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When the new year rolls around, many people will resolve to get in better shape. Last year, Americans poured $44.8 billion into the fitness industry, flocking to gyms and buying at-home fitness equipment. But it usually takes just two weeks for people to abandon their goals. Gym memberships go unused. Peloton bikes collect dust. Researchers at the National Institutes of Health have found that amidst all the fitness options on the market, personal training tends to lead to better results for several reasons: It involves a personalized program, fits into the participant’s schedule, and requires being accountable to the trainer. But personal training is expensive, priced anywhere from $50 to $150 (or more) per hour for one-on-one sessions. Ray, a new AI-powered fitness app, wants to offer all the benefits of a personal trainer for a fraction of the price. (In fact, the service is free for early users, but will eventually start charging a monthly fee.) When you open the app, an AI trainer that looks and sounds like a real person will guide you through a workout. The program will be customized to your goals, your bodily limitations, the equipment you have handy, and the amount of time you have. And like a human trainer, Ray will observe your movements to help you improve your form and offer more challenging workouts as you improve. Ray will also follow up with you by text, like a real trainer, to see how the session went and to help schedule the next one. Importantly, the technology is going to keep improving as more people use Ray and as AI evolves. “The conversation’s going to get more fluid; the vision is going to get better,” says Colin Raney, Ray’s cofounder. “We’re currently working on grunt recognition, to see if we can identify how the user is doing based on the sounds they’re making.” [Photo: Ray] Why Personal Training Works Ray is the brainchild of Rich Miner, cofounder of Android, and Raney, an Ideo veteran and former CMO of PillPack. Over the years, both have relied on personal trainers and found them transformative. For Raney, it was clear that there were many aspects of working with a human being that could cultivate real behavior change. “I needed the accountability of not wanting to let my trainer down by not showing up,” he says. “Or tuning the workout to me if I had a bad day, or my back wasn’t feeling right, or if it looked like I was ready to push myself that day.” Raney has thought about improving people’s health by changing their behavior. He helped build PillPack, which was designed to help people actually take their medicine by delivering it monthly in packets sorted by date and time. He believed it would be possible to get people to workout more frequently if they had access to the qualities of a personal trainer. [Photo: Ray] “Our thesis was that if you build the right behavioral loop, people will workout more regularly,” he says. This aligns with research that finds that people who relied on a personal trainer lost fat and built muscle, with a lower rate of injury, compared to people who worked out alone or in groups. As Raney spoke with Miner about building a fitness tool, it became clear that AI technology was evolving to the point that it could mimic a personal trainer. Miner has been working on AI for decades, and has the patent to one of the first “wake words” for a voice-based personal assistant 35 years ago. “If you’re not a movie star or someone with a lot of money, you can’t afford to get that kind of personalized training,” he says. “But I realized that with agentic AI, you could actually start building virtual people who could watch you and talk to you naturally.” [Photo: Ray] Building an AI Native Tool The fitness industry is working hard to incorporate technology into existing tools. Over the last decade, there’s been an explosion of tech-enabled machines, from Peloton and NordicTrack machines with screens that provide feedback about the workout, to weight-lifting machines like Mirror, Tempo, and Tonal that can help count your reps. Now, these companies are figuring out ways to incorporate AI into their systems, to better tailor workouts to the user. Minor and Raney began building Ray two and a half years ago. What sets it apart from many other tools on the market is that it is built on AI, rather than simply retrofitting existing technology with AI. Ray is designed to approximate a real person that can interact with the user in a natural way. “It adapts to you,” Minor says. “You don’t have to change a bunch of settings to make sure the workout is tailored to you. You can just say, “Ray, my shoulder’s hurting today.” The technology is equipped with several cutting-edge AI technologies. It has natural language processing, to create real conversations with the user. It is able to observe the user across 35 different points, and has a machine learning algorithm that identifies your body movements. It is also equipped with an AI planner that helps you dynamically plan workouts based on the user and their workout history. Ray has also incorporated a lot of highly specific data about personal training. The data is trained on the textbooks and manuals that personal trainers use to get qualified. Raney also became certified as a personal trainer to ensure the Ray experience is as realistic as possible. “Ray’s team has a huge amount of domain expertise,” he says. “We have a lot of knowledge about things like what constitutes a good workout and how to create a complete workout in a given amount of time.” Raney believes that the seamlessness of the interaction is important because one big obstacle to behavioral change is decision fatigue. “Part of what holds people back is the mental load,” he says. “You have to decide when you will do the workout, and then make a lot of decisions about what exactly you’ll do and for how long. With a personal trainer, all you need to do is to show up at the agreed upon time and do the program.” Minor believes that consumers will immediately see the difference between an AI-native fitness app, versus one that is back-solving into an existing system. He compares it to how companies started making mobile-first apps instead of just adapting their websites to mobile apps. “That’s when you got Instagram and Uber,” he says. “People rethought what an app could be if you didn’t have to rely on a legacy application. That’s what we’re trying to do with Ray.” How An AI Personal Trainer is Different Six months ago, Ray quietly launched on the app store, without any marketing. Thousands of users have already started using it. The founders say they wanted to see how users interacted with it and use this data to further train the AI. When I tried it, I was impressed by how well the program adapted to my needs. In 20 minutes, I was able to do a range of exercises in my office without any equipment. As I did push-ups and jumping jacks, my Ray trainer was encouraging, telling me that I was on the right track. It also respected the fact that I hate burpees. (You can pick whether the trainer is supportive or a little more assertive, since different users respond to different approaches.) [Photo: Ray] But as with other agentic AI platforms I’ve used, I found that the interaction wasn’t perfectly seamless. I didn’t exactly feel like I was interacting with a human trainer; the AI trainer’s eyes seemed blank and unfocused. When I spoke, Ray would pause before responding to me in a way that made the conversation a little stilted. Ray’s founders say that these aspects of the interactions will only get better as the more people use the platform and the AI itself improves. But for now, Ray didn’t feel human enough that I felt bad about letting it down if I didn’t show up for a workoutthe way I wold if I were working with a real person. [Photo: Ray] Miner acknowledges that an AI agent won’t provoke the same level of accountability that a human would, but he says that there are still benefits to creating an anthropomorphic app. “It’s more than about creating a sense of guilt about letting a person down,” he says. “A trainer guides you through what to do and they’re watching you as you workout, counting your reps and motivating you. Ray gives you all of that.” And there are some ways that a virtual personal trainer is more convenient than a human one. You can do workouts at odd hours that a human may find objectionable. You don’t have to compete with the trainer’s other clients and you can cancel at the last minute. And then there’s the price. Right now, Ray is free. But in the coming months, the founders will develop a pricing structure that is designed to be significantly less than the price of hiring a human personal trainer. Over time, the founders believe that Ray will begin to feel even more like the real thing. “Ray has improved so much over the past six months since it’s launched,” says Raney. “It’s going to feel more and more real as time goes on.”
Category:
E-Commerce
For those of us who earn a living publishing content on the open internet, Amazon’s lawsuit against AI startup Perplexity can seem darkly amusing. Perplexity is among the many AI companies that has spent years extracting value from the internet in exchange for little. Its crawlers have synthesized endless amounts of content from publishers, even working around publishers’ attempts to block this behavior, all so Perplexity can summarize content without having to send traffic to the websites themselves. Now Perplexity and its rivals are going a step further, with a new wave of AI browsers that can navigate pages automatically. Perplexity has Comet, OpenAI has ChatGPT Atlas, Opera has Neon, and others are on the way. The pitch is that AI “agents” will soon be able to trudge through the web on your behalf, booking your flights, buying your groceries, and shopping on sites like Amazon. Both Perplexity and OpenAI view these browsers as imperative in their goals to build AI “operating systems” that can manage your life. Amazon, which has a lot to lose if people stop accessing its website directly, is suing to stop that from happening. It’s been trying to block Perplexity, but so far to no avail. Therein lies the irony: These AI browsers promise a future where you’ll never have to visit a website again, yet that promise depends on having viable websites to crawl through in the first place. Amazon’s lawsuit is a sign that these two goals may be incompatible. Feeding the beast For companies like Perplexity and OpenAI, web browsers are suddenly important because they open the door to content and data that would otherwise be inaccessible. Consider Amazon. If you’re just using ChatGPT’s website, you might ask it to recommend a few Amazon items or summarize a product’s user reviews, but its answers wouldn’t include any personal data from Amazon’s site. By contrast, ChatGPT Atlas and Perplexity Comet can access Amazon exactly as it appears in your own browser window. That means they can crawl through your order history or weigh in on Amazon’s personalized product recommendations. Perplexity says these “agentic” browsers make for a better shopping experience, which is why Amazon should embrace thembut Perplexity also stands to benefit in other ways. By understanding things like your order history, personalized recommendations, and all the questions you asked Perplexity’s AI to arrive at a particular product, the company can build a much richer user profile for things like targeted advertising. “You’ve gone from behavior tracking to psychological modeling,” says Eamonn Maguire, who leads the machine learning team at Proton. “Where you have traditional browsers tracking what you do, AI browsers infer why you do it.” This isn’t speculation. Perplexity CEO Aravind Srinivas said on the TBPN podcast earlier this year that its browser will enable “hyper-personalized” ads by understanding more about users’ personal lives. “What are the things youre buying, which hotels are you going to, which restaurants are you going to, what are you spending time browsing, tells us so much more about you,” Srinivas said. Amazon, meanwhile, has much to lose from AI shopping agents, even if they ultimately help make a purchase. The company has its own $56 billion advertising business, fueled in part by the ads it stuffs into its shopping pages. CEO Andy Jassy has acknowledged that AI agents could disrupt that business. You may have little sympathy for Amazon in that scenario, but consider also the many smaller entities that stand to lose from an agentic web. Your favorite newsletter, for instanceone that paywalls content for its most loyal readersmay now have that content exposed within the tabs of an AI browser. Eamonn also gives the example of research papers that sit behind paywalls, or personal documents that wouldn’t exist on the web at all. The contents of emails, shopping lists, and productivity apps could all become fodder for AI to learn more about you. And while Perplexity and OpenAI have said they won’t train AI models on what people view in their web browsers, Eamonn says they could easily change that policy in the future. “Cynically speaking, it’s a smart way not only of building particularly good profiles of users but also getting more data,” Eamonn says. Why the web? Srinivas has acknowledged that AI companies need the openness of the web to provide them with all this context, because other platforms are too locked down. “The only reason we’re doing a browser is there’s no other way to build an agent with enough control over many applications simultaneously,” Srinivas said at the Upfront Summit in February. “Especially on iOS, you cannot even access another app. You don’t want to be bottlenecked by how Apple is building its ecosystem. You want to work around it, and the browser is a very good work-around in the short term for us.” OpenAI has similarly described the web browser as key to its broader ambitions. “Now that we have feedback and signals from hundreds of millions of people around the world, its clear ChatGPT needs to become so much more than the simple chatbot it started as,” Fidji Simo, OpenAI’s CEO of Applications, wrote in a blog post announcing the Atlas browser. “Over time, we see ChatGPT evolving to become the operating system for your life: a fully connected hub that helps you manage your day and achieve your long-term goals.” While AI companies have clear ideas of what they can do on te open web, it’s less certain whether the open web will cooperate. Lots of websites already attempt to block AI crawlersReddit has even cut off search engines that don’t provide compensationbut AI browsers represent yet another way around those restrictions. Amazon’s lawsuit against Perplexity could be a sign of further fights to come when attempts to block AI fail. AI companies would have you believe that these efforts are just delaying the inevitable. But that raises a bigger question of what the open web even looks like if it becomes entirely intermediated by AI. A common complaint against AI tools like ChatGPT is that they’ll erode the incentives to create new content, and that AI itself will ultimately suffer from having nothing new to train on. “Nothing really gets better unless you have content, but the content is getting worse because people are just using AI to generate this content, and then these models are getting worse because the content is getting worse,” Proton’s Maguire says. With the rise of agentic AI browsers, a similar argument could be applied to the web as a whole: What motivation will exist to design beautiful, unique websites for humans when there’s no one left to browse them?
Category:
E-Commerce
Tis the season for givingand that means tis the season for shopping. Maybe youll splurge on a Black Friday or Cyber Monday deal, thinking, Ill just return it if they dont like it. But before you click purchase, its worth knowing that many retailers have quietly tightened their return policies in recent years. As a marketing professor, I study how retailers manage the flood of returns that follow big shopping events like these, and what it reveals about the hidden costs of convenience. Returns might seem like a routine part of doing business, but theyre anything but trivial. According to the National Retail Federation, returns cost U.S. retailers almost $890 billion each year. Part of that staggering figure comes from returns fraud, which includes everything from consumers buying and wearing items once before returning thema practice known as wardrobingto more deceptive acts such as falsely claiming an item never arrived. Returns also drain resources because they require reverse logistics: shipping, inspecting, restocking, and often repackaging items. Many returned products cant be resold at full price or must be liquidated, leading to lost revenue. Processing returns also adds labor and operational expenses that erode profit margins. How e-commerce transformed returns While retailers have offered return options for decades, their use has expanded dramatically in recent years, reflecting how much shopping habits have changed. Before the rise of e-commerce, shopping was a sensory experience: Consumers would touch fabrics, try on clothing, and see colors in natural light before buying. If something didnt work out, customers brought it back to the store, where an associate could quickly inspect and restock it. Online shopping changed all that. While e-commerce offers convenience and variety, it removes key sensory cues. You cant feel the material, test the fit, or see the true color. The result is uncertainty, and with uncertainty comes higher rates of returns. One analysis by Capital One suggests that the rate for returns is almost three times higher for online purchases than for in-store purchases. When the COVID-19 pandemic hit, the move toward online shopping went into overdrive. Even hesitant online shoppers had to adapt. To encourage purchases, many retailers introduced or expanded generous return policies. The strategy worked to boost sales, but it also created a culture of returning. In 2020, returns accounted for 10.6% of total U.S. retail sales, nearly double the prior year, according to the National Retail Federation data. By 2021, that had climbed to 16.6%. Unable to try things on in stores, consumers began ordering multiple sizes or styles, keeping one and sending the rest back. The behavior was rational from a shoppers perspective but devastatingly expensive for retailers. The high cost of convenience Most supply chains are designed to move in one direction: from production to consumption. Returns reverse that flow. When merchandise moves backward, it adds layers of cost and complexity. In-store returns used to be simple: A customer would take an item back to the store, the retailer would inspect the product, and, if it was in good condition, it would go right back on the shelf. Online returns, however, are far more cumbersome. Products can spend weeks in transit and often cant be resoldby the time they arrive, they may be out of season, obsolete, or no longer in their original packaging. Logistics costs compound the problem. During the pandemic, consumers grew accustomed to free shipping. That means retailers now often pay twice: once to deliver the item and again to retrieve it. Now, in a post-pandemic world, retailers are trying to strike a balancemaintaining customer goodwill without sacrificing profitability. One solution is to raise prices, but especially today, with inflation in the headlines, shoppers are sensitive to price hikes. The other, more common approach is to tighten return policies. In practice, thats taken several forms. Some retailers have begun charging small flat fees for returns, even when a customer mails an item back at their own expense. For example, the direct-to-consumer retailer Curvy Sense offers customers unlimited returns and exchanges of an item for an initial $2.98 fee. Others have shortened their return windows. Over the summer, for example, beauty retailers Sephora and Ulta reduced their return window from 60 days to 30. Many brands now attach large, conspicuous do not remove tags to prevent consumers from wearing items and then sending them back. And increasingly, retailers are offering store credit rather than cash or credit card refunds, ensuring that returned sales at least stay within their company. Few retailers advertise these changes prominently. Instead, they appear quietly in the fine print of return policiespolicies that are now longer, more specific, and far less forgiving than they once were. As we head into the busiest shopping season of the year, its worth pausing before you click purchase. Ask yourself: Is this something I truly wantor am I planning to return it later? Whenever possible, shop in person and return in person. And if youre buying online, make sure you familiarize yourself with the return policy. Lauren Beitelspacher is a professor of marketing at Babson College. This article is republished from The Conversation under a Creative Commons license. Read the original article.
Category:
E-Commerce
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