Overview
- Clem Delangue told an Axios event that today’s exuberance centers on large language models and said the bubble might burst next year.
- He contends many tasks are better served by cheaper, faster, specialized models rather than one model meant to handle everything.
- As an example, he pointed to bank customer chatbots that can run on a company’s own infrastructure without relying on a general-purpose LLM.
- Delangue said a downturn in LLM valuations could affect Hugging Face to a degree, but he argued the wider AI field remains diversified.
- He emphasized financial prudence, noting Hugging Face still holds roughly half of the $400 million it has raised and is focused on long-term sustainability.