Tech
A New AI Math Startup Just Cracked 4 Previously Unsolved Problems
Five years ago, mathematicians Dawei Chen and Quentin Gendron were trying to untangle a difficult area of algebraic geometry involving differentials, elements of calculus used to measure distance along curved surfaces. While working on one theorem, they ran into an unexpected roadblock: Their argument depended on a strange formula from number theory, but they were unable to solve or justify it. In the end, Chen and Gendron wrote a paper presenting their idea as a conjecture, rather than a theorem.
Chen recently spent hours prompting ChatGPT in the hopes of getting the AI to come up with a solution to the still unsolved problem, but it wasn’t working. Then, during a reception at a math conference in Washington, DC, last month, Chen ran into Ken Ono, a well-known mathematician who had recently left his job at the University of Virginia to join Axiom, an artificial intelligence startup cofounded by one of his mentees, Carina Hong.
Chen told Ono about the problem, and the following morning, Ono presented him with a proof, courtesy of his startup’s math-solving AI, AxiomProver. “Everything fell into place naturally after that,” says Chen, who worked with Axiom to write up the proof, which has now been posted to arXiv, a public repository for academic papers.
Axiom’s AI tool found a connection between the problem and a numerical phenomenon first studied in the 19th century. It then devised a proof, which it helpfully verified itself. “What AxiomProver found was something that all the humans had missed,” Ono tells WIRED.
The proof is one of several solutions to unsolved math problems that Axiom says its system has come up with in recent weeks. The AI has not yet solved any of the most famous (or lucrative) problems in the field of mathematics, but it has found answers to questions that have stumped experts in different areas for years. The proofs are evidence of AI’s steadily advancing math abilities. In recent months, other mathematicians have reported using AI tools to explore new ideas and solve existing problems.
The techniques being developed by Axiom may prove useful outside the world of advanced math. For example, the same approaches could be used to develop software that is more resilient to certain kinds of cybersecurity attacks. This would involve using AI to verify that code is provably reliable and trustworthy.
“Math is really the great test ground and sandbox for reality,” says Hong, Axiom’s CEO. “We do believe that there are a lot of pretty important use cases of high commercial value.”
Axiom’s approach involves combining large language models with a proprietary AI system called AxiomProver that is trained to reason through math problems to reach solutions that are provably correct. In 2024, Google demonstrated a similar idea with a system called AlphaProof. Hong says that AxiomSolver incorporates several significant advances and newer techniques.
Ono says the AI-generated proof for the Chen-Gendron conjecture shows how AI can now meaningfully assist professional mathematicians. “This is a new paradigm for proving theorems,” he says.
Axiom’s system is more than just a regular AI model, in that it is able to verify proofs using a specialized mathematical language called Lean. Rather than just search through the literature, this allows AxiomProver to develop genuinely novel ways of solving problems.
Another one of the new proofs generated by AxiomProver demonstrates how the AI is capable of solving math problems entirely on its own. That proof, which has also been described in a paper posted to arXiv, provides a solution to Fel’s Conjecture, which concerns syzygies, or mathematical expressions where numbers line up in algebra. Remarkably, the conjecture involves formulas first found in the notebook of legendary Indian mathematician Srinivasa Ramanujan more than 100 years ago. In this case AxiomProver did not just fill in a missing piece of the puzzle, it devised the proof from start to finish.
Tech
A School District Tried to Help Train Waymos to Stop for School Buses. It Didn’t Work
One of the purported advantages of self-driving car tech is that every car can learn from one vehicle’s mistakes. Here’s how Waymo puts it on its website: “The Waymo Driver learns from the collective experiences gathered across our fleet, including previous hardware generations.”
But in Austin, Waymo’s vehicles struggled for months to learn how to stop for school buses as drivers picked up and dropped off children. An official with the Austin Independent School District (AISD) alleged that the vehicles had, in at least 19 instances, “illegally and dangerously” passed the district’s school buses while their red lights were flashing and their stop arms were extended rather than coming to complete stops, as the law requires.
In early December, Waymo even issued a federal recall related to the incidents, acknowledging at least 12 of them to federal regulators at the National Highway Traffic Safety Administration (NHTSA), which oversees road safety. According to federal filings, engineers with the self-driving vehicle company had “developed software changes to address the behavior” weeks before.
But even after the recall, the school-bus-passing incidents continued, according to school officials and a report from the National Transportation Safety Board (NTSB), an independent federal safety watchdog that’s also investigating the situation.
Now, email and text messages between school officials and Waymo representatives, obtained by WIRED through a public records request, show the lengths that the Austin public school district and Waymo went to try to solve the problem. AISD even hosted a half-day “data collection” event in a school parking lot in mid-December, the documents show, with several employees pulling together school buses and stop-arm signals from across the fleet so the self-driving car company could collect information related to vehicles and their flashing lights.
Still, by mid-January, over a month later, the school district reported at least four more school-bus-passing incidents had taken place in Austin. “The data we collected from the beginning of the school year to the end of the semester shows that about 98 percent of people that receive one violation do not receive another,” an official with the school’s police department told the local NBC affiliate that month. “That tells us that the person is learning, but it does not appear the Waymo automated driver system is learning through its software updates, its recall, what have you, because we are still having violations.”
The situation raises questions about the self-driving technologies’ curious blind spots and the industry’s ability to compensate for them even after they’ve been spotted.
Self-driving software has long struggled with recognizing flashing emergency lights and road safety devices with long, thin arms, including gates and stop-arms, says Missy Cummings, who researches autonomous vehicles at George Mason University and served as a safety adviser to the NHTSA during the Biden administration. “If [the company] didn’t fix this a few years ago, the more they drive, the more it’s going to be a problem,” she says. “That’s exactly what’s happening here.”
Waymo did not respond to WIRED’s requests for comment. A spokesperson for the Austin Independent School District referred WIRED to the NTSB while the incidents are under investigation. A spokesperson for the NTSB declined to answer WIRED’s questions while its investigation continues.
Illegal Passing
By midwinter of 2025, AISD officials were frustrated. In one of the 19 incidents alleged by a lawyer for the district in a letter later released by federal road safety regulators, a Waymo passed a school bus letting off children “only moments after a student crossed in front of the vehicle, and while the student was still in the road.”
“Alarmingly,” the lawyer wrote, five of the alleged incidents had occurred after Waymo had assured the district that it had updated its software to fix the problem. Federal regulators with the NHTSA had already launched a probe into the behavior. “Austin ISD is evaluating all potential legal remedies at its disposal and intends to take whatever action is necessary to protect the safety of its students, if required,” the lawyer warned.
Tech
The Deceptively Tricky Art of Designing a Steering Wheel
Cars didn’t always have steering wheels. The very first car—the 1885 Benz Patent-Motorwagen, invented by Karl Benz—used a tiller system: a horizontal bar with a handle mounted to a vertical bar. The lever-like handle was similar in many respects to a boat’s rudder. Amazingly, it would be another nine years before French engineer Alfred Vacheron saw sense and fitted the first known steering wheel to his 4-horsepower Panhard for the Paris-Rouen race. Just four years later, in 1898, Panhard made the infinitely preferable and safer steering wheel standard on all its cars. And we’ve been using them ever since.
Hans-Peter Wunderlich is Mercedes’ creative director of interior design. He has been designing steering wheels for 35 years. “I started in 1991 on my first,” he tells me. “A steering wheel is really the most challenging and difficult element to sculpture, to design, to develop in the car.” It is so difficult that Wunderlich has used the wheel as a test on potential recruits.
“When we hire a designer, I have given them the task, after I see a nice portfolio, to draw me a steering wheel,” he says. “The steering wheel is, for me, the proof. Should I hire them or not? If a designer is able to create a perfect steering wheel, even just as a scribble, then they will be a good designer for the total interior of a car.”
It was this challenge, in part, that attracted Ive and his team. “Our starting point was trying to understand the essential nature of the problem to be solved, and that normally means dismissing received wisdom,” Ive tells me. “A car is the aggregation of multiple products, and, in many ways, we’re designing furniture. We’re designing complex and sophisticated input methods. One of the challenges was to try to create cohesion. You don’t get something to be cohesive by a set of rules. That was a wonderful new challenge, and one wrestled with over a number of years.”
For both Ive and Wunderlich, science accompanies the art of design. They talk of the intricacies of the ergonomics, the logic of the switches, factoring in an “exploding element in the center” (the airbag), which is getting more and more complicated, says Wunderlich. “Even the rim is an ergonomic science in itself,” he adds, saying that his team works hand in glove with Mercedes’ in-house ergonomics department on these stages. “It’s almost 50-50. We get requirements data from engineering and ergonomics.”
Spinning Out
Look closely at your steering wheel rim; in cross-section, it won’t be round. Cut it into segments, and each will likely have a different profile, aiming to optimize grip wherever your hands grasp the wheel. Even the padding has to be just right. “It mustn’t be like bone but also not too fat. You need a nice balance,” Wunderlich says. “[It must say] this car is solid, it’s quality, it’s strong, it’s powerful, but it’s not crude.”
“If you hold the wheel on the three and nine o’clock positions, you can carve in with your fingers on the rear of the rim—so you have the hump, the scallop of the rim,” Wunderlich says. “And then we carve into a valley where your fingers could rest. That means your hands can close. You have the feeling you’re holding the car. This is so challenging, because in that area you have such a technical structure to maintain—complex electronics and heating elements. We torture the engineers to keep that area so small so we can sculpt it out.”
Ive tortured Raffaele De Simone, Ferrari’s chief engineer and head development driver. De Simone is sometimes described at the company as “Customer No. 1” because, apparently, no Ferrari road car leaves the factory until he is satisfied with its performance.
Tech
Deals From the Amazon Spring Sale That Passed Our BS Test
After a relatively quiet few months, Amazon is bringing back another of its famously invented shopping holidays. The Amazon Spring Sale is in its third year, running now through March 31. Like during last year’s event, Amazon is promising customers thousands of deals across various daily, themed categories.
Of course, as we’ve seen in the past with Prime Day, Black Friday, and Cyber Monday, the true discounts on good products will likely be buried among junk deals on shoddy wares. The WIRED Reviews team tests gear all year long, and we fact-checked discounts on the products we actively recommend to our friends, family, and readers. We’ve highlighted the best deals from the Amazon Spring Sale below.
Be sure to check out our other deals coverage for vacuum discounts, smart bird feeders, and more.
Updated March 27, 2026: We’ve added additional deals, removed expired discounts, and checked for accuracy throughout.
WIRED Featured Deals:
Our audiophile reviewers test more headphones than anyone would deem sane or necessary. The Sony WH-1000XM6 are the pair they’ve declared the best wireless headphones of all, with “the best noise reduction on Earth.” You’ll also get 30 hours of battery life, multipoint Bluetooth pairing, folding ear cups and a travel case, sparkling and clear sound, and fabulous controls. They’re nearly perfect. When they’re not on sale for this price, they’re selling for the full MSRP. If you’re in the market, now is the time—or, if you’re not ready right now, wait until the next time they’re on sale for this price.
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