NVIDIA CEO Huang urges faster AI development—to make it safer

At a time when some are calling for a pause on the development of generative artificial intelligence, Jensen Huang, founder and CEO of NVIDIA, has an argument for accelerating the work: AI advances are going to provide tools to better understand the technology and to make it safer, Huang said in a discussion with Goldman Sachs Asset Management.

“We need to accelerate the development of AI as fast as possible, and the reason for that is because safety requires technology,” Huang said in an interview at The Forum with Sung Cho, co-head of Tech Investing for Fundamental Equity in GSAM. The Forum is a daily meeting at GSAM, and a core part of its investment culture, that convenes leading experts to discuss global trends that impact our investments.

Consider how much safer today’s passenger cars are compared with those of earlier generations, Huang suggested, because the technology has advanced. He cited as an example how OpenAI’s ChatGPT uses reinforcement learning from human feedback (RLHF) to create guardrails that make its responses more relevant, accurate, and appropriate. The RLHF is itself an AI model that sits around the core AI model.

Huang lists examples of other AI technologies that hold promise for making the models safer and more effective. These range from retrieval augmented generation, in which the model gets information from a defined knowledge base or set of documents, to physics-informed reinforcement learning, which grounds the model in physical principles and constraints.

“We need a bunch more technology like that,” Huang said.

NVIDIA makes graphics processing units (GPUs) that provide computing power for developing generative AI models, some of which are trained on more than a trillion parameters.

Huang believes the direst warnings about AI are overblown. “In the final analysis, what is AI? It’s going to come into the world as a product or service,” he says. And it will end up being regulated under the existing framework for each specific industry where it’s adopted, he added.

In his view, that means AI in automobiles will be evaluated by the National Highway Transportation Safety Administration, AI in planes will be tackled by the Federal Aviation Administration, AI involved in something you consume may be the purview of the Food and Drug Administration, and so on. 

What Huang rejects is the idea of a “universal, galactic, planetary” governance system for all things AI. No one, he says, could possibly have so much knowledge about generative AI technologies to do that effectively.

Huang said he sees enormous potential for new generative AI capabilities to drive growth for many businesses, with large enterprise software providers among the biggest beneficiaries initially. Many are already beginning to add AI-powered technologies to their products, providing an opportunity to boost revenue from their existing customer base. Business database providers, for example, are working to enable retrieval augmented generation, he said. 

“My guess is that AI will help the providers of today’s services and applications the most,” Huang said. “They all have to find their AI moment.”

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