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Hugging Face's Clem Delangue on Open Source AI and the LLM Bubble | MTS Live

5/22/202616 min

Clem Delangue joins MTS to discuss the global open-source AI landscape, the current large language model bubble, and the future of consumer robotics.

Originally aired on MTS, Theo Jaffee and Sofia Puccini speak with Clément Delangue, CEO at Hugging Face, about the global open-source AI race, why he believes the real bubble is in API-based large language models, and how robotics could become the next major interface for AI. They also discuss AI safety, U.S.-China competition, open-weight models, and why Hugging Face became the infrastructure layer for open AI development.

 

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Clips

Transcript preview

First 90 seconds
  1. Clément Delangue· Guest0:00

    The idea of, like, restricting a technology like AI based on risks is just like, for example, you would say, "Okay, some people can punch other people, so let's tie down everybody's hands," right? Because it is too dangerous. Some people can punch, right? But in reality, [laughs] you don't wanna do that because your hands are so useful. The way you wanna control it is untie everyone and then regulate or fight the bad actors. So for example, if hacking that creates cybersecurity risks, it's illegal, right? [laughs] So you have to, to fight it, but not by preventing everyone from getting these capabilities. Otherwise, you slow down progress, you create massive gaps in terms of controls, in terms of capabilities, and you create actually a-additional risks.

  2. Speaker 10:50

    This episode originally aired on MTS. Open source software built much of the modern internet. Linux, Apache, Kubernetes, and even the transformer architecture behind ChatGPT all spread because researchers and developers could study, modify, and improve them in public. But AI is increasingly moving in the opposite direction, with the most powerful models distributed behind closed APIs controlled by a small number of companies. At the same time, China has emerged as one of the biggest contributors to open source AI, while debates around safety, regulation, and access are becoming more

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