Nvidia Aims for $32.5B in Q3 Revenue, Guarantees Rapid AI Infrastructure Profits

Analysts peppered the CEO with questions about the return on AI spending. His response was several versions of: “people who invest in Nvidia’s infrastructure get immediate returns.”

While Nvidia’s biggest customers have yet to boast a significant return on their billions in AI investments, Huang looked at several places where he sees returns.

GPUs speed everything up

“Accelerated computing, of course, accelerates applications. It also allows you to do computation on a much larger scale, for example scientific simulations or database processing,” Huang said.

“Accelerated computing” is Huang’s term for the kind that Nvidia’s GPUs enable. Also called parallel computing, where chips perform many tasks simultaneously and not in a sequence. This is the foundation of generative AI, and Huang argued that almost all existing computing jobs are moving in this direction for one major reason.

“It’s not uncommon to see someone save 90 percent of their computing cost” when they convert to accelerated computing, Huang said. The reason, he continued, is “you’ve sped up an app 50 times. You would expect the computational cost to drop quite significantly.”

Targeting consumers

Recommendation engines, such as those that tell you what to post next, and digital ad targeting were two modern data processing tasks that are quickly converting to accelerated computing, Huang said.

Cheaper, more accurate recommendations and more targeted ads could generate more revenue for companies that adopt those technologies. Meta, for example, has grown its bottom line in recent years by using AI to improve content recommendations and ad targeting.

Sophia Velastegui, a venture capitalist and former Microsoft AI director, told Insider that identifying the return on investment in artificial intelligence may not be easy because it is embedded in these everyday functions of the Internet.

“You may not be able to say, ‘Hey, this growth is specifically from generative AI,'” Velastegui said. She added that companies may be reluctant to disclose details of their AI gains for competitive reasons.

The wave of the AI ​​cloud

The third pillar of Huang’s AI ROI, at least for cloud providers, is the frenzy of startup development in generative AI applications.

The biggest cloud computing providers, including Amazon and Microsoft, are important customers of Nvidia. When they buy GPUs, they put them in data centers and get paid relatively quickly for renting this new AI computing capacity.

“Anything you raise, you’re going to be rented because there are so many companies being set up to create generative AI, and so your capacity is rented immediately, and the return on investment is very good,” Huang said.

Indeed, Nvidia has propelled a host of new or reimagined cloud providers that purchase chips almost exclusively from Nvidia and specialize in the latest and greatest in AI computing.

It will be difficult to assuage investors’ concerns in this area because, ultimately, Huang is not the executive they need to hear the message from. And what they’ve heard from other top tech executives and Nvidia’s top customers is the call for patience.

Meta spent 8.5 billion dollars in the second quarter on computing infrastructure for AI and the metaverse. It plans to spend between $37 billion and $40 billion this year, although CEO Mark Zuckerberg told investors in July not to expect immediate returns.