A la Bourse de New York, le 10 juin 2025. RICHARD DREW / AP En 1973, Burton Malkiel, un professeur à l’université Stanford (Californie), avait fait polémique en affirmant qu’un singe avec un bandeau sur les yeux lançant des fléchettes sur les pages d’un journal financier sélectionnerait un portefeuille d’actions « aussi bon » que celui soigneusement choisi par des experts. Le test a été tenté. Il s’avéra que M. Malkiel avait tort : les singes étaient meilleurs. Cinquante ans après, la question désormais est de savoir si les robots peuvent battre les loups de Wall Street. Lire aussi | Article réservé à nos abonnés Dans les banques, la marche à pas comptés vers l’IA générative Stanford a la réponse. Un article paru lundi 9 juin sur le site de l’université relate que des chercheurs ont entraîné sur des données de marchés allant de 1980 à 1990 un modèle prédictif d’investissement. Puis, ils lui ont demandé de recomposer les portefeuilles de 3 300 fonds communs de placement en actions américaines entre 1990 et 2020. Verdict : l’intelligence artificielle (IA) a écrasé 93 % des gérants, obtenant des performances en moyenne six fois supérieures. Pas étonnant que l’industrie de la gestion d’actifs mette les bouchées doubles sur la technologie. Selon Bloomberg, BlackRock a révélé, jeudi 12 juin, avoir bâti une « IA analyste » sur les actions, baptisée « Asimov », du nom de l’auteur de science-fiction fasciné par la relation entre l’humain et les robots. « Pendant que tout le monde dort la nuit, ces agents d’intelligence artificielle balayent les notes de recherche, les dépôts de documents des entreprises, les courriels », a expliqué Rob Goldstein, le responsable des opérations du premier gestionnaire d’actifs mondial. Il vous reste 41.24% de cet article à lire. La suite est réservée aux abonnés.

Hi, friends! Welcome to Installer No. 87, your guide to the best and Verge-iest stuff in the world. (If you’re new here, welcome, happy It’s Officially Too Hot Now Week, and also you can read all the old editions at the Installer homepage.) This week, I’ve been reading about Sabrina Carpenter and Khaby Lame and intimacy coordinators, finally making a dent in Barbarians at the Gate, watching all the Ben Schwartz and Friends I can find on YouTube, planning my days with the new Finalist beta, recklessly installing all the Apple developer betas after WWDC, thoroughly enjoying Dakota Johnson’s current press tour, and trying to clear all my inboxes before I go on parental leave. It’s… going.I also have for you a much-awaited new browser, a surprise update to a great photo editor, a neat trailer for a meh-looking movie, a classic Steve Jobs speech, and much more. Slightly shorter issue this week, sorry; there’s just a lot going on, but I didn’t want to leave y’all hanging entirely. Oh, and: we’ll be off next week, for Juneteenth, vacation, and general summer chaos reasons. We’ll be back in full force after that, though! Let’s get into it.(As always, the best part of Installer is your ideas and tips. What do you want to know more about? What awesome tricks do you know that everyone else should? What app should everyone be using? Tell me everything: installer@theverge.com. And if you know someone else who might enjoy Installer, forward it to them and tell them to subscribe here.)The DropDia. I know there are a lot of Arc fans here in the Installerverse, and I know you, like me, will have a lot of feelings about the company’s new and extremely AI-focused browser. Personally, I don’t see leaving Arc anytime soon, but there are some really fascinating ideas (and nice design touches) in Dia already. Snapseed 3.0. I completely forgot Snapseed even existed, and now here’s a really nice update with a bunch of new editing tools and a nice new redesign! As straightforward photo editors go, this is one of the better ones. The new version is only on iOS right now, but I assume it’s heading to Android shortly.“I Tried To Make Something In America.” I was first turned onto the story of the Smarter Scrubber by a great Search Engine episode, and this is a great companion to the story about what it really takes to bring manufacturing back to the US. And why it’s hard to justify.. That link, and the trailer, will only do anything for you if you have a newer iPhone. But even if you don’t care about the movie, the trailer — which actually buzzes in sync with the car’s rumbles and revs — is just really, really cool. Android 16. You can’t get the cool, colorful new look just yet or the desktop mode I am extremely excited about — there’s a lot of good stuff in Android 16 but most of it is coming later. Still, Live Updates look good, and there’s some helpful accessibility stuff, as well.The Infinite Machine Olto. I am such a sucker for any kind of futuristic-looking electric scooter, and this one really hits the sweet spot. Part moped, part e-bike, all Blade Runner vibes. If it wasn’t $3,500, then I would’ve probably ordered one already.The Fujifilm X-E5. I kept wondering why Fujifilm didn’t just make, like, a hundred different great-looking cameras at every imaginable price because everyone wants a camera this cool. Well, here we are! It’s a spin on the X100VI but with interchangeable lenses and a few power-user features. All my photographer friends are going to want this.Call Her Alex. I confess I’m no Call Her Daddy diehard, but I found this two-part doc on Alex Cooper really interesting. Cooper’s story is all about understanding people, the internet, and what it means to feel connected now. It’s all very low-stakes and somehow also existential? It’s only two parts, you should watch it.“Steve Jobs - 2005 Stanford Commencement Address.” For the 20th anniversary of Jobs’ famous (and genuinely fabulous) speech, the Steve Jobs Archive put together a big package of stories, notes, and other materials around the speech. Plus, a newly high-def version of the video. This one’s always worth the 15 minutes.Dune: Awakening. Dune has ascended to the rare territory of “I will check out anything from this franchise, ever, no questions asked.” This game is big on open-world survival and ornithopters, too, so it’s even more my kind of thing. And it’s apparently punishingly difficult in spots.CrowdsourcedHere’s what the Installer community is into this week. I want to know what you’re into right now as well! Email installer@theverge.com or message me on Signal — @davidpierce.11 — with your recommendations for anything and everything, and we’ll feature some of our favorites here every week. For even more great recommendations, check out the replies to this post on Threads and this post on Bluesky.“I had tried the paper planner in the leather Paper Republic journal but since have moved onto the Remarkable Paper Pro color e-ink device which takes everything you like about paper but makes it editable and color coded. Combine this with a Remarkable planner in PDF format off of Etsy and you are golden.” — Jason“I started reading a manga series from content creator Cory Kenshin called Monsters We Make. So far, I love it. Already preordered Vol. 2.” — Rob“I recently went down the third party controller rabbit hole after my trusty adapted Xbox One controller finally kicked the bucket, and I wanted something I could use across my PC, phone, handheld, Switch, etc. I’ve been playing with the GameSir Cyclone 2 for a few weeks, and it feels really deluxe. The thumbsticks are impossibly smooth and accurate thanks to its TMR joysticks. The face buttons took a second for my brain to adjust to; the short travel distance initially registered as mushy, but once I stopped trying to pound the buttons like I was at the arcade, I found the subtle mechanical click super satisfying.” — Sam“The Apple TV Plus miniseries Long Way Home. It’s Ewan McGregor and Charley Boorman’s fourth Long Way series. This time they are touring some European countries on vintage bikes that they fixed, and it’s such a light-hearted show from two really down to earth humans. Connecting with other people in different cultures and seeing their journey is such a treat!” — Esmael“Podcast recommendation: Devil and the Deep Blue Sea by Christianity Today. A deep dive into the Satanic Panic of the 80’s and 90’s.” — Drew“Splatoon 3 (the free Switch 2 update) and the new How to Train Your Dragon.” — Aaron“I can’t put Mario Kart World down. When I get tired of the intense Knockout Tour mode I go to Free Roam and try to knock out P-Switch challenges, some of which are really tough! I’m obsessed.” — Dave“Fable, a cool app for finding books with virtual book clubs. It’s the closest to a more cozy online bookstore with more honest reviews. I just wish you could click on the author’s name to see their other books.” — Astrid“This is the Summer Games Fest week (formerly E3, RIP) and there are a TON of game demos to try out on Steam. One that has caught my attention / play time the most is Wildgate. It’s a team based spaceship shooter where ship crews battle and try to escape with a powerful artifact.” — Sean“Battlefront 2 is back for some reason. Still looks great.” — IanSigning offI have long been fascinated by weather forecasting. I recommend Andrew Blum’s book, The Weather Machine, to people all the time, as a way to understand both how we learned to predict the weather and why it’s a literally culture-changing thing to be able to do so. And if you want to make yourself so, so angry, there’s a whole chunk of Michael Lewis’s book, The Fifth Risk, about how a bunch of companies managed to basically privatize forecasts… based on government data. The weather is a huge business, an extremely powerful political force, and even more important to our way of life than we realize. And we’re really good at predicting the weather!I’ve also been hearing for years that weather forecasting is a perfect use for AI. It’s all about vast quantities of historical data, tiny fluctuations in readings, and finding patterns that often don’t want to be found. So, of course, as soon as I read my colleague Justine Calma’s story about a new Google project called Weather Lab, I spent the next hour poking through the data to see how well DeepMind managed to predict and track recent storms. It’s deeply wonky stuff, but it’s cool to see Big Tech trying to figure out Mother Nature — and almost getting it right. Almost.See you next week!See More:

Image by Andrew BrodheadResearchers have developed a novel device that literally spins away the clots that block blood flow to the brain and cause strokes.As Stanford explains in a blurb, the novel milli-spinner device may be able to save the lives of patients who experience "ischemic stroke" from brain stem clotting.Traditional clot removal, a process known as thrombectomy, generally uses a catheter that either vacuums up the blood blockage or uses a wire mesh to ensnare it — a procedure that's as rough and imprecise as it sounds. Conventional thrombectomy has a very low efficacy rate because of this imprecision, and the procedure can result in pieces of the clot breaking off and moving to more difficult-to-reach regions.Thrombectomy via milli-spinner also enters the brain with a catheter, but instead of using a normal vacuum device, it employs a spinning tube outfitted with fins and slits that can suck up the clot much more meticulously.Stanford neuroimaging expert Jeremy Heit, who also coauthored a new paper about the device in the journal Nature, explained in the school's press release that the efficacy of the milli-spinner is "unbelievable.""For most cases, we’re more than doubling the efficacy of current technology, and for the toughest clots — which we’re only removing about 11 percent of the time with current devices — we’re getting the artery open on the first try 90 percent of the time," Heit said. "This is a sea-change technology that will drastically improve our ability to help people."Renee Zhao, the senior author of the Nature paper who teaches mechanical engineering at Stanford and creates what she calls "millirobots," said that conventional thrombectomies just aren't cutting it."With existing technology, there’s no way to reduce the size of the clot," Zhao said. "They rely on deforming and rupturing the clot to remove it.""What’s unique about the milli-spinner is that it applies compression and shear forces to shrink the entire clot," she continued, "dramatically reducing the volume without causing rupture."Indeed, as the team discovered, the device can cut and vacuum up to five percent of its original size."It works so well, for a wide range of clot compositions and sizes," Zhao said. "Even for tough... clots, which are impossible to treat with current technologies, our milli-spinner can treat them using this simple yet powerful mechanics concept to densify the fibrin network and shrink the clot."Though its main experimental use case is brain clot removal, Zhao is excited about its other uses, too."We’re exploring other biomedical applications for the milli-spinner design, and even possibilities beyond medicine," the engineer said. "There are some very exciting opportunities ahead."More on brains: The Microplastics in Your Brain May Be Causing Mental Health IssuesShare This Article

Navigating the dense urban canyons of cities like San Francisco or New York can be a nightmare for GPS systems. The towering skyscrapers block and reflect satellite signals, leading to location errors of tens of meters. For you and me, that might mean a missed turn. But for an autonomous vehicle or a delivery robot, that level of imprecision is the difference between a successful mission and a costly failure. These machines require pinpoint accuracy to operate safely and efficiently. Addressing this critical challenge, researchers from the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland have introduced a groundbreaking new method for visual localization during CVPR 2025 Their new paper, “FG2: Fine-Grained Cross-View Localization by Fine-Grained Feature Matching,” presents a novel AI model that significantly enhances the ability of a ground-level system, like an autonomous car, to determine its exact position and orientation using only a camera and a corresponding aerial (or satellite) image. The new approach has demonstrated a remarkable 28% reduction in mean localization error compared to the previous state-of-the-art on a challenging public dataset. Key Takeaways: Superior Accuracy: The FG2 model reduces the average localization error by a significant 28% on the VIGOR cross-area test set, a challenging benchmark for this task. Human-like Intuition: Instead of relying on abstract descriptors, the model mimics human reasoning by matching fine-grained, semantically consistent features—like curbs, crosswalks, and buildings—between a ground-level photo and an aerial map. Enhanced Interpretability: The method allows researchers to “see” what the AI is “thinking” by visualizing exactly which features in the ground and aerial images are being matched, a major step forward from previous “black box” models. Weakly Supervised Learning: Remarkably, the model learns these complex and consistent feature matches without any direct labels for correspondences. It achieves this using only the final camera pose as a supervisory signal. Challenge: Seeing the World from Two Different Angles The core problem of cross-view localization is the dramatic difference in perspective between a street-level camera and an overhead satellite view. A building facade seen from the ground looks completely different from its rooftop signature in an aerial image. Existing methods have struggled with this. Some create a general “descriptor” for the entire scene, but this is an abstract approach that doesn’t mirror how humans naturally localize themselves by spotting specific landmarks. Other methods transform the ground image into a Bird’s-Eye-View (BEV) but are often limited to the ground plane, ignoring crucial vertical structures like buildings. FG2: Matching Fine-Grained Features The EPFL team’s FG2 method introduces a more intuitive and effective process. It aligns two sets of points: one generated from the ground-level image and another sampled from the aerial map. Here’s a breakdown of their innovative pipeline: Mapping to 3D: The process begins by taking the features from the ground-level image and lifting them into a 3D point cloud centered around the camera. This creates a 3D representation of the immediate environment. Smart Pooling to BEV: This is where the magic happens. Instead of simply flattening the 3D data, the model learns to intelligently select the most important features along the vertical (height) dimension for each point. It essentially asks, “For this spot on the map, is the ground-level road marking more important, or is the edge of that building’s roof the better landmark?” This selection process is crucial, as it allows the model to correctly associate features like building facades with their corresponding rooftops in the aerial view. Feature Matching and Pose Estimation: Once both the ground and aerial views are represented as 2D point planes with rich feature descriptors, the model computes the similarity between them. It then samples a sparse set of the most confident matches and uses a classic geometric algorithm called Procrustes alignment to calculate the precise 3-DoF (x, y, and yaw) pose. Unprecedented Performance and Interpretability The results speak for themselves. On the challenging VIGOR dataset, which includes images from different cities in its cross-area test, FG2 reduced the mean localization error by 28% compared to the previous best method. It also demonstrated superior generalization capabilities on the KITTI dataset, a staple in autonomous driving research. Perhaps more importantly, the FG2 model offers a new level of transparency. By visualizing the matched points, the researchers showed that the model learns semantically consistent correspondences without being explicitly told to. For example, the system correctly matches zebra crossings, road markings, and even building facades in the ground view to their corresponding locations on the aerial map. This interpretability is extremenly valuable for building trust in safety-critical autonomous systems. “A Clearer Path” for Autonomous Navigation The FG2 method represents a significant leap forward in fine-grained visual localization. By developing a model that intelligently selects and matches features in a way that mirrors human intuition, the EPFL researchers have not only shattered previous accuracy records but also made the decision-making process of the AI more interpretable. This work paves the way for more robust and reliable navigation systems for autonomous vehicles, drones, and robots, bringing us one step closer to a future where machines can confidently navigate our world, even when GPS fails them. Check out the Paper. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 100k+ ML SubReddit and Subscribe to our Newsletter. Jean-marc MommessinJean-marc is a successful AI business executive .He leads and accelerates growth for AI powered solutions and started a computer vision company in 2006. He is a recognized speaker at AI conferences and has an MBA from Stanford.Jean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/AI-Generated Ad Created with Google’s Veo3 Airs During NBA Finals, Slashing Production Costs by 95%Jean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/Highlighted at CVPR 2025: Google DeepMind’s ‘Motion Prompting’ Paper Unlocks Granular Video ControlJean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/Snowflake Charts New AI Territory: Cortex AISQL & Snowflake Intelligence Poised to Reshape Data AnalyticsJean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/Exclusive Talk: Joey Conway of NVIDIA on Llama Nemotron Ultra and Open Source Models

Although the US unemployment rate held steady at 4.2% in May with 139,000 jobs added to the US workforce, nearly 100,000 layoffs were also announced — up 47% from last year, according to new data from the US Bureau of Labor Statistics and others. Tech and federal cuts led the way in layoffs, driven by economic pressure, programmatic firings and AI-driven shifts in workforce needs, according to outplacement firm Challenger, Gray & Christmas. Technology remains a top sector for cuts amid ongoing disruptions, according to the firm’s data. In May, tech companies announced 10,598 layoffs, bringing the 2025 total to 74,716; that’s up 35% from 55,207 at the same time last year. “Tariffs, funding cuts, consumer spending, and overall economic pessimism are putting intense pressure on companies’ workforces. Companies are spending less, slowing hiring, and sending layoff notices,” Andrew Challenger, senior vice president of Challenger, Gray & Christmas, said in a statement. Uneasiness continues to weigh on tech hiring, according to CompTIA, a provider of IT training and certification products. The unemployment rate for tech jobs in May was 3.4%, roughly in line with April’s 3.5%, CompTIA data showed. The tech unemployment rate continues to sit below the national rate. CompTIA Tech sector companies added a modest 1,571 net new employees in May, analysis of the BLS jobs report by CompTIA showed. Job growth in cloud infrastructure and tech services was offset by reductions in the telecommunications sector. Tech employment across the broader economy declined by an estimated 131,000 positions. “With prior month employment gains, tech occupation employment remains in the positive for the year,” CompTIA said. “It is undoubtedly a challenging time for employers and job seekers facing uncertainty on multiple fronts,” said Tim Herbert, CompTIA’s chief research officer. “At the same time, it requires taking a measured approach given the data continues to hold up reasonably well.” One bright spot for tech hires in May was the finance and insurance industry, which collectively saw a 21% increase in new tech job postings; new tech job openings also rose by 16% in the retail sector, according to CompTIA. Even so, tech layoffs have continued as AI adoption soars and economic pressures drive a major shift toward new roles and skills in the workforce. “AI isn’t replacing jobs,” said Kye Mitchell, president of tech workforce staffing firm Experis US. “It’s fundamentally redefining how work gets done. We’re seeing AI augment skillsets and make professionals more capable, faster, and able to focus on higher-value work.” Technology only displaces jobs when about 80% of tasks can be automated — and AI isn’t close to doing that, said Mitchell. Right now, AI is enhancing skills, boosting productivity, and freeing up time for higher-value work. Hiring for AI positions and those requiring AI skills continues to grow rapidly, according to a CompTIA analysis of data from Lightcast and Stanford University study. CompTIA found that employer job postings related to AI are up 117% year-to-date year-over-year. Challenger, Gray & Christmas Skills-based hiring remains core to many employers’ recruiting strategies. About half of all tech job postings did not specify a need for a four-year academic degree, seeking instead a combination of work experience, training and industry-recognized certification, according to CompTIA’s and other data. Even so, employers are hesitant to hire. “Economic uncertainty is absolutely creating a cautious hiring environment, but it’s more complex than tariffs alone,” Mitchell said. “Our data shows employers adopting a ‘wait and watch’ stance as they monitor economic signals, with job openings down 11% year-over-year.” Still, the tech job market is adjusting as AI adoption grows. AI skill mentions in job postings fell 10% in May but are still up 10% for the year, showing steady demand, Mitchell said. The tech industry had been nearly bullet-proof from mass layoffs prior to 2022. After a hiring surge between 2020 and 2022 to meet digitization efforts as more people worked from home, the market shifted and began slashing jobs to readjust to the new reality. Tech companies such Google, Amazon, Meta (Facebook) and others laid off tens of thousands of workers  as an adjustment to over-hiring during the COVID-19 pandemic. In 2023 alone, 1,186 tech companies laid off about 262,682 staff, compared to 164,969 layoffs in 2022. In January 2024, job cuts leaped 136% over December and hit a 10-month high, according to Challenger, Gray & Christmas. While the labor market remained steady, there are signs that hiring across the board is softening. Open job postings fell 7% this year and new postings dropped 16% in the past month — the first full contraction of 2025. Year-to-date, new postings are flat compared to last year, according to Ger Doyle, ManpowerGroup’s regional president for North America. Doyle, however, was optimistic. “This is a chill, not a freeze,” he said. “Workers and employers are holding steady, awaiting clarity.” For example, he said, project management roles are up 483% year-over-year, and as the broader outlook improves, a rebound could follow, he added.  Demand for data roles is surging as companies shift from AI experiments to execution. Database architect postings are up 2,140% year-over-year, with data scientist postings up 280% — clear signs of companies building the backbone for an AI-driven future, Experis’s data showed. “This shift is also reshaping how talent enters the industry. Entry-level opportunities are becoming more limited, making it harder for recent graduates to gain a foothold,” Mitchell said. “For those looking to break in, deep analytical and technical skills are no longer optional.”