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  1. The robots won’t be replacing us, but we will increasingly be working side-by-side with artificial intelligence tools that can then learn from our human expertise. That’s one conclusion of researchers and engineers who are applying AI to the physical world in transformative ways, from autonomous vehicles to microscopes for detecting malaria to the design of wholly new materials. And there’s a balance to be struck between automation and human expertise, according to K.T. Ramesh, the Alonzo G. Decker Jr. professor of science of and engineering at Johns Hopkins University and a senior advisor to the university’s president for AI. “We can develop autonomous resea…

  2. The boom in data center construction is taking up much of the supply of high-tech components, especially processor and memory chips. This demand is squeezing consumer device makers, which are having trouble acquiring enough chips. This is happening even though data center servers and smartphones use different types of chips. The key distinction between consumer electronics and data centers is what they need chips to be optimized for. Smartphones and PCs require low power use, thermal efficiency, and tight integration. Data centers that run AI systems such as large language models, or LLMs, require maximum compute power, memory bandwidth, and storage throughput. To…

  3. Every time you ask ChatGPT to draft an email, or prompt an AI assistant to help you decide which refrigerator to buy—somewhere, a data center hums to life to make it happen. These facilities, which can span the size of a small city, are the unglamorous physical infrastructure behind the AI revolution. They’re cavernous buildings packed with servers, cooled by industrial systems, drawing power at a scale that strains local electrical grids. What almost no one talks about is the human beings building them. To construct a single data center, developers source millions of tons of concrete, steel, copper, lithium, and critical metals from supply chains that stretch across …

  4. As marketing leaders, we don’t wake up thinking about algorithms. We wake up thinking about growth. For CMOs, the job has always been the same: drive real business impact, improve ROI, and prove—repeatedly—that marketing is a growth engine, not a cost center. Long before generative AI entered the conversation, marketing leaders were under pressure to connect activity to revenue, align tightly with sales, and make performance visible. The pressure to quantify value didn’t start with AI. It started when the business demanded proof. What has changed is the speed and precision with which we can now deliver that proof. AI ISN’T REINVENTING MARKETING. IT’S REWIRING …

  5. A few months ago, I walked into the office of one of our customers, a publicly traded vertical software company with tens of thousands of small business customers. I expected to meet a traditional support team with rows of agents on the phones, sitting at computers triaging tickets. Instead, it looked more like a control room. There were specialists monitoring dashboards, tuning AI behavior, debugging API failures, and iterating on knowledge workflows. One team member who had started their career handling customer questions over chat and email (resetting passwords, explaining features, troubleshooting one-off issues, and escalating bugs) was now writing Python scripts…

  6. Layoffs rose sharply in March, and a quarter of these job losses were due to AI. Job cuts rose about 25% in March reaching 60,620 up from 48,307 cuts the month before. The new data comes from outplacement and executive coaching firm Challenger, Gray & Christmas, who released the report on Thursday. While cuts could be seen across industries, more than 52,000 tech jobs have been cut so far this year with 18,720 happening last month. Reductions took place at major technology companies like Meta, Oracle, Block, and more. However, the report explained that the number was driven up significantly by the workforce reduction at Dell Technologies (DELL), making the t…

  7. Daniel Kokotajlo predicted the end of the world would happen in April 2027. In “AI 2027” — a document outlining the impending impacts of AI, published in April 2025 — the former OpenAI employee and several peers announced that by April 2027, unchecked AI development would lead to superintelligence and consequently destroy humanity. The authors, however are going back on their predictions. Now, Kokotajlo forecasts superintelligence will land in 2034, but he doesn’t know if and when AI will destroy humanity. In “AI 2027,” Kokotajlo argued that superintelligence will emerge through “fully autonomous coding,” enabling AI systems to drive their own development. The r…

  8. When David Mesfin was producing his documentary on Black surfing culture, Wade in the Water, back in 2023, he had a problem. Like millions of other people since ChatGPT and other GenAI tools emerged in late 2022, Mesfin was experimenting and using these tools to generate imagery for the film. “But the results were always the same: white surfers with darkened skin,” says Mesfin, a creative director at ad agency Innocean. “It was a clear sign that these systems weren’t built with us in mind. That moment made it impossible to ignore how deeply bias is embedded in the technology.” This week, sparked by that moment, Mesfin and his colleagues have launched “Breaking B…

  9. From my earliest days as a journalist, I’ve always prized my dictaphone. It sounds quaint now, but I actually remember excitedly keeping up with advancements in the field. Sony’s ICD-TX50 was a particular revelation for me in 2012, with its tiny OLED display and world’s-thinnest 6.4mm frame. There was no sleeker way to show up to Tokyo press conferences. In recent years, though, my dictaphone collection has taken on a new, less physical form. Google’s Pixel phones have been a revelation for journalists, offering real-time, on-device transcription through the Recorder app. I’ve often found myself bringing a Pixel along to a press event even if I wasn’t actively using i…

  10. While companies cram artificial intelligence features you never asked for into their apps, Domino’s seems to have found a valid use case for the technology: more accurate tracking of when your pizza will be ready. When Domino’s launched its pizza tracker in 2008, it was a marvel of UX. The tracker gave customers a lens into when their pizza would be ready through a simple interface that lit up as the pizza progressed from ordered to baked to delivered. The tool turned Domino’s into a tech company, and inspired industries (and governments) to adopt the same UX for their own needs. Now, Domino’s made the biggest update to its pizza tracker in years. The new tracke…

  11. There’s a scene in Office Space where Peter sits across from two consultants during a company downsizing. They ask him, “What would you say you do here?” He hesitates, smirks, and admits he only works about 15 minutes a week. The rest of the time, he’s pretending. It was comedy in 1999. It’s confession now. That question has come back to us. For years, we filled our calendars, stayed visible, and kept the machine moving. Our worth was measured in hours, output, and presence. It had to be. Humans were the system, and the system required us to keep it running. We didn’t question it because that was how things got done. AI has changed that. It can now do many…

  12. Human skills fall into three major buckets: physical, intellectual, and emotional. Of these, the last two are critical differentiators of talent across all knowledge economy jobs. When it comes to intellectual skills, such as learning ability, a century of scientific evidence reveals that this trait is the most consistent predictor of job performance and career success across all occupations. Why? Because it predicts how fast and well you can learn, reason, and solve problems, which basically matters in every job. That said, intellectual skills are clearly not enough to do well in your job or career. In fact, most jobs will also require you to understand, influenc…

  13. A new study out Wednesday in the journal Nature from the University of California, Berkeley found that women are systematically presented as younger than men online and by artificial intelligence—based on an analysis of 1.4 million online images and videos, plus nine large language models trained on billions of words. Researchers looked at content from Google, Wikipedia, IMDb, Flickr, and YouTube, and major large language models including GPT2, and found women consistently appeared younger than men across 3,495 occupational and social categories. (Note: It’s possible that filters on videos and women’s makeup may be adding to this age-related gender bias in visual cont…

  14. In January, Elon Musk’s artificial intelligence startup, xAI, announced that it would use its chatbot to develop an AI tutoring system for more than a million students in El Salvador. The announcement came on the heels of similar ones from OpenAI, which is connecting students in Kazakhstan with its ChatGPT Edu services, and from Microsoft, which is similarly equipping students and teachers in the United Arab Emirates with AI-based tools and training. While other countries are executing on national infrastructure projects for the AI era and treating it as an economic imperative, here in the United States, we can’t seem to move past a narrative of how AI makes it easier…

  15. Almost 10 years ago, physician and data scientist Dr. Ruben Amarasingham founded Pieces Technologies in Dallas with a clear goal: use artificial intelligence to make clinical work lighter, not heavier. At a time when much of healthcare AI focused on prediction and automation, Pieces concentrated on something harder to quantify but more consequential—how clinicians actually think, document, and make decisions inside busy hospital workflows. That focus helped Pieces gain traction with health systems looking for AI that could assist with documentation, coordination, and decision-making without disrupting care. But as hospitals began relying more heavily on AI for diagnos…

  16. According to new research from Whop, a marketplace for digital products, one in three Gen Z consumers now make purchasing decisions based on recommendations from AI-generated influencers. The report gathered survey data from 2,001 Americans 12-to-27 years old and found the trend particularly strong among college-aged consumers. Nearly half of 19-to-21 year olds follow AI influencers, with 47% of young men following these accounts, compared to under 40% of women. While many have argued that AI influencers lack the authenticity needed to sell products, that might not matter—especially to Gen Z. Authenticity vs reach Previous research backs this up. Nearly h…

  17. Spending on AI infrastructure is now contributing more to U.S. GDP growth than the entire consumer economy, according to new data from the Bureau of Economic Analysis. The comparison, which was posted to Twitter (X) by economist Heather Long on Monday, suggests that hype may not be the only thing propping up the high stock prices and valuations of AI companies such as Nvidia and OpenAI. Here, “consumption” means consumer spending on goods and services for personal use, which traditionally contributes about 70% of U.S. gross domestic product. “AI Spending” means business investment in software and information processing equipment, including data center construction, c…

  18. Most of the executive teams I work with have been investing in AI for a few years. The ones who are frustrated are not the skeptics. They are the believers whose programs have not connected to the P&L. They have the pilots, the internal momentum, the board slide showing everything in flight. What they do not have is a clear line between that activity and business performance, and at this point in the AI cycle, that gap is no longer acceptable. I spent several years running AI at scale inside Kroger and its data science subsidiary 84.51°, where we processed millions of predictions per second across thousands of store locations. We measured work in margin, basket si…

  19. AI can do incredible things. So far, though, most of those things have been virtual. If you want a killer article for your bichon frise blog or an expertly crafted letter disputing a parking ticket you probably deserve, chatbots like ChatGPT and Gemini can deliver that. All those things are locked into the nebulous world of information, though. They’re helpful, but the products of today’s large language models (LLMs) and neural networks aren’t actually doing much of anything. AI’s silicon-bound status, however, is beginning to change. The tech is increasingly invading the real world. 2026 is the year that AI gets physical. And that shift has huge impl…

  20. There’s no shortage of inspiration for what to do with a part of the house that’s not quite looking its best. Interior design magazines and furniture blogs are stuffed with idealized bedrooms, and online vision boards make it easy to cast a dragnet over the myriad images of classy lounges or perfectly ordered home offices. But there’s always the unavoidable catch that while these images may be helpful references for how to rethink a room, they don’t actually represent your room. A new AI tool offers a more personalized alternative. Created by the online interior design service Havenly, it’s an app-based AI design assistant that takes user-submitted images of rooms and…

  21. Twenty-five years ago, Google unveiled Adwords, which pledged to enable advertisers “to quickly design a flexible program that best fits [their] online marketing goals and budget,” Google cofounder Larry Page said at the time. The principle was simple. AdWords allowed advertisers to purchase individualized, affordable keyword-based advertising that appears alongside search results used by hundreds of millions of people every day. That decision was a game changer for Google. Advertising now accounts for around three in every four dollars of revenue the company has made so far this year, growing 10% in the last year alone. The product, since renamed Google Ads, has …

  22. The U.S. military was able “to strike a blistering 1,000 targets in the first 24 hours of its attack on Iran” thanks in part to its use of artificial intelligence, according to The Washington Post. The military has used Claude, the AI tool from Anthropic, combined with Palantir’s Maven system, for real-time targeting and target prioritization in support of combat operations in Iran and Venezuela. While Claude is only a few years old, the U.S. military’s ability to use it, or any other AI, did not emerge overnight. The effective use of automated systems depends on extensive infrastructure and skilled personnel. It is only thanks to many decades of investment and experi…





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