Clem Delangue

The idea of like restricting a technology like AI based on risks is just like, for example, you would say, OK, some people can punch other people.

So let's tie down everybody's hands.

Why?

Because it is too dangerous.

Some people can punch.

But in reality, you don't want to do that because your hands are so useful.

The way you want to 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, you...

blow down progress, you create massive gaps in terms of controls, in terms of capabilities, and you create actually additional risks.

Yeah, so, I mean, historically, the US was super, super strong with open source, right?

That's kind of like what led to the current AI revolution, right?

Like the T in chat, GTT, is actually coming from Transformer, which was open source from Google.

Unfortunately, for the past few years, this trend has changed and things tended to kind of like close down in the US and kind of like frontier labs more kind of like sharing their models behind like closed source APIs.

China saw the complete opposite movement.

They're the strongest open source contributors today

If you ask most startups, most academia in the U.S.

that are using open source, they're usually using Chinese open source models.