- NVIDIA announced Xavier, a new AI supercomputer designed for use in self-driving cars, more powerful and efficient.
- The company also announced a software suite dubbed DriveWorks and a partnership with mapping and car navigation system developer TomTom.
- Meanwhile, NVIDIA's AI supercomputing solution continue to gain acceptance, as shown by the partnership with enterprise software giant SAP.
Xavier is a complete System-on-Chip (SoC) built with 16nm FinFET process technology. The new NVIDIA SoC supercomputer has 7 billion transistors, a new GPU architecture called Volta, a custom 8 core CPU architecture, and a new computer vision accelerator. The processor will deliver 20 TOPS (trillion operations per second) of performance, while consuming only 20 watts of power.
Designed for self-driving car, Xavier is intended to be compliant with critical automotive standards, such as the ISO 26262 functional safety specification.
"This is the greatest SoC endeavor I have ever known, and we have been building chips for a very long time," said Huang. "Just imagine what an autonomous vehicle can do in the near future with Xavier."
The NVIDIA CEO added that AI computing is exploding. "GPU computing is at the beginning of something very, very important, a brand new revolution, what people call the AI revolution, the beginning of the fourth industrial revolution," he said. "However you describe it, we think something really big is around the corner."
In January, at the Consumer Electronics Show (CES) 2016 in Las Vegas, NVIDIA launched the NVIDIA DRIVE PX 2 in-car AI-powered supercomputer to enable smart cars to sense the world around them and drive themselves. At the time, the NVIDIA DRIVE PX 2 was presented as the world's most powerful engine for in-vehicle AI for autonomous cars. But things evolve rapidly in the fast-moving sectors of AI computing and self-driving car technologies. Now, according to NVIDIA, a single Xavier AI processor will be able to replace today’s DRIVE PX 2 configured with dual mobile SoCs and dual discrete GPUs - at a fraction of the power consumption.
Other NVIDIA announcements at GPU Technology Conference Europe include the launch of the Alpha 1 release of NVIDIA's DriveWorks software, which includes deep neural networks that enable self-driving car developers to achieve new levels of safety and reliability, and a partnership with car navigation system developer TomTom to create a cloud-to-car mapping system for self-driving cars. The two companies will begin with TomTom’s RoadDNA localization and mapping software on the DRIVE PX 2, and integrating TomTom’s HD map support into DriveWorks.
Alain De Taeye, a member of TomTom’s management board, is persuaded that AI will be a key component of future mapping and car navigation systems. "You want to localize your car with a centimeter of accuracy, because you don’t want to miss by 20 centimeters when you have a self driving car," he said. "People used to believe creating navigable maps was unaffordable, now people believe HD maps, which are very detailed, very accurate is unaffordable - it’s not: you need to be clever about it and use AI and AI platforms to automatically create and maintain them."
Recently, NVIDIA and Baidu announced a partnership to create a cloud-to-car autonomous car platform for self-driving car makers.
The Motley Fool notes that NVIDIA is continually moving further into the driverless-car market with its technologies and partnerships. The market for self-driving cars will be worth an estimated $42 billion by 2025, according to Boston Consulting Group, and NVIDIA is already well-positioned to benefit. While it may take a while for NVIDIA investors to see the payoffs, the company is fast-growing its automotive segment and there's no doubt that it will benefit from the shift from traditional to autonomous cars.
NVIDIA's AI supercomputing solutions are finding applications beyond the sector of connected autonomous cars. A new IBM supercomputing server, already used by large clients, is powered by NVIDIA technology to accelerate critical applications such as advanced analytics and deep learning for Big Data.
Huang announced new partnerships with high-profile AI research centers in Europe and the US, which are using NVIDIA's DGX-1 AI supercomputers. According to NVIDIA, the DGX-1 is a system for deep learning that can be deployed quickly and easily, with revolutionary performance and fully integrated hardware and software.
But the new partnership with enterprise software giant SAP seems more interesting in terms of shorter term revenue prospects. SAP is now using DGX-1 AI supercomputers at its operations in Potsdam, Germany, and in Israel, where teams are building machine learning solutions for enterprises.
"Now with the partnership of SAP we will soon have applications running on these servers to serve the world's largest enterprises," said Huang.
NVIDIA stock outperformed all other tech stocks in the last year, and the company is pursuing an aggressive strategy in the hottest technology sectors. Investors should feel confident that NVIDIA stock will continue to be a winner and perform above market.
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