John Hayes is the founder and CEO of Ghost Autonomy, the self-driving AI software platform for the automotive market.
When Apple launched the iPhone, it never dreamed of the emergence of an app like Uber. What will flagship automotive applications look like in the long term, and who will make them a reality?
As the software-defined car takes shape before our eyes, it becomes clear that beyond autonomy, the opportunities for automotive software are wide open and largely undefined in terms of scope and potential applications. While copying existing iPhone apps for cars may not possibly be the solution, the right answer is that copying the progression style of Apple’s open-source software could be the right way to build the next trillion-dollar automaker.
It’s simple to communicate about software but complicated to build. It’s even harder to determine what to build, especially for client applications. Consumers have capricious whims, which creates risks. Like Hollywood movies, software production can be expensive and difficult. expect precisely what other people want.
Automakers have struggled to expand software over the past decade, both in terms of execution and visitor adoption. A July 2023 J. D. Power study found that consumers are largely disappointed with their cars’ new tech features, contributing to an overall decline in the number of owners. satisfaction in consecutive years. Internal efforts have been mixed at best, with a number of high-profile failures. Tesla is still years, if not decades, ahead of classic automakers.
While it’s straightforward to point out that software is rarely part of the automotive industry’s old experience, software is also difficult for software companies to develop, even Silicon Valley giants. Look no further than Meta, which created a disruptive consumer product 20 years ago on Facebook. Today, the company relies heavily on products and features you’ve purchased (Instagram, WhatsApp) or copied (short videos on Snapchat and TikTok). The fact is, most large companies struggle to innovate. especially in the software space.
Silicon Valley has developed two answers to this problem, relying on third-party developers for innovation: venture capital (VC) and APIs.
• Venture capital. The largest companies outsource the failure to develop new products into the VC/startup system. This allows them to avoid painful strategy changes and reorganizations that would slow their growth.
Venture capitalists fund new software companies to build the next generation of applications. Some startups ultimately become standalone companies, but many are bought by large incumbents and sold as new product lines or features. YouTube, Instagram, WhatsApp, Beats, Android, Nest and Ring are all household names that started as venture-backed standalone companies and eventually became product lines at larger companies.
• APIs. In this model, like Apple’s App Store, the large incumbent corporations build an open platform that allows new applications to access their user base. Critically, this model typically pushes the go-to-market burden on the app developers, pushing them to market and service their own apps.
Concretely and financially, it works more like a tax. The platform/company is much less concerned with owning and offering the specific features of the application, allowing many other types of programs to exist. New APIs (with the promise of stability) have been shown to create a wave of new business.
For an ecosystem of developers, cars will want to adapt to a new open architecture, with some significant technical changes.
Automakers will have to get into building and maintaining a true API in the mold of Silicon Valley’s leading platforms with those fundamentals.
• Self-service: Open progression that does not require a contract to extend an application.
• Open documentation. An API that makes specific promises about functionality, access, data structures and requirements. (This is hard and requires sophisticated thinking.)
• Long-term stability. Once documentation and apps are published, car companies must be willing to support apps built this way for at least a decade.
Automakers want the entire car to be available through software and software developers. This requires allowing direct access to core parts, such as sensor knowledge streams. It also requires cutting or disposing of completely specialized parts or modules that are far removed from the input of developers and innovation. After all, the amount of space available to third-party developers is proportional to the duration of the overall software opportunity.
Automakers want to ensure that the car has connectivity that enables interoperability with the cloud and with the next generation of knowledge center applications. Cars are expected to stay on the roads for more than 10 years. While the car’s processing functions may be constant for a given style year, the cloud will continue to evolve.
Large Language Models (LLMs) and Visual Language Models (VLMs) are the newest intermediate knowledge programs capable of generating normal results, but only with ordinary computational resources. While quick-use instances for those car models are still being developed, it’s clear that there will be more complex systems available in the data center. The software-defined car will need access to the data center to run the next generation of systems, making connectivity essential.
Software is clearly the new chassis on which future vehicles will be built. Traditional automakers need to figure out software to compete with technology-forward upstarts across the globe. By embracing an open software development model with APIs, they should be able to fuel innovation at low effort and cost while bringing a dynamic ecosystem of valuable, interconnected applications to market—inspiring consumers to buy into a new vehicle experience.
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