Overview
- Clem Delangue argued the overvaluation is concentrated in large language models rather than the broader field of AI, which spans biology, chemistry, image, audio, and video.
- He criticized the industry’s focus on a single, compute-heavy general model, saying attention and money have been misallocated to the one-model-for-everything idea.
- As a practical example, he said a banking customer chatbot is better served by a cheaper, faster, specialized model that can run on enterprise infrastructure.
- Delangue said Hugging Face has retained roughly half of the $400 million it has raised, describing a capital‑efficient posture compared with rivals spending at multi‑billion‑dollar levels.
- He acknowledged a potential LLM correction could touch Hugging Face but emphasized the industry’s diversification and framed his approach with 15 years of experience building for the long term.