With all the media coverage of Intel’s recent announcement of its intention to acquire Mobileye
, NVIDIA found itself in the rare position of not being foremost in the self-driving car headlines. The battle for leadership in providing the compute platform for automotive artificial intelligence and self-driving car applications is getting intense. Newcomers (in automotive terms) such as Intel, Qualcomm, NVIDIA and Samsung have been taking the fight to established players such as NXP (now in the process of being acquired by Qualcomm
), Texas Instruments, Renesas, Xilinx and others.
The debate over architectures (CPU? GPU? FPGA?) is arguably generating as much heat as light at the moment, but some market realities are clear. This was highlighted by the Bosch announcement that was made yesterday and fleshed out in more detail during a speech by NVIDIA CEO Jen-Hsun Huang today.
Bosch has announced at its “Bosch Connected World 2017” event that “NVIDIA will supply Bosch with a chip that stores algorithms, generated with machine learning methods. The AI onboard computer is expected to go into production by the beginning of the next decade at the latest”.
The Bosch AI Car Computer will incorporate NVIDIA’s forthcoming Xavier technology. It is claimed that Xavier can process up to 30 trillion deep learning operations a second while drawing 30 watts of power. It was claimed that Bosch will start production “by the beginning of the next decade at the latest”.
Bosch AI Car Computer
The move is part of a strong push by Bosch further into automated driving technology. At the beginning of 2017 it announced that it was investing some €300 million by 2021 in expanding its expertise in the area. This includes the establishing of a Center for Artificial Intelligence, across sites in India (Bengaluru), the U.S. (Palo Alto), and Germany (Renningen).
Equipment in Trunk of Bosch Tesla-Based Autonomous Research Vehicle
As noted, this is the second Tier One announcement of production-intent for an NVIDIA-powered module for automated driving. At CES 2017
, ZF launched its ProAI for highway automated driving. It will be the first commercial implementation of the NVIDA DrivePX2 platform featuring the Tegra Parker processor. Start-of-production is currently planned for 2018.
It would seem that NVIDIA thus has a lead when it comes to announced production intent for deploying deep-learning AI in automated vehicles. Its processors are already used in Tesla vehicles, and it now has two major automotive Tier One suppliers (Bosch and ZF) stating that they will go into production with NVIDIA-powered modules.
In recent interactions with other semiconductor processor vendors, Strategy Analytics has seen a shift in their messaging around automated driving. The talk used to center mainly on the processing/brain part of the automated driving problem. It has now shifted to a more holistic and integrated positioning across sensing, on-board processing, communication and cloud. This new automotive “Quad-play” is perhaps a natural move for the likes of Intel and Qualcomm, which either have existing expertise in many of these spaces or are in the process of acquiring more pieces of the jigsaw. To date, NVIDIA has remained resolutely focused on the processing task – be it in-vehicle or in the cloud.
However, at the moment it is far from clear that customers are demanding a “Quad Play” capability from their suppliers. Historically, OEMs and Tier Ones have been very content to pick and choose from a range of vendors, and have sometimes been wary of getting “locked in” to a platform solution that leaves them less room to seek best-in-class in each area as well as bring their own innovations to market.
NVIDIA, with announcements such as this Bosch one, can certainly claim an early lead in getting production intent for deploying deep-learning AI solutions in automated vehicles. Other vendors are keen to expand the discussion beyond the processing task, and Strategy Analytics expects to hear a lot more about emerging automotive semiconductor “Quad Plays” in the coming months.
Separating the hype from the reality will be key in understanding where the true opportunities lie.