A remarkable dance occurs between the flowers of avocado trees every spring: they change sex daily, moving from female to male or male to female, then back before the next morning. Botanist A. B. Stout observed this reproductive strategy as early as 1927, but researchers couldn’t explain how it worked until now.
All avocado trees (Persea americana) are cosexual, or hermaphrodites, meaning they contain both sexes in one plant. A-type trees begin with flowers in the female phase (receptive to pollen) in the morning and change to the male phase (producing pollen) in the afternoon of the next day. B-types operate on a different timing, making them male in the morning and female in the afternoon. For a new study in the Proceedings of the National Academy of Sciences USA, Jeffrey Groh, a postdoctoral researcher at the University of California, Berkeley, and his colleagues pinpointed a single protein-coding gene that lets A- and B-type trees inherit the sex-swapping behavior. The protein produced activates a host of additional genes to coordinate flowers opening and closing in rhythm to aid the trees’ reproductive strategy, letting “the whole tree [pulse] female to male or male to female,” he says.
Cathy Rushworth, a plant evolutionary geneticist at Utah State University, who was not involved in the study, says the gene region in question shows a very clear signal in this work—almost like it can “glow in the dark.” Tools to reveal this level of detailed genetic information, she adds, have only recently become available and inexpensive enough to see wider use.
Flowering plants, called angiosperms, employ an immense diversity of reproductive strategies. And while the strategy used by avocados is found in a few other species in the same family, the researchers determined that it was not driven by the same mechanism in, for instance, the distantly-related true cinnamon. This, they say, indicates that it likely evolved separately multiple times. The genetic evidence suggests avocados’ ancestors picked the habit up about 40 million years ago.
“Through the power of genetics,” he says, “we can detect traces of this rhythm far into the ancient past, a humbling reminder that our own experience of this beautiful phenomenon is just a tiny sliver of its evolutionary history.”
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Avocado flowers in their female phase. Jeffrey Scott Groh
A clock aboard a fast-moving spacecraft does not break, lag, or malfunction. It ticks normally for everyone inside. Hearts beat, coffee cools, and hair grows at the usual pace.
Yet when the travelers return, they may have aged far less than people who stayed on Earth.
That unsettling result does not come from radiation, weightlessness or some hidden effect of space travel. It comes from the structure of time itself. According to special relativity, observers moving at different speeds can experience different amounts of time between the same events.
The idea sounds remote until you consider that nothing is ever truly still. Earth moves around the sun at roughly 30 kilometers per second. The sun circles the Milky Way at about 230 kilometers per second. The galaxy moves through the universe at hundreds of kilometers per second more.
Those speeds do not provide a universal measure of motion. Physics offers no fixed background against which everything else can be judged. Motion only has meaning relative to another object.
No observer owns the correct viewpoint
Place two people in otherwise empty space and let them drift apart at half the speed of light. One person can say the other is moving. The second person can make the same claim in return.
Neither observer has privileged access to an absolute state of rest.
That principle once seemed like a technical detail. It became a crisis when physicists tried to understand light. Under ordinary experience, speeds add together. A ball thrown forward on a moving train travels faster relative to the ground than a ball thrown from a stationary platform.
Light refused to follow that rule.
Measurements taken in different directions and at different times of year returned the same result. Earth’s movement did not change the measured speed of light. The value remained 299,792,458 meters per second.
That consistency forced a radical choice. If motion remained relative and light traveled at the same speed for every observer, then familiar ideas about distance and time could not remain fixed.
In 1905, Albert Einstein developed the framework that became special relativity while working in a Swiss patent office. His solution joined space and time into a single structure known as spacetime.
Time could no longer serve as one universal clock for the entire universe.
Motion changes the passage of time
One way to picture relativity is to think of movement as divided between space and time. An object sitting still relative to an observer moves only through time from that observer’s viewpoint. Once the object begins moving through space, the amount of time recorded along its path changes.
The faster the spatial motion, the less time passes for the moving object compared with a stationary observer.
This effect is called time dilation.
Nothing feels unusual to the traveler. Each second still feels like one second. Local clocks agree with nearby heartbeats, chemical reactions and everyday events. The difference appears when the traveler’s clock is compared with a clock that followed another path through spacetime.
Consider a spacecraft heading toward a star 10 light-years away at 99 percent of light speed. From Earth, the trip lasts slightly more than 10 years. People watching from home see the ship cross the enormous distance.
The crew experiences about 1.4 years.
Their clocks do not suddenly tick in slow motion from their own perspective. Life aboard the spacecraft proceeds normally. The crew simply records fewer elapsed seconds between departure and arrival than observers on Earth.
At 99.9999 percent of light speed, the contrast becomes more dramatic. The travelers could experience the 10-light-year journey in roughly five days. A round trip could leave them only about two weeks older while approximately 20 years passed on Earth.
The effect is not presented as a trick of perception. Each observer measures a different elapsed time because each follows a different path through spacetime.
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Einstein’s relativity explains why fast travelers age more slowly and why time never passes at one universal rate. (CREDIT: Wikimedia / AI-Generated / CC BY-SA 4.0)
Giant utility deals do not come along often. Mergers in this heavily regulated industry require approvals from multiple agencies and often face pushback from politicians and local civic groups worried about rising electricity prices.
But two of the largest power companies in the United States, NextEra Energy and Dominion Energy, are giving it a try, with a $67 billion tie-up announced in May. Sysco, the big food distributor, also went big in March with the $29 billion acquisition of Jetro Restaurant Depot, a supplier to independent restaurants, a deal that could reshape the food supply industry. And this month, Stripe and the private equity firm Advent International offered about $53 billion to acquire PayPal, in what would be one of the largest-ever deals in financial services.
Companies across America are seizing on what may be the most favorable regulatory environment for businesses in years to complete deals that might have been unlikely under previous presidencies. The rush is on to get them done before President Trump’s term runs out.
“There is a ‘now or never’ attitude for attempting transformational combinations,” lawyers at Hunton Andrews Kurth wrote in a note this year.
Although Mr. Trump plays no formal role in approving most mergers, he has publicly weighed in on deals. Some executives, recognizing that the administration is more transactional than its predecessors, have stopped by the White House during their efforts to get his administration’s blessing for them.
The regulators the president has appointed to oversee deals have taken a more flexible approach. For example, the Justice Department said last week that it would fast-track its review of some mergers, asking fewer questions upfront. That new policy was a sign the department was “open for business,” lawyers at Wilmer Hale wrote in a memo for clients.
“You have a federal antitrust enforcement regime that is viewed generally as meaningfully more accommodative than the Biden administration,” said Edward Lee, a partner at the law firm Kirkland & Ellis. “Obviously, or in terms of dealmakers and dealmaking animal spirits, that’s always a good thing.”
Analysts at Goldman Sachs said they expected busy deal activity to continue into the second half of the year, citing, among other factors, a “friendly” regulatory backdrop. The firm’s list of potential targets for acquisitions include the copper company Freeport-McMoRan, as the building of A.I. data centers increases demand for the metal. Analysts expect the boom in data centers to spur other deals as well, particularly in power and energy.
Banking executives have picked up talks about merging their own businesses, as regulators have unwound the Biden administration’s efforts to make those deals harder. There has long been a debate about how stringently to monitor banking deals, because some critics argue they could force the closure of vital community branches or consolidate risk among fewer banks. Some, though, including former Treasury Secretary Janet L. Yellen, have argued that more consolidation among the roughly 4,100 small U.S. banks could help steady industry volatility.
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NextEra Energy, led by John Ketchum, its chief executive, and Dominion Energy announced their merger in May. Credit…Danielle Villasana/Reuters
In French author Marcel Proust’s 1906 novel À la recherche du temps perdu (In Search of Lost Time), a bite of madeleine cake triggers a flood of childhood memories. Scientists call this phenomenon “Proust’s madeleine,” and it was even featured on The Sopranos. Now a study in PLOS Biology suggests these vivid memories of early childhood smells are encoded in very specific parts of the brain.
“Smells are exceptional cues for accessing autobiographical memories,” says the study’s co-senior author Nathalie Mandairon of the Lyon Neuroscience Research Center in France. Scientists suspected for decades that the phenomenon involved certain brain areas, specifically long-lived “granule” cells in the brain’s olfactory bulb, or smell center. These relatively tiny cells are created on the very first day of a child’s life and are primed to capture pleasurable smells from their first decade—which may explain why childhood memories evoked by smells can be so vivid even when they were thought to be forgotten.
Mandairon’s team surveyed more than 600 volunteers and found that most had remembered pleasant childhood experiences from the “Proust’s madeleine” phenomenon. The researchers then exposed mice to pleasing natural scents when they were about three to four weeks old, an age that roughly corresponds to early childhood in humans. Normal mice were drawn to the scents—but not mice whose granule cells had been silenced by optical fibers that the researchers implanted in the animals’ brains to switch these cells on and off.
The reaction confirmed that early smells are imprinted in the granule cells of the brain’s olfactory bulb, perhaps because these cells can make “privileged connections” with the brain areas for pleasure and reward, the study says. The human responses suggested that mainly positive memories are linked to the phenomenon.
Physical chemist Hervé This, director of France’s AgroParisTech-INRAE International Center for Molecular and Physical Gastronomy, says the study gives a “fascinating” explanation of the brain areas involved. But he would have liked to see it account for negative childhood memories as well because “unpleasantness is equally significant.” He adds that he has experienced the phenomenon himself: pâté lorrain has to be cooked for exactly one hour to match the taste from his childhood.
Another expert, however, broadly welcomes the study but thinks that the singular role of smell in memory may only be an illusion: Every sense has the power to evoke strong memories, says biophysicist Luca Turin of England’s University of Buckingham. “The only peculiarity of smell [is] that it is like a password and needs to be exact,” he adds.
Hmmmm … Central Park covers approx 843 acres in Manhattan. Check it out! It has an interesting history!
Click the link below the picture
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The Gottesman Pool at the Davis Center, managed by NYC Parks, is the City’s newest public pool—offering free swimming to all in the beauty of Central Park.
Come cool off with NYC Parks this summer: Swim season runs from June 27–September 13, 2026.
Hours:
Open daily, 11:00 am–7:00 pm (closed from 3:00 pm–4:00 daily for cleaning) *Adult lap swimming hours: Monday–Friday, 7:00 am–8:30 am (Registration is required at nycgovparks.org)
Learn To Swim
NYC Parks offers free swimming lessons at recreation centers across the City—including the Gottesman Pool at the Davis Center. Registration for this popular program takes place by lottery. Learn to Swim classes are held for tots and one guardian, and for children. You may enter the lottery once per session.
Lottery results will be confirmed on the last day of each registration date. Check your email from NYC Parks for confirmation.
Registration Dates
You must enter the lottery before the following date for a chance to be selected:
Registration for all programs started at noon on Friday, June 12, 2026.
Session I Registration: ends Friday, June 26, 2026
Session II Registration: ends on Wednesday, July 8, 2026.
Session III Registration: ends on Friday, July 24, 2026.
Advanced Child Learn to Swim Registration: ends on Thursday, August 20, 2026.
Program Dates
Session I: July 6–July 21, 2026
Session II: July 22–August 6, 2026
Session III: August 7–August 21, 2026
Advanced Child Learn to Swim: August 24–August 28, 2026
This program is managed by NYC Parks. For more information, visit nycgovparks.org or call the Citywide Aquatics team at 718.760.6969.
Adult Lap Swimming
July 6–August 28, 2026 Mondays–Fridays | 7:00 am–8:30 am
Join us before the pool opens for early bird lap swimming! Swimmers also have the option to participate in a long-distance lap swim challenge while enjoying their morning swim. An awards ceremony will be held at the end of August to celebrate the health and fitness achievements of swimmers who complete 25 miles or more.
Tech giants are setting records every few months for how much they are spending on artificial intelligence — but this time, some jitters are also growing.
On Thursday, Amazon said its capital expenditures totaled $53 billion in the second quarter, up 69 percent from a year earlier, as it built A.I. data centers and other infrastructure. It joined a parade of other big tech companies, with Meta on Wednesday reporting that its costs had risen 55 percent from last year, while Microsoft said its capital expenditures had soared 69 percent. Last week, Google also disclosed that its costs had jumped and said it would boost its spending further.
These numbers are only set to skyrocket. Across this year and next, Amazon, Google, Meta and Microsoft are expected to spend a staggering $1.5 trillion building data centers and stuffing them with advanced chips, according to Wall Street estimates compiled by FactSet.
“The scale of it is nuts,” said Melissa Otto, who leads research at S&P Global’s Visible Alpha division.
Alarms are rising as Wall Street and others question when this spending can be justified. On Thursday, Amazon’s share price rose almost 10 percent in after-hours trading after its cloud computing division saw its fastest growth since early 2022, and shares of Microsoft, which did not change its spending forecast, jumped more than 15 percent.
But Meta’s stock sank more than 7 percent on Thursday after it revealed its A.I. outlays and that costs were growing faster than its revenue. And last week, for the first time since going public in 2004, Google said it had “negative free cash flow,” which meant it was spending more on day-to-day operations and building new infrastructure than it was taking in from its businesses. Google’s stock fell more than 6 percent the next day.
Even so, the companies insist they are doing the right thing. “As long as we see these attractive opportunities to invest, we will continue to invest,” Anat Ashkenazi, Alphabet’s finance chief, told Wall Street analysts last week.
More than a dozen years ago, tech companies became the largest enterprises on the planet, fueled by their software and digital businesses. But A.I. has flipped tech’s “asset-light” model on its head. Multibillion-dollar data centers, which the industry likes to call “A.I. factories,” have become critical investments for developing advanced systems and making them available to customers.
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Meta’s Eagle Mountain Data Center in Utah. Meta, Amazon, Google and Microsoft are expected to spend $1.5 trillion building data centers through next year. Credit…Christie Hemm Klok for The New York Times
On July 20, 1976, NASA’s Viking 1 lander became the first spacecraft to safely touch down on Mars. Shortly after, it beamed back our first close-up image of the surface—a drab view of pebbles strewn at the lander’s feet.
“I don’t think we’d have been surprised if there were blades of grass,” recalls Tom Young, Viking’s mission director. Scientists had speculated for years about what scenes would await Viking 1 and its twin, Viking 2, which landed elsewhere on Mars a few weeks later. Most thought any Martians would, at most, be simple, small life-forms—although Carl Sagan had impishly suggested that polar-bear-sized creatures could populate the landscape.
Humans have imagined other inhabited worlds for millennia. And we’ve even “discovered” life on Mars more than once across the last century or two. Yet each time we’ve built sharper tools and taken a closer look, all those claims have evaporated, much like the Red Planet’s ancient seas. By the time the Viking landers launched, we knew there were no signs of life that could be seen from orbit.
But there was still hope that perhaps something stirred there—hope enough to launch the Viking landers on an audacious mission to look for it. Their results, however, weren’t conclusive. Most experts agree the twin spacecraft failed to find definitive signs of organisms in scoops of Martian soil, but some scientists continue to believe they did.
Even now, a half-century later, the outcome of those investigations fuels debate, and the Viking landers remain the only missions ever sent to the surface of another world to search for extant alien life. The ambiguity that wafted from their soil samples has become emblematic of the uncertainty that plagues the greater search for extraterrestrial life—not just on Mars and our sun’s other worlds but across the observable universe. Our knowledge of life’s physical limits and the unearthly forms it might take remains so incomplete that we could all too easily declare a discovery where none truly exists—or fail to recognize genuine extraterrestrial biology hidden in plain view.
As a result, astrobiologists have, for decades, defaulted to a conservative burden of proof that leans into two aphorisms coined by Sagan when he wasn’t musing about Martian polar bears: life, he and his co-authors wrote, should be considered a “hypothesis of last resort,” largely because “extraordinary claims require extraordinary evidence.”
But what if Sagan had it all wrong? If we live in a universe where life is common and not extraordinary at all, setting such an extraordinarily high bar for its discovery beyond Earth can backfire. What if life’s fingerprints have been on Mars all along, and we were too cautious to admit that we’d found them?
Already, a growing pile of evidence suggests ancient Mars could very well have been an inhabited planet—and may still be. Our search for life there is a bit like bobbing for apples blindfolded—except we don’t know what an “apple” might feel like, and the apples may exist only in scattered pieces. What’s needed, many scientists argue, is a clearer way of separating signs of “life” from “nonlife,” a quantitative method that leverages statistics and probabilities to guide our interpretations of biology’s potential fingerprints.
“There’s all these different lines of evidence that keep coming together that make me go, ‘Gosh, it’s becoming more and more difficult to explain everything on Mars abiotically,’” says Amy Williams, an astrobiologist at the University of Florida. “I’m not yet ready to say that we’ve found evidence for life, but I think the story is building to help us understand what that potential is—to put a probability on that instead of just saying ‘yes’ or ‘no.’”
Present-day Mars is marginally habitable at best, but 3.5 billion years ago the planet was almost certainly a more life-friendly world. Ancient Mars was warmer, with a thicker atmosphere and a global magnetic field that protected its surface from cosmic radiation; seas and lakes filled its basins, and rivers tumbled through its valleys. Over eons, Mars lost its magnetic field and, with it, those bodies of water and thick, insulating atmosphere.
Yet across the sweep of Mars’s lifetime, organic compounds—life’s building blocks—have rained down on the planet, delivered by meteorites and cosmic dust.
“If we live in a universe where life takes advantage of watery environments when there’s juicy chemistry going on—which is the way I picture the universe, but that’s unvalidated intuition—then something should have started happening in some of those places on Mars,” says astrobiologist David Grinspoon of the Planetary Science Institute. “So there’s this predisposition to think, ‘Either there should have been an origin of life on Mars—or we’re really wrong about something on Earth.’”
Since 2012 NASA’s Curiosity rover has been searching for signs of ancient habitable environments in Gale Crater. And in 2021 the agency’s Perseverance rover touched down in Jezero Crater with the goal of looking specifically for ancient biosignatures, not present-day life. Now, based on the results of those robotic explorations, many experts suspect that ancient Mars was indeed a biological world, even if they can’t yet prove it.
“The evidence for habitable environments and life on early Mars is getting stronger every time we look at it,” says Chris McKay, an astrobiologist at NASA’s Ames Research Center.
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A model of NASA’s Viking 1 Mars lander (inset) against a panoramic view of the Martian surface snapped by Viking 1 on July 20, 1976. NASA/JPL-Caltech
A rare cancer tied to past industrial work has long left patients with few options and little time. Mesothelioma, most often caused by asbestos exposure, develops slowly and strikes decades later. By the time symptoms appear, the disease is often advanced. Survival averages about one year, and long-term outcomes remain poor.
Now, new research by the University of Vermont offers a different approach. Instead of protecting cells from damage, scientists are turning cancer’s own survival system against it. Early clinical results suggest the strategy may slow disease and extend lives.
A Disease With Few Options
Mesothelioma affects about 30,000 people worldwide each year. Many patients worked in shipbuilding, oil refining, or construction, where asbestos exposure was common.
Current treatments, including chemotherapy and immunotherapy, provide limited benefit. Most patients face a median survival of around 12 months. The five-year survival rate is near 10 percent.
“It’s a disease of a significant unmet medical need,” said Brian Cunniff, a professor at the University of Vermont.
Researchers have spent years searching for better treatments. Many past efforts focused on reducing harmful molecules inside cancer cells. This new study takes the opposite approach.
Turning A Survival Mechanism Into A Weakness
Cancer cells grow quickly and consume large amounts of energy. This process produces unstable molecules called reactive oxygen species. These molecules can damage cells if they build up.
To survive, tumor cells increase their defenses. They produce antioxidant enzymes that neutralize these harmful compounds. One key enzyme is called peroxiredoxin 3, or PRX3.
PRX3 works inside mitochondria, the parts of cells that produce energy. It removes hydrogen peroxide, a damaging molecule that forms during metabolism.
Scientists realized that mesothelioma cells depend heavily on this system. Without it, the cells could be overwhelmed by their own stress.
The idea was simple but bold. Instead of reducing oxidative stress, increase it. Block PRX3 and allow harmful molecules to accumulate. Push the cancer cells past their limit.
Lab Results Show Strong Effects
To test this idea, researchers removed PRX3 from mesothelioma cells in the laboratory. The results were immediate.
Cells without PRX3 grew more slowly. Their ability to multiply dropped sharply. Energy production declined, and oxidative stress increased.
In animal studies, the effect was even more dramatic. When these altered cells were introduced into mice, they failed to form tumors.
The findings showed that PRX3 is not just helpful for cancer cells. It may be essential for their survival.
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A new therapy targets cancer’s stress defenses, showing promise in early trials for mesothelioma patients with limited treatment options. (CREDIT: Shutterstock)
The milestones for artificial intelligence keep getting grander.
In 2023, an A.I. system passed the bar exam. In 2025, the technology helped scientists identify a suspected cause of Alzheimer’s disease. In May, A.I. had advanced so far that it solved a complex math problem that had stumped experts for 80 years. Last week, two A.I. systems under testing went rogue and hacked into a company’s database.
And this is still just the beginning.
From the American Midwest to the Persian Gulf, hundreds of major data centers now under construction will be turned on in the coming years. They are set to deliver an avalanche of computing power to develop and run A.I. that has no equal in the history of the technology industry, with breakthroughs that once felt revolutionary likely to become increasingly routine.
Behind each leap in A.I. are corresponding jumps in computing power. Today, there are about 20 million A.I. chips crammed into the data centers that underpin the technology’s growing abilities and usage worldwide, according to the research firm Epoch AI.
That figure is expected to double roughly every nine months, putting the world on pace to have about 200 million of chips by the end of 2028 — 10 times current levels.
In size and ambition, this moment compares to the building of the railroads in the 1800s, President Franklin D. Roosevelt’s New Deal in the 1930s, and the Manhattan Project to create an atomic weapon in the 1940s, technologists said.
“This is the largest scale infrastructure build-out in the history of humanity,” said Rob Wachen, a co-founder of the microchip firm Etched, which has raised more than $1 billion to meet the growing demand for A.I. components.
Peter DeSantis, who leads foundational A.I. models at Amazon — which provides computing power to the A.I. firms Anthropic, OpenAI and others — said the Seattle company has doubled its computing capacity since 2022 and would double it again by next year. “It’s hard to get your mind around the scale,” he said.
Fueling the surge is the belief that A.I. can take on more human responsibilities and solve increasingly complicated tasks with the more data and computing power you feed it. This tenet, sometimes called “the Scaling Laws,” has become the driving force behind this technological era. Those with the most computing power will create the most advanced A.I. systems, capturing the biggest share of profit and value, tech leaders argue. The biggest engine, they say, will win the race.
Confidence in the Scaling Laws has led A.I. leaders to make ever bolder predictions. Dario Amodei, the chief executive of Anthropic, has said that if these laws hold for another year or two, A.I. will be able to perform huge amounts of white-collar work. Demis Hassabis, the head of Google’s A.I. lab DeepMind, wrote recently that A.I. could usher in “10x of the Industrial Revolution at 10x the speed.”
Scientists and technologists see the coming deluge of computing power leading to drug discoveries and robotics advances, and industry analysts said it would drive more everyday use of A.I. in people’s personal and professional lives.
But the build-out has also stoked a backlash, spurring protests in many communities over how data centers could harm the environment, raise electricity prices and drain water. In the United States, data centers are shaping up as a major issue for November’s midterm elections, with a growing national movement pushing back against the tech industry and its billionaires.
Economists and investors have raised concerns that tech firms are spending faster than they can profit from A.I. Past infrastructure booms have been followed by downturns before the benefits of the technology were realized. The railroad boom in the 1800s, electrification in the 1920s, and the dot-com bubble in the late 1990s were punctuated by economic recessions and a stock market crash as companies that overspent went out of business.
“Each time you’ve had a technological revolution, this kind of bubble bursting happened,” said Philippe Aghion, who won the Nobel in economic science in 2025 for research on innovation-driven economic growth. “A.I. is like the fourth industrial revolution, and it has this aspect to it that generates a bubble.”
With more computing power coming online, geopolitical divisions are only set to widen.
The United States, home to about 5,500 data centers, about 10 times the next closest country, is far ahead of the rest of the world, including China. U.S. companies like Amazon, Google, Microsoft and Meta control about 80 percent of global computing power that drives A.I., according to Epoch AI. Google alone is believed to have four times as many A.I. chips as all of China’s companies, which are racing to catch up by developing new semiconductors and A.I. infrastructure of their own.
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Amazon’s sprawling complex in New Carlisle, Ind., which is spread across an area that was once cornfields.AJ Mast for The New York Times
On Thursday, SpaceX pulled off the second consecutive successful test flight of its Starship megarocket. The launch hints at sustained progress after years of botched tests, but there is a caveat.
Just after 6:50 P.M. EDT, Starship lofted into space atop SpaceX’s Super Heavy V3 booster from the company’s Starbase launch complex in Texas. After two and a half minutes, the booster separated from Starship and returned to Earth. SpaceX was aiming for the reusable booster to make a pinpoint landing in the Gulf of Mexico, but that part of the mission didn’t go according to plan. The booster’s landing burn appeared to fail, resulting in a hard crash into the water.
Once in space, however, Starship successfully deployed its payload of 20 Starlink V3 satellites, some of which were armed with cameras to check its heat shield—and offer audiences on the ground in-flight views of the rocket in space.
The Starlink satellites are the same as those SpaceX is planning to use to further build out its orbital broadband Internet constellation. But for the purposes of this test, the Starlink craft merely attempted to establish laser communications with the wider network, before ultimately plummeting to their doom in Earth’s atmosphere.
Eventually, SpaceX wants to use Starship as its workhorse rocket, replacing the smaller Falcon 9. With its ability to carry 100 metric tons of cargo to orbit, Starship will be able to loft many more Starlink satellites at a time than the Falcon 9 rocket.
Alone in space, Starship also showed improvements over its last test flight, successfully reigniting one of its six Raptor engines for a brief burn. The spacecraft didn’t attempt this feat during its previous test flight in May because the Raptor engine shut down prematurely during launch.
The new flight, which was originally slated for last week but was delayed, ended after an hour and five minutes. After deploying its satellites, Starship splashed down successfully north of Australia in the Indian Ocean, although it did briefly catch fire in the water.
The mostly successful test is good news for SpaceX’s ambitions—but it also matters for the future of human space exploration. NASA hopes to use Starship to get humans to and from the moon as part of its Artemis program.
If SpaceX can get a lunar-lander variant of Starship ready on time, NASA could use it to send humans to the surface of the moon for the first time in more than 50 years as soon as 2028.
A watchdog report published in March found SpaceX was lagging in that effort, and NASA is also funding development of a Blue Origin lunar lander for the task.
The clock is ticking for both companies: NASA’s Artemis III, a crewed mission to test key capabilities for both vehicles in low-Earth orbit, is targeted for launch before the end of next year. The current plan is to try to dock NASA’s crew capsule, Orion, with Starship—but SpaceX still needs to show it can get Starship to orbit in the first place. That means many more test flights, if nothing else.
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SpaceX Starship launches on July 24, 2026. NASA/SpaceX/YouTube
Film and Writing Festival for Comedy. Showcasing best of comedy short films at the FEEDBACK Film Festival. Plus, showcasing best of comedy novels, short stories, poems, screenplays (TV, short, feature) at the festival performed by professional actors.
Einstein’s relativity explains why fast travelers age more slowly and why time never passes at one universal rate. (CREDIT: Wikimedia / AI-Generated / CC BY-SA 4.0)
skynesher/Getty Images
Gottesman Pool at the Davis Center
A new therapy targets cancer’s stress defenses, showing promise in early trials for mesothelioma patients with limited treatment options. (CREDIT: Shutterstock)
James' World 2 