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Ryan Knudsen (3:31)

In 2017, Beijing announced that it planned to lead the world in AI by 2030. But back then, the country was focused on a specific aspect of AI, something called computer vision.

Josh Chin (3:43)

So computer vision basically is exactly what it sounds like. It's a technique in which machines teach themselves how to recognize objects from coffee mugs, cats, dogs, airplanes, and people's faces. It is what's being used. Like when your phone is, like, categorizing your photos for you. That's computer vision.

Ryan Knudsen (4:04)

Why was Beijing investing so much in facial recognition technology?

Josh Chin (4:08)

That's an area that China, because it has this huge surveillance state, was really interested in, because it's just a much faster way to kind of track down people of interest, as they call them, which would be criminals, political dissidents, that sort of thing.

Ryan Knudsen (4:24)

But In November of 2022, the US jumped ahead when OpenAI released ChatGPT.

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The AI landscape as we know it.

Josh Chin (4:32)

Was rocked and forever changed, I think you can say, by a single chatbot, ChatGPT, which stands for generative, pre trained, transformer, essays, philosophical questions, even therapy. ChatGPT is a computer program that will write whatever you want quickly and convincingly.

Ryan Knudsen (4:51)

ChatGPT is a large language model, or LLM, that has much broader applications than computer vision. And since then, US companies have been pouring tens of billions of dollars into AI development and specifically into LLMs. And after ChatGPT, the advancements kept coming.

Josh Chin (5:07)

After OpenAI launched ChatGPT, Google started promoting its model. Facebook launched Llama. Anthropic came out with Claude. It was basically all American companies across the board. There were really no major competitors anywhere.

Ryan Knudsen (5:22)

El when the Soviet Union launched the Sputnik satellite in the 1950s, it jolted the US to speed up its own work on the space race. And the debut of ChatGPT was a similar wake up call for China.

Josh Chin (5:34)

That's when top Communist party officials really started to ramp up pressure on Chinese tech companies to do more. One major AI company told us that it received calls from 10 different government agencies in the space of a month as the Communist party was trying to catch up.

Ryan Knudsen (5:50)

Saying what? Like, get to work on AI?

Josh Chin (5:54)

Yeah. Basically.

Ryan Knudsen (5:59)

Beijing's strategy is to throw everything it has at the problem. That includes promoting AI in schools and at private companies and offering generous subsidies to industries that power AI development, like infrastructure and cloud computing.

Josh Chin (6:14)

So it's building computing clusters in these remote places with lots of cheap, renewable energy like Inner Mongolia. It eventually wants to connect, like, hundreds of data centers nationwide into what calls a national cloud for training and running models. It's putting, like, billions of dollars into expanding its power grid.

Ryan Knudsen (6:32)

Beijing has also been mobilizing local governments, which act essentially as the Communist Party's middle management.

Josh Chin (6:38)

And it's basically signaling to local governments, you know, that this is the big priority. So the local governments are going to their, the companies in their areas and really trying to get them going on AI efforts.

Ryan Knudsen (6:49)

This isn't the first time China has done something like this. When the country wanted to accelerate development of electric vehicles and renewable energy, it adopted a similar strategy.

Josh Chin (6:59)

I mean, a lot of economists will say will tell you that, like there's, there's a ton of waste in this approach in part because you have all these local governments all trying to compete with each other for Beijing's favor. But in some industries, like EVs, for example, or renewable power, it does have the ultimate effect of making China very competitive. Right, and also making it really hard in the global marketplace for companies from other countries to compete just because other countries don't have the level of state support for companies.

Ryan Knudsen (7:32)

And earlier this year, finally there was a breakthrough.

Josh Chin (7:35)

A new China based artificial intelligence startup is shaking up an industry known for its rapid innovation. It's called deepseek. Deepseek, the Chinese artificial intelligence intelligence upstart that rattled the American AI industry and the markets.

Ryan Knudsen (7:48)

This week, Deepseek, the Chinese artificial intelligence startup, dethroned ChatGPT on Apple's app store to become the store's top app. A Chinese startup named DeepSeek released a large language model.

Josh Chin (8:02)

It managed to build this model that was basically almost as good as the best model that OpenAI had.

Ryan Knudsen (8:06)

At the time, Deepseek hadn't initially benefited much from China's centralized AI efforts. It had largely been bankrolled by its founder's hedge fund and marched to its own beat. Still, what was notable about Deepseek was that it managed to build a model using much less computing power and a fraction of the money compared with OpenAI and other US companies.

Josh Chin (8:27)

There's some debate about some of their claims in terms of how they did this, but the bottom line is they sort of figured out how to engineer chips and algorithms in a way that just massively improved the efficiency of training a large language model. Marc Andreess, who's arguably Silicon Valley's most visible venture capitalist, comes out and calls it one of the most impressive accomplishments he's ever seen.

Ryan Knudsen (8:54)

In the aftermath of deep seq, US investors freaked out. The Nasdaq lost 3% of its value as Deep Seek's model cast doubt on whether all this spending by US tech companies was necessary. What did the Deep Seat moment, say, about the status of the AI race between the US and China?

Josh Chin (9:11)

Well, I mean, after Deep Sea, basically to a lot of people, the gap had closed, almost closed completely. Some people even went so far as to say China was on the verge of pulling ahead. The lead was basically in the sort of months, not years category.

Ryan Knudsen (9:25)

Now that it's developed a proven model, China has put state power and support behind Deepseek. Does China have everything it needs now to get ahead in the AI race?

Josh Chin (9:38)

China has a lot of what it needs. I mean, it has tons of engineering talent and AI relies a lot on data and China has huge amounts of that. Just because it's a massive country and has pretty plentiful power. Those are all working in its favor. But the one thing it really doesn't have is chips.

Ryan Knudsen (9:57)

What China is trying to do about computer chips is next.

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Ryan Knudsen (11:19)

Advanced computer chips are the secret sauce when it comes to the US's lead in AI development.

Josh Chin (11:25)

So the best models were trained on huge numbers of very expensive, cutting edge chips. And American companies made the best chips. American investors had the financial power to buy them.

Ryan Knudsen (11:38)

Back in 2022, under the Biden administration, the US decided to cut China off from those advanced chips. The government restricted exports, hoping to hobble China's ability to catch up. Most of those restrictions are still in place. So what is China doing about the chips problem?

Josh Chin (11:56)

Yeah, so the biggest burden for all of this for China right now falls on one company, which is Huawei.

Ryan Knudsen (12:05)

Huawei is a giant Chinese tech company that makes things like smartphones and wireless equipment. It also makes the best chips among Chinese companies. And Huawei has a plan.

Josh Chin (12:15)

What Huawei is doing is trying to link together as many as a million of Its chips to produce these systems that, according to Huawei, offer similar levels of computing power, which is a strategy that some in industry in China refer to as swarms to beat the titan.

Ryan Knudsen (12:31)

Hmm, swarms to beat the titan. Basically, just like mass produce as many lower quality chips, stitch them all together and that'll compete with the big ones that the US has.

Josh Chin (12:42)

Yeah, I think it's, you know, it's a strategy that China applies in a lot of ways. Right. It's just trying to take advantage of its capacity to produce relatively good quality things in huge quantities in order to sort of compete with the more exquisite but less numerous American technologies.

Ryan Knudsen (13:00)

In response to these moves from China, and to stay ahead in the AI race, the US government has taken a page out of China's playbook and adopted some elements of state run capitalism.

Josh Chin (13:10)

I mean, traditionally the US has kind of let the market take the lead, right. In private enterprise, although, you know, increasingly you're starting to see the US kind of adopt elements of the Chinese sort of state capitalist model. You know, the Trump administration was taking a stake in intel, one of the big chip companies in the us. It's also under the Biden administration, we had the Chips act right, which pumped a lot of money into building chip factories in the us. So the models are sort of converging somewhat, although this still is a much bigger role obviously for private enterprise and private capital in the us.

Ryan Knudsen (13:50)

One consequence of this race is that in order to move faster, both countries are throwing a bit more caution to the wind and placing less emphasis on AI safety.

Josh Chin (14:00)

For Silicon Valley's part, their argument, which has been pretty successful, is that the threat of competition from China means that the government should take a pretty hands off approach, regulation wise, and kind of let them do what they're going to do, not slow them down. And that has generally been what's happened.

Ryan Knudsen (14:16)

The Chinese government has also relaxed some regulations. At one point, Chinese tech companies are required to prepare as many as 70,000 questions to test their model's answers for safety. Though in China, these rules are mostly focused on content, including political speech. But now that testing process has been simplified, including allowing Chinese companies with a good track record to skip reviews of training data, according to people involved in the process. The goal, of course, is to accelerate the arrival of all the potential benefits that AI could offer.

Josh Chin (14:47)

Just like with the Cold War, this competition feels likely to fuel a lot of innovation on both sides and that could be a good thing in terms of making the technology better.

Ryan Knudsen (14:56)

The risk though, is that all this competition could instead accelerate the arrival of all the harms people worry AI could cause.

Josh Chin (15:04)

I mean, you have the potential, for example, for non state actors to ask AI to help them build bioweapons, right? Or maybe more immediately, like there's this fear of how AI could make warfare faster and deadlier.

Ryan Knudsen (15:16)

Or maybe an AI superintelligence turns the entire earth into paperclips. Sorry, that was an AI joke. If, you know, you know, a lot.

Josh Chin (15:25)

Of AI experts, especially AI safety experts, are still worried that that race dynamic will effectively make it very difficult to counteract some of the risks associated with this technology.

Ryan Knudsen (15:40)

So in this AI race between the US and China, who do you think is going to win?

Josh Chin (15:45)

The most likely scenario is that the US maintains its lead for the foreseeable future. But if China figures out how to close the chip gap or finds new ways to do more with less, the way that Deepsea did, build bigger, better models with fewer chips, or it finds a path to new forms of AI that are more powerful than what we have now, then it's totally plausible the US could fall behind. I think closing the chip gap is a major hurdle, and I think there are a lot of people who are skeptical that China will be able to do that. But like we said, China's surprised people before.

Ryan Knudsen (16:34)

That's all for today. Tuesday, December 2nd. The Journal is a co production of Spotify and the Wall Street Journal. Additional reporting this episode by Raphael Huang. Thanks for listening. See you tomorrow.