Amazon, Jassy wrote, using the abbreviated version of Large Language Models, or AI that can mimic human writing styles based on data they've ingested.

On Thursday, Amazon also announced several new services that will allow developers to build their own AI tools on its cloud infrastructure.

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