Hugging Face's Clem Delangue on Open Source AI and the LLM Bubble | MTS Live
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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. Why? Because it is too dangerous. Some people can punch. Right? But in reality, 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? So you have to fight it, but not by preventing everyone from getting these capabilities. Otherwise, y
This episode originally aired on NPS. Open source software built much of the modern Internet. Linux, Apache, Kubernetes, and even the transformer architecture behind Chachi PT, 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 politic
We are live here on MTS with Clement Delong, who is the CEO of Hugging Face, which has been really an incredible resource for anyone who's interested in large language models and especially open weight large language models. I've been a Hugging Face user for a while now, so it's great to have
you here.
Clem, thanks so much for coming on MTS.
Yeah. Of course. Thanks for having me.
Absolutely. Okay. So you are a big proponent of open source. First of all, how do you predict and you believe that open source is like a very important, you know, thing for innovation and competition. So can you compare and contrast sort of like the open source environments in The US and China to start?
Yeah. So, I mean, historically, The US was super, super strong with open source. Right? That's kind of like what led to current AI revolution. Right? Like, T in chat, GPT, is actually coming from Transformer, which was open source from from Google. Unfortunately, for the past past few years, this trend has has changed, and and things tended to kind of, like, close down in in The US and kind of, like, Frontier Labs more kind of like sharing their models behind, like, closed source APIs. The China, so the complete opposite movement. They're the strongest open source contributors today. If you as
Great. So you recently said we're in an LLM bubble. What makes you think that?
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