Lifeboat Foundation

It’s a stormy holiday weekend, and you’ve just received the last notification you want in the busiest travel week of the year: the first leg of your flight is significantly delayed.

You might expect this means you’ll be sitting on hold with airline customer service for half an hour. But this time, the process looks a little different: You have a brief text exchange with the airline’s AI chatbot, which quickly assesses your situation and places you in a priority queue. Shortly after, a human agent takes over, confirms the details, and gets you rebooked on an earlier flight so you can make your connection. You’ll be home in time to enjoy mom’s pot roast.

In 2018, researchers reported that they had managed to get a coral larva to survive freezing and thawing for the first time. The scientists had added gold nanoparticles to their antifreeze to help the corals warm evenly during reheating. However, the thawed larvae were unable to settle and develop into adults. Instead, they kept swimming until they died.

When Narida began her experiments with hood corals in 2021, she included gold in her antifreeze recipe and combined several different antifreeze chemicals to reduce the solution’s toxicity. To thaw the animals quickly and minimize damage, Narida used a high-powered laser designed for welding jewelry. Then, she carefully washed the antifreeze away with seawater, rehydrating the corals. In the end, a whopping 11 percent of larvae in the experiment survived thawing, then settled, and developed into adults.

Leandro Godoy, a coral cryobiologist at the Federal University of Rio Grande do Sul in Brazil, is impressed by how many larvae survived after settling. “It’s a huge step,” he says, considering that, in the wild, only about five percent of corals make it that far.

Artificial intelligence already wears multiple hats in the workplace, whether its writing ad copy, handling customer support requests, or filtering job applications. As the technology continues its ascent and capabilities, the notion of corporations managed or owned by AI becomes less far-fetched. The legal framework already exists to allow “Zero-member LLCs.”

How would an AI-operated LLC be treated under the law, and how would AI respond to legal responsibilities or consequences as the owner/manager of an LLC? These questions speak to an unprecedented challenge facing lawmakers: the regulation of a nonhuman entity with the same (or better) cognitive capabilities as humans that, if left unresolved or poorly addressed, could slip beyond human control.

“Artificial intelligence and interspecific law,” an article by Daniel Gervais of Vanderbilt Law School and John Nay of The Center for Legal Informatics at Stanford University, and a Visiting Scholar at Vanderbilt, argues for more AI research on the legal compliance of nonhumans with human-level intellectual capacity.

Data assimilation is the combination of the latest observations with a short-range forecast to obtain the best possible estimate of the current state of the Earth system. Machine learning can contribute to it by optimizing the use of satellite observations.

Obtaining the best possible estimate of the current state of the Earth system, known as the analysis, is extremely important for weather forecasting. That’s because the analysis serves as the initial conditions of forecasts.

To use the latest observations, we rely on a vast system of instruments that regularly measure aspects of the atmosphere and other components of the Earth system. Over the last few decades, satellite observations have become increasingly important.

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We live in an age of exoplanet discovery. One thing we’ve learned is not to be surprised by the kinds of exoplanets we keep discovering. We’ve discovered planets where it might rain glass or even iron, planets that are the rocky core remnants of gas giants stripped of their atmospheres, and drifting rogue planets untethered to any star.

Now, astronomers have uncovered evidence of an exoplanet in a circumbinary disk around a binary star. The remarkable thing about this discovery is that the disk is in a polar configuration. That means the exoplanet moves around its binary star in a circumpolar orbit, and this is the first one scientists have found.

AC Herculis (AC Her) is a binary star about 4,200 light-years away. The primary star is well-studied, while its partner is invisible. It has a polar circumbinary disk, which is unusual but not unheard of. In a new paper, a team of researchers presents evidence for the polar circumbinary exoplanet.

About 400 earthquakes have rumbled under Mount St. Helens since mid-July, the largest chain of shakes since the volcano finished erupting in 2008, the U.S. Geological Survey reported last week.

Small magnitude earthquakes, detected only by sensitive equipment, signal a volcano’s “recharging” as magma flows through chambers and cracks deep under the ground, said Wes Thelen, U.S. Geological Survey Cascades Volcano Observatory geophysicist and seismologist.

Between late August and early September, scientists observed 40 to 50 earthquakes per week located between 2.5 to 5 miles below the crater floor, before recently dwindling to 30. To compare, Mount St. Helens averaged roughly 11 quakes per month since 2008.

Machine learning (ML) is now mission critical in every industry. Business leaders are urging their technical teams to accelerate ML adoption across the enterprise to fuel innovation and long-term growth. But there is a disconnect between business leaders’ expectations for wide-scale ML deployment and the reality of what engineers and data scientists can actually build and deliver on time and at scale.

In a Forrester study launched today and commissioned by Capital One, the majority of business leaders expressed excitement at deploying ML across the enterprise, but data scientist team members said they didn’t yet have all the necessary tools to develop ML solutions at scale. Business leaders would love to leverage ML as a plug-and-play opportunity: “just input data into a black box and valuable learnings emerge.” The engineers who wrangle company data to build ML models know it’s far more complex than that. Data may be unstructured or poor quality, and there are compliance, regulatory, and security parameters to meet.

NASA’s Lucy mission will soon have its first asteroid encounter as the spacecraft travels through deep space en route to Jupiter’s orbit. But before the spacecraft passes 265 miles (425 kilometers) from the surface of the small asteroid Dinkinesh, researchers have used 13-year-old infrared data from NASA’s Wide-field Infrared Survey Explorer (WISE) to support the mission’s flyby. Their new study provides updated estimates of the asteroid’s size and albedo—a measurement of surface reflectivity—that could help scientists better understand the nature of some near-Earth objects.

Located between Mars and Jupiter, the main asteroid belt is home to most asteroids in our solar system, including Dinkinesh, which is following an orbit around the sun that places it near Lucy’s path. The Lucy mission is using the Dinkinesh encounter as an opportunity to test systems and procedures that are designed to keep the asteroid within the science instruments’ fields of view as the spacecraft flies past at 10,000 mph (4.5 kilometers per second). This will help the team prepare for the mission’s primary objective: investigating the Jupiter Trojan asteroids, a population of primitive small bodies orbiting in tandem with Jupiter.

In the new study, published in the Astrophysical Journal Letters, University of Arizona researchers used observations made by the WISE spacecraft, which serendipitously scanned Dinkinesh in 2010 during its prime mission. Managed by NASA’s Jet Propulsion Laboratory in Southern California, WISE launched on Dec. 14, 2009, to create an all-sky infrared map of the universe.