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Megan Rapinoe, Caitlin Clark, Serena Williams, Mia Hamm, Lindsey Vonnthe list of high-profile, recognizable women athletes is growing. And track and field athletes may be the next to become household names. Thats the bet that Alexis Ohanian is making with Athlos, an all-womens track and field league, which is hosting its second event in New York this week. Ohanian is perhaps best known as the cofounder of Reddit, but he’s also an investor whos made no secret of his interest in investing in sports. During a press event in New York City this week, he said the idea for Athlos came to him while watching the Olympics, during which millions of people tune in to watch track and field events. His logic: Why not try to tap into that audience outside of larger events? Thats how Athlos was born. The league is an attempt to capture the excitement around track and field events that has, traditionally, only existed around the Olympics and other big-time track and field events. Last year, during its inaugural event, Ohanian says it drew 3 million viewers, attracted big-name advertisers like Toyota and Tiffany & Co., and was more successful than anticipated. This year, he expects it to be even bigger, and hopes that some of the athletes taking part will start to become recognizable to casual sports fansperhaps on a level that even matches what Clark has achieved in basketball. “Americans are going to be paying attention” When the Olympics or World Championship track and field events come around, Americans are going to be paying attention,” Ohanian says. “[We] have a legacy of American excellence in the sport, especially among our women. No one doubted for a second that womens soccer, womens basketball, was a tier-one opportunity. Ohanian was joined at the press conference by a lineup of Olympic Gold Medalists, world champions, and recordholders, including Masai Russell, Alexis Holmes, Grace Stark, Keely Hodgkinson, Faith Kipyegon, and Georgia Hunter Bell. Those athletes and others will compete this week for a top prize of $60,000. And Athlos is also giving some of them the chance to focus entirely on their chosen events, something that, until very recently, only the top sliver of athletes have been able to do. British mid-distance runner Georgia Hunter Bell, for instance, said that she only recently was able to quit her full-time job in tech sales to focus on track and fieldand shes an Olympic medalist who has set national records. It was hard training around a full-time, corporate job and trying to train like a professional athlete, she said. But leagues like Athlos are creating pathways to the pros for athletes like her. Globally, revenue from women’s sports doubled from 2023 to 2024 and was expected to exceed $2.3 billion this year, according to a March 2025 report from Deloitte. Basketball and soccer remain the sector’s biggest moneymakers. Athlos is only the most recent attempt at creating a professional-level league for female athletes. Several others are already gaining traction, including the WNBA, the National Womens Soccer League (NWSL), and the Professional Womens Hockey League (PWHL). The demand is there, Ohanian argues, and theres a big business opportunity for brands, advertisers, athletes, and others to get in on itthough he thinks itll take some time. I think this is just the start. Were not at F1 (Formula 1) size yet, he said. But I want people to take for granted that this sportwhich, again, is the most popular sport during the Olympicscan have the same-size platform outside of that, and bring together athletes, builders, CEOs, and investors who can keep driving it.
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Greetings, salutations, and my thanksas alwaysfor reading Fast Companys Plugged In. Me: Are you here just to monitor for safety? Guy sitting in the drivers seat of the Tesla Model Y Im riding in: I cant specify. That was the extent of the conversation during a recent trip I took using Teslas Robotaxi service. I was curious why the car that picked me up had a human in it: After all, Tesla bills its service as the future of autonomy, and the car did, in fact, drive itself for the entirety of my 4.5-mile journey. But I didnt get any answers from this guyor Tesla the corporate entity, which prides itself on ignoring the media and didnt reply to my emailed questions. This we do know. After years of anticipation, Tesla rolled out Robotaxis in Austin in June. A month later, they arrived here in the San Francisco Bay Area. For now, however, it falls far short of a full-blown deployment of a small-r robotaxi service. (The term is often used generically for self-driving car services as well as being a Tesla trademark.) For one thing, I spent time on a waitlist before being allowed to start hailing cars. For another, Tesla reportedly launched Robotaxi in the Bay Area without securing the necessary approval to operate a fleet of autonomous vehicles in California. Its Robotaxis are autonomous in the same sense that any Tesla car with the misleadingly named full self driving package is autonomous. Hence the need for the guy in the drivers seata safety monitor who could take over in an emergency. Its a little like getting a lift from a friend who owns a Tesla, who would also be required to stay behind the wheel. In Austin, where Tesla is further along in the regulatory process, the company initially put the safety monitors in the front passenger seat, but has reportedly moved them to the drivers seat as well. All of this is fundamentally different from Waymo, which began as Googles self-driving car project andafter an extraordinarily long, hard, expensive slogis up and running in Austin, San Francisco, and three other U.S. metropolitan areas. Waymos have no safety monitors; its just you, any friends or relatives youve brought along, and the car. The service is a triumph not only of technology but also the patient labor required to convince relevant officials that permitting unsupervised cars to drive themselves around a city isnt a deadly mistake, and might even be safer than letting humans behind the wheel. The Robotaxis back-seat touchscreen [Photo: Harry McCracken] In its present incarnation, Teslas Robotaxi service also bears scant resemblance to the one Elon Musk talked up at an event in April 2019. Back then, the company was going to have a million such vehicles on the roadnot Tesla-owned ones, primarily, but privately owned cars that could hit the road and ferry passengers when their owners didnt need them. Oh, and Musk said that would happen by the end of 2020. During this presentation, Musk did cheerfully acknowledge his tendency to blow deadlines. But a half-decade later, his 2019 plan has barely inched toward reality. Even his comparatively modest recent prediction of Tesla autonomous ride-hailing being available to half the U.S. population (subject to regulatory approvals) by the end of 2025 is not going to happen. Meanwhile, I dont intend to pay much attention to the Cybercaba self-driving two-seater Tesla with no drivers seat, allegedly due next yearuntil Im riding in one. Judged on their own merits as a mode of transportation, Ive found my first Tesla Robotaxi trips uneven at best. Unexpectedly, the best part has been their aggressively low pricing. Tesla has abandoned its original per-trip flat rate of $4.20 (ha ha, Elon!). But for my journeys, Robotaxi always beat Waymo and Uber pricing, sometimes by a lot. The first trip I tookreturning home from a nearby mallcost a mere $1.92. More pluses: Teslas Robotaxi fleet of Model Y cars is more reliably clean and cushy than Uber or Lyft. The service covers a far broader swath of the Bay Area than Waymo. And unlike Waymos in their present form, Robotaxis can take the highwaypresumably because theyre not officially autonomous vehiclesmaking longer trips practical. Once one of the best-regarded car companies in the world, Tesla is now dogged with a reputation for safety problems, especially when it comes to self-driving: When I announced Id been in a Robotaxi, one friend told me I shouldnt put my life at risk like that. Grim humor aside, all the trips Ive taken felt safe and involved efficient routes. (I should note that in one case, the safety monitor did have his hands on the wheel a fair amount of the timewhether out of necessity or force of habit, I cant say.) Still, moving past the question of autonomy for a moment, I didnt find Robotaxis ready to replace ride-hailing services even in their traditional, human-driven form. How many taxis Tesla has in the Bay Area is a mystery, but its clearly not enough: When I checked, pickup wait times usually were in the neighborhood of 13 to 15 minutes and got as high as 29 minutes.Worse, the Robotaxi app often said no cars were available at all, and told me to try again later. The Robotaxi software also lacks Waymos polish. When I leaned forward to play with the back-seat touchscreen, I kept getting a message telling me to put my (still buckled) seat belt back on or the car would pull over. That screen appeared to offer an array of entertainment options, but when I tapped on Netflix and Disney+, all I got were sign-up promos. Then theres the services iPhone app, which has a rickroll-style gag involving tipping that I didnt find funny the first time and dont relish encountering on any future trips. Screens from Teslas Robotaxi app, including a supposed tipping option and what you get if you choose it Most of all, the need for the safety monitor eviscerates any possibility of Robotaxi rivaling the experience Waymo is already delivering. Once you get over the coolness factor, much of Waymos value proposition is the aura of comfy isolation. You can take calls, bang away at your laptop, or maybe even take a short nap without feeling like privacy is an issue or youre being rude to the driver. Its the closest thing to an office on wheels Ive ever encountered. The Robotaxi safety monitors may be a vestigial concession to regulatory reality, but they eliminate the magic of autonomy. Whenif?Tesla is able to safely ditch them, it will make the service a true Waymo competitor. For now, the monitors I encountered were perfectly polite but also resistant to my efforts to chat them up. Heres another dialogue I had with one: Me: So the car is driving itself? Safety monitor: Yeah. Surveys show that many people who havent been in a self-driving car remain deeply skeptical of the whole idea. I cant help but think that Tesla is missing an opportunity by not turning the monitors into ambassadors. Rather than deflecting inquiries, maybe they should be volunteering information, as if they were welcoming tour guides to the autonomous future Musk has promised but not yet fully delivered. Youve been reading Plugged In, Fast Companys weekly tech newsletter from me, global technology editor Harry McCracken. If a friend or colleague forwarded this edition to youor if you’re reading it on FastCompany.comyou can check out previous issues and sign up to get it yourself every Friday morning. I love hearing from you: Ping me at hmccracken@fastcompany.com with your feedback and ideas for future newsletters. I’m also on Bluesky, Mastodon, and Threads, and you can follow Plugged In on Flipboard. More top tech stories from Fast Company Whats it really like to use a folding phone? Life with the Google Pixel 10 Pro FoldA gimmicky category is growing up. And skepticism be damned, it does feel like a taste of the future. Read More Metas next big bet for VR: Your living roomThe companys Hyperscape VR app will have the ability to create digital replicas of your surroundings. Photorealistic avatars may soon follow. Read More What can the rise and falland reboundof NFTs teach us about the AI bubble? After the market for NFTs collapsed in 2022, the tech quickly fell out of the mainstream. It never went away, though. Experts now tell Fast Company what went wrong and whats next. Read More The flailing Trump Media is part of the Russell 3000 index. These states want to know why The companys poor performance raises questions about its inclusion. Read More This massive new data center is powered by used EV batteries A new project from battery recycling startup Redwood Materials and data center builder Crusoe shows that its possible to build data centers cheaper and faster while also slashing emissions. Read More ChatGPT wants to be the new operating system. Heres why that should worry us Compute has become the new oil, and OpenAI just secured drilling rights. Read More
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This past June, Meta set off a bomb in the marketing world when it announced that it would fully automate the advertising on its platforms by 2026. People in advertising wondered: Is this the end of ad agencies as we know it? Has the AI slopification of social media finally been fully realized? The hyperbolic reaction is understandablemaybe even justified. With 3.43 billion unique active users across its platforms around the world, and an advertising machine that brought in $47.5 billion in Q2 sales alone (up 22% over last year), Meta is an accurate bellwether for where the ad business is heading. Meta has been working for years to build a machine that is already pretty damn close to automating its entire ad system, from creative concept generation to determining whose eyeballs see the final product. Its current capabilities are good enough to give most advertising creatives the flop sweats. But now is not the time for marketers to cower in fear. The opposite, actually. This is a great moment for marketers face head-on how Meta views its relationship with creatives, agencies, and brands, as it continues to roll out new technologies and features. To help, we asked Meta ad execs to break down their strategy. Below is a detailed explainer to help you understand how Meta is thinking about its role in the advertising space, and what brands, agencies, and even consumers can do to better prepare themselves for whats to come. In this premium piece, youll learn: What Metas new AI advertising tools are and how they work, straight from the people creating them The reason why agencies will always be a part of Meta’s advertising equation Which tools are turbocharging growth for marketers, according to Helen Ma, Metas VP of product management (GenAI ad formats, video growth, creative diversification) Five key breakthroughs Earlier this month, Meta announced a slew of features to its AI-powered ad platform, including virtual try-on tech, AI-generated video for advertisers, and generative CTA (call to action) stickers to replace the common Buy Now” button. But to understand the significance of the new tools, its important to step back for a moment and dig into the technology infrastructure that powers Metas advertising system. [Image: Meta] Over the past few years, Meta has systematically rebuilt its entire ad infrastructure around AI. Each innovation builds on previous advances, creating compounding improvements in the effectiveness of ads on its platforms. (Take haircare brand Living Proof, for example, which saw an 18% boost in purchases after using Meta’s generative AI feature for ad creative, compared to using its usual campaign strategy and creative.) This all-in-one-place approach to marketing tools reduces the operational burden for advertisers while increasing their dependence on Meta’s systems. The goal for Meta is to be as embedded as possible in a brand’s overall marketing operation. Matt Steiner, Metas VP of monetization infrastructure for ranking and AI foundations, says there are essentially five key technological breakthroughs that underpin Metas AI advertising platforms. The focus is on automating and optimizing every part of the advertising process, from creative generation to targeting and performance measurement. Here’s what you need to know: Advantage Plus Shopping Campaigns: The Automated Ad ManagerInstead of advertisers needing large teams to constantly monitor their ads, analyze spreadsheets, and manually decide when to increase or decrease spending, Meta introduced Advantage Plus in 2022 to use machine learning models to do the heavy lifting. The AI constantly monitors which campaigns and audiences are performing well and automatically redirects the budget and changes the bid strategy 24 hours a day to maximize results. I think the key innovation that drives it is that machine learning models don’t get tired, Steiner says. He notes that this technology was key to Metas ad business when Apple introduced anti-tracking changes for iPhone users. Historically, Meta could track whether ads you saw on its platforms ultimately led to a purchase elsewhere, and this anti-tracking change cut off its lifeline to that information. Meta bypassed the blockage using transfer learning and combining its app data with advertisers own data on the people using its sites and making purchases. Meta Lattice: The “Shared Knowledge” SystemThis is a deep machine learning technology that allows different AI models to learn from each other. Traditionally, Meta had separate AI models predicting different user behaviors. For example, one model would predict who will click on an ad, while another would predict who would actually buy the product. Announced in 2023, Lattice utilizes transfer learning, which allows these models to share knowledge. Transfer learning is a concept where a machine learning model trained to do one task can be trained to do a second task, and its performance on the first task improves by being trained to do the second task. Generative AI for Ads Creative: The Automatic Ad DesignerThis set of tools, originally introduced in May 2024, automatically creates variations of a brands ad content across text and image backgrounds as well as entirely new images from scratch. It then optimizes them to look good and perform well on Meta platforms. This saves advertisers time by allowing them to test and learn what consumers respond to much faster than a human team could. Humans are best at coming up with novel ideas, says Steiner. They’re not really good at thinking of all variations of the word buy or sale, and thats not something people are really excited to do. So with machine learning models to automate that, they can spend their time doing the things that are uniquely human-skilled, like coming up with new ideas and really understanding why a campaign will resonate with peoplethings that are not really automatable today. [Image: Meta] Andromeda: The High-Speed Ad FinderThe goal of all Meta advertising is to match the right brands ad to the right person at the time that person is most likely to click (and buy). Thanks to the new AI ad tools rolled out over the past year, the number of ads available in Metas system increased rapidly. Within a month of launching its first AI tools in 2024, more than a million advertisers used Metas generative AI tools to create more than 15 million ads. This essentially clogged the system and made it harder and slower for Meta to search through all those ads to find the few that might be relevant to any particular user. In December Metaintroduced Andromeda, a massive technical and hardware upgrade to Metas backend infrastructure that lends it up to 10,000 times more computing power. Codesigned with Meta Training and Inference Accelerator (MTIA) and Nvidias Grace Hopper Superchip, Andromeda allows Metas system to handle the massive increase in demand for computing power from all the ads being created using its generative AI tools. Steiner says the result has been a dramatic improvement in the selection of relevant ads, increasing the likelihood of people finding a useful ad and ultimately driving up conversions for advertisers. According to the company, so far it has boosted conversions on Facebook mobile Feed and Reels by 4%. Generative Ads Recommendation Model (GEM): The Customer MapIntroduced in April, GEM is new AI model architecture for deciding which ad to show you, based on predicting future behavior. Just as an LLM uses sequence learning to predict the next logical item in a sequence, this does the same thing for ads. Instead of just predicting whether youll click on the next single ad, GEM tracks your entire history of ad interactions and purchases. This allows the model to recognize that you might be on several different, parallel “purchase journeys” simultaneously and react accordingly. The company says these improvements increased ad conversions by approximately 5% on Instagram and 3% on Facebook Feed and Reels in Q2. Virtual try-on [Image: Meta] Ad feeds of the future This new backbone technology is powering all the ads you see, but it’s all more or less invisible. Heres what Meta is betting on to get you buying more across Instagram, Facebook, and WhatsApp: Virtual try-on: This is exactly what it sounds like. Meta is now testing with select advertisers the ability to see how clothing featured in an ad looks on them after they upload a photo of themselves. AI Sticker CTA (call to action): Most of the time you see an ad on Instagram, theres a generic Shop Now button at the bottom. Now brands are going to be using custom AI-generated stickers that could be a product photo or a logo graphic to add a bit more flair. We’re seeing something like 50% to 200% higher click-through rates on these AI-generated CTA stickers, because they’re fun and visually appealing and bring the product to life, says Helen Ma, Metas VP of product management. Previously announced at Cannes, this visual enhancement is now available to more advertisers globally for Facebook Stories and testing for Facebook Reels, as well as Instagram Stories and Reels. Creative generation upgrades: Meta rolled out two notable updates to its generative AI tool kit. First is an AI-generated music feature that understands the content of an ad and produces unique, custom music that reflects the product, style, and sentiment a brand wants to convey. It will also feature AI dubbing for international or multilingual audiences. The other is what Meta calls persona-based image generation, to help advertisers further personalize ads to different customers. This is like an AI vibes tool, changing the vibe of an ad to fit specific audiences. If you’re selling headphones, it can create one image that focuses on style for a fashion angle, one to highlight sound quality for audiophiles, and another that emphasizes comfort for travelers, all from the same product image. Facebook creator discovery API: This makes it easier for brands to find creators on Facebook by allowing them and third-party partners (like agencies) to search for creators using keywords. It also helps agencies and brands explore creator insights like audience demographics and average engagement rate to find the best match. Meta AI assistant-informed ads: The Meta AI digital assistant has more than 1 billion active monthly users and is available as a stand-alone app, as well as across its apps like Facebook, Instagram, WhatsApp, and Messenger. Starting December 16, the company will utilize users’ interactions with the AI assistant to inform ads and other content it shows them. Krassimir Karamfilov, Meta Advertisings VP of product, says that the number of Meta platforms, combined with billions of users, makes it impossible for individual marketers to get the most out of their ads without the help of tools like this. It’s just impossible to manually test all the potential variants, so this is why AI is just making it easier to experiment efficiently and then home in on what works, Karamfilov says. He knows that some advertisers have expressed concerns over a lack of control, but he counters that ads perform better when theyre not limited to the brands initial parameters. We see a lot of suboptimal usage of our products, he says. What were doing is all about aligning our systems to the way the advertisers measure value. Creator marketplace [Image: Meta] Enter the AI Concierge Meta isnt stopping at the ads in your feed. It sees a bigger business opportunity in helping brandsespecially small and midsize businessesutilize AI agents in their own business operations like customer service. Earlier this month, the company launched Business AI, which acts as a sales concierge to help take a consumer from an ad in a Meta feed all the way to purchasing a product. It acts as a personalized AI agent on Meta ads, messaging threads inside Meta platforms, and can even extend to the brands own websites. Clara Shih, VP of Business AI, says Metas clients were asking for help beyond the advertising side. Our customers have said, We want AI to not only help with product discovery and generating leads, help us all the way to closure, help us with our business operations, help us with customer support questions, Shih says. [Image: Meta] A recent MIT study reported that 95% of enterprise generative AI pilots fail to deliver measurable business impact, despite a collective billions invested. Shih says Business AI takes the burden of infrastructure off of companies in order to feel that impact. It’s just very hard, and a lot of companies don’t have big machine learning and AI teams where they can piece all these things together, she says. So something else that’s been really important to us is creating something that’s easy to set up and maintain. The benefit to brands is that a Meta-powered AI chatbot doesnt have to learn about a brand from scratch because so many businesses and brands have been active on Meta foryears. Shih says all of their past ads and social posts are a gold mine of tacit knowledge about a businesses within the Meta universe, giving the Business AI chatbot a lot of information to work with from the start. They don’t have to hire a consultant and pay millions of dollars to set up their chatbot. We could just look at what they’ve said and what they’ve done and what their brand is all about, she says. And just by using LLMs to mine that information, we’ve been able to create the world’s first turnkey business agent that just works because it’s them. It’s all based on what they’ve done. Its all very fun and convenient in the short term. And Metas recent earnings prove that its working. Second-quarter ad sales hit more than $47 billion, a 22% increase year over year. Every executive I spoke to emphasized that these are tools for humans to use, and that the companys relationship with agencies and creatives are crucial to any of this workingat least for now. Just keep in mind that the end game here is still full automation. As Shih put it, Mark [Zuckerberg] has talked about how in the future, the dream state for a business is to come to Meta, share their product catalog, share their business outcomes, and then we can automate the rest through a combination of Advantage Plus AI features, all as a business agent, she says. And we are getting closer and closer to that.
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