Experian Automotive is a company that helps car dealers use data to find the right customers. Instead of guessing who to advertise to, it helps dealers target people at the right time with the right message.
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Volkswagen
Volkswagen is the company being discussed here. The segment is about VW changing how much it produces to avoid building too many cars for the market.
A “tech stack” is the combination of hardware, operating systems, middleware, and applications that work together to deliver a product. In automotive, “custom tech stacks” means automakers tailor the software and compute layers to their specific vehicle features and architectures.
Restructuring is when a company changes how it operates to get back on track financially. For carmakers, it often means cutting costs and adjusting production plans.
Overcapacity means a company can build more cars than people are willing to buy. When that happens, it can hurt profits and force companies to cut jobs or production.
EV spending refers to the investment automakers make to develop and produce electric vehicles—such as new platforms, batteries, factories, and software. The segment frames it as a cost pressure that can reduce near-term profitability.
Tariffs are taxes imposed on imported goods, which can raise the cost of vehicles or parts crossing borders. For automakers, tariffs can pressure pricing, reduce demand, and complicate supply-chain planning.
ZF is a big parts company that makes important stuff for many car brands. Here, they’re dealing with financial trouble and reorganizing parts of their business.
A driver assistance unit refers to the hardware and software that enable features like adaptive cruise control, lane keeping, and automated safety functions. Selling this unit indicates ZF is refocusing its resources away from that segment.
The Range Rover is a luxury SUV from Land Rover. It’s designed to be comfortable for everyday driving but still capable off-road. The podcast brings it up because it’s part of the newer lineup shaped by the same leadership.
The Defender is a tough SUV made for off-road driving. It’s known for being durable and capable on rough roads. The podcast mentions it because it connects to the newer version of the Defender and the team behind it.
Instead of selling the car as “the best,” the ads will highlight how much it costs to own each month. That can attract people who were priced out before.
“EV only” would mean the company only sells electric cars. Mercedes is saying it doesn’t want to limit itself that way because not everyone is ready for EVs yet.
ICE is the regular gas-engine car. EV is fully electric, and a hybrid uses both gas and electricity. Mercedes is saying it wants to sell all types, not only electric.
Mercedes wants its electric versions to cost less. That usually means making the batteries and the car cheaper to build, so more people can afford them.
It means using different kinds of information—about cars people have, who they are, and what financing they might qualify for. Dealers use it to find buyers who are ready to shop.
NVIDIA makes computer chips and AI software. Automakers use NVIDIA tech to power the computers in cars that help with advanced driver features like safety systems and navigation.
They teach the AI using data, then test it in a virtual environment. That way, the car can handle more situations safely before it’s used on real roads.
“Full stack” means having the whole toolkit—from the car-side computing to training and testing. Some customers only use parts of it, depending on what they already have.
An end-to-end pipeline is the full process from learning (training) to testing and then using the software. Wave didn’t take everything—they picked the parts that worked for them and customized the rest.
Uber is being mentioned as a company working on self-driving or automated ride services. The key idea is they’re willing to add hardware if it makes the system safer.
Active safety is technology that helps prevent accidents or reduce their severity while you’re driving. The speaker is saying it may not require as much compute as full autonomy.
This means the chip might feel fast at first, then slow down later. The question is whether that kind of change is a problem for a car that must drive safely all the time.
Sustained performance means the system keeps working at a high level for a long time, not just for a short burst. In a car, heat and power limits can make performance drop if the system isn’t designed for it.
Algorithms are the car’s software “rules” for interpreting what it sees and deciding what to do. Different driving modes make the car run different software tasks.
Peak power is the highest “energy use” the car’s computer hits when it’s working hardest. The point here is that some designs waste power by staying at high demand all the time.
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Welcome to Daily Drive.
For Monday, March 23rd, 2026, I'm Kellan Walker in Las Vegas.
Today on the show, Volkswagen doubles down on capacity cuts despite an order backlog.
ZF could sell off more assets as debt weighs down the German supplier.
And Jaguar's design chief, Jerry McGovern, makes his exit official.
Plus, NVIDIA's Ali Khani talks about how automakers can build custom tech stacks using
the chip giant's tools.
Now we go to a customer and we say, do you need help building your version of this?
And we'll help them any way they want.
Let's run through all the news you need to know to keep up in the auto industry.
Volkswagen's restructuring isn't slowing down, even as orders pile up.
CEO Oliver Bloom told German newspaper, Bill Dom Zongtog, that VW will keep scrutinizing
factory capacity worldwide, whether in Europe or China, to avoid overcapacity.
The automaker is cutting about 50,000 jobs in Germany by 2030, citing high labor and
energy costs, plus heavy regulation.
Bloom says Germany should take notes from China's disciplined, systematic five-year
planning approach.
VW expects operating returns as low as 4% this year, as tariffs and EV spending squeeze
margins.
Staying in Germany, ZF is looking to shed more assets as it wrestles with over $11 billion
in debt.
The supplier just spun off its wind power division and says it's exploring strategic
options for the business.
That's on top of selling its driver assistance unit to Samsung's Harman for $1.7 billion
last December.
ZF is also cutting up to 14,000 jobs in Germany by 2028.
It took a $1.8 billion hit last year after scaling back EV projects when demand didn't
materialize as expected.
And Jaguar Land Rover's design chief Jerry McGovern is officially stepping down at the
end of March to start his own creative consultancy.
JLR's statement draws a line under a period of uncertainty, during which the automaker
declined to clarify McGovern's employment status after reports in January said he had
been dismissed.
McGovern's been overseeing design for both brands since 2020 and before that he was Land
Rover's design chief starting in 2006.
He's the guy behind the modern Range Rover Defender and models like the Evoke.
His exit comes before Jaguar unveils its first new all-electric sedan later this year.
Part of that controversial rebrand he led that kicked off with the Type 00 concept back
in 2024.
And those are today's headlines.
You can find more details on all those stories at AutoNews.com.
Our own Urvash Karkaria has been covering Mercedes-Benz's ambitious product push which
includes a pair of electric AMG crossovers and a four-door G-Wagon convertible coming
to the US.
He joins me now to talk about the thought process behind the plan.
Urvash, welcome back to Daily Drive.
Hi, Gal.
Good to be here.
Great to have you, Urvash.
Why is Mercedes betting on battery-electric models while many other brands retreat from
the segment?
Sure.
So, the scoop last week was about these three high-performance electric AMG models that
Mercedes is going to bring in the next year or two.
Obviously, these products were developed several years ago before the whole market for
EVs started crumbling.
So I guess Mercedes cannot stop production or product development mid-cycle.
They needed to push this out.
But in the future, Mercedes has changed its EV strategy.
They were initially going to go EV-only, build a lineup of all-electric vehicles like they
had with the EQs.
But now they've changed their strategy.
They've adopted a tactic from their rival BMW, where future models like the E-class,
the C-class, GLS, GLE, they will be offered essentially in a hybrid, ICE, and battery-electric
powertrains.
The designs will be similar.
So the top of the cars will be similar.
However, the powertrains will change.
So they're taking a more diversified powertrain strategy and essentially giving the customer
the choice of powertrain that they wish.
So beyond these new AMG models, how does Mercedes plan to reach its goal of 400,000 annual US sales?
Yeah, so Mercedes has this ambitious goal of 400,000 by the end of the decade.
And the executives have been clear that this is more of a North Star rather than a firm goal.
But in the near term, this year, they want to basically increase sales about 7%.
This is retail sales, and that would be about 325,000 passenger vehicles, so not vans.
And this is not fleet.
And the way they want to do it is by reducing the number of dealer programs, reducing the number of trims.
So it's less complicated for the customer when it comes to choosing what variation of a particular model that they want.
They're also going to get more tactical with their marketing.
And the marketing is going to now focus on affordability.
So one of the challenges Mercedes has had is until recently, they've had this focus on the top end, the AMGs, the Mybox.
They've been pushing those kinds of vehicles because they had the highest margin.
This was coming out of the pandemic when everybody was willing to pay more prices.
So Mercedes said, you know what, let's try and sell the most expensive cars and maximize our bank for the buck.
But of course, as we moved away from the pandemic, the competition has increased.
They've realized that they've been giving up a lot of sales to BMW and Lexus in their core lineup, their more affordable lineup,
which is like the GLE, the C-Class, the GLS to some extent, the E-Class.
So now they want to focus on those models and they want to do it by basically advertising better deals, better lease payments.
So customers will know or potential customers will know that a Mercedes can be an affordable payment.
It's not just for the high, high end.
So that's one way they hope to sort of attract a broader audience.
In terms of the affordability angle, Mercedes also is by essentially developing a comprehensive lineup of ICE, EV and hybrid models rather than EV only models.
They hope to lower the price of these electric variants.
And one of the top executives, Adam Chamberlain, the CEO of Mercedes-Benz USA, said that in the future Mercedes will price its EVs in the same zip code as their gasoline-powered counterparts.
So there will be more price parity.
So once again, it's lowering the price even of the EVs.
So while demand is more subdued, there's still a reason for people to pick Mercedes-Benz EVs.
Interesting stuff.
Urvash, thank you so much for joining me.
Thanks for having me, Gil.
Have a great day.
You too.
Coming up, NVIDIA's Ali Khani talks about how automakers can pick and choose from the Chip Giants Automotive Toolkit.
That's next on Daily Drive.
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Welcome back to Daily Drive.
I'm Kellan Walker.
NVIDIA has become one of the biggest names in automotive technology, offering everything from AI training tools to in-vehicle computing platforms.
But the company's approach isn't one size fits all.
On the latest episode of the Automotive News Shift podcast, our own Molly Boygon spoke with Ali Kani, NVIDIA's vice president of automotive.
They talked about how automakers can build custom tech stacks using NVIDIA's modular tools, including training and simulation platforms.
Here's a piece of that conversation.
You know, so much of the show has focused on NVIDIA's movements in ADAS and autonomy and partnerships in ADAS and autonomy, but, you know, Thor and Hyperion are, to my understanding, a full vehicle compute play.
So is NVIDIA's automotive strategy about full vehicle compute, or is it focused on ADAS and autonomy, especially for high-end vehicles?
It's a little bit different.
Like our strategy is consistent in automotive as other markets.
We're trying to build the reinforced data loop from car to cloud, and that spans three computers, the training computer, the simulation computer, and the in-car computer.
So we're trying to build the most efficient loop across those three computers, and we're helping our partners.
And we built this stack to be modular so they can pick and choose what parts of that full stack they want our help to develop.
So, but what you're driving in today is a reference of how NVIDIA has built the entire stack, the platform layer, the chip, the sensors, the operating system, the models that run on this car, the application of parking, active safety, and driving.
You're experiencing it.
This is really good for a passenger car, right?
And we trained the models and we simulated the models.
And then the point is, is now we go to a customer and we say, do you need help building your version of this?
And we'll help them any way they want across that three computer challenge.
And the point of it is building this needs those three computers.
That's, that's what we do.
And so we have customers like Tesla, who says to us, we don't need any of your help for the chip in the car, the operating system or the models in the car.
We got that.
But so Tesla is an example of, I don't need you in the car or to build the models, but I need your help for training.
And it turns out that you could, you can use us just there.
And Tesla is still our biggest customer and automotive.
Because the infrastructure computer is the biggest computer.
It's the most important part of, you know, it's the biggest brain.
That's where we help most.
But then here is the case, a reference partner who obviously is asking us to do the full, like all three computers and full stack.
Okay.
And that's okay.
And then last week, there was an announcement that Wave is working with Nissan to do RoboTaxes in
Japan.
And they're also doing it in London, right?
Wave is a customer that builds the AV software themselves, but they develop on our chip in the car that that car was a is a Hyperion 10 car.
So they're getting our chips in the car.
They're building the AV software.
They're training on our GPUs in the cloud.
And they're using parts of our omniverse and dedicated generation platform to test their software.
So it's a three computer customer, though they didn't take the full stack.
They took the portions of that end to end pipeline that made sense for them and they augmented.
And that's what's unique.
There's no company that does that, right?
There was another announcement that Zeus is working with Uber on RoboTaxes.
They're using us in the car and they're training their models in the cloud with us.
So they're there with us on two of the computers.
And so you're kind of seeing just recent news of, you know, different kinds of companies.
Waymo is another one they use us in the car.
And of course, they use our models to trade.
Yeah.
And for those companies that are using the models in the car, I wanted to talk to you a little bit about PowerDrop because that's been that's been coming up in my conversations with industry analysts.
So, you know, the GPU based system is so powerful for level four plus plus autonomy and beyond.
But it's very compute intensive.
And I wonder if you can explain how you're sort of rationalizing the PowerDrop gap between a GPU based SOC and purpose built ADAS chips from other suppliers.
Like, how do you sort of defend the additional PowerDrop?
Yeah, I mean, it's like, I think what we're finding is, is when you're doing something like level four,
the most important thing is the safety of the car.
You're trying to optimize for experience.
You're not trying to optimize for, hey, can I like lower the cost?
Actually, I don't know if you know that there was a good session yesterday with Uber.
And I was hosting it, but Sophros, who's the president of their mobility solution, was talking about, hey, when we're building a level four car,
if you needed a few extra sensors or a little bit more compute, we would invest that because it's worth it.
Safety is the most critical thing.
So where we're at is the industries at an inflection point.
Every car will want to be autonomous.
And when you are trying to build that kind of a car, what matters is these things, right?
But if all you wanted was NCAP.
NCAP to me, I think if that's what you want in your car, my personal opinion would be, I think you're not realizing the experience that your customer can have.
But if that's what you want, please buy a purpose-built chip, it'll be really cheap and it'll be really low power and you're fine, right?
Because the car, there is a chip that can do that and you're not missing anything, right?
But I think the industry has moved off from that.
And if then you say, look, I want an autonomous car, the factors that come into play in your decision-making should be different.
And the other thing is, if you look at the end-to-end performance efficiency of our platform,
actually, we're super efficient and the most efficient option from a performance per watt perspective.
Does that make sense?
Like, if I told you I need 4,000 FP4 TOCs, I would say, let me show you how Thor is actually the lowest power way to build that system.
So if your software needs to be like that, this is the lowest power way you can do it.
But if somebody said, I need active safety, I would say you could probably do that in 50 TOCs.
And definitely there's something that can do it in like 15 watts or something.
Do you see what I'm saying?
But performance per watt of a 4,000 TOC system, I would show you that Thor is the lowest power way to get it.
So it's also a relative question.
So that's the way I would kind of respond to that question.
Yeah, that makes sense.
And you mentioned safety at the beginning.
Another perspective I've heard related to the GPU based approach versus NPU based approach is that GPU based performance peaks and drops.
Do you agree with that?
And how do you address concerns about the sustained performance of GPU based systems given the safety critical nature of driving?
Yeah.
So I think what we mean by that is one of the nice features of CUDA is that its performance and its power scales in a consistent way.
Like if you want more performance, it's more power if you want 70% of the performance.
It's close to 70% of the power.
It kind of scales with performance.
So the point is, if you're driving this car right now and you don't want to engage L2++ and you just want an active safety on, it's actually dissipating less power.
And actually, if you want to have the car parked and you leave the car but you want Century Boat on, it's operating it like a few watts only.
And so then if you park the car and you leave, it's actually essentially off even though it's on.
And it will record people who are coming in your car and trying to do something.
And so it's actually efficient for what it needs to be.
And so that's an advantage of the architecture.
These other architectures, it's like kind of always at the same peak power.
But this application is not like that because the algorithms are running to right now are different than if you weren't engaging autopilot and you just want an active safety.
And it's definitely not if the car is parked and you just want Century Moat on.
Got it.
So if I hear you correctly, you're saying that the peaks and drops are...
It's valuable.
...valuable.
Yeah, that's the advantage because they're catered to the different functions being executed.
You actually want that in an automotive car.
You can get the latest news on automotive tech and innovation, manufacturing and everything happening in the auto industry at AutoNews.com.
Come back tomorrow for a look at whether AI could replace vehicle listing sites in generating leads for dealerships.
Money is money if you can save it and be more efficient with it.
Why wouldn't you want to try it?
At this point, it's early, but dealers are showing some interest in finding another way.
And you never miss an episode.
About this episode
Volkswagen is pressing ahead with restructuring, cutting factory capacity and planning job reductions in Germany even as its order backlog grows, aiming to avoid overcapacity amid margin pressure from tariffs and EV spending. ZF is also under strain, exploring asset sales while dealing with more than $11B in debt and further job cuts after scaling back EV projects. Jaguar Land Rover confirms design chief Jerry McGovern’s departure. Mercedes doubles down on EVs via an expanded hybrid/ICE/EV lineup and affordability-focused marketing. NVIDIA’s Ali Kani explains its modular “car-to-cloud” compute stack and why GPU-based autonomy can be efficient and safety-ready.
