AI Skeptic: This Business Makes No Sense

Added: 2026-05-15

[00:00:00]I think that 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 AAI seem particularly concerned with bringing those costs down. These margins do not make sense.

[00:00:21]These costs don't make sense. I don't see how you pick up the pieces here. I don't see it at all.

[00:00:28]Today's number two. That's the number of times Sir David Atenburgh has been kned for his services to British television and conservation. It appears that after Brexit, the UK has run out of people tonight.

[00:00:48]Welcome to Profy Markets. I'm Edson. 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 Cali, the odds of a rate hike this year have steadily climbed to 31%.

[00:01:15]Meanwhile, Apple 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.

[00:01:24]We will be discussing that shortly as well. Okay, what else is happening?

[00:01:31]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 Zitran, 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. Uh, our producer Cla mentioned this to you offline, but uh, 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. We're finally here. So, thank you uh for joining me.

[00:03:06]>> Thanks for having me.

[00:03:07]>> 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 in 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. across the board with public stocks, nobody is showing a profit from AI. And for the most part, nobody is showing even the revenue they're making from AI. And 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 AAI's venture capital funders and probably left over as your 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 open AI. In fact uh between Microsoft, Google and Amazon $748 billion of their 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 OpenAI 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 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 hyperscalers only has around one and a half gawatts 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.

[00:05:00]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 has 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. Uh I agree with you your points about the data centers, the fact that they're not coming online and there's 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 uh regulation and through uh 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.

[00:06:11]These are privately reported but that's the way private companies work but open AI was $2 billion in ARR in 2023. It's up to $25 billion in ARR today.

[00:06:22]Anthropics reached $30 billion ARR. You know it took Salesforce about 20 years to get that. They've done it in under three years. I mean, that's 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 as what whatever they can to get this through.

[00:06:50]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 around as well, but overall I don't want to write it off. What would you make of that?

[00:07:05]>> 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.

[00:07:12]Been yeah, coming up on four years since Chat GPT came out. And if you think about what constitutes early, it really is investment and innovation. We have had all the king sources, all the king's men trying to make generative AI into something that generates profit. Hasn't happened yet. No one has happened it to.

[00:07:30]I also have serious questions about how Anthropic is doing revenue. Krishna Ralph, their CFO in the department of war laws sue actually said in an affidavit on March 9th, 2026 that they had made $5 billion in lifetime revenue.

[00:07:44]That does not match up with any of the reported previous annual recurring revenue or AR 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. I my theory is that when so with the largest clients they have clients don't pay in a rears smaller ones do but the largest don't they buy massive amounts of tokens in advance I think anthropic for example if someone is going to do $50 million worth of tokens and it lasts over 6 months they're going to take that money up front they're going to say wow in that month cuz all AR is is month times 12 or 13 depending on how they do it so I think both openai 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 Curser and now they've been kind of sort of not really bought by Elon Musk. They 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 suggest there is a fundamental weakness and no real major business model here. We still don't know Anthropic's 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 a 10 10 20 $30 million a month? It's not actually that much for what is meant to be an industry changing thingamajig. And there are signs that the economics don't work. The biggest being that Microsoft, GitHub Copilot, by the way, one of the largest clients of Anthropic, is moving to tokenbased billing on June 1st, 2026.

[00:09:57]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 that 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.

[00:10:27]>> So some really interesting points in there. I I would still disagree with your point that it isn't early. I mean I when we're talking about technologies of this size I I still think four years is early and to the point about profitability like you know you you look back to the internet it took a long time for the internet to get running Amazon took 9 years before it was consistently profitable and eventually I mean it it can you can take decades before your business model model works properly and we have seen that with companies in the past when we >> this one specifically just because Amazon web services was profitable in 9 years. The total capex between 2002 and 2017 was 50 $52 billion and that was for all of Amazon just not not just AWS between 20 2002 and 2017. If we're talking about the dot bubble, the 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 isn't wrong that it took it took 9 years to get profitable for for Amazon. And there were many other uh.com companies that took many many years to get profitable.

[00:11:40]>> But Amazon was also not just a cloud compute company. It was a basically went from a bookstore to a store to a cloud computing to the side.

[00:11:51]>> Right. And the point I'm making is the way this is being invested in doesn't have the recovery story from the com bubble. Because with the 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. 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.

[00:12:36]>> Yeah, I think those points I I I agree with and I think it's something that needs to be talked about more and I'm glad that that you're bringing this up.

[00:12:43]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 the sheer size of the spending to to a lot of your points I do wonder if when we extrapolate this you know 10 15 20 years down the line whether it will look like the dot boom and whether these internet companies are will be comparable and I am increasingly thinking they won't and something that I've been thinking and and this is something that Sam Alman has said is I wonder if it looks like utility services I mean Sam Alman has said open AI 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 a a specific area. And so I guess what I'm getting at is the business model. I 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 uh or if you think that they just won't work at all and they will therefore implode.

[00:14:02]>> So if we think about the dotcom comparison and we break down the kind of businesses we had with the dotcom 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 bucks a customer or something insane like that.

[00:14:25]But it was being invested and it involved the movement of physical goods and there 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 Web van, 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 rappers, and then you have infrastructure.

[00:14:54]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 Corewave and a Nebius and a iron or a Lambda. They're all backed by Nvidia. They're all feeding money from Jensen Hong to Jensen Hong. Point is is that 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 within the telecoms and >> just to clarify what you mean there.

[00:15:38]Profitable to use those GPU chips and then generate a return from AI model.

[00:15:43]>> Exactly. More money than they have spent.

[00:15:45]>> Which is I love.

[00:15:46]>> Not Nvidia. Very profitable for Nvidia.

[00:15:48]>> Nvidia incredibly. That's the thing.

[00:15:49]Nvidia, memory stocks, they're all profitable because they're pre-elling a bunch of capacity, storage and servers and all that, but a vast majority like the com bubble there was was also much smaller than this as far as actual money being invested. Venture capital was a I think one round from anthropic this year is bigger than all the venture capital that went in during the com b. 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 200300 million ARR.

[00:16:33]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 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 and OpenAI also do not have assets. They don't have CAPEX.

[00:16:57]They have their models. They have their model weights, which by the way, Microsoft has full and complete access to OpenAI's model weights. 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.

[00:17:09]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 core weaves, 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 com bubble. You could do something with that. What you going to do with a GPU? Especially when it's insanely expensive to run. I have a source at Oracle that told me it's about $6.30 an hour of cogs to run a G uh 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 cuz people are saying, "We're in a bubble now. We're in a bubble now." But don't worry, after the.com bubble, people picked up stuff for cheap. What stuff? We already have piles of unused GPUs. Super Micro had a multi-billion dollar order cancelled from Oracle. They have at least a billion dollars of B200 chips that no one wants to buy. We've already got the FOW inventory. Nothing's happening. I'm sure someone will do something, but nothing's going to be cheaper in 10 years. things were like you could pick up the servers and you could actually put them in like there's ways that you could make that useful from the com bubble. It's not really the story here.

[00:18:43]>> The I think the the part where I I start to disagree is 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 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 I 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 activives. I know that nearly nine in 10 developers are using AI to code. What percentage of them are being forced to do that? I don't know. But I doubt that that that the answer is is all of them. My belief is that there is some value 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 there is no value that >> I think there is. I 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 it's a it's a spread it's spread from it's spread all around by certain >> words. I wouldn't say I'm hearing what you're saying and I'm >> No, no, no. But you're not you're not saying this. I'm just being clear.

[00:20:25]You've been very you've been very fair to me. Point is there is use but all of that use and that utility is subsidized.

[00:20:36]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.

[00:20:53]Someone else three grand. 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 on inference. This is just straight up token bum. I would love to see how popular this was if people actually paid what it cost. Cuz I think that right now this all you can eat nonsense is inflating the value of it.

[00:21:17]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.

[00:21:26]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 OpenAI, 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 tokenbased billing because that's the only way you see the realistic cost here. Cuz yeah, if you get this thing massively subsidized and you don't know the real cost, you're creating a completely fantastical environment to explain these things. 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 cat's asleep." And it's like a weird weird series of asterisk like Barry Bonds's baseballs.

[00:22:28]The thing is, we are yet to actually meet the point when people really have to judge how valuable this is. We are seeing it already. Service Now just blew through their AI 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.

[00:22:56]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.

[00:23:11]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 on inference, that comment came from three separate times when an when anthropics Dario Amade, Mr. Wario himself has said, well, here's a stylized fact. Um, say you're 50% profitable on Inference. It's always this weird duck and weave thing that is decidedly non-GAAP 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 anthropic's 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. It's there is no profitability for any of this and you have to keep training the models because of model drift. Yeah, I mean just I think these are all reasonable points. I would add that this as a concept isn't new and this is sort of what this is what venture capital is all about and this is sort of taking it to another level. But if you know you 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 switch the flip and 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 Ubers 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. Yes, but this would be this would be like if Uber paid for the cars, paid for the gas, the gas was giraffe blood, uh they paid for the customers clothes like >> I'm I'm being facitious, but like it is the economics of Uber were also they didn't do a degree. Yes.

[00:25:15]>> Well, also they didn't do the same kind of subsidy. They made a trip cheaper.

[00:25:20]Way cheaper. Way I remember those days.

[00:25:23]Way cheaper. But they didn't charge like they still charge trip to trip. Uh point to point even. This is we are charging you're paying $20 to drive a 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.

[00:25:45]>> 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 ees out what has been a gigantic cost. And to your point, the costs are gi gigantic and they're not really going down. I guess the question becomes, will that happen? I mean, there's a question of of the certainty with which the numbers going to be negative versus positive when we turn that switch on. Um, >> yeah.

[00:26:15]Lots more that we can get into. I do have to wrap us up here. Um, but I'm sure we will be discussing this another time. Ed Zitron is the author of the Where's Your Edsletter.

[00:26:25]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. Uh, thank you for joining me.

[00:26:33]>> Thanks so much for having me.

[00:26:35]>> We'll be right back. And if you're enjoying the show, be sure to subscribe to the Prof Markets YouTube channel at the link below. Support for today's show comes from Granola.

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[00:29:01]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 Frink. Trump and Xiinping are sitting down to discuss trade, AI, Rare Earth, Taiwan and Iran. This meeting comes as the US and Iran remain deadlocked and the straight of muzz is still closed disrupting the globe. The US 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 ProfG Media's China Decode Podcast and also senior research fellow at Chattam 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?

[00:29:51]>> Thanks a lot, Ed. Great to be with you.

[00:29:52]Um, I think that obviously the two sides are hoping for different things. For for Trump, uh, I think this summit is all about three B's and one I. The three B's are beans, beef, and Boeing jets. Those are the big deals I believe that uh, the Trump delegation is hoping for. Uh, and the I of course is Iran. Um I think that the White House is understood to be kind of needing Chinese acquiescence if not assistance in pressuring Iran to unblock the straight of Hormuz and try to end the war. So to me that's the kind of crystallization of what the US 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 US closer to China's uh position on Taiwan and particularly whether Taiwan is an independent country which Beijing strongly objects to uh or uh or not. Um so Taiwan I think will be there and also um I think that um China will be hoping that access into the US market will be smoother for lots of Chinese companies.

[00:31:14]Um 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 uh an extraordinary meeting going to take place between Trump and C in the temple of heaven in Beijing. It's an amazing old shrine to the old kind of um agricultural gods of China. Um so that's kind of amazing. I don't know there could be surprises but at the moment I think those are the 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 what's Elon doing? Tim Cook, what is their role in all this?

[00:32:04]>> I think yeah, as you as you rightly say, um Steven Schwarzman from Blackstone and Black Rocks, Larry Frink, Elon Musk from Tesla and SpaceX, Tim Cook from Apple, they're all there. Jensen Hang from Nvidia is there as well. And uh 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 even 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 uh interested in helping these companies win deals uh 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 major uh 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 uh figuring out a way to get ahead of China sort of establishing we are two different opposing nations. the idea that he's bringing these guys along and I guess trying to reestablish a sense of a relationship and a trade relationship.

[00:33:38]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?

[00:33:45]>> Yeah, that's such a great insight, Ed.

[00:33:47]Um, 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 uh the US the US put 145% tariffs on Chinese exports at one point last year Chinese exports to the US and then after China uh 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 um um and then you know engaged with the US in a series of of talks and finally backed down uh Trump then blinked and now the tariffs are back down to 47.5% on average. So to me the key inflection point in this relationship in Trump in this Trump administration's relationship with China has been China's uh invocation of these critical mineral export sanctions on the US last October and then Trump blinked. uh the tariffs the US tariffs on Chinese exports came down and this trip has sort of you know been in the offing ever since. This is a patchup work. This is an attempt to make nice to the Chinese. And this is why I was saying on the previous episode of uh China Decode. If you ask me, this is the first summit in US China history where the Chinese president has the upper hand and Trump is going there asking uh you know rather than the other way round.

[00:35:36]Yeah, it seems so striking and especially given a conversation that I had with your co-host Alice Han 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 a 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. Yeah, I mean our thinking is very much aligned on this. Uh in addition to what we've just been talking about, you know, the commercial side of it, um obviously Trump is looking for deals. Uh he's also needs China on the issue of Iran. And I think that Iran is becoming a more and more pressing issue for the US. Uh there are, you know, there are all kinds of secondary effects that we're beginning to see. Um I really think that Trump needs to, you know, get done with this war with Iran and the route to that could lie significantly through China.

[00:37:06]Obviously, China is the biggest trade partner of Iran. It buys by far the biggest chunk of of the Iranian uh oil exports. It has long-standing relationships with Iran. It's got a 25-year economic agreement with with Thran, um, etc., etc. So, I think that is also what Trump is aiming at. So yes, I 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 uh that we've seen an American president go to China for a summit under those conditions. I mean, I've been covering these US China summits since the middle of the 1980s.

[00:37:57]This is remarkable. Uh, this really is remarkable.

[00:38:01]>> All right, James King, host of the China Decode podcast and senior research fellow at Chattam House to hear more from the China Decode team. Allison James will be going live this Friday, May 15th, at 10:00 a.m. Eastern on Substack to break down the meeting between Trump and Xiinping. They will be joined by Kevin Shu, founder of Interconnected Capital and writer of the Interconnected Newsletter. To catch it live, become a subscriber of ProfG Plus at profgdia.com.

[00:38:28]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.

[00:38:38]We'll be right back. And if you're enjoying the show, be sure to subscribe to the Prof Markets YouTube channel at the link below.

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[00:40:06]We're back with Profy Markets.

[00:40:09]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.

[00:40:24]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.

[00:40:40]Now going back to 2022, let's just remind ourselves why that all happened.

[00:40:45]For one, we had CO which blocked up global supply chains which 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 rose everywhere. Global inflation hit roughly 8% that year.

[00:41:11]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 2026?

[00:41:27]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 6 months. And the second reason that prices are rising is of course Iran.

[00:41:48]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 shot up.

[00:41:58]Freight prices skyrocketed and now gas prices in America are up roughly 30%.

[00:42:04]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 instead the PPI is rising, which means the CPI will rise even further.

[00:42:38]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. Thank you for watching Profy Markets from ProfG Media. If you like this episode, please subscribe to our YouTube channel and tune in tomorrow for a conversation with Professor Aswath Demodora.