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Japanese auto manufacturer Mazda has released a simplified new logo, and it has bigger implications than your typical brand refresh. It’s indicative of a broader brandingor should we say blandingtrend that’s taking over the car industry. Mazda Motor Corp. rolled out a new, flatter version of its logo at the Japan Mobility Show 2025 in October that did away with the dimensional, beveled silver chrome effect the logomark used to have in favor of a solid black line. The new M mark is more angular, too, evoking a pair of wings that was first introduced in 1997. The company says it designed the flat new logo for improved visibility, especially in digital environments. That also makes it late to the party. [Images: Mazda] Yesterdays bland is todays car brand A dozen car brands have flattened their logos in roughly the past half dozen years, and Mazda is now the latest. Toyota did so in 2019; Rolls Royce in 2020; BMW, Cadillac, Kia, Nissan, and Volvo in 2021; Audi and Bugatti in 2022; and Genesis and Jaguar Land Rover in 2023. [Images: BMW] Jaguar famously introduced its new, lighter logo with a mix of upper- and lowercase letters in 2024; and this March, Lamborghini toned down the sheen on its bull-and-shield logo. Bentley, which updated its winged B logo in July, kept the chrome look but simplified the mark. It’s not flat, but it’s more minimalist. [Images: Jaguar] Overall, a “blanding” and flattening of car branding has swept through the industry years after the trend hit graphic design more broadly. Out are chrome, 3D, skeuomorphic logos designed to look like car badges. In are logos meant to be rendered at small sizes on screens. [Images: Volkswagen] Sans serif? Its electric Now de-chromed, these new logos are thinner and lighter, and they come as automakers adapt to a more electric future. At the same show where it unveiled its new, flat logo, Mazda also showed off a pair of futuristic-looking hybrid concept cars. Its first EV is expected in 2027. Graphically, the updated logos of legacy automakers are going up against those of EV newcomers such as Tesla and Rivian, which use sleek, futuristic-style fonts inspired by the typography of 20th-century science fiction, like Blade Runner and Back to the Future II. It’s possible that legacy car brand logos are getting updated to visually signal contemporary relevance in those markets as well. Ironically, the trend toward flat logos better designed for digital expression comes even as carmakers are getting rid of touchscreens in their vehicles in favor of old-school, analog knobs and dials. As automakers reconsider the screens in car interiors, they may one day reconsider their flat, digital-first logos too. For now, the flat-logo look reigns supreme.
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In recent years, leading artificial intelligence labs and startups have released AI software designed for tasks of ever-growing complexity, including solving PhD-level math problems, reasoning through complex questions step-by-step, and using tools like web browsers to carry out intricate tasks. The role of AI engineers in making that happen is well-documentedand often well-compensated. But less publicized is the role of a growing army of freelance experts, from physicists and mathematicians to photographers and art critics, enlisted by companies specialized in AI training, itself a multibillion-dollar industry. Those companies say human wisdom is essential to create sample problems, solutions, and grading rubrics that help AI improve its performance in a wide range of fields. As long as AI matters, humans will matter, says Aakash Sabharwal, vice president of engineering at AI training company Scale AI. Scale AI recently made the news when Meta announced plans to invest $14.3 billion in the companyand hired away its then-CEO Alexandr Wang to lead a new Superintelligence lab focused on AI research. But the company remains a top player in the field, recruiting expert AI trainers in a wide variety of subjects and building digital environments Sabharwal compares to flight simulators for AI, where humans can help machines learn everything from sending business emails to writing code. “Way more PhDs” The modern AI training industry grew out of earlier work to create labeled training data teaching computers to identify objects in photos or spot social media posts in need of moderation. The early days of how people thought of this industry was what you’d call commodity labeling, like cat/dog, cat/dog, cat/dog, says Matt Fitzpatrick, CEO of AI training company Invisible Technologies. More recently, as generative AI models became available, human workers helped steer the software to correctly answer questions about topics like high-school level mathematics and communicate with virtual fluency in a variety of languages. Companies like Scale and Invisible have also built relationships with big businesses to help them fine-tune AI technology that can deliver insights based on their own needs and internal data. And now, as leaders of AI companies regularly boast of their chatbots prowess at tackling advanced math and science problems, human experts are working behind the scenes to test their limits and push their knowledge levels forward. You’ve seen a real change in the seniority and expertise set of the expert pools, says Fitzpatrick. Way more PhDs, way more masters [degrees]. Hyper-specificity Exactly what training firms provide to AI companies varies from task to task. It can include a mix of AI prompts and ideal answers, rubrics for evaluating AI responses, and corrections to the AIs current best attempts. Trust is also an implicit part of the product: As Holger Mueller, a principal analyst and vice president at Constellation Research, points out, it has taken some time for big businesses to trust AI companies with their own dataincluding for fine-tuning purposes. And many AI training companies decline to publicly share a list of clients, citing confidentiality, with even training workers often not told exactly which companys AI theyre working to improve. Another big part of what training firms deliver is access to vetted pools of experts, and the promise that they can produce training data in even obscure areas on short notice, which is critical given the AI industrys pace of growth. Its not unusual for a client to expect Invisible to line up 50 experts in, say, computational biology overnight, with the expectation theyll deliver usable training data within a week, Fitzpatrick says. Despite reports that some AI companies have begun directly hiring experts themselves to train their systemsOpenAI has reportedly hired more than 100 former bankers from top Wall Street institutions to help teach its systems to do at least entry-level financial analysisFitzpatrick and other training company leaders say the specialized nature of their work, involving managing both technically sophisticated training platforms and large numbers of human workers, generally makes it hard for AI labs to do themselves. The vast majority of our work is hyper-specific experts for short sprints at a time, he says. It’s a complicated thing to do in house. That means that Invisible, which announced a $100-million funding round in September, along with its competitors, have all also devoted time to building robust recruitment and evaluation pipelines for human expertsoften complete with AI tools of their own to speedily screen and onboard those experts and assess their progress. And clients are likely doing their own assessments of the data they get back. Its not unusual for AI companies to solicit training data from multiple companies and compare the results, Fitzpatrick says. Intellectual curiosity The market for freelance experts with the time and knowledge necessary to train AI in obscure fields is, itself, naturally competitive, with training company executives boasting of their expert contractors credentials the way college presidents might brag about a new class of elite undergrads. One AI training company, Mercor, currently has listings posted seeking recreation workers at $60 to $80 per hour, a bilingual Spanish marketing expert at $20 to $60 per hour, legal experts at $90 to $120 per hour, and Ireland-based general practitioners in medicine at $160 to $185 per hour, among numerous other listings. And in many areas of knowledge, the bar steadily rises to get assigned to projects, according to Mercor product manager Osvald Nitski. Software engineers are now required to have either experience in some niche programming language or incredibly strong scores on competitive coding challenges, Nitski says. We’re now sometimes sourcing named individuals, because the bar that needs to be met is so high that there are limited number of people in the world who actually meet it. Mercor, which on Octoer 27 announced a $350 million Series C round at a $10-billion valuation, says it pays more than $1.5 million per day to its experts, with average pay above $85 per hour. More than 30,000 experts are signed to Mercors platform, according to the company. And while the pay no doubt motivates experts, many of whom are working full-time in their fields, to enter the AI training arena, some are also motivated by intellectual curiosity and the desire to help hone software they hope can one day assist in their work or tackle outstanding problems. “A harder problem” Alice Chiao, an emergency medicine physician who serves as an expert for Mercor, says she hopes that AI can automate some of the drudgery, like charting and scribing, of medicine and thus help doctors better connect with their patients. She says her AI training work includes asking the systems to answer medical questions that may have stumped her in her practicethe kind of puzzling scenarios that pop up when real-world patients differ from textbook examples. We input these things and try to see where a model might fail, she says. And then we create an ideal responseyou know, based on this finding, I would have ranked this differential diagnosis higher. Chiao emphasizes that she doesnt anticipate the AI she trains replacing her or her fellow physicians. Rather, she sees the technologys assistance helping to restore a level of human interaction thats often disappeared from medical practice. I do not think that training the AI is training a replacement, she says. I think that it has the significant potential to enhance the patient-physician relationship, which has eroded to a point where most physicians are not happy with the quality of patient-physician conversation and dialog that they get anymore. Another AI training company, Micro1, focuses on talent in finance, medicine, law, and engineering fields, says founder and CEO Ali Ansari. Average rates paid by the company hover around $100 an hour, though it varies between subject areas, with about 70% of experts making between $70 and $210 per hour, he says. Micro1, which in September announced a $35 million Series A round at a $500-million valuation, also operates an AI recruiter that can vet potential candidates and even help share job listings on platforms like LinkedIn. Finding talent is a critical part of its operations. Part of the companys goal, Ansari says, is to make sure that in-demand experts will not only perform well at a certain training task but have a good time doing it. We want to be able to predict how much an expert will enjoy a certain job as well, which is, in fact, actually a harder problem, he says. A social calling One expert that works with Micro1 is Mark Esposito, a professor of economics and public policy at Harvard University. He now serves as Micro1s chief economist but began his association with the company by training AI to answer policy questions. Thats something he sees as important in ensuring AI doesnt give misguided advice to users looking to make important decisions. You don’t want any policymaker to be dealing with information that is grossly incorrect, he says. So that’s why I think there’s a bit of a social calling for this, in making sure that youre really training models ethically, because they might really help people make a decision in the real world. Edwin Chen, CEO of AI training company Surge AI, speaks to a similar sort of calling, saying hes dreamed of helping craft artificial general intelligence (AGI)essentially, truly thinking machinessince he was a child. Instead of playing the startup game, we’re a lot closer to a research lab, he says. And the only thing that matters to us is whether we succeed in building AGI. Still, the company recently boasted its making more than $1 billion in annual revenue, and Chen says pay rates for some of the experts it works with can reach as high as $500 per hour, with the company website citing contributions by Supreme Court litigators, Oxford linguists, Navy SEALs, and Olympic athletes. The proportion of specialized experts among the AI training workforce has grown over time, but people with more general knowledge still contribute as well, Chen says. Thats unlikely to change, he adds, since AI tools do need steady training on even basic problems. And even if AI continues to do better with hard problems and take on more roles, itll still need human guidance, as standards for its performance will continue to grow. This means AI is unlikely to make its human teachers obsolete any time soon. As they get used more and more, the capabilities increase, the applications increase, and so it’s no longer okay for models to be at 80% accuracyyou need to be at 99.99999% or whatever it is, Chen says. And at the same time, as the models get smarter and smarter, you always need humans to steer and align them. Historically, some AI training companies have faced complaints from less-expert training contractors of unpredictable hours, difficulties getting paid, and other issues familiar to gig economy workers. Others, including Scale AI, have since said theyve taken steps to address complaints or otherwise emphasized their commitment to fair pay. And in general, work in the AI training field seems likely to grow as long as businesses continue to invest in deploying AI, as training companies expand into enterprise work and even work with robotics companies to help AI understand how to move about in the physical world.
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The 9-to-5 is fading, replaced by a fragmented cycle of early logins, late-night pings, and weekend catch-up. Microsofts latest Work Trend Index shows the infinite workday is no longer an edge case. Its the norm for many knowledge workers. Unfortunately, it seems the pandemic-era triple peak work patternmorning, afternoon, and an evening spikehas stuck. After-hours activity is rising. Meetings after 8 p.m. are up 16% year over year, and by 10 p.m. nearly one-third of active workers are back in their inboxes. Weekends are not off-limits: Among those working weekends, about 20% say they check email before noon on Saturday and Sunday. During the week, prime focus windows are being eaten alive. Half of meetings land between 9 and 11 a.m. and 1 and 3 p.m.the very hours when many people are naturally sharpest. What feels like productivity is quietly fueling burnout, chaos, and replaceability The risk is fatigue and focus. When communication never sleeps, neither does context-switching, a leading cause of mental exhaustion. Microsofts telemetry finds employees are interrupted, on average, every two minutes during core work hoursadding hundreds of pings a day among heavy-communication users. Its no surprise that nearly half of employees (48%) and more than half of leaders (52%) say work feels chaotic and fragmented. Samantha Madhosingh, a leadership consultant and executive coach with a background as a psychologist, says the issue is exacerbated by flexi-working while working remotely and trying to do it all. She says remote working makes it difficult for folks to have the strong structure and boundaries around their workday. And I see people really struggling. Theyre struggling to remain organized, to stay focused, and to not burn out. At Lifehack Method, weve seen this up close as we coach busy professionals to reclaim their time and do meaningful, fulfilling work. When new clients arrive, most are drowning in what feels like normal work like an overflowing inbox, constant notifications, and a booked-up calendar. Well ask them, Whens the last time you had two uninterrupted hours to do your actual job? The answer is usually nervous laughter. But when they start putting up strategic boundaries, the turnaround is dramatic. Heres how to set new boundaries around the infinite workday so that you can not only survive but thrive. What Frontier Firms do differently Some 53% of leaders say productivity must climb, yet 80% of the global workforce reports lacking the time or energy to do their jobs. That mismatchrising demand versus human bandwidthcreates a capacity gap that organizations are racing to close. Microsofts Frontier Firms, which are early adopters deploying AI across the org, report better sentiment and headroom: 71% of workers at these firms say their company is thriving (versus 37% globally), and 55% say they can take on more work (versus 20% globally). Many leaders plan to upskill existing employees (47%) and use AI as digital labor (45%). Microsoft CEO Satya Nadella repeatedly posted on LinkedIn in August 2025 highlighting new AI tools that free people from drudgery and give them more time for highimpact work. He wrote that GPT5 integrated into Microsoft 365 Copilot has become part of his everyday workflow, adding a layer of intelligence across apps, and praised the new =COPILOT() function in Excel that lets users analyze, generate content, and brainstorm directly in the grid. But AI is only part of the fix. It can automate tasks, but it cant make your choices for you. Your scarcest asset isnt talentits time. Go a month without clear goals or let each week fray into constant notifications, and you quietly become easier to replace. Thats because reactive work, jumping at every @mention or ping, keeps you busy without moving the needle. Push back on norms for big results Teams that tame the infinite workday reject the normal flow of work and actively redesign their calendars. For example, Shopify periodically purges calendars of recurring meetings with more than two people. Meta and Clorox have meeting-free days. Dropbox has core collaboration hours, a four-hour block of synchronous time across its workforce that relieves the pressure of all-day meetings and lets employees decline meetings outside this window. GitLab runs on asynchronous workflows (a favorite trick here at Lifehack Method) to reduce urgency and alleviate stress. If youre not in a position to flip the switch company-wide, here are some individual power moves: Swap meetings for screencasts. Most 30-minute info-transfer meetings could have been an email, or at least a shorter meeting. Record a Loom or Clipchamp, send it off, and let people listen at 1.5x speed. Boomyou just gifted yourself and your team back half an hour. Trade 1:1s for weekly office hours. You become more accessible, employees get a pressure valve for urgent problems, and you solve a pile of small issues in two to five minutes instead of bloating everyones calendar with half-hour blocks. The best leaders use office hours as a speed bump. If someone really needs a private 1:1, theyll earn that time after showing up in office hours first. Set a win-win communication policy. Uncertainty kills productivity. People dont need instant replies, they need predictable ones. Instead of winging it (aka defaulting to chaos), publish a simple rule: I check email at 9 a.m., 12 p.m., and 3 p.m., or I dont take meetings on Mondays because Im with clients. The magic is in the head-nodding clarity. People stop expecting and start respecting. Close the floodgates. There should be moents when people can reach you and moments when they cant. Otherwise, youre drowning 24/7. The best way to enforce those on/off cycles? Plan your week in advance. If you dont, the week will make a (bad) plan for you. Which leads to the next suggestion: Make weekly planning a ritual, not a wish. Pros dont win with fancy hacks, they win by doing the boring basics consistently. Thousands of our clients at Lifehack Method use weekly planning as their tip of the spear. If you want to win the week, youve got to plan the week. Prioritize your physical and mental health, before its too late. Madhosingh warns that work cannot take over your entire day and life. For a lot of people, thats what ends up happening. They dont know when to stop. Ultimately, your brain or your body will shut you down. . . . People end up really physically ill and sick because theyre not taking care of themselves. The infinite workday isnt your destiny If you dont set boundaries, your tools will set them for you, and theyll always choose chaos. Thats why the most competitive professionals and companies in 2026 wont be the ones who can stay logged in the longest. Theyll be the ones who deliberately carve out time for deep work, compress their collaboration windows, and enlist AI to strip away drudgery. The infinite workday is real, but its not inevitable. You can either accept it as the new default, or treat it as the wake-up call it is. Leaders who redesign their calendars, enforce boundaries, and invest in human focus will not only outlast the chaos, theyll outperform it.
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E-Commerce
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