How AI and 5G will power the next wave of innovation
Here are four real-world examples of where the combination of AI and 5G connectivity is reshaping industries.
By Zeus Kerravala | September 10, 2021 -- 22:54 GMT (15:54 PDT) | Topic: 5G
In the next 10 years, artificial intelligence is expected to transform every industry, and the catalyst for this transformation is 5G. Together, the two technologies will enable fast, secure, and cost-effective deployment of internet of things devices and smart networks.
AI-powered 5G networks will accelerate the "fourth industrial revolution and create unprecedented opportunities in business and society," Ronnie Vasishta, senior vice president of telecom at graphical chipmaker and software platform developer NVIDIA, said in a special address at the 2021 Mobile World Congress in Barcelona several we ago.
"Billions of things are located throughout the network and data centers. A ubiquitous 5G network will connect these data centers and intelligent things at the rate, latency, cost, and power required by the application," Vasishta said. "As this network morphs to adapt to 5G, not only will AI drive innovation, but it will also be required to manage, organize, and increase the efficiency of the network itself."
Unlike previous wireless tech generations, 5G was born in the cloud era and designed specifically for IoT. 5G can connect billions of sensors—such as video cameras—to edge data centers for AI processing.
Every industry will be transformed
Here are four real-world examples of where the combination of AI and 5G connectivity is reshaping industries:
- Thousands of cameras monitoring automated vehicle assembly. Visual inspection software with deep learning algorithms is used to recognize defects in vehicles. This allows car manufacturers to analyze and identify quality issues on the assembly line.
- Urban planning and traffic management for smart cities. In an environment where massive amounts of people and things interact with each other, AI-powered visual inspection software monitors all moving and non-moving elements to improve city safety, space management, and traffic.
- Conversational AI and natural language processing enabling future services. Chatbots, voice assistants, and other messaging services are helping various industries automate customer support. Conversational AI is evolving to include new ways of communicating with humans using facial expression and contextual awareness.
- Powerful edge computing for extended reality.Virtual reality and augmented reality are no longer tethered by cables to workstations. Thanks to advanced wireless technologies such as 5G, industry professionals can make real-time design changes in AR or be virtually present anywhere in VR.
NVIDIA has been developing AI solutions for more than a decade, working with an extensive ecosystem of independent software vendors and startups on the NVDIA platform. The company recently partnered with Google Cloud to establish an AI-on-5G Innovation Lab, which network infrastructure and AI software providers will use to develop, test, and launch 5G/AI apps.
NVIDIA's AI-on-5G portfolio includes a unified platform, servers, software-defined 5G virtual radio area networks, enterprise AI apps, and software development kits such as Isaac and Metropolis. A commercial version of NVIDIA AI-on-5G will become available in the second half of this calendar year.
NVIDIA Aerial A100 is built for the 5G era
Back in April, NVIDIA launched Aerial A100, which, according to Vasishta, is a "new type of computing platform designed for the (network) edge, combining AI and 5G into EGX for the enterprise." NVIDIA EGX is an accelerated computing platform that allows continuous streaming of data between 5G base stations, warehouses, stores, and other locations. When implementing EGX with Aerial A100, organizations get a complete AI suite of capabilities.
5G and AI infrastructures today are inefficient because they're deployed and managed separately. For enterprises, running AI and 5G on the same computing platform reduces equipment, power, and space costs, while providing greater security for AI apps. For telcos, deploying AI apps over 5G opens up new uses cases and revenue streams. They can convert every 5G base station to an edge data center to support both 5G workloads and AI services.
Telcos and enterprises can greatly benefit from converged platforms like NVIDIA's AI-on-5G, where 5G serves as a secure, ultra-reliable, and cost-effective communication fabric between sensors and AI apps.
Nvidia eyes ARM roadmap for AI, 5G integration from server to card to chip
First use cases of AI on 5G will be enterprise computer vision apps that need 5G bandwidth, such as to a shop floor.
By Tiernan Ray | June 28, 2021 -- 13:24 GMT (06:24 PDT) | Topic: Artificial Intelligence
Nvidia on Monday announced it would be offering its converged 5G and artificial intelligence infrastructure to support not only x86 chips from Intel and AMD but also chips from ARM Ltd., the microprocessor intellectual property company that Nvidia is in the process of buying.
"ARM is a leading provider of 5G in mobile handsets, but as 5G RAN host infrastructure evolves, there is increasing demands to deliver the kinds of high performance, low power-per-watt that ARM CPUs are known for," said Ronnie Vasishta, head of telecom products at Nvidia.
"We believe that AI and machine learning is going to be an essential element of 5G networks, and AI and 5G are already essential elements of the applications that run on top of a 5G network," said Vasishta. Hence, there is a need to put AI acceleration next to network elements that run the radio access network, or RAN, stack, he said.
Nvidia had already announced in April, at its annual GTC conference, its partnerships to develop the 5G machines; the element of ARM-based chips is the new factor with Monday's press release.
The announcement comes on the opening day of the Mobile World Congress trade show in Barcelona, which was moved from its usual slot in February. It had been canceled in 2020 amidst the coronavirus pandemic.
The machines, which Nvidia refers to as AI-on-5Gon a server, will consist of three parts: an Nvidia A100 GPU, a BlueField 2 data processing chip, or DPU, created from the assets that Nvidia acquired with Mellanox; and a processor, either ARM or x86. The machine runs Nvidia's Aerial A100 software stack for 5G networking and the various Nvidia AI libraries, such as CuDNN.
Nvidia's roadmap specifies collapsing the server parts into a single board in 2022, consisting of an A100 GPU and a BlueField 3 DPU with embedded ARM cores, followed by the BlueField 4 DPU around 2024 that will combine ARM cores and GPU on a single DPU die.
Nvidia
Nvidia
Nvidia has a roadmap that extends beyond the initial server configuration. The next step, coming sometime next year, is what Nvidia calls "AI-on-5G on a card." That brings A100 to a plug-in card with the next version of the DPU, BlueField 3, which will combine 16 embedded ARM "A-78" cores on the die, a "CPU cluster," as ARM puts it.
"This means you no longer need an external host," said Vasishta, what the company considers "self-hosted."
Next, sometime around 2024, Nvidia will offer a converged part containing GPU plus DPU plus ARM cores on a single die, the so-called BlueField 4 part. That chip is unrelated to the Grace ARM-based CPU that Nvidia disclosed in May.
The premise for combining AIwith 5G is the renovation of society, from retail selling to industrial transpiration, said Vasishta.
"Every industry will be transformed in the next ten years because the forces of artificial intelligence and 5G connectivity are combining with digital automation to drive a revolution called the fourth industrial revolution."
Corporations want to use that combination of AI and 5G on open systems computing, including industry-standard servers, argued Vasishta.
"That's where the value is, the applications that will run on 5G."
Applications of the devices will initially lie in the domain of computer vision, Vasishta said in a media briefing.
"The first use cases are going to be using our Metropolis SDK, which is computer vision," said Vasishta. "Whether in a smart factory of retail, those elements of computer vision are becoming a lot more pervasive, and so are those 5G networks, because they need to move around, and so I think that would be one of the first [applications] you will see."
The first machines, coming later this year, are being built with partners including Mavenir, Radisys, Fujitsu, and Ericsson.
ARM technology has had a tough time cracking the data center, with only 1% of the world's data centers using ARM-based servers, Dion Harris, head of accelerated computing products at Nvidia.
To promote development on ARM, Nvidia is also offering a development kit that will include ARM CPUs from startup Ampere Computing Inc., and A100 GPUs, along with the BlueField 2 DPU.
Nvidia announced as well a collaboration with Google's cloud business unit to run an "innovation lab" to develop 5G applications. The company is in talks with other public cloud operators for similar initiatives, said Vasishta.
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