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Front Burner Transcript for January 30, 2025

Host: Jayme Poisson

JAYME POISSON: Hey, I'm Jayme Poisson, and today on the show, we're going to talk about this small Chinese company called DeepSeek that has really upended the world of AI. If you haven't been following, DeepSeek recently released this large language model that rivals ChatGPT. It shot up to number one on the app charts. The interesting thing about it is that the company built it really cheap, and that has called into question this narrative that you need an endless supply of chips and data centres and money to develop AI. After people started noticing, the biggest market loss in history ensued. Chipmaker Nvidia saw its stock plummet 17% on Monday. Microsoft and Google also took big hits. They've since recovered somewhat. Anyhow, wrapped up in all of this is an AI cold war between the U.S. and China, and as always, we still have lots of questions about where AI is headed and what it's actually good for. I'm going to get into all of that today with Wired's senior tech writer Zeyi Yang.

JP: Zeyi, thanks so much for coming on to the show.

ZEYI YANG: Hi. Glad to be here.

JP: It's great to have you. So let's start with DeepSeek. What can you tell me about this company and where it comes from? I understand it started as like an offshoot of a Chinese hedge fund.

ZEYI YANG: Yes, that is exactly correct. So there has been this Chinese quant hedge fund called High-Flyer since, I believe it was founded in 2015. It was actually one of the best performing quantitative hedge funds in China. And one thing special about them is that they have been using machine learning to come up with their trading strategy. But the founder of this company called Liang Wenfeng, he has a master degree in computer science. And as I understand it, he's just himself very obsessed with AI. So in 2023, he decided that, well, we already have a lot of experience in AI, but we wanted to establish a new entity called DeepSeek to really focus on researching the larger language models and all the kind of AI technologies out there. So DeepSeek has existed for less than two years so far. And it has released quite a few models, open source, out there to the public. And the latest one released, R1, in January, was the one that really kind of set off the discussions.

JP: Yeah. This is the one that came out just very recently you said. And just tell me what it is and what it does and then why it is freaking everybody out.

ZEYI YANG: Sure. Well, the deal with R1 is that it really focused on the reasoning test. So, and people have been familiar with this because OpenAI released their o1 a little bit earlier last year.

JP: Is that, is it fair-- Is that like the ChatGPT or?

ZEYI YANG: It is a version of ChatGPT, but this version just really focused on telling you the train of thought that goes on within the model to come to-- for it to come to the conclusion. So, for example, it tells you a math problem, it's going to tell you every step it takes to get to the answer, which is really appreciated by a lot of people. And what we're seeing with R1 is that it kind of like replicated that train of thought processing there. And if you ask a question to R1 now, it will also show you like the step-by-step calculation or reasoning that gets to the answer.

JP: Huh. Could you give me an example of what something like that might look like if I asked it a question?

ZEYI YANG: Sure, yeah. I've been poking with the model right now. For example, if you ask it, please give me a summary of what's the most important historical events that happened in the 20th century. Right? It will actually give you this very human-like reasoning process. They would tell that, okay, I should start thinking about, like, the first ten years, first decade of the 20th century, and then a second decade of 20th century. And then after going through all of that, it will say, oh, maybe I have missed something because I focused on things like wars. What about culture? What about other entertainment events? So it kind of mimics the process that goes inside a human brain of answering this complete question. I think before OpenAI-o1, most of the models will hide these processes. Or maybe they don't go through these processes at all. But then as models started to realize that people actually appreciate seeing what's going on like within the models, they started to show that, like, transparently. And R1 is an example of doing that really well.

[music]

JP: As I mentioned, I think in the intro, this shot up to number one on the app and people really started to pay attention. And then we saw this massive tanking of Nvidia.

SOUNDCLIP

COMMENTATOR 1: You're seeing markets being absolutely eviscerated on news from a company most people have never even heard of.

COMMENTATOR 2: Let's talk about DeepSeek, because it is mind-blowing, and it is shaking this entire industry to its core.

JP: Google and Microsoft take a hit as well. And like, why? So explain to me that freak-out.

ZEYI YANG: I think the important background here is that, so far, up to before DeepSeek R1 was released, most people had believed that there's one certain pathway for AI to become more powerful and capable. And that is to buy more computer chips, to train the AI model on more chips for a longer period of time, and just through this scaling effect, the AI model is just going to be better and better. [JP: Mm-hmm.] The good thing about that kind of belief is that it's a very reliable pathway. It's like if you just follow the instructions, you're going to get a better AI over time. But what happened with DeepSeek is that when DeepSeek released its R1 model, and people started to realize that, oh, it actually performs really well, it also released quite a few papers, academic papers, explaining how it reached here. And that includes explaining how it trained its model with a surprisingly small budget. And at that point, people started to realize, actually, there isn't just this one way of getting more powerful AI model. If you focus on, for example, making the training process more efficient, or some innovative architecture within the model, then maybe you don't need that many chips or that long, like, a training time. So this kind of questions a established belief in the AI industry, and I think that's what caused a really large shock in the market.

JP: Right. And fair for me to say -- you know, and we're talking, they did it a lot cheaper. Like we're talking about 6 million, so they say, versus hundreds of millions of dollars, right? And these chips that we're talking about, like, they're produced by Nvidia and then these enormous data centres owned by Microsoft and Google. So like, that's why those companies started to see that sell-off, right?

ZEYI YANG: That's true. [JP: Yeah.] Yeah. I do think there are some nuances with that 6 million number. A lot of people just take it for granted. But yeah, the fact is that people realized that you can train the models for a lot cheaper.

JP: Okay. So does this ultimately upend this billion-dollar industry that has been created around developing AI?

ZEYI YANG: I wouldn't say it completely disrupted. Because first thing to know that, well, DeepSeek still has to use these Nvidia chips. Like they admitted themselves to train their R1 model. So it's not like, oh, with some new innovative techniques you can just get rid of the Nvidia chips completely. That's not true. And the other thing is that I've started to see more people reason that DeepSeek had-- what DeepSeek has done, is really to propose a more efficient way to use whatever chips you have. And at that point, if you have a thousand chips, you're still going to have a model that's better than someone with 100 chips. So it's not to say that the scaling effect doesn't exist anymore. It's more like it's not that simple, and we can put in more resources into other things to make-- to change the efficiency of training. But still, like the number of chips you have or the resource, the money you have, is still a very important factor in making a good model.

[music]

JAYME POISSON: Hey guys, we're going to be back to the show in a second, but if I could just ask you a favour. If you could hit that follow button, if you could give us a follow. I know I've been asking you that a lot lately, but it's super helpful for us. And hopefully it helps you too. Okay. Back in a second.

JP: DeepSeek released this latest model as open source, right? [ZEYI: Mm-hmm.] Just explain to me what that is and why it was significant.

ZEYI YANG: Yeah, so I think there has long been this kind of a divergence within the AI industry as to closed source and open source. With closed source, we're mostly looking at companies like OpenAI, Microsoft and Google, because they invested a lot of resources and talents into making their own models. They're not going to open up... open the model up to everyone to use it. They're charging people a fee to use their kind of most advanced models. On the other hand, we're seeing companies like Meta or quite a few Chinese companies, including DeepSeek or the Chinese tech giant like Alibaba, who have chosen this more open source route. So when they kind of like come up with a really powerful model, they will decide to put a model online for anyone to download and test it and run it by themselves, and in this way, they're giving up a lot of control. [JP: Yeah.] Like they cannot charge you anymore, right, for using that model.

JP: Yeah. Why would they do that?

ZEYI YANG: The reason why they want to do that is that, first of all, they started a little bit late. Like OpenAI was already the leader. If they want to catch up, they need to find out some other ways. And providing your models for free is a really good way to attract more attention from the industry, and also to get more users to just try to use it, to test it, and to maybe collaborate with you. And those kind of advice can really help the company itself catch up faster. So that is one way for a lot of companies to decide that, okay, we're not going to catch up with OpenAI through a traditional commercial way, so we're going to try to find out another way to have more people just willingly collaborate with us and help us grow.

JP: Are there concerns that people could use that, you know, for evil? Like, right? Are there security concerns with that?

ZEYI YANG: Yeah. I think the way that these models have been shared under certain open source licence is that if you are someone who downloaded a model and did it for malicious purposes, you are the one responsible for it. The companies themselves, they're giving it out there, but they're also making sure that they're not the one who will be legally responsible for that. And I think there has been kind of like an established open source community rules, so people won't really go after the company for releasing one and for other people to do something wrong. So in that way, it's not completely reli-- the companies are not completely responsible for it.

JP: Right.

ZEYI YANG: And I do think there's another, uh, another thing to notice here, which is that there's a separate set of laws in China to regular [sic] the AI companies, and they do put these AI companies under very strict regulations. However, they also sort of carve out some space there. They're like, if you're releasing this-- if you're releasing a model for scientific research or you're releasing it not to the general public, but only to people who are kind of like very savvy enough in technology, then you're not going to subject to like a strict scrutiny or responsibility, legal responsibility, in there.

JP: Could it... I guess the question I have is, could it be bad for humanity?

ZEYI YANG: Well... Hmm. That's a good question.

JP: Is it?

ZEYI YANG: I feel like...

JP: I don't know. Yeah.

ZEYI YANG: I think that is a... that is actually a very hard question to answer. Because a lot of times with this open source model, what's happening is that there were already a lot of models out there. Even if this company doesn't release another one, if you are someone with malicious intent, you can probably find another one for that. So I guess the marginal responsibility there is, it's ignorable? I don't know. But that's what I'm thinking right now.

JP: Yeah. I also wanted to ask you, because you were talking about the Chinese government and the guardrails that they put on these companies. [ZEYI: Mm-hmm.] You know, I've also heard people concerned about this model in particular. Like, for example, I saw that if you asked it about Tiananmen Square, like just won't reply to you. Or I think somebody tried to ask it about the Uyghurs and the response was that, you know, China is a multi-ethnic society where, you know, its entire population is is... has equal rights, right? Obviously, that's not. So just are there legitimate concerns about that?

ZEYI YANG: Definitely. I think this is, this applies to every single Chinese model out there, which is that they are subject to a set of different content moderation rules that are very specific to Chinese content. And a lot of times we're talking about these models cannot talk about political sensitive situations. They cannot talk about kind of like territorial disputes in China or the political movement, protest movements. All of things like that. So personally, I was not surprised at all that DeepSeek also has some kind of censorship mechanisms when user tries to prompt it with these kind of questions. I do think there's a difference here that because DeepSeek is open source, there's a lot more possibility to tweak with the model and try to get it to censor less. So I think one thing for the open source AI community to figure out is that, there is this model out there, and we know it has this, this drawback of censoring political information. Can we actually modify it so it doesn't do that anymore? I think it's a tall task, but it still is worth trying.

[music]

JP: I just want to situate this conversation in this broader context of this larger global tech war, right? Largely between the United States and China. Trump seemed, I think it's fair to say, a bit blindsided by the rise of DeepSeek.

SOUNDCLIP

DONALD TRUMP: The release of DeepSeek AI from a Chinese company should be a wake-up call for our industries that we need to be laser focused on competing to win.

JP: You know, just for our listeners, could you just briefly talk to me a bit about this so-called, I've heard it called like a 'cold war' between the U.S. and China, when it comes to developing AI and what we've seen in recent years?

ZEYI YANG: Yeah, I think this, like, cold war interaction has really defined the U.S.-China relations in the past, I would say, two to three years. We're talking about how both companies feel like they have to come up ahead of the other one in terms of the key technologies. And AI is definitely the one that both countries are paying their most attention to right now. And specifically we're talking about the U.S. government and U.S. companies really want to make sure that the American AI models are performing much better than the Chinese ones. And so far, like until DeepSeek, I think most people agree that that's true. Like Chinese models are just not as good as the Western ones, and usually when a Western model first introduce a feature, it will take a few months or even a year for their Chinese counterpart to come up with a similar one. And I think that kind of status quo has made a lot of people, like, comfortable feeling that, well, the U.S. still leading in this field. What's happening with DeepSeek is that DeepSeek R1 really rivals OpenAI's o1 in a lot of the key reasoning and math benchmarks. And I think a lot of people are just kind of scared and surprised by that. And that kind of just changes the... like, their calculation of, like, how long does it take China to catch up.

JP: Right. I've seen people make the argument that the breakthrough that DeepSeek made was actually like the unintended consequence of the trade war. That essentially DeepSeek was forced to innovate because the U.S. had banned the export of high-end processing chips, right? So like they couldn't get them, so they had to kind of work around it. What do you make of that?

ZEYI YANG: I think that's a reasonable explanation of what happened, because... I think this really happened under the Biden administration, where they started to put this like chip export control against China. So we're talking about they're restricting the most advanced GPUs from being exported to China and help the Chinese companies grow their AI models. And DeepSeek's innovation is really kind of inspired by that. Because DeepSeek as a company knows that, I'm not going to get an infinite supply of GPUs like OpenAI has, so what I really need to do is focus on, can I circumvent the obstacle by coming up with like software-focused innovations or coming up with some like more scientific research that helps my model grow? So it's kind of like a innovation born out of necessity. And that's always been the criticism to the export control in the recent years, because people are saying that, yes, you are cutting off a very important pathway to AI-- to Chinese advance on AI, but there are other pathways out there. And you're just trying, you're just encouraging them to figure out these other pathways. And I do think DeepSeek's success in some way proves that it's possible to find those alternative pathways. But we're still, we're still waiting to figure out, like, how effective these alternative pathways are.

[music]

JP: I also wanted to ask you about Stargate, right? This is this [ZEYI: Mm-hmm.] initiative that Trump recently announced alongside all of these tech CEOs, including OpenAI's Sam Altman.

SOUNDCLIP

DONALD TRUMP: Together, these world-leading technology giants are announcing the formation of Stargate.

DONALD TRUMP: So put that name down in your books, because I think you're going to hear a lot about it in the future. A new American company that will invest $500 billion, at least, in AI infrastructure in the United States, and move-- and very, very quickly, moving very rapidly...

JP: The idea being that they want to, you know, ramp it up. And do you think that project, Stargate, will go ahead as planned? Is it going to change now?

ZEYI YANG: Well, I think even before DeepSeek became the talk of town, there will have been a lot of suspicions to Stargate, right? And I think it goes back to this idea that Stargate is a example-- it's a culmination of this belief that the more chips you have, the more data centres you have, the more powerful your AI will be. And up until DeepSeek, there hasn't really been a challenging narrative like that. So that's why I think a lot of people-- There is a lot of genuine support for a project like Stargate, that really kind of like concentrates the resources, the money and the talents towards kind of getting more chips and building more powerful AI. At the same time, I think there are a lot of criticisms to that too, because when you are building data centers, when you are piling up these computer resources, you are also kind of... It also has the environmental effects. [JP: Yeah.] It also like endangers the other research that could use those resources, right? So I think what DeepSeek has provided at this moment isn't... is evidence for these other arguments. That, well, yes, like maybe we can achieve like AI supremacy through your Stargate way. But you're asking us to forget all of these, like, counter effects out there. But maybe there's another way. Maybe if we follow kind of the more model efficiency pathway, we don't need to spend so much money and so much, I guess, resources on a Stargate project like this. And I think that will prompt more kind of the counterarguments out there. Which is what prompts me to believe that it will be really hard for OpenAI to carry out Stargate as it wants to be. But still, they have a lot of political support, so maybe they can pull it off.

JP: Okay. And just, since I have you here, I wonder if I could end this conversation by asking you like a bigger picture question. Because look, like it seems to me, at least, that this... a Chinese AI company has done something really interesting in terms of process and cost. But there are these other big questions lingering about whether AI can surpass its current use case, right, or current utility. In other words, can it get better? [ZEYI: Mm-hmm.] Or I guess worse, for people who think that we're headed towards a dystopia. And does this get us closer to that answer?

ZEYI YANG: Mm-hmm. So the founder of DeepSeek, Liang Wenfeng, he's basically in the same age as Sam Altman. And it also strikes me that he has probably very similar beliefs with Sam Altman. He's a firm believer of AGI, which means that AI at some point will just completely surpass human in terms of like their reasoning, their -- all kinds of abilities. And the reason why he has kind of dedicated so much resources and built up a team to build DeepSeek, is that he believes that AGI is achievable. So in some way, the success of, success with DeepSeek, proves that there's still this very strong belief in the AI industry that we should build like the most powerful AI ever, and it will solve a lot of the problem in this society. Even though DeepSeek provides a more efficient way to get there, I don't think it kind of changes the direction that it's heading to.

JP: Right.

ZEYI YANG: I feel like if we want more kind of resistance to the narrative or if we want more kind of other alternatives out there, it might not come from DeepSeek.

JP: Okay. Zeyi, this was really interesting. Thank you so much for this.

ZEYI YANG: Of course. Glad to help.

[Music: Theme]

JP: All right. So before we go today, Trump's commerce secretary pick was asked during a Senate committee hearing on Wednesday if he would maintain U.S. AI leadership. Howard Lutnick responded by saying that DeepSeek had stolen U.S. technology to create a "dirt cheap" model and said that he would impose new restrictions on China. "They stole things. They broke in. They've taken our IP," Lutnick said of China, adding, "I'm going to be rigorous in our pursuit of restrictions and enforcing those restrictions to keep us in the lead, because we must stay in the lead." All right. That is all for today. I'm Jayme Poisson. Thanks so much for listening. Talk to you tomorrow.

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DeepSeek and China's AI power move - Transcript

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