00:00Michelle Guida, CEO of the Crack Institute for Tech Diplomacy at Purdue and also a former assistant secretary of state
00:06for global public affairs under the first Trump administration,
00:09writes the U.S. won't be able to win the AI race simply by limiting China's technology and joins us
00:16now.
00:17And frankly, that's where the debate is.
00:19You know, you would have seen the headlines this morning and the open letter essentially on open weight.
00:25The timing of that, there must be a reason for it.
00:30Well, what I think you're actually seeing, Ed, is a really good example of Silicon Valley and Washington, D.C.
00:35talking past each other.
00:37Because if you look at that letter, the real debate isn't about open weight models.
00:42It's about Chinese open weight models, which unfortunately are the most available, most price effective option that's on the table
00:50right now,
00:51and especially for a lot of new businesses and startups that are trying to build their AI stacks.
00:57And so the real debate is on Chinese open weight models.
01:00And the problem there is we know that presents national security risk.
01:04We know it presents corporate risk, given all that we know about Chinese technology being untrustworthy.
01:09It's why we've banned Huawei.
01:10It's why we banned and then had to restructure TikTok.
01:13It's why there's legislation moving through the House right now about banning connected vehicles that are coming from China.
01:20And so there's a pattern here, and I think the focus on what do we ban versus what do we
01:26keep open is actually misplaced focus by both the private sector and the U.S. government.
01:30The focus should be on how do we turbocharge America's open weight ecosystem so we have a world-class, robust,
01:39really price effective offering for the rest of the world
01:41so we can diffuse American AI as fast as possible, and not only overseas, but here at home where businesses
01:47are trying to grow.
01:48On the here at home bit, I've read the open letter as many times as I could before we came
01:54to air, and I'm thinking, what is the concern?
01:57What catalyzed them writing it and putting it out?
02:00One take is the concern that Washington just over-regulates open source models, right, in a way that is detrimental
02:10to American interests.
02:11Where do you sort of sit on that debate?
02:15Yeah, well, I think it's because open weight models, cheaper open weight models, have become really core to a lot
02:21of how businesses are developing their AI stacks.
02:24As you mentioned earlier, we just saw a big tech wipeout, $890 billion, because AI is really expensive.
02:30Everybody's looking to see if we can keep up with this spending bubble.
02:33And so the cheaper, good enough versions are really important for our private sector to be building their AI stacks.
02:40The problem is it comes from an adversary, and there is no really robust U.S. trusted alternative to the
02:47Chinese open weight models that we're seeing.
02:48And then the Kimi 3 launch this week catalyzed our awareness of that.
02:53And so the debate now is not really just open weight, it's Chinese open weight, and can we get an
02:57American alternative out there fast?
03:00So NVIDIA CEO Jensen Wang did sort of an extended interview with Axios and basically said, you know, the top
03:07lines are that the Chinese models are excellent and that the open source models that are excellent too should be
03:15used.
03:15And so, you know, based on your line of argument that the risk is too great if the open model
03:20comes from an economic adversary, it comes down to how influential is Jensen Wang with this administration?
03:29Well, I actually think it comes down to how fast can we turbocharge an American open weight ecosystem.
03:35Look, all the things that he's saying and other Silicon Valley leaders are saying make sense if you're looking at
03:40this purely through an innovation and a commercial lens.
03:44It makes a world of sense.
03:45If you then factor in the communist adversary lens, the risk calculus looks a whole lot different.
03:50And that's why these technologies are different.
03:52Look, we just spent, Ed, the better part of a decade with businesses thinking about how they decouple and they
03:59de-risk from China because of the supply chain risk, the financial risk, the corporate risk, the national security risk.
04:05And now we're talking about entrenching Chinese technology into the very foundation of our American companies' AI stacks.
04:13Like, that makes no sense.
04:15And so how do we focus instead on getting trusted American AI, cheap, effective, price-effective AI into the hands
04:24of American companies and as much of the world as possible?
04:26That's where the focus needs to go.
04:29Let's go back to the beginning.
04:30You know, your argument through the lens of policy research reflecting on your time in government is that at the
04:36end of the day, America won't win the AI race by restricting China.
04:41So you indicate that America needs to be proactive in its own approach, get its own house in order.
04:48How far does today's action go?
04:51What else needs to be done?
04:54Yeah, I think, look, the president has this great group on his PCAST, this presidential advisory board with a bunch
05:00of technology leaders.
05:01I think they should get in a room as quickly as possible and figure out how they go on offense
05:06really quickly with American open-weight AI.
05:09And, by the way, get all of our allies on board because even if we ban and limit the use
05:14of Chinese technology, Chinese AI models here, if we're using AI models from America here, but the rest of the
05:21world is running on a Chinese AI stack, it's still a problem for us.
05:24And so I think they can rally around that.
05:26And, look, we have a lot of lessons.
05:28When I was at the State Department, Huawei was a threat across the world.
05:32And there's a lot of lessons to be learned there.
05:34And a big lesson is that we're not going to win on principle.
05:38We're going to win on price.
05:39So how do we get much more cost-effective, trusted American AI open-weight models out into the world now?
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