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Ed Elson (Prof. G)

Money Market Matter if money is evil, then that building is hell. Welcome to Prof. G Markets. I'm Ed elson. It is July 21st. Let's check in on yesterday's market vitals. The s and P500 and the Dow declined as conflict in the Middle east escalated. The NASDAQ was flat, oil was volatile. More on that in a moment. The yield on 10 year Treasuries rose. SpaceX stock hit a new low of $120 per share. And finally, Warner Brothers shares fell nearly 4% after a judge temporarily halted its deal to get acquired by Paramount. The judge said the sale likely violates antitrust laws and scheduled a hearing for next month. Okay, what else is happening? Conflict over the Strait of Hormuz keeps escalating and now it is spreading to Saudi Arabia. As of Monday, the US had bombed Iran for nine consecutive nights in response to Tehran's attacks on oil tankers, and Iran had retaliated with strikes across the region. But yesterday, Iran's Houthi allies in Yemen declared a naval blockade against Saudi Arabia. This blockade stands to threaten the primary way in which oil has been able to get around the Strait of Hormuz through a Saudi pipeline to the Red Sea. These developments immediately shot the price of oil back up. Crude is now about $89 a barrel, and the national average for a gallon of gasoline has yet again hit $4 in America, up 15% in just the past week. So to discuss what is happening in the Middle east and also how it's affecting the price of oil, we are speaking with Matt Smith, Director of Commodity Research at KE. Matt, great to have you on the show. A lot happening here. If you could just give us your initial reactions and a quick rundown. What has unfolded and how is it being reflected in oil prices?

Matt Smith

Right now we're tracking those tankers that are passing through the Strait of Hormuz here. Our job has become increasingly more difficult as there's been different routes to try and traverse the Strait. And so what you've essentially got is you've got got the Iranian route, which is right at the top, kind of the north, and then you have the pre conflict highway which was straight through the middle, and then at the bottom you've got the Omani route, which is the kind of the southern corridor. As we've seen escalations increasing here and you've seen some of the tankers being hit that were passing the Omani route, all we're actually seeing now is essentially traffic grinding to a halt again, except for those Iranian tankers and friendlies that are passing the Iranian route. So it's been undulating right over the last few months. You know, March, April and even into May, the traffic was very, very slow. And then, you know, just over the last month or so, we've really seen it pick up because of the signing of the Memorandum of Understanding between the US And Iran. Now that has basically been, you know, dissolved. And we're seeing an escalation here in attacks. As you mentioned, it's been nine consecutive nights. We'll probably have the 10th today. And so this is causing oil prices to start to kick back higher again.

Ed Elson (Prof. G)

Just looking at what happened with Saudi Arabia and that blockade, it seems as though oil supply was figuring out a way to kind of reroute itself away from the Strait of Hormuz or around the Strait of Hormuz. I guess my question is to what extent was that successful and to what extent has that now been kind of blocked? Now that We've got this new development.

Matt Smith

It was working pretty successfully. And so it was able to reroute about three and a half million barrels a day of Saudi crude across to the Red Sea. And so Saudi was exporting about 7 million barrels a day out of the Middle East Gulf prior. So it was able to reroute half of that crude. So that put them in a better situation more than most. So that has definitely helped somewhat cushion the supply shock because all of that crude was then going across to the Red Sea and was heading into the likes of India, China, South Korea, the countries that were otherwise getting their crew from the Mid East Gulf. And it had stopped. And so it was definitely providing some support there and helping, you know, in terms of support in terms of supply and then helping to keep prices in check somewhat now that the Houthis are threatening to do that blockade. They're not actually doing it yet. We're not seeing tankers or anything being hit. But this essentially is the ace that Iran has in its pocket because we've had this escalation that's been happening over the last few months here. And some have said, oh, they could close Baba Mandeb, but they've kind of held that back until the point where the US Would essentially start perhaps attacking infrastructure, energy infrastructure, bridges. And that's kind of the point that we've got to. So then it's for Iran to up the ante here, and that's basically bringing Bab El Mandeb into play. And so it's really just a sign that essentially Iran is getting to the point where they've really got nothing left to lose. Or, you know, they're just getting to the point where they're willing to do this kind of scorched earth tactic. And so we'll have to see how this plays out. But the threat of stopping these flows will definitely have a bullish impact on prices.

Ed Elson (Prof. G)

So the memorandum of understanding has been dissolved. We are now fully at war, striking Iran on multiple consecutive nights. Now they are, as you say, playing their ace card. They are trying to block any of the other supply routes that have been resorted to over the past several months. I mean, it doesn't look good. And we're at $89 a barrel. Gas in America has gone back up to $4. Why should we believe that that number is going to come down within the next, I don't know, several weeks?

Matt Smith

Yeah, no, we shouldn't. And actually, what has developed over the last few months here, or essentially since the beginning of March when this has happened is everyone's been watching that oil price and you haven't felt the biggest impact on that oil price. And the reason for that has been a number of different reasons. China has really come out of the markets. China has just stopped buying oil. They dialed back on their imports by about 5, 5 and a half million barrels per day. So that has been hugely help helpful. You've also had essentially a lot of these refineries dialing back on their activity, so they haven't taken that crude. And that has largely offset the production loss we've seen from the Middle East. But what that has meant is that the pain has essentially been transferred from the oil price across to the products. And so when you talk about gasoline at $4 a gallon on the national average, we see diesel at $5 breaking above 5, and that's going to be really pushing higher because in barrel terms, it's about $170 a barrel for, for a barrel of diesel. And so that's where that pain is coming through is in the products, because we're not seeing those produced, whereas the crude market is somewhat, remains somewhat in balance because of this rerouting and because this less lack of refining.

Ed Elson (Prof. G)

When you look at that number, $89 a barrel to you, does that say that investors are feeling optimistic about the current state of affairs or pessimistic? I mean, does that number hold any biases inside of it?

Matt Smith

One huge bias that it holds is that even if you are bullish on oil markets, you are not going to go and buy a paper barrel because you could have President Trump Tweet something in five minutes time and oil prices could drop by 10, 15%. So I'm not saying prices are manipulated per se, but, but they are definitely under the influence here of things other than fundamentals. And so because of that, you've got some that are simply not getting involved in the oil trade. And that has been happening for a good number of months here. There's a lack of liquidity there. The flip side of that, that's why I point to the diesel market again, is because the US Administration is fixated on the oil price, super fixated on prices at the pump. It's not necessarily paying that much attention or putting that much emphasis at all on diesel prices. And so that's perhaps the least influenced out of all of the petroleum complex. And that's the one that we're seeing absolutely ripping here.

Ed Elson (Prof. G)

I mean, this is essentially the most important question for the US Economy right now, which is what's going to happen to the price of oil. What's going to happen to the price of fuel? As we saw in the previous inflation report, it was lower oil prices as a result of the Memorandum of Understanding that made the number go down more than the previous month. But now we know that whatever pricing was being priced into the market at the time was incorrect. Because the Memorandum of Understanding is over, we're now back at war. Some would argue we continue to be at war the entire time. I won't get into it, but it seems as though what we have seen over the past week is going to have material impact on U.S. consumers and the U.S. economy. And perhaps that isn't being fully reflected or appreciated or priced in by investors and traders right now. How impactful and how bad do you think it will be going forward?

Matt Smith

Well, we could just continue in the status quo, right, in that there's this back and forth between the US And Iran in terms of the attacking of tankers by Iran, the attacking of infrastructure by the US and then in the background there is talks and whispers of diplomacy which helps keep oil prices in check here, which in turn helps keep prices of the pump in check. But when we came into this thing, there was the expectation, you can't close the store strain of Hormuz for two, three weeks, it will cause like Armageddon. Yet here we are four and a half months in. And so it's really realistic to try and consider the scenario. Could this still be closed in November and December? Yes, there are workarounds, there's medium term plans here to reroute crude. But we really could be just continuing to scramble over the next four or five months here. And that's a reality. If that happens, you're not going to be in an environment where prices at the pump and diesel prices are moving lower.

Ed Elson (Prof. G)

What kind of price do you think that would result in if we find ourselves in the same situation that we're in today? And to be clear, I mean, it seems like a couple ships are making their way through the Strait of Hormuz. I mean, is that right or is it just zero?

Matt Smith

There was like a week or so ago or even just before the weekend where you were seeing some getting through there. But the Iranians have turned their focus to targeting those because they were going through the Omega mining route, they were getting like a US Naval escort. And so they're trying to deter any kind of traffic. So the only traffic that we're seeing going through right now is related to Iranian or Iranian and it's just empty tankers. And so but to your point, we were seeing over the last month this increase in traffic going through, increased confidence, increased risk taking, and that really helped the oil market, not necessarily on the oil price, but in the differentials. You really saw the air being let out of the tires there, the pressure taken out as we saw the stranded cargoes in the Mideast Gulf getting out of there. But then again, it's one step forward, two steps back here where we're back to essentially the doors being shut again.

Ed Elson (Prof. G)

So I'll return to my question, which is if we find ourselves in the same position that we are in today, four or five months from now, what would you estimate the price of oil will look like?

Matt Smith

It's gotta be higher. I'll hold up my hands here. And in March, if you'd asked me that question or you may have done actually be like, you know, oil prices should be 120, 130, $140 if you close the straight for months and months. And so perhaps I've been burned by saying that.

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Matt Smith

But maybe if we're going to be pushing above 100 here, that doesn't seem unrealistic at all. If we're in the same scenario that we're in now in four or five

Ed Elson (Prof. G)

months time, if we are in the same scenario that we're in now and it isn't above $100 a barrel, what would have had to have happened to get it lower than that? What truths would need to exist in the world for oil to not be more than 100?

Matt Smith

Well, we'd be drawing down inventories absolutely everywhere that we could. You'd be having tankers sneaking out of the Strait of Hormuz. However, that was possible. Rerouting of crude as much as possible, too. But it's just difficult to see a scenario where you're not pushing into triple digits if this is still the situation in four, five months time.

Ed Elson (Prof. G)

All right. Matt Smith is director of commodity research at Kepler. Matt, appreciate your time. Thank you.

Matt Smith

Thanks, Ned.

Ed Elson (Prof. G)

After the break, why investors are so worried about the latest Chinese model. And for even more markets insights, you can subscribe to my weekly newsletter, simply put@simply put.profgmedia.com.

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Ed Elson (Prof. G)

We're back with profty markets. China just gave Wall street its second deep seek moment. Chinese startup Moonshot AI released Kimik3, the world's largest open source model, on Thursday. On some benchmarks, including front end coding, K3 beats the best models from OpenAI and Anthropic. But the bigger story may be the price tag. Running K3 costs roughly a third of what Anthropic charges for its flagship model, and businesses are starting to notice on OpenRouter, a marketplace for AI models. Chinese open weight models now occupy the top five spots by weekly global token usage. The Nasdaq fell about 1 1/2% on Friday as US tech stocks sold off following the release of Kimik3. So we wanted to speak with an expert who works hands on with both open and closed models. So joining us is Charlie O', Neill, Co Head of Model Training Base 10. Charlie, thank you for joining us. So this Kimi K3 model that was just released had everyone kind of with their hair on fire. We obviously saw The NASDAQ erased 1 1/2% chip stock sold off. A lot of people saying that it was a problem. David Sachs, the former aizaw, called the release quote concerning what do you make of KMEK3?

Charlie O'Neill

Yeah, I think the big story here is not necessarily Chinese models versus American models. I think the big story here is open source versus closed source. So obviously the story we've been told for the last several years is that closed source is going to continue to dominate the American frontier. Closed source labs are going to continue to pull ahead and open source will never catch up to that. And I think what we're seeing with Kimi, with other Chinese models like glm, GLM caused a very big wave. It may not have done the rounds in the same way that Kimi did, but it was certainly a great model and even releases like Inkling from Thinking Machines, which is an American company. What we're seeing is that basically the recipe to build these things, there's no secret source. The big labs, they don't have anything that the open source labs don't have. And open source is going to continue to improve the capabilities and intelligence of the models they release as we scale up the size of these models and the amount of data and compute that goes into them. And so yes, from one kind of aspect it's concerning that this is like a Chinese model that is leading the charge with this sort of open source versus closed source debate. But I think there's really promising signs for the open source ecosystem in general. And I think a lot of people are starting to realize that that's potentially a better world to end up in where compared to where you have maybe a duopoly with OpenAI and Anthropic having these models that pull away from everyone else and they dictate all the terms of access and control that intelligence.

Ed Elson (Prof. G)

Just for the uninitiated, what is the difference between an open source model and a closed source model?

Charlie O'Neill

Anthropic, OpenAI, Google their flagship models are what we refer to as closed source, in the sense that I can ask a question, that question gets sent off over the Internet, goes to their GPUs, which run the model, they do the number crunching, and then they send the answer back to me. I never get to touch the model weights, which you can think of with this big collection of numbers that do a bunch of multipliers to give me my answer. Whereas with open source, I can actually download those numbers. Not only can I host that on my own GPUs, I can also do things like continue to train it myself for specific tasks. So it's really about being able to download the actual weights of the model, rather than than just being able to send a question to it. So you can think of this as like owning the disk for an Xbox game versus having that Xbox game installed through the cloud on your particular Xbox. I can actually see the physical disk.

Ed Elson (Prof. G)

What would be the pros for developing a closed source model instead of an open source model? Why would OpenAI and Anthropic pursue those methods instead?

Charlie O'Neill

I guess there's two answers here. The first answer is the one that OpenAI Anthropic will tell you, which is that these things, as they become increasingly intelligent, we have to think very carefully about how they're applied in society. There's obviously real safety concerns, there's cybersecurity concerns, there's biological weapons development concerns. And so we should really think about who we trust to build and control this intelligence. And anthropic and OpenAI's argument is you should trust us. We are the best at developing this intelligence, and hence we should be the ones to dictate how it's used and how it's applied, basically in perpetuity. There should be a very small number of actors who can choose how what we do with LLMs and intelligence. And I think the real argument is that obviously this stuff is so lucrative that if you do manage to prevent anyone else from developing it, you can capture insanely high margins on the tokens that you're producing. So Anthropic's rumored to have margins north of 80%. I think when there is a case or a world where there's only two major players and you end up in a duopoly, that is a very real possibility to continue. And I think that's obviously very, very lucrative to open Anthropic. And so open source is a threat to them in the sense that those margins aren't going to remain at 80% for long. Of Course there are security concerns. We have to really think carefully about how these things are used. But at the moment it doesn't seem like open source versus closed source. The intelligence ceiling that we've gotten to hasn't led to any increased concerns around can I use this model through open source or closed source? The risk of developing a bioweapon, for instance, is about the same.

Ed Elson (Prof. G)

In either case, it seems that there has been kind of a shift towards both Chinese models, but also open source models. Most of these Chinese models are open source or open weight. Why is that happening do you think? What is the value proposition that developers are deciding is greater when they use these types of models as opposed to one offered by OpenAI or Anthropic?

Charlie O'Neill

I think there's developers who have a

Ed Elson (Prof. G)

very

Charlie O'Neill

inelastic demand for the frontier intelligence and we'll always want to use the most intelligent models. And then there's the ecosystem and the economy in general. The way I like to think of it is that for all the economically valuable tasks that we could plausibly use an LLM for, there is some intelligence threshold at which below that it's very difficult to do the task. And above that you're getting very diminishing returns to having more and more intelligent models. And usually intelligence is correlated with cost. So the obvious argument here is that there is margin pressure on all these startups, all these companies, even enterprise now who are doing these particular tasks with LLMs. They've hit the threshold of intelligence probably even a while ago with open source. Open source has been accelerating rapidly and you just don't need a fable or Mythos level model in order to do some of these things. And you get exactly the same performance if you use a model that's a tenth of the size or even a fiftieth of the size. Post training is also really important here because it means you can teach a much smaller model to do one thing really, really well. Well, as opposed to taking an off the shelf open source or closed source model and trying to prompt engineer your way to doing that task. So post training really changes the economics here. And of course you can only post train on open source models because you can actually touch the weights as opposed to closed source. And so I think margin pressure is a big one. Another one is like Anthropic and OpenAI, I think are realizing that the recipe is the same amongst all these companies. There is no secret sauce. Yes, there's probably a long tail of optimizations, small optimizations that Anthropic and OpenAI have that the rest of the ecosystem doesn't have have. But their moat is no longer in there. Being them being the only ones who can post train or sorry, train, these very, very large multi trillion parameter models, their moat now is starting to shift towards, okay, well if we have a little bit of a head start, what if we try and hit particular verticals? And so anthropic is very clearly doing this. They're going after the verticals of finance and legal OpenAI as well. And so I think companies are really feeling this pressure. If you're a startup or a company in legal or finance and you're using LLMs to do these particular things and you have previously just been an anthropic rapper, you've just got some logic calling anthropic models. You don't have a distinguishing moat between you and anthropic. And so you're starting to think about, okay, what's the one thing I have that anthropic doesn't have? And that's a really nice feedback cycle. I have users who love and hate my product for various reasons and they will tell me what they love and hate and I can use that to improve the intelligence of a model. And again, you do that through training. And the only real way to do that is with open source models. And so I think it's this combination of margin pressure and, and companies wanting to develop their own moat to protect themselves against their vertical being eaten by these closed source frontier labs.

Ed Elson (Prof. G)

It seems like a big piece of the story for an enterprise, for a company that's trying to leverage AI as much as they can. And Alex Kopp talked about this in his interview with CNBC that has since gone viral is basically just the price. Anthropic tokens are expensive. OpenAI tokens are expensive. Tokens from Chinese model providers are less expensive. So my question is, to what extent is there a relationship between price and being open source? Why is it that these Chinese models and these other models that aren't, you know, frontier lab models, how is it that they can offer a product that does the job pretty well, but at literally a fraction of the cost?

Charlie O'Neill

The answer to this used to be simply that the Chinese and open source models were much smaller. So the big labs were the only ones that had the compute to be able to train the really large models. And of course the scaling laws that we have predict that intelligence increases, but with diminishing returns in model size. And so yes, of course the big labs had better and bigger models, but you often could use a much smaller model to do the task. I think now it's more of a case of like, okay, some of these open source models are actually very large and I think K3 was a massive shifting point because previously we'd gone into, just forayed into the 1 trillion parameter model range with the previous Kimi models and Deep Seq very, very recently, but this is almost 3 trillion parameters. This is a big boy. And so now it's much more about, okay, we're really seeing under the hood that the reason that anthropic and OpenAI models are so expensive is because they have great margins, because they were sitting at the frontier and there was no real competitor at the very frontier. And again, a lot of this stuff, it is inelastic. You do demand frontier intelligence. But now we're really seeing, okay, okay, if we do have multi trillion parameter open source models that any company can host on their own GPUs and can post, train and then host on their own GPUs, then what that's telling us, and a lot of analysis is telling us, is that the Frontier Labs margins are just massive. And so I think that the shift that's going to happen now is if there is an alternative that is essentially the Same and to 99.99% of people doing 99.99% of things is indistinguishable like Kimi is indistinguishable from a fable or a GPT 5.6 SOL, we're just going to see those margins shift. So instead of being 80% to the person who trained the model, they might end up being 40% and the rest of that margin is going to be distributed one to the consumer and then two to the rest of the ecosystem. So the compute providers and the inference providers are going to be big wins of all this competition amongst model trainers. It's no longer the case where there's only one or two players who can do this and capture those massive margins. There's going to be much lower margins for model trainers and the rest is going to kind of be spread out amongst the ecosystem.

Ed Elson (Prof. G)

It seems to me that These models, Kimi, K3 and plenty of others that seem to be released practically every month, and then we see all these benchmarks where they're performing either in line with OpenAI's models or outperforming them. It seems like that combined with the pricing pressure could literally bring the Frontier Labs to their knees. If we know that they're already struggling to generate more revenue than they spend, if we know that they're also stacking up billions of dollars in losses and they essentially need to develop more pricing power if they want to get profitable and get cash, cash flow positive over the next few years. And that's been OpenAI's objective. It seems like this is exactly the kind of thing that will get in the way of that. Is this dire to the AI ecosystem? How does this actually play out for the largest names in AI?

Charlie O'Neill

I've obviously been a big advocate and proponent of open source for a long time and want open source to win in some reasonably significant capacity. I think my honest take here is that this isn't the death knell for anthropic@OpenAI. I think ideally, and probably most likely now, we're going to live in a world where there are a few key core frontier players and then a large diverse ecosystem of open source model providers. The reason I think that is because of kind of the distribution of tasks in the economy that we're currently trying to tackle with LLMs and the distribution of tasks in the economy that we should be tackling with LLMs in the next 10 years. I think what we're going to see is a little bit of a bifurcation. I think tasks that we can currently conceive of as being economically useful and all the jobs that we currently do, we are going to rely more and more on open source to be able to do those things. I think very, very frontier things, for instance science and maths discovery, which they have a lagging period. There's a bunch of labs like periodic labs who are really looking forward to tackling science over multi decade horizons with LLMs and this new intelligence. I think the frontier labs are going to gain a lot of economic benefit from tackling those tasks. I just don't think we're going to live in a world where the labs subsume everything. I think we're going to see this rising tide of intelligence. Open source is probably going to continue to lag behind a little bit to some extent. I think those are going to be fairly parallel lines that go up together. But if you're doing frontier science and you are planning these very, very long scientific endeavors in order to extract economic value from whatever it is you're doing, you are going to be wanting to using the best intelligence and I think anthropic and OpenAI and other players like them will make significant profits and contribute significant value on those fronts. It's just that it's not the world we thought it was going to be two years ago where, where they would also get all the value underneath that of current GDP and the things that we currently conceive of as economically valuable. And I think that's a good outcome for everybody. No one player wins. I think we still have significant capitalistic pressure to advance the intelligence of these models. And the frontier labs will feel that at the very frontier, and then that's going to diffuse throughout the rest of the ecosystem as well.

Ed Elson (Prof. G)

All right, Charlie O', Neill, Co Head of Model Training at Base 10. Charlie, we appreciate your time. Thank you.

Charlie O'Neill

Thanks for having me.

Ryan Reynolds

Yep.

Ed Elson (Prof. G)

Okay, that's it for today. If you're catching this episode on Tuesday morning, I hope you'll take the opportunity to join our live stream later today at 1:30 Eastern Time. Scott and I are going live on substack with economist Noah Smith. We'll be unpacking the biggest question marks about the economy with him. And we'll also be exploring China's role in the AI ecosystem further. Head to profitmedia.com to subscribe if you haven't already. The live stream is free and open to all subscribers. This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer. Our video editor is Brad Williams. Our research team is Dan Shalon, Kristen o' Donoghue and Mia Silverio. And our social producer is Jake McPherson. Thank you for listening to Prof. G Markets from Prof. G Media. If you liked what you heard, give us a follow. I'm Ed Elson. I will see you tomorrow.

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