logo
BMWs Will Look Very Different Very Soon

BMWs Will Look Very Different Very Soon

Motor 128-05-2025

BMW's next era of design starts with the iX3 electric SUV, which is scheduled to debut before the end of the year. But it won't be the only vehicle in the Bavarian brand's lineup to get the Neue Klasse look. According to Group design boss Adrian van Hooydonk, every BMW will have a 'Neue' face—and soon.
In an interview with
Autocar
, van Hooydonk said that BMW's new design language will roll out on every model. Even though it just debuted in 2023, the
5 Series
sedan will be the first vehicle to get the new look, although, as a facelift, it will remain on its current CLAR architecture. The 5 Series redesign will be followed by the X5, 2 Series, X2, 7 Series, and X7.
BMW M3 EV Rendering
"We will make sure that the form language that we are developing now—and starting this year at the IAA [Munich] with the first of the Neue Klasse vehicles—will be rolled out over the entire product portfolio, leaving no car behind," said van Hooydonk.
Product boss Bernd Körber reiterated van Hooydonk's statement, noting that the new design rollout won't take long. It will happen, "within three and a half years across the entire portfolio," Körber notes.
But don't worry, this doesn't mean every BMW will have the same cookie-cutter Neue Klasse look. Van Hooydonk confirmed that, while every BMW will have a familial resemblance, each model will have its "own distinct character traits."
BMW iX3 Rendering
Photo by: Motor1.com
BMW originally planned to limit the Neue Klasse design language to its EVs, but the company confirmed
back in October
that the design direction would make its way to gas models as well. Previewed by the Neue Klasse concept in 2023 and the Neue Klasse X crossover, BMW will likely ditch its massive kidney grille for a smoother front fascia and subtler design elements.
The Latest From BMW
BMW Has a 'Higher Demand' for the M5 Wagon in the US
This Beautiful BMW Wagon Is Actually Going Into Production
Source:
Autocar
Share this Story
Facebook
X
LinkedIn
Flipboard
Reddit
WhatsApp
E-Mail
Got a tip for us? Email:
tips@motor1.com
Join the conversation
(
)

Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

How your AI prompts could harm the environment
How your AI prompts could harm the environment

CNN

timean hour ago

  • CNN

How your AI prompts could harm the environment

AI Sustainability Climate change EconomyFacebookTweetLink Follow Sign up for CNN's Life, But Greener newsletter. Our limited newsletter series guides you on how to minimize your personal role in the climate crisis — and reduce your eco-anxiety. Whether it's answering work emails or drafting wedding vows, generative artificial intelligence tools have become a trusty copilot in many people's lives. But a growing body of research shows that for every problem AI solves, hidden environmental costs are racking up. Each word in an AI prompt is broken down into clusters of numbers called 'token IDs' and sent to massive data centers — some larger than football fields — powered by coal or natural gas plants. There, stacks of large computers generate responses through dozens of rapid calculations. The whole process can take up to 10 times more energy to complete than a regular Google search, according to a frequently cited estimation by the Electric Power Research Institute. So, for each prompt you give AI, what's the damage? To find out, researchers in Germany tested 14 large language model (LLM) AI systems by asking them both free-response and multiple-choice questions. Complex questions produced up to six times more carbon dioxide emissions than questions with concise answers. In addition, 'smarter' LLMs with more reasoning abilities produced up to 50 times more carbon emissions than simpler systems to answer the same question, the study reported. 'This shows us the tradeoff between energy consumption and the accuracy of model performance,' said Maximilian Dauner, a doctoral student at Hochschule München University of Applied Sciences and first author of the Frontiers in Communication study published Wednesday. Typically, these smarter, more energy intensive LLMs have tens of billions more parameters — the biases used for processing token IDs — than smaller, more concise models. 'You can think of it like a neural network in the brain. The more neuron connections, the more thinking you can do to answer a question,' Dauner said. Complex questions require more energy in part because of the lengthy explanations many AI models are trained to provide, Dauner said. If you ask an AI chatbot to solve an algebra question for you, it may take you through the steps it took to find the answer, he said. 'AI expends a lot of energy being polite, especially if the user is polite, saying 'please' and 'thank you,'' Dauner explained. 'But this just makes their responses even longer, expending more energy to generate each word.' For this reason, Dauner suggests users be more straightforward when communicating with AI models. Specify the length of the answer you want and limit it to one or two sentences, or say you don't need an explanation at all. Most important, Dauner's study highlights that not all AI models are created equally, said Sasha Luccioni, the climate lead at AI company Hugging Face, in an email. Users looking to reduce their carbon footprint can be more intentional about which model they chose for which task. 'Task-specific models are often much smaller and more efficient, and just as good at any context-specific task,' Luccioni explained. If you are a software engineer who solves complex coding problems every day, an AI model suited for coding may be necessary. But for the average high school student who wants help with homework, relying on powerful AI tools is like using a nuclear-powered digital calculator. Even within the same AI company, different model offerings can vary in their reasoning power, so research what capabilities best suit your needs, Dauner said. When possible, Luccioni recommends going back to basic sources — online encyclopedias and phone calculators — to accomplish simple tasks. Putting a number on the environmental impact of AI has proved challenging. The study noted that energy consumption can vary based on the user's proximity to local energy grids and the hardware used to run AI partly why the researchers chose to represent carbon emissions within a range, Dauner said. Furthermore, many AI companies don't share information about their energy consumption — or details like server size or optimization techniques that could help researchers estimate energy consumption, said Shaolei Ren, an associate professor of electrical and computer engineering at the University of California, Riverside who studies AI's water consumption. 'You can't really say AI consumes this much energy or water on average — that's just not meaningful. We need to look at each individual model and then (examine what it uses) for each task,' Ren said. One way AI companies could be more transparent is by disclosing the amount of carbon emissions associated with each prompt, Dauner suggested. 'Generally, if people were more informed about the average (environmental) cost of generating a response, people would maybe start thinking, 'Is it really necessary to turn myself into an action figure just because I'm bored?' Or 'do I have to tell ChatGPT jokes because I have nothing to do?'' Dauner said. Additionally, as more companies push to add generative AI tools to their systems, people may not have much choice how or when they use the technology, Luccioni said. 'We don't need generative AI in web search. Nobody asked for AI chatbots in (messaging apps) or on social media,' Luccioni said. 'This race to stuff them into every single existing technology is truly infuriating, since it comes with real consequences to our planet.' With less available information about AI's resource usage, consumers have less choice, Ren said, adding that regulatory pressures for more transparency are unlikely to the United States anytime soon. Instead, the best hope for more energy-efficient AI may lie in the cost efficacy of using less energy. 'Overall, I'm still positive about (the future). There are many software engineers working hard to improve resource efficiency,' Ren said. 'Other industries consume a lot of energy too, but it's not a reason to suggest AI's environmental impact is not a problem. We should definitely pay attention.'

2025 Hyundai Ioniq 5 N Review: A Racing Sim You Can Drive on the Road
2025 Hyundai Ioniq 5 N Review: A Racing Sim You Can Drive on the Road

The Drive

time3 hours ago

  • The Drive

2025 Hyundai Ioniq 5 N Review: A Racing Sim You Can Drive on the Road

The latest car news, reviews, and features. It's easy to go gaga over the 2025 Hyundai Ioniq 5 N on a short backroad blast or rip around a track. It's mind-blowingly fast and, more impressively, a genuinely unique driving experience. Though I have to admit, I never completely got over the inherent goofiness of fake manual shifting and the video-game interface. I understand why people love this car, but I wasn't sad when my weeklong test came to a close. A curb weight of 4,861 pounds is a lot—but so is an output of 601 horsepower, which can spike to 641 hp with the 10-second N Grin Boost button. The torque figure of 545 lb-ft also increases to 568 when that button is pushed. Hyundai says the Ioniq 5 N can do a zero-to-60-mph run in 3.25 seconds at maximum attack, but MotorTrend recorded an even more dizzying 2.8-second pull and ran the quarter-mile in 11 seconds flat. In a mass-produced car that can also carry four people and a dog comfortably? That's crazy talk—but it's real. Andrew P. Collins The 5 N's specs, grip, responsiveness, and real-time customizability have been discussed ad nauseam on podcasts, in reviews, and here on The Drive . It looks great and loads a lot of cargo because, as you've also probably read, while it may have the shape of an '80s rally car, it's got the footprint of a crossover. Four adults can easily fit, plus luggage. The $70,000 list price is justified, too. A BMW X3 M50 is about the same money, and while that may feel fancier, the Hyundai is far, far quicker. At least, until it runs out of juice, which does happen annoyingly soon. Hyundai's official max range estimate for this car is 221 miles; expect a bit less if you drive as hard as the car invites you to. Former The Drive staff writer Chris Rosales (now at Motor1 ) called out the weak driving range as the 5 N's 'one major flaw,' and yeah, it does make a long day of adventuring less free-wheeling. Where he's at, at the north end of Angeles Crest Highway in California, you could easily rack up 200 miles bombing canyons. Similar story here in rural New York, where I do my relaxation driving—I can put 100 miles on a car just doing weekend errands. This checker-stripe appears all over the place. But as you can see by the scratches in the door card, the car's not made of the most elite materials. Seating materials, however, felt excellent. Rear cargo room is bountiful—this is an SUV, after all. Door handles tuck away when you put the car in drive. The interior door arm rests kind of float on some backlighting. Here's another perspective on that interesting floating interior door trim design. Not much to see under the hood, but at least the motor cover has some decoration on it. This has to be one of the most creative reflector designs on any car right now. When you do need a charge, the car's supposed to be able to go from 10% to 80% in 18 minutes if you can connect to a 350 kW DC fast charger. A 50 kW DC charger should be able to do it in one hour and 10 minutes. Charging the car to max from 10% on a 240-volt outlet at 10.9 kW would take 7 hours and 20 minutes—even that's not terrible as long as you can just have it plugged in overnight. The cockpit layout is tidy but not aggressively minimalist, and the sporty seats are taut and supportive. It can be driven in near-silence, but the Ioniq 5 N has no chill. It wants to party. It wants to be driven hard. It might even be too stiff to be practical in some regions. Rough roads felt extremely unforgiving to me, and there are a whole lot of those in the Hudson Valley. Andrew P. Collins I'm not saying the car should be softer. On the contrary, the ride felt very well matched to the vehicle's vibe and intentions. And while it punishes you in potholes, it does reward you with a good feel for where the car is below you. Arguably, the 5 N's best party trick is its customizability. As our former reviews editor Chris Tsui wrote wrote last year after his drive at Laguna Seca: 'Eleven driver-selectable, fully variable levels of front-rear torque output mean Ioniq 5 N can go from fully FWD to fully RWD (70 rear, 30 front is the default), while an electronic limited-slip differential and 'N Drift Optimizer' function can simulate a clutch-kick to make smoky slides easier.' I was completely blown away by that idea when I first read about it. Now having now driven it on public roads for an extended period of time, I have some salient thoughts. If you're a car nerd, you can amuse yourself for hours running the same loop, trying it with different power distribution. You'll be able to enjoy and appreciate it at socially acceptable speeds, too. The sliding, I have to admit, I simply could not find a place that seemed safe enough to drift. This brings me to another key factor in what this car's like to drive: You really need to treat it with respect. You can sneeze on the accelerator and warp into the next zip code. An EV that's idling? It's not really, but it's a weirdly impressive imitation. The other images here are just to give you a sense of how deep you can go in the car's customization menu. If you like to tinker with settings, you're going to love this car. Andrew P. Collins But I'm happy to confirm that, unlike with some modern performance vehicles, you don't need to drive this thing like you're in a Mission: Impossible movie to enjoy it. Lastly, you can also select between a traditional EV experience and a simulated 'engine,' where you get a tach that climbs as you push the tall pedal, and then 'shift' with the paddles. The way the car bucks as you 'shift' and stutters if you hit the 'rev limiter' is spectacularly realistic. As a fan of science and technology, I'm deeply impressed with Hyundai's achievement in creating what is essentially a drivable video game. That said, as a driving enthusiast and open-road appreciator, the 5 N kind of leaves me feeling like the kid in this meme: TheOdd1sOut/YouTube I know—one could argue that every modern performance car has a degree of this experience. With today's traction management tech and almost-everything-by-wire, how connected to the road are you, really, in anything built after about 2015? In principle, the idea of a manual mode that can only affect performance adversely, and forces the computer to behave exclusively for my amusement, feels kind of cringey, just like the sound piped in to give the motor an aural character. I'm glad Hyundai allows you to silence it with the push of a button. As long as you can work with a 200-ish mile range EV, this is an easy one to endorse. The Hyundai Ioniq 5 N is absolutely a compelling option if your car budget is in the $70,000 neighborhood. It's got a great combo of novelty, style, and serious speed. Personally, I would rather get a softer, cheaper EV for getting around and keep my 22-year-old manual Bimmer for fun. I can push that E46 and probably not even break the speed limit. Andrew P. Collins The weight of the wheel in your hand, the sigh of the straight six when you make a higher-rev shift, the momentum transfer through corners. It's cliché to say, but new hardware just doesn't hit the same, even if it does a perfect job simulating a transmission. The other side of that is something I touched on above—the speeds you can hit in this car without even thinking about it. I get that it's cool, and I certainly admire the capability from a technological standpoint. But at the risk of sounding crotchety, do we need mass-market vehicles that snap to 60 mph in under three seconds? The Ioniq 5 N didn't convert me to categorical EV superiority, but it impressed the hell out of me. There's no question this is a good car; it's just not the ultimate performance experience. Andrew P. Collins Want to talk about what the most enjoyable 0 to 60 time is? Email the author at

Scientists Just Found Something Unbelievably Grim About Pollution Generated by AI
Scientists Just Found Something Unbelievably Grim About Pollution Generated by AI

Yahoo

time5 hours ago

  • Yahoo

Scientists Just Found Something Unbelievably Grim About Pollution Generated by AI

Tech companies are hellbent on pushing out ever more advanced artificial intelligence models — but there appears to be a grim cost to that progress. In a new study in the science journal Frontiers in Communication, German researchers found that large language models (LLM) that provide more accurate answers use exponentially more energy — and hence produce more carbon — than their simpler and lower-performing peers. In other words, the findings are a grim sign of things to come for the environmental impacts of the AI industry: the more accurate a model is, the higher its toll on the climate. "Everyone knows that as you increase model size, typically models become more capable, use more electricity and have more emissions," Allen Institute for AI researcher Jesse Dodge, who didn't work on the German research but has conducted similar analysis of his own, told the New York Times. The team examined 14 open source LLMs — they were unable to access the inner workings of commercial offerings like OpenAI's ChatGPT or Anthropic's Claude — of various sizes and fed them 500 multiple choice questions plus 500 "free-response questions." Crunching the numbers, the researchers found that big, more accurate models such as DeepSeek produce the most carbon compared to chatbots with smaller digital brains. So-called "reasoning" chatbots, which break problems down into steps in their attempts to solve them, also produced markedly more emissions than their simpler brethren. There were occasional LLMs that bucked the trend — Cogito 70B achieved slightly higher accuracy than DeepSeek, but with a modestly smaller carbon footprint, for instance — but the overall pattern was stark: the more reliable an AI's outputs, the greater its environmental harm. "We don't always need the biggest, most heavily trained model, to answer simple questions," Maximilian Dauner, a German doctoral student and lead author of the paper, told the NYT. "Smaller models are also capable of doing specific things well. The goal should be to pick the right model for the right task." That brings up an interesting point: do we really need AI in everything? When you go on Google, those annoying AI summaries pop up, no doubt generating pollution for a result that you never asked for in the first place. Each individual query might not count for much, but when you add them all up, the effects on the climate could be immense. OpenAI CEO Sam Altman, for example, recently enthused that a "significant fraction" of the Earth's total power production should eventually go to AI. More on AI: CEOs Using AI to Terrorize Their Employees

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store