At the Goldman Sachs tech conference, NVIDIA CEO Jensen Huang identified cybersecurity as AI’s next major use case, and said that AI automation of computer programming is changing the pace of cyber offense and defense from the ground up.
On Thursday, at a Goldman Sachs tech conference in San Francisco, Jensen Huang told the audience:
Cybersecurity is very likely to become AI’s next major use case.
He explained that AI models’ automation of computer programming is disrupting the cybersecurity industry because code is being exploited, and the speed at which fixes are needed has become extremely fast.
NVIDIA recently issued a strong long-term sales outlook last month, leading Wall Street to believe that massive AI data center spending will continue. Still, the market keeps demanding that the company prove these capital expenditures are creating real economic value. By pointing to cybersecurity at this time, Huang is effectively finding a new high-value outlet for AI computing power.
Meanwhile, Nvidia’s continuing flurry of M&A activity has also drawn market attention. The company announced last week that it would acquire AI startup Hugging Face for about $13 billion, further extending its footprint across the AI industry chain.
At the summit, Huang Renxun directly addressed outside doubts about the circularity of M&A, emphasizing that Nvidia’s investment decisions are based on a deep judgment of genuine demand.
AI accelerates programming automation, and cybersecurity faces a structural shock
At the summit, Huang Renxun explained the inherent logic between AI and cybersecurity: as AI dramatically lowers the threshold for writing code, the amount of code that can be exploited and the number of vulnerabilities requiring rapid patching are increasing in tandem. This is fundamentally reshaping the supply-and-demand structure of the entire cybersecurity industry.
He said:
What could create demand more effectively than making problems? Which company wouldn’t want its market to be mobbed by customers lining up to buy its products? There are responsible ways to achieve that—and less commendable ways.
This statement came after Nvidia released unexpectedly strong long-term earnings guidance last month. The guidance reinforced Wall Street’s confidence that spending on AI data centers will continue to expand, and it further strengthened the market’s view that Nvidia can keep benefiting from this trend.
In response to concerns from outside that heavy investment and acquisitions could distort the market, Huang Renxun clearly denied that there is any element of circularity. He said:
This isn’t a loop, because when we put in a little money, we get back a lot. People are starting to realize that wherever I invest, it isn’t a bad investment target—because I’m a professional investor and I take on no risk.
Huang Renxun said that before Nvidia makes an investment, it needs to see a “sure thing” opportunity. He defined the standard as: the potential target must already have customers waiting in line.
