I recently wrote about the automotive sector being the new competitive battleground for semiconductor companies, and announcements from three key chipmakers – Intel, Nvidia and Qualcomm – at CES earlier this month highlighted the extent to which that competition is heating up across four specific vectors: the electrification of vehicles (EVs), autonomous driving and semi-autonomous driver assisted features (ADAS), infotainment (digital cockpits), and connectivity (5G, C-V2X, etc.) With CES now in the rear view mirror, I want to share two observations about the intersection of silicon and the automotive space that deserve a little more attention. One involves the opportunities that all three chipmakers’ very different approaches to the automotive market present to OEMs and automakers. The other addresses the potential aftermarket pain points that these different approaches could create for consumers.   

 

Three chipmakers, one market, completely different strategies

Intel, Nvidia, and Qualcomm have taken radically different approaches to tackle the overall automotive market opportunity: While Intel and Nvidia are currently leaning on a software-defined vehicle strategy, essentially empowering carmakers to build or piece together custom hybrid systems on top of (and around) their solutions like Drive and Mobileye, Qualcomm is pursuing a more one-stop-shop approach with its Digital Chassis, which presumably aims to simplify integration and implementation for automakers. 

Qualcomm’s digital chassis is currently composed of four cardinal components that address ADAS, infotainment and telematics, car-to-Cloud Services, and connectivity, all of which are designed to work seamlessly together and provide OEMs with a complete modular platform. A system of systems, if you will. It can naturally be fully customized to create brand-specific UX and implementations, but automakers can opt to integrate only one or several of these components in their vehicles according to their needs if they want to mix and match vendors. Since Qualcomm’s roster of automotive partners and implementers already reads like a who’s who of automotive brands, with Renault Group adding its name to that already impressive list and GM selecting Qualcomm to power its Ultra Cruise feature, that approach appears to be off to a solid start. 

Caveat: In this competitive equation, Qualcomm may come across as something of a Jack of all trades, but the “master of none” caution that usually comes with that expression does not apply here. Right out of the gate, the company’s leadership in connectivity gives it a strong competitive edge in a market that needs vehicles to be connected as much as it needs them to be intelligent. That piece of the tech equation for connected, intelligent vehicles is as foundational as the connectivity component in mobile devices, including laptops and XR headsets. Moreover, Qualcomm is also very much an AI company, particularly when it comes to edge AI. It therefore stands to reason that combining both connectivity and AI into its automotive platforms is already providing the chipmaker with a compelling sales pitch to automakers, all of which are looking to combine cloud, edge cloud and edge compute capabilities into their vehicles. That can’t happen with a reliable and robust connectivity platform that integrates naturally with AI, and Qualcomm can deliver that. 

Intel and Nvidia, for their parts, seem to be focused more on deep specialization in ADAS and adjacent systems. Intel has been pretty open about its strategy for  Mobileye: achieving market-wide adoption at scale, and being the world’s #1 ADAS platform provider. To that end, the company just updated its automotive SOC to serve three distinct price tiers and ADAS levels: Its premium offering is the new 5nm L4-capable SOC, the EyeQ Ultra, which can deliver 176 trillion TOPS and 4.2 teraflops. EyeQ 6 High serves the L2+ and L3 market, and EyeQ 6 Light rounds out the more economically scalable L1 and L2 segment of the market.

One of the things I find most interesting about Intel’s approach to ADAS platform design is that it looks at consumer AVs and robotaxis differently. And because it seems to have found the right approach to make robotaxis more affordable for OEMs and operators, Mobileye’s install base could see itself significantly boosted by an early mover advantage in that growing market.

The work that Mobileye is also doing in driving policy logic (ADAS predictive modeling of other road users) is also pretty fascinating, and may be key to giving it an additional competitive edge against other ADAS platforms as automakers gauge which platform is most likely to make the right decisions in the most unpredictable road scenarios. The short of it is that Mobileye is still laser-focused on creating the best possible ADAS system for each automotive pricing tier, and that focus has paid off so far, with thirteen of the world’s biggest automakers using EyeQ products, and over 100 million chips already shipped.

Like Intel’s Mobileye, Nvidia’s Drive Hyperion platform is designed to be easily integrated with other vehicle solutions, in part thanks to partnerships with Desay, Flex, Quanta, Valeo and ZF. But a closer look reveals an acceleration of Nvidia’s expansion into adjacent systems. Drive Concierge is a prime example of how Nvidia is already coloring outside the lines of ADAS and expanding its capabilities into intelligent cockpit functionality. The new concierge platform draws on other solutions like Nvidia Omniverse, AV 4D perception, Riva GPU-accelerated speech AI SDK and neural networks to connect speech AI, computer vision, natural language processing, and recommendation engines into a concierge avatar that can assist drivers with helpful tasks like planning, navigation, scheduling, and so on. 

One way to look at this is that Nvidia is leveraging ADAS as the springboard from which to launch and scale additional connected automotive platforms, much in the way that Qualcomm approaches its own Digital Chassis strategy. Another way to look at it is that ADAS will simply morph into an AI-first automotive platform model that encompasses autonomous driving, assistant/concierge/chauffeur features, adaptive connectivity, power management, and the management of infotainment and telematics. The latter would essentially transcend the “software-defined” vehicle concept that we are discussing today and evolve into a more intentional “AI-defined” vehicle design approach. 

This may seem like a mere semantic difference but it isn’t. AI-forward design is different from a broader software-forward design in both form and function, to say nothing of the impact that a deeper focus on AI is likely to have on UX. To consumers, AI-defined translates into UX-defined, and as automotive platforms continue to move towards fully autonomous driving functionality, so will the AI interfaces inside vehicles that will manage and create experiences for their occupants. Nvidia looks to be on that evolutionary path, and that is an exciting prospect for car owners and robotaxi operators. Yes, here we are, talking about robotaxis again. They’re going to be a big part of this ecosystem. 

Taking a big step back, what we see emerging here is a competitive debate between the three most important chipmakers in the automotive space that pits three approaches against each other: deep specialization into ADAS (Intel’s Mobileye), a one-stop shop of automotive platforms (Qualcomm’s Snapdragon Digital Chassis), and a little bit of both that falls somewhere in the middle (Nvidia Drive). On the plus side, this will give automakers a lot of choices to pick from, and that is good for them and for consumers. On the less positive side, the complexity of these new systems, whose combinations may not be consistent across all makes and models, could translate into a nightmare scenario of maintenance, repairs, and TCO for consumers.

 

Maintenance concerns: could too much heterogeneity in automotive platforms create new headache for consumers?

Because automakers looking to land on the right cost/benefit equation for their smart, and connected vehicles could end up with any combination of Intel, Nvidia, and Qualcomm solutions packaged together in the same vehicle. These combinations are likely to vary depending on the make and model, which means that potentially, every model of an automaker could ship with entirely different combinations of new system components (hardware and software). This is bound to put a strain on repair shops, especially outside of dealerships, as few are likely to be able to service every single technology solution packaged into smart and connected cars, and EVs.  

The problem is simple: the more heterogeneous a vehicles’ buildout, the more difficult it may be to have it reliably serviced in one place. This creates a potential new friction point for vehicle owners who fear that they will have to find a half as many as a dozen new types of certified auto specialists to help fix or tune up these individual new systems. That concern grows in less densely populated areas where that breadth of technical expertise required to work on so many systems and platforms may be in short supply for some time. 

To address this pain point, automotive chipmakers have been busy building an entirely new aftermarket service model that enables secure OTA software updates via broadband and other SaaS services. But is enough being done to train and equip auto mechanics outside of the approved dealer ecosystem with the right skills and tools to work on these vehicles? Is there also an opportunity to empower vehicle owners themselves to manage and optimize their cars through apps and other frictionless interfaces? These are questions that automakers and their platform vendors are going to start addressing more clearly.

On the one hand, this aftermarket issue could push automakers towards more homogeneous platform builds, which would give Qualcomm’s Digital Chassis an edge. In other words, the appeal of Qualcomm’s complete Digital Chassis approach might not be limited to providing OEMs with a fully integrated one-stop design-build solution. It may also enable a one-stop aftermarket maintenance and service model for car owners as well, which automakers could seize upon to create a compelling case for why their vehicles will be less of a headache to service and more cost-effective to own. Simplicity on the front end and on the back end.

The flip side of that argument is that a high degree of specialization applied to one or two automotive technology platforms, particularly ADAS, could be worth the extra aftermarket/maintenance complexity. This is especially true if that particular platform is the most commonly found in vehicles. This would obviously give Intel’s Mobileye enough of an edge to make maintenance concerns moot, as most service centers that focus on ADAS systems will be likely to have experienced Mobileye-certified staff on hand. It is too soon to get a clear picture of how well Nvidia’s platform maintenance and service will scale outside of the dealership ecosystem, but Drive’s install base growth will determine what that footprint will look like. 

It is also possible that some automakers may turn this consumer friction point into a business opportunity for their dealership ecosystem by providing a complete no-stress, one-stop maintenance, upgrade, and repair shop option for their customers, and recapture a lot of the aftermarket dollars that they had traditionally not been able to hold on to. The economics and logistics behind that strategy will need a fairly significant reboot, however, especially over the course of the next decade, as automotive service centers expand their breadth of specialization, staff, physical footprint, and warehousing volume to be able to handle a higher volume of vehicles and a higher degree of platform complexity. As this is likely to add cost to a model that already drives consumers to look for more budget-friendly alternatives, it will be interesting to see how the automotive industry and its aftermarket ecosystem innovate to respond to that challenge.

It will also be interesting to see how much consumer-facing marketing, if any, Intel, Nvidia and Qualcomm will put behind their automotive platforms, and how that could help drive consumer preference. Conversely, assuming that consumers become more aware of whose platforms power their vehicles, will this awareness create a risk of blowback against specific chipmakers when something goes wrong with one of their systems, instead of the negative press being limited to the carmakers, as has traditionally been the case? 

Our upcoming auto research study may help shed some light on some of those questions, so be on the lookout for it.

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