Clem DeLang, co-founder and CEO of Hugging Face, says it’s not an AI bubble but an “LLM bubble” that may be ready to burst. At Tuesday’s Axios event, the entrepreneur behind the popular AI platform and community site agreed that the bubble story is today’s “multi-trillion dollar problem,” but said he doesn’t think the future of AI is in jeopardy if the bubble bursts.
Instead, large-scale language models (LLMs), like those powering ChatGPT, Gemini, and other chatbots, are getting a lot of attention, and that attention may not last, in Delang’s view.
“We are in an LLM bubble right now, and I think the LLM bubble may burst next year,” Delangue explained. “But in terms of applying AI to biology, chemistry, images, audio, (and) video, ‘LLM’ is just a subset of AI. I think we are still at the beginning of it, but there will be a lot more to come in the next few years,” he noted.
He argued that one of the issues is that LLM is not a one-size-fits-all solution and that the adoption of smaller, more specialized models will increase in the future.
“I think all the attention, all the focus, all the money is focused on this idea that with a lot of computing you can build one model and solve all the problems for all the companies and all the people,” Delangue said. “The reality is that in the coming months and years, I think we’re going to see something like a number of models that are more customized, more specialized, and solve different problems.”
As an example, he suggested the use case of a bank’s customer chatbot.
“We don’t need AI to tell us the meaning of life, right? With smaller, more specialized models, it’s cheaper, faster, and maybe we can run it on our infrastructure as a company. I think that’s the future of AI,” DeLang noted.
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The Hugging Face founder acknowledged that the bursting of the LLM bubble could have some impact on his company, but noted that the AI industry is very large and already diverse. This means that even if some parts of the industry, like LLM, are overvalued, it won’t have a huge impact on the AI field itself or his business.
Additionally, he noted that Hugging Face still has half of the $400 million it raised in the bank. This cautious approach to spending represents a different strategy than what other AI companies have been doing lately, especially in the LLM space.
“In AI standards, we call that profitability, because what other people are spending isn’t hundreds of millions of dollars. It’s clearly billions of dollars,” he said.
In comparison, Hugging Face takes a more capital efficient approach.
“I think a lot of people are rushing or panicking right now and taking a very short-term approach. I’ve been in AI for 15 years, so I’ve seen several cycles,” DeLang added. “So we’re trying to learn from that and build a company that is long-term, sustainable, and has an impact on the world.”
