Nvidia founder and CEO portrays AI-centricity

For fiscal 2022, Nvidia recorded revenue of $26.91bn, up 61% from $16.68bn a year ago. Fourth-quarter revenue from its datacentre chips rose to $3.26bn, up 71% from Q4 2021. The company is pushing a new software business model, with Nvidia AI, Nvidia Omniverse, the company’s play in the metaverse, and Nvidia Drive for autonomous vehicles.

Meta’s (Facebook’s) new AI Research SuperCluster system is being built using Nvidia’s technology and the company’s founder and CEO, Jensen Huang, sees a strong future for the application of artificial intelligence (AI) across different industries. In a transcript of the earnings call, posted on the Seeking Alpha financial blogging site,  Huang gave a snapshot of some of these AI application areas.

“The applications for AI are unquestionably growing, and growing incredibly fast,” he said. Existing application areas include fraud detection, customer service and conversational AI, where people speak to chatbots.

But in the future, said Huang: “Every website will have a chatbot, every phone number will have a chatbot. So customer service will be heavily, heavily supported by artificial intelligence in the future. Almost every point of sales, I think, will have chatbots and AI-based customer service.”

In his vision of how retail checkouts will be supported by AI agents, Huang said breakthroughs in computer vision will enable an AI to make eye contact and recognise the posture of a customer. He said the AI would also recognise speech, understand the context and what is being spoken about and have a reasonable conversation with people, which would enable retailers to provide good customer service.

“The ability to have humans in the loop is one of the great things about an AI much, much more so than a recording, which obviously is not intelligent and therefore it’s difficult to, if you will, call your manager or call somebody to provide services,” said Huang.

He said he anticipated huge growth in the use of AI across different application areas, and added: “I think we remain in the early days in our adoption, but it’s incredible how fast it has grown and how many different applications are now possible with AI. It pretty much says that almost all future software will be written with AI or by AI.

“And when it’s done, it will be an AI. And we see it in all these different industries. And so I’m pretty certain AI is going to be one of the largest industries of software that we have ever known.”

Around the world, said Huang, excluding public clouds, between 20 million and 25 million servers have Nvidia’s AI software installed. “We believe that every single server in the future will be running AI software. And we would like to offer an engine that enables enterprises to be able to use the most advanced, the most trusted, the most utilised AI engine in the world. And so that is essentially the target market for Nvidia AI.”

According to analyst firm GlobalData, Nvidia’s biggest customers, and potential customers such as Amazon, Google and Tesla, are developing their own AI processors. There are also a number of new competitors offering a compelling alternative for some organisations, according to Mike Orme, consultant analyst in the thematic research team at GlobalData.

He said: “Nvidia faces mounting competition from left field as a new breed of lavishly funded specialist AI companies, such as Cerebras, Graphcore and SambaNova, design AI chips from scratch, rather than adapting GPU technology.

“GSK and Argonne Labs in the US, for example, have both used Cerebras Wafer Scale Engines to power heavy-duty, real-world applications. Further, both reportedly outperform Nvidia GPU clusters while using much less energy. The battle lines have been drawn. How quickly can the upstarts scale up?”