Welcome to the Market Maker Podcast, hosted by me, Anthony Chang. Where every Friday, I talk to a member of the team about what happened in markets this week. From MacFrow themes and single stock news to cryptocurrencies and careers in finance, our aim is simple. To make finance interesting and easy to understand for everyone. So let's get to it.
Hello and welcome to what is a breaking news episode and the reason why is nothing like starting the week on a Monday morning with a big bang, a trillion dollar sell off. You can already envisage the headlines at the end of today appears. But what's happened here is
Something's come out over the weekend and it has seen the likes of the Nasdaq 100 in the futures market. The cash is going to open while we are live recording this and we'll update you. We're looking down about 5% with Nvidia down 12%. Now, I was looking quick. Look at the technicals on the actual Nvidia chart and it's going to open below quite a key phase of consolidation. It's been in really over the last three months, so it could get.
pretty interesting throughout Monday's trading session for sure. But more than that, want to understand what is going on. What is this new Chinese AI startup breakthrough? Why is it so important? We're also going to look at why perhaps
a couple things that you might want to consider if you were just kind of getting somewhat blindsided by what's going on. But Piers, to bring us up to speed, I know you had an important client call this afternoon, which kind of goes and testifies to how big this market and unforeseen the reaction has been because they've had a lot of senior traders on that call and they had to cancel it to go back to the desk, right?
Well, I had a Morgan Stanley meeting here with some sort of various kind of trade, managing directors from various parts of the trading division. They've all postponed. They're like, we cannot leave the desk. It is absolutely kicked off.
to say the least. And actually, look, obviously there's a lot of trade volume going through. We'll talk about why in a sec, but as of this morning, and this was like, this is a few hours ago now, about 200,000 NASDAQ 100 futures contracts had traded, which was actually four times more than the 30-day average. And that was like one hour after the sort of open of that futures contract.
Yeah, it's a classic scenario of people rolling out of bed and going, what, hang on, what? Are those numbers actually true? And I think it's been, it's almost like, you can't say this wasn't sort of on the risk radar.
And it's always just one of those things that, okay, it's a risk, could happen, got no idea really when. Well, when is now? And so deep seek is the new name in town. And this is a Chinese mainland kind of startup. And I mean, this has been kind of rolling through, I'd say the second half of last week.
So they released a detailed paper. This is deep-seek now. They released a detailed paper last week explaining how basically an instruction manual to build a large language model that could then automatically learn and improve itself. Remember that these large language models, let's say like Facebook or, sorry, Metas, Lama, for example, these large language models are key for training.
AI tools like chat GPT for example and of course up until this point there's been a massive moat and a barrier to compete because of the cost of compute power. Nvidia the poster child of the AI revolution as an almost you know not even sure what the percentage market share is but it's it's almost the entire market share for producing these super chips
that are these GPUs that are the only ones we thought that are powerful enough to kind of deal with all of this large language model training situation. And so, you know, and the US have been quite keen to protect their lead in this. What is a technology arms race? We'll come back to that point in a minute, because some people are kind of
beginning to start to compare this to another arms race that happened a few decades ago it kind of kicked off the space race but we'll come come on to that in a second but yeah basically you know Nvidia we had thought had been well ahead of the game producing these chips the Biden administration had prevented these chips from being exported to China the idea being to hold China back so they can't compete on the same level well this news
really throws all of that out of the window. And actually, maybe they can compete with insuffiria chips, but also as a result on a budget that is a tiny fraction of what are these big, you know, MAG-7 companies have been spending. And so in short, this is thrown a spanner in the whole works of this AI revolution to date, where it's the rich
and those big MAG7 companies that have got the cash to afford these Nvidia chips. It was thought that it was an exclusive race, not anymore. It was just our episode last week. We were talking about how this joint venture between OpenAI
And SoftBank was like bringing together some entities to be able to provide the capital and firepower to get up onto the level to compete with, you know, the Metas and the Googles and the Microsofts. And actually, this news here is, well, actually forget all of that. You can do it at a fraction at the cost.
So just looking and videos just opened, it opened down, I think about 13% and it's just bounced back to down just 10 and a half now, but early days. Yeah, but just explain to me then, because Microsoft are down 4.4, Google's down 3.5, so all the big names, big tech. But just talk to me about the kind of context here, what it, in terms of the implications on cost in particular.
So the market reaction, all right, there's several, there's several different pockets of the market. They're getting hammered here for slightly different reasons. So you've got the Nvidia's. So well, firstly, so you've got your chip producers, you've got any companies that are supplying, you know, part of the AI supply chain. So Nvidia arm, for example, there your chip
Supplies AML, ASML, sorry, they're getting hammered. And that's because, well, maybe you don't need their super advanced chips that are crazy expensive to get involved with this game, right? It was thought they'd had dominant market share. Maybe that market share is now going to get eroded. So that's kind of number one. Then you go back a step. Or sorry, one more step through the supply chain. There's companies like Siemens Energy,
Schneider Electric, they supply hardware for AI infrastructure, right? Siemens Energy, German company, down 22% today. Schneider's Electric, that's a French company, they're down 9.2, right? They're kind of electrical power products, okay? Which are used in these big data centers, okay? So you've got those types of companies. So they're directly involved with this AI software infrastructure side then.
take another angle. Well, all of these big MAG7 companies, Meta, Microsoft, and actually Meta just on Friday, which was kind of after this kind of deep-seek stuff started to move, Zuckerberg on Friday, actually said, reconfirmed that Meta planned to spend $65 billion in 2025 on AI infrastructure. Microsoft last week,
They said they're going to spend $80 billion in 2025 on infrastructure. You just had that open AI soft bank tie up. They're going to spend $500 billion in the next five years. Up until this point, there's been a thesis that you have to spend big to be in this race.
Is there going to be a return on investment for, you know, are these companies that are spending big? Are they the ones that are going to win the big pie that will be the revenue that comes out of all this AI world of the future, right? Well, all of this big news is basically potentially saying, well, you've wasted all that money.
you shouldn't have spent it or you can do it at a fraction of the cost. Okay, so that argument about they're going to see big return on investment from these massive investments. That argument's been massively dented here. So you're getting the big companies, as you were mentioning there, so I'll just go through them. Yeah, Microsoft has just opened down 4.2%.
You've got metadata in 2.5, Google are down, all right? Not as much as Nvidia, who are directly in the firing line as in potential direct revenue hit here. The second order effect is that lack of return on investment. And so Amazon are down 3% here, Tesla down 2 and so on, right?
Then you've got, well, what does this mean for the big indices? Because obviously all these companies I've just mentioned, well, they're the big dominant forces in the indexes. So now you go and look at the NASDAQ, which is just open. It's just open down 3%. OK, and actually it has bounced here a little bit.
already, as you were mentioning, so that some of these, I mean, this is so live, as we're talking, it was, I think we opened down about 5% on the NASDAQ, it's now down three. But of course, because these massive MAG7 companies make up such a huge part of the index, we'll then, of course, they're getting hammered as well.
There's one Mag 7, your defensive death star. He's actually up, nearly 2%. So the fact that Apple is so far behind in the AI race is actually coming as their savior today. You're absolutely right. Apple is up 1.6% here, because they haven't spent anything yet or nowhere near the amount the others have. And it's almost like, well, hang on, that's genius. Now they've held back. Well, now they can enter the race at a much cheaper price.
Other market reactions, the VIX, which is looking at its volatility index, the fear gauge we called it earlier on this morning, that was spiked up 45%. Let me see, I'll try and get a reading on the current price. It's now up 33%.
So yeah, you're definitely getting some big kind of reversals, but these markets are all still quite quite heavily down, although the amount they're down is reducing as the more we go through this podcast, actually.
Yeah, and interestingly, this is earning season. So we do, in fact, have the likes of Microsoft, Apple, all coming out this week with their profit growth already under a bit of pressure. So interesting that they're obviously going to be asked in the analyst calls about this. And this has kind of shifted the entire focus on that.
You might remember a couple of years back, even before like three years back, before the AI thing kicked off. Meta, we're talking about investing in the metaverse.
Right? And actually, as Zuckerberg came onto these earnings calls and said, we are going to spend X billions, X being a large number on this metaverse thing. It was almost like the more they were committing to spend, the worse it was. And their share price would get hammered. I think you might actually now get a beginning of that trend here.
for AI so the more like if if Microsoft on their earnings call later this week come out and said yeah we're still committed to 80 billion dollar spend this year i think you're going to see that feed through negatively in their share price and analysts on the call are going to be asking well why now why are you spending that amount of money surely this is a waste of cash flow and and so on so it'll be these earnings calls i mean the cfo i do not
Envy the CFOs and the CEOs on those earnings calls later this week having to try and navigate through this kind of very obviously live development.
Yeah, everyone's becoming an AI expert once again. I'm sure the thought leadership on LinkedIn is going to be lit up later on today. But it's going to be interesting what Trump says. I mean, look, it's only 2.30 at 9.30 AM over in the east coast of the US. What's Trump's response? Obviously, last week, Trump was like...
You know, obviously slapping everyone on the back from open AI and soft bank coming to the Oval Office. Aren't you amazing? We're going to spend 500 billion. We're going to make so, you know, create so many jobs. So the geopolitical angle here, you know, given that how the US had imposed those stringent restrictions on chip exports to China, thinking that they were hindering their ability to compete. I mean, well,
What did I say now? This is what happens when the president makes decisions without his co-president. If you leave Elon out in the cold, you have to pay a penalty, I'm afraid.
But look, I just thought, yeah, having worked in news aggregation, let's call it, in my career, you know, for the 20 years, there's definitely, I think, behavioral elements to this, i.e. the interpretation, as you would have seen many times, where it's that knee-jerk reaction, as you said, at the top of the show, you wake up and you see the markets down there heavy, they start selling, momentum selling, and it all starts to trigger off.
There's a couple of things I was just thinking, right, let's just step back and let's just ask a couple questions here about more legitimately, whether this is as a serious cut of
existential threat is kind of how the press are pinning it, and this is their job to talk it up. So a couple of things I'd just like to flag. One is the potential strategic messaging behind this. So, i.e. a counter to the US leadership narrative of what we just had last week. So, deep seeks announcement
I think it's not without surprise. It comes just literal week one week after this first week in office, this real kind of signposting of make American AI leader and this investment project. And a couple of things on that. One.
It's Chinese New Year this week as well. So I think that timing is compounded particularly because there was economic data that came out that again shows the Chinese economy is faltering.
Industrial activity is weakening. There's still big question marks on many different pockets of the Chinese economy and people in China are about to go and see their friends and loved ones all across the country and have a week of down tools. And so that in combination with the stockate announcement, you know, there's nothing like a little bolstering of national pride. And we see this with what we have with the quality of information.
So people always say, you should always question the quality of Chinese economic statistics that you see. Why? Because there's such deep state kind of involvement in a lot of these things. And deep-seek self-senses on topics. So actually, if I was reading this thing, it was saying, if you were to basically do a query on Tiananmen Square protests,
or geopolitical events, it won't answer your questions. So actually then, yes, it's open source and all these different things, but it's being content curated in terms of what information is actually driving these models. So yeah, the deep-seak bot is capable of giving detailed responses about political figures, of course, in India, but it won't say anything about Xi. So that's one thing. The next then is, who's actually vetted this claim?
I mean, it seems quite clear the case is very compelling and it's absolutely the perfect kind of antidote if you like for a Chinese response. But so far, there is no public third party confirmation of what Deepseeker say. Zero.
And you seek publication of the paper outlining their R1 model, while I think you can argue some transparency of putting that out. Does it lend some credibility? One of the things I'd be looking out for is it independently verified experts who start running this model to see about his performance and efficiency claims? Because it's not like the Chinese don't overstate these things in the past. But to counter your point, they're at.
is right now available in the App Store. And actually one of the things that's kind of triggered some of this reaction is it went to number one in the App Store over the weekend. And so it's there, you can use their product. And actually people that are using it are saying, actually, wow, yeah, this is, all right, it's not as quick and as good as the latest, you know, chat GPT version. But it's like, well, hang on, how have they built this
when they have not had access to H100 chips from Nvidia, because they've been blockers of sanctions. So it's like, well, how has it been possible for them to have done this?
And sure, I mean, I don't know, I saw one number saying they managed to train it with a budget of $5 million. I don't know where that $5 million came from, rather than the multiple, multiple billions. I think actually, US big tech spent $250 billion last year on infrastructure, right? So $5 million, God knows where that number came from. But it's like, well, how have they done it?
Now, how have they done it? Well, fine, they're spinning the story that they've done it on their own super cheap. Now, that hasn't been verified. I don't know how they've actually done it, but for now the product is there. It's available. They can download it, have a go. And the experience is very good.
Yeah, until Trump will come out and announce in the next 48 hours that that app is no longer going to be downloadable in certain geographic territories, I'm sure. But a couple of things then. So one, is this just a natural cycle? You said earlier in video is so dominant in this space that not that they're getting complacent.
But you need an event like this in order to just sharpen the mind again from the US big tech scene to just actually, this is a good wake up call talking not, you know, today, Monday's trading session, but over the more medium term, now that they're aware of this and the possibility of this, then that's a good thing.
Yeah, I mean, so there are a counter argument. Well, firstly, hang on, before the counter argument, it shouldn't be a surprise. I think it should be a surprise if the cost of all of this remains crazy ridiculously high. Price is set by Nvidia because they've essentially cornered the market. There's this law, it's called Moore's Law. Basically Microsoft wouldn't exist
as a business if Moore's law wasn't true. So Moore's law is this law dates back to the 60s and the 70s and the 80s where basically every two years the cost of infrastructure for all things like using semiconductors and all the rest of it, anything computing, basically the cost of it all halves every two years. This is Moore's law.
And Microsoft in the 80s took advantage of computers going from being this massive, crazy, expensive things that take up a whole room to being on everybody's desk, you know, across the workforces of the Western world, right? That was only possible because the cost of it all dropped.
This is now, you know, why would you expect Moore's Law to not apply in this new AI age? And I think some investors have been expecting it for some reason. They don't think it's going to apply. Well, here it is. And I don't think that should be surprising.
That's one thing to say. But there are counter-arguments, right? And look, you've got to be careful here because there's a lot of people talking in their own book. If you're still long in video, you're out messing note to clients this morning going, ah, this is nonsense. You shouldn't believe it. You shouldn't believe these Chinese
You know, I'm verified, you know, breaking news and what have you. One argument that's kind of coming to the surface of all of that, which might have some credibility, I would say, is that apparently they, you know, they deep-seat were able to kind of take shortcuts in its own training costs by leveraging the latest models from OpenAI, right? Meaning, okay, they might have caught up
They're not in line with OpenAI, and they're certainly not in front of them. They're behind, but they're a lot closer behind than we had thought. But if they're reliant on whatever latest model OpenAI has available out to the world, well, of course, they're always going to be behind.
because OpenAI, well, they're working on their next version right now, right? It's not available to anybody other than themselves. So if they're reliant on OpenAI's models, they will always be 12 months behind. And so that's, I think, actually a pretty good argument to say that whilst this is, wow, shock big news, it's not the death knell for Nvidia's sort of 90% of their revenue.
And ultimately, if this was a completely Chinese run shop and not using that open AI system, for example, surely the adoption of this AI would be impeded by a business's willingness to use that technology if it's Chinese owned.
And so isn't it then better that this happened so big tech in the US can basically understand the kinks in their armor and understand the adoption techniques to drop costs perhaps because there's no way that a Western developed world is going to buy Chinese and implement its technology within its business on a large scale surely. No, but I think the point is that
If your Microsoft sat there, right, you budgeted that for 2025 and the biggest line item on your whole budget is 80 billion spend on AI infrastructure. If I was Microsoft, I'd now be going, okay, hang on a sec.
let's just revisit that line item. And how is it that this Chinese company has managed to do what they've done on a shoestring budget? Actually, maybe we don't need to be spending disgusting amounts of billions. And maybe we can do this as in Microsoft, maybe we can do this much more efficiently. So I think it actually could be
In the medium term could be good for the big tech as they actually end up spending a lot less than they would have done. In the short term it's bad because they've already spent a ridiculous amount and it might be that it's wasted money but then Nvidia are right in the firing line because right how much market share will they now lose if their chips are being sold at a crazy price and people that need to buy them anymore.
So I think this is going to be a messy few days, and those earnings calls are going to be really key. Nvidia right now is down 11%. Is Nvidia going to rebound to unchanged and recover all of these losses? In my opinion, no.
I actually think for Nvidia, this is kind of end of chapter one where they've just had the whole market to themselves and they could price whatever they want. I think it's literally end of chapter one. Chapter two then, I'm not saying they're now, that's it. But it's just, it's going to be a step change and just an interesting turn of the page.
Yeah, and interestingly as well to close, there was that consumer electronics show that we just had a lot of weeks ago. And in video, we're talking very much around robotics, autonomous vehicles. So are they looking to spread their wings as well into different?
Well, that's it. And that's what you should do. If you've got in the good times, don't just sit back in your armchair on the beach and think, wow, aren't I amazing? You've got to start planning ahead, right? How are we going to diversify? You know, because they're obviously hugely reliant on one type of revenue. So it's about, right, let's diversify this thing out and make sure we're locked in, you know, across the different kind of stages of this sort of AI journey.
OK, great. Well, look, great to get your thoughts. I know it's fresh off the press. I'm sure there's going to be lots of developments throughout the week. But yeah, good to get your take. And I hope everyone found that useful. Thanks, Piers. Thanks a lot.