Is the Generative AI Hype Fading?

Published Date: 6/08/2024

The value of top tech stocks, including Nvidia, has been falling, and investors are losing confidence in generative AI technologies.

The past couple of weeks have been rocky for the S&P 500's top tech stocks, including Alphabet Inc., Apple Inc., Amazon.com Inc., Meta Platforms Inc., Microsoft Corp., Nvidia Corp., and Tesla Inc.  These seven corporations represent a significant portion of the US stock market, and their decline in value has pushed down the overall public market, causing panic among investors.

On Monday, the panic reached a fever pitch as global markets tumbled, with Big Tech taking the biggest hit.  At one point, Nvidia was down over 7%, and the Magnificent Seven lost more than $500 billion in market capitalization.

So, what's behind this sudden downturn?  It looks like the generative AI bubble is finally bursting.  I wrote in April that generative AI technologies look like money pits with significant social costs attached - and it seems I was right.

Several analyst and investor reports have come out recently, making similar points.  David Cahn at Sequoia argued that generative AI needs to generate $600 billion in revenues to pay back current infrastructure spending - and we're nowhere near that.  Jim Covello at Goldman Sachs argued that, in light of future expected infrastructure investment, generative AI needs to find a $1-trillion problem to solve - but it's still unclear what that problem is.

All of this highlights the problem of putting too much money into one technological bet when it doesn't offer a clear case for doing so.  Ross Sandler at Barclays Bank pointed out that the investment in generative AI is large enough for 12,000 new products - which sounds like an extraordinary number, but not in a good way.

While generative AI may be faster, it raises costs six-fold, and the International Energy Agency has calculated that an AI-driven search application requires ten times the electricity of regular search.  This means that generative AI not only requires significant investment in energy infrastructure, but it's also going to increase energy costs across the board.

Other studies have shown that generative AI is not doing what its boosters promised, namely raising productivity.  Forbes reported on research by the Upwork Research Institute, which found that 77% of employees using AI say it has added to their workload and created challenges in achieving expected productivity gains.

So, why do so many people buy into the generative AI hype?  I think there are at least three reasons for this.  First, all bubbles are driven in part by a self-fulfilling fear of missing out.  Investors know that a bubble is a bubble, but they have to participate because they still make money.

Second, generative AI technologies are currently underpriced or free.  As Cahn noted, going forward, firms will need to start generating revenues from their technologies, which means charging for them.  Customers are unlikely to pay for technologies with ambivalent functionality, and investors are coming around to this perspective.

Lastly, generative AI technologies have enabled some corporations to capture more revenues from their operations.  Finance YouTuber Sasha Yanshin pointed out that Alphabet's paid clicks through Google Search have increased 5%, while impressions through Google Network have fallen 13%.  This is because AI-driven Search keeps users on Google's own platforms rather than sending them to their Network partners, enabling them to capture more advertising revenues.

FAQS:

Q: What is generative AI?

A: Generative AI refers to a type of artificial intelligence that can generate new data, such as text, images, or music, based on patterns learned from existing data.

Q: Why is the value of top tech stocks falling?

A: The value of top tech stocks is falling due to a decline in investor confidence in generative AI technologies, as well as concerns about their social costs and potential impact on productivity.

Q: How much does generative AI need to generate in revenues to pay back current infrastructure spending?

A: According to David Cahn at Sequoia, generative AI needs to generate $600 billion in revenues to pay back current infrastructure spending.

Q: What is the impact of generative AI on energy costs?

A: According to the International Energy Agency, an AI-driven search application requires ten times the electricity of regular search, which means that generative AI will increase energy costs across the board.

Q: Why do investors still invest in generative AI despite the concerns?

A: Investors still invest in generative AI because they fear missing out on potential profits, despite knowing that it's a bubble. They also hope to make money from the hype surrounding the technology.

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