The car world is filled with designers still obsessed with shoehorning sex into their rides. Slate went a different route, and it's why people are smitten with the charming electric pickup. Tisha Johnson is a rare anomaly in the car world: a design leader for an automaker who is not a man. In a resolutely testosterone-fueled industry where, traditionally, women have seemingly been given positions of authority in design labs as long as they focus on interiors, colors, or material selections, very few have been afforded free rein on the most important visual element of the car, the exterior, let alone promoted to run the entire aesthetic show. As head of design at Slate, this gender-specific fact might be why the world has fallen in love with the Jeff Bezos-backed truck . Casual observers might put the Slate EV's popularity down to its low price. Starting at $24,950, the Slate arriving later this year won't just be the cheapest EV on the US market; it will also be the cheapest pickup truck of any power flavor.

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen How to create flyers with AI that people won't hate: 8 tips (and prompts) that really work Most AI flyers are still a mess, but the right prompts can make all the difference. AI can make decent flyers, but most still aren't great. Clear prompts and limits can produce much better AI flyers. A designer is best, but these tips work when that's not an option. I personally don't love them, and I can instantly spot one.

Robots walking down the street, surrounded by astounded onlookers, is an increasingly common sight. But these machines aren't yet the do-it-all assistants you'd want working in a kitchen or factory, and a major bottleneck is data. Much like humans, robots learn best by experience. The challenge is that it's labor-intensive and time-consuming to physically teach these machines so many actions across different settings. "One natural idea is to use simulation as a training ground. While there has been significant progress over the last few years in the physics engines that power robotics simulators, one of the remaining challenges has been creating sufficiently rich and diverse simulation content to capture the complexity of the real world," says Russ Tedrake, the Toyota Professor of Electrical Engineering and Computer Science (EECS), Aeronautics and Astronautics, and Mechanical Engineering at MIT, and a principal investigator at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL).

Richard Sutton's "Bitter Lesson" is usually read as a warning against building too much human knowledge into AI systems. Over the long run, the methods that win are not the ones that encode our clever intuition most directly, but the ones that scale: search, learning, and other general methods that can absorb more compute and data. We take a general architecture, expose it to massive data, and train it with a simple self-supervised objective. Language models predict the next token. Vision models reconstruct masked patches, align views, or match teacher representations.

IBM hails new'block of flats' design breakthrough for ultra tiny chips Image caption, IBM's new sub-1 nm chip crams almost 100 billion transistors onto a surface the size of a fingernail IBM has unveiled a new chip design which it says could enable manufacturers to cram 100 billion transistors on a silicon chip the size of a fingernail. The current industry-standard size for chips, measured in a the unit of nanometres - a billionth of a metre and the size of a few atoms - is around two nanometres (nm). But IBM claims its new chip tech is the equivalent of around 0.7nm, which may make it the world's first known chip technology below 1nm. However, it will be several years before the chip tech could be ready to go into production. The firm claims in tests, its prototype performed 50% better than its own 2nm chip and was 70% more energy efficient.

Is the Ferrari Luce's Design Really That Bad? 3 Italian Auto Experts Weigh In The first electric Ferrari is already this year's most divisive car. We asked three Italian auto industry professionals to explain where the EV's design makes sense, and where it doesn't add up. The Ferrari Luce, the first electric vehicle in the brand's history, has generated heated discussion online, as comments and opinions about the design continue to bounce around the web. The Luce, an electric sedan with a $650,000 price tag that Ferrari presented with pomp and circumstance at the Quirinale in Rome on Monday, has paid dearly for its coming out from behind the curtain. Since Monday, the automaker has been suffering an avalanche of complaints and skepticism about the Luce.

Best Power Banks Best Smart Rings Routers vs. Modems Choose the Right Laptop Smart Sprinklers Deals Delivered But This Is Why It's Heartbreaking Designed by Jony Ive and a host of ex-Cupertino colleagues, the Luce shows us what might have been had Apple made good on its $10 billion bet. You know things are bad when the Pope gets involved . No doubt reeling from a launch that somehow went down even worse than Ferrari itself anticipated, the Italian carmaker sought to get the endorsement of none other than His Holiness Pope Leo XIV for its first EV, the Luce. Guided by Ferrari chairman John Elkann and senior Ferrari executives, in a hillside town about 15 miles southeast of Rome, the pontiff sat in the driver's seat and listened patiently as test driver Raffaele De Simone explained the vehicle's controls and driving modes as if he really was speaking to a man clearly in the market for a 1,000-horsepower electric car capable of hitting 62 mph in 2.5 seconds. Meanwhile, as Pope Leo was no doubt pondering how the Luce could boast one of the largest batteries in any production EV yet still only manage a maximum 329 miles, or how an accelerometer on the rear axle somehow worked like a guitar pickup to create in-cabin sound like an "instrument," the market was speaking.

Meet the UK's very own LeBron James... but not as you know it Look out LeBron James and Michael Jordan, there's a new basketball champ around. But it was made in Lisburn rather than Los Angeles or Chicago. The name 25416 may not appear on many replica vests, but it can shoot hoops like no-one else. And the basketball-playing robot won a school in Lisburn first prize at the UK-wide First Tech Challenge robotics competition. The team of sixth-formers from Friends' School came top of 48 schools from across the UK at the competition held in London's Copper Box Arena. Going down and working on it with my friends is honestly one of the highlights of my last year in school, he said.

Off-policy evaluation (OPE) estimates the value of a target treatment policy (e.g., a recommender system) using data collected by a different logging policy. It enables high-stakes experimentation without live deployment, yet in practice accuracy depends heavily on the logging policy used to collect data for computing the estimate. We study how to design logging policies that minimize OPE error for given target policies. We characterize a fundamental reward-coverage tradeoff: concentrating probability mass on high-reward actions reduces variance but risks missing signal on actions the target policy may take. We propose a unifying framework for logging policy design and derive optimal policies in canonical informational regimes where the target policy and reward distribution are (i) known, (ii) unknown, and (iii) partially known through priors or noisy estimates at logging time. Our results provide actionable guidance for firms choosing among multiple candidate recommendation systems. We demonstrate the importance of treatment selection when gathering data for OPE, and describe theoretically optimal approaches when this is a firm's primary objective. We also distill practical design principles for selecting logging policies when operational constraints prevent implementing the theoretical optimum.

Matt Keightley in his 2015 Chelsea garden, designed for Prince Harry. This year he is launching an AI app that has'designed' three full-size gardens for the show. Matt Keightley in his 2015 Chelsea garden, designed for Prince Harry. This year he is launching an AI app that has'designed' three full-size gardens for the show. Wed 13 May 2026 01.00 EDTLast modified on Wed 13 May 2026 01.01 EDT With glasses of champagne sipped among the peonies, Chelsea flower show is generally a friendly and genteel occasion.