Most investors know Tesla (NASDAQ:TSLA) for its electric vehicles (EVs) and energy storage solutions. For years, however, its CEO, Elon Musk, has been describing a vision to transform Tesla from a traditional auto manufacturer and green energy pioneer into a full-stack technology enterprise.
Specifically, Musk's interests surround how artificial intelligence (AI) will play an integral role in developing the company's next-generation products and services -- from humanoid robots to fleets of fully autonomous vehicles.
But in early August, Musk delivered some sobering news to investors regarding Tesla's ambitions. Let's dig into the current state of affairs surrounding Tesla's AI road map and assess why these shifts should be celebrated by Nvidia (NVDA 0.24%) stock investors right now.
Understanding Tesla's AI vision
Today, most AI developers rely on clusters of GPUs supplied by the likes of Nvidia or Advanced Micro Devices to train and inference their models. If you know anything about Musk, though, then it should come as no surprise that the serial entrepreneur took a bolder approach beyond off-the-shelf solutions -- developing an internally built supercomputer system called Dojo.
While Dojo was nothing short of a moonshot in AI infrastructure, the vision was admirable on paper. If Tesla could vertically integrate its own AI architecture across robotaxis and humanoid robotics, the company would essentially own its compute stack and have a competitive moat.
Image source: Getty Images.
Musk's latest headline-grabber is one for the ages
While Dojo has been one of the core pillars supporting Tesla's bull narrative for years, Musk just dropped some heavy news on investors. The executive took to social media platform X (formerly known as Twitter) to tell investors that Tesla's focus will now be on chip projects dubbed AI5 and AI6, calling the stand-alone Dojo platform "an evolutionary dead end."
Essentially, it doesn't make strategic or economic sense for Tesla to pursue multiple chip designs geared toward different applications. Instead, AI6 represents something more multifaceted than Dojo. While Dojo's applications were niche-oriented, AI6 will handle both training workloads and inferencing neural networks across Tesla's broader infrastructure use cases without requiring a specialized and limited computing platform such as Dojo.
Why is this big news for Nvidia?
The idea of Dojo was to migrate away from chip suppliers like Nvidia and potentially even compete in the semiconductor industry more broadly down the road.
However, with AI6 now the primary focus at Tesla, it's reported that the company will rely on external GPU providers such as Nvidia -- which it already uses in some capacities -- in the interim as it takes time to build, develop, and scale its new services.
I see Tesla's decision to sideline Dojo as a massive win for Nvidia, as it reinforces the idea that even the most technologically ambitious and financially strong businesses can't out-innovate established industry powerhouses. In many ways, Musk's decision is a subtle nod that Nvidia remains king of the AI realm -- a bullish catalyst supporting the durability of the chipmaker's long-term growth prospects.
In addition, Tesla's pivot could create meaningful opportunities for Nvidia's automotive business. While the company's compute and networking services are still the main driver of revenue and profits, the company's automotive business is an emerging growth engine that should not be overlooked.
In my view, more automakers will reach the same conclusion as Tesla: Building custom infrastructure is both costly and time-intensive. As a result, reaffirmed dependence on external hardware and software systems from partners such as Nvidia could accelerate broader demand for the company's ecosystem of automotive products -- spawning a new source of infrastructure growth to complement the company's core data center segment.
For these reasons, Nvidia's presence in the autonomous vehicle and robotics landscapes could expand significantly over the next several years -- solidifying its position as an integral power source in the AI infrastructure ecosystem.
