How Substack Creators Are Covering This Strange Markets Era

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1:56Hello and welcome to another episode of the Odd Thoughts podcast. I'm Tracy Allaway. And I'm Joe Weisenthal. So, Joe, we continue to publish some of the conversations from our recent live show in New York. And I hope people didn't mind. They didn't seem to. They seemed to enjoy it. But we did do a little bit of media industry navel gazing. Totally. So as we've been talking about, if you listen to past episodes from the show, you know, the theme obviously had this big like sort of future of markets, future of trading theme. But, you know, I would say and maybe this is like I'm very biased here, but I would say that information dissemination and collection and I guess you say journalism is an important part of markets.

2:36Right. How people get information. Journalism like that. Huh? Journalism. No, but, you know, like the thing like in the if you think about like the the flora and the fauna of the market ecology, then the people who like report the news, digest the news, explain the news, highlight what news is relevant, what is not relevant, are important actors in that system. And in a period of so much change and uncertainty, the question of like, A, how you decide what's important and B, how you convey that to an audience. These are really tough questions. Yeah. So I think there's two major challenges here.

3:10One of them is what you just said, which is like, how do you explain these huge technological shifts to people who may not, you know, they might be outside of the tech industry? How do you explain like an incremental improvement in a model to the average layperson? And then secondly, the other big challenge is the media itself is caught in the crosshairs of the debate over whether AI is going to take all the jobs. Right. That's right. So any one of us who's in the business of trying to consume, figure out what's important and relay it is also thinking about, will AI do a better job than we do?

3:44And precisely that, including writing newsletters or producing podcasts. That's right. So we had a trio of perfect guests for this particular discussion. All of them have been on the show before. We had James Van Geelen. He is, of course, the founder of Citrini Research and the author of the viral AI jobs doom scenario, as well as Jasmine Sun. She writes a sub stack that's all about AI and the culture of Silicon Valley and tech, as well as Sam Rowe. He is the author of one of my favorite newsletters with the best name, the TKR. So take a listen. Where do you even begin? I'll start with James because he's next to me and I just want to know what his life is like right now.

4:25Do people like recognize you on the street and scream at you about AI job losses? I've gotten two credible death threats, but not on the street. Okay, I guess that's a plus. Yeah, no, yeah, I mean, you know, it's better when it's not in person, right? But no, luckily I've been very much an internet personality and not someone that does a lot of taped interviews like this. We appreciate you making your time. I assume like 95 % of you know, but in case if you randomly don't, I assume you do. When was that? February or something? February. You wrote a post about a theoretical possibility of, you know, we're all going to lose our jobs.

5:04But anyway, so I could see why people were upset about that. Jasmine, you write about AI and you sort of like try to, when I read your writing, it's like bridging a gap, right? To some extent, because there are people, most of them in San Francisco, often on a lot of drugs, or maybe they're in a cult or something like that. And there's like, these are like the people who are going to influence the rest of our lives. How do you think about the question of like, what is actually important to communicate to a broader public? Yeah, I mean, it's really interesting because I think the vast majority of AI media coming out of Silicon Valley is by AI people for other AI people.

5:41And it serves that purpose really well, right? Like you got really in-depth podcasts, you got the Dwarakash podcast, you got this like whole ecosystem of sub stacks. One thing that I really noticed and I think most people who listen to the comms coming out of the industry leaders will notice is they're saying all these crazy things without like for a second thinking that like any normal person might hear them say it. And they're like, oh man, why don't these people like AI very much? It's like, I don't know. You've been telling them you're going to take all their jobs and kill everybody for the last several years.

6:07And like, you're on the record saying this stuff. And so I think it's really interesting where it's not like crypto, where only a small fraction of sort of the broad public ever deeply engage with it. AI is something that whether people want to or not is impacting their lives. It's on their social feeds. Their kids are using it. It's in their workplace. And so people have all these questions about the intersection of AI and politics, AI and affordability, AI and parenting and education. And the majority of, I think, AI media historically has not really focused on that. It's been more the business and technology communities.

6:38And so I'm sort of trying to say like, OK, but what about the rest of us? Sam, you write a newsletter and the tagline is basically, you know, stock markets usually go up over time. You've been very right for the past couple of years because they've certainly gone up. But like, are things starting to get uncomfortable for you when people are talking about AI bubbles and overvaluations? Oh, yeah. Things are always uncomfortable for me. I think that's sort of like one of the most important things about understanding this idea of stocks usually go up is the key word there is usually, right? Like every way you cut the data historically, even good times and bad times and bull markets and bear markets, you always have like these periods of volatility where, you know, stocks do go down.

7:22Like that's the catch here with stocks usually go up is that they go down a lot often. So, yeah, of course I'm nervous, especially when you're at peaks. I mean, of course, the data will also tell you that the 12-month returns after all-time highs can tend to be higher than when you're at lows. But yeah, of course, I'm nervous. I mean, I think that's very healthy for anybody in the investor class is even no matter how optimistic you might be over the near term or long term, you have to be prepared for those big drawdowns because they do happen and they happen frequently. Jasmine, so James wrote his piece about the potential, at least, and it wasn't a forecast, Yes, it was a prediction, but a scenario.

8:02We've also written other stuff too. Right, right. But no one likes the idea of like mass job laws, but I've been reading some other stuff and there's a lot of people who don't talk about AI job laws. They talk about AI will literally kill every single person in the world if the labs don't do a good job of aligning the models. How seriously do you think the public should take that specific element that if the models are misdesigned, they will destroy humanity as we know it? Oh, man. Yes or no? Contentious question. Oh, God. They call this a P-doom out in San Francisco. I won't give you a probability, I suppose.

8:45But without getting to the question of like, will literally every single person die? I do think there is a very good reason to be concerned about misalignment and rogue AI. Because when you think about it, sometimes people say that safety and the safety of a model is maybe in tension with these goals like acceleration and is the model really useful. And I think the thing that's really interesting is in the history of AI research, it's often the people who make the biggest technical advances in these foundational models who end up the most concerned about misalignment. And that's because actually the product functionality of the models, their utility is only as good as how controllable they are and how much they do what you expect.

9:23So when you say, hey, like AI agent, like go off and like make me a million dollars or whatever, like whether that model goes and does so in a law abiding and safe and nonviolent way, the safety of the model, the alignment of the model is very correlated with whether it is economically useful as well. So I think that it's important that we not hold them in total tension. And I think there are really good reasons to be concerned with whether these agents are doing the things that we expect them to do. Just going back to AI job losses, and I guess any of you can answer this question and please feel free to chime in on every question that we ask.

9:57But you also hear a lot of the big tech CEOs talk about being genuinely concerned about the future of society once AI is developed and starts taking people's jobs. Some people interpret that as AI CEOs basically talking their own book and hyping up the capabilities of AI. And then you have some people who argue that maybe they're genuinely concerned, not least because they're going to get Molotov cocktails thrown at their houses and things like that. Where do you fall in that spectrum? Is this a real concern when you talk to senior people in Silicon Valley? I do think that most of the people that I've spoken to who are worried about it are genuinely worried about it.

10:42Something that I'd add to it is pretty much unanimously throughout history, when we've had any sort of technological leap forward, it's been a positive thing. And I think that AI will mirror that. It's just the question is, we've never had a technological kind of advancement this quickly. We go from having the industrial revolution and the mechanization of agriculture, and 95 % of people used to work in agriculture, and then now I think it's 5 % do. And I'm very happy to work in an air-conditioned office rather than in a field. I know you do some gardening. A little bit, yeah. So maybe not. But the thing is, that will happen, I think, believe very strongly it will happen with AI.

11:27It's just what happens in the interim? What happens if the models get so good and people kind of adopt them with the same approach and use them correctly over five years instead of 100? So I think speaking to some of the senior people, they would echo the fact that over the next 30 years, AI is going to be an immense force for good and going to make people's lives more comfortable. They're just worried about the pace of the trend. Yeah, I think the transition is like super important because as much as everyone likes this idea, like even on the corporate side or the shareholder side, like the promise of all this productivity that's unlocked by AI.

12:10And, you know, maybe some people are thinking quietly in terms of like, oh, this is going to replace all of our workforce. But, you know, the economy sort of stops working when no one has jobs and no one has income. It's great that you have this huge profit margin, but you have no revenue because everyone's unemployed and they don't have any money. And those people aren't shopping. Those people aren't buying washing machines. And the washing machine manufacturer can't buy metal parts. And suddenly we're digging up less copper and the whole economy shrinks because no one has jobs. Then the whole point of this exercise becomes sort of meaningless.

12:41So which is why I think you're increasingly hearing from folks on this side, you know, talking about things like, you know, basic income and guaranteed jobs and all these things. So I think that's where, you know, the conversation sort of goes is, all right, let's make this assumption that we have all this productivity because of job loss. Well, that doesn't work. You know, people need to have money to go out and spend and buy these products that are being produced so efficiently. And I mean, it's worth noting that, like, for example, like people, politicians will point to say retraining is the default.

13:13We have never had a successful large scale reskilling program in the history of the United States during, say, you know, the deindustrialization. You lost all these factory jobs. It wasn't that many jobs. And we created way more net jobs, say, in Silicon Valley. But the steelworkers did not learn to code. Right. And so people are right to be concerned both morally and about the political backlash that could occur, even with relatively small numbers of net job loss.

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16:04Whatever your goal, 4imprint makes it easy to find your perfect promo match. Explore the possibilities today at 4imprint.com. 4imprint, 4certain. Sam, I love your newsletter. I read it. I'm a paid subscriber, all that. I think I could train a model to write a newsletter that says stocks go up. believe it or not my sister my sister recently got into cloud coding and she did this project with herself and thought that I find this really interesting and basically she created this app that was like a Sam robot that was informed by stuff that I've published and by Byline and all this free stuff that's out there and it's like I was kind of offended first of all but yeah it's a problem.

16:54Do you worry about Is it sole proprietor of a media company? You know, it's funny. It's like there was this time where you could go out and say, well, you know, something that you can't really replace is, you know, the individual's voice, the personality or whatever. And it's like, you know, I run some of this stuff, too, and run these queries and say, like, well, how would Sam Rowe write this? And it's like, it sounds like me. And sometimes it actually, you know, uses the language and comes up with the words faster than how I would. So it's like, what I do has to be about something more than just having the Samro voice.

17:31So to answer the question, the problem and the challenge, James and Jasmine and I, we talked about this a little bit in the back, is where do you add that value? And it can't be something that's just sort of replicable or something that someone who might be interested in what you're reading or writing about can put into a query and get back. Like, you know, the toughest part about my job and I think a lot of our jobs is being able to come up with those ideas and those angles that no one's asking for. Yeah. And, you know, again, like I write about the stock market usually going up, which, by the way, even before AI, it's kind of a ridiculous thing to be writing about.

18:12Because everyone who has money in their 401ks and IRAs, I've already been told this. They already know this. So it's like, why do I exist? And, you know, it's a relatively small market of people who are reading what I'm writing about. But yeah, I guess there's something about, and not to toot my own horn, this is reader feedback that I'm getting. But I've been told that there's something about whether it's the cadence or the timing of things I do write about or the way I frame it, that feels a little bit more human than the research or the analysis that, you know, of the chief investment strategist or whatever is sending out to their financial advisor who's regurgitating it back to them.

18:50James, one of the things you've been doing that I don't think a bot can replicate just yet is sending actual human beings or a human being to the straight of hormones. Is that like the edge in media? Is it like first person experiments and data gathering? Yeah. I mean, you just have to look at this from, I'm pretty confident that investment research won't exist in the same way that it does now. The internet kind of made it democratized, so to speak, the distribution. It was like only the banks had distribution. Now we have distribution and we can utilize that. But if we're just utilizing it to kind of do the same thing that the banks are doing, well, there is so much investment research that these models have been trained on.

19:32And as they get better, they will pretty much be able to do the same thing. So it becomes very much about doing something different and I think that uh there's like two ways you can do that one uh you can be right all the time so hopefully you know fingers crossed well you know uh I think that that one aspect is like like when I came on Adlets was the only media that I did after that piece which I was very happy thank you I said one of your questions Joe was like why do you think this went so viral and I think it's like uh and this is not like tooting my own horn. It's just sometimes you go on a hot streak.

20:07And when we started, that was very much in like a year of just like 100 % correct calls. And, you know, obviously I've had a bunch of wrong ones since then, but it was like a bunch of people were reading something and they would read it and they would say, well, if I hadn't read this piece, I wouldn't have bought NVIDIA in 2023 or wouldn't have bought Eskai Heineck or something. So I generated value from it. And then if you can add into that something that the model can't do with a query, they can't be out in the real world, then it's going on in the real world. If there's, if, you know, in five years, the robots come and then the models can go out in the real world, we'll have to find something else that they can't do.

20:41Jasmine, how do you think about this question of like what the human writer can still bring to the table? The one time you were on Adelaide's before was nothing about AI. You were talking about Chinese peptides consumption. No, but you did go to a peptide rate. No, I know, this is what I'm saying. So like that is sort of your equivalent of sending an analyst to the Strait of Hormuz. I mean, we were talking about this. I'm going to be the San Francisco spy that James sends out. I guess I've doxed myself already, but I can get a wig. But is that like, do you feel like that's a big, like, that like being in it in some way, physically in it, is like what you can do, at least currently, that the AI can't?

21:19Basically. I mean, I'm very bullish on secrets and I'm very bullish on gossip, right? And I mean, that's kind of what journalism is in the end. It's you have what is not in the training data. Like data is like one of the most valuable things. It's like chips, data algorithms, right? And the data is out there in the world and they've scraped the entire internet. They've torn the covers off all these books. They're Mercore is like paying hundreds of dollars for these experts to like feed all their knowledge into the models. But the thing is the world's constantly changing. It's very dynamic. There are parts of the world, parties, uh, straits that are unexplored by humans.

21:51And if you go and you are the first person to see that, or you're the first person to be there at a critical moment in time, as news is happening, as news is breaking, that kind of actual reporting is like more valuable than ever. One way that I think about reporting is that you have this private knowledge that's maybe known in whisper networks in the, you know, in some party scene or whatever, or you have tacit knowledge that nobody's really written down yet. And as a reporter, my job is to take the tacit or to take the private and to turn it into public knowledge. Like that particular task I think is extremely robust in the era of AI.

22:21Okay. So speaking of secrets and gossip and going out into the real world, you recently came back from a trip to China, where you were sort of comparing, I guess, how China is thinking and undertaking AI versus the US. What's your big takeaway? Yeah, I mean, China is one of those places where it's hard to get a sense of without going in person because it's so restricted what's on the public internet. And we have these world off internets. One interesting thing is the way that I think about USAI research is it sort of had three eras of American AI. You had the academic era. Maybe you call the boom kicking off with ImageNet or AlphaGo.

22:55You had the commercial era, let's call it kicked off with ChaiGPT. You had the maybe geopolitical era that's sort of Pentagon and mythos drama. And China is weirdly still in the academic era more so. It's very collaborative, very pro-open source. The labs and the researchers themselves seem unconcerned pretty much with the sort of big philosophical and geopolitical questions. And there's sort of a division of labor where because the party and the government is so active in shaping exactly what AI's role in society ought to be, then the companies themselves have sort of abdicated that responsibility.

23:28And they're also much more focused on collaborating because they'd see collaboration as the only way to sort of maybe have a chance against the U.S. frontier. Just to follow up on this a little bit, because so much of the American AI conversation is suffused with both the job loss question and then the even more sinister question of like, will the models turn against us? Is that dimension there as well, that sort of the safety alignment part? Is that a big part of the Chinese AI culture? Not a lot. And I mean, we asked researchers at a lot of the top Chinese labs how much they thought about safety.

24:00And it was clear that it was less of a priority. One is that they're compute constrained, right? So one open AI researcher is allocated and more compute than like an entire Chinese lab oftentimes because of the chip controls. And so when you're that constrained, you're probably not going to devote as many as much compute to safety and alignment. So that's one thing. The other thing I noticed is just that China has a little bit of this more almost like I call it like it's not techno optimism, which sometimes people confuse. It's more like techno determinism or this pragmatic approach, which is that technology has always progressed.