 |
|
|
|||||
As young people report feeling lonelier and less connected than ever, the dating app Hinge is driving its users into real human experiences. CEO Justin McLeod shares how the platform is combating digital fatigue amongst users, as well as navigating the risks and opportunities of AI in online dating. McLeod also explores Hinges recent collaboration with renowned psychologist Esther Perel, and offers insider tips to find that special someone in the chaos of modern romance. This is an abridged transcript of an interview from Rapid Response, hosted by the former editor-in-chief of Fast Company Bob Safian. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with todays top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode. You partnered earlier this year with Esther Perel who’s a renowned psychotherapist to launch Your World prompts. Are there things from her perspective or your perspective at therapy do or don’t apply to what you’re trying to do with folks in their dating lives? I’ve had a long-standing relationship with Esther and I think she’s been skeptical about dating apps and we’ve had our conversations about how beneficial they are in the right way to implement them, and I think over time we’ve really earned her trust as a partner because we really do approach it in a very thoughtful way that’s very human-centric and very outcome-based. And so I think she trusts us. And especially because the prompts fit so well with her brand. She has her game. Where should we begin where she writes prompts for people to have deeper conversations at places like dinner parties or at the office. I feel like a very natural fit. I should say for the listeners, these prompts are not about building your profile, they’re about having conversation with someone to get to know them better. Precisely. Essentially that’s what we’re trying to do on Hinge. The purpose of a prompt on Hinge is to prompt you to talk about something so that you can start interaction and a conversation, form a connection, and then move offline. And she had some great ideas for some prompts that she wanted to put on Hinge. They are very much in the spirit of inviting someone into your world. So before we go out, you should listen to X, or when I want to feel more like myself, I go do Y. And that really helps people understand a bit like what am I listening to? Where am I spending my time? And giving people a bit of a fuller picture about who you are. We mentioned in passing earlier the rising conversation about more in-person experiences and young people choosing them or wanting that in some ways over digital interactions. Now you’re a digital service of course, but you’ve also talked about expanding into broader community building and in-person activation. I’m curious how you think about real-world iterations, how important that might be to Hinge’s future and where you’re going with it. Well, we do millions of in-person events every month and they’re called dates and that ultimately is the purpose of what we’re doing and that really is our wheelhouse. Listen, I’m all for people spending more time meeting together in person out in real life. We have a program called One More Hour because we support groups that gather together on a regular basis. We see the decline in time spent together in person, especially among young people. And the requisite increase in anxiety and depression among that group. So the more people are spending time together out in real life and the less time on their devices the better. And that very much mirrors the ethos of Hinge where we really are trying to get you to spend less time on our app, more time out on dates and relationships so that you’ll find your person and then ultimately go tell your friends to try Hinge. Does the brand of Hinge need to have a community in the real world . . . I don’t know, interaction for itself aside from my personal date that I might be going on? Yeah. I think we are so precious and thoughtful about our brand and we really try to do things that are really going to have an impact and aren’t just for show. And to be able to do something at scale with quality across tens of millions of users where people can get together in real life on a regular basis and still maintain the control of the experience and the brand is not territory that I exactly know how to approach. There are lots of people out there doing real life events and I applaud it, encourage it, we fund it, we’re all for it, but it’s just not our core competency. When you look at the competition at the other apps . . . Actually I don’t even know how much you do look at the competition. I know some of it is in-house within your parent company with Match Group, which also owns Match and Tinder and OkCupid and a bunch of others. How much do you pay attention to the competition? We really don’t look to the competition. That’s a mistake that I’ve made the first time around, is spending way too much time thinking about the competition and what they were doing. And when I did the reboot of Hinge, I steered the team to just pay attention to our customer and our users who are out there trying to find dates and there’s so much rich territory when we just try to deeply understand our users and the problems they’re facing. And that is why I think Hinge has become so innovative. And I think a lot of other dating apps are paying attention to us because you can see how they’re all slowly introducing features that make them more and more similar to Hinge and that’s why it’s all the more important that we don’t look at them, we actually look to our users and to emerging technology and that’s how we stay at the forefront of innovation. How much of building your business from this point is there’s a road map that you’re on that you’re implementing versus reacting and staying open and finding whatever’s next? Or do you have like no, no, no, we know where we’re going, we know exactly where we’re going next. I think we know the big picture of where we’re going. I think we know high-level that the future and what AI is going to enable is much more personalized matching. We can collect more data that’s more nuanced and use it in a better way to create a much more efficient matching process. And we can help our users put their best foot forward by giving them the right coaching and the right udges so that they fill out good profiles and use the app well. Those I think are the two main vectors of work that we’re focused on right now and we have to stay really curious because the market’s changing a lot, technology’s changing a lot, and so how exactly that is going to manifest, we don’t know yet and I think we can’t know because everything is changing so quickly. So that’s why it’s really important to have just a very nimble team, a very solid research organization and continue to just experiment.
Category:
E-Commerce
When youre brushing your teeth and you’ve squeezed out the last bit of toothpaste, you probably toss the empty tube in the trash. Few people realize that most toothpaste tubes are now recyclableat least in theory. A team at Colgate spent five years redesigning its packaging so that it could easily be recycled, and rolled it out across the brands products in 2022. They also open-sourced the project so other companies could deploy the same approach. Now at least 95% of all toothpaste tubes sold in the U.S. use the design. “We’re proud of the role weve played in transforming plastic tubes into a recyclable format,” says Ann Tracy, chief sustainability officer at Colgate-Palmolive. But recycling companies are still catching up to the news, and most cities still havent told residents that its okay to put the tubes in a recycling bin. Furthermore, a lawsuit currently underway argues that the tubes shouldnt be labeled as “recyclable” since so many cities don’t officially accept them yet. Its a classic challenge for any company working on sustainable packaging: The hardest part isnt necessarily the design but getting recyclers and consumers on board. The innovation Until recently, toothpaste packaging was made with multiple materials, including a layer of aluminum in between plastic. Much like in other types of products, such as sneakers, the mix of materials meant that it wasnt feasible to recycle. More than a decade ago, Colgate started seeking a solution. The old design, with the aluminum, preserved flavor and ingredients like fluoride, and the new tubes needed to perform the same way. They also needed to use a material that was widely accepted for recycling and that could work in the existing manufacturing equipment at packaging plants. Colgates engineering team turned to high-density polyethylene (HDPE), the same material used to make milk jugs. Because basic HDPE wasn’t squeezable enough and wasn’t compatible with the current manufacturing process, they spent years developing a new design with multiple layers of the material. Colgate then shared the design with competitors, realizing that for the tubes to be accepted for recycling, theyd need to become universal. Other major consumer packaged goods companies, like Procter & Gamble, made the switch. Then even completely different products that use the same type of tubeslike some kinds of shampoostarted using the design. There really has been a wholesale movement into recyclable [tubes] in the last couple of years, says Tonya Randell from the sustainability consultancy Stina, which has been working with Colgate on the project. How the tubes can be recycled The tubes are designed to be compatible with commonly used recycling infrastructure. After a garbage truck hauls off your neighborhoods recycling, it ends up at a materials recovery facility (aka MRF, pronounced murph in the industry). A typical urban MRF might deal with hundreds of tons of used packaging each day. Many rely on machines called optical sorters to identify materials: as trash moves down a conveyor belt, a near-infrared light shines on it and can tell if its made from paper or PET (polyethylene terephthalate) or HDPE or something else. Then a puff of air blows each item down a different conveyor belt, depending on the material. Multiple MRFs told me that optical sorters could easily identify the new HDPE tubes. In some cases, consumers are already putting them into recycling bins even when their cities don’t “allow” it. The tubes that make it through MRFs are getting sent to the next step in the recycling process. Some facilities also use AI to help with sorting. Glacier, one fast-growing startup, uses cameras and AI to identify different recyclables by sight. (The company also separately sells a robot that can help sort materials.) The tech can either be used on its own or in combination with optical sorting equipment to help recycle even more materials. In a pilot with Colgate, one MRF in California is using Glacier’s tech to track how many tubes are being recycled. “We want to have better and better data that’s helping us to understand what’s really happening in our system, and how well we’re doing at identifying and then ultimately recovering the materials that are going through our stream,” says Kish Rajan, CEO of Mt. Diablo Resource Recovery. The pilot is still underway, but should yield useful data about actual recycling rates of toothpaste tubes. “With AI like Glacier’s, you suddenly, for the first time, have a real-time item-level understanding of what packaging is actually going where,” says Glacier cofounder Rebecca Hu. “What volume is it coming to the MRF, where is it being sorted? Is it going to the bale? Is it going to landfill? And so that dataset creates a very powerful source of truth.” Some small MRFs that don’t have optical sorting equipment may have more difficulty recycling tubes, though the AI tool could be used as an alternative to sorting by hand. Because the equipment helps recyclers collect more material to sell for recycling, it can pay for itself relatively quickly. Hu says it’s affordable for MRFs of all sizes. It’s not clear how many of the hundreds of MRFs in the U.S. currently have optical sorters. After HDPE plastic is sorted out, it’s baled and shipped off to other recycling companies called reclaimers. They shred it, melt it, and turn it into pellets that can be made into material for something else. Last month, an association of HDPE reclaimers said, for the first time, that tubes were officially acceptable in the bales they buy. “That’s a really critical market validation piece,” says Randell of Stina. It’s also one example of how slowly the system moves: The change came after the tubes had already been on the market for years. The messaging gap Though many MRFs are already sorting and recycling tubes that come into their system, the cities they work with may not be telling residents. Some cities, like New York, still specifically say that tubes should go in the trash. Others post lists of recyclable items that show various types of plastic, but leave out tubes. One recycling company told me that it has little control over what cities say; though the MRF can tell the city what it’s capable of doing, the city ultimately decides whether to communicate that. The company, which works in multiple cities, said that governments tend to err on the side of simplicity and not making frequent changes so that people don’t get confused. But that means some recyclable items get left out. Other cities don’t have the resources to communicate more. “If you know anything about recycling budgets, a lot of midsze and smaller communities just don’t have a lot of money for outreach,” Randell says. “They maybe only print something every couple of years. They maybe only update the website as the webmaster for their county or city has time, not in real time. So even though their MRF may be able to take tubes, for example, and be willing to accept them, that information may not go out to the public for months or years because of the ability to actually leverage education.” Stina is currently focused on direct outreach to both recyclers and communities. “All of those tubes can now be accepted in bales,” Randell says. “So now the next step is, how do you convey that to the public?” What’s recyclable? Right now, consumers who want to recycle toothpaste tubes are in a tricky spot: If your community doesn’t explicitly say the packaging is recyclable, you may have to wait. And critics argue that packaging can’t be called “recyclable” if consumers don’t have easy access to recycling. The U.S. Federal Trade Commission’s Green Guides say that recycling claims can’t be based on theoretical recyclability, but whether the majority of people can recycle a product in the place where it’s being sold. (Colgate’s tubes include recycling instructions, but also say, “Your community may not yet accept tubes for recycling,” and tell people to check locally.) The definition of “recyclable” is obviously complicated by the fact that recyclers may already be recycling the packaging, but community instructions are lagging behind. Other redesigned packaging faces similar challenges. Kraft redesigned ketchup bottles to make the caps recyclable, but caps are still often rejected in recycling programs. Unilever switched to a single material for some deodorant sticks to make the packaging recyclable, but they also may not make it through the system. Seventh Generation switched to a paperboard bottle for laundry detergent, but the complicated designwith a pouch insidemeans that it often isn’t recycled correctly. Then there’s the bigger challenge of low recycling rates: Even when something can easily be recycled anywhere, like a plastic water bottle, it often isn’t. (PET water bottles had a dismal 33% recycling rate in the U.S. in the most recent data.) Some consumers are skeptical about recyclingand make the problem worse by not participating. There’s an unhelpful narrative that recycling doesn’t work at all, even when MRFs are investing in sophisticated equipment and getting valuable materials out. For something like a toothpaste tube, even if a city tells residents it’s recyclable, many may still assume that it isn’t. When communication is a problem, a simple recycling message on the package seems like an obvious part of the solution. But when a company is sued over that labeling, and accused of greenwashing, it’s not clear how that’s really helping advance sustainability at all.
Category:
E-Commerce
DataPelago has created a new engine called Nucleus that dramatically speeds up data processing for AI and analytics. It outperforms Nvidias cuDF library by large margins while working across different types of hardware. Todays GPUs are powerful, but older software often wastes their potential, making faster tools like Nucleus especially valuable. This shift could have dramatic implications for Nvidia. For years, enterprises have leaned on GPUs (Graphics Processing Units) to handle ever-growing mountains of data, leveraging their ability to run thousands of calculations in parallel for AI and analytics workloads. Every generative AI model, recommendation engine, and analytics dashboard depends on data libraries to prepare, join, and transform massive datasets. Yet the industry faces a quiet challenge: Despite advances in hardware, performance often stalls at scaling limits because the software stack struggles to fully exploit the hardwares capabilities. Many legacy data libraries were optimized for CPUs, not GPUs. As a result, memory bandwidth and compute throughput often go underutilized, and every time data moves between CPU and GPU, much of the performance advantage evaporates. To address this, Nvidia launched cuDF in 2018 as part of its open-source RAPIDS suitea GPU-accelerated DataFrame library that quickly became the gold standard for data operations. It delivered speedups over CPU-based libraries and better utilization of GPU hardware. But cuDF also has limits. It requires an Nvidia GPU with ample memory and CUDA support, ruling out environments without compatible hardware. In many ways, cuDF became the industrys ceiling: powerful enough to accelerate AI and analytics pipelines, yet constrained by the quirks of GPU architecture itself. Now, California-based data startup DataPelago says it has surpassed those limits with its universal data processing engine, Nucleus. Built atop Nvidia hardware, Nucleus reportedly delivers performance gains so steep they could reset the economics of GPU acceleration. In a benchmark test, Nucleus outpaced cuDF by 38.6 times on hash joins, eight times on sorts, and 10 times on filters and projections. To fully realize the benefits of GPUs, data processing engines need to fully leverage the hardwares strengths while compensating for its limitations, says DataPelago CEO Rajan Goyalsomething he argues demands fresh algorithms built for data workloads. The implications go far beyond engineering bragging rights. Cloud GPUs are expensive, and enterprises face pressure to maximize every compute cycle. Faster data processing means lower cloud bills and quicker time-to-insight. Goyal says Nucleus is designed to run on any hardware and handle any type of data, while integrating with existing frameworks without requiring changes to customer applications. We slot into the existing environments that developers are already working in, he adds. Empowering Enterprise AI with a Hardware-Neutral Approach DataPelagos benchmark test ran on standard public-cloud servers with both entry-level Tesla T4 and high-end H100 GPUs. The test mimicked real-world tasks: moving data from CPU to GPU, processing it, and returning results to the host. Using the same dataset and harness, Nucleus was compared head-to-head with cuDF on core AI and analytics operations. We wanted to improve the performance ceiling for GPUs, and the only way to do that credibly was to compare ourselves directly to cuDF, says Goyal. He notes that accelerating data prep by an order of magnitude gives businesses the capacity to process exponentially more information for AI training and retrieval tasks, keeping systems up-to-date. The engine achieved these results by redesigning its execution layer to handle complex workloads, including kernel fusion, native multi-column support, and optimized handling of variable-length data such as strings. Interestingly, while Nucleus runs on Nvidias CUDA framework and GPUs, it delivers higher performanceessentially out-engineering Nvidia on its own tech stack. DataPelago president JG Chirapurath says Nucleus delivers far greater performance from existing hardware investments and stresses that enterprises prefer solutions that build on what they already have rather than forcing a rip-and-replace. Goyal argues that cuDF is tightly coupled to Nvidias GPU ecosystem, creating vendor lock-in and limiting hardware flexibility. This dependence restricts open innovation and ties enterprises to Nvidias roadmap. Nucleus is designed to work across any hardware (not only GPUs), while also handling any type of data and supporting any query engine. It is designed to lift the performance ceiling of any hardware, claims Goyal. The engine also includes built-in intelligence that automatically maps data operations to the most suitable hardware and dynamically reconfigures tasks to maximize performance. Software Over Silicon: The Emerging Battle for Enterprise AI Efficiency If DataPelagos approach takes hold, enterprises may begin prioritizing universality and efficiency over single-vendor ecosystems when building AI infrastructure. Still, analysts caution that benchmark results often look stronger in controlled tests than in real-world production, and risks remain if the hardware landscape evolves quickly. The offering will appeal to those looking to avoid vendor lock-in, says Alvin Nguyen, senior analyst at Forrester. But with tools like AMDs CUDA translation for its data center GPUs, the real advantage is if youre also targeting CPUs and Field Programmable Gate Arrays (FPGAs). There is a large population of developers experienced with NVIDIAs ecosystem, so moving away from NVIDIA now means a bigger short-term investment in other options. Nguyen also notes that progress on transformer-based workloads, such as training large foundational models, is slowing compared with prior years. As inferencing begins to outpace training, raw GPU horsepower is no longer the main driver. A more balanced view, including the software layer, is a smart way to look at things. Still, investors are buying in. DataPelago has raised $47 million in seed and Series A funding from Eclipse, Qualcomm Ventures, and Taiwania Capital, and recently hired industry veteran JG Chirapurath as president. CEO Goyal himself worked at Cisco and Oracle before founding the company. For years, the AI industry has fixated on chip shortages and the race for ever-more powerful GPUs. Nucleus points instead to a different kind of competition. If the biggest performance gains now come from software rather than hardware, the battleground could shift from chip foundries to algorithmic innovation. The future of AI infrastructure may depend less on building bigger chips and more on rethinking how we harness the ones we already have. Hardware neutrality is strategic differentiation, not just technical capability. Enterprises want infrastructure investments that remain valuable as technology evolves, says Chirapurath. My long-term vision is positioning DataPelago as the universal data processing foundation that accelerates the next decade of AI and analytics innovation. We’re making previously imposible applications economically feasible.
Category:
E-Commerce
All news |
||||||||||||||||||
|
||||||||||||||||||