This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. How a couple of ski bums built the internet’s best weather app  The best snow-forecasting app for skiers isn’t a federally-funded service or a big-name brand. It’s OpenSnow, a startup that uses government data, its own AI models, and decades of alpine-life experience to deliver the best predictions out there.  The app has proved especially vital this winter, one of the weirdest on record. It’s even made microcelebrities of its forecasters, who sift through reams of data to write “Daily Snow” reports for locations around the world.   We headed to the Tahoe mountains to hear how two broke ski bums became modern-day snow gods. Read the full story. 
—Rachel Levin  Here’s why some people choose cryonics to store their bodies and brains after death  —Jessica Hamzelou 
This week I reported on unusual research focused on the frozen brain of L. Stephen Coles.  Coles, a researcher who studied aging, was interested in cryonics—the long-term storage of human bodies and brains in the hope that they might one day be brought back to life. It’s a hope shared by many.  Over the past few years, I’ve spoken to people who run cryonics facilities, study cryopreservation, or just want to be cryogenically stored. All of them acknowledge that there’s a vanishingly small chance of being brought back to life. So why do they do it?  Read the full story to find out.  This article is from The Checkup, our weekly biotech newsletter. Sign up to receive it in your inbox every Thursday.  What’s next for space exploration?   Whether it’s the race to find life on Mars, the campaign to outsmart killer asteroids, or the quest to make the moon a permanent home to astronauts, scientists’ efforts in space can tell us more about where humanity is headed. To learn more about the progress and possibilities ahead, our features editor Amanda Silverman sat down with Robin George Andrews, an award-winning science journalist and author, on Wednesday. If you missed their conversation, fear not—you can catch up and watch the video here. You’ll need to be a subscriber to access it, but the good news is subscriptions are discounted right now. Bag yours if you haven’t already!  The must-reads 

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.  1 The Pentagon’s ban on Anthropic has been halted A judge has paused its designation as a supply chain risk. (CBS News)  + She said the government was trying to “chill public debate.” (BBC) + Sam Altman claimed he tried to “save” Anthropic in the clash. (Axios)  2 Elon Musk has lost his lawsuit against an ad boycott on X A judge admonished the “fishing expedition.” (Ars Technica) + Ad revenue fell by more than half as advertisers fled X after Musk took over. (BBC)  3 OpenAI has put plans for an erotic chatbot on hold “indefinitely” Staff and investors had raised concerns. (The Information $) + The company is making a sharp strategic pivot. (FT $) + AI companions are the final stage of digital addiction. (MIT Technology Review)  4 A helium shortage has started impacting tech supply chains The problem stems from the Middle East conflict. (Reuters) + The era of cheap helium is over. (MIT Technology Review)  5 Trump’s new science advisers: 12 tech chiefs and just one academic They include at least nine billionaires. (Nature) + David Sacks is stepping down as Trump’s crypto and AI czar. (TechCrunch)  6 Anthropic is mulling an IPO as soon as October It’s racing OpenAI to hold an initial public offering. (Bloomberg $)  7 Wikipedia has banned all AI-generated content  LLM-related issues had overwhelmed editors. (404 Media) + Here’s what we’re getting wrong about AI’s truth crisis. (MIT Technology Review) 
8 OpenAI’s ad pilot generated $100 million in under 2 months More than 600 advertisers are working on the trial. (CNBC) + Ads will arrive on ChatGPT free ‌and Go in the coming weeks. (Reuters)   9 An Irish village is giving kids a phone-free upbringing The ban works because almost everyone’s bought in. (NYT $)  10 Chatting with sycophantic AI makes you less kind New research found it encourages “uncouth behavior.” (Nature) 
Quote of the day  “I don’t know if it’s ‘murder,’ but it looks like an attempt to cripple Anthropic.”  —Judge Rita Lin rules against the Pentagon’s ban on Anthropic, The Verge reports.  One More Thing  AURELIA INSTITUTE This futuristic space habitat is designed to self-assemble in orbit   More and more people are traveling beyond Earth, but the International Space Station can only hold 11 of them at a time.   Aurelia Institute, an architecture R&D lab based in Cambridge, MA, is building a solution: a habitat that launches in compact stacks of flat tiles—and self-assembles in orbit.   The concept may sound far-fetched, but it’s already won support from NASA. Read the full story. 
—Sarah Ward  We can still have nice things  A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.)  + These optical illusions are absolute brain-melters. + The web design museum lovingly visualizes the evolution of the internet. + Zara Picken’s modernist illustrations are a new window into the mid-20th century. + Explore our planet’s connections through the digital Knowledge Garden. 

This week I reported on some rather unusual research that focuses on the brain of L. Stephen Coles. Coles was a gerontologist who died from pancreatic cancer in 2014. He had spent the latter part of his career specializing in human longevity. And before he died, he decided to have his brain preserved by a cryonics facility. Today, it’s being stored at −146 °C at a center in Arizona, where it sits covered in a thin layer of frost. Coles also tasked his longtime friend Greg Fahy with studying pieces of his brain to see how they had fared (partly because he was worried his brain might crack). Fahy, a renowned cryobiologist, has found that the brain is “astonishingly well preserved.” But that doesn’t mean Coles could be reanimated. Over the past few years, I’ve spoken to people who run cryonics facilities, study cryopreservation, or just want to be cryogenically stored. All those I’ve spoken to acknowledge that the chance they’ll one day be brought back to life is vanishingly small. So why do they do it?
The first person to be cryonically preserved was James Hiram Bedford, a retired psychology professor who died of kidney cancer in 1967. Affiliates of the Cryonics Society of California, an organization headed by a charming TV repairman with no scientific or medical training, perfused his body with cryoproctective chemicals to protect against harmful ice formation and “quick-froze” him. Today, Bedford’s body is still in storage at Alcor, a cryonics facility based in Scottsdale, Arizona. It’s one of a handful of organizations that offer to collect, preserve, and store a person’s whole body or just their brain—pretty much indefinitely. It’s where Coles’s brain is stored.
Both men died from cancer. Medicine could not cure them. But in the future, who knows? One of the premises of cryonics is that modern medicine will continue to advance over time. Cancer death rates have declined significantly in the US since the early 1990s. I don’t know what exactly drove Coles and Bedford to their decisions, but they might have hoped to be reanimated at some point in the future when their cancers became curable. Others simply don’t want to die, period. Last year, I attended Vitalist Bay, a gathering for people who believe that life is good and that death is “humanity’s core problem.” Emil Kendziorra, CEO of the cryonics organization Tomorrow.Bio, spoke at the event, and a healthy interest in cryonics was obvious among the attendees. Many of them believe that science will find a way to “obviate” aging. And some were keen on the idea of being preserved until that happens. Think of it as a way to cheat not only death but aging itself. This sentiment might have support beyond the realms of Vitalist Bay, according to research by Kendziorra and his colleagues. In 2021, they surveyed 1,478 US-based internet users who were recruited via Craigslist. They found that men were more aware of cryonics than women, and more optimistic about its outcomes. Just over a third of the men who completed the survey expressed interest “a desire to live indefinitely.” Still, cryonics is a niche field. Worldwide, only around 5,000 or 6,000 people have signed up for cryopreservation when they die, Kendziorra told me when we chatted at Vitalist Bay. He also told me that his company gets between 20 and 50 new signups every month. And there are plenty of reasons why people don’t do it. A small fraction of the people who responded to Kendziorra’s survey said that they thought the idea of cryonics was dystopian, and some even said it should be illegal. Then there’s the cost. Alcor charges $80,000 to store a person’s brain, and around $220,000 to store a whole body. Tomorrow.Bio’s charges are slightly higher. Many people, including Kendziorra himself, opt to cover this cost via a life insurance policy. Perhaps the main reason people don’t opt for cryonic preservation is that we don’t have any way to bring people back. Bedford has been in storage for more than 50 years, Coles for more than a decade. All the scientists I’ve spoken to say the likelihood of reanimating remains like theirs is vanishingly small.

The fact that the possibility—however tiny—is above zero is enough for some, including Nick Llewellyn, the director of research and development at Alcor. As a scientist, he says, he acknowledges that the chances reanimation will actually work are “pretty low.” Still, he’s interested in seeing what the future will look like, so he has signed himself up for the cryonic preservation of his brain. But Shannon Tessier, a cryobiologist at Massachusetts General Hospital, tells me that she wouldn’t sign up for cryonic preservation even if it worked. “It turns into a philosophical question,” she says. “Do I want to be revived hundreds of years later when my family is gone and life is different?” she asks. “There are so many complicated philosophical, societal, [and] legal complications that need to be thought through.” This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

Today, we’re advancing Gemini’s real-time dialogue capabilities with Gemini 3.1 Flash Live, our highest-quality audio and voice model yet. It delivers the speed and natural rhythm needed for the next generation of voice-first AI, offering a more intuitive experience for developers, enterprises and everyday users.3.1 Flash Live is available across Google products:For developers: Robust reasoning and task executionWe’ve improved 3.1 Flash Live’s overall quality, making it more reliable for developers and enterprises to build voice-first agents that can complete complex tasks at scale. On ComplexFuncBench Audio, a benchmark that captures multi-step function calling with various constraints, it leads with a score of 90.8% compared to our previous model.

As AI models get better at holding natural conversations, we must examine how these interactions affect people and society.Building on a breadth of scientific research, today, we are releasing new findings on the potential for AI to be misused for harmful manipulation*, specifically, its ability to alter human thought and behavior in negative and deceptive ways. With this latest study, we have created the first empirically validated toolkit to measure this kind of AI manipulation in the real world, which we hope will help protect people and advance the field as a whole. We’re publicly releasing all materials necessary to run human participant studies using the same methodology. (Note: The behaviors observed during this study took place in a controlled lab setting, and do not necessarily predict real-world behaviors.)Why harmful manipulation mattersConsider two scenarios: One AI model gives you facts to make a well-informed healthcare decision that improves your well-being. Another AI model uses fear to pressure you to make an ill-informed decision that harms your health. The first educates and helps you; the second tricks and harms you.These scenarios highlight the difference between two types of persuasion in human-AI interactions (also defined in earlier research):Beneficial (rational) persuasion: Using facts and evidence to help people make choices that align with their own interestHarmful manipulation: Exploiting emotional and cognitive vulnerabilities to trick people into making harmful choicesOur latest work helps us and the wider AI community better understand the risk of AI developing capabilities for harmful manipulation and build a scalable evaluation framework to measure this complex area. To do this effectively, we simulated misuse in high-stakes environments, explicitly prompting AI to try to negatively manipulate people’s beliefs and behaviours on key topics.Developing new evaluations for a complex challengeTesting the outcomes of AI harmful manipulationTesting for harmful manipulation is inherently difficult because it involves measuring subtle changes in how people think and act, varying heavily by topic, culture and context.This is what motivated our latest research, which involved conducting nine studies involving over 10,000 participants across the UK, the US, and India. We focused on high-stakes areas such as finance, where we used simulated investment scenarios to test if AI could influence how people would behave in complex decision-making environments, and health, where we tracked if AI could influence which dietary supplements people preferred. Interestingly, the AI was least effective at harmfully manipulating participants on health-related topics.Our findings show that success in one domain does not predict success in another, validating our targeted approach to testing for harmful manipulation in specific, high-stakes environments where AI could be misused.How could AI manipulate?In addition to tracking efficacy (whether the AI successfully changes minds), we also measured its propensity (how often it even tries to use manipulative tactics). We tested propensity in two scenarios: when we explicitly told the model to be manipulative, and when we didn’t.As detailed in our research, we counted manipulative tactics in experimental transcripts, confirming the AI models were most manipulative when explicitly instructed to be.Our results also suggest that certain manipulative tactics may be more likely to result in harmful outcomes, though further research is required to understand these mechanisms in detail.By measuring both efficacy and propensity, we can better understand how AI manipulation works and build more targeted mitigations.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Why this battery company is pivoting to AI  Qichao Hu doesn’t mince words about the state of the battery industry. “Almost every Western battery company has either died or is going to die. It’s kind of the reality,” he says.   Hu is the CEO of SES AI, a Massachusetts-based battery company. It previously developed advanced lithium batteries for major industries, but is now shifting to AI materials discovery. Read our story to find out why.   —Casey Crownhart 
This startup wants to change how mathematicians do math  Axiom Math, a California startup, has released a free AI tool with a big ambition: discovering mathematical patterns that could unlock solutions to long-standing problems.  Most of the successes with AI tools have involved finding solutions to existing problems. But that’s not all they could do. There are lots of problems in math that require new ideas nobody has ever had, which could come from spotting patterns that have never been spotted before.  
Axiom Math’s new tool aims to find these hidden links. Read the full story to discover their plans—and how AI in general could change mathematics.  —Will Douglas Heaven  Are high gas prices good news for EVs? It’s complicated.  As the conflict in Iran has escalated, fossil-fuel prices have been on a roller-coaster—and some EV owners are celebrating.   They believe the volatility will create an opportunity for electric vehicles to make headway. But even the carless among us should be concerned about a sustained rise in fossil-fuel prices.   To find out why, read the full story.  —Casey Crownhart  This article is from The Spark, our weekly climate newsletter. Sign up to receive it in your inbox every Wednesday.  The must-reads 

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.  1 Meta and YouTube have been fined for designing addictive products They must pay damages of $6 million for harming young people. (Guardian) + The verdicts will reshape legal protections for Big Tech. (WSJ $) + They could also ripple through social media markets worldwide. (Rest of World) + Juries have started taking the lead in the push for child online safety. (NYT)  2 SpaceX aims to file for IPO as soon as this week It’s hoping to raise more than $75 billion. (The Information) + Rocket stocks soared on the report. (BBC)  + But rivals are challenging SpaceX’s dominance. (MIT Technology Review)  3 A new AI safety bill would halt data center construction It was introduced by Bernie Sanders. (Wired) + Nobody wants a data center in their backyard. (MIT Technology Review + One solution: launch them into space. (MIT Technology Review)   4 Meta has laid off 700 employees After raising compensation for top earners. (NYT $)  5 Elon Musk wants a Delaware judge to recuse herself over an emoji She liked a LinkedIn post criticizing him. (CNBC) + The case had ruled Musk misled investors during the Twitter purchase. (Reuters)  6 Reddit will require “fishy” accounts to verify that a human runs them The process aims to combat the deluge of bots. (Ars Technica)  7 Uber and Pony AI aim to launch Europe’s first robotaxi service in Croatia Pony AI is also running trials in Luxembourg, while Uber is testing in London. (The Verge) 
8 Google says quantum computers could break all cryptographic security by 2029 It’s set a timeline to secure the quantum era. (Gizmodo) + Quantum computers could soon solve health care problems. (MIT Technology Review)  9 New research shows cloning doesn’t produce perfect copies Clones have lots of extra, potentially dangerous mutations. (New Scientist) 
10 The landmark AI Scientist has just completed peer review  It’s billed as the first AI tool built to fully automate the scientific process. (Nature)  Quote of the day  “For years, social media companies have profited from targeting children while concealing their addictive and dangerous design features. Today’s verdict is a referendum—from a jury, to an entire industry.”  —Attorney Rachel Lanier offers her view on yesterday’s fines for Meta and YouTube, the Washington Post reports.   One More Thing  GETTY IMAGES Longevity enthusiasts want to create their own independent state. They’re eyeing Rhode Island.   It’s incredibly difficult and expensive to study innovative ways to slow or reverse aging. In response, longevity enthusiasts have devised an ambitious plan: establish an independent state for life-extension experiments.   They envision a jurisdiction that slashes red tape, encourages self-experimentation with unproven treatments, and eliminates laws that limit how companies develop drugs.  
Exactly where their longevity state might emerge is still being worked out—but one appealing location is Rhode Island. Read the full story to learn more about the plans.   —Jessica Hamzelou  We can still have nice things  A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.)  + These gleaming photos of ancient insects in amber are time capsules of the dinosaur age. + Paint with pixels across a world map at this unique digital canvas. + Hands have a new shield against hammers: a nail holder that protects your fingers. + This new audio player uses cartridges to give digital music a soul. 

The best snow-forecasting app for skiers and snowboarders isn’t from any of the federally funded weather services. Nor from any of the big-name brands. It’s an independent app startup that leverages government data, its own AI models, and decades of alpine-life experience to offer better snow (and soon avalanche) predictions than anything else out there.Skiers in the know follow OpenSnow and won’t bother heading to the mountains—from Alpine Meadows to Mont Blanc, Crested Butte to Killington—unless this small team of trusted weathered men tells them to. (And yes, they’re all men.) The app has made microcelebrities of its forecasters, who sift through and analyze reams of data to write “Daily Snow” reports for locations throughout the world. “I’m F-list famous,” OpenSnow founding partner and forecaster Bryan Allegretto says with a laugh. “Not even D-list.”  The app has proved especially vital this year, which has been one of the weirder winters on record. The US West saw very little daily snow, despite an intense storm cycle that led to one of the deadliest avalanches in history. That storm was followed by one of the fastest melts in memory, and several resorts in California are already shutting down for the season. Meanwhile, in the East, the ongoing snowfall has offered a rare gift: a deep and seemingly endless winter..  MIT Technology Review caught up with Allegretto, better known as BA, in the Tahoe mountains to talk about the weather, AI, avalanches, and how a little weather app became the closest thing powder-hounds have to a crystal ball: a daily dump of the freshest, most decipherable, and most micro-accurate forecasts in the biz. And how two once-broke ski bums—Allegretto and his Colorado counterpart, CEO Joel Gratz— managed to bootstrap a business and turn an email list of 37 into a cult following half a million strong. 
This interview has been edited for clarity and accuracy.  You grew up in New Jersey. Middle of the pack as far as snowy states. What were your winters like as a kid?
I was always obsessed with weather. Especially severe weather. Nor’easters. There was the blizzard of ’89, I believe, that hit the East Coast hard—dropped two to three feet of snow, which was a lot for the Jersey Shore. My dad worked for the highway authority, so he had tools other than the evening news. He was in charge of calling out the snowplows whenever it snowed, so I just remember chasing storms with my dad. I wasn’t allowed to ride in the snowplows. I’d watch them. When I got older, I was the one shoveling the neighbors’ driveways. I just liked being out there. In it. In college, I used to go around and shovel all the girls’ sidewalks. That was fun.  When did you start skiing? We would cut school and take a bus to go skiing, unbeknownst to our parents. It was the ’90s, and the surfers decided snowboarding would be fun, so the local surf shop started  running a bus and all these surfers would show up and hop the bus to Hunter Mountain. We’d drive to the Poconos, go night skiing, turn around. It wasn’t uncommon for me in high school to get in the car by myself, either —and just drive. Me, my dog, my backpack. I’d sleep in gas stations and ski. Storm-chasing around the Northeast.  What were you really chasing, you think? Natural highs. Happiness. I’ve always been a soul-searcher. I grew up in a crazy house situation, a broken home. My dad left. My mom became a drug addict. I just wanted to be gone. I’m the oldest. I was always trying to help my mom and make sure she was okay. No one was telling me to go to school and have a career. I just wanted to do something that fulfills me. How’d you go about figuring out what that was?  For me, to go to school was a big task, given where I was coming out of. There wasn’t any money. I could get grants and scholarships because my mom was so poor. I wanted to go to Penn State but didn’t have the grades. I ended up at Kean, a public university in New Jersey. It had a meteorology program. We got to go to New York City, to NBC, and practiced on the green screen. In meteorology school, I started thinking: How do I work in the ski and snowboard industry and use weather at the same time? I went to Rowan [University] for business, in South Jersey, and in between moved to Hawaii to surf and spent a year teaching snowboarding. My goal the whole time was to not work in a career I hated. I imagine you weren’t like most meteorology students. 

Us punk rockers, skaters, snowboarders—we were a little different than the typical meteorology nerds. I was the radical storm chaser. A big personality. I still am. You didn’t quite fit the traditional weatherman mold. Back then, there were no smartphones or social media. If you were a meteorologist, you either worked in a cubicle for the government or at an insurance company assessing weather risk.  Or you were on the local news. That wasn’t my thing. They didn’t want Grizzly Adams up there with his big beard. Beards belong in the mountains? Meteorologists live in cities because that’s where the jobs are. They don’t live in small mountain towns.  That’s what was missing in the industry. When I moved to Tahoe, in 2006, I realized nobody had any trust in the weather forecasts. It was more like a “We’ll believe it when we see it” old-fashioned mentality. If you’re a forecaster in flat areas, you just look at the weather model and regurgitate the news. Weathermen in Sacramento or Reno didn’t give a crap about the ski resorts! They’d just say “We’ll see three feet above 6,000 feet” and go on to the next segment. And skiers were like: “Wait a minute. Is it going to be windy at the top?” I thought: Let’s home in and give skiers what they’re looking for. So you were living in Tahoe, skiing and forecasting? I was working in the office at a resort, snowboarding, and doing weather on the side. I’d get up at 4 a.m. and do it before my 9 a.m. day job. Forecasting, figuring out: How the heck do these storms interact with these mountains? I started emailing everyone in the office what I’d see coming, and people kept saying “Add me! Add me!”  Eventually, resorts around Tahoe started asking to use my forecasts. How were you actually forecasting, though? 
The NOAA, the GFS [Global Forecasting System], the Canadian model, the Euro model, German, Japanese—all these governments make these weather models to forecast the weather. And share it. Anyone can access it. But you can’t just look at a weather model and go, Yep, that’s what’s going to happen. That’s not how it works in the mountains. It’s way harder. You can’t rely on model data. It’s low-res, forecasting for a grid area that’s too big. It can’t understand what’s going on. It’s going to generalize the weather. You can try that, but you’re going to be wrong. A lot of people are going to stop listening. I was able to forecast more accurately than most people because I was living there; I could fix a lot of these errors. Around 2007, I started my own website, Tahoe Weather Discussion. Bryan Allegretto (right) on the lift with OpenSnow CEO Joel Gratz and Gratz’ wife Lauren.COURTESY OF BRYAN ALLEGRETTO Snazzy. Meanwhile, I heard about this guy Joel out in Boulder, Colorado. People were telling us about each other, saying: “You guys are doing the same thing!” He was sleeping on his friend’s couch, running a site called Colorado Powder Forecast. And then there was Evan [Thayer, who would later join the company], in Utah. I think his website was called Wasatch Forecast. 
Great minds!He actually grew up outside Philly, only about an hour from me. We both were obsessed with storms and snow and moved west to the mountains and started similar websites. We would’ve been best friends as kids! Anyway, Joel called me in 2010 and was like, “Hey. I’m building this site, forecasting skiing in ski states.” And wanted me to join. He knew I had big traffic. He was like, “Let’s do it together, not against each other.” I asked, “What’s the pay?” He said, Zero. Give me your company.  And you just said: Yeah, sounds good? I just really trusted him. He’d asked Evan too—but Evan was like, Give you my site and my traffic for free?? No, I built this. A normal response. I was the knucklehead that was like, okay. Evan was still single. I already had a wife and two kids. I’d just had my son. I was working two jobs. I was so overwhelmed. So busy with my day job, as an account manager at the Ritz at North Star. Vail had just bought them and we all thought we were going to lose our jobs. My site was struggling. I was desperate for somebody to do it with. I think I thought it was a good opportunity. I was scared, though. For sure.   That was 15 years ago. How’d OpenSnow work in the old days?  We were just using our brains. That’s how it started: with us using our brains.Looking at all the weather models—all the data from the government models and airplanes, satellites, balloons. A million places. Building spreadsheets and fixing all the errors in the forecast models. We’d take the data and reconfigure it—appropriate it for the mountains. It was all manual for a really long time. How manual? 
It was old-school. All the resorts had snowfall reports on their sites, and I was the one hand-keying it in: “three to six inches.” That was me on the back end, typing it in every single morning for every single ski resort. It’d take me hours.  And then? Around 2018, we built our own weather model to do what we were doing. We called it METEOS. It’s an acronym—I can’t even remember what it stood for!  METEOS was just us using our brains and our experience to create formulas. It automated everything and allowed us to create a grid across the whole world and forecast for any GPS point. It took all this data, ingested it, fixed some of it, and then spit out a forecast for any location. In the world. 
Were you guys making any money?  It was crap in the beginning. Advertising-based. We stole Eric Strassburger from The Denver Post —he doubled our ad revenue in his first year full-time with us. Still, Google Ads had chopped our ad rates in half; it wasn’t a good long-term strategy to rely just on ads. We had to pivot to plan B so we didn’t go out of business.  Subscriptions. When all the newspapers started charging to read articles, Joel was like: We are meteorologists writing columns every day. Journalism weather is not sustainable! We need to be a weather site. We need to be a weather app.  What happened when you moved from ads to subscriptions?  The money took off.  We could quit our day jobs and work full time on OpenSnow. The company exploded. We were like: Are people gonna really pay for this? They did! Although they could still access the majority of the site for free.  At the end of 2021, you put in a pay wall?That’s when we panicked! We’re gonna lose 90% of our customers! But 10% will stay loyal and pay. Since the beginning, there’s been only two times our traffic went down: the paywall and covid. Otherwise, every year it’s gone up. People were like, Okay I can’t live without this. I admit, I’m one of those people. So is my editor. Any other weather app is useless for skiers. When it comes to ski towns, everyone uses OpenSnow. When the Tahoe avalanche happened, we were up early on search-and-rescue calls, helping the rescuers with forecasts. We’re now the official lead forecast providers for Ski California. Ski Utah. Head of Forecasting for National Ski Patrol. Professional Ski Instructors of America. US Collegiate Ski & Snowboard Association. Dozens of destinations and ski resorts. Joel doesn’t like to talk about it publicly, but our renewals and retention and open rates blow away the industry standards.  I bet. OpenSnow is like a benevolent cult.  People connect with a small company with underground roots. We’re independent. Fourteen full-time, plus seasonal. About half have meteorology backgrounds, from bachelor’s to doctoral degrees. Our very first employee was Sam Collentine,  a meteorology student in Boulder, who started as an intern in 2012 and is now our COO and does everything.  Sounds like employees and subscribers sign on and just … stay. Everyone stays! Our cofounder Andrew Murray, Joel’s friend and OpenSnow’s web designer, left around 2021. But yeah, people feel like they know us. They’ve been reading me in Tahoe with their coffee for 20 years! I get recognized everywhere I go. For example, I broke my binding, and went into a ski shop and asked if I could demo. And the guy was like, ARE YOU BA? Just take it! Sounds fun—until you just want to have dinner with your family, or buy a glove. Joel gets the same thing—people make Joel shrines in the slopes that look like Catholic candles. You guys are like modern-day snow gods. Gods of snow. People are weird. How weird? Someone once sent me a photo, saying: “Look, my friend dressed up as you for Halloween!” People are always inviting me over to dinner, to PlumpJack with Jonny Moseley. I guess they want to hang out with the “Who’s who of Tahoe.” There was an executive from Pixar who had me to his multimillion-dollar home on the west shore of Lake Tahoe. He had a photo of me over the fireplace in the bathroom. I thought: That’s weird, he has a photo of me over the fireplace. What was even weirder, though: It was autographed. I’ve never autographed a photo in my life! This guy just signed it—himself. I didn’t say anything. I just left. Do you get a lot of hate mail? Mean DMs?  Thousands. People think I can make it snow. I think they think I’m to blame when it doesn’t. The other day, someone messaged me on Instagram with a picture I’d posted over California of the high-pressure map—somebody had shared it, and wrote “Fuck Bryan Allegretto” over the high pressure. Hilarious. People were yelling at me during covid: You’re encouraging people to go out skiing! It wasn’t March 202o, it was January 2022. I’ve since deleted my personal social media. I never wanted to be in the spotlight. That’s the whole reason signing off my forecasts with “BA” became a thing— I didn’t want to use my full name. I just do it because it’s good for the company. Joel realized years ago that people come to us for forecasts —and forecasters. That’s why we still have forecasters. Even though AI can do what we’re doing now. Is AI doing what you do now?  We were using METEOS until this season. In December, we launched PEAKS. We built our own machine-learning model. The AI is taking what we were doing—and doing it everywhere, faster. The whole world instantly, in minutes. It can go back and actually ingest decades of government data—estimated weather conditions over the entire US from 1979 to 2021—and correct the errors.  What makes it so accurate? Before PEAKS, it wasn’t very specific. The data used to be what Joel calls “blobby”—like giant blobs, just big splotches of color over a mountain range. It’s like, if you take a pen and press into a piece of paper, the ink will spill out. The AI is like if you just tap the paper. A dot versus a blot. Now we can know how much it will snow, say, in the parking lot at Palisades and how much at the summit. It’s less blobby, more rigid and defined.  Defined how? All weather models output forecasts on a grid. The gridpoints are essentially averaged data over the grid box. So a model with a 25-kilometer grid resolution averages data over 25 kilometers, or around 16 miles. This is far too large an area, especially in mountainous terrains where a few miles can make a massive difference in experienced conditions. The AI is downscaling the models into smaller and smaller grid boxes. We are able to train a model to transform lower-resolution data from the same period into this high-resolution “ground truth” data. Then the model can generalize this training to global real-time downscaling. PEAKS is learning wind patterns, thermal gradients, terrain, and weather patterns and connecting all these factors to learn how to transition from coarse resolution into high, three-kilometer resolution—leading to more precise forecasts. We’ve basically taught the AI how to forecast like us. Except 50% more accurate. Now, when I wake up at 4 a.m., PEAKS has already done it. So … then what are you doing at four in the morning? Oh, I’ll still do the forecasting. I like to double-check it—but I don’t really need to. PEAKS has allowed me to spend more time on writing. Now instead of spending four hours forecasting and then rushing to write it,  I’ve been able to make my forecasts more interesting, more entertaining. Yeah, AI could probably write it—but I want to. It’s all about the personal connection.  How did last year’s federal funding cuts for the NWS and NOAA affect your business? Are you guys concerned about that going forward?We had those discussions when it first happened. In forecasting, you still need humans: to launch the weather balloon, staff the weather stations, collect the initial data. Some people in our office panicked—they had spouses or friends getting laid off. We were wondering if we’d have less data coming in, if it’d make the models less accurate. But the backlash in the weather community was swift. I think they were like, There are important things you can’t cut. It was pretty short-term. Are we worried going forward?  No, not as long as the data keeps coming in! We won’t survive without the government publishing data. What’s next?  We recently bought a small company called StormNet that tracks severe weather, probability of lightning, hail, tornadoes. We just launched it. Used to be like, “The storm is an hour away.” Now we can say, “In seven days there might be a tornado here.” And next winter, we’re working on a feature that can help forecast avalanches using AI. Right now, it’s still manual—people going out testing the snow layers. Forecasting is limited. This wouldn’t replace the avalanche centers, but it will be able to look at everything, including slope angle and previous weather and current conditions, and forecast further out, give people more advance—and location specific—warning. Help alert the public sooner. Help save lives.  I talked to one of the guys who left the Frog Lake huts on Sunday, before the storm. Before the group that was caught in the Tahoe avalanche. He told me: “People are always like, Oh, it’s never as bad as they say. But I read OpenSnow. I could tell by the language you were using, that we should get the heck out of there. I wanted no part of that.” We don’t hype storms. Or sugarcoat. Our only incentive is to be accurate. True that it was the biggest storm in Tahoe in four decades? In 1982, we got 118 inches over five days, and this one was 111 inches—two storms of similar size created the same level tragedy. It’s too much, too fast. It was snowing three to four inches an hour. That was the fastest we’ve seen. I don’t know what’s the bigger story—the fact that we’ve had the biggest storm in over four decades or the fact that all that snow disappeared in five days. Do you worry about the future of OpenSnow given, you know, the future of snow?We’ve had the second-warmest March in at least 45 years. We’re just getting these wild swings now. The seasonal snow averages are almost the same, but we’re seeing more variability than we did in the 1980s and ’90s. We’re either getting really cold and really warm, or really dry and really wet. Bad years can affect our business, for sure.  It’s certainly affecting the industry—I know Vail, Alterra took big hits this year. Usually we’re okay, because if it’s dry in Tahoe, it’s snowing in Utah or Colorado. Our three biggest markets. I don’t recall a season where the whole, entire West was in the same boat. It’s been the worst year in the West. Yet our traffic keeps going up. Everything is up. The East Coast had a good year, Japan, BC. We’re slowly expanding in those places. It happens to be the first year in 15 years we started marketing. Marketing works! Amazing.Joel and I have had this repeat conversation for years—we just had it again two weeks ago: “Can you believe what we’ve done? This was never the goal.” I’m still blown away daily. We’ve never borrowed from investors. No series A, B, C. We’ve gotten offers to sell, but no. We’re still having too much fun. All I know is: Joel and I didn’t come from money. We’ve never chased money or fame, and got both. I think it’s because we never chased them. We’ve always chased the joy of skiing and forecasting powder, and doing that for other people.We were just trying to create something that made us happy.