Gas Is Back Above $4 — And Could Keep Rising

[00:00:00]Gas in America has gone back up to $4.

[00:00:03]Why should we believe that that number is going to come down within the next [music] I don't know several weeks.

[00:00:10]>> Yeah. No, we shouldn't. And 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. 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 five and that's going to be really pushing higher because in barrel terms it's about $170 for a barrel of diesel.

[00:00:45]Welcome to Profit [music] Markets. I'm Edson. It is July 21st.

[00:00:49]Let's check in on yesterday's market vitals. The S&P 500 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.

[00:01:08]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.

[00:01:23]Okay, what else is happening?

[00:01:27]Conflict over the straight 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 Thran'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 straight 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 [music] of commodity research at Kepler.

[00:02:27]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 right now?

[00:02:41]>> Yeah, absolutely. So, you know, we're tracking those tankers that are passing through the straight of Hormuz here. Our job has become increasingly more difficult as there's been different routes to to try and traverse the straight. And so, what you've essentially got is is uh you've got the Iranian route which is right at the top, kind of the north, and then you have the the the typical or the pre-conlict 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. Now, 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 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 uh because of the signing of the me memorandum of understanding uh between the US and Iran. Now that has basically been you know dissolved uh and and we've seen an escalation here in in attacks as you mentioned it's been nine consecutive uh nights we'll probably have the 10th today and so this is this is causing all prices to uh to to start to kick back higher again. Just looking at what happened with Saudi Arabia and and that blockade, it seems as though oil supply was figuring out a way to kind of reroute itself away from the straight of Hormuz or around the straight of Hormuz. Um, 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? Yeah, sure.

[00:04:33]So, it it was working pretty successfully and so it was able to reroute about 3 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, uh South Korea, these countries that were otherwise getting their crude from the Middle East Gulf and it had stopped and so it was definitely providing uh some support there and helping uh you know in terms support in terms of supply and then helping to keep prices in check somewhat. Now the the Houthies are threatening to to do that blockade.

[00:05:18]They're not actually doing it yet. We're not seeing tankers or anything being being hit, but this is 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, you know, they could close Babam and but they've kind of held that back until the point where the US would essentially start perhaps taking attacking infrastructure uh energy infrastructure bridges and 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 Babel Mandeb into play and so it's really just a sign that essentially Iran has is getting to the point where they've really got not nothing left to lose or you know that they're just getting to the point where they're 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 will definitely have a bullish impact on prices.

[00:06:11]>> 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. It doesn't look good.

[00:06:38]And we're at $89 a barrel. Gas in America has gone back up to $4.

[00:06:45]Why should we believe that that number is going to come down within the next I don't know several weeks.

[00:06:54]>> Yeah. No, we shouldn't. And and actually what has 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. You know, China has really come out of the market. China has just stopped buying oil. They've stopped they dial back on their imports by about five 5 and a half million barrels per day. So that has been hugely helpful. Uh 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 five. And that's going to be really pushing higher because in barrel terms it's about $170 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.

[00:07:58]uh whereas the the the crude market has somewhat remained somewhat in balance because of this rerouting and because this less lack of uh refining.

[00:08:06]>> When you look at that 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?

[00:08:25]>> Yeah, absolutely. One huge bias that it holds is that even if you are bullish on oil markets, you're not going to go and buy a paper barrel because you could have President Trump tweet something in 5 minutes time and oil prices could drop by 10 15%. So I'm not saying prices are manipulated per se, 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.

[00:08:58]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. [snorts] 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 uh influenced market out of all of the petroleum complex. And that's the one that we're seeing. absolutely ripping here.

[00:09:23]>> 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. Uh some would argue we continue to be at war the entire time. I won't get into it, but it seems that what we have seen over the past week is going to have material impact on US consumers and the US economy. and perhaps that isn't being fully reflected or appreciated or priced in by investors and traders right now.

[00:10:17]How impactful and how bad do you think it will be going forward? 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 uh the 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 you know when when we came into this thing there was the expectation you can't close the straight of horses for two three weeks it will cause like Armageddon yet here we are 4 and a half months in and so it's really realistic to to to try and consider the scenario. Could this still be closed in November and December? Yes, there are workarounds. There's mediumterm plans here to reroute crude, but we really could be just continuing to scramble over the next four or five months here.

[00:11:11]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.

[00:11:20]>> What kind of price do you think that that would 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 straight of Hormuz. Is that right? Or is it or is it just zero? Well, [laughter] there so 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 cuz they were going through the Armani route. They were getting like a US naval escort. And so those 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 but to your point we were seeing over the last month this increase in traffic going through increased confidence increased risk takingaking and that really helped the oil market not necessarily on the the oil price um but in in the differentials you really saw the air being let out of the tires there the pressure taken out as we saw the stranded caros in the M East Gulf getting out of there but then again we've it's one step forward two steps back here where we're back to to essentially the doors being shut again.

[00:12:31]So I I'll return to 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? Yeah, sure. It's it it's got to be higher. You know, uh I'll hold up my hands here and you know in March you if you'd asked me that question or you may have done actually been like you know all 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 right but but maybe if we're going to be pushing above 100 here that doesn't sound seem unrealistic at all if we're in the same scenario that we're in now in four or five 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?

[00:13:22]What would what truths would need to exist in the world for oil to not be more than 100?

[00:13:28]>> Well, we'd be we'd be drawing down inventories absolutely everywhere that we could. You'd be having tankers sneaking out of the straight of Hormuz, however that was possible. Rerouting of crews as much as possible, too. But it's it's just difficult to see a scenario where you're not pushing into triple digits if this is still the situation in 4 5 months time.

[00:13:48]>> All right, Matt Smith is director of commodity research at Kepler. Matt, appreciate your time. Thank you.

[00:13:56]>> Thanks, Ed.

[00:13:57]>> We'll be right back. And if you're enjoying the show, be sure to subscribe to the ProfG Markets YouTube channel at the link below.

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[00:16:48]China just gave Wall Street its second deepseek moment. Chinese startup Moonshot AI released Kimmy K3, 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.

[00:17:08]Running K3 costs roughly a third of what Anthropic charges for its flagship model, and businesses are starting to notice. on Open Router, a marketplace for AI models. Chinese openweight models now occupy the top five spots by weekly global token usage. The NASDAQ fell about 1 and a2% on Friday as US tech stocks sold off following the release of Kimmy K3. So, well, we wanted to speak with an expert who works hands-on with both open and closed models. So, joining us is Charlie O'Neal, co-head of model training at Base 10. Charlie, thank you for joining us. So, this Kimmy K3 model that was just released has everyone kind of with their hair on fire. We obviously saw the NASDAQ erased one and a half% ship stock sold off. A lot of people saying that it was a problem. David Saxs, the former AISR called the release quote concerning. Uh, what do you make of Kimmy K3? 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 sold for the last, you know, 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 and open source will never catch up to that.

[00:18:32]And I think what we're seeing with with Kimmy with, you know, other Chinese models like GLM, GLM caused a very very big wave. It may not have done the rounds in the same way that Kimmy did, but it was certainly a great model. And even like releases like Inkling from Thinking Machines, which is an American um 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 from one kind of aspect, it's concerning that this is like a Chinese model that is leading the charge with with this sort of like 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 open anthropic having these models that pull away from everyone else and and they dictate all the terms of access and and um control that intelligence. Just for the uninitiated, what is the difference between an open- source model and a closed source model?

[00:19:39]>> Yeah. So, Anthropic, OpenAI, Google, their flagship models are what we refer to as closed source in the sense that I can ask it 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 as 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. Um, not only can I host that on my own GPUs, I can also do things like continue to train it myself for specific tasks. Um, so it's really about being able to download the actual weights for the model rather than just being able to send a question to it. So you can think of this as like, you know, owning the disc for an Xbox game versus like having that Xbox game installed through the cloud on your on your particular Xbox. I can actually like see the physical disc.

[00:20:28]What would be the pros for developing a closed source model instead of an open- source model? Why would OpenAI and Anthropic pursue uh those methods instead?

[00:20:41]>> Well, I guess there's two answers here.

[00:20:43]The first answer is the one that OpenAI Anthropic will tell you, which is that, you know, these things as they become increasingly intelligent, we have to think very carefully about how they're applied in society. Um there's obviously real safety concerns. There's cyber security 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 open AI's argument is you should trust us like 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. Um there should be a very small number of actors who who can choose how what we do with with LMS and intelligence. And I think the 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, you know, margins north of 80%. Um I think like when there is a a case or a world where there's only two major players and you end up in a duopoly, that is a a very real possibility to to continue. And I think that's obviously very very lucrative to open anthropic.

[00:21:48]So open source is a threat to them in the sense that those margins aren't going to remain at 80% for long. Um, of course there are like security concerns.

[00:21:55]We have to really think carefully about how these things are used. Um, but at the moment it doesn't seem like open source versus closed source the the intelligence ceiling that we've gotten to hasn't led to any increased concerns around you know can I use this model through open source or close source like the the risk of developing a bioweapon for instance is about the same in either case. It seems that there is 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. Um why is that happening do you think? What is the value proposition that developers are deciding is greater uh when they use these types of models as opposed to one uh offered by OpenAI or anthropic? Yeah, I I I think there's developers who have a very inelastic demand for the frontier intelligence and will always want to use the most intelligent models and then there's the ecosystem and the economy in general.

[00:22:49]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 LMS. 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 50th 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 as opposed to taking an off the offtheshelf 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 open AI I think are realizing that the recipe is the same amongst all these companies like there is no secret source. Yes, there's there's probably a long tale of optimizations, small optimizations that anthropic and open area have that the rest of the ecosystem doesn't have. But their moat is no longer in there being them being the only ones who can train these very very large multi- trillion parameter models.

[00:24:11]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 like hit particular verticals and so anthropic is very clearly doing this.

[00:24:20]They're going after the verticals of you know finance and legal open AI as well.

[00:24:24]And so I think companies are really feeling this pressure. If you're if you're a startup or or a company in legal or finance and you're using LM 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 mo for anthrop 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.

[00:24:51]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 companies wanting to develop to develop their own mode to protect themselves against their their vertical being eaten by these like closed source frontier labs.

[00:25:08]>> It seems like a big piece of the story for an enterprise for a company that is trying to leverage AI as much as they can. and Alex Cop talked about this in his interview with CNBC that has since gone viral is basically just the price.

[00:25:22]Uh anthropic tokens are expensive, open AI 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?

[00:25:55]>> Yeah, the 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. Um and of course like 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.

[00:26:18]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 you know previously we've gone into the just 48 into the 1 trillion parameter model range with the previous Kimmy models and deepse very very recently but this is you know almost 3 trillion parameters like this is a big boy um and so now it's much more about okay we're really seeing under the hood that the reason that anthropic and open AI 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 like it is inelastic. They you do demand frontier intelligence. But now we're really seeing, okay, if we do have, you know, multi- trillion parameter open- source models that any company can, you know, 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.

[00:27:10]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 Kimmy is indistinguishable from a fable or a GPD 5.6 soul. We're just going to see those margins shift. So instead of being 80% to the person who trained the model, they might being 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, you know, 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. It seems to me that these models, Kimmy 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 open eyes models or outperforming them.

[00:28:09]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 open'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?

[00:28:50]>> Yeah, I think 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 nail for anthropic at 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 LMS and the distribution of tasks in the economy that we should be tackling with LMS in the next 10 years. I think what we're going to see is a little bit of a bifocation. 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 um and maths discovery which you know have a longer they they have a lagging period um there's a lot there's a bunch of labs like periodic labs who are really looking forward to to tackling science over multi-deade horizons with LMS and and this new intelligence. I think the frontier labs are going to gain a lot of like, you know, economic benefit from tackling those tasks. I just don't think we're going to live in a world where the the labs subsume everything. I think we're going to see this like 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 fairly parallel lines that that go up together. But you know if you're doing frontier science and you are planning these very very long you know scientific endeavors in order to extract economic value from from whatever it is you're doing you are going to be wanting to using the best intelligence and I think anthropic and open AI and other players like them will make you know significant profits and and contribute significant value on those fronts. It's just that it's not the world we thought it was going to be 2 years ago where they would also get all the value underneath that of like you know current GDP and the the things that we currently conceive of as economically valuable. And I think that's a good that's a good outcome for everybody. Um, no one player wins. I think we still have significant, you know, 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.

[00:30:59]>> All right, Charlie O'Neal, co-head of model training at base 10. Charlie, we appreciate your time. Thank you.

[00:31:06]>> Thanks for having me.

[00:31:07]>> 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 profia.com to subscribe if you haven't already. The live stream is free and [music] open to all subscribers.

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