Marketplaces often say that the stock market is not an economy. But the stock market can also tell us where the economy is headed.
Case in point, computer chip designer Nvidia’s stock has more than doubled since the beginning of the year to about $300 a share. The Silicon Valley-based company currently has a larger market capitalization than Visa, Tesla and Facebook.
What makes investors so bullish on Nvidia? Two letters: AI.
Ask ChatGPT for a short essay on whether a hot dog is a sandwich or not and in seconds it will write 8 completely original and highly entertaining paragraphs. And there is a system of mathematics behind each of these paragraphs.
“That was about 400 trillion operations. That’s a lot,” Bernstein Research analyst Stacey Rasgon said.
ChatGPT requires a very powerful computer chip to perform all these operations behind the scenes, not to mention training the AI in the first place. There aren’t many companies making these chips at the moment.
“Nvidia is clearly leading, but others are far behind,” Rasgon said.
Companies like Intel specialize in traditional CPUs, the chips that power your PC and sequentially process one computing task at a time. Nvidia specializes in his GPUs, or graphics processing units. They are typically used for video games, but they are also multitasking wizards.
“When dealing with AI workloads, you need massive amounts of parallel computing,” explains Bank of America analyst Vivek Ariya. “That’s why customers don’t mind paying extra for those GPUs.”
Nvidia’s latest AI GPUs are priced at around $30,000 per chip. Aria expects the total market to reach about $80 billion in four years. Other semiconductor companies are also trying to get into the AI business, with Google and Amazon launching their own chip lines.
But Carson Elmgren, of Georgetown University’s Center for Security and Emerging Technologies, said it’s important to remember that Nvidia and other companies only design chips.
“They outsource all manufacturing to TSMC, a Taiwanese semiconductor manufacturing company based in Taiwan,” she said.
This leaves the entire AI industry vulnerable to supply chain issues and geopolitical threats.
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