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Profits also fell last year at world’s largest asset managerView the full article

Earlier this week, Time published an explosive story about an American company that reportedly revived a long-extinct species, the dire wolf. To some, it’s a scientific miracle: Some 10,000 years after the species went extinct, the planet is once again home to three living dire wolf pups, brought about by the ingenuity of scientists at Colossal Biosciences. But let’s not mistake spectacle for substance. Yes, it’s cool that biotechnology can now create animals that resemble extinct species. Colossal is already eyeing its next acts—the woolly mammoth and the dodo. But beyond the buzz and the billion-dollar ambition, this project doesn’t offer real solutions to our planet’s biodiversity crisis. At best, it’s a novelty. At worst, it’s a distraction—and a dangerous one. There are over 47,000 species currently considered to be threatened with extinction, including both plants and animals. Many are under threat because of human activity, whether we’ve eliminated their habitats, over-hunted them, or polluted the land, air, and water they rely on to the point that they can no longer sustain life. Colossal’s gene editing experiments are being described as a kind of “conservation,” but they won’t help the many species that are currently fighting for survival. The company has argued that their discoveries can be used to save those species that are still hanging on—for example, by “engineer[ing] more robust elephants that can better survive the climatic ravages of a warming world,” as the Time article puts it. It wouldn’t be the first time humans tested an unprecedented idea on wild populations in an attempt to influence biodiversity. In 1935, Australia introduced the cane toad as a means of controlling the sugar cane beetle population. But it backfired—not only did it fail to fix the beetle problem, but much worse, cane toads took over the region, causing ecological havoc everywhere they went. The Asian carp is another example, introduced to the U.S. by farmers in the 1970s who wanted to use them to clean their commercial fishing ponds. Today, they’re one of the most notorious invasive species plaguing the eastern United States. We know by now that meddling with natural ecosystems can cause unpredictable, damaging chains of events. Even if Colossal’s efforts go as planned, let’s be clear-eyed about what this means: We’re not fixing the damage caused by humans. We’re just modifying animals to make them less susceptible to it. Drivers of biodiversity loss like climate change and industrial animal agriculture are forces that are not going to stop on their own, which makes gene-editing endangered species little more than a bandaid. We may prolong the existence of a handful of species, but meanwhile, the core issue would only continue to grow. And what’s worse, the idea that we can bring back species from the dead may lead us to treat the issue of biodiversity loss with less urgency. If we can just fix it later, why worry too much about it now? It’s not as if this project offers any benefit for the dire wolves themselves, or any individual nonhuman animals, for that matter. When animals are “summoned back from the dead” in this manner, they can’t be reintroduced into the natural world. It’s not the same place, with the same ecology and biodiversity makeup, that the wolves lived in 10,000 years ago. Throughout modern history, there are only a few cases where captive breeding was used to successfully fortify a declining natural population, as animals kept or bred in captivity often cannot survive in the wild, let alone thrive. That’s why the three wolf pups bred by Colossal are going to spend their entire lives in a monitored fenced-in enclosure. They won’t be able to form the complex social structures wolves are known to, with distinct familial roles. They were created to be analytical subjects for human study, and will presumably never experience life in the wild. Colossal’s chief science officer, Beth Shapiro, called their pups “the luckiest animals ever,” thanks to their containment and human supervision. It’s true the wild is no picnic, but I’m skeptical that any undomesticated animal in captivity would agree with Shapiro, no matter how cushy the cage—the pups were much better off not being born in the first place. And aside from all of this, the three pups aren’t technically real dire wolves. In breeding the pups, Colossal’s scientists didn’t actually reanimate the genetic material of the dire wolves that lived thousands of years ago. They studied that genetic material, and artificially rewrote the code of a tiny portion of the common gray wolf in a slippery attempt to make it match. As one commentator put it, “You could probably create an unusually hairy elephant, but that wouldn’t be a wooly mammoth.” All in all, the genetically modified pups are bootleg-like recreations, not authentic recoveries, part of a mad science experiment to generate PR. To paraphrase a certain movie about scientists who recreated long-extinct animals for the sake of human curiosity, it’s neat that our scientists can do something like this—but it’s high time to consider whether they should. Building the off-brand dire wolves took a chunk of the whopping $200 million the company raised and the work of some 130 bright minds. It pains me to imagine other, more immediately useful ways those resources could have been applied. Few efforts are as noble as conservation, and I acknowledge that stemming the biodiversity loss is a complicated issue that’s going to call for many different solutions. But with so much at stake and a clock that won’t stop ticking, we ought to be sensible about the approaches we try. Before indulging in science fiction-inspired reveries, let’s do what we can to save those species that still have a chance while keeping the welfare of the individual animals in mind along the way. To not do so would be a colossal mistake. View the full article

The humanoid robotics revolution is just around the corner. Test models are already working in factories alongside human beings across the world, while AI companies develop new foundation models designed to help robots navigate their environments as easily as humans do. But computer “brains” are useless without the skeletons that give humanoid robots their form—and the many components that make up those skeletons need to come from somewhere. Alongside bearings, which reduce friction, motors, and gears, the average humanoid robot relies on dozens of screws—key components that convert the rotational motion produced by a motor into linear motion. Traditionally, ball screws—which feed a series of balls through a screw shaft and nut—have been the primary type used in robotics. But a new component is set to supercharge humanoid motion and could become the next must-have physical part. “Over time, planetary roller screws should represent the majority of screws used in humanoids,” researchers at Morgan Stanley wrote in a February 2025 note. Planetary roller screws are a next-generation alternative to ball screws, able to withstand higher loads and last longer—both vital qualities for the wear and tear humanoid robots are expected to endure over their operational lifetimes. Tesla’s Optimus uses four planetary roller screws in its calves, and they’re also used by Figure AI, Agility, 1X, and the majority of China’s humanoid robot manufacturers. One China-based expert, Jack Li, research and development and product manager at Nanjing Process Equipment, a Chinese screw manufacturer, told investment bank Jefferies that the total market for the screw is already $1.8 billion, and is likely to grow at a compound rate of more than 30% over the next five years. Actuators—described as “the crown jewel of the core moving parts of robots”—convert rotary motion into linear motion, a crucial function for robotics and especially for humanoid robots, says Jonathan Aitken, an expert in robotics at the University of Sheffield. “They’re highly accurate as we get good precision in conversion from angle to linear distance travelled,” he explains. “Traditionally linear actuation isn’t good for load, rotational is. This gives the best of both.” So far, the use of planetary roller screws in humanoids has been limited by their cost—a result of the specialist skills needed to manufacture them reliably, which only a handful of companies worldwide currently possess. “The bulk of the cost of a humanoid will be in the actuators,” says Scott Walter, widely considered one of the world’s leading experts on robot design. Walter is chief technical advisor for Visual Components, a manufacturing production design company. “Each bot needs 40 or more,” he says. “So that is a huge supply need.” Researchers at J.P. Morgan estimate that reducers and roller screws account for around 33% of the average humanoid robot’s “bill of materials,” or cost of parts. The average planetary roller screw sells for between $1,350 and $2,700, according to the investment bank. While Walter admits, “The logical choice would be just to use rotary actuators at all the joints, since the actuators axle can also form the joint,” cost concerns are currently holding back their widespread deployment. That looks set to change as engineering and manufacturing expertise grows alongside demand, driving down production costs. China appears to be in the driving seat when it comes to controlling the supply of planetary roller screws in the years ahead. “Because of drone manufacturing, China already had a large installed base of small actuator manufacturers,” says Walter. “While not having exactly the same requirements, they were close enough to allow China to produce enough rotary actuators at scale for initial bot prototypes,” he says. “They are in the drivers’ seat if rotary rules the day.” Chinese companies are betting on the potential of planetary roller screws to meet future humanoid demand: In October 2024, Shanghai Beite Technology—traditionally a manufacturer of auto parts—announced a 1.85 billion yuan ($260 million) investment to build a facility dedicated to the production of planetary roller screws. The West will likely need to compete by developing its own planetary roller screw supply chain—and fast—given the potential impact of increasing U.S. tariffs and the ongoing trade war with China, where most of these components are made. “The dirty little secret is even if actuators are assembled stateside, the important components are still coming from China because few companies have the expertise and equipment to produce vital components outside of China,” says Walter. “Planetary roller screws are precision equipment. For humanoids, they need to be small and efficient,” he adds. Yet there’s a complication. “The supply chain does not yet exist because the designs are not yet locked,” Walter explains. “Nor is there a consensus on the size of this supply chain.” But quick action may be required if the humanoid robotics revolution turns out to be even a fraction of the size some experts predict. View the full article

When an AI-assisted résumé lands on a hiring manager’s desk, most people have the knee-jerk reaction to chuck it straight onto the reject pile. While more and more companies are using AI in their day-to-day operations, when it comes to résumés and cover letters, the use of artificial intelligence remains taboo. The importance of AI-savvy talent This instinctive aversion to AI is costing firms invaluable AI-savvy talent. And with the demand and competition for AI skills so fierce, many employers are letting prospective talent slip through their fingers, straight into the laps of their competitors. It’s time to overhaul recruitment processes out of the dark ages. We need to reshape and sharpen the AI-powered workplace that’s already taking shape. To do this, companies need to root out anti-AI bias, implement AI-based tasks in their skills assessments, and then actually prioritize hiring for AI talent. The hypocrisy of rejecting AI-generated résumés A recent study by Capterra found that more than half of job seekers have used AI to aid their job search as they look to dull the sting of a brutal and unforgiving job market. Now, it’s not just the applicants who are using AI. Seven in ten businesses admit they’re happy to use AI to reject applicants without any review or oversight from a human. Yet despite their willingness to let AI make the hard decisions for them, a staggering majority of hiring managers say they view AI-generated content on a job application in a negative light. Some have even admitted that they’d be less likely to hire a candidate who’s used AI altogether. So you could be rejected by AI for using AI. The irony is palpable. Hypocrisy aside, hiring managers’ AI aversion is ruinous. Companies can’t get enough of AI at the moment. They’re so desperate for AI talent that they’re happy to sacrifice experience if it means the candidate knows how to use a chatbot. Why, then, are firms turning away candidates who use AI to aid their job search? Getting rid of anti-AI bias in hiring The first step firms must take to achieve this is to root out anti-AI bias in their hiring processes. To achieve this, executives need to make it their responsibility to ensure hiring managers are familiar with the business’s skills needs now and over the coming years. In addition, they should make sure that indications of these skills aren’t being ignored or punished at the application stage. Instilling hiring managers with a stronger understanding of how businesses are deploying AI will help reduce bias and ensure that hiring managers can spot AI talent amid a sea of applicants. Introducing AI-based tasks in skills assessments Then, we need to see companies introduce AI-based tasks in their skills assessments. This should be for all job roles, not just tech-oriented ones. Along with the usual tasks hiring managers typically give, like drafting a client brief or giving a presentation, employers should assess candidates on their ability to use and deploy AI tools effectively. AI-based tasks might include creating a prompt for a chatbot capable of outputting high-quality materials—where they mark applicants for the quality of the output. Or if the business employs specific AI tools, they can test applicants on their knowledge of the tool or ability to get to grips with it in a short time frame. Finally, employers should take the final step and strategically prioritize AI-fluent applicants over those who show no capability (or an unwillingness to learn). They might want to do this by creating an AI-capability score. Hiring managers need to prioritize AI skills, talents, and appetite, just as they have the mandate to hire for other role-relevant technical skills. AI will impact every single role within every company in the next few years. And in a world where AI tools are increasingly critical to businesses’ success, a base level of AI capability among workforces will be a make-or-break factor. Firms that continue to penalize AI use and ignore its critical nature to their business risk relegating themselves to anti-AI obscurity. They’re likely to find themselves left in the dust of their more open-minded and forward-thinking competitors. If you’re a hiring manager, why not take another look at those AI-supported applications? After all, the future of your workforce might sit behind them. View the full article

Last month I posted a job description on our blog for a chief of staff role at my venture capital firm, Graham & Walker. Turns out, that job description really hit a nerve. Within an hour, more than a hundred candidates had put their hat in the ring and filled out the long Google form that served as our only form of application. Quickly overwhelmed by the interest, I asked everyone I knew for tips on how to review all those applications most efficiently. They recommended several tools, from LLMs to custom built. I was deep in research when something happened that made me change my mind. Our Google form included an optional field for “anything else you’d like to share.” And that’s where I saw what one applicant wrote: “Applying for jobs is so dehumanizing.” In that moment, I decided that if someone was going to take the time to thoughtfully fill out my Google form, I was going to do my best to read it. I don’t hire often. I decided that this time, I would take no shortcuts. And that is how I ended up spending an entire week reading 597 job applications for one open role at Graham & Walker. Not scrolling. Not AI-prompting. Not keyword searching. Actual reading. I do realize this is not normal. Most people—most general partners, most hiring managers—do not do this. They can’t, and they probably shouldn’t. To be honest, I don’t think I will be able to do anything like this ever again. But for me, and for this moment in time, it felt like time well spent. It was an experience I will never forget. A very manual hiring process To be clear, I didn’t review 597 resumés. I reviewed 597 candidates’ answers to four open-ended questions: 1. Why do you want to work in venture capital? 2. Why do you want to work at Graham & Walker? 3. Why are you the best person for this role? 4. Anything else you want us to know? I read as fast as I could, slowing down whenever something really grabbed my attention. And based on those, I decided whether to look at the resumé. Out of 597 applicants, I clicked on 174 resumes. Two of my colleagues also reviewed around 200 applicants each. We gave a score to each one, selected the top scorers, and narrowed the field down to 15 finalists. Those candidates did a first interview. Seven moved on to a second interview. Three moved on to a third, and final, round. By which point, I could see us working with any of them. They were truly that amazing—so much so that I was sad I couldn’t hire all three. In the end, we made an offer to a stellar candidate and she accepted. What job seekers should know Let’s be real—this process isn’t sustainable, let alone scalable. Most hiring managers won’t do what I did, especially in the age of AI. Job seekers should be aware of that. That being said, one crucial tip I would share is to know your audience. Just like we tell founders to research investors before they pitch, job seekers should research companies before they apply. If you’re applying to high headcount organizations, your resumé needs the right keywords. But for smaller organizations, you can’t rely on that same resumé to tell your story. Some of the best answers came from people with the least polished or traditional resumés. And others packed both resumé power and answers that jumped off the page. There’s a big difference between someone who wants a job and someone who wants this job. That may not matter as much to employers hiring hundreds or thousands of people every year. But for a high-impact, high-trust role at a pre-seed VC fund like mine, it makes a world of difference. Another lesson? Hundreds of you bring to the table a “unique combination of strategy and execution.” I lost count of how many times I read that. Perhaps not quite so unique after all? What hiring managers should know AI is changing how we work, fund, and build. But some decisions still require a human touch—and hiring is one of them. Behind every application is a real person, with a real story. And if we want to build real companies, we can’t afford to lose sight of that. I could only hire one person this time. But reading 597 applications reminded me that talent is everywhere. It forced me to slow down and pay attention. To read between the lines. To notice the difference between qualified on paper and eager to contribute. To consider the people who have the right attitude, not just the right experience. And to remember that raw talent, enthusiasm, grit, effort, and authenticity are just as valuable as credentials—sometimes more. In venture, we talk about backing people, not companies. This was the hiring version of that. It wasn’t the most efficient process. But it’s one I’ll never forget. This story originally appeared on Leslie Feinzaig’s Blind Spots Substack. Subscribe to it here. View the full article

For years, baby boomers have been “aging in place” and keeping home turnover low. And now, not only are boomers holding onto their homes, they’re also the generation buying the most property—boxing out millennial homebuyers for only the second year since 2013. Millennials, who range from 26 to 44 years old, have largely dominated the housing market for the past decade. The only exceptions to this rule have occurred in 2023 and 2024, according to data from the National Association of Realtors (NAR). Between July 2023 and July 2024, the share of millennial homebuyers dropped to 29%, down from 38% a year ago. Meanwhile, boomers (ages 60 to 78) accounted for 42% of home purchases. “In a plot twist, baby boomers have overtaken millennials—the largest U.S. population—to become the top generation of home buyers,” Jessica Lautz, NAR deputy chief economist and vice president of research, said in a press release. “What’s striking is that half of older boomers and two out of five younger boomers are purchasing homes entirely with cash, bypassing financing altogether.” What does this mean for aspiring homebuyers? While this is only the second time that boomers have overtaken millennials in recent years, it does represent a larger pattern: First-time homebuyers are getting older. In 1991, the median age of first-time homebuyers in the U.S. was 28 years old. In 2024, it was 38 years old. As real estate expert Lance Lambert put it, “the median first-time U.S. homebuyer in 2024 (age 38) has been out of high school for 20 years but is also only 24 years away from the earliest age at which they could receive Social Security benefits (age 62).” One main driver for this shift is the fact that both cost of living and home affordability have increased significantly in the past several years. Since 2020, the income needed to afford the average American home has shot up by a whopping 79%. Starter homes are a thing of the past for many aspiring young homebuyers. Still, some young Americans are managing to become first-time homebuyers, and they’re establishing new standards for home ownership along the way. Per the NAR report, 3% of homebuyers over the past year were Gen Zers. “Gen Z is slowly entering the housing market with the lowest household income and they’re more likely to be single than other buyers,” Lautz said. Of the generations, Gen Z had the largest share of single, female homebuyers—presumably as many women put off marriage or choose to remain single. View the full article

Where legislatures have refused to boost pay and benefits for workers, advocates have often taken the fight straight to voters. In recent years, voters in Michigan, Missouri, and Nebraska overwhelmingly backed higher state minimum wages and guaranteed paid sick leave at the polls. But despite that strong showing of support, lawmakers on both sides of the aisle are now trying to water down or even roll back the measures their constituents approved. In November, 58% of Missouri voters approved Proposition A, which raises the state minimum wage to $15 by 2026 and requires employers to provide paid sick leave. That level of support, said Missouri Jobs with Justice Policy Director Richard Von Glahn, stems from the fact that the measure “speaks to the experiences that voters have in their lives and where the economy is not working for them.” Typically, when his organization was out gathering signatures, voters expressed surprise that the minimum wage was not already $15 an hour and that paid sick leave was not already a guarantee. The vote shows it was “the clear will of what voters want,” Von Glahn said. But in March, the Missouri House passed legislation repealing the paid sick leave measure and undoing the state’s decades-long practice of regularly updating the minimum wage to keep up with inflation. If the bill becomes law, wage increases will cease in January 2027. To justify such changes, Republican state Representative Mitch Boggs said, “Of course the people voted for it. It would be like asking your teenager if he wanted a checkbook. They’re going to vote for it every time.” Republican state Representative Scott Miller put it another way: “Just because 57% of the people that voted that day voted in favor of something, that doesn’t make it right. They’re taking away the choice of businesses to engage in [the] free market.” It’s not just lawmakers trying to undo the will of the voters, however. A group of businesses and individuals have asked the state Supreme Court to strike down the measure entirely, arguing that it violates the state Constitution’s single subject requirement. In their lawsuit they claim that wages and paid sick time are separate issues that should not have been combined in a single measure. Von Glahn pushed back on that argument: “Wages for hours worked and wages for paid sick time, that’s part of total compensation. As a working person, if I have money in my check, do I care if it’s from paid sick days or from hours that I worked?” Nebraska voters passed their own paid sick leave ballot measure by a staggering 74% this past November. A majority of voters in every legislative district supported it, and the support was higher than for the lawmakers themselves. That’s not the only measure state lawmakers want to change, however. In 2022, nearly 59% of voters approved a measure that will raise the state’s minimum wage to $15 an hour by 2026 and keep increasing it in later years to keep up with inflation. “Nebraskans really care about their neighbors,” Jo Giles, executive director of the Women’s Fund of Omaha, said of the support both measures received. Paid sick leave, she said, is “a common sense solution.” As in Missouri, many voters she spoke to while gathering signatures were surprised it wasn’t already guaranteed. And yet efforts to get lawmakers to take action themselves had not succeeded. “We tried for many years,” Giles said, including during the height of the pandemic when workers were getting sick by the thousands. But bills never moved forward. “After many, many attempts, we determined, ‘Okay, we’re not going to get it through the Legislature, so let’s ask the people what they want,’” Giles said. “It was pretty clear what the people wanted: They wanted paid sick leave, they wanted to increase the minimum wage.” That hasn’t stopped Nebraska lawmakers from seeking to change the measures approved by their constituents. Last year, two state lawmakers introduced bills to exempt young workers from the higher wage. The Nebraska Legislature is officially nonpartisan, but one of the lawmakers was aligned with Democrats and the other with Republicans. The effort failed to advance in the Legislature. This session, those two lawmakers and others are seeking to weaken both the minimum wage and sick leave policies. Legislative Bill 698, introduced by a Republican-aligned senator, would exempt companies with 10 or fewer employees from the paid sick leave requirement. Yet the measure voters passed already makes an allowance for small businesses by allowing those with 20 or fewer employees to provide their workers with fewer days of leave. The bill would also exempt agricultural workers and those under 16 while eliminating employees’ right to sue their employers if they aren’t given the leave they’re owed. Giles argued that these changes gut “the core aspects” of the initiative. Another bill introduced this year, Legislative Bill 258, meanwhile, would allow employers to pay people younger than 19 a lower minimum wage and would eliminate future minimum wage increases. Beyond the impact on workers themselves, Giles believes lawmakers’ actions could harm the entire state. “What does that mean for our overall democracy if people cannot exercise their voice and implement policies that are popular?” she said. Residents’ votes “should be honored.” In both Missouri and Nebraska, conservative lawmakers have led the charge to roll back ballot measures. In Michigan, Democrats have joined the effort. Back in 2012, Mothering Justice, a nonprofit that advocates for issues impacting women of color, started pushing for a paid sick leave bill in the state Legislature, but Republicans stood in the way. It became clear that “if we wanted to get this done, we would have to go straight to voters,” said Danielle Atkinson, the nonprofit’s founder. Her group was poised to do so, submitting more than 280,000 signatures to put both paid sick leave and a higher minimum wage on the ballot in 2018. There was “always overwhelming support” from voters, she said, because it “was extremely popular and needed.” But then the Republican-controlled Legislature stepped in that September. Over united Democratic opposition in the state Senate but with some Democratic support in the state House, lawmakers passed legislation to raise the minimum wage and institute a paid sick leave requirement before voters had the chance to weigh in. That wasn’t because lawmakers agreed with the ballot measures; they did so explicitly to come back and gut both measures later on, something that would have been much harder had the issues passed by ballot measure. State Senate Republican Majority Leader Arlan B. Meekhof explained the vote this way: “The Senate adopted the policy to preserve the ability for this Legislature and future legislatures to amend the statute to better fit our state and our economy.” And lawmakers did in fact later amend the legislation by voting to delay the minimum wage increase by nearly a decade, scrap future inflation adjustments and preserve a lower tipped minimum wage. Lawmakers also exempted employers with fewer than 50 employees from paid sick leave and scaled it back for everyone else. The groups behind the ballot measures fought back in the courts, arguing that what lawmakers did violated the state Constitution. That took “time, energy,” and “a considerable amount of resources,” Atkinson said. “But we thought it was important to fight for the will of the people and direct democracy.” Last summer, it seemed they had finally won: The state supreme court found the Legislature had indeed violated the state Constitution and reinstated the original wage and sick leave measures. The new benefits were set to go into effect on February 21. “We were extremely hopeful,” Atkinson said. “We were like, ‘Great, on to the next fight.’” But the Legislature wasn’t done intervening. An hour before midnight on February 20, lawmakers passed bills to preserve a lower tipped minimum wage, delay implementation of paid sick leave, exempt young and temporary seasonal workers, reduce guaranteed unpaid time off for employees of small businesses, and strip workers of the right to sue employers for violating the new rights. This time, nearly half of Democrats in both chambers joined with all Republicans to pass the measures, and Democratic Governor Gretchen Whitmer signed them into law. The governor had “heard concerns about implementation of the new law,” according to a statement from spokesperson Stacey LaRouche, while the bill was under consideration, and supported “a bipartisan deal that protects servers and wait staff, while also providing certainty to small businesses and helping Michigan remain competitive.” Business groups, particularly the Michigan Restaurant and Lodging Association, had lobbied hard for the tipped minimum wage changes. It was “very clear” that lawmakers of both parties “were being influenced by the business community,” Atkinson said. “The restaurant industry did a very good job of manufacturing outrage.” Atkinson is frustrated that those tactics succeeded. “Michigan is a place where we’re known for workers’ rights, and we had an opportunity to be a pretty big part of a larger movement to eliminate a sub-minimum wage, and we missed it,” she noted, referring to the lower wage employers can pay tipped employees. Having Democrats join in was even worse. “When you see Democrats introducing legislation that’s undermining workers’ rights, it makes . . . an easier target for Republicans to do the same,” she said. “It’s really unfortunate that that came from members of a party that claims to be for workers’ rights.” This piece was originally published by Capital & Main, which reports from California on economic, political, and social issues. View the full article

AI is an extraordinary tool that amplifies our cognitive capacity. It can analyze, summarize, and generate content faster than any human. However, AI is only ever as good as the questions we ask it. It will never replace our capacity for thinking, and can, in fact, reinforce bias because it is learning what we teach it. For this reason, the top skills of the future include thinking skills. According to the World Economic Forum’s Future of Jobs report, employers anticipate that beyond technical literacy, the most in-demand capabilities will be creative thinking, critical thinking, resilience, and the capacity for learning. Thinking is a premium, and yet it is also the very thing that is most at risk. We all know that when it comes to data, rubbish in = rubbish out. The same goes for our mind. What we feed it and how we use it determines the quality of our contribution and the value we add. As a high-performance coach and leadership expert, I spend my time consulting with leaders and their teams, challenging them to do better thinking and extract the value of their collective capacity. Modern-day workers are facing a triple threat from the joint epidemics of algorithms, attention theft, and burnout. Here’s why: 1. Algorithms reinforce biases More and more, our capacity to think, create, and problem-solve is being challenged by algorithms delivered through social media. Our viewpoints are being regurgitated back to us via algorithms that sense what we like, what we tolerate, and what we think we need. Social media serves to reinforce existing beliefs, not challenge them. We are slowly losing the capacity for critical thinking, and this is the very capacity we need to develop if we are to remain adaptive in a world where cognitive load is being managed more and more by computers. 2. Attention theft robs us of time Attention theft is catastrophic to independent thinking and crippling our ability to focus. How many notifications are pinging right now to pull your attention away from reading this article? How many times a day are you pulled away from the task at hand? Research from Tania Barney, neuroscience and sensory processing expert, suggests that distractions are costing us time as well as money. Her research found: An average of 2.1 hours are lost daily as a result of distractions. The average time spent on a task before we get distracted is 11 minutes. The average time it takes after a distraction to return to a task is 25 minutes. After meetings, emails, unplanned interactions, and rest breaks, how many hours do we have left in a day for thinking and productive work? We get pulled into the urgent things that feel pressing but do not meaningfully matter (like chats with colleagues, reply-all emails, and notification alerts). All this leads to the next major threat to thinking—burnout. 3. Burnout robs us of energy Burnout is the compound interest on lost productivity due to attention theft. Just because we’re getting distracted by “urgent” unimportant stuff doesn’t mean that the real important stuff goes away. It piles up, weighing us down psychologically and eating into recreation hours where we should be recharging our batteries through rest, exercise, or time with loved ones. Burnout is a global issue, costing humans their well-being and businesses millions in lost productivity. Burnout is the result of prolonged work stress. Symptoms include overwhelm, constant exhaustion, and a feeling of being ineffective at work no matter how hard you try. Increased rates of burnout add up to bad news for business. Burnout has been identified as one of the leading causes driving people to leave their jobs. But it also leads to disengagement, which can cost employers 34% of a disengaged employee’s annual salary, according to the Gallup State of the Global Workplace 2021 report. Prioritize team thinking time to leverage collective potential With the joint epidemics of algorithms, attention theft, and burnout, our most precious resources have changed from time and money to energy and attention. To counteract this, we all need to be more curious. Promote and legitimize thinking time by asking more questions in daily interactions. Encourage your team members to build on one another’s ideas. Create regular cadences when the team meets to reflect, reprioritize, and reset, such as quarterly team-planning workshops. The future of work is human—and your capacity to create spaces and places where people can think, learn, adapt, and grow is what will allow teams and organizations to transform and endure. View the full article

With their drab gray suits and their Buddy Holly glasses, the so-called traitorous eight don’t look like revolutionaries. Given no context, you can imagine them occupying some kind of middle-management role at a small regional bank. And yet these are the people you can thank for the digital world. The eight—which included Intel cofounder Gordon Moore—had departed Shockley Semiconductor Laboratory to found Fairchild Semiconductor, which soon became the world’s biggest producer of electrical components for computers. Many of its founders would, in turn, leave again to launch their own ventures. Many of these companies coalesced in the same area—the place we now call Silicon Valley—creating an ecosystem for innovation and technological development that endures to this day. Look again at that photo. Even with the suits and the glasses, these are arguably some of the most interesting and influential people that the technology industry has ever known. Even if you don’t know their names, and even though they have never appeared on the Joe Rogan podcast, they still have a legacy that endures to this day. The Power of Hardware On a personal level, I have always found hardware more interesting than software. There’s a joke that CPUs are just “rocks we tricked into thinking,” which has some truth to it. You can’t help but be amazed at the process that turns iron, copper, gold, and silicon dioxide into something that can run unfathomably complex mathematical calculations, play chess, and stream Netflix. And that’s before you take into account that even the most basic consumer CPU has billions of transistors, each measuring a fraction of the width of a hair. Perhaps the main reason I’m drawn to hardware is that it’s often easy to measure whether something is better than the thing that preceded it. With a tape measure, you can see whether one computer is smaller than another. You can calculate how many mathematical operations a CPU can perform in a second, or count the number of pixels on a display. You can measure its weight, or the heat it gives off, or whether one battery has a larger capacity than another. Hardware is clean-cut. Straightforward. Unambiguous. And these improvements aren’t theoretical, but are felt directly by the end user. When a physical object is meaningfully better, you can tell. If you have upgraded from an Intel to an Apple Silicon Mac, you know this. You probably remember what it was like when you ditched your bulky CRT monitor for an LCD flat panel. You know the difference between a computer with a mechanical hard drive and one with flash storage. Hardware is typically built with utility in mind. The old adage “hardware is hard” is true, but it neglects the fact that it’s also pretty expensive. You only really build something if you believe it’s better than the existing thing, and that somebody will find it useful enough to pay for it. Silicon Valley Needs to Rediscover Its Roots The modern tech industry—especially that which now occupies the same hallowed ground once trod by the treacherous eight—has become a shell of its former self. Tech’s “innovations” feel only marginally iterative at best. It is this that makes me nostalgic for the era when Silicon Valley was about silicon—or, more specifically, physical, tangible objects that changed the world. And I believe it is an era that we can, and must, return to. The Silicon Valley of the late 1960s, 1970s, and 1980s was a glorious time of American innovation and engineering, where verifiable geniuses discovered the breakthroughs that allowed our current world to exist. The integrated circuit. The microprocessor. The computer mouse. It was an era when technological vision and clear-thinking business strategy combined to bring new inventions to a market, and then popularize them to a global scale. And in doing so, Silicon Valley changed everything. To be clear, I am not just talking about vision. I’m talking about hardware. The applications we will need to run in the future will require faster, better computers, and we need somebody to invent them. Faster, better computers will allow us to reclaim ownership of the tech we use, enabling us to finally break free of the cloud. It will help undo some of the disastrous cultural changes that have occurred over the past decade or so, when people got used to the idea that they must always be subject to the mercies of another, larger tech company. Hardware is hard. Change is even harder. But in this case, I think it’s worth it. The Bright Light on the Tip of the Spear So, there is some cause for optimism, and it’s not in giant GPUs. Buried in the news coming out of CES was the announcement of Nvidia’s DGX Spark, a $3,000 desktop computer powered by Nvidia’s GB10 Grace Blackwell Superchip, that went relatively unnoticed but I believe is a significant moment in personal computing. The DGX Spark delivers up to 1 petaflop of performance in a compact form factor, giving researchers and developers unprecedented access to cutting-edge computational power directly at their desks. It’s like having a computer that’s a thousand times faster than a regular desktop in the body of a Mac Mini, and I’m a little surprised it isn’t being taken more seriously. In more human terms, Nvidia created an ultrapowerful Mac Mini that developers, data scientists, and AI researchers are able to use to run reasonably large data workloads and AI models on their desk as opposed to a fleet of massive GPU servers in the cloud. While Silicon Valley’s biggest companies have grown on the back of software, the truth is that it needs hardware to grow any further, and while those GPUs might be the headline-grabbers during Nvidia’s earnings, creating meaningful new kinds of computing is what will lead to actual innovation in software. As a result, by creating a Blackwell chip inside a Mac Mini-size supercomputer, Nvidia allows companies to crunch through large data sets or run self-hosted generative AI models quickly and efficiently, all without relying on the cloud to do so. This vastly lowers the barrier to entry for high-performance computing, which currently requires buying or renting expensive specialized hardware or spinning up expensive infrastructure. I’m going to dive briefly into why this matters. For years, both at Voltron Data and previously at BlazingSQL, I’ve advocated for clustering smaller, more efficient, and less-expensive GPUs together using high-performance networking. However, network limitations have always prevented full utilization of the cluster’s compute performance since data simply couldn’t move fast enough to keep GPUs fully fed. While it hasn’t shipped yet, Nvidia has specifically called out the inclusion of ConnectX to allow users to connect two Nvidia DGX Spark computers together, as well as other features (NCCL, RDMA, GPUDirect storage) that are specifically built for faster networking. This will enable efficient parallel processing and high-bandwidth communication, making high-performance AI and analytics workloads accessible to a broader range of researchers and enterprises. A distributed model using a cluster of Nvidia DGX Spark units could offer a more cost-effective and flexible alternative to currently available GPU clusters, lowering the barrier to entry for basically any high-performance computing use cases. My focus on Nvidia DGX Spark is to illustrate a greater point about what will keep Silicon Valley at the forefront of technological progress. True innovation doesn’t come from just making things “bigger” or “more powerful,” but in the distinct relationship and interactions between software and hardware, and even between different pieces of hardware. Nvidia DGX Spark isn’t just Nvidia making a chip smaller, but finding ways to add faster on-device memory, software to make getting the data to both the memory and the GPU faster, and (I imagine) some unique ways to keep it cool. The truly world-changing innovations and technological breakthroughs that will advance humanity will come from a deep commitment to silicon engineering, and Silicon Valley needs to remember that this is the only way that software will continue to grow. View the full article

Pharma group builds out American supply chains as part of preparations for potential US tariffsView the full article

Insulated from industry tumult, smaller French group seeks to move on from turnaround by boosting EV and hybrid salesView the full article

‘When I see £4 for an espresso in London . . . I see the limit,’ says Italian roaster’s bossView the full article

Testers have raised concerns that its technology is being rushed out without sufficient safeguardsView the full article

It’s not just bread and circuses any moreView the full article

Canva has officially launched Visual Suite 2.0, its most comprehensive product update to date, during the Canva Create 2025 event. The update introduces a suite of AI-powered tools and new features aimed at seamlessly merging creativity with productivity. According to the announcement, Visual Suite 2.0 is designed to eliminate the disconnect between productivity tools and creative platforms by allowing users to work across presentations, videos, whiteboards, websites, and spreadsheets within a single format. “Whether you’re brainstorming on a whiteboard, mapping out your strategy in a doc, or building a campaign across slides, spreadsheets, and socials, everything lives in one place,” the company stated. Canva Sheets and AI-Driven Insights One of the flagship features in this launch is Canva Sheets, which reimagines the traditional spreadsheet as a visual and creative workspace. With AI features like Magic Insights and Magic Formulas, users can input text prompts and let the platform automate data tasks. Canva notes that Sheets connects directly with the rest of the Visual Suite, allowing for integrated and visually dynamic data presentations. “With drag-and-drop visual layouts, your spreadsheets aren’t just functional, they’re beautiful,” Canva said in its release. Enhanced Automation with Magic Studio Canva reports that its Magic Studio tools have been used over 16 billion times. With Visual Suite 2.0, those tools are now integrated into Sheets to streamline content creation. Features include the ability to automatically fill empty cells with Magic Write, bulk translate content for global localization, and generate multiple versions of a design using Bulk Create. Magic Resize, another included feature, enables users to convert entire sets of designs into different formats and dimensions while preserving layout integrity. Magic Charts for Data Visualization Visual Suite 2.0 introduces Magic Charts, a feature that transforms raw data into interactive, real-time visualizations. Users can connect data from platforms such as Google Analytics and HubSpot and receive intelligent chart recommendations to present information effectively. AI-Enhanced Design and Interactivity Canva AI is positioned as a “creative companion” for users. From generating presentations and graphics to offering suggestions based on text, voice, or media prompts, the tool is integrated across the suite. Users can also fine-tune designs using the Brand Kit or turn them into shareable templates. Additionally, the new Canva Code feature allows users to build interactive experiences like calculators, educational games, or custom tools with natural language descriptions—no coding experience required. New Photo Editing Tools Visual Suite 2.0 also introduces an upgraded Photo Editor, allowing users to modify images within the design interface. The new Background Generator can replace image backdrops to match the subject with lighting and mood. Users can also manipulate image elements by pointing and clicking to reposition, resize, or recolor them. Availability and Community Involvement Canva emphasized that many of the new tools and features were developed based on feedback from its community of 230 million users. “Each year we receive more than one million ideas, feature requests, and dreams from our community,” the company stated. Users can begin exploring Visual Suite 2.0 today by visiting the Canva homepage. The company notes that this release marks just the beginning, encouraging continued feedback to drive future innovation. This article, "Canva Unveils Visual Suite 2.0 with Major AI-Powered Productivity Tools" was first published on Small Business Trends View the full article

Canva has officially launched Visual Suite 2.0, its most comprehensive product update to date, during the Canva Create 2025 event. The update introduces a suite of AI-powered tools and new features aimed at seamlessly merging creativity with productivity. According to the announcement, Visual Suite 2.0 is designed to eliminate the disconnect between productivity tools and creative platforms by allowing users to work across presentations, videos, whiteboards, websites, and spreadsheets within a single format. “Whether you’re brainstorming on a whiteboard, mapping out your strategy in a doc, or building a campaign across slides, spreadsheets, and socials, everything lives in one place,” the company stated. Canva Sheets and AI-Driven Insights One of the flagship features in this launch is Canva Sheets, which reimagines the traditional spreadsheet as a visual and creative workspace. With AI features like Magic Insights and Magic Formulas, users can input text prompts and let the platform automate data tasks. Canva notes that Sheets connects directly with the rest of the Visual Suite, allowing for integrated and visually dynamic data presentations. “With drag-and-drop visual layouts, your spreadsheets aren’t just functional, they’re beautiful,” Canva said in its release. Enhanced Automation with Magic Studio Canva reports that its Magic Studio tools have been used over 16 billion times. With Visual Suite 2.0, those tools are now integrated into Sheets to streamline content creation. Features include the ability to automatically fill empty cells with Magic Write, bulk translate content for global localization, and generate multiple versions of a design using Bulk Create. Magic Resize, another included feature, enables users to convert entire sets of designs into different formats and dimensions while preserving layout integrity. Magic Charts for Data Visualization Visual Suite 2.0 introduces Magic Charts, a feature that transforms raw data into interactive, real-time visualizations. Users can connect data from platforms such as Google Analytics and HubSpot and receive intelligent chart recommendations to present information effectively. AI-Enhanced Design and Interactivity Canva AI is positioned as a “creative companion” for users. From generating presentations and graphics to offering suggestions based on text, voice, or media prompts, the tool is integrated across the suite. Users can also fine-tune designs using the Brand Kit or turn them into shareable templates. Additionally, the new Canva Code feature allows users to build interactive experiences like calculators, educational games, or custom tools with natural language descriptions—no coding experience required. New Photo Editing Tools Visual Suite 2.0 also introduces an upgraded Photo Editor, allowing users to modify images within the design interface. The new Background Generator can replace image backdrops to match the subject with lighting and mood. Users can also manipulate image elements by pointing and clicking to reposition, resize, or recolor them. Availability and Community Involvement Canva emphasized that many of the new tools and features were developed based on feedback from its community of 230 million users. “Each year we receive more than one million ideas, feature requests, and dreams from our community,” the company stated. Users can begin exploring Visual Suite 2.0 today by visiting the Canva homepage. The company notes that this release marks just the beginning, encouraging continued feedback to drive future innovation. This article, "Canva Unveils Visual Suite 2.0 with Major AI-Powered Productivity Tools" was first published on Small Business Trends View the full article

Landbase has announced the launch of the Campaign Feed, a new enhancement to its agentic AI-powered go-to-market (GTM) platform, along with the acquisition of Delegate, a company known for its predictive and automated customer success solutions. These developments are aimed at accelerating Landbase’s mission to automate omnichannel sales outreach and improve go-to-market strategies through advanced AI-driven solutions. The Campaign Feed is designed to address key GTM challenges such as fragmented data, manual processes, and ineffective audience engagement. With the new capability, users receive AI-enriched campaign recommendations that can be reviewed, approved, edited, or denied quickly, enabling campaign launches in minutes rather than months. “Unlike traditional outbound techniques that rely heavily on disparate tools and manual input, the Campaign Feed leverages agentic AI and Landbase’s proprietary model GTM-1 Omni to automate complex workflows and provide actionable campaign recommendations,” said Daniel Saks, CEO and co-founder of Landbase. “The Campaign Feed brings the fun and effortless experience of the ‘vibe coding’ phenomenon to GTM, making it easy to review, edit and launch campaigns in minutes instead of months.” The acquisition of Delegate supports the accelerated development of the Campaign Feed and other innovations. Delegate’s team brings its expertise in customer success automation to Landbase, contributing to faster product enhancements. Key hires from Delegate include Hugh Hopkins as head of product development and Alex Berry as head of sales. “Landbase is revolutionizing how people work by launching the Campaign Feed with recommendations that make it easy to take action to help businesses grow,” said Hopkins. “The Campaign Feed represents a significant paradigm shift in how companies approach their GTM strategies, combining AI-driven insights with hyper-targeted recommendations and seamless agent-driven execution.” Key features of the Campaign Feed include: AI-driven automation: Automates repetitive tasks to free up time for strategic initiatives. Predictive audience recommendations: Identifies and prioritizes high-potential audiences. Omnichannel outreach: Automates communication across email, LinkedIn, and phone channels. “The Campaign Feed enhances Landbase’s platform’s ability to amplify its omnichannel outreach efforts in record time, setting a new standard in the industry,” said Berry. “By combining our expertise with Landbase’s breadth of engineering skills and recently announced agentic AI Lab and proprietary GTM-1 Omni model, we’ll help make our collective GTM vision a reality and be able to deliver better results for our customers in a highly competitive and fast-moving space.” The Campaign Feed is now available as part of Landbase’s subscription-based platform. This article, "Landbase Launches Campaign Feed and Acquires Delegate to Boost AI-Driven GTM Strategies" was first published on Small Business Trends View the full article

Landbase has announced the launch of the Campaign Feed, a new enhancement to its agentic AI-powered go-to-market (GTM) platform, along with the acquisition of Delegate, a company known for its predictive and automated customer success solutions. These developments are aimed at accelerating Landbase’s mission to automate omnichannel sales outreach and improve go-to-market strategies through advanced AI-driven solutions. The Campaign Feed is designed to address key GTM challenges such as fragmented data, manual processes, and ineffective audience engagement. With the new capability, users receive AI-enriched campaign recommendations that can be reviewed, approved, edited, or denied quickly, enabling campaign launches in minutes rather than months. “Unlike traditional outbound techniques that rely heavily on disparate tools and manual input, the Campaign Feed leverages agentic AI and Landbase’s proprietary model GTM-1 Omni to automate complex workflows and provide actionable campaign recommendations,” said Daniel Saks, CEO and co-founder of Landbase. “The Campaign Feed brings the fun and effortless experience of the ‘vibe coding’ phenomenon to GTM, making it easy to review, edit and launch campaigns in minutes instead of months.” The acquisition of Delegate supports the accelerated development of the Campaign Feed and other innovations. Delegate’s team brings its expertise in customer success automation to Landbase, contributing to faster product enhancements. Key hires from Delegate include Hugh Hopkins as head of product development and Alex Berry as head of sales. “Landbase is revolutionizing how people work by launching the Campaign Feed with recommendations that make it easy to take action to help businesses grow,” said Hopkins. “The Campaign Feed represents a significant paradigm shift in how companies approach their GTM strategies, combining AI-driven insights with hyper-targeted recommendations and seamless agent-driven execution.” Key features of the Campaign Feed include: AI-driven automation: Automates repetitive tasks to free up time for strategic initiatives. Predictive audience recommendations: Identifies and prioritizes high-potential audiences. Omnichannel outreach: Automates communication across email, LinkedIn, and phone channels. “The Campaign Feed enhances Landbase’s platform’s ability to amplify its omnichannel outreach efforts in record time, setting a new standard in the industry,” said Berry. “By combining our expertise with Landbase’s breadth of engineering skills and recently announced agentic AI Lab and proprietary GTM-1 Omni model, we’ll help make our collective GTM vision a reality and be able to deliver better results for our customers in a highly competitive and fast-moving space.” The Campaign Feed is now available as part of Landbase’s subscription-based platform. This article, "Landbase Launches Campaign Feed and Acquires Delegate to Boost AI-Driven GTM Strategies" was first published on Small Business Trends View the full article

The U.S. Small Business Administration (SBA) has introduced a series of new verification protocols aimed at preventing fraud within its loan programs and ensuring that financial support reaches only eligible American small business owners. The changes follow recent findings by the Department of Government Efficiency (DOGE), which uncovered widespread abuse of SBA loan programs. According to data from the U.S. Social Security Administration, over $630 million in loans were granted to applicants with birthdates suggesting they were either younger than 11 or older than 115 years old. Key measures now in place include citizenship and date-of-birth verification as part of the SBA loan application process. These updates are intended to safeguard the integrity of the agency’s programs and restore public trust. Fraud Prevention Measures The SBA now requires lenders to verify the citizenship status of all applicants to ensure businesses are not owned wholly or partially by illegal aliens. This new protocol aligns with an executive order aimed at ending taxpayer subsidization of individuals in the country unlawfully. In addition, loan applications must now include verified dates of birth. Any applicant reporting an age under 18 or over 115 will automatically be flagged under the SBA’s fraud alert system. The SBA stated these changes are designed to deter applicants from using identities belonging to deceased individuals or minors. “With the help of DOGE, the SBA has already made a number of common-sense reforms to prevent the rampant fraud we’ve seen over the last four years,” said SBA Administrator Kelly Loeffler. “Unlike the previous Administration, we respect the American taxpayer and are dedicated to ensuring every dollar entrusted to this agency goes to support eligible, legitimate small businesses. With these simple fraud prevention measures, we will end the abuse of our loan programs – with stronger safeguards to hold bad actors accountable.” Examples of Past Abuse The SBA outlined examples of fraud that occurred under previous policies: In June 2024, the agency approved a $783,000 loan to a business that was 49% owned by an illegal alien. However, the SBA identified the individual’s immigration status during a February audit and stopped disbursement, ensuring no funds were released. Between 2020 and 2021, DOGE found more than 3,000 SBA loans, totaling $333 million, were issued to borrowers over the age of 115 according to Social Security records. During the same period, DOGE identified over 5,500 loans worth approximately $300 million that were disbursed to children under the age of 11. Commitment to Reform The SBA emphasized that the new safeguards are part of a broader commitment to fiscal responsibility and program integrity. These steps are expected to reduce fraud and improve public confidence in the agency’s mission to support genuine small business development. This article, "SBA Implements New Verification Measures to Combat Loan Fraud" was first published on Small Business Trends View the full article

The U.S. Small Business Administration (SBA) has introduced a series of new verification protocols aimed at preventing fraud within its loan programs and ensuring that financial support reaches only eligible American small business owners. The changes follow recent findings by the Department of Government Efficiency (DOGE), which uncovered widespread abuse of SBA loan programs. According to data from the U.S. Social Security Administration, over $630 million in loans were granted to applicants with birthdates suggesting they were either younger than 11 or older than 115 years old. Key measures now in place include citizenship and date-of-birth verification as part of the SBA loan application process. These updates are intended to safeguard the integrity of the agency’s programs and restore public trust. Fraud Prevention Measures The SBA now requires lenders to verify the citizenship status of all applicants to ensure businesses are not owned wholly or partially by illegal aliens. This new protocol aligns with an executive order aimed at ending taxpayer subsidization of individuals in the country unlawfully. In addition, loan applications must now include verified dates of birth. Any applicant reporting an age under 18 or over 115 will automatically be flagged under the SBA’s fraud alert system. The SBA stated these changes are designed to deter applicants from using identities belonging to deceased individuals or minors. “With the help of DOGE, the SBA has already made a number of common-sense reforms to prevent the rampant fraud we’ve seen over the last four years,” said SBA Administrator Kelly Loeffler. “Unlike the previous Administration, we respect the American taxpayer and are dedicated to ensuring every dollar entrusted to this agency goes to support eligible, legitimate small businesses. With these simple fraud prevention measures, we will end the abuse of our loan programs – with stronger safeguards to hold bad actors accountable.” Examples of Past Abuse The SBA outlined examples of fraud that occurred under previous policies: In June 2024, the agency approved a $783,000 loan to a business that was 49% owned by an illegal alien. However, the SBA identified the individual’s immigration status during a February audit and stopped disbursement, ensuring no funds were released. Between 2020 and 2021, DOGE found more than 3,000 SBA loans, totaling $333 million, were issued to borrowers over the age of 115 according to Social Security records. During the same period, DOGE identified over 5,500 loans worth approximately $300 million that were disbursed to children under the age of 11. Commitment to Reform The SBA emphasized that the new safeguards are part of a broader commitment to fiscal responsibility and program integrity. These steps are expected to reduce fraud and improve public confidence in the agency’s mission to support genuine small business development. This article, "SBA Implements New Verification Measures to Combat Loan Fraud" was first published on Small Business Trends View the full article

Today’s B2B CEOs are tasked with a delicate balancing act: driving growth, improving efficiency, and creating seamless customer experiences, all while navigating unprecedented market complexity. Meanwhile, the revenue professionals responsible for executing these goals face their own challenges. Buying journeys have become increasingly labyrinthine, with big buying teams and long sales cycles. Seventy-seven percent of B2B buyers say their last purchasing decision was very complex or difficult, with more than 800 interactions on average with potential vendors. Misalignment across revenue teams compounds the issue, making it nearly impossible to deliver efficient, relevant, and cohesive buyer experiences. This complexity creates a cycle of inefficiency, where teams work harder to achieve diminishing returns. Fortunately, we’re at a pivotal moment in technology. AI and data advances are empowering organizations to simplify complex revenue cycles. Among these innovations, AI agents offer a promising solution. AI agents aren’t simple software add-ons. They’re intelligent partners that enable teams to act faster, collaborate more effectively, and scale more strategically. Let’s explore how CEOs can equip their teams with AI agents to achieve sustainable growth. AI agents are partners, not tools AI agents represent a significant evolution in business technology. Unlike traditional software, which passively waits for human input, AI agents actively analyze data, surface opportunities, make recommendations, and drive results in real time. For CEOs, this distinction is critical. AI agents don’t just automate repetitive tasks; they perform work that aligns with strategic goals. From identifying early buying signals to optimizing customer engagement, AI agents seamlessly integrate into workflows to ensure every touchpoint is efficient, personalized, and impactful. In a world in which breaking down silos and acting on intelligence faster than competitors defines success, AI agents are the bridge between vision and execution. Why good data powers great outcomes AI agents are only as effective as the data that fuels them. AI agents are built on large language models (LLMs) trained on public data. That data can sometimes produce sketchy results—like when Google’s AI search raised (and then dashed) Disney fans’ hopes by describing the impending release of Encanto 2 because it pulled its data from a fan fiction site. The fallout of misinformation in business can do much more damage than simply disappointing movie-goers. Poor-quality data can lead to disjointed recommendations and faulty business decisions. Not only that, but if you only use public data to feed your AI agents, you’ll have the same output as everyone else relying solely on LLMs. The solution for this lies within a business’s own walls. Enterprises have massive amounts of data that LLMs have not seen. Feeding this data to AI agents allows them to produce differentiated, contextualized output. For instance, integrating intent data into a sales-focused AI agent’s “diet” yields personalized outreach based on individual prospects’ needs. It’s also important that the data AI agents use is clean, accurate, and comprehensive—and that it spans the entire revenue organization. Shared data ensures that AI agents can piece together the full picture of the buyer journey—from early intent signals to post-sale engagement. What CEOs get wrong about AI agents AI agents are difficult to implement. AI agents don’t necessarily require complex overhauls. Scalable, modular solutions make it easier than ever to adopt AI incrementally, starting with specific use cases and expanding as success builds. Example:Many of our customers quickly deploy our conversational email agent for one-use case (such as re-engaging closed/lost opportunities) and build from there. This enables teams to see the immediate value of AI agent-led contextual email conversations, while at the same time laying the foundation for broader adoption. AI agents are only about efficiency. While AI agents excel at streamlining processes, their real value lies in their ability to drive strategic outcomes across industries. Example:Johnson & Johnson uses AI agents in drug discovery to optimize chemical synthesis processes. AI enhances efficiency, but more importantly, it drives strategic advancements in pharmaceutical innovation by accelerating development timelines and improving cost-effectiveness. The ROI of AI agents: Real-world impact Harri, a global leader in workforce management technology for the hospitality industry, faced a challenge familiar to many CEOs—the need to scale engagement without increasing resources. To support their strong marketing team in generating demand, Harri implemented an AI agent through 6sense as part of its outreach strategy. The AI agent autonomously identified high-intent prospects and delivered timely, personalized messages at scale, enabling Harri to engage buyers more efficiently and effectively. The results: They generated more than $12 million in pipeline and $3 million in closed/won deals in just one quarter. Campaigns achieved a 34% view-through-rate (VTR) rate, far exceeding the initial goal of 20%. They scaled marketing efforts without compromising on personalized engagement. By scaling outreach, improving engagement, and targeting high-value opportunities, Harri took pressure off its team, while achieving significant growth and enhancing the buyer experience. Pave the way for smarter growth AI agents are still so new that CEOs who aren’t using them yet can get ahead of the competition by learning to incorporate them now. These agents simplify complexity, align revenue teams, and deliver results. By integrating AI agents, CEOs can create seamless, personalized buying journeys that meet today’s expectations while driving growth. With significant AI advancements ahead, having a clear strategy is essential. By proactively adopting AI agents, organizations can address challenges and position themselves for sustained success in a rapidly evolving market. Jason Zintak CEO of 6sense. View the full article

Gold hits record high as investors seek haven assetsView the full article

The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. What’s in a claim? Sometimes a product can’t be defined by its claim, and that has become a huge problem for the consumer packaged goods industry. Take Dr. Bronner’s and Scrumbles, for example, which both recently announced they’re dropping their B Corp certification for what they perceive to be weakening standards that allow greenwashing. The changing claims landscape What B Lab Global has done is admirable. In 2006, they set out to recognize businesses that were a force for good—meeting high standards of social and environmental performance, transparency, and accountability. They deserve credit for their part in starting a global movement that redefined the role of business in society and helped usher in a new era of capitalism where purpose and profit are both priorities. But something pivotal happened along the way that revolutionized how deeply we’re able to understand products, yet B Corp and many of today’s product claims don’t account for it: the proliferation of data. Consumers initially saw the “B” and assumed it signified health, sustainability, or ethical practices. But as access to information increased, people started digging deeper. And what did they find? Sometimes, not much. The B Corp label, like many generic claims, became an umbrella term indicating different things to different people—or nothing at all. A consumer reckoning is here This problem isn’t unique to B Corp; it’s a symptom of a larger consumer reckoning. Consider the term “clean beauty.” It lacks a standardized definition, leaving its meaning up to interpretation. For some, it equates to products with safe ingredients; for others, it might be about sustainable packaging. But even “safe” and “sustainable” are too vague to tell us what we really want to know, such as if a fragrance is allergen-free or if its packaging is compostable. Shopping has almost become a guessing game; but it’s one the modern consumer refuses to play. I had my own “aha” moment when I was pregnant with my first daughter and started to become hyperaware of what ingredients and materials were in the things I was putting in and on my body. Through my extensive research, I quickly discovered how much of what we’re exposed to is toxic to human health and even started an Excel spreadsheet of what to avoid, that I consulted every time I made a purchase. It’s what led me to found Novi Connect, which gives brands and retailers the tools to provide data, signals, and even stories to consumers about their products. Ten years ago, this might have sounded excessive. But today, more consumers are demanding this level of transparency. They want clarity and precision, not ambiguity, and it’s time for brands and retailers to deliver. The power of granular data Here’s the good news: They can. With the proliferation of data and AI, we’re rapidly moving beyond binary labels and embracing a world of sophisticated, specific product attributes. This granularity allows brands and retailers to cater to the nuanced values of their customers. My favorite illustrative example of how this can show up is glycerin. Glycerin is one of the most benign, noncontroversial ingredients and is present in almost every product we use. But based on how it’s made, it can cater to consumers with very different values. If it’s derived from plants, that means it’s vegan; but that also typically means it’s derived from palm oil. Was the palm oil responsibly sourced? If so, that claim can be made to provide assurance that no deforestation or unfair labor practices were used in the production of the glycerin. Or, maybe no palm was used and the glycerin was derived from a less common feedstock like coconut oil. Now a palm-free claim can be made, which might be important to those looking for products that align with their environmental values. These are the questions shoppers are asking, and they’re demanding verified answers before deciding where to spend their money. The retailer responsibility While consumers are driving this change, the onus is on brands and retailers to embrace it and figure out how to make it work for their customer, and ultimately, their business. It’s important to note that there’s a delicate balance between presenting information for a seamless shopping experience and providing detailed product claims. Amazon is a poster example of what this can look like. They use the green leaf symbol to provide a high-level signal and draw the customer in, then also allow you to explore the details of why a product earned that designation. Their program includes 55 unique certifications a product can qualify for. That might sound overwhelming; but it takes into account that not all shoppers care about the same things, and not all certifications are relevant for all products. With this system, it’s easy to identify products that meet your personal criteria, whether you’re focused on ingredient health and safety; carbon emissions and reduction; agriculture and how products are grown and processed; and so forth. You can see how this approach respects the buyer’s need for both simplicity and depth. And Amazon is strengthening their bottom-line in the process, driving double digit increases in both page discovery and sales with their badge program. That’s how you align purpose and profit. When companies properly leverage data to enable people to shop with purpose by aligning purchases with beliefs, it creates a more personalized shopping experience that keeps the customer coming back. In today’s market where there are endless options and instant access to information, loyalty is paramount. After all, if you don’t have repeat customers, you don’t have a business. So the choice is clear: Embrace transparency or risk irrelevance. The future of retail belongs to those who empower consumers with the truth. Tell them exactly what’s in a claim. Kimberly Shenk is cofounder and CEO of Novi Connect. View the full article

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The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. Retail is at a turning point. AI is no longer a futuristic idea or marketing buzzword—it’s a business necessity. Consumers expect intelligent, seamless, and personalized experiences at every touchpoint. The brands that deliver on those expectations will win. Those that don’t will fall behind. Still, when I talk with retail leaders, I hear the same concerns again and again: How do we make AI feel natural, not robotic? Can it really drive sales—or is it just a cost-cutting tool? How do we integrate AI without blowing up our current operations? And beyond the contact center, where else can AI have real impact? These aren’t just passing questions. They’re real blockers, slowing down progress. That’s why we launched an AI Lab webinar series, and write articles like this to get information out publicly with practical, business-first answers. AI needs to do more than automate Retailers have dipped their toes into AI—automated chatbots, product recommendations, predictive analytics—but too often, these tools operate in silos. That leads to clunky experiences and limited impact. The mindset is shifting. It’s no longer just about efficiency. It’s about impact. AI shouldn’t only reduce costs. It should increase engagement, drive revenue, and build customer loyalty. Here are three principles we’ve seen drive real success: 1. AI should sell, not just support Traditionally, retail AI has played defense—handling order tracking, return policies, and FAQs. But it’s time to put AI on offense. Think of guided selling: AI that acts like a smart associate, asking about customer preferences, budget, or style—and responding naturally. It’s the digital equivalent of a great in-store experience. One example: A luxury jewelry brand used conversational AI to recommend add-ons and upgrades based on a customer’s past purchases. The result? A 30% boost in upsells—with zero human agent involvement. The takeaway: AI can drive conversions and revenue. It just needs to be designed with that goal in mind. 2. Proactive > reactive Most AI waits for customers to initiate the conversation. That’s a missed opportunity. Take cart abandonment. Nearly 70% of online carts are abandoned before checkout. AI can spot hesitation—lingering on the checkout page, revisiting items—and respond in real time with: A one-click checkout to reduce friction A last-minute incentive A helpful AI assistant offering answers AI shouldn’t just respond when customers get stuck. It should help them move forward. 3. AI that works with people, not instead of them The most successful retailers don’t replace humans—they empower them. Think about frontline staff. AI can handle the repetitive stuff so humans can focus on high-value interactions: complex purchases, emotional moments, loyalty-building conversations. It also works the other way. Human agents generate valuable data—about buying habits, objections, preferences—that AI can learn from and use to personalize future experiences. That’s the real win: a human-AI partnership that gets smarter over time and drives better outcomes across the customer lifecycle. Rethink the AI roadmap Too often, brands start with customer support because it feels “safe.” But forward-thinking leaders are broadening their lens—and seeing greater return. We’re working with retailers that are embedding AI into every stage of the customer journey: Pre-purchase: Digital consultations, guided product discovery, preference-based recommendations In-purchase: Smart upsell suggestions, checkout support, frictionless payments Post-purchase: Delivery updates, service requests, loyalty rewards, re-engagement And here’s the kicker: these touchpoints don’t need to be siloed. The right AI platform can stitch them together into a seamless, personalized journey. What makes the difference Three things separate retailers who are winning with AI from those still spinning their wheels: Start with the customer, not the tech. Don’t ask, “What can this tool do?” Ask, “Where is the customer getting stuck—and how can we help them move forward?” Design for outcomes. If your AI project doesn’t tie back to a business metric—conversion, lifetime value, customer satisfaction (CSAT)—you’re flying blind. Make it measurable. Set clear goals. Track impact. Optimize based on results. This isn’t about proving AI works in general—it’s about proving it works for your brand. Final thought: Innovation without disruption AI doesn’t need to blow up your tech stack. It should integrate with your existing systems, layer in intelligence, and get smarter over time. We call it “innovation without disruption.” You don’t have to rip and replace. You just have to start with the right mindset—and the right partner. AI in retail isn’t just about answering questions. It’s about asking the right ones—and making sure your tech stack is ready to answer them in ways that actually move the business forward. John Sabino is CEO of LivePerson. View the full article