Prof G Markets - AI Skeptic: This Business Makes No Sense

Episode Date: May 14, 2026

Ed Elson is joined by Ed Zitron to discuss the state of the AI industry (read: bubble). Zitron argues that every AI startup is unprofitable at its core. Then James Kynge breaks down what to expect from President Trump’s visit to China. Finally, Ed digs into data from the producer price index and what it could signal for inflation and the broader economy.  Ed Zitron is the author of the Where’s Your Ed At Newsletter, and the Better Offline Podcast. James Kynge is the host of the Prof G Media’s China Decode podcast and Senior Research Fellow at Chatham House. Get your tickets to the Prof G Markets tour  Subscribe to the Prof G Markets Youtube Channel  Check out our latest Prof G Markets newsletter Follow Prof G Markets on Instagram Follow Ed on Instagram, X and Substack Follow Scott on Instagram Send us your questions or comments by emailing [e-mail] Learn more about your ad choices. Visit podcastchoices.com/adchoices

Today's number two. That's the number of times Sir David Attenborough has been knighted for his services to British television and conservation. It appears that after Brexit, the UK has run out of people tonight. Money markets met. If money is evil, then that building is held. Welcome to Prof.G Markets. I'm Ed Elson. It is May 14th.

let's check in on yesterday's market vitals. The major indices were mixed as investors digested new inflation data from the producer price index. Tech stocks drove the S&P and the NASDAQ to new records while the Dow fell. We'll talk about that inflation in a moment. Inflation concerns also pushed the yield on 10-year treasuries higher, and on Kalshi, the odds of a rate hike this year have steadily climbed to 31%. Meanwhile, Apple's stock closed at a record high as CEO Tim Cook joined President Trump. as well as several other big tech leaders for a summit in China.

We will be discussing that shortly as well. Okay, what else is happening? Big Tech is on track to spend $725 billion on AI in 2026, and it shows no signs of slowing. Yesterday, reports surfaced that Anthropic is in talks to raise $30 billion at a valuation north of $900 billion, and SoftBank posted a $46 billion gain for the year fueled by the soaring value of its stake in Open AI. The markets are currently rewarding the AI boom.

The NASDAQ is up 27% since its March 30th low. Much of the gain comes from the AI trade with chip stocks recording their best monthly performance in decades, but not everyone is buying it. Big Tech's free cash flow has been shrinking as AI CapEx balloons, and some investors are asking when, if ever, the spending will generate a return. So we wanted to check in with one of AI's fiercest skeptics and critics and ask what could the market be missing. So joining us to talk about the state of AI and perhaps some of the stuff that people are not paying enough attention to. We are speaking with Ed Zitrin, author of the Where's Your Ed at, newsletter, great name, and the Better Offline podcast.

Ed, thank you for joining me on the show. Our producer Claire mentioned this to you offline, but I will say it now. You are probably the most requested guest we've ever had on the show. My audience has been asking over and over again, you have to talk to Ed Zittrin. We have to talk to Ed Zittran. We're finally here.

So thank you for joining me. So I want to start with maybe just a summary of your views. You have been writing for a long time that you believe that a lot of what we're seeing at AI is fake, misleading, not what we think it is. If you could just start with a summary of what you believe is really going on in the AI world right now. So across the board with public stocks, nobody's showing a profit from AI, and for the most part, nobody is showing even the revenue they're making from AI. When I say revenue, I do not mean profit. Microsoft revealed that a $37 billion ARR run rate for AI,

The majority of that comes from OpenAI feeding it money from, well, Open AI's venture capital funders and probably left over a zero tokens from the $13 billion in funding. Anthropic similarly is funded entirely with venture capital and their connected counterparties are seeing massive boosts in their remaining performance obligations, so their revenue backlog, mostly from Anthropic and OpenAI. In fact, between Microsoft, Google and Amazon, $748 billion of their revenue backlog. upcoming revenue. Over half of it comes from two companies, either buying compute or in Google's case, Anthropic buying TPUs from Google to rent back from Google. The whole thing is very circular, and really outside of Open AI and Anthropic, there's not really any sign that there's a real revenue stream here. I have serious questions about the way they count revenue, but as private companies, it's hard to pierce. There's also the other real problem. Big Tech is, there's

between meta, Google, Amazon, and Microsoft, over $800 billion of CAPEX. I don't think data centers are being built at anywhere near the rates that people think. I have on good authority that one of the major hyperscalis only has around a one and a half gigawatts of actual IT capacity despite hundreds of billions of dollars of CAPEX. And data centers are just not getting built, 18 to 24 months minimum. People see the AI boom as something that's happened, as in something that's, there's tons of data centers being built. I've seen people saying tens of gigawatts built every year. It's nonsense. I think there may only be a gigawatt or two built every year.

The compute constraints people are facing are not a result of incredible demand, but a lack of actual data center capacity coming online. We are yet to get to the real monstrosity that this is created, and when it pops, it's going to be very bad for everyone involved. So I'm going to play a little bit of devil's advocate. I want to couch this by saying a lot of what you're saying I agree with. I agree that the revenue is circular in a lot of ways.

I agree with you, your points about the data centers, the fact that they're not coming online and there is a lot of questions on, are these data centers even going to get built? Are they even going to work? Are we even going to allow them to get built through regulation and through policy? I agree with a lot of that. At the same time, though, I do look at the growth of some of the revenues of some of these AI labs. I look at Open AI. And to your point, we haven't gotten the financial audit of these companies.

These are privately reported, but that's the way private companies work. But Open AI was $2 billion in ARR in 2020. It's up to $25 billion in ARR today. Anthropics reached $30 billion to ARR. You know, it took Salesforce about 20 years to get that. They've done it in under three years. I mean, those are dollars that are coming in. and companies are trying to adopt AI as much as possible,

and they're paying money to do it. And I guess the way that I feel about it is we're probably very early to this game. They're doing whatever they can to get this through. They want to adopt AI, but I still find those numbers striking, and to me it tells me that something about this is real and meaningful. Maybe there's some BS around as well, but overall I don't want to write it off.

make of that? So let's start with that statement about being early. We're not. Early, if we do it by time, it's been four years. Coming up on four years since chat GPT came out. And if you think about what constitutes early, early, it really is investment and innovation. We have had all the King's sources, all the Kingsmen trying to make generative AI into something that generates profit. Hasn't happened yet. Not one that's happened to. I also have serious questions about how Anthropic is doing revenue. Krishna Rao, their CFO, in the Department of War lawsuit, actually said in an affidavit on March 9, 2026, that they had made $5 billion in lifetime revenue. That does not match up with any of the reported previous annual

recurring revenue or ARR or run rate or whatever they use numbers. It just doesn't. When you add those all together, it's $6 or $7 billion, maybe more. I think Anthropic is counting revenue in a way that is different, fundamentally different to how most companies count it. My theory is that when, so with the largest clients they have, clients don't pay in arrears, smaller ones do, but the largest don't. They buy massive amounts of tokens in advance. I think Anthropic, for example, is someone who's going to do $50 million worth of tokens that lasts over six months, they're going to take that money up front. They're going to say, wow, in that month, because all ARR is is month times 12 or 13, depending on how they do it. So I think,

think both Open AI and Anthropic are inflating their numbers. I actually think one or both of them is misleading investors, but that's something we'll find out about in the future. I also fundamentally just don't see evidence outside of these two companies that anything's happening. The largest company within this space was cursor, and now they've been kind of sort of not really bought by Elon Musk. Also, if there was so much demand, by the way, why did Elon Musk give up an entire data center to Anthropic? There are enough signals here. that suggests there is a fundamental weakness and no real major business model here. We still don't know Anthropics' true burn rate,

but we do know that if all of the commitments from Amazon and Google come together on this $50 billion round, it's $30, it's $50, it changes every day, it seems, they'll have raised $108 billion in the last year. What's going on? Where is that money going, and to whom is it going to, other than Google, Microsoft and Amazon? So one of my simplest points as well is, other than Anthropic and Open AI, why are there no other AI winners? Why is everyone piddling around 100 to 300 million ARR, which is 10, 20, 30 million dollars a month? It's not actually that much for what is meant to be an industry-changing thing imidgig.

And there are signs that the economics don't work, the biggest being that Microsoft, GitHub co-pilot, by the way, one of the largest clients of Anthropic, moving to token-based billing on June 1, 2026. They have been subsidizing tokens for their users to the tune of, I saw one person who spent $5,000 worth of API calls on a $39 a month program. I think this problem is across the industry. I think basically every AI startup is unprofitable at its core, and there is nothing that's going to shift these economics in their favor. There is no sign that inference is becoming cheaper. There is no sign that anyone has any plan to do so, and neither anthropic nor open AI seem particularly concerned

with bringing those costs down. So some really interesting points in there. I would still disagree with your point that it isn't early. I mean, when we're talking about technologies of this size, I still think four years is early and to the point about profitability,

like, you know, you look back to the internet, it took a long time for the internet to get running. Amazon took nine years before it was consistently profitable. And eventually, I mean, you can take decades before your business model works properly. And we have seen that with companies in the past.

Which one specifically? Because Amazon Web Services was profitable in nine years. The total capex between 2002 and 2017 was $52 billion. And that was for all of Amazon, not just AWS, between 2002 and 2017. If we're talking about the dot-com bubble, the dot-com bubble's economics were actually fundamentally different. Fiber was much cheaper and also had more uses, more obvious uses. Let me put it really simply. I know what you're getting at, but to put it really simply, my point isn't wrong that it took nine years to get profitable for Amazon. And there were many

other dot-com companies that took many, many years to get profitable. But Amazon was also not just a cloud compute company. It was a basically went from a bookstore to a store to a two-way cloud compute company added to the size. Totally different business. Right. Yes. Yes. The point I'm making is the way this is being invested in doesn't have the recovery story

from the dot-com bubble. Because with the dot-com bubble, the dark fiber that was laid and the interchanges and the various bits of lucent telecom stuff that was left abandoned, it didn't cost a ton of money to operationalize it. And its running costs were not incredibly expensive. Yes. If data centers end up not being built, it's going to cost just as much money to finish them in 10 years as it will today.

And then on top of it, electricity costs are likely to be more in the future, not less, and there will be less customers. I understand where people get this from. It's just a difficult, difficult to square with me. Yeah, I think, so those points I agree with, and I think it's something that needs to be talked about more, and I'm glad that you're bringing this up. My point, just to be clear about what my point was, the idea of these businesses, these business models not working yet, to me, doesn't seem to be a huge problem. But when you

look at the amount that they are spending and when you look at just the sheer size of the spending, to a lot of your points, I do wonder if when we extrapolate this 10, 15, 20 years down the line, whether it will be, whether it will look like the dot-com boom and whether these internet companies will be comparable. And I am increasingly thinking, they won't. And something that I've been thinking, and this is something that Sam Altman has said, is I wonder if it looks like utility services. I mean, Sam Altman has said, Open Eye is going to be a utility company, and we've seen this with utility companies before, where, you know, having a regular market doesn't really work because the economics don't make sense,

and so you basically just have to have one company that's operating for a specific area. And so I guess what I'm getting at is the business model, I don't write it off entirely, but it does seem that it will have to be different fundamentally from other businesses. And I wonder if you agree with that, or if you think that they just won't work at all, and they will therefore implode. So if we think about the dot-com comparison, and we break down the kind of businesses we had, with the dot-com bubble you had really, it was really two bubbles. It was the telecommunications bubble and the software bubble. The software bubble and the e-commerce bubble, the Pets.coms, the Cosmos and such, their economics didn't make sense because they didn't make them make sense.

They just were the Pets.com, I think, was spending like $250 a customer or something insane like that. But it was being invested and it involved the movement of physical goods. And those are margins you can bring down as Amazon did, build their own logistics network. And also, chewy.com is basically Pets.com. Cosmo now exists as Instacart. Like there are Webvan, pardon me, I think is Instacart now. Not the literal same company, the same business model. In the AI bubble, you really have three different kinds of companies.

You have AI labs. You have AI startups, so wrappers. And then you have infrastructure. Infrastructure within AI, data sense of GPUs, is one of the most commoditized businesses of all time. It's a horrible business, but it's also, there's really no difference between a Corweave and a Nebius and an iron or a Lambda. They're all backed by NVIDIA. They're all feeding money from Jensen Huang to Jensen Huang. Point is, is the, those companies do not have really, like, there is no changing this business model.

Even if, I don't believe this, there was a chip in the future that was theoretically profitable. Blackwell isn't. Vera Rubin won't be. Hopper wasn't. None of the Nvidia GPUs are clearly profitable for operators, otherwise we would have someone making a profit. Within the telecoms and dot-com bubble. Just to clarify what you mean that, profitable to use those GPU chips. chips and then generate a return from an AI model.

Yes, exactly. More money than they have spent. Yes, but not Nvidia. Very profitable for Nvidia. Invidia, incredibly. That's the thing. Invita, memory stocks, they're all profitable because they're pre-selling a bunch of capacity. Storage and servers and all that.

But a vast majority, like the dot-com bubble, there was also much smaller than this as far as actual money being invested. The venture capital was a, I think one round from Anthropic this year is bigger than all the venture capital that went in. in a dot-combo, it's insane. And that's, I mean, even with inflation, it's still pretty close. AI Rapper startups are all dying. And also, the way that they are raising and dumping money is not something that's creating

any useful residue. Harvey, for example, I think they've raised $900 million, and they make $200, 300,000, 300 million ARR. Ooh, those are stinky margins. But the point is, it's not like Harvey is buying a bunch of stuff and doing proprietary. data or buying servers, like happened a lot during the dot-com bubble because AWS didn't exist so people were buying their own servers. There's no useful residue. All of that money is being dumped directly into OpenAI and Anthropic. Anthropic at OpenAI also do not have assets.

They don't have CAPEX. They have their models. They have their model weights, which, by the way, Microsoft has full and complete access to Open AI's model weights, I confirmed today. Yeah. And so they don't have their, they have talent, I guess, they have research, but they don't really have, they just have their models. That's the only thing. Those companies die. There's not really any useful residue to pick up. Perhaps someone could buy the assets of Anthropic, even though Amazon and Google will take them, but there's not really a thing to recover. And then you get to the coreweaves Nebius's irons of the world. And again, you've got a bunch of old GPUs, probably in data centers that haven't been built yet, which means that there's nothing really

to pick up, other than you pick up a cheap office chair or a cheap server back in the dot-com bubble. You could do something with that. What are you going to do with a GPU? Especially when it's insanely expensive to run, I have a source of Oracle that told me it's about $6.30 cents an hour of cogs to run a B300, pardon me, GPU from Nvidia. These margins do not make sense. These costs don't make sense. I don't see how you pick up the pieces here. I don't see it at all. And indeed, I don't think there's much useful infrastructure left over. And this is the big argument that people are making, because people are saying, we're in a bubble now, we're in a bubble now. But don't worry, after the dot-com bubble, people picked up stuff for cheap.

What stuff? Right. We already have piles of unused GPUs. Super Micro had a multi-billion dollar order canceled from Oracle. They have at least a billion dollars a beef 200 chips that no one wants to buy. We've already got the fallow inventory. Nothing's happening. I'm sure someone will do something, but nothing's going to be cheaper in 10%.

10 years. Things worked like you could pick up the servers and you could actually put them in it. Like there's ways that you could make that useful from the dot-com bubble. It's not really this story here. I think the part where I start to disagree is, I mean, I'd be interested to hear what your views are on AI as a use case. Like we've seen what I believe to be sort of BS industries before. One of them in my view was the crypto industry that I was very critical of for a long time. That to me was people trying to sell us a solution to a problem that doesn't exist and then hammering it over and over and over again.

And my view was this isn't really a problem. This isn't really helping people. There isn't much of a use case here. With AI, I don't think of that the same way. I mean, I see a lot of what you're saying, which is companies are almost trying to force AI down their employees' throats because they just, they know or they believe that this is the most important thing that they have to do, figure out how to use AI. And I think a lot of that is BS in a lot of ways. But at the same time, I do find AI useful in certain areas of my life. I know that other people do as well. I know that

open AI has a billion weekly active. I know that nearly nine and ten developers are using AI to code. What percentage of them are being forced to do that? I don't know, but I doubt that the answer is all of them. My belief is that there is some value here. here, and the question is how much of it is real, how much of it is fake, and how do we figure out the proportions between the two? But sometimes I get the sense that you believe that there is no value, that it won't work at all. I think that there is, I've, I have very specifically said, there is value in coding. I've said that for years. That's, classic misinformation there, not from you. It's a spread, it's spread from, it's spread all around by certain.

No, I'm just, I'm hearing what you're saying, and I'm trying to. No, no, no, no, no, but you're not, you're not saying this. Just being clear. You've been very, you've been very fair to me. The point is, there is use, but all of that use and that utility is subsidized. Yes. So GitHub Copilot. I talk a lot about Anthropic. We can talk about GitHub Copilot. They were selling $15 for a dollar. Like that's fundamentally there was a person who posted. They've seen someone who spent $39 bucks a month. They spent $1,500 worth of tokens. Someone else, five grand, someone else, $3,000. Someone else, $200. This is direct money to Anthropic and Open AI.

This is not something where it's, oh, they can claim they're profitable and inference. This is just straight up token bum. I would love to see how popular this was if people actually paid what it cost. Because I think that right now, this all you can eat nonsense, is inflating the value of it. Because if you were paying, Anthropic estimates $13 a day is what someone will spend using Claude Code. That's a lot of money. It's hundreds of dollars a month. I don't think most people get that much value out of it.

If you had to every little fun little turn you had with Open AI, a couple cents each time, you're spending several dollars a day. I don't think people would think it was quite as useful. I also, the hallucination problem, the incorrect information, it applies everywhere. It's a very bad thing. But on a fundamental utility level, if this was being charged at cost, I actually think that every journalist should be barred from using it in any way other than token-based billing, because that's the only way you see the realistic cost here. Because, yeah, if you get this thing massively subsidized

and you don't know the real costs, you're creating a completely fantastical environment to explain these things. 100%. And so, and people will argue, well, the cost of intelligence has come down. No, not at all. That is a very weird aberration where they've said, well, to do a task that you did two years ago,

it's now 10x cheaper if your dog's awake, but your cats asleep. And it's like a weird, weird series of asterisk, like Barry Bonds is baseballs. The thing is, we are yet to actually meet the point when people really have to judge how valuable this is. We're seeing it already. Service Now just blew through the AI yearly token budget in, what, five months? Uber burned through it in four. We're seeing now the real costs start to come in. That's where my big argument is.

And this stuff is not getting cheaper. It isn't. They might be charging less for some models, but that is not necessarily helpful if the models are burning more tokens. Killer code had a great piece about this. So in the end, it comes down to, yeah, if this costs nothing, that would be a completely different conversation. But this costs everything. And the argument that people keep making is that training costs will go away. No, they won't.

When? How? In fact, very simple question. How does Anthropic become profitable? And my God, if someone says they're profitable and inference, that comment, came from three separate times when Anthropics Dario Amade, Mr. Wario himself, has said, well, here's a stylized fact. And say you're 50% profitable on inference.

It's always this weird duck and weave thing that is decidedly non-gap and also entirely made up. Like he even said it was made up. So people have come up with this vision that inference is profitable. If it was, 85% of Anthropics revenue comes from API calls. Why is Anthropic losing billions of dollars a year then? And if the answer is training, okay, when does training go away? Why is training getting more expensive every year?

The answer is training is a cost of goods. Yeah. There is no profitability for any of this, and you have to keep training the models because of model drift. I think these are all reasonable points. I would add that this as a concept isn't new, and this is sort of what venture capital is all about. and this is sort of taking it to another level. But if, you know, the idea of subsidizing a product that making it a lot cheaper and in some cases free

until it's reached a level of scale and a level of penetration that people are willing to pay for it, and then suddenly you can sort of turn the business on and it works. I think a good example of that would be Uber, for example, where, you know, we're all taking Uber's because it was subsidized and the VCs were essentially paying for our rides. We keep using it and using it and using it. the network effects grow and then eventually everyone's using Uber and then eventually it turns into

a real business that is profitable. Now, to your point... Yes, but this would be, this would be like if Uber paid for the cars, paid for the gas, the gas was giraffe blood, they paid for the customer's clothes. Like, I'm being facetious, but like, it is, the economics of Uber were also, they didn't do... To a different degree, yes. Well, also, they didn't do the same kind of subsidy. They made a trip, cheaper, way cheaper, way, I remember those days, way cheaper, but they didn't charge, like, they still charge trip to trip, point to point even. This is, we are charging, you're paying $20 to drive 100 miles a month, except in reality, each mile is costing Uber 25 bucks or more. And there is no compelling argument as to how that changes. Yeah, I mean, it seems as though

it's a bet on eventually when we flip that. switch, the prize is going to be so gigantic that it eaks out what has been a gigantic cost. And to your point, the costs are gigantic and they're not really going down. I guess the question becomes, will that happen? I mean, there's a question of the certainty with which the number is going to be negative versus positive when we turn that switch on. Yeah. Lots more that we can get into.

I do have to wrap us up here. but I'm sure we will be discussing this another time. Ed Zitrin is the author of The We're Ed at Newsletter. He is the host of the Better Offline podcast. Ed, I'm so glad we finally had you on the podcast. Lots more to get into. Thank you for joining me. Thanks so much for having me.

After the break, Trump meets with Xi Jinping. And by the way, we're heading out on tour at the end of the month. So for more info and to get tickets to a show near you, head to Prof. Gmarkets tour.com. Support for the show comes from Monarch. With the weather warming up, you're probably looking at more time out and about. But you can't really enjoy your time in the sun if you're completely caught up in how much money you're spending and how much you have left in your bank account. Thankfully, there's Monarch.

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We're back with Profi Markets. President Trump just touched down in Beijing for his first visit in almost 10 years. He arrived with 17 CEOs including Tim Cook, Elon Musk, Jensen Huang, and Larry Fink. Trump and Xi Jinping are sitting down

to discuss trade. AI rare earth. Taiwan and Iran. This meeting comes as the U.S. and Iran remain deadlocked and the Strait of Hormuz is still closed, disrupting the globe. The U.S. and China are also in the midst of a fragile trade truce that is set to expire this fall. So here to help us break down what we might see in this meeting. We're speaking with James King, host of the Profti Media's China Decode podcast and also Senior Research Fellow at Chatham House. James, good to see you. Thank you for joining us. What are we going to see in this meeting, what are you looking out for? Thanks a lot, Ed. Great to be with you. I think that

obviously the two sides are hoping for different things. For Trump, I think this summit is all about three Bs and one eye. The three Bs are beans, beef and Boeing jets. Those are the big deals, I believe, that the Trump delegation is hoping for. And the eye, of course, is Iran. I think that the White House is understood to be kind of needing Chinese acquiescence, if not assistance, in pressuring Iran to unblock the Strait of Hormuz and try to end the war. So to me, that's the kind of crystallization of what the U.S. side is looking for. The Chinese side, well, these summits for China are all, always about Taiwan. Beijing will be hoping that either Trump will say something big on Taiwan, that moves the U.S. closer to China's position on Taiwan,

and particularly whether Taiwan is an independent country, which Beijing strongly objects to or not. So Taiwan, I think, will be there. And also, I think, that China will be hoping that access into the U.S. market will be smoother for lots of Chinese companies. And I think the last thing is more of a kind of mood music thing, but an important one. To me, the Chinese want to give Trump face so that the US in the future doesn't turn vengeful again against China.

So to me, those are the outlines of what either side is looking for. But, you know, these summits, they can surprise. There is an extraordinary meeting going to take place between Trump and C in the United States. the Temple of Heaven in Beijing. It's an amazing old shrine to the old kind of agricultural gods of China. So that's kind of amazing. I don't know. There could be surprises, but at the moment, I think those are the contours.

Why did he bring all these CEOs along with him? What are they going to do? What's Jensen Huang doing? What's Elon doing? Tim Cook? What is their role in all this? I think, yeah, as you rightly say, Stephen Schwartzman from from Blackstone and Black Rocks, Larry Fink,

Elon Musk from Tesla and SpaceX, Tim Cook from Apple. They're all there. Jensen Huang from Invidia is there as well. And Trump already said on the plane as he was coming over, quote, I will be asking President C a leader of extraordinary distinction to open up China so that these brilliant people can work their magic

and help bring the People's Republic to an evil. higher level. My sense is that he's not that interested in bringing the People's Republic to an even higher level. I think he's interested in helping these companies win deals, win market access, and maybe stave off some of the actions that we've seen China begin to take against, not just American companies, but all companies that would like to put sanctions on China or to decouple from China. So there's a very, there's a very, very major commercial aspect to this whole trip as well. Which seems striking to me because it seems that at the start of this administration, it was all

about kind of separating and kind of putting up the tariffs, figuring out a way to get ahead of China, sort of establishing we are two different opposing nations. I mean, the idea of bringing these CEOs, I mean, we even saw the chip restrictions, which directly affected Jensid Wang and MVIDIA. So the idea that he was. he's bringing these guys along, and I guess trying to reestablish a sense of a relationship and a trade relationship. I don't think that's a bad thing. I'm just a little confused as to why he's doing it. It seems like a 180 to me. Is that right? Yeah, that's such a great insight, Ed. If I had to sum this up in one sentence, I would say that Trump is going to Beijing to rectify some of the

problems that he himself created. As you rightly say, the US put 145% tariffs on Chinese exports at one point last year, Chinese exports of the US. And then after China said that it was going to restrict exports of critical minerals, these are critical minerals that are needed to make US weapons, that are needed by all the big US tech companies to make the products that they sell. after China threatened, well, did that, and then, you know, engaged with the US in a series of talks and finally back down, Trump then blinked. And now the terrorists are back down to 47.5% on average. So to me, the key inflection point in this relationship, in this Trump administration's relationship with China, has been China's invoenix. of these critical mineral export sanctions on the U.S. last October, and then Trump blinked. The tariffs, the U.S. tariffs on Chinese exports came down, and this trip has sort of, you know,

been in the offing ever since. This is a patch-up work. This is an attempt to make nice to the Chinese. And this is why I was saying on the previous episode of China Decode, if you ask me, this is the first summit in U.S.-China history where the Chinese president has the upper hand, and Trump is going there asking, you know, rather than the other way around. Yeah, it seems so striking and especially given a conversation that I had with your co-host, Alice Hahn, last week, where she pointed out that, I mean, when you think about the after-effects of the Iran War, the real winner here in a lot of ways has been China. China has the upper hand in a lot of ways. And now we have Trump going to China in a

position, in probably a weakened position for both those critical minerals point that you point out there, but also when it comes to Iran, and you've got inflation, which is rising, and you've got consumer sentiment plummeting and people saying they don't support this war, it seems like he's almost begging for something here, in which case he's going to have to give them something in return, which makes me think maybe he will give them something when it comes to Taiwan. Well, yeah, I must say our thinking is very much aligned on this. In addition to what we've just been talking about, you know, the commercial side of it, obviously Trump is looking for deals.

He also needs China on the issue of Iran. And I think that Iran is becoming a more and more pressing issue for the U.S. There are, you know, there are all kinds of secondary effects that we're beginning to see. I really think that Trump needs to, you know, get done with this war with Iran. And the root to that could lie significantly through China. Obviously, China is the biggest trade partner of Iran. It buys by far the biggest chunk of Iran. the Iranian oil exports. It has long-standing relationships with Iran. It's got a 25-year economic

agreement with Tehran, et cetera, et cetera. So I think that is also what Trump is aiming at. So, yes, I believe, I wouldn't quite say that Trump is going to Beijing as a supplicant, but I definitely think that Trump has a bigger ask from the Chinese than the Chinese have of Trump. And this is why I really do think this is historic. The first time that we've seen an American president go to China for a summit under those conditions. I mean, I've been covering these U.S.-China summits since the middle of the 1980s. This is remarkable. This really is remarkable.

All right. James King, host of the China Decode Podcast and Senior Research Fellow at Chatham House. To hear more from the China Decode team, Alice and James will be going live this Friday. May 15th at 10 a.m. Eastern on substack to break down the meeting between Trump and Xi Jinping. They will be joined by Kevin Shoe, founder of Interconnected Capital and writer of the Interconnected newsletter. To catch it live, become a subscriber of ProfG Plus at Profgmedia.com. You will also get the China Decode newsletter every week and first notice on future live streams. James, thanks for joining us. Thanks so much, Ed.

The producer price index was published yesterday. This is a measure of wholesale inflation, i.e. the prices that businesses are paying for domestic products, and the results were quite ugly. The index rose 6% from a year ago. That was higher than expected, and it was also the largest increase we've seen since 2022. Yes, 2022, the year we experienced the highest inflation in 40 years and also the year the stock market, fell more than 18% as a result. Now, going back to 2022, let's just remind ourselves why that all happened. For one, we had COVID, which blocked up global supply chains, we made it more difficult and more expensive to transport goods around the world. And two, Russia launched a war on Ukraine,

which interrupted global energy flows and resulted in higher gas prices around the world. Emphasis on around the world, because inflation didn't just rise in America. It wrote, everywhere. Global inflation hit roughly 8% that year, which is why it doesn't really make sense when people say Biden is the reason prices went up. No, prices went up because of two extremely large exogenous events that were actually out of our control. Now let's compare it to today. Why are prices rising in 26? There are two reasons. Number one, tariffs. Last year, we decided to issue indiscriminate tariffs on our global trading partners, which immediately raised prices. for our own consumers and brought inflation up from 2.3% before Liberation Day to 3% in less than

six months. And the second reason that prices arising is, of course, Iran. This year, we decided to drop bombs on the nation that controls roughly a quarter of the global flow of oil, and, as expected, fuel prices shut up, freight prices skyrocketed, and now gas prices in America are up roughly 30%. You will notice the big difference between inflation this year versus inflation four years ago, and that is this year's inflation is notably self-inflicted. We chose it. If we had just sat around and done nothing, no tariffs, no wars, inflation would be roughly half where it is today. We would have hit the Fed's target of 2%. And we would have been on track for rate cuts. But it's Instead, the PPI is rising, which means the CPI will rise even further, and we are now looking at the possibility of rate hikes.

You could not have dreamed up a more self-destructive economic policy than the one we are witnessing today. AI might be our saving grace, we'll see, but when it comes to the economic decisions we've made, we have totally and utterly let ourselves down. First word, own, second word, goal. Okay, that's it for today. This episode was produced by Claire Miller and Alison Weiss, edited by Joel Patterson, and engineered by Benjamin Spencer. Our video editor is Brad Williams. Our research team is Dan Chalon, Isabella Kinsel, Chris No Donahue, and Mia Silverio, and our social producer is Jake McPherson.

Thank you for listening to Profty Markets from Profit Media. If you liked what you heard, give us a follow. I'm Ed Elson. Tune in tomorrow for our conversation with Professor Aswath Demoderen. Support for this show comes from Vanta. If you run a business, you don't need us to tell you that risk and regulation are rising. More and more customers expect clear proof of security before they'll commit.

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