
The Search for Extraterrestrial Life Is a Roller Coaster of Hope and Disappointment
American astronomer Percival Lowell took Schiaparelli's observations and ran with them. He became obsessed with the Martian markings, which he interpreted as evidence of a sophisticated network of water-transportation channels. 'That Mars is inhabited by beings of some sort or other we may consider as certain as it is uncertain what those beings may be,' Lowell wrote in his 1906 book Mars and Its Canals.
It sounds ludicrous now, but it wasn't back then. At the time, ideas about life were evolving rapidly, says David Baron, author of the new book The Martians: The True Story of an Alien Craze That Captured Turn-of-the-Century America. In 1858 Charles Darwin published his theory of natural selection. One year later German scientists Robert Wilhelm Bunsen and Gustav Robert Kirchhoff invented the spectroscope, which they and others used to analyze the chemical signatures in light from the sun and the planets. These studies revealed that other worlds are made of the same elemental constituents as Earth. If life evolves by a natural process, and all planets form in similar ways, why wouldn't life take hold on the Red Planet, too?
On supporting science journalism
If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.
More than 100 years later scientists searching for extraterrestrial life are guided by the same reasoning: The universe is vast, and it's all made of the same basic stuff we are, so why wouldn't there be life elsewhere? Yet the evidence for intelligent life beyond Earth has taken several turns. In fact, the only constant has been hope: the desire that many people have to prove we are not alone. The question of extraterrestrial life's existence isn't just a neutral scientific debate—it matters to humans, including the humans searching for that life. And our optimism that we'll find it has tended to flip on and off.
The idea that Mars is home to canal-digging civilizations began to lose its sparkle in 1909, when French astronomer Eugène Antoniadi observed the Red Planet during one of its biannual close approaches. The lines, he found with a better telescope and a more intimate view, were an optical illusion. Those data didn't convince Lowell, and it didn't put the theory to rest—in 1916 Scientific American managing editor Waldemar Kaempffert was still convinced the canals were real. Nevertheless, belief in advanced life on Mars faded in the following decades. When the Mariner 4 spacecraft flew by Mars in 1964, relaying images of a dry and desolate world, the Martian hypothesis died for good.
And the signs weren't promising for extraterrestrials elsewhere, either. In 1950 physicist Enrico Fermi had pointed out what he called the 'Great Silence': If life is likely to be plentiful, then where is everybody? The fact that humanity hadn't heard from other intelligent beings became known as the Fermi paradox. Maybe life is common, but advanced life is rare, scientists suggested. Or perhaps other civilizations arise often and then destroy themselves, as humanity seemed newly capable of doing after the invention of the atomic bomb in 1945.
Astronomers began a more systematic study of the question. In 1960 Cornell University researcher Frank Drake started Project Ozma, which used a radio telescope to scan for broadcasts from two distant star systems. In 1977 astronomers caught a batch of radio waves that blasted out for 72 seconds, looking more like a hugely powerful cosmic radio station than something natural. They called it the WOW! Signal and got excited. But the same transmission was never heard again. So far the search for extraterrestrial intelligence (SETI) has not found convincing evidence of broadcasting aliens.
Yet lately there are new reasons to hope. In 1992 astronomers Aleksander Wolszczan and Dale Frail discovered two rocky worlds circling a dense, rotating star called a pulsar. Although those planets are bombarded with too much radiation to be habitable, more exoplanet discoveries trickled in through the 2000s. Then the Kepler space mission launched in 2009. It revealed thousands of worlds beyond this one, with more than 5,900 total confirmed as of publication time. 'Planets became the rule, not the exception,' says Nathalie Cabrol, director of the Carl Sagan Center for the Study of Life in the Universe at the SETI Institute.
This wealth of worlds once again changed the calculus on the likelihood of life beyond Earth. Back in 1965 Drake developed a formula to calculate the odds of communicating with extraterrestrial civilizations. It factored in the rate of star formation, the fraction of stars with planets, the fraction of those that are habitable, the proportion of habitable planets that actually develop life, the proportion of that life that becomes intelligent, the fraction of civilizations that develop communications technology, and the length of time they are likely to be transmitting. Most of those variables were unknown at the time—and still are—but the exoplanet boom helped to narrow down the second variable, and it's making headway on the third. We now have a much better idea of how many stars host planets, and it's at least most of them.
We still don't know how life started here on Earth, so we don't know how it might happen elsewhere. And we don't know how likely advanced civilizations are to destroy themselves—a pressing question for reasons beyond SETI. But we do now know that primitive life can thrive in profoundly inhospitable conditions, and that means that microbial aliens may be a lot easier to find than intelligent ones.
In 1966 ecologist Thomas Brock discovered the first extremophile, Thermus aquaticus, living in the hot pools of Yellowstone. Since then, scientists have found microscopic organisms in hydrothermal vents at the bottom of the ocean and in toxic mine waste, in the interiors of rocks and in radioactive water. Just because a planet looks barren doesn't necessarily mean that it is. There is good reason to think primitive life could survive in the buried oceans of Jupiter's moon Europa and the geysers of Enceladus, a moon around Saturn. There might even be microbes in the pools of meltwater under the ice caps of Mars. More than a century after Percival Lowell and his illusory Martian civilization, science has given us plenty of reason to think we're not alone, even if aliens turn out to be single-celled organisms rather than canal-building architects.
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles

USA Today
2 hours ago
- USA Today
Could Starship help humanity establish a city on Mars? Inside SpaceX, Elon Musk's plan
Starship, which SpaceX has launched on nine flight tests from Starbase in South Texas, is the centerpiece of Elon Musk's plan to establish a city on Mars in a matter of years. The idea that humans could one day populate and even colonize Mars is one no longer confined to the realm of science fiction. Astronauts are on the cusp in the years ahead of journeying all the way to the Red Planet, where so far only rovers and orbiters have dared to venture. And when they do, it's likely they'll make landfall aboard a SpaceX Starship. Billionaire Elon Musk founded SpaceX in 2002 with the vision of paving the way to create a self-sustaining colony on the Red Planet. By April 2023, the company rolled out its massive Starship – the rocket/spacecraft combo designed to reach Mars – to its South Texas launch pad for what would be its first of nine flight tests to date. While Starship has endured a few explosive setbacks in 2025, SpaceX is preparing for a mission it refers to as flight 10 as early as Sunday, Aug. 24 to get the vehicle's development back on track. But Starship has a long way to go before it can carry the first spacefarers to Mars and fulfill Musk's oft-stated dream of "making life multiplanetary." Here's everything to know about Elon Musk's goal of setting up the first human city on Mars, and how Starship, which could soon fly again for the first time since May 27, fits in to those plans. Why is Elon Musk interested in sending Starship to Mars? Musk, who has often spoken publicly about his Mars vision, delivered his latest public updates in late May in front of employees from Starbase, SpaceX's headquarters near the U.S.-Mexico border that recently became its own Texas city. In a video SpaceX shared May 29 on social media site X, which Musk owns, the world's richest man described to his employees the goal of sending humans to Mars as essential 'for the long term survival of civilization." Under Musk's vision, humans would not just step on the planet before departing, but would remain to establish a settlement that could function independently if any cataclysmic event were to ever happen on Earth. So, why Mars, as opposed to, say, Jupiter or Venus? Well, while other planets in our solar system are anything but habitable for humans, Mars gets a decent amount of sunlight, has water sources and is already a planet where humanity has sent robotic rovers to scout the terrain. At an average distance of 140 million miles from Earth, it's also one of our closest cosmic neighbors. While Mars has a thin atmosphere and is relatively cold, SpaceX claims on its website, "we can warm it up." Gravity on Mars is about 38% of that of Earth's, meaning humans would be able to lift heavier objects and bound around. What is Starship? World' largest rocket developed for travel to Mars SpaceX is developing Starship specifically with a Martian destination in mind. The spacecraft is designed to be a fully reusable transportation system, meaning the rocket and vehicle can return to the ground for additional missions. The Starship, standing 403 feet tall when fully stacked, is regarded as the world's largest and most powerful launch vehicle ever developed. When fully integrated, the launch system is composed of both a 232-foot Super Heavy rocket and the 171-foot upper stage Starship itself, the spacecraft where crew and cargo would ride. Super Heavy alone is powered by 33 of SpaceX's Raptor engines that give the initial burst of thrust at liftoff. The upper stage Starship section is powered by six Raptor engines that will ultimately travel in orbit. When could SpaceX launch Starship to Mars? Musk wants to send the first uncrewed Starship to Mars by the end of 2026 for a very critical reason: The timeline coincides with an orbital alignment around the sun that would shorten the journey between Earth and Mars. It's a slim window that occurs once about every two years, and if SpaceX misses it, Musk has said the company would target another mission during the next alignment. If Starship were to blast off for the Red Planet by the end of 2026, the journey itself would take between seven to nine months. While no humans would have a seat on the first flight to Mars, Starship won't be empty. Instead, the vehicle would carry one or more Optimus robots designed and built by Tesla, Musk's electric vehicle company. Where, how would Starship land on Mars? Starship would enter Mars' atmosphere while zooming at 4.6 miles per second before it begins decelerating. The vehicle's heatshield is designed to withstand multiple atmospheric entries, but the Martian environment is expected to be harsher on the spacecraft, given its higher levels of atomic oxygen in the atmosphere, according to SpaceX. SpaceX is still considering multiple potential landing sites on Mars for Starship, but the leading contender appears to be a region known as Arcadia. The volcanic plain is on Mars' northern hemisphere far from the planet's frigid poles, with access to water sources in the form of shallow ice. Arcadia is also flat enough to make landings and takeoffs relatively safer, Musk has said. What happens when the first humans arrive on Mars? Crewed trips with humans would then follow most likely in the early 2030s, Musk has claimed. Musk said he envisions eventually launching 1,000 to 2,000 Starships to Mars every two years so enough people and supplies can make it to the surface to quickly establish a livable, self-sufficient city. Achieving that goal would require more than 1 million Martian residents and millions of tons of cargo, according to SpaceX. For that reason, the company has an ambitious target of one day in the years ahead launching Starship more than 10 times per day from Earth to Mars during those crucial transfer windows every 26 months. The first humans on Mars would be tasked with taking account of local resources, setting up landing operations, establishing a power source and building homes. How does Musk's vision fit in Trump's, align with NASA's Artemis campaign? NASA also has designs on astronauts reaching Mars – even if the agency's plan of attack differs from Musk's. Starship is crucial to the U.S. space agency's goal of returning astronauts to the moon's surface for the first time in five decades. NASA's lunar exploration plans call for Artemis III astronauts aboard the Orion capsule to board the Starship while in orbit for a ride to the moon's surface as early as 2027. Once NASA has established a basecamp on the lunar south pole in the years ahead, the agency envisions sending humans from the moon on to Mars. Musk, though, has long favored a more aggressive Earth-to-Mars approach. President Donald Trump also outlined in his January inauguration speech his intent for humans to "plant the Stars and Stripes on the planet Mars" during his second term – a vision from which he hasn't appeared to waver even after a public spat with Musk in June. While Trump has proposed a significant 25% slash to NASA's overall budget, the cuts mostly target the space agency's science programs while increasing funding for space exploration – including missions to Mars. The White House's 2026 budget proposal calls for allocating more than $1 billion for Mars exploration, while an additional $10 billion in funding for NASA was included in Republican spending legislation known as the One Big Beautiful Bill. Trump also signed earlier in August an executive order aimed at rolling back federal regulations on commercial spaceflight companies, including SpaceX. The move came a few months after the Federal Aviation Administration, which licenses commercial rocket launches, gave approval in May for SpaceX to conduct as many as 25 Starship test flights a year as Musk seeks to ramp up development of the Mars-bound spacecraft. When is the next Starship launch from Starbase, Texas? SpaceX plans to conduct the 10th flight test of its Starship spacecraft Sunday, Aug. 24, with a target liftoff time of 7:30 p.m. ET the company's Starbase headquarters in Cameron County, about 23 miles from Brownsville. Eric Lagatta is the Space Connect reporter for the USA TODAY Network. Reach him at elagatta@


Scientific American
2 hours ago
- Scientific American
Can Writing Math Proofs Teach AI to Reason Like Humans?
A few months before the 2025 International Mathematical Olympiad (IMO) in July, a three-person team at OpenAI made a long bet that they could use the competition's brutally tough problems to train an artificial intelligence model to think on its own for hours so that it was capable of writing math proofs. Their goal wasn't simply to create an AI that could do complex math but one that could evaluate ambiguity and nuance—skills AIs will need if they are to someday take on many challenging real-world tasks. In fact, these are precisely the skills required to create artificial general intelligence, or AGI: human-level understanding and reasoning. The IMO, held this year on Australia's Sunshine Coast, is the world's premier math competition for high schoolers, bringing together top contenders from more than 100 countries. All are given the same six problems—three per day, each worth seven points—to solve over two days. But these problems are nothing like what you probably remember from high school. Rather than a brief numeric answer, each demands sustained reasoning and creativity in the form of a pages-long written proof. These logical, step-by-step arguments have to span many fields of mathematics —exactly the sort of problems that, until just this year, AI systems failed at spectacularly. The OpenAI team of researchers and engineers—Alex Wei, Sheryl Hsu and Noam Brown—used a general-purpose reasoning model: an AI designed to 'think' through challenging problems by breaking them into steps, checking its own work and adapting its approach as it goes. Though AI systems couldn't officially compete as participants, the notoriously tough test served as a demonstration of what they can do, and the AIs tackled this year's questions in the same test format and with the same constraints as human participants. Upon receiving the questions, the team's experimental system worked for two 4.5‑hour sessions (just as the student contestants did), without tools or the Internet—it had absolutely no external assistance from tools such as search engines or software designed for math. The proofs it produced were graded by three former IMO medalists and posted online. The AI completed five of the six problems correctly, receiving 35 out of 42 points—the minimum required for an IMO gold medal. (Google's DeepMind AI system also achieved that score this year.) Out of 630 competitors, only 26 students, or 4 percent, outperformed the AI; five students achieved perfect 42s. Given that a year ago language-based AI systems like OpenAI's struggled to do elementary math, the results were a dramatic leap in performance. On supporting science journalism If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today. In the following conversation, Scientific American spoke with two members of the OpenAI team, Alex Wei and Sheryl Hsu, to discuss how they conducted their work, why the model's lack of response to the sixth question was actually a major step toward addressing AI's 'hallucination' problem and how developing a system capable of writing complex proofs could help lead to artificial general intelligence. [ An edited transcript of the interview follows. ] What led you to suddenly begin preparing an AI model for the IMO just a few months before the competition? What was the spark? WEI: I had been thinking about math proofs for quite a while. I'm on a team at OpenAI called MathGen. We had just seen the results progress a lot. We felt like we had a shot to get a model that could do really well at the IMO, and we wanted to make a mad dash to get there. HSU: I used to do math competitions. [Wei] used to do math competitions—he was a lot better than me. The IMO is definitely well known within the [AI research] community, including among researchers at OpenAI. So it was really inspiring to push specifically for that. Can you talk about your decision to work with a general‑purpose AI system rather than a system that was specifically designed to answer math problems? WEI: The philosophy is that we want to build general‑purpose AI and develop methods that don't just work for math. Math is a very good proving ground for AI because it's fairly objective: if you have a proof, it's easier to get consensus on whether it's correct. That's harder for, say, poetry—you'll have more disagreement among readers. And IMO problems are very hard, so we wanted to tackle hard problems with general‑purpose methods in the hope that they'll also apply to domains beyond math. HSU: I'd also say the goal at OpenAI is to build AGI—it's not necessarily to write papers or win competitions. It was important that everything we did for this project also be useful for the bigger goal of building AGI and better models that users can actually use. In what ways could a reasoning model winning a gold in the IMO help lead to AGI? WEI: One perspective is to think in terms of how long tasks take. A year ago, ChatGPT could only do very basic math problems. Two years ago—and even a year and a half ago—we were often thinking about grade‑school math problems you'd find on fifth‑grade homework. For someone really good at math, those take a second or two to read and solve. Then we started evaluating using AIME [the American Invitational Mathematics Examination, a 15-question high school math contest]. That takes around 10 minutes per problem, with about three hours for 15 problems. The IMO is four and a half hours for just three problems—that's 90 minutes per problem. ChatGPT started off being good for quick questions. Now it's better at longer‑running tasks, such as 'Can you edit this paragraph for me?' As AI improves, you can expand the time horizon of tasks, and you can see that progression clearly in math. HSU: Another aspect is that reasoning models were previously very good at tasks that are easy to verify. If you're solving a non‑proof‑based math problem, there's one numerically correct answer. It's easy to check. But in the real world—and in the tasks people actually want help with—it's more complex. There's nuance: maybe it's mostly correct but has some errors; maybe it's correct but could be stylized better. Proof‑based math isn't trivial to evaluate. If we think about AGI, those tasks won't be easy to judge as correct or not; they'll be more loosely specified and harder overall. What was the process for training the model? WEI: In general, reinforcement learning trains a model by rewarding good behavior and penalizing bad behavior. If you repeatedly reinforce good behavior and discourage bad behavior, the model becomes more likely to exhibit the good behavior. HSU: Toward the end, we also scaled up test‑time compute [how long the AI model was able to 'think' before answering]. Previously, for a human, problems of this sort might be a few minutes; now we were scaling to hours. That extra thinking time gave surprising gains. There was a moment when we ran evaluations on our internal test set that took a long time because of the increased test‑time compute. When we finally looked at the results—and Alex graded them—seeing the progress made me think gold might be within reach. That was pretty exciting. On the IMO test, the model you developed got five out of six answers correct. But with the sixth question, the model didn't try to provide an answer. Can you tell me more about the significance of this response? WEI: The model knowing what it doesn't know was one of the early signs of [progress] we saw. Today if you use ChatGPT, you'll sometimes see 'hallucinations'—models don't reliably know when they don't know. That capability isn't specific to math. I'd love it if, for everyday questions, the model could honestly say when it doesn't know instead of giving an answer I must verify independently. What kind of impact could your work on this model have on future models? HSU: Everything we did for this project is fairly general‑purpose—being able to grade outputs that aren't single answers and to work on hard problems for a long time while making steady progress. Those contributed a lot to the success here, and now we and others at OpenAI are applying them beyond math. It's not in GPT‑5, but in future models, we're excited to integrate these capabilities. WEI: If you look at the solutions we publicly posted for the IMO problems, some are very long—five to 10 pages. This model can generate long outputs that are consistent and coherent, without mistakes. Many current state‑of‑the‑art models can't produce a totally coherent five‑page report. I'm excited that this care and precision will help in many other domains.


Washington Post
4 hours ago
- Washington Post
He thought he found life on Mars — and sparked an alien craze
Percival Lowell, a 19th-century American businessman and astronomer, had a pet theory: that a careful look through a telescope revealed that intelligent life exists on Mars. Skeptics cried not enough evidence, but Lowell wouldn't back down. Affected by what is known today as confirmation bias — the tendency to cherry-pick data that supports one's prejudices and swat away the other kind — Lowell kept peering through his telescopes and seeing what he expected to see.