Clem Delangue, co-founder and CEO of Hugging Face, has voiced a nuanced perspective on the current fervor surrounding artificial intelligence. Speaking at an Axios event, Delangue asserted that the industry is not experiencing a general AI bubble, but rather an "LLM bubble" focused specifically on large language models, which he believes may be poised to burst.
While acknowledging that discussions around an AI bubble represent a "trillion-dollar question" today, Delangue remains confident that the broader future of AI is not at risk, even if the LLM segment faces a downturn. His primary concern is the disproportionate attention and investment directed towards large language models (LLMs) like those powering popular chatbots such as ChatGPT and Gemini.
"I think we're in an LLM bubble, and I think the LLM bubble might be bursting next year," Delangue explained. "But 'LLM' is just a subset of AI when it comes to applying AI to biology, chemistry, image, audio, [and] video. I think we're at the beginning of it, and we'll see much more in the next few years."
Delangue argues that LLMs are not a universal solution for every problem. He anticipates a future where smaller, more specialized AI models will gain significant traction due to their efficiency and targeted capabilities. He criticized the prevailing notion that a single, massive model, built with extensive computational resources, can solve all problems for all companies and individuals.
"I think all the attention, all the focus, all the money, is concentrated into this idea that you can build one model through a bunch of compute and that is going to solve all problems for all companies and all people," Delangue stated. "I think the reality is that you'll see in the next few months, next few years, kind of like a multiplicity of models that are more customized, specialized, that are going to solve different, different problems."
As an example, he cited a banking customer chatbot. For such a specific application, Delangue suggests that a smaller, specialized model is far more appropriate. "You don't need it to tell you about the meaning of life, right? You can use a smaller, more specialized model that is going to be cheaper, that is going to be faster, that maybe you're going to be able to run on your infrastructure as an enterprise, and I think that is the future of AI," he elaborated.
Despite his predictions, the Hugging Face founder conceded that an LLM bubble bursting could impact his company to some extent. However, he emphasized the vast and diversified nature of the AI industry, suggesting that even if a portion, like LLMs, is overvalued, it won't severely affect the overall AI field or Hugging Face's business.
Hugging Face itself maintains a cautious financial strategy, notably retaining half of the $400 million it has raised. This capital-efficient approach stands in contrast to the significant spending habits of many other AI companies, particularly within the LLM sector, where investments often run into billions of dollars.
"In AI standards, that's called profitability because the other guys — it's not hundreds of millions that they're spending. It's obviously billions of dollars," he remarked, highlighting Hugging Face's prudent financial management.
Delangue attributes his company's measured strategy to his extensive experience in the field. "I think a lot of people right now are rushing — or maybe even panicking — and taking a really short-term approach to things. I've been in AI for 15 years now, so I've seen some of the cycles," Delangue added. "And so we're learning from that and trying to build a long-term, sustainable, impactful company for the world."
