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.

Classical design theory treats the type of an object as a given: the designer decides in advance that this will be a cup, then optimizes its parameters. This paper argues that object type is not a presupposition but an inference, something that can be determined from physical data and functional requirements jointly. We call this problem requirement-steered interface type inference and show that it is inexpressible within existing design frameworks. This paper makes two contributions that are jointly necessary and individually incomplete. The first is the problem itself, which classical design cannot pose because it presupposes the very thing our problem seeks to determine. The second is C-DMBD, a constrained extension of the Dynamic Markov Blanket Detection algorithm, which makes requirement-steered inference computationally tractable. Drawing on the free-energy principle and active inference, established frameworks in theoretical neuroscience and Bayesian mechanics, we model a product's surface as a Markov blanket: the minimal boundary through which all causal exchange between object and environment must pass. Different blanket structures correspond to different object types; different parameterizations of the same structure correspond to different functional modes of the same type. This paper is a proof of concept and a theoretical proposal. It reframes design as inference rather than optimization, and as a relation between generative models rather than a specification of parameters.

The streamline shape is still more aerodynamic than most cars today. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. In 1930, English engineer Sir Dennis Burney told Popular Science that his teardrop-shaped car would cut fuel consumption in half. Breakthroughs, discoveries, and DIY tips sent six days a week. From the start, cars were built wrong. At least, that's what Chrysler's head of automotive research, Carl Breer, thought in 1930. Automobiles had never been built to be aerodynamic, he posited, and he was right.

A specialized glass layer could make tomorrow's computers faster and more energy efficient. An early version of the glass substrate developed by Absolics. Human-made glass is thousands of years old. But it's now poised to find its way into the AI chips used in the world's newest and largest data centers. This year, a South Korean company called Absolics is planning to start commercial production of special glass panels designed to make next-generation computing hardware more powerful and energy efficient. Other companies, including Intel, are also pushing forward in this area.

Hosted by Eleanor Drage and Kerry McInerney, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. In this episode, we talk to Tomasz Hollanek, researcher at the Leverhulme Centre for the Future of Intelligence at the University of Cambridge. Tomasz argues that design is central to AI ethics and explores the role designers should play in shaping ethical AI systems. The conversation examines the importance of AI literacy, the responsibilities of journalists in reporting on AI technologies, and how design choices embed social and political values into AI. Together, we reflect on how critical design can challenge existing power dynamics and open up more just and inclusive approaches to human-AI interaction.