Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: I'm Stephen Carol and this is here is Why, where
Speaker 2: we take one news story and explain it in just
Speaker 2: a few minutes with our experts here at Bloomberg.
Speaker 1: It was done very cheaply. So why the crazy amounts
Speaker 1: of spending that are happening from the US big tech companies.
Speaker 2: What's happening here is the collapse in the cost of innovation.
Speaker 1: What this development has shown is the hardware that these
Speaker 1: companies have procured, they weren't using it efficiently. A lot
Speaker 1: of question marks around deep Seek, in particular, how much
Speaker 1: did it really cost for them to develop this new
Speaker 1: quote unquote cheap model that they've self reported.
Speaker 2: The implication is, of course that things got cheap, that
Speaker 2: things got more simple, but we'll have to see that
Speaker 2: manifest itself in the real world. Shocking, a game changer,
Speaker 2: a Spotnik moment, just a few of the things that
Speaker 2: have been said about the Chinese AI startup deep Seek.
Speaker 2: The company shot to global fame over a weekend after
Speaker 2: the launch of it's R one chatbart, seen as arrival
Speaker 2: to the likes of Chat GPT, but crucially, the company
Speaker 2: says it used less expensive chips. So here's why Deep
Speaker 2: Seek is a wake up call for the AI Titans.
Speaker 2: Joining me Iwo to discuss Boomberg's TV anchor. Tom mackenzie,
Speaker 2: a former China correspondent and our resident tech watcher. Thanks
Speaker 2: for being with us. Tom, First of all, tell me
Speaker 2: about R one, the product that Deep Seek makes. Is
Speaker 2: it something that's really comparable to.
Speaker 1: Chat GPT or to Gemini so on a number of
Speaker 1: metrics measured by experts, and there are platforms online where
Speaker 1: you can see how these measurements are displayed and how
Speaker 1: they categorize these models. Then yes, R one competes with
Speaker 1: chat gbt's most sophisticated model, the latest model to zero one,
Speaker 1: but also the models from Gemini and Anthropic. It is
Speaker 1: up there top of the list alongside those kind of players.
Speaker 1: It is sophisticated. It is a text based model and
Speaker 1: chat bop you can download it onto your phone. It
Speaker 1: is not multimodal, so it doesn't produce video, it doesn't
Speaker 1: produce pictures, but what it does do is reasoning. Like
Speaker 1: one from chat GBT, it goes through how it comes
Speaker 1: to its responses, and unlike O one, it actually displays
Speaker 1: those for you, so you can see the chat bot
Speaker 1: processing your question, going through how it's going to get
Speaker 1: to the answer, and that level of transparency has led
Speaker 1: to a lot of tech enthusiasts out there who are
Speaker 1: getting their hands on this thing responding very favorably, and
Speaker 1: that's led to a lot of optimism and some very
Speaker 1: positive feedback about what this chatbot based on deep seeks
Speaker 1: model can actually do. Now, one thing it can't do
Speaker 1: is answer an honest question about Hi Jinping and his
Speaker 1: leadership or what happened in Chaneman Square in nineteen eighty nine,
Speaker 1: because it is not allowed to full foul of Chinese
Speaker 1: government censorship. So there is that important caveat.
Speaker 2: Okay, all very interesting. What do we know about how
Speaker 2: it was developed?
Speaker 1: What we know is what is claimed by deep Seek.
Speaker 1: So they claim that it was developed at a fraction
Speaker 1: of the cost of some of their competitors, around six
Speaker 1: million US dollars. They claim the model was trained on
Speaker 1: much older chips, not the most cutting edge in video chips,
Speaker 1: because those are restricted from the Chinese markets. We know
Speaker 1: that they have very innovative and sophisticated engineers. They've been
Speaker 1: recruiting talent for the top universities domestically in China systems engineers.
Speaker 1: We also know that they put in place an infrastructure
Speaker 1: and a method of building models called a mixture of
Speaker 1: experts procedure, which basically has lots of mini models much
Speaker 1: easier to put together, and if you align them, you
Speaker 1: can create these efficiencies. So the engineers, the mixture of
Speaker 1: experts method that they've used, they say has led them
Speaker 1: to creating these efficiencies, building a model much more cheaply,
Speaker 1: using less efistigated chips, and much more quickly. They say
Speaker 1: they built this model, design this model within about two months.
Speaker 1: Now there are question marks. Microsoft and open ai are
Speaker 1: scrutinizing whether or not deep Seak actually lent on open
Speaker 1: AI's own model to learn from the outputs from that
Speaker 1: model that they then fed into the training of the
Speaker 1: deep Seat model that potentially went over and above what
Speaker 1: was allowed. That is being scrutinized, And we have to
Speaker 1: take them on face value when they talk about the
Speaker 1: chips they're using, because we don't know exactly how they
Speaker 1: built this. But if we take them on face value,
Speaker 1: the more cheaply, more cost effectively, in a shorter time
Speaker 1: and with a slightly different method, that created a very
Speaker 1: efficient and very capable model.
Speaker 2: Okay, got questions being asked, as you know, more broadly,
Speaker 2: when we talk about AI open on now we've mainly
Speaker 2: been talking about the models developed by American companies. What
Speaker 2: is this revealing something that we didn't already know about
Speaker 2: China's AI industry? How does it compare to what we
Speaker 2: know out of the US.
Speaker 1: There is an argument that we've had a blind spot
Speaker 1: when it comes to the innovation that's coming out of China.
Speaker 1: There's been a lot of talk about the slowdown in
Speaker 1: the economy rightly, so, there's been a lot of concern
Speaker 1: about the real estate market. There's been a lot of
Speaker 1: concern about a crackdown on technology in recent years out
Speaker 1: of China. That has allowed some to overlook the real
Speaker 1: innovation that is happening in that Chinese market. One of
Speaker 1: the most competitive places to build and test technology is
Speaker 1: in the Chinese markets because you have so many people
Speaker 1: who pile in, they test their products, they fight to
Speaker 1: the death, and then the survivors come out on top.
Speaker 1: And if they can compete in the Chinese market, my goodness,
Speaker 1: they can compete globally. And we've seen that, whether it
Speaker 1: is with drone makers like DGI, whether it's like TikTok,
Speaker 1: social media companies like TikTok, or whether it's indeed the
Speaker 1: solar panel makers of China. Across all those different areas,
Speaker 1: they compete in the domestic market, they win, and then
Speaker 1: they go to compete internationally. I haven't even mentioned the
Speaker 1: electric vehicle makers that are posing a challenge to Europe's
Speaker 1: EV model now as well. They have the engineers, They
Speaker 1: have almost double the number of engineers of the US
Speaker 1: in terms of AI engineers. They have the data in
Speaker 1: vast quantities what they don't have, and the most sophisticated chips.
Speaker 1: If Deep Sea really is an example of how to
Speaker 1: circumvent that by using older chips, then China has all
Speaker 1: the ingredients it needs to compete on the global level. Interestingly,
Speaker 1: we also saw another Chinese company, Ali Baba, coming out
Speaker 1: with model this week that is also as capable as
Speaker 1: the most sophisticated models coming out of the US. So
Speaker 1: every indication suggests that China is a serious player, and
Speaker 1: if it hasn't caught up with the US yet, then
Speaker 1: it's very very close to doing that.
Speaker 2: It does seem like all of a sudden everyone has
Speaker 2: an opinion on deep Seek and its breakthrough. Even the
Speaker 2: US President.
Speaker 1: The release of deep Seek AI from a Chinese company
Speaker 1: should be a wake up call for our industries that
Speaker 1: we need to be laser focused on competing to win.
Speaker 2: So, Tom, what do the AIA companies in the US
Speaker 2: need to be woken up to with this deep Seek story?
Speaker 1: Well, interestingly, it's earnings week as well, so we've been
Speaker 1: hearing from the CEOs of some of those major players.
Speaker 1: We've been hearing from Mark Zuckerberg from Meta, We've been
Speaker 1: hearing from sati In adell At, CEO of Microsoft. What
Speaker 1: you're not hearing from them is any walk back on
Speaker 1: the spend around CAPEX, the spend on the chips, the
Speaker 1: spend on the data centers, the spend on the servers,
Speaker 1: and the spend on the energy that's needed to power
Speaker 1: this AI revolution. Because one of the major questions that
Speaker 1: Deep Seek has posed this week is is all of
Speaker 1: that spending worth it? Do we need to spend tens
Speaker 1: of billions of dollars and all of that AI infrastructure?
Speaker 1: If a bootstrap company in China with six million dollars
Speaker 1: can produce a model that competes with Chat GBT at
Speaker 1: a fraction of the price. But the CEOs are not
Speaker 1: walking back from these investment commitments. In fact, Mark Zuckerberg,
Speaker 1: who praised deep Seat and said there was real innovation there.
Speaker 1: He's committed to sixty five billion dollars of spending this year.
Speaker 1: He says they're going to be building their own AI agents,
Speaker 1: and he hopes the Meta is going to be getting
Speaker 1: those agents to a billion people by the end of
Speaker 1: this year, and that they'll be leading in that space.
Speaker 1: Microsoft Satiy and Nadella also praising deep Seek, but his
Speaker 1: take was this is going to lead to greater adoption
Speaker 1: of artificial intelligence. It will drive down prices, and longer
Speaker 1: term that will be good news for Microsoft. Microsoft committing
Speaker 1: to spend eighty billion dollars this fiscal year on AI infrastructure.
Speaker 2: Okay, a rude awakening for some, perhaps not for everyone.
Speaker 2: Tom McKenzie, our Blimberg TV anchor, thank you very much
Speaker 2: for joining us for more xp like this from our
Speaker 2: team of twenty nine hundred journalists and analysts around the world.
Speaker 2: Search for Quick Take on the Bloomberg website or Bloomberg
Speaker 2: Business app. I'm Stephen Carroll. This is Here's why I'll
Speaker 2: be back next week with more thanks for listening