Long before this year's Consumer Electronics Show in Las Vegas, we already knew NVIDIA Corporation (NASDAQ:NVDA) was striving to ensure its technology would play a central role in advancing self-driving cars.
When NVIDIA unveiled its 192-core Tegra K1 chip at CES two years ago, for example, investors marveled as Audi showcased a self-driving car that relied on the supercomputer-esque power of the tiny new processor contained in a small module in the trunk.
Then at last year's show, NVIDIA launched the first iteration of NVIDIA DRIVE PX, an autopilot platform powered by two of its even more powerful Tegra X1 processors, and a slew of advanced algorithms created by NVIDIA's computer vision engineering team. The Tegra X1 for is part, packed over one full teraflops of computing power, making it technically faster than ASCI Red, the world's first teraflops system and the fastest supercomputer up until the year 2000.
Deep learning on the road
But the graphics chip specialist has outdone itself this year.
Earlier this week, NVIDIA kicked off CES 2016 by launching NVIDIA DRIVE PX 2, describing its as "the world's first in-car artificial intelligence supercomputer."
More specifically, NVIDIA DRIVE PX 2 is powered by a combination of two next-generation Tegra processors and two next-gen discrete GPUs based on NVIDIA's Pascal GPU architecture. All that processing might is able to collectively deliver up to 24 trillion "deep learning operations" per second -- that is, in NVIDIA's words, "specialized instructions that accelerate the math used in deep learning network inference."
By that measure, NVIDIA DRIVE PX 2 packs more than 10 times the computational power of the original DRIVE PX released one year ago. And these specialized operations allow the vehicle to more effectively identify and handle abnormal driving tasks like road debris, erratic drivers, and construction zones.
Meanwhile, DRIVE PX 2's GPU architecture delivers up to 8 trillion general purpose floating point operations per second -- or four times the GPU power of last year's DRIVE PX -- allowing NVIDIA's automotive partners to more effectively implement the more predictable driving algorithms, including localization, path planning, and fusion of data collected from a multitude of sensors. On the latter, for example, DRIVE PX 2 can process inputs from as many as 12 video cameras, as well as LiDAR, radar, and ultrasonic sensors, providing 360-degree situational awareness around the car.
If you build it...
Of course, even the most superior technology is nothing without partners willing to implement it. Luckily, NVIDIA has already seen over 50 automakers adopt its AI platform for antonymous driving development since launching DRIVE PX last year.
It would seem to follow, then, that these automakers should have little hesitation continuing to move forward with DRIVE PX 2. To be sure, Volvo (NASDAQOTH:VOLVY) has already committed to be the first to implement DRIVE PX 2 using a fleet of self-driving Volvo XC90 SUV's which will hit the road in a "public trial" next year.
Meanwhile, don't be surprised if additional automakers announce their intent in short order; NVIDIA says the platform will be available to early developmental partners in second quarter of this year, and "generally available" by Q4.
As part of its end-to-end solution for partners, NVIDIA also supplies a "deep learning" platform called DIGITS, which helps train each system's deep neural network to better "understand" the vast quantities of data provided by the vehicles' sensors.
That's also not to say automakers haven't tried doing it on their own.
"Using NVIDIA's DIGITS deep learning platform, in less than four hours we achieved over 96 percent accuracy using Ruhr University Bochum's traffic sign database," explained Matthias Rudolph, Audi's director of Architecture Driver Assistance Systems. "While others invested years of development to achieve similar levels of perception with classical computer vision algorithms, we have been able to do it at the speed of light."
And according to Dragos Maciuca, technical director of Ford's (NYSE:F) Research and Innovation Center, "Deep learning on NVIDIA DIGITS has allowed for a 30X enhancement in training pedestrian detection algorithms, which are being further tested and developed as we move them onto NVIDIA DRIVE PX."
NVIDIA's automotive growth and market potential
So where does that leave NVIDIA investors today?
As it stands, there are already more than 10 million vehicles on the road featuring NVIDIA technology -- though nearly all that technology is still in the form of high-tech infotainment modules powered by NVIDIA's GPUs.
But even absent a significant contribution from self-driving vehicle technology, automotive segment revenue still climbed 51% year over year to $79 million in NVIDIA's most recent quarter. And though NVIDIA hasn't specifically outlined expected automotive growth rates going forward, CEO Jen-Hsun Huang did insist during last quarter's conference call that they anticipate automotive will "continue to grow through next year and a couple years after that."
To be fair, the young state of the self-driving car industry makes it virtually impossible to forecast how growth will play out with any reasonable degree of certainty. So the most NVIDIA can do is continue to drive innovation to position itself firmly at the center of the trend.
Thankfully for shareholders, it seems that's exactly what NVIDIA is doing given the vast improvements it continues to deliver in self-driving vehicle technology with each passing year. In the end, that's why I remain convinced NVIDIA stock is a great bet for investors with the foresight and patience to buy early and profit as the self-driving car narrative unfolds.