What is Nvidia (NVDA) CEO Jensen Huang's biggest worry?
“We have a lot of people on our shoulders, and everybody is counting on us,” Huang said when asked that question by Goldman Sachs CEO David Solomon at the Goldman Sachs Communacopia and Technology Conference.
“Demand is so great that delivery of our components, our technology, infrastructure, and software is really emotional for people," Huang added. "Because it directly affects their revenues, it directly affects their competitiveness.”
Investors and journalists lined up more than an hour before the session just to catch a glimpse of one of the world's most sought-after CEOs. Huang told the audience that although generative AI is still in its early days, it’ll expand beyond data centers.
“Now what’s amazing is, so the first trillion dollars of data centers is going to get accelerated and invented this new type of software called generative AI. Generative AI is not just a tool, it’s a skill," Huang told Solomon.
"For the first time, we’re going to create skills that augment people.”
Following Nvidia's brutal sell-off last week, Huang's keynote was seen as an opportunity to calm investors' nerves.
“The infrastructure players like ourselves and all the cloud service providers put the infrastructure in the cloud so that developers can use these machines to train the models and fine-tune the models, guardrail the models,” Huang said. “And the return on that is just fantastic.”
According to Huang, for every dollar a cloud service provider spends with Nvidia, it translates to $5 worth of rentals.
“I think the days of every line of code being written by software engineers, those are completely over,” Huang said. “The idea that every one of our software engineers will essentially have companion digital engineers 24/7 — that’s the future.”
For example, Huang shared that Nvidia has 32,000 employees who will be supplemented by “hopefully 100x more digital engineers” in the near future.
Nvidia servers "look expensive, and it could be a couple of million dollars per rack, but it replaces thousands of nodes," Huang said. "The amazing thing is the cables of connecting old, general purpose computing systems cost more than replacing all of those and densifying into one rack."
Companies such as Microsoft (MSFT), Meta (META), Amazon (AMZN), Google (GOOG, GOOGL), and OpenAI use Nvidia’s GPUs. Despite the tech giant reporting $30 billion in second quarter revenue, its stock fell by more than $200 billion on the same day.
Last week, Nvidia shed another $400 billion in market value following a Bloomberg report that the Department of Justice subpoenaed the company as part of an antitrust investigation. Nvidia denied the report.
“We have inquired with the US Department of Justice and have not been subpoenaed,” the company said in a statement. “Nonetheless, we are happy to answer any questions regulators may have about our business.”
Huang was not asked about the Bloomberg report on Wednesday. And despite the recent sell-off, Nvidia shares are up nearly 150% in the last 12 months.
Huang also said while training AI models is resource-intensive, it pays off in the long run.
“One of the takeaways there is AI isn’t just about training the model, of course; that’s just the first step,” he said. “It’s about using the model. And so when you use the model, you save enormous amounts of time — processing time.”
However, Huang said it’s amazing to watch the AI his company uses to design the chips. “The part of that that is really intense is just the world on our shoulders,” Huang said. “Less sleep is fine. Three solid hours is all we need.”
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Yasmin Khorram is a Senior Reporter at Yahoo Finance. Follow Yasmin on Twitter/X @YasminKhorram and on LinkedIn. Send newsworthy tips to Yasmin: [email protected]
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