The former CEO of Google, Eric Schmidt, who led the technology giant thanks to the collapse of the Dot-Com bubble in the early 2000s, says that the boom of current artificial intelligence is fundamentally different and that it would undergo a similar spell.
Speaking at the top of the increase in Paris, Schmidt responded to the growing concerns that AI could go to bubble territory, especially while Wall Street Voices Prudence and large technological companies pay billions in the sector.
“I think it is unlikely, based on my experience, that it is a bubble,” said Schmidt. “It is much more likely that you see a whole new industrial structure.”
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His comments arise at a time when the rapid expansion of the AI made comparisons with the technological boom – and the blow of the 1990s. Since Chatgpt d’Openai has broken down in the dominant current, the AI was plunged into the center of global technological innovation, large companies like Microsoft, Amazon, Google, Meta and Nvidia investing in the IA infrastructure talents and startups.
According to market studies mentioned at the summit, the AI sector was estimated at $ 189 billion in 2023, with projections showing a dazzling increase to 4.8 billions of dollars by 2033. But with this growth came from the skepticism of the financial circles.
Torsten Sløk, chief economist at Apollo Global Management, recently warned that the US stock market is experiencing an even larger bubble than during the Dot-Com boom. In a research note published Wednesday, Sløk blamed what he described as an irrational exuberance around AI.
“The difference between the computer bubble in the 1990s and the Bulle of IA today is that the 10 best companies in the S&P 500 today are more overvalued than they were in the 1990s,” wrote Sløk, warning that the rise may disconnect from the underlying benefits.
Schmidt, however, rejected the idea that the evaluations of them alone prove a bubble. He underlined the investment of the AI industry in physical infrastructure – in particular high performance computer equipment – as a sign of long -term viability.
“You have these massive data centers, and Nvidia is very happy to sell them all the chips,” said Schmidt. “I have never seen a situation where the hardware capacity has not been taken care of by software.”
The former Google chief, who currently has participation in AI startups such as Anthropic, has recognized that there are concerns within the industry. Some leaders admitted that they have “over-built” the data infrastructure and anticipate overcapacity in the two to three years. Schmidt told conversations with leaders who say in private: “I’m fine and the other guys will lose all their money”. It’s a classic bubble, right?
However, he argued that dichotomy within the industry – between overcapacity fears and beliefs in transformative breakthroughs – explains to what extent the AI landscape remains early and dynamic. Schmidt has described certain pioneers of the AI of the Bay region who believe that technologies such as the learning of strengthening will fundamentally redefine human society.
“If you believe that these will be the determining aspects of humanity, then it is undervalued and we need it even more,” he said.
Adding to the conversation, Nvidia, who became the child of the AI Boom poster with an increase of 173% of the action course in 2024 only, also announced a split of 10 to 1 and a hike of dividends earlier this year, movements that reflect investors’ demand. Revenues from its data centers led $ 22.6 billion in the last quarter, up more than 400% in annual sliding, pulled by cloud suppliers and AI startups to extend IT capacity.
However, for some, they are red flags. With Nvidia negotiating around 40 times the long -term profits – higher than the peers of most major capitalizations – some market observers argue that the company embodies the type of flight evaluations which recall the technological enthusiasm of the 1990s.
Despite these fears, Schmidt’s position indicates that although AI can be in a phase of frantic investment and occasional irrational behavior, the underlying transformation is real and global. For him, investments in hardware, software and automatic learning infrastructure indicate a structural change rather than a speculative point.
