Foxconn and Nvidia collaborate to supercharge the AI industry
- A new collaboration between Nvidia and Foxconn starts with creating AI factories.
- Foxconn will also collaborate with Nvidia to put AI in cars.
- Foxconn’s Smart Manufacturing robots will utilize Nvidia’s Isaac™ autonomous mobile robot platform, while their Smart City will integrate the Nvidia Metropolis video analytics platform.
When graphics chipmaker Nvidia Corp announced at the beginning of this year that it is partnering with electronics componentmaker Foxconn Technology Group on electric vehicles (EVs), the tech giant’s goal was to continue its push into the booming EV market. Ten months later, both companies announced that they are expanding their decade-long partnership, this time to supercharge the AI industrial revolution.
Alongside Foxconn’s Chairman and CEO, Young Liu, the CEO of Nvidia, Jensen Huang, said that the world is at the beginning of a “new computing revolution, which leads to the eminence of a new type of manufacturing. “The production of intelligence and the data centers that produce it are AI factories,” Huang said during a fireside chat at Foxconn’s Tech Day.
That said, Foxconn, the world’s largest manufacturer, according to Huang, has the expertise and scale to build AI factories globally.
Foxconn will integrate Nvidia technology to develop a new class of data centers, or ‘AI factories’ as Huang put it, powering a wide range of applications — including the digitalization of manufacturing and inspection workflows, development of AI-powered electric vehicles and robotics platforms, and a growing number of language-based generative AI services.
“This factory takes data input and produces intelligence as its output. In the future, every company and industry will have AI factories. What we showed here today is Foxconn building an entire end-to-end system,” Huang explained. What he meant was that the collaboration would start with the creation of AI factories.
The AI factory will utilize an Nvidia GPU computing infrastructure specially built for processing, refining, and transforming vast amounts of data into valuable AI models and tokens — based on the Nvidia accelerated computing platform, including the latest Nvidia GH200 Grace Hopper superchip and Nvidia AI Enterprise software.
Huang shared an example of the collaboration by explaining how the AI factory will build Foxconn’s Model B EV concept car with its AI software. “This car will go through ‘life experience’ and collect more data, then go to the AI factory where the software will be improved to update the entire AI fleet. This entire end-to-end system – on one side AI factory, on the other, AI EV fleet – is what Nvidia and Foxconn are collaborating on,” Nvidia’s CEO said.
“Most importantly, Nvidia and Foxconn are building these factories together. We will be helping the whole industry move much faster into the new AI era,” Liu added.
AI factories for Foxconn and its customers
Foxconn is expected to build many systems based on Nvidia CPUs, GPUs, and networking for its global customer base. It wants to create and operate its AI factories optimized with Nvidia AI Enterprise software. Among the key Nvidia technologies Foxconn is using to create these custom designs are Nvidia HGX reference designs (featuring eight Nvidia H100 Tensor Core GPUs per system), Nvidia GH200 superchips, Nvidia OVX reference designs and Nvidia networking.
With these systems, Foxconn customers can leverage Nvidia accelerated computing to deliver generative AI services and use simulation to speed up the training of autonomous machines, including industrial robots and self-driving cars. In addition to equipping its customers with Nvidia technology-powered AI factories, Foxconn is eyeing its own factories that will tap into the Nvidia Omniverse™ platform and the Isaac and Metropolis frameworks to meet the electronics industry’s strict production and quality standards.
“Advances in edge AI and simulation are enabling the deployment of autonomous mobile robots that can travel several miles a day and industrial robots for assembling components, applying coatings, packaging, and performing quality inspections,” the company explained. An AI factory with these Nvidia platforms will allow Foxconn to accomplish AI training and inference, enhance factory workflows, and run simulations in the virtual world before deployment in the physical world.
Simulating the entire robotics and automation pipeline from end to end provides Foxconn with a path to operational efficiency gains, saving time and costs.
Foxconn and Nvidia beyond AI factories
Foxconn is also developing other smart solution platforms based on Nvidia technologies. The solutions are listed below:
- Foxconn Smart EV will be built on Nvidia Drive Hyperion 9, a next-generation platform for autonomous automotive fleets, powered by Nvidia Drive Thor, its future automotive systems-on-a-chip.
- Foxconn Smart Manufacturing robotic systems will be built on the Nvidia Isaac autonomous mobile robot platform.
- Foxconn Smart City will incorporate the Nvidia Metropolis intelligent video analytics platform.
Foxconn’s Liu also announced that his company would be delivering a range of Nvidia Drive solutions to global automakers, serving as a tier-one manufacturer of Nvidia Drive Orin-based electronic control units (ECUs) today and scaling to Nvidia Drive Thor-based ECUs in the future.
“As a contract manufacturer, Foxconn will offer highly automated and autonomous, AI-rich EVs featuring the upcoming Nvidia Drive Hyperion 9 platform, which includes Drive Thor and a state-of-the-art sensor architecture. This will enable Foxconn and its automotive customers to realize a new era of functionally safe and secure software-defined cars,” he concluded.
- Biometric tool from INTERPOL is a game changer in capturing most wanted criminals
- AI and the changing cyberthreat landscape make data management crucial in 2024
- Global semiconductor sales to pass US$588bn in 2024, fueled by memory surge
- Dell Technologies sees AI, zero trust, and quantum computing leading 2024
- IBM makes significant breakthrough in quantum computing