Silicon Valley’s latest obsession with generative AI has tech investors and companies riding a wave of excitement, but some experts warn the bubble is set to burst.
Since OpenAI released ChatGPT less than two years ago, a torrent of venture capital has flooded AI startups, with investors pouring over $24 billion into the sector, according to EY.
Goldman Sachs predicts tech firms will shell out $1 trillion on AI infrastructure in the coming years.
Despite the hype, the return on investment has been lackluster. Howard Young from AAEON, speaking at the Reuters Momentum AI conference in San Jose, noted, “Everybody wants to make money in the AI race. The true, organic revenue, I don’t see it yet.” Young’s skepticism is echoed by others in the industry who believe generative AI’s capabilities are overstated.
Goldman Sachs’ chief global equity researcher, Jim Covello, highlighted this in a June newsletter, stating the technology is not yet practical. “If AI technology ends up having fewer use cases and lower adoption than consensus currently expects, it’s hard to see the massive returns investors are hoping for,” Covello said.
David Cahn of Sequoia pointed to a “speculative frenzy” in a June blog post, warning of widespread delusion in Silicon Valley. “We’re all going to get rich quick” seems to be the motto, but the reality may be far less rosy. Steve Blank from Stanford University likened the AI boom to the dot-com bubble, suggesting that a shakeout is necessary to separate the wheat from the chaff.
For Bay Area startups, the current climate is one where “You’re not getting funded unless you have AI in your title or story,” Blank said. He described the scene as “insane,” with investors chasing the next big thing. “One or two will strike gold, the rest are going to lose their shirt.”
Even if the AI bubble bursts, it might not be as catastrophic as the dot-com crash. Covello noted that many companies today are better capitalized. Yet, the grand promises of business transformation through AI remain largely unfulfilled. The technology still struggles to solve complex problems necessary for widespread automation.
Generative AI is also mired in legal battles over alleged copyright infringements, as major developers face lawsuits from artists, authors, and media outlets. Environmental concerns are growing too, with AI operations significantly increasing energy and water usage at tech giants like Google and Microsoft.
Moreover, generative AI is not without its social pitfalls. From spreading misinformation to aiding in scams and cheating, the technology has raised ethical concerns, prompting nearly 200 state legislative bills aimed at regulation last year.
Despite these issues, some industry leaders remain optimistic. Blank believes the challenges will be overcome, comparing the current state of AI to a “molten earth” just beginning to form continents. The potential applications of generative AI, if realized, could indeed reshape the business landscape.
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