In early July, as Hurricane Beryl churned through the Caribbean, a top European weather agency predicted a range of final landfalls, warning that that Mexico was most likely. The alert was based on global observations by planes, buoys and spacecraft, which room-size supercomputers then turned into forecasts.

That same day, experts running artificial intelligence software on a much smaller computer predicted landfall in Texas. The forecast drew on nothing more than what the machine had previously learned about the planet’s atmosphere.

Four days later, on July 8, Hurricane Beryl slammed into Texas with deadly force, flooding roads, killing at least 36 people and knocking out power for millions of residents. In Houston, the violent winds sent trees slamming into homes, crushing at least two of the victims to death.

The Texas prediction offers a glimpse into the emerging world of A.I. weather forecasting, in which a growing number of smart machines are anticipating future global weather patterns with new speed and accuracy. In this case, the experimental program was GraphCast, created in London by DeepMind, a Google company. It does in minutes and seconds what once took hours.

“This is a really exciting step,” said Matthew Chantry, an A.I. specialist at the European Center for Medium-Range Weather Forecasts, the agency that got upstaged on its Beryl forecast. On average, he added, GraphCast and its smart cousins can outperform his agency in predicting hurricane paths.

In general, superfast A.I. can shine at spotting dangers to come, said Christopher S. Bretherton, an emeritus professor of atmospheric sciences at the University of Washington. For treacherous heats, winds and downpours, he said, the usual warnings will be “more up-to-date than right now,” saving untold lives.

Rapid A.I. weather forecasts will also aid scientific discovery, said Amy McGovern, a professor of meteorology and computer science at the University of Oklahoma who directs an A.I. weather institute. She said weather sleuths now use A.I. to create thousands of subtle forecast variations that let them find unexpected factors that can drive such extreme events as tornadoes.

“It’s letting us look for fundamental processes,” Dr. McGovern said. “It’s a valuable tool to discover new things.”

Importantly, the A.I. models can run on desktop computers, making the technology much easier to adopt than the room-size supercomputers that now rule the world of global forecasting.

“It’s a turning point,” said Maria Molina, a research meteorologist at the University of Maryland who studies A.I. programs for extreme-event prediction. “You don’t need a supercomputer to generate a forecast. You can do it on your laptop, which makes the science more accessible.”

People depend on accurate weather forecasts to make decisions about such things as how to dress, where to travel and whether to flee a violent storm.

Even so, reliable weather forecasts turn out to be extraordinarily hard to achieve. The trouble is complexity. Astronomers can predict the paths of the solar system’s planets for centuries to come because a single factor dominates their movements — the sun and its immense gravitational pull.

In contrast, the weather patterns on Earth arise from a riot of factors. The tilts, the spins, the wobbles and the day-night cycles of the planet turn the atmosphere into turbulent whorls of winds, rains, clouds, temperatures and air pressures. Worse, the atmosphere is inherently chaotic. On its own, with no external stimulus, a particular zone can go quickly from stable to capricious.

As a result, weather forecasts can fail after a few days, and sometimes after a few hours. The errors grow in step with the length of the prediction — which today can extend for 10 days, up from three days a few decades ago. The slow improvements stem from upgrades to the global observations as well as the supercomputers that make the predictions.

Not that supercomputing work has grown easy. The preparations take skill and toil. Modelers build a virtual planet crisscrossed by millions of data voids and fill the empty spaces with current weather observations.

Dr. Bretherton of the University of Washington called these inputs crucial and somewhat improvisational. “You have to blend data from many sources into a guess at what the atmosphere is doing right now,” he said.

The knotty equations of fluid mechanics then turn the blended observations into predictions. Despite the enormous power of supercomputers, the number crunching can take an hour or more. And of course, as the weather changes, the forecasts must be updated.

The A.I. approach is radically different. Instead of relying on current readings and millions of calculations, an A.I. agent draws on what it has learned about the cause-and-effect relationships that govern the planet’s weather.

In general, the advance derives from the ongoing revolution in machine learning — the branch of A.I. that mimics how humans learn. The method works with great success because A.I. excels at pattern recognition. It can rapidly sort through mountains of information and spot intricacies that humans cannot discern. Doing so has led to breakthroughs in speech recognition, drug discovery, computer vision and cancer detection.

In weather forecasting, A.I. learns about atmospheric forces by scanning repositories of real-world observations. It then identifies the subtle patterns and uses that knowledge to predict the weather, doing so with remarkable speed and accuracy.

Recently, the DeepMind team that built GraphCast won Britain’s top engineering prize, presented by the Royal Academy of Engineering. Sir Richard Friend, a physicist at Cambridge University who led the judging panel, praised the team for what he called “a revolutionary advance.”

In an interview, Rémi Lam, GraphCast’s lead scientist, said his team had trained the A.I. program on four decades of global weather observations compiled by the European forecasting center. “It learns directly from historical data,” he said. In seconds, he added, GraphCast can produce a 10-day forecast that would take a supercomputer more than an hour.

Dr. Lam said GraphCast ran best and fastest on computers designed for A.I., but could also work on desktops and even laptops, though more slowly.

In a series of tests, Dr. Lam reported, GraphCast outperformed the best forecasting model of the European Center for Medium-Range Weather Forecasts more than 90 percent of the time. “If you know where a cyclone is going, that’s quite important,” he added. “It’s important for saving lives.”

Replying to a question, Dr. Lam said he and his team were computer scientists, not cyclone experts, and had not evaluated how GraphCast’s predictions for Hurricane Beryl compared to other forecasts in precision.

But DeepMind, he added, did conduct a study of Hurricane Lee, an Atlantic storm that in September was seen as possibly threatening New England or, farther east, Canada. Dr. Lam said the study found that GraphCast locked in on landfall in Nova Scotia three days before the supercomputers reached the same conclusion.

Impressed by such accomplishments, the European center recently embraced GraphCast as well as A.I. forecasting programs made by Nvidia, Huawei and Fudan University in China. On its website, it now displays global maps of its A.I. testing, including the range of path forecasts that the smart machines made for Hurricane Beryl on July 4.

The track predicted by DeepMind’s GraphCast, labeled DMGC on the July 4 map, shows Beryl making landfall in the region of Corpus Christi, Texas, not far from where the hurricane actually hit.

Dr. Chantry of the European center said the institution saw the experimental technology as becoming a regular part of global weather forecasting, including for cyclones. A new team, he added, is now building on “the great work” of the experimentalists to create an operational A.I. system for the agency.

Its adoption, Dr. Chantry said, could happen soon. He added, however, that the A.I. technology as a regular tool might coexist with the center’s legacy forecasting system.

Dr. Bretherton, now a team leader at the Allen Institute for A.I. (established by Paul G. Allen, one of the founders of Microsoft), said the European center was considered the world’s top weather agency because comparative tests have regularly shown its forecasts to exceed all others in accuracy. As a result, he added, its interest in A.I. has the world of meteorologists “looking at this and saying, ‘Hey, we’ve got to match this.’”

Weather experts say the A.I. systems are likely to complement the supercomputer approach because each method has its own particular strengths.

“All models are wrong to some extent,” Dr. Molina of the University of Maryland said. The A.I. machines, she added, “might get the hurricane track right but what about rain, maximum winds and storm surge? There’re so many diverse impacts” that need to be forecast reliably and assessed carefully.

Even so, Dr. Molina noted that A.I. scientists were rushing to post papers that demonstrate new forecasting skills. “The revolution is continuing,” she said. “It’s wild.”

Jamie Rhome, deputy director of the National Hurricane Center in Miami, agreed on the need for multiple tools. He called A.I. “evolutionary rather than revolutionary” and predicted that humans and supercomputers would continue to play major roles.

“Having a human at the table to apply situational awareness is one of the reasons we have such good accuracy,” he said.

Mr. Rhome added that the hurricane center had used aspects of artificial intelligence in its forecasts for more than a decade, and that the agency would evaluate and possibly draw on the brainy new programs.

“With A.I. coming on so quickly, many people see the human role as diminishing,” Mr. Rhome added. “But our forecasters are making big contributions. There’s still very much a strong human role.”

Astronomers around the world are preparing for one of the most anticipated cosmic firework shows of the year — but you don’t need a fancy telescope to join in on the festivities.

The hydrogen that a small, dense star has spent the past 80 years siphoning off of its nearby neighbor is about to explode like a thermonuclear bomb a hundred thousand times the brightness of the sun.

From Earth, it’ll be about as bright as the North Star, making it visible to the naked eye — even with Los Angeles’ light pollution.

Countless amateur astronomers and observatories around the world — and in space — are planning to watch the explosion, called a nova. Here’s everything you need to know to join in on the fun:

To get the word when the star goes nova, you can follow NASA Universe on X, formerly known as Twitter. For hardcore enthusiasts that want to know as soon as the astronomers do, you can sign up for novae instant email notices from the Astronomer’s Telegram.

Scientists expect it to happen any time between now and the end of the year, likely before the end of August. (The nova technically occurred some 3,000 years ago, but the light is just now reaching Earth.)

Once the star, nicknamed the “Blaze star,” goes nova, you have just two or three days in Los Angeles — or about a week out in the desert — to hope for clear weather and try to spot it. The star will be at its brightest the very first night after it explodes.

To spot the star the old-school way, first locate the Big Dipper. Then, follow the direction its handle points (before it curves down) until you find a group of stars in a tight “U” shape. This is Corona Borealis, the constellation the Blaze star is located in. The nova will be just outside the “U” on the bottom left.

Or, you can use websites and apps like Stellarium to spot it in the sky. Just input your location, and select the Blaze star. (It’ll likely be listed under its formal name T Coronae Borealis, or T CrB for short).

If you want to make a night out of it, Griffith Observatory hopes to give the public a view — they just need it to get dark early enough that the stars come out before they close at 10 p.m.

If the nova holds out for a while longer, they’ll bring out their lawn telescopes in addition to the 12-inch Zeiss telescope on the roof of the observatory that’s open to the public. Both options are free, and lines close for the telescopes at 9:30 p.m. Griffith staff will be at the ready to help visitors spot it.

One last thing you can do to prepare: practice now. Look at maps showing where the Blaze star is in relation to the Corona Borealis constellation, and try spotting the constellation in the night sky before the big day. It’ll not only help you spot the star faster, but give you an appreciation for how the nova changes the night sky.

Exposure to wildfire smoke increases the odds of being diagnosed with dementia even more than exposure to other forms of air pollution, according to a landmark study of more than 1.2 million Californians. The study — released Monday at the Alzheimer’s Assn. International Conference in Philadelphia — is the largest and most comprehensive review of the impact of wildfire smoke on brain health to date, according to its authors.

“I was expecting for us to see an association between wildfire smoke exposure and dementia,” said study author Dr. Holly Elser, an epidemiologist and resident physician in neurology at the University of Pennsylvania. “But the fact we see so much stronger of an association for wildfire as compared to non-wildfire smoke exposure was kind of surprising.”

The findings have big health implications, particularly in Western states, where air pollution produced by wildfires now accounts for up to half of all fine-particle pollution — a figure that’s been trending upward as wildfires grow larger and more intense due to climate change and legacies of fire suppression and industrial logging that have altered the composition of many Western forests.

The researchers looked at a type of particulate-matter pollution called PM2.5. These particles are 30 times smaller than the width of a human hair — tiny enough to penetrate deeply into the lungs and cross over into the bloodstream, where they can cause inflammation. Exposure has been shown to raise the risk of dementia and a host of other conditions, including heart disease, asthma and low birth weight.

“We increasingly see that PM2.5 is tied to virtually every health outcome we look at,” said study author Joan Casey, associate professor of public health at the University of Washington.

Elser, Casey and fellow researchers analyzed the health records of more than 1.2 million Kaiser Permanente Southern California members 60 or older between 2009 and 2019. None had been diagnosed with dementia at the beginning of the study.

They estimated each person’s exposure to PM2.5 based on their census tract of residence and then separated that into wildfire and non-wildfire pollution using air quality monitoring data, satellite imagery and machine learning techniques.

They then looked at how many participants were eventually diagnosed with dementia. Unlike past studies, the researchers were able to determine this using patients’ full electronic health records, rather than relying on hospitalizations as a proxy for such diagnoses.

Looking at participants’ average wildfire PM2.5 exposure over three years, the researchers found a 23% increase in the odds of a dementia diagnosis for each increase of 1 microgram of particulate matter per cubic meter of air. When it came to non-wildfire PM2.5 exposure, they documented a 3% increased risk of dementia diagnoses for each increase of 3 micrograms of particulate matter per cubic meter of air.

“That’s what it comes down to, is what’s so different about wildfire smoke?” Casey said.

More research is needed to learn exactly what that is. Possibilities include the fact that wildfire particles are produced at higher temperatures, contain a greater concentration of toxic chemicals and are, on average, smaller than PM2.5 from other sources.

These ultrafine particles can translocate from people’s noses into their brains via the olfactory bulb, Casey said.

“Normally the brain is protected by the blood-brain barrier, but here there’s actually a direct route for ultrafine particles to get into the brain and possibly cause some of the problems that we’re seeing in folks living with dementia,” she said.

The way in which people are exposed to wildfire smoke also differs from other types of fine-particle pollution, the researchers said. Background or ambient fine-particle pollution levels are usually relatively constant in a given place over time. But wildfire particulate matter tends to fluctuate wildly, resulting in more exposure over shorter periods of time, which may overwhelm the body’s defenses.

Of some 5,500 abstracts submitted to the Alzheimer’s Assn. International Conference, this one stood out due to its novelty, importance and impact, said Dr. Claire Sexton, senior director of scientific programs and outreach for the Alzheimer’s Assn.

“There have been other studies looking at different types of pollution, but this was unique in terms of the extent and the way in which it was able to do these analyses,” she said.

The researchers found the effects to be stronger on Asian, Black and Latino people, as well as those living in high-poverty areas. The most heavily impacted group was one that researchers classified as “other” because it didn’t contain enough people to differentiate further, Casey said. That group included Indigenous people, Pacific Islanders and people whose race was unknown.

“So these disparities are playing out again, as we unfortunately often see with environmental exposures,” she said. “But the level at which we observed it here was fairly striking.”

Casey believes those disparities are due to differential exposure based on where populations are located, noting that her previous research has shown that Indigenous people in California have by far the highest levels of wildfire particulate exposure. Other factors could include poorer housing quality, lack of access to air filtration devices, jobs that prevent people from staying indoors during wildfire events and disparate responses to the same amount of pollution due to preexisting hypertension or diabetes, she said.

“All those things are driven by social determinants of health,” she said. “The fact that we need to allocate additional resources to these people and places to protect health and to try to reduce health disparities going forward is really important.”

The researchers did not differentiate between dementia subtypes like Alzheimer’s, the most common form, because they relied on diagnostic codes rather than using brain imaging or postmortem studies. That’s important to know — and a key area for future study — because in order to best protect people, clinicians need to have an understanding of what’s underpinning the relationship between wildfire smoke and different dementia subtypes, Elser said.

Still, the study is notable for its massive sample size and careful approach, taking into account sociodemographics like comorbidities and census tract poverty, said Rachel Whitmer, the director of the UC Davis Alzheimer’s Disease Research Center who was not involved in the research.

The prevalence of dementia is on the rise as the baby boomer generation ages, but environmental factors may also be contributing to the increase, she said.

Research like this lays the groundwork for future studies, she said.

“With the increase in wildfires, this is a really important question and I think they did a really rigorous job in exploring it,” she said.

Levels of PM2.5 had been declining since the Clean Air Act took effect in 1970. But wildfires have reversed those trends in California, undercutting efforts to reduce emissions. In recent years, wildfire smoke has also affected the Midwest and East Coast. In 2023, smoke from Canadian wildfires blanketed the Atlantic seaboard, triggering air quality alerts and forcing the cancellation of outdoor events.

“It’s a big problem in places where wildfires are endemic,” Elser said. “And I worry that as we continue to experience increasingly frequent wildfire events, this could affect more people over a larger geographical distribution, more of the time.”