In this episode of QAV, Cam and Tony explore the U.S. market for the first time, with a brief introduction of Tony and his QAV system of value investing, a discussion of value v growth investing, a discussion of the performance of our U.S. dummy portfolio, a deep dive or ‘Pulled Pork’ segment on Reinsurance Group of America (RGA), and a review of the FY survey results we’ve received so far from club members.

00:00 Introduction and Episode Overview, Health and Fitness Anecdotes, Kung Fu Goals
04:12 Introduction to our first US episode
07:57 Tony’s Investing Background
13:07 Value vs Growth Investing
17:50 QAV System Explained
24:19 US Dummy Portfolio Performance
30:45 Top Performers in the US Portfolio
43:20 Market Emotions and Cycles
45:25 Pulled Pork: Reinsurance Group of America (NYSE:RGA)
01:09:49 Survey Results and Performance Analysis
01:16:20 Ethics and AI in Financial Advice
01:19:43 AFTER HOURS – mostly a debate about the future of AI

Transcription

QAV 724 US1

[00:00:00] Cameron: Uh, welcome back to QAV, TK. Now this is, um, uh, episode, seven to four, but in some ways, It’s also episode one, because today we’re going to be doing our first, uh, episode about the U. S. market.

[00:00:27] Cameron: Something that we’ve been talking about doing for five years, one day, finally, finally got some ducks lined up and, uh, have an opportunity to start talking about this stuff. Anyway, before we get into that, how are you, TK? How’s your week been? You’re back in Sydney, I see.

[00:00:43] Tony: yep, holiday’s over. Jen was away for the weekend, so, um, she’s back now. Uh, you know, just, we’ve both been hit by the winter lurgy, so we’re just trying to lay low for a bit and let our

[00:00:54] Tony: bodies recover. But, um, otherwise, we’re well.

[00:00:57] Cameron: mmm. It’s all that golf in cold wet

[00:01:01] Cameron: weather not good for you.

[00:01:02] Tony: wet weather’s right. I mean, it was, I think I, like, whatever I caught, I caught when I was inland, like in Scone and then Warwick, where it was pretty cold at night, and I wasn’t really

[00:01:13] Tony: used to it or prepared for it. But anyway,

[00:01:15] Cameron: Ruddy wasn’t cuddling up to you enough to keep you

[00:01:18] Tony: I Ruddy didn’t turn up until Brisbane.

[00:01:20] Cameron: Oh, okay, well, there

[00:01:22] Cameron: you go.

[00:01:23] Tony: And whatever I got, I gave it to him as well. So yeah, I’m Typhoid Mary at

[00:01:29] Tony: the moment.

[00:01:32] Cameron: um, I had a discovery over the weekend, just talking about health and fitness. You know, I did a lot of Kung Fu last week, did a 90 minute class on Friday night, and then went to do another hour long class on Saturday morning. And I was feeling crap like Friday night, Saturday morning before the class, just feeling sore, like I haven’t felt for a long time, really struggling to just Get my shoes on and get into it.

[00:01:59] Cameron: And then the fitness class that we did, which was sort of a high intensity fitness class on Saturday morning, I struggled like a couple of minutes into it, I was ready to die, got to the end of it and suddenly realized I probably hadn’t been hydrating enough that week or taking electrolytes, came home.

[00:02:14] Cameron: Made an electrolyte drink and drank a liter of water with it. Felt immediately better. All my pains went away, the fog lifted. I was like, I’m such a dumbass, you know, I should have been, I gotta hydrate more because I was sweating a lot, working hard. Like I probably did 10 hours of Kung Fu last week and it was just, uh, you know, draining my body.

[00:02:36] Cameron: So yeah, that was a big lesson. Hydrate. Electrolytes.

[00:02:40] Cameron: It’s important

[00:02:41] Tony: Yeah, well, there should be an app for that, shouldn’t there? Maybe that’s a business

[00:02:44] Tony: opportunity for us.

[00:02:46] Cameron: Well, there is it’s GPT. I said, this is how I’m feeling. And it said, you’re probably not drinking enough water doing your electrolytes. I was like, all right, thanks GPT.

[00:02:56] Tony: So, so I was thinking, thinking about your Kung Fu after we met up in Brisbane, you were telling me about it. And, uh, You’ve got, I mean, how many hours do you have to put in to get to a black belt? Is it

[00:03:08] Tony: the normal 10, 000 hours

[00:03:10] Cameron: Oh, I don’t

[00:03:11] Tony: be an

[00:03:12] Tony: expert?

[00:03:13] Cameron: Well, you’re not an expert at a black belt. No,

[00:03:15] Tony: Oh,

[00:03:16] Cameron: no, no.

[00:03:18] Tony: anyway, so you’re doing a couple of hours a week. It’s going to take you a long time to get to a

[00:03:22] Cameron: I’m doing about,

[00:03:23] Tony: level of Kung

[00:03:23] Tony: Fu. 10

[00:03:24] Cameron: about 10 hours a week.

[00:03:25] Cameron: So,

[00:03:26] Tony: hours a week. Wow.

[00:03:28] Cameron: so that’s a thousand weeks, that’s, uh, 19 years,

[00:03:33] Tony: Yeah.

[00:03:34] Cameron: I’ve, given myself, uh, seven years to get a black belt, so I started when I was, hold on, no, I started when I was 51, nine years. So my goal is to have a black belt by the time I’m 60. When you’re a black belt, you just, they say, you, you, then you’re just the beginner of the black belts.

[00:03:49] Cameron: Then you need to, that’s when you actually start learning Kung fu is when you’re a black belt. They, okay, now, now you’ve, you’ve demonstrated that you know the basics well enough to get a black belt. Now this is where the real training starts.

[00:04:02] Tony: I couldn’t imagine doing body contact sport at my age, at any sort of advanced level.

[00:04:08] Cameron: eh.

[00:04:09] Tony: Golf’s, golf’s good enough for me, I

[00:04:11] Cameron: Yeah. Anyway, let’s talk about the US market, Tony. So, as I said at the beginning, like we’ve had a couple of, a handful of US listeners, uh, and some Canadian listeners since the beginning. We’ve had a lot of Australians over the years, not so much in recent years, but early on people would ask us a lot about investing in the US market.

[00:04:32] Cameron: We’ve always said, nah, it’s not something that you do, you’ve done, even though you’ve lived in, you lived in Canada for what, five

[00:04:40] Cameron: years?

[00:04:41] Tony: five years? yep.

[00:04:43] Cameron: Always invested in Australia. Uh, but that said, you know, there’s a, we think there’s a, an audience for the QAV method in the U. S. We want to be able to teach, not just in the U.

[00:04:56] Cameron: S., but in, uh, the U. K., Europe, Canada. I, you know, I want

[00:04:59] Cameron: to teach QAV

[00:05:00] Tony: Whoa, whoa, whoa, whoa, whoa,

[00:05:02] Tony: whoa.

[00:05:04] Cameron: ha! What I’m

[00:05:05] Cameron: saying is, there are people all over the world. The system should work everywhere.

[00:05:09] Cameron: I mean, you learnt the system, how to invest basically from Americans mostly, right? And then added your own,

[00:05:18] Cameron: um, thinking to it.

[00:05:19] Cameron: But so, uh, the, one of the problems that we’ve had though, over the years is that the data source that you have traditionally used and that we, uh, mostly use is Stock Doctor, which is Australian based and they don’t have. data. So, uh, you know, I’ve spent the last couple of years trying to figure out what data source we could use to do international markets.

[00:05:46] Cameron: And, uh, coincidentally, a year or so ago, Elio from Stock Doctor, formerly of Stock Doctor, ended up running Stockopedia in Australia, uh, who I think are UK based, but they not only have Australian data and UK data, they also have US data. So I. We spent some time last year building a version of our checklist that would use Stockopedia’s US data and I’ve been running that for about six months and it’s been doing okay.

[00:06:17] Cameron: And so we felt like we’re sort of ready now to start looking at some US stocks. But there’s obviously a process that we’re going to have to go through to get our feet wet. understanding U. S. market, U. S. companies, some of the differences about reporting and taxation and dividends and legals and all that sort of stuff in the U.

[00:06:38] Cameron: S. But over time, if this goes well, I think, um, you know, we might have like a separate, um, Series that we do on a monthly basis, once a month, something like that, where we look at a US stock and talk to our US listeners. Uh, and then, you know, UK, Canadian, Japanese, Chinese. Tony’s given me this look like, Oh, really?

[00:07:01] Cameron: Oh, uh, oh, really? No, yeah, yeah,

[00:07:06] Tony: I can get paid multiples of what I’m getting paid now then for the new

[00:07:09] Tony: markets.

[00:07:10] Cameron: absolutely. As many multiples of zero as you like. So. Uh, I’m assuming though that most people listening to this are our existing Australian listeners or our existing international listeners who already know us, but I thought, just in case there are any new listeners to this, let’s do a quick intro to you, me, QAV, oh how happy we will be.

[00:07:33] Cameron: Uh, and then we’ll get into talking about the U. S. market. And if people want to know more about Tony and the QAV system, if they are new, please do. Go and have a listen to our episode 301, find it on our website or in our feed. That’s sort of an hour long background that we don’t need to repeat because it’s all the same stuff, but you can go and have a listen to that.

[00:07:57] Cameron: So give everyone the couple of minute version of your investing background, TK,

[00:08:05] Tony: Yeah, sure. So, uh, I’ve had, I have a corporate background, so I worked for the Shell Company of Australia for 12 years and then for a company called Coles Myer, which is now West Farmers after it was taken over. So a big oil company and a big retailer, um, gave me a lot of experience in corporate life, in how businesses work, gave me a lot of experience, Shell in particular, and, um, Businesses around the world and what it’s like operating in different countries, uh, and then towards the end of my corporate life, actually that’s not quite true, uh, towards the end of my shell life, um, I started investing.

[00:08:44] Tony: So, uh, we were offered a, uh, a corporate loan as part of our salary packaging or the option to take a corporate loan, which I, um, invested, uh, and Very quickly lost half of because I had no idea what I was doing. And then, uh, decided to back up and teach myself about investing and subscribe to every newsletter I could, every, um, read every book I could on investing.

[00:09:09] Tony: Um, listen to tapes back in those days from, um, people who were teaching investing and, or were, uh, famous investors themselves, uh, prior to podcasts. In fact, the ASX started launching podcasts around. I think about the mid nineties and that used to be a good series. It’s a shame that it’s still doing it.

[00:09:28] Tony: Cause I, that was one of the better

[00:09:30] Tony: business podcasts around and that introduced me to people like Roger Montgomery,

[00:09:34] Cameron: Podcasting wasn’t invented until 2004,

[00:09:36] Cameron: Tony, so I doubt

[00:09:37] Tony: and I must’ve been later then, sorry. Okay. Um, yeah, you could be right. And, uh, But I started doing it about 25 years ago, so it would have been, would have been about the mid 90s when I started, um, and came across a book on Warren Buffett called The Making of an American Capitalist by a chap called Lowenstein, who’s written a number of books on Buffett since then, uh, which was an unauthorized biography, but it sort of resonated with me.

[00:10:06] Tony: I think, uh, that was kind of like the total ecosystem. that appealed to me about investing. Up until then, most of the stuff I read was either very dry financial type analysis, uh, or it was, um, you know, out there kind of go with the vibe type analysis. And then, and of course, the dot boom, dot com boom came along where it was all about forget about the bottom line and just, just get revenue.

[00:10:33] Tony: and Disrupt and Get Eyeballs, and that didn’t really appeal to me either. Even though I did work in the dot com section of Coles Myer for a while. Ran a company called Myer Direct, which was an online catalogue retailer and eventually became, um, well sorry, it was a catalogue retailer and eventually became an online seller as well and pioneered e tailing in Australia.

[00:10:56] Tony: Uh, and um, Yeah, the value investing side of things, uh, struck a chord. I think, luckily enough for me, uh, IT was improving, probably because of the dot com revolution, and so I had access to better tools. Uh, I had a background in business analysis, so I knew how to use Excel. Back then it was, I think, Lotus 1 2 3, and, um, you know, prior to Excel.

[00:11:21] Tony: And, uh, Tools like Stock Doctor were launched in the late 90s and that provided data to use. I mean, in my early days of investing, I used to write away and get sent a book once a year, or once a half of everyone’s one page summary of their Annual report. And yeah, for a long time, I had about a dozen of these on my shelf.

[00:11:44] Tony: Um, and if I had to, if I had a thought about, you know, looking up a company, I could go to that and pull out its numbers quickly, but that was how you did it. But that’s all improved now over time. And particularly with Stock Doctor and Excel, we had the ability to download, Lumps of data and then be able to, um, to analyze it yourself and look for, for important pieces of information in the data.

[00:12:08] Tony: And, you know, that started to be as formative, uh, in terms of my investing career, as much as value investing was, because it started to teach me that, um, CEOs were basically salespeople and they could say whatever they liked, but it was generally to try and boost the share price, uh, and oftentimes did not reflect what was underlying in the company.

[00:12:28] Tony: So I found it was appealing to be able to use the data to, um, to analyze what was actually going on in a company and, and, um, ignore what the CEO was saying to a large extent. And, um, Um, and then read a book called The Checklist Manifesto, which, uh, highlighted the virtues of being able to systemically, uh, operate a business, I guess, uh, which, which investing is, and, uh, put together All the thoughts I’d had, or all the nuggets I’d found during my experience as an investor, into a checklist.

[00:13:03] Tony: And that’s evolved a little bit over time and it’s become what we use in QAV now. So, in summary, it’s, um, it’s based on value. I’ve seen enough and read enough in my experience to know that, um, value investing appeals to me, but it’s generally not. been the style that’s worked the best over the years, way back, you know, from Ben Graham’s days in the, in the sort of post depression years in the U.

[00:13:31] Tony: S. Um, so, sure there are other, other ways, and especially growth, which would be the other sort of main topic that people often talk about.

[00:13:40] Tony: And, and for me, both value and growth go in and out of style. Um,

[00:13:45] Tony: but, Yeah, sure.

[00:13:47] Cameron: value and growth?

[00:13:48] Tony: uh, say that all investing is value investing. We’re trying to buy, you know, something for a dollar now, which will be worth more than a dollar down the track.

[00:13:57] Tony: And, um, there’s two ways of doing that. One is to say that, you know, I’m a value investor. So I’m looking to buy something that’s, um, actually worth 2 now, but I’ll pick it up for a dollar. Um, so that’s, it’s, it’s looking for the bargains, I guess, in the stock market, much the same way as you’d probably shop for something that’s important in your life, like a A car or a house or a rug or whatever.

[00:14:18] Tony: Um, and then there’s growth investing, which is saying that, uh, you know, this is a, there’s enough I can see in this business to tell me that it’s going to be much larger down the track than what it is now. And I can ignore the fact that it’s not making money now. Because it’s growing revenues, for example, quickly, or I can see that it’s going to disrupt a particular industry, or it’s, um, going to do well, for whatever reasons, um, like it’s a new way of doing something, uh, and I’m going to bet that, you know, the company will be well managed, it’ll get to a stage where it’s profitable, and then we’ll, um, you know, go on to be a large Large market cap company and actually start to produce some results down the track.

[00:14:57] Tony: Um, I think they, they tend to be two styles that go in and outta fashion. Um, but from my point of view, I found value investing, even though you can have down years, um, overall it, it continues to work. Whereas I found when I have dabbled in growth investing, it’s, um, first of all, it’s. It tends to be less rules based than the way I like to invest.

[00:15:19] Tony: So you’re pretty much trying to assess something based on your experience that hasn’t happened, um, before. So it’s, it’s, you can’t sort of go back and say, Oh, I’ve seen this before. It’s going to, you know, I can, I can apply this framework to it and value it this way. Generally, it’s something that’s new. Um, and then you, you’re kind of hoping that it, you know, it’s going to grow, but then you’re hoping it’s going to turn a profit.

[00:15:42] Tony: Which, um, sometimes these growth companies don’t do, um, and sometimes for good reasons if you look at Amazon, um, but, uh, I found growth investing is, is more, it, it’s good for a while and then a growth stock when it crashes, crashes really badly, so if you think back to the dot com period, you know, the Nasdaq dropped 80 percent in, you know, I think it was 2001 or maybe 2000, whenever it was when the dot com balloon burst, and that tends to happen with these companies when they’re not making money and something turns against them, whether it’s the economy or some kind of existential threat, um, they can drop like lead balloons, uh, so that’s the first thing that I struggle with, with growth investing, and the second thing is, um, it’s very hard to have a growth strategy.

[00:16:32] Tony: A sell trigger for Azure growth investment. You’re always worried it’s going to go up more if you decide to sell and take some money off the table. Whereas, um, I think it’s, it’s an important part of investing to have not just a buy signal, but also a sell signal. Um, that’s not saying that they aren’t out there and that someone hasn’t mastered that, but I found it difficult to do myself.

[00:16:51] Tony: So, um, that’s why I prefer, um, The value investing, data driven, sort of rules based checklist for a style for investing. I, I like the, you know, we put a quality overlay on it, so I like, um, being able to find good solid companies that have good cash flows and, and then be able to, to look at them and say, okay, I can buy this at a reasonable price rather than, um, trying to assess whether this is a good buy now, pay later company versus that one, or whether, you know, um, NVIDIA chips are going to, you know, be able to keep growing from where they are now or whether they’re going to be competed out of existence by the next manufacturer.

[00:17:33] Tony: So I just find that stuff, it requires a deep vertical knowledge of a particular industry, which I don’t have. Whereas with, um, the data driven approach, I can do market scans and come up with a checklist and then

[00:17:45] Tony: work through the checklist and, and find a company that I like there.

[00:17:50] Cameron: essentially, the system that you develop to invest, we now call QAV, Quality At Value. Basically, the way that we do it is that we look at all of the companies that are listed, In the market, traditionally Australia, but now also the U S and we run filters over them to determine which companies we believed are undervalued.

[00:18:14] Cameron: And it’s based on historical measurements and current, um, measurements in terms of their sales, their profits, their, their revenues, and we buy them when we determine that we think they’re currently available to be bought at a discount to what their actual valuation is today. Not that what their valuation might be five years in the future, but what we think a share of it is worth today and the basic rationale is that if we think it’s undervalued at some point, it’s undervalued.

[00:18:47] Cameron: The rest of the market will determine that it’s undervalued and the price will go up to where it should be, where its value is. And companies can be undervalued at any given point in time for a whole bunch of emotional factors in the marketplace that have nothing to do with the, how well the business is run, how profitable the business is, how good the management is.

[00:19:08] Cameron: And so we’re trying to exploit, uh, and leverage those, uh, factors in the marketplace, as opposed to trying to buy something and predict that its revenues five years from now will be X or ten years from now will be Y, because we don’t believe we have a crystal ball.

[00:19:26] Tony: Yeah, I think that’s a good summary. And I just want to add that it all comes down to me, to regression to the mean. So we’re buying something which we think is undervalued and we’re waiting for it to regress back to fair value. If you’re a growth investor, you’re buying something which you think is Kind of go up, but, you know, again, regression to the mean will apply.

[00:19:45] Tony: It will eventually come back down to what’s fair value. So, um, I’d rather be on the other side, I’d rather be on the value side, waiting for things to regress upwards than to regress

[00:19:54] Tony: downwards.

[00:19:55] Cameron: what does regression to the mean mean?

[00:19:58] Tony: if you think about a rational approach to investing, then every, every company should trade at its fair value. And that’s, that was a theory on the stock market for a long time. The efficient market hypothesis. There’s no new news. You can’t have an edge that every piece of news has already backed it into the price of a share.

[00:20:16] Tony: Um, but you know, we, we now know from, thanks to the work of people like Kahneman and Tversky, that there’s a whole lot of human emotion in this, in

[00:20:26] Tony: marketplaces, not just the stock market, of course, but any marketplace.

[00:20:30] Tony: Um, there are Fear who are trying

[00:20:31] Tony: to do, fear and greed, yeah, but also all the hard wiring in your brain, which has evolved to do something else, like evade being eaten by a tiger.

[00:20:42] Tony: Um, so, so, uh, it gets exploited in the stock market and used against you by, uh, by people. Um, just like it, like, just like it’s exploited everywhere else in You know, the media, and in life, and etc, etc, but um, so the stock market isn’t completely efficient, is what I guess I’m trying to say. And there can be gems hiding in plain sight, that once the spotlight goes on them, will be bid up in price, back to what they should be worth, and there are also companies which have a huge spotlight on them.

[00:21:15] Tony: Where FOMO drives the price up, but eventually most of those will fall back down to what they’re really worth. And that’s, that’s what regression to the mean

[00:21:22] Tony: is in my book. Yeah.

[00:21:24] Cameron: Everything will, um, either go up or go down to the level that it should be over time. And you know, when we think about it, this is something that, uh, so for, for my story, uh, for people that are new, I know nothing about investing or at least didn’t when we started this podcast, but I had done a lot of podcasting and, uh, one of the things that Tony taught me early on that really helped me start to understand investing from his perspective was to think about.

[00:21:56] Cameron: a share that you buy in the stock market as literally that, a share of a business. And so we’re looking at these companies as going concerns, going businesses. And instead of, instead of thinking about a company as having a million shares, imagine it had four and you were being offered, you know, The opportunity to buy one of those four shares.

[00:22:19] Cameron: How would you determine whether or not the price you were being offered for that share was a reasonable price? What are the things that you would look at? You would look at how many customers does it have? You know, what’s the sales? Like this year, what’s its track record of sales? How, how capable of the, do the management seem to be based on what they’ve been doing with the business for the last four or five years?

[00:22:41] Cameron: Uh, what, how many competitors do they have? What are their profit margins like? Are they going up? Are they going down? You’d look at all the basic stuff that. Most people listening to this probably understand if you’re thinking about it in terms of a, a coffee shop is the analogy that you’ve always used with me.

[00:22:56] Cameron: Something that most of us can probably understand. It’s got some costs. It’s got some customers. It’s got some products and services that it delivers for a profit. When you start to think about it like that, it makes a lot more sense. Then you go, okay, well, I’m being offered a share. Being offered the opportunity to buy a share of this, do I think the price that they’re offering is worth it?

[00:23:18] Cameron: Is a good deal? Is it a bargain? Or is it, is their asking price way too high? And, and how do I determine what way too high is? And then we, you know, so that’s basically the approach to investing as opposed to, you know, maybe the other thing is somebody comes to you with a startup idea and they’ve got a business plan and they say, this is going to be doing a billion dollars a year in five years, uh, buy a share today.

[00:23:45] Cameron: Don’t miss out.

[00:23:47] Cameron: You’re like, Oh,

[00:23:48] Tony: Yeah. That’s a good idea. It’s a good summary, isn’t it? It’s an idea. They’re selling the

[00:23:50] Tony: idea.

[00:23:51] Cameron: Yes.

[00:23:52] Tony: I’m, I’m going to use AI to run coffee shops more efficiently than what

[00:23:56] Tony: they run now. Okay. How much do you want for that?

[00:24:00] Cameron: So that’s, um, that’s a quick intro to, um, QAV for people that are new. And if you want to know more, as I said, go look into, listen to 301 and then 303 and 305 is where we actually go into the checklist process in a lot more detail. It’ll take a couple of hours to go through it and you can have a listen to those.

[00:24:19] Cameron: So, as I mentioned in the intro, about 6 months ago, um, I started building our dummy portfolio of US stocks. We call it a dummy portfolio because we’re not Investing real money. It’s just on paper, but we, we doing it sort of transparently, publicly, and I’ve been reporting on the performance of that US portfolio each week on our, um, on our episodes and in our emails, uh, for the last six months and it’s been doing okay.

[00:24:49] Cameron: Um, it’s not, I wouldn’t say shooting the lights out in terms of being double market, which by the way is something we didn’t mention. So, sort of the goal that we have with our investing is to do about double what the market is doing and how you determine what the market is doing is a little bit subjective.

[00:25:08] Cameron: The benchmark that you pick, but there are indexes like the S& P 500 in the US. Or the ASX 200 or the ASX 500, 300. There’s a number of different indexes in Australia. So we tend to pick an index that we think is relevant and then assess our performance against that. Now, our goal is to do twice as good as the index over time, over a long period of time.

[00:25:36] Cameron: Because obviously this is a long time. term investing strategy, not a short term investing strategy. And what I’ve learned in the last five years of doing this with you, just looking at the Australian market is there was one year in particular when we knocked the lights out. We did about four times the market performance.

[00:25:52] Cameron: 2020, 2021. And then it’s come back down. Um, we’ve underperformed the market a little bit in the last year or two, but it’s come back down to about double market. So over the last five years, our average return in Australia has been about double the Australian benchmark that we look at. With the US portfolio that we’ve been doing, and I’ve been tracking in Stockopedia.

[00:26:16] Cameron: Let’s see, according to this, I started at September 20, 2023. So a little bit more than six months, that, isn’t it? It’s like nine months, really. Um, it’s performance according to Stockopedia has been about 21 and a half percent over that period. Now that’s not a, CAGR performance, which is the one that we normally prefer, that’s a time weighted return, I think.

[00:26:46] Tony: Right,

[00:26:46] Cameron: The S& P 500 index, which is the benchmark that they give me, is up 20. 6 percent over that same period of time. So, we’ve done better than the index, but not quite. Nowhere near double the index, but we’ve at least matched the index. Although I do suspect that dividends are included in our performance here and probably not included in the S& P 500.

[00:27:10] Cameron: So if you actually added the dividends to the S& P 500 stocks, it’ll probably be doing quite a bit better than us. In that nine month period, I. Don’t think I can get Stockopedia to give me a benchmark that includes the dividends. We should have a chat to the Stockopedia people about maybe helping us out with them.

[00:27:33] Cameron: But

[00:27:34] Tony: Well, bear in mind too that dividends are a smaller portion of the U. S. The yields are smaller in the U. S. than they are in Australia. So dividends are a smaller portion of performance in the U. S. They don’t have our franking credit system as far as I’m aware. And, um, it’s, it’s kind of more business philosophy over there to reinvest profits rather than to pay them out as

[00:27:54] Tony: dividends.

[00:27:55] Cameron: Right. Oh, that’s good to know. Yeah. So, I will try and get figures so we can do a more accurate comparison over time. But, bottom line is that the portfolio, like our Australian portfolio hasn’t done 21. 5 percent in the last 9 months. I’d be happy if it

[00:28:14] Cameron: had. So,

[00:28:16] Tony: No, exactly. Ha,

[00:28:18] Cameron: the U. S. is an interesting market

[00:28:20] Cameron: and we’ll talk a little bit about that and sort of, you know, I think I read in the Financial Review, which is an Australian, um, financial newspaper for our non Australian listeners, saying today that Wall Street’s, uh, like doing record highs.

[00:28:36] Cameron: Australian market was on a record high up until the last, until today, dropped back down again. But a lot of the US market we know is being driven by what they call the Magnificent Seven these days, the Mag Seven. And these are basically the tech stocks that, uh, have a lot to do with the AI boom. And they’ve just been knocking the lights out for the last year or so.

[00:29:00] Cameron: Well, there were tech companies that were doing well before that, but particularly since the ChatGPT started the AI boom 18 months ago. Uh, these companies who the investors in the U. S. seem to believe are going to profit the most out of the AI boom are doing extraordinarily well in terms of their share price.

[00:29:21] Cameron: And, uh, I think that’s accounting for a large component of the buoyancy in the market in the U. S. is those mag seven. I have seen some stats saying what percentage of the, uh, Um, growth in the U. S. is, uh, because of the Mag 7 in the past, I can’t remember what it is, but it’s a, it’s a significant number.

[00:29:43] Tony: that’s, that’s interesting in itself, isn’t it? So the S& P 500, which has, as you said, a large, um, wouldn’t say weighting perhaps, but a large component of its, its performance is through the Mag 7, uh, is doing about the same as our dummy portfolio, which is a value stock portfolio. So

[00:30:04] Tony: I think that’s interesting.

[00:30:05] Tony: Um, it shows that value investing, in my opinion, anyway, can, can do as well as growth, um, and it’ll be interesting to see even further if the Mag 7 come off, what happens to. Our portfolio compared to the S& P 500.

[00:30:19] Cameron: Mm. Yes. If and when that happens, who knows what’s going to Yeah.

[00:30:26] Cameron: But the interesting thing for me in building this U. S. portfolio in the last nine months has been looking at the, uh, companies that, uh, make up our portfolio, which have a very different, uh, Profile of companies than we’d normally be investing in, in Australia.

[00:30:45] Cameron: Uh, if I run through the stocks that we hold in our current portfolio, I think there’s about 14 of them. Land’s End is, uh, the one that has done the best. If I stack rank these by their performance, Land’s End is a retailer, clothing retailer, I think, or a digital retailer of mostly clothing and home products.

[00:31:11] Cameron: Um, it’s up. Hundred and five percent. Since we bought it, clothing, I don’t think there are any major digital retailing or clothing brands in our portfolio, and I don’t think there ever have been in Australia. Can you think of any,

[00:31:29] Tony: Myer in there for a while, but it’s not a digital retailer. Um, super, super,

[00:31:34] Tony: yeah, super, super group. They do, I guess, aesthetic clothing, but, but yeah, you wouldn’t expect it to. Yeah. We haven’t had much in the, in our portfolio. And, and interestingly enough, I had a bit of a relationship with Lanzin when I was running MyerDirect.

[00:31:50] Tony: It was one of the, it was a catalog retailer from the US that we had a licensing deal with to remarket their apparel in Australia. So it’s been around for a long time. And as you say, it’s not, it’s by no means some kind of AI tech, um, gross

[00:32:04] Tony: stock. It’s, you know, it’s a, a fashion retailer, basically.

[00:32:08] Tony: Oh, buying

[00:32:11] Cameron: stocks for this portfolio, of course, I mean, I know nothing about anything anyway, but particularly, I know nothing about these U. S. companies. I had heard of Land’s End, but I hadn’t heard of the rest of them. But all I was doing was running our filter over them.

[00:32:27] Cameron: So looking at their financials, essentially, and their performance, giving them a score based on what our Checklist told me that, uh, their value and their quality was, and then buying the ones with the highest score. And then really not doing any more research or any more thinking about it. And in some cases it was quite scary because I was looking at some of them thinking, God, I know nothing about this.

[00:32:51] Cameron: And sometimes their charts looked horrendous, um, their stock charts. But, you know, I’d run them through the process, and if it said they were a buy, I’d buy them, and not all of them have worked, but some of them have worked, like this one, up a hundred percent, um, since I bought it. And let me tell you, um, I’ll try and open up the transactions for this.

[00:33:16] Cameron: So I bought it in November, 20th of November, so a little over seven months it’s, um, gone up. 100 percent which is astounding. I have no idea why. Can’t tell you why. Don’t know. It just has. The second one in terms of performance is Stealth Gas, G A S S, which is a freight and logistics company, provider of international seaborne transportation services.

[00:33:45] Cameron: I think that just means shipping to liquefied petroleum gas producers and users as well as crude oil. It’s up about 64 percent since, um, I bought that in October last year, so about 7 months, 8 months. Um, you familiar with Stealth Gas, Tony?

[00:34:07] Tony: I am not, no, even though I worked in the oil and gas industry, it sounds, it sounds like it’s a, it’s a shipping company for oil and gas, you know, oil and gas

[00:34:16] Tony: transport. Didn’t we do it? We did an Australian company called Stealth Something last week. Uh, the week before, we were doing a deep dive We did.

[00:34:25] Tony: Yeah. Different

[00:34:25] Tony: company.

[00:34:26] Cameron: And they had nothing to do with being stealthy. I don’t know what stealth, I don’t know why

[00:34:29] Cameron: Stealth Gas is particularly stealthy.

[00:34:32] Tony: Yeah, Stealth, the Stealth company listed in the ASX was about, um, it was a hardware chain, or it was selling

[00:34:40] Tony: industrial equipment and hardware, basically in WA.

[00:34:45] Cameron: Stealth Gas is a shipping company, just is the first of a number of shipping companies that we’ll talk about. The next one is Grinrod Shipping Holdings, G R I N. A Singapore based shipping company that owns, charters in, and operates a fleet of dry bulk carriers. It’s up 49 percent since I bought it.

[00:35:07] Cameron: I bought it in October, sold it in November, and then bought it again at the end of January this year. Um, It’s done quite well since then. The fourth is Global Ship Lease, GSL, a United Kingdom based container ship owner, leasing ships to container shipping companies. It’s up, uh, about 42 percent since I bought it in, let’s see, January this year, the 12th of January.

[00:35:40] Cameron: And again, shipping companies is something that I really don’t see turn up on our buy list in Australia.

[00:35:47] Cameron: And

[00:35:48] Tony: we have any in the

[00:35:49] Tony: ASX that I can think of. Mm. Mm. Mm

[00:35:53] Cameron: this is interesting that three of the top four performers in the US portfolio have been shipping companies. So obviously when I was assessing them all six months ago, something was going on, whether it was Ukraine or Gaza or who knows what, that had forced the prices of these stocks down or something has happened over the course of the last six months that has caused the prices of all these shipping companies to go up some geopolitical global conflict or market trade issues who knows but our system identified six months or so ago that they were undervalued based on their financials and the the marketers uh also recognized that over the course of the

[00:36:40] Cameron: last six months and their And that’s something we’ve noticed in the, you know, running QAV in Australia is that, uh, we can seem thematic in the portfolio construction, even though we weren’t setting out to do that. But the numbers just happen to focus on one particular industry, whether it’s gold mining or airlines or banks or whatever.

[00:36:59] Tony: But at the moment, in the US, it tends to be shipping companies. And you’re right, that could be because of, you know, if you remember, the Suez Canal was blocked about a year ago. Mm hmm. And shipping had to go around the long, the long way, uh, which added time and cost to the, to, uh, transport. So I don’t know if that had a bit to do with it, whether interest rates are playing into it, who knows.

[00:37:19] Tony: We don’t really care. Um, we just thought they were, you know, good quality companies selling at a reasonable price. And, um, and then the industry re rated. Regression to the mean

[00:37:28] Tony: happened. Yeah. Rerated. That’s a good term. There’s a fifth one, uh, fourth one out of the top five here, by the way, is Euroseas, E S E A. Euroseas is engaged in the shipping business. The company is an owner and operator of dry bulk and container carrier vessels. So there you go. That one is up about 40 percent since I bought it, uh, November 2023.

[00:37:54] Cameron: So four out of the top five, uh, shipping companies, which is Euroseas. Quite strange. Then we get into the banking and finance sector. So, number six on my list is Optimum Bank Holdings, OPHC, a bank holding company, a state charted bank, whatever the hell that means. It’s up 35% Then we have Willis Lease Finance, WLFC, it’s a lesser and servicer of commercial aircraft and aircraft engines.

[00:38:27] Cameron: But, uh, a finance company, I guess. Um, for some reason it’s share price is just Blown up in the last, uh, month and a half. We went from 48 on the 29th of April, up to 65. I got no idea why, but it’s up 32 percent since I added it. This one, I obviously had to buy because it’s TK. Literally, letter T, letter K, um, which is, uh, as listeners know, what I always refer to Tony as, Tony Kynaston, TK.

[00:39:05] Cameron: This TK, though, not you, it’s a provider of international crude oil and other marine transport services. You’re just a provider of international crude jokes. Um, ah, again, another, uh, shipping company. This one’s up 31%. Then we get back to finance and banking. This is, uh, next one is regional management. RM is the code, Diversified Consumer Finance Company.

[00:39:34] Cameron: It provides installment loan products primarily to customers with limited access to finance. It’s up 21%. Next, you know, the Foreign Trade Bank of Latin America, BLX. Multinational Bank, up 18%, Mitsuho Financial, MFG, a Japan based bank holding company, up a whopping 2 percent since I bought it. And then these last two, the last three are actually underwater.

[00:40:12] Cameron: IVR, Invesco Mortgage Capital. It’s down about 1 percent since I bought it. Innova International, ENVA, a technology and analytics company is down about 1%. And Andersen’s, ANDE, a diversified company engaged in the operations of agricultural supply chain, down about 2. 6 percent since I bought it. When did I buy it?

[00:40:36] Cameron: Uh, November 23. So handful, three of them. They’re not doing great. Um, 1, 2 percent Mitsuo, the rest up 18 to 100%, um, which is extraordinary, um, by knowing nothing about the market or nothing about these companies, just analyzing their financials and buying them if they score well.

[00:41:03] Tony: Yeah, I think I just want to add at this stage too is that discussing those individual stocks are, um,

[00:41:08] Tony: it’s not a recommendation for people to buy them Go and do your own research,

[00:41:12] Tony: but, um, you should have bought them

[00:41:14] Cameron: six months ago

[00:41:15] Cameron: Yeah, you should have bought them six months ago when we bought them.

[00:41:18] Tony: Yeah.

[00:41:19] Cameron: Yes. Yeah, look, and we’ll put a disclaimer at the end of this as we always do, but obviously you shouldn’t take anything you hear on this as financial advice. We’re talking about an investing system.

[00:41:30] Cameron: We’re not telling you what to buy. But we’re happy to, if you stick around, Teach you the process by which we analyze these stocks. So, um, running through that list, Tony, does anything else apart from the thematics of it jump out at you?

[00:41:49] Tony: doesn’t. Um, it’s, it’s, in some ways it’s like the Australian experience, isn’t it? There’s, uh, you said before you hadn’t heard about any of those stocks in the US. Well, it’s often the case that something will come up on our buy list and I’ve never heard of it before either and go along and research it and have a look at what it does.

[00:42:05] Tony: But, um, yeah, it’s, and maybe that’s part of the process is that the market hasn’t focused on it yet and there’s no chatter about it yet. It’s undiscovered, so to speak. Um, yeah. But no, nothing, nothing else sticks out, um, other than what we’ve been saying, that the process is about using data to drive our decision making.

[00:42:25] Tony: Um, you know, building on the principles of value investing, looking for strong cash flows in businesses, and then waiting for them to be discovered and regressed back to the mean, or for whatever was causing them to be depressed to fade away. That’s the other important thing too, is that, you know, even the very best companies will have, you know, Times in the shade, um, for whatever reason, you know, interest rates have risen or the war in Ukraine or whatever.

[00:42:51] Tony: Um, but that’s the best time to buy them, right? Because they, they, you know, generally, um, don’t take, they don’t take forever to get out of that position and get back to rewriting or regressing back to where they’re, they should be. In investors eyes, back to their true value. Um, and that’s the time to buy.

[00:43:10] Tony: So that’s one of the other reasons why I like value investing. You’re a bit of a contrarian investor. Um, so you’re buying stocks when they’re cheap for whatever reason.

[00:43:17] Cameron: mm

[00:43:18] Tony: an article today on the AFR as I was skimming through it. I don’t often read the property section but I was skimming through it and there was an article there saying that retail shopping malls are now You know, um, so sought after investments, top of the list for property investors, and it was only, you know, one or two years ago when you couldn’t give them away because of COVID shutting down, you know, retail and, um, companies going out of business following COVID and lots of leases, and now they’re, you know, they’ve gone from basement to the penthouse, um, in probably 18 months, so that’s just the way that things work in cycles, and that’s an important part of value

[00:43:56] Tony: investing.

[00:43:56] Cameron: mm And you know, there’s a lot of emotion tied up in those things. I mean, and you know, another thing I’ve learned doing this with you for the last five years is just looking at the market in general. Talking about the Australian market is how much that seems to be driven. Uh, you know, at a macro level, buy emotion.

[00:44:15] Cameron: You know, we often talk about it. Like the market will go up by a significant amount one week and then down by a significant amount the next, like what changed? Well, really nothing, I guess. And then it’ll go back up

[00:44:27] Tony: people’s

[00:44:27] Tony: opinions.

[00:44:28] Cameron: Yeah. There’s a new story about this conflict or

[00:44:31] Cameron: this interest rate rumor that interest rates will go up, or they’ll be cut, or the US jobs growth is gonna go up, and the market just fluctuates, and you go, well, really, nothing’s, there’s no real new data or new facts that should shape where the market’s going, it’s just all over the place.

[00:44:50] Cameron: By the way, I just noticed that in the Stockopedia portfolio, it says, um, Dividend Income Zero. So, it’s either, we either haven’t earned any dividend income from these stocks, or it’s not tracking dividend income from these

[00:45:08] Cameron: stocks. So, uh, our performance versus the S& P 500 is, uh, net net there, I guess.

[00:45:15] Cameron: It’s, uh, both of them probably not including any dividend income.

[00:45:20] Cameron: All right, well that’s a quick overview of the US portfolio and how it’s doing. Uh, now what we often do or what we usually do on the show is you will do a deep dive on a stock even though typically we don’t spend a lot of time researching individual companies. It is good to get a sense for different businesses and what they do.

[00:45:40] Cameron: We call this the pulled pork. Uh, no, No good reason. I think just once you said you were going to pull it apart and I called it a pulled pork and it just sort of stuck. So, what company are you doing a pulled pork on today, Tony, and why?

[00:45:57] Tony: Pulled Pork on RGA, which is listed on the New York Stock Exchange, Reinsurance Group of America. And the reason why I’m doing the Pulled Pork on that is that, uh, it’s very high up on the buy list that you produce from Stockopedia. And it’s also a large cap stock, so, uh, their ADT is something like, 76 million dollars.

[00:46:18] Tony: So the average daily transaction amount is 76 million dollars. And that’s something we look at because when people are constructing their portfolio, we don’t want them to get into very small companies and then find it hard to get out, and that they’re buying or selling in or out of those companies is forcing the price up or down.

[00:46:38] Tony: So, which is, you know, something we try to avoid. So this is a big one. Um, I guess I should also say, this is kind of learning by doing for me anyway, that you’ve done all the work and it’s been good in terms of putting together the Stockopedia feed of US stocks, but we don’t have every item in the checklist that we use currently in Australia because, you know, Stockopedia has a different data feed and different, you know, numbers are in or out of what they produce compared to what we’ve been using.

[00:47:07] Tony: So we’re kind of learning as we go here about, you know, what, um, what we can, um, Do with or without, and also what we might need to find other sources for, so that’s, I guess, an important caveat to make as well. Um, so I’ll go through the numbers for Reinsurance Group of America as they appear on that checklist.

[00:47:27] Tony: Before I do that, I’ll talk a bit about what it is and its history. So, uh, began life back in 1973. Uh, it was a business unit of a bigger insurance company called General American Life Insurance Company and, uh, that, that company, GAL, decided to start, uh, an insurance or reinsurance division and, um, a bit on, um, I guess the terminology because the company adopted the strategy of what they call facultative underwriting.

[00:47:58] Tony: I hope I pronounced that right. And I guess I should also apologize in advance. I’m not an insurance specialist. I have invested in insurance companies in the past. I do invest at the moment in QBE, which is an insurance company in Australia. So if I get some of the terms wrong or mispronounce them or my Definitions aren’t right, and forgive me.

[00:48:17] Tony: I’m happy to be schooled, but my understanding of reinsurance is that, uh, you have an insurance company, um, and then sometimes insurance companies will want to lay off their risk to reinsurance companies. So they provide partners to partner with them. And, um, I guess, uh, that could be for a number of reasons.

[00:48:36] Tony: The simplest example would be that an insurance company decides that they want to service the customer who’s come to them and ask for insurance, but they, uh, if everything goes bad and they have to pay out 100 percent on the policy, then they probably can’t afford to do that by themselves. Or they want to, they want to protect their own balance sheet.

[00:48:54] Tony: And so they’ll go and seek a partner to come into that deal with them. And on the, when, when insurance has entered into that way with re insurers, it’s called facultative. Or case by case in reinsurance. So basically the reinsuring business will do the sort of normal underwriting checks that the insurance company did.

[00:49:13] Tony: So for example, you know, if it’s one of the shipping companies you talked about and they’re after insurance for a vessel, uh, they go to their insurer and say, I need, you know, a hundred million dollars if Um, to replace this vessel if it sinks, um, you know, give me a quote on insurance. Well, the insurance company might decide they’ve already got a hundred of these policies in force and they can’t afford to pay out a billion dollars if every boat sinks, um, or whatever the sums are.

[00:49:40] Tony: Um, so they go and talk to a reinsurer who’ll take on some of the risk as well and charge a fee or, or split the commission, um, with the boat company. Um, and the insurer. So, uh, that’s what facultative reinsurance is. It’s this kind of, um, laying off by the insurance company, but the reinsurance company will assess the risk and charge a price.

[00:50:01] Tony: I guess that’s the other side of the coin is what they call treaty reinsurance, which is where, um, A company might decide that it has too much exposure to one sector and then will offload the whole sector to a reinsurer. So, for example, um, you know, one of the insurance companies in Australia might decide that it’s got too much exposure to, um, flood insurance.

[00:50:21] Tony: You know, there’s been lots of floods in Australia over the last, you know, And so they might decide to go to a reinsurer and say we’d like to offload some of our risk for all the flood insurance policies. And then the reinsurer will do an assessment of what the risk is in general for flood insurance in Australia and then offer a price to take over some of that liability.

[00:50:42] Tony: So two types of reinsurance. RGA tends to play in the case by case side of things. And they started back in 73. And, uh, they’ve made a good go of it. So, they, uh, quickly expanded overseas, into Canada in particular. Um, they, in the 80s, they kind of pioneered using technology as it was back then, um, to quickly review cases.

[00:51:09] Tony: So, so I should say that they specialized in life insurance to start off with. And, uh, Their niche was to be able to quickly review policies and make a decision about the re insurance cost of those policies to the insurance company. And in the early 80s, they were able to do up to 60, 000 cases a year in this way, and that gave them a bit of an edge in the market.

[00:51:33] Tony: Uh, by 89, the division was the second largest life insurer in the USA. So, they decided soon after that, Um, to separate that business and spin it off and list. And so in 1993, RGA listed on the New York Stock Exchange, even though the parent company still maintained a controlling stake. Um, since listing in 1993, the company reports that it’s achieved greater than 17% Uh, compound annual growth in total assets and, uh, the last figure I saw was in 2021, assets totaled 92 billion.

[00:52:11] Tony: So it’s been a successfully operated and run business since then. Certainly a large business now. Uh, after listing in 93, RGA expanded overseas and it actually hit Australia in 1996, um, offering the first reinsurance treaty to an Australian company back then. Uh, they operate all around the world. Uh, particularly in Asia Pacific, where they’ve, um, been able to expand into countries like Japan, which has had, uh, uh, from, you know, some reports, uh, some curious rules around insurance companies, so RGA was able to navigate its way through those, and also into countries like Indonesia, which, um, RGA pioneered, uh, Shariah law, uh, compliant insurance, uh, Businesses for them.

[00:52:57] Tony: So quite innovative, um, company and, and working around the world. Uh, in 2003, uh, they, they acquired the life, the reinsurance business of Allianz, uh, for 275, well, they acquired 275 billions, uh, dollars of packages, a package of policies worth 275 billion dollars, um, and met life around that time. Bought the controlling stake from General American Life in the company, uh, in 2009.

[00:53:34] Tony: Uh, RGA acquired the reinsurance business of ING in the US and Canada. Uh, and soon after that entered the Fortune 500 at number 321, and in 2018. They entered the Forbes Best Regarded Company and World’s Best Employers list. So, um, they’re now quite large in worldwide operations, but large in the US. Along the way, they were able to, um, uh, to, uh, buy out the MetLife controlling stake.

[00:54:06] Tony: And so there is no sort of large insurance controlling stake within this company now. Um, in COVID, they paid out. More than two and a half billion dollars in COVID related claims in 2020. And in 2021, they were named the Life Reinsurer of the Year. And last year, 2023, was their 50th anniversary. So, big company.

[00:54:30] Tony: Got it. The first question that I was sort of thinking of when I read about this company was, It’s a large company. It’s in the Fortune 500. Why can I buy it so cheaply? And, um, I guess I’m going to extrapolate my, my knowledge of the insurance industry in Australia and assuming it’s, it’s having some kind of, uh, similar resonation in the US.

[00:54:51] Tony: But, um, if people think back a year or two, insurance companies were a bit on the nose in Australia, life insurance companies, I should say, were a bit on the nose in Australia. Um, and for a couple of reasons, uh, and I guess some of these will also be applicable to the States, but, um, low interest rates was hurting their business.

[00:55:11] Tony: So if you think about Berkshire Hathaway and it’s, um, storied float that they talk about that Warren, um, uses to, to fund his, uh, his investments, it’s basically the premiums that are taken from customers, but then have, um, many years sitting around on the balance sheet. of the insurance company before it needs to get paid out in claims.

[00:55:33] Tony: That’s particularly the case in life insurance. Um, but life insurance, um, not sure about the US, but outside of the US, like in Australia, it’s pretty heavily regulated how they invest. their float because governments are concerned that someone’s been paying a life insurance policy, you know, over their, the term of their life.

[00:55:53] Tony: And when they come to collect it, the money’s got to be there. So, uh, investments for life insurance companies, uh, uh, highly regulated, at least in this jurisdiction. Um, and so they have to be put into, you know, AAA government bonds and, um, corporate bonds. I’m not sure exactly what the cutoff is on, on the ratings, but they have to be in highly rated, uh, Investments, usually bonds.

[00:56:16] Tony: I guess they can have some other kind of equivalent investments, but certainly the insurance, life insurance companies in Australia weren’t able to go out and buy railway companies or electricity companies like Warren does in the US with his insurance float. I suspect the same thing Perhaps it’s happening with, um, the insurance business in the US, although, you know, Berkshire Hathaway is kind of leading me to think it may not be as regulated as it is in Australia.

[00:56:42] Tony: But anyway, the point I’m going to make is that, um, companies that were invested, um, over the last, say, four or five years face very low interest rates and therefore their, their earnings from their float wasn’t very high. Interest rates are now returning back to, um, like I’ll call them normal, but You know, regressing to the mean, going back to what they were before the last sort of 10 years of almost zero interest rates, which has been unusual in my lifetime.

[00:57:08] Tony: Uh, and that means that the, the life insurance companies are getting paid something for the premiums that they’re, they’re holding, uh, long term. Um, when life insurance companies weren’t making much from their float, they, they basically had to raise all their profits by putting up their premiums. And, you know, because of competition, that’s hard to do.

[00:57:29] Tony: Um, because your competitors may not want to, you know, will be trying to undercut you for market share. So you can’t just raise a premium willy nilly. You’ve got to consider how it affects your market share position. And so life insurance companies were doing it tough. They didn’t have the float income they normally would have gotten or had gotten in past years.

[00:57:47] Tony: Um, and, you know, were therefore trying to compete on premium price and they were Racing stiff competition and a lot were losing money. Additionally, the other sort of bump in the road for life insurance companies, at least in the Australian context, was that there’s a lot more mental health related claims in the last sort of five to 10 years than would have been factored in by their actuaries when some of the policies were written, you know, way back 20, 30 years ago.

[00:58:15] Tony: Um, and so. Given the fact that they were all competing on price with their premiums, it was hard for them to raise the price to account for that sort of spike in mental health claims. Um, and, and therefore, you know, that’s, that’s been another driver of negative profit growth for them. Um, I think what’s probably happened on the positive side of things and maybe a tailwind as to why RGA is starting to to tick up and it’s been doing well in terms of its stock price movement in the last sort of 6 to 12 months, um, is because, uh, A, the float is earning a reasonable income now, and B, Because of inflation, every sort of insurance policy is going up in price, and it’s much easier to to raise prices when prices are going up anyway.

[00:59:04] Tony: So, you know, you don’t, you don’t stick out like a sore thumb if you’re the only person raising prices because everyone’s raising prices. Um, and you know, if your price goes up by 11 percent when inflation wasn’t running quite that high, You know, it’s going to get lost in the, in the wash sometimes. So it’s easier to, to start to reprice for mental health risk when prices are rising due to inflation is, I guess, what I’m trying to say.

[00:59:29] Tony: So, um, that’s another, um, Tailwind for this for this company at the moment. Um, and I think the other thing which, which probably favors this business, even though it is a life insurer itself, it’s probably main business is still reinsurance. Uh, the, the reinsurance business isn’t customer facing. So the life insurance businesses are, they’re the ones who are going to cop.

[00:59:51] Tony: Um, any sort of, you know, government inquiry into insurance prices going up. The reinsurance businesses have a, um, less of a public spotlight on them, and therefore have less of a dampener on price increases. They just, you know, they still have to be competitive because it’s a competitive market, but they’re not going to face as much scrutiny.

[01:00:12] Tony: Um, their price will be absorbed by the life insurer, who will then try to pass on the price rise to the customer, you know. The, the end customer, the retail customer. And that’s, that’s the area that the governments are gonna focus on if they, if those prices rise too much. So now the reinsurers do get a, um, a, a bit of a benefit from, from being in the back room, so to speak.

[01:00:31] Tony: So, um, interesting company to go through the numbers now, which might shed some light on why, why we like it. Uh, and all of these numbers are in US dollars. I, I hasten to add, um. Large cap stock, 13. 7 billion US dollars market cap, 76 million ADT. Uh, the thing I really like about this company is it’s PropCaf, so price to operating cash flow is 1.

[01:00:56] Tony: 68 times. So, it’s throwing off lots of cash, and you’re being paid back quickly for your investment, is how I like to look at that, in under two years. So, to use the coffee shop analogy, um, your, whatever you, buy into the coffee shop for, you’re going to get back in terms of its cash takings at least, I know it’s not profit, but it’s the cash, in 1.

[01:01:19] Tony: 68 years. So it’s a quick, it’s a quick return for your investment, um, which I like. Uh, Stockopedia don’t have the same sort of financial health ratings that, uh, that Stock Doctor do, um, but they do rank companies according to financial health. So Stockopedia is a factor based system where they rank companies based on momentum, quality and value and then combine all those three things to stack rank scores from 100 down in terms of their scoring.

[01:01:53] Tony: Um, interestingly enough, this, this company in Stockopedia ranks best for momentum. So as I said, the share price has been going up nicely. It ranks 97 due to momentum, but actually on the quality side of things, it looks like it’s about 56, which is, um, pretty good. Low. And on the value side of things, it’s 76.

[01:02:12] Tony: So even though we’re calling this a QAV stock, and certainly on the, if you ignore the, the stock Edia rankings, it, it rates well. Um, stock Edia, uh, aren’t rating at highly, uh, for quality and value and not rating it poorly, but there are other companies higher up on their list. Um, so I’m not gonna give her the score for that.

[01:02:32] Tony: Uh, the share price I’m using, uh, when this download was done is. 209 per share and it’s a bit less than that today. I think it’s about 204. 50 when I had a look this morning. Um, but 209 is greater than our intrinsic valuation number one and less than intrinsic valuation number two. So there are two, um, IVs which are based on the forecast earnings per share for the stock, um, and using different hurdle rates.

[01:02:57] Tony: One at, uh, at, um, uh, the cash rate plus risk premium. And, which is IV2, and one at a 19. 5 percent hurdle rate, which is quite a high bar indeed, but we’ve used it traditionally to seek out value. We can’t buy this stock for book plus 30%, so we can’t buy it for anywhere near book value, so we can’t score it for that.

[01:03:23] Tony: Um, one of the things I still have to find a source for is historical PE ratio. So, QAV looks for, um, the lowest PE in the last three halves, or, um, sorry, the last six halves, the last three years, but I couldn’t see that in Stockopedia. I had a look through Yahoo Finance and couldn’t find it easier. It’ll be out there, but I just haven’t sourced it yet, so I haven’t been able to score it for that.

[01:03:47] Tony: Having said that, the PE is 14. 5, which is not overly high. And one thing we use the PE for is to look at the PEG ratio, the PE ratio compared to growth. Um, we do growth over PE. Which is not quite the PEG ratio, it’s the reverse of it, but anyway, um, the Stockepedia is reporting that the earnings per share is forecast to grow 25.

[01:04:14] Tony: 7 percent next year for this company, which is quite a lot for a Fortune 500 company operating in the reinsurance space, so, um, That’s quite a big increase for a big company. But if I put 25. 7 over the PE of 14. 5, I get 1. 77. And we look for companies and score them if they’re above 1. 5. So that’s a, you know, quite a nice, um, uh, metric there.

[01:04:38] Tony: Growth over PE, 1. 7 is a good score. Uh, this company is only yielding 1. 6%. Um, and it doesn’t have any franking credits, so we’re not going to score it for yield. Uh, we look for companies which are above the, or yield, uh, above the, the current average mortgage rate, which is six point something in Australia.

[01:04:56] Tony: Um, might be lower in the US, but even so, 1. 6 percent wouldn’t cut it. Uh, so, can’t score it for that. Uh, doesn’t have an owner founder, so, Stockopedia is, um, reporting that Insiders, uh, Bye. I own a small fraction of this company. Although I did notice when I was doing the research that RGA’s first actuary, a guy called Greg Woodring, went on to be the president and CEO for three decades.

[01:05:22] Tony: So it was run by, not so much an owner founder, but certainly a founder for a long time, which might account for its success over those first 30 years. Haven’t been able to find, um, again, uh, the consistent equity, increasing equity, uh, score that, uh, I like to see, but, um, we will find a replacement for it.

[01:05:46] Tony: But, yeah, we look for whether equity’s been consistently increasing over the last two and a half years, uh, by half, and, um, I couldn’t score it on that because I can’t see it. So given that we have a few gaps in in our checklist that we normally use, um, I’ve summed up the 10 things we could score this company on and uh, it gets a score of 8 for those.

[01:06:06] Tony: Uh, so 8 out of 10 is 80%. That’s the quality score for the company. And if I divide that by the price to operating cash flow, I’m getting a QAV score of 0. 48, which is quite high up on our On our checklist, um, I think it was number three or four on the download you, you sent through to do this analysis. Um, so a big company scoring very well.

[01:06:29] Tony: Um, obviously one of these, you know, companies which, uh, it’s, Uh, it’s coming out of perhaps what I was talking about before with interest rates. Um, and I guess the last thing I should mention is that we use sentiment as a check for us, a go or no go. And, um, our tool, the Bredalator, does work for the New York Stock Exchange, as it does for many stock exchanges, and RGA is well above its buy price.

[01:06:56] Tony: It’s basically been on the improve since, um, well it’s been a buy since about, uh, January 2022. Although I would add it’s a bit of a Josephine at the moment, meaning that it’s trading for less than its previous month’s close. So it’s had a bit of a, um, a tick down at the moment, even though the trend’s pretty solidly up.

[01:07:17] Tony: Uh, but it’s worth watching because when it does, um, If it does, and I expect it would, um, tick up, given its forecast earnings per share is growing, uh, it might be a good time to look to purchase this stock, but certainly do your own research on this one, but I found it very interesting to go through. Mm

[01:07:36] Cameron: Thank you, Tony. RGA. I was just asking ChatGPT to explain reinsurance to me

[01:07:46] Tony: hmm. how it works. Risk management, capital relief, stabilizing losses, capacity expansion, and solvency protection. Apparently, uh, sort of some of the reasons why insurance companies do reinsurance.

[01:08:01] Tony: hmm.

[01:08:02] Cameron: Not something that I know much about.

[01:08:04] Cameron: Okay, so any other takeaways from doing your first pulled pork on a U. S. stock,

[01:08:09] Cameron: Tony?

[01:08:10] Tony: I think it’s, uh, you know, it’s a rare thing, um, on our buy list to find a large cap stock like this so high up. We do, it does happen from time to time, you know, Fortescue Metals Group, the big iron ore miner is there, occasionally BHP and Rio have been there, other big iron ore miners, um, Commonwealth Bank, the biggest stock on our index was there.

[01:08:31] Tony: Um, but at the moment, there, there Many big stocks at the top of our buy list, whereas perhaps because the U. S. is such a big market, we’re going to find larger, uh, market cap stocks there, um, which are sort of meeting the metrics of value stocks, um, more frequently than we do here.

[01:08:50] Cameron: Well, if you scroll down to about number 20 on the US list, you see AT& T with an average daily trade of 650 million. So,

[01:08:59] Cameron: and

[01:09:00] Tony: Yeah, right.

[01:09:03] Cameron: score of 0. 25 when I did this buy list, which was about a week and a half ago, two weeks ago. But, uh, yeah, that’s huge,

[01:09:15] Tony: And then of course we need to check the sentiment of AT& T. So that’d be interesting to see what its share graph is telling me.

[01:09:21] Cameron: Yeah, I was positive then, but I haven’t looked at it today.

[01:09:26] Tony: Okay,

[01:09:28] Cameron: Okay, well, uh.

[01:09:31] Cameron: Yes, that’s pretty much all I’ve got to talk about in terms of US stocks for this week.

[01:09:38] Cameron: I think we

[01:09:38] Tony: Well, it’s a lot.

[01:09:39] Tony: I do.

[01:09:40] Cameron: Yeah. It’s

[01:09:41] Cameron: a lot. It’s a good little introduction.

[01:09:43] Cameron: Um, couple of things I did want to just finish off with though, uh, one thing. Last week on our show and in our newsletter, I mentioned that we have a financial, end of financial year survey.

[01:09:58] Cameron: Um, I asked people to go and let us know what their performance have been for the financial year because for non Australian listeners, our financial year closes at the end of June. And also to tell me their performance, uh, over the course of how long they’ve been investing with QAV and, uh, the performances were all over the place as we kind of expected. Can we talk a bit about this on the show last week? There’s a lot of variables in the short term, depending on, you know, what stocks you happen to buy, how many stocks you hold in your portfolio.

[01:10:37] Cameron: Whether you’re buying big ADT or low ADT stocks, uh, how well you follow the rules. All sorts of things can happen. Um, over the long term, we would expect that people’s performances sort of average out, but in the short term, year to year, it can be quite different. So I’ve only had seven responses since I posted this last week.

[01:10:59] Cameron: People don’t like answering my surveys, I’ve determined, I just stopped doing them outside of this one. But to give you an indication of these seven responses, uh, one person said their financial year was 10. 43%. Next person said theirs was 5. 3%, next was 4. 45%. The next was 19. 57%. Um, next person said there was down 4 percent their portfolio due to a lot of free PTL sales.

[01:11:37] Cameron: So their long term returns are only 15. 6 percent per annum, which is pretty good. Um, but I don’t know how they didn’t tell me what their inception date is. So I don’t know what that, how long term that long term is. Then I got a couple of comments, uh, not quite. Part of the survey, but just comments on my post.

[01:11:57] Cameron: One was from Michael. He said his financial year return was 27. 71%, which is astounding. Congratulations, Michael. And his inception, since inception, it’s 22. 41%. But again, he didn’t tell me when his inception is. So, um, and he also says that’s coming out of ShareSite. Uh, not sure if that’s CAGR. I think you use ShareSite a bit.

[01:12:25] Cameron: Does it, do you do CAGR? Time weighted? And then Ed said, um, his performance since inception is 12. 08 percent measured by share site. But he also said since inception was November 2019. And I know Ed didn’t become a QAV member until the middle of 2021. So I shot him an email today going, how does that work? Um, He said his past year is 8.

[01:12:59] Cameron: 4%. Um, he said, I’m happy with greater than 12%, but I’d dearly love to be getting double market. I’m thinking it’s due to having a higher ADT and most have current analysts commentary. We have talked from time to time. How about. We like stocks that don’t have any analysts looking at them because we can often get in before the analysts give them too much coverage.

[01:13:25] Cameron: Anyway, thank you to everyone who filled that out. And if you haven’t filled out the survey, do consider it. You can do it anonymously, uh, because it’s good for us to know what the range of results is. But I think even just with that small sample, we can see that it’s, it’s all over the place. And I know my super portfolio had a negative return again for this year, um, as it did the year before.

[01:13:50] Cameron: Just a whole bunch of rule ones, uh, I think in a few 3PTL sells in my super portfolio, which again has a high ADT requirement. Um, so yeah, hasn’t been the best year for my own portfolio, but then again the dummy portfolio has had a relatively good year. Not quite as good as the index, but I think it’s up like, I don’t know, 12 percent or something for the financial year, so it had a, uh, reasonably good year.

[01:14:16] Tony: me. I think, um, it looks like my, my super portfolio finished negative this year as well. Um, I think it only holds about two or three stocks at the moment. So that could be contributing to it. But, um, again, um, you. The price you pay for a concentrated portfolio is volatility. So when, if those two or three stocks turn around or

[01:14:37] Tony: when they turn around, it’ll reverse pretty quickly and pretty hard.

[01:14:42] Cameron: And why do you only have two or three stocks

[01:14:44] Cameron: in it?

[01:14:45] Tony: Um, well, I have a small, smaller portfolio, um, And the Superfund’s only a part of that. So I have, you know, I think it’s, I don’t have many stocks. I probably have seven or eight stocks across everything, all the sort of structures that I own stocks in. Um, but the Superfund is the one that, uh, is easiest for me to manage because it doesn’t have cash flowing in and out of it for other uses, like, uh, stocks in my own name do, or, um, stocks in our family trust do.

[01:15:14] Tony: So it’s, um, it’s the kind of pure way to, to measure the

[01:15:18] Cameron: Easy to report on. Yeah, right.

[01:15:20] Tony: Yeah,

[01:15:21] Cameron: Okay. Uh, well, that’s all the main show for this week. Now, for people that are new, what we normally do at the end of the investing chat is we just do after hours where we just talk about everything else that we’ve been doing and that we’ve been thinking about. You can turn off at this point if you’re not interested, but, uh, I’m interested because this is my chance to chat to Tony each week about what’s going on.

[01:15:44] Cameron: What’s been going on outside of investing with you, TK?

[01:15:48] Tony: yeah, a couple of things. It’s, you know, because of our AFSL license requirements in Australia, I’ve had to finish off my 20 years, 20 years, 20 hours of study, which I did in the last week or so, which, um, I had been slack and kind of back ended through to, um, the last month, so I’ve done a lot, a lot of reading and taking exams in the last month

[01:16:15] Tony: to, on the Kaplan system, which is fine.

[01:16:18] Tony: That’s, that’s been interesting. Um, what did you learn from your 20 hours of study, Tony?

[01:16:24] Tony: Well, um, It’s, because I’m not doing my AFSL requirements to meet a particular license section, like if I was a credit provider or if, if, um, you know, I was a mortgage broker or bank or something like that, um, I tend to focus on this, the, um, general stream and the ethics stream, which, um, I guess are more pertinent to what we talk about.

[01:16:50] Tony: Um, ethics has been interesting. Um, I mean, yeah, basic. Ethics that you do, you know, do the best, use the best interest of the customer in, um, will hold the best interest of the customer in your mind when you’re making decisions about how to service them. Um, but there’s been some other interesting, um, modules around that and going into the philosophy of how you work out what your values are and your ethics.

[01:17:19] Tony: So that’s, that’s been interesting and, and conflicting. I think if you, you know, sort of step back and look at everything that they’re talking about, uh, cause like there’s the utilitarian approach to ethics when it’s applied to the financial advice industry, which is to do the, you know, the best, have the best outcome for the most people, which may not suit the individual that’s right in front of you asking for financial advice.

[01:17:44] Tony: You might, um, you know, you might decide that it’s the best outcome for the best people is to only invest in ESG stocks. You know, as I read an article in the Financial Review recently, which said that something like 20 billion has exited the ESG market. Um, Recently because people aren’t making money investing in the ESG market.

[01:18:05] Tony: So, yeah, it’s interesting having, investigating an ethics overlay into financial services and financial advice. So that’s been fun. Um, yeah, and the other, I guess, theme that’s appearing in financial advice is in every industry is AI. So, I’ve read a couple of modules on that, um, seems like at least in terms of, um, financial advisors, the, um, AI is going to play a part, but seems to be at this stage, um, I’ll, I’ll use the term mere automation.

[01:18:42] Tony: So it’s, it’s about automating, uh, the marketing for financial advisors, the checking of work before it goes out with financial advisors and less about, um, actually dealing. with an end customer and trying to understand their risk tolerances and, and provide dedicated advice. Potentially that’s coming, but there were plenty of case studies in, in examples I read where, you know, it’s a fairly nuanced game reading someone’s risk tolerance and then providing the right advice to suit, to suit that.

[01:19:15] Tony: And, um, there are examples of, Where people had tried to use AI for that, but there were hallucinations and there was wrong information coming out and that kind of thing. So, sort of consensus from what I read was, is the industry is looking to to AI, but not yet for financial advice, but certainly for automation.

[01:19:35] Tony: So that was interesting too.

[01:19:36] Cameron: Hmm. Okay.

[01:19:39] Cameron: What else?

[01:19:40] Tony: Um, and then, uh, I watched a couple of things on TV. Um, Jenny was away, so I had a lot of time on my hands in the evening. So, uh, I watched Dumb Money, which is worth a look. That’s just come out, I think, in the last day or so. Um, the story of, uh, Wall Street Bets and, uh, what’s it? Flaming Kitty, I

[01:19:59] Tony: think, and

[01:19:59] Tony: GameStop.

[01:20:01] Tony: Roaring Kitty, that’s right, and GameStock, and how, uh, how the Flaming Kitty analyzed the GameStock shorts and thought they were wrong and took on Wall Street and that took off and, um, and, you know, how then they had to decide whether they should hang on now they’ve made millions of dollars and when they should sell and, and how the hedge fund shorters, um, still made money in the end out of, uh, out of what went on.

[01:20:24] Tony: So it’s, yeah, it’s worth a look. It’s, um, interesting movie. Hmm. I think it will resonate with quite a few of our listeners. That was good. I watched Eric. Have you heard of Eric? The Netflix series with

[01:20:38] Tony: Cumberbatch starring in

[01:20:39] Tony: it.

[01:20:40] Cameron: seen the thumbnail for it on Netflix, but I know

[01:20:42] Cameron: nothing about it.

[01:20:43] Cameron: I might’ve seen the trailer. What’s it about?

[01:20:45] Tony: it’s, a lot of good things going for it, including the acting, but it’s set back in New York in the 80s and it’s about an abduction of a child who goes missing. Um, and, uh, Cumberbatch is the father, who’s a puppeteer on a puppet show. And, uh, he spirals out of control, um, probably was spiraling out of control, which is why the kid left, but, um, spirals out of control when he disappears, and that’s about the police investigation to find him.

[01:21:16] Tony: Really, really well written. It’s about six episodes, I think. Um, and at the end of every episode, you’re just thinking, Yeah, that’s another clue. That’s, or is it the red herring? And you really get dragged into the story because it all kind of ties together between the police and, and the vice squad and, uh, you know, the people who work in the studio, TV studio.

[01:21:36] Tony: And Cumberbatch’s father is a property developer with links to City Hall. So City Hall’s dragged into it. So it’s like one of those, you know, Um, Life On The Streets, New York, Gritty, Um, Back When Graffiti Was Everywhere, And The Sanitation Wasn’t Being Picked Up, Everyone Was Telling Everyone Else To Fuck Off On The Streets Of New York, So, That Was Really Good.

[01:22:00] Tony: Unfortunately, It Has A Really Bad Hollywood Ending, Which I Just, You Know, That Was Just So Sacchariney, I Just, I Just, If You Had, If I Hadn’t Watched Everything But The Last Episode, I Would Have Raved About This Show, But The Last Episode Really Spoiled It For Me.

[01:22:13] Cameron: Yeah, right. Hmm.

[01:22:16] Cameron: Disappointing.

[01:22:16] Tony: But Otherwise, Good. Yeah, and the last thing I wanted to say was, um, RIP for John Blackman, the comedian,

[01:22:24] Tony: used to be the voiceover artist on Hey Hey It’s Saturday, amongst other

[01:22:27] Tony: things. I hadn’t Don’t know John Blackman? Yeah. I hadn’t heard that he passed away until I saw it in your notes and I

[01:22:33] Cameron: went and looked it up. That’s sad.

[01:22:36] Tony: Very sad. and his whole jaw surgery and everything he’s been through in the last five or six years, I knew

[01:22:42] Cameron: nothing about that too. That’s terrible.

[01:22:45] Tony: mmm, and I guess I just, it just resonated with me, you know, sad to see him pass. He certainly was a part of my life, um, on various TV shows, but, uh, when we first started racing race horses, we had a horse that Jan Russo, my, you know, my, a partner in, in the horse racing business, um, called Blackman after the artist, because he just bought the Charles Blackman painting to hang on his wall.

[01:23:10] Tony: Um, and after his first race, which it won, it was actually, we were told by, uh, the powers that be in the racing industry that we couldn’t call a horse Blackman because people were complaining about, um, calling it Blackman, even though it wasn’t, you It was named after an artist whose name was Blackman. So we had to change its name and we called it, um, the trainer said, let’s just call it Lady Blackman because it was a mare, uh, and that got through and we’re just like, what’s, what’s the difference in calling a horse Blackman versus Lady Blackman?

[01:23:39] Tony: But then, um, John Blackman, um, Uh, entered the media scrum and just said how ridiculous was it, you know, the people were complaining about a horse called Blackman and his name was Blackman and no one complained about that. And, um, and then, um, I found out, I was in the pro shop of my golf club one day and he was there as well.

[01:23:58] Tony: So we had a chat about it and a few laughs. So I got to meet him at one stage, um, and, and talked about that. And he was a really nice guy. Um, so yeah, sad to see he, um, he’s

[01:24:08] Tony: gone. How long ago was that that you

[01:24:11] Cameron: ran into it?

[01:24:12] Tony: Uh, least 10 years, I’d say.

[01:24:14] Cameron: Hmm, Pre Canada, so

[01:24:16] Tony: probably 12, 12 years or so ago.

[01:24:18] Tony: Hmm. Mm

[01:24:19] Cameron: Yeah, I mean, for our generations growing up with Hey Hey It’s Saturday, uh, with John doing all of the character voices and providing the humor and the comedy, um, just like a huge part. Uh, of, of my childhood, you know, absolutely legendary. His voice will always be in my head, you know, doing, doing Dicky Knee and stuff like that, Mm hmm. yeah.

[01:24:48] Cameron: And just, and just his voice introducing

[01:24:51] Cameron: segments and doing little sidelines when Molly was on camera. Like little, uh, jokes about Molly’s sexuality. Um, Like, stuff that you could get away with in the 80s that, uh, would be highly inappropriate being done today. Making fun of somebody’s sexuality, making, uh, you know, snide remarks about his sexuality.

[01:25:20] Cameron: Yeah, um, anyway, R. I. P. John Blackman.

[01:25:24] Cameron: Well, I’ve had a, uh, a busy week. Um, Chrissy and I tried Fallout. Um, we watched the first episode. She, she’s not into it, so I don’t think that’ll go any further. It was a bit

[01:25:35] Cameron: sort of, Ah, okay. bit too sci fi ish for her, I think.

[01:25:39] Cameron: Um, I’ve been re watching Firefly, just as my feel good thing.

[01:25:43] Cameron: I mean, like, one of my all time favorite shows. Don’t know if you’ve ever gotten to that. Did you get into

[01:25:47] Cameron: Firefly?

[01:25:49] Tony: Yeah.

[01:25:50] Cameron: It’s a great rewatch show. The lines, the lines are great. Like, there’s so many great lines in it, and the characters are so much fun. Like, at the end of the first episode, when, um, Mal invites Simon and River to stay on Firefly, and Simon says, How do I know you won’t just kill me in my sleep?

[01:26:09] Cameron: Mal says something like, You don’t know me too well yet, son, so let me tell you something. If I ever kill you, you’ll be awake. You’ll be looking at, you’ll be, you’ll be looking at me, and you’ll have a weapon in your hand.

[01:26:22] Tony: Mm hmm. Just really, really great lines like that. Um, I’ve been reading Riley Ace of Spies, I’ve also been reading Geoffrey Blaney for the first time.

[01:26:32] Tony: Ah. of his books, Short History of the World, which I’ve been reading, and The Causes of War. Which I found out about through another thing I was reading. He did an analysis of, I think, from 1700 through to late 20th century and talked about all the causes of war and breaking it down, so I’m interested to get into that.

[01:26:55] Cameron: But I think it’s the first Geoffrey Blainey book I’ve ever read. I’ve always felt like I should have read Geoffrey Blainey, seeing as I do history for a living,

[01:27:01] Cameron: and he’s Australia’s trying to remember,

[01:27:05] Tony: trying to remember there was, um, who was his competitor? There was, uh, I know, I know as I was growing up there was always two historians, there was Geoffrey Blaney and there was someone else and one was, one was Liberal and one was Labor, and I can’t remember which one was which.

[01:27:21] Cameron: Right. You familiar with the affiliations of

[01:27:25] Tony: Blaney? No,

[01:27:27] Cameron: I’m not.

[01:27:28] Tony: Okay. Because it was like, it was, it was two schools of thought about Australian history and one was always, um, anathema to the

[01:27:35] Tony: other. I’m just trying to remember what Blaney was. Yeah.

[01:27:39] Cameron: Hmm. Tyranny of Distance, obviously, probably being his most famous book, but I have to get my hands on that, too. Causes of War, 1973 was the first edition of that, so it’s probably around about where it is.

[01:27:52] Cameron: Anywho, what else? Well, Apple’s WWDC. was today, last night, uh, in the U. S., Tony, their Worldwide Developer Conference, where they finally announced their, the role of AI in all of their OSs moving forwards, Apple Intelligence, as they’re calling it. And they also are integrating ChatGPT into Siri, for the stuff that Apple Intelligence can’t do, which is, it’s designed to be all of the on device AI, so it, Can read and interact with all of your apps and do stuff for you involving all of the apps on your device, calendar, email, messages, phone, photos, et cetera, et cetera.

[01:28:38] Cameron: Anything else that needs, uh, to go into the greater world, it’ll have ChatGPT integrated into it, they say. And it’ll say, do you want me to, you can ask Siri a question. It’ll say, do you want me to use ChatGPT for this? And you say, yes. And it’ll. Go out and do it, uh, love to know how much money they’re paying OpenAI to have ChatGPT integrated in it.

[01:29:01] Cameron: 1. 5 billion iPhones, um, but this is going to be one of the major turning points for AI, I think, is now people that don’t use ChatGPT all day, like I do, by the time this rolls out, which they say will be later in the year, Um, and it’s, there’s still some question about how much of this AI stuff will be on legacy phones, and how much of it, I think for a lot of the Apple intelligence on device stuff, you’re going to need to have a fairly current phone, a year or two old, that’s running the latest Apple chips, because it’s all being done on the chipset, or an M1 or later Mac. And my iPhone is like an iPhone 13. So it’s probably not going to get a lot of this sort of stuff until I do an upgrade. But, um, Siri calling out to ChatGPT is probably something that it can do, but this’ll, this’ll introduce, uh, hundreds of millions of people to using AI every day that they probably don’t already.

[01:29:59] Cameron: So I think it is going to be a major turning point in the rollout of, uh, AI to the broader marketplace. Uh, so that’s, it’s a big deal.

[01:30:10] Tony: says you.

[01:30:11] Cameron: Ha ha ha ha ha.

[01:30:13] Cameron: Yeah, it’s I’ll believe it when I see it. I could be wrong. I mean, um, I could probably count, I think I’ve probably sworn at Siri more times than I’ve used Siri. It’s like when she butts in and tries to ask me a question. I’ve got absolutely zero use for it, but I’m old school. I’d rather type my question into Google than talk to Siri.

[01:30:36] Tony: I’m not, I’m not holding my breath. It’s going to improve my life at all. The only thing I think it might help with is, um, when I do. Use spreadsheets. I’m sure that ChatGPT or Siri or whatever Apple Intelligence is can say, Hey, you can do this better. So that might be a benefit to me. Um,

[01:30:53] Tony: but that’s about it, I think.

[01:30:55] Tony: I don’t need anything crawling over my calendar telling me

[01:30:57] Tony: how to operate my calendar better or, I mean,

[01:31:01] Tony: yeah. one I’m so, I’m sick and tired of going to a website and having Google ask me if I want to sign in using my Google account. It’s like, fuck off Google. I’ve even delved into the details of my settings of Google to turn that off and it still does it.

[01:31:15] Tony: So it’s

[01:31:16] Tony: like I just don’t need it.

[01:31:18] Tony: It’s just leave me alone. I know what I’m

[01:31:20] Tony: doing. like one of the demos that they did in the keynote was, uh, one of the ladies at Apple had a phone and she said, Hey, when’s, when’s my mother’s flight get in? And it was able to tell her by going through her emails when the flight was going to get in. And she said, what are, what are our lunch plans again?

[01:31:39] Cameron: And it was able to tell her what the lunch plans are by reading through her messages

[01:31:43] Cameron: and, Well, was, was this person seriously retarded? They couldn’t, they couldn’t go

[01:31:48] Tony: to the, the Qantas, you know, website and look up the ETA of

[01:31:52] Tony: the flight? She said, it would have taken me several

[01:31:56] Cameron: minutes to have recovered this information, and it could do it for me immediately,

[01:32:00] Cameron: so, And her time is

[01:32:02] Tony: gold, is it? Well, if you’re doing, if you’re doing that 50 times a day,

[01:32:06] Cameron: Tony, it?

[01:32:06] Cameron: all

[01:32:07] Cameron: adds up.

[01:32:08] Tony: You’ve got 50 mothers flying in on 50 flights.

[01:32:10] Cameron: God, you are such a cynic when it comes to this stuff, it’s astounding. But the bigger,

[01:32:15] Cameron: like, you and I were I’ve just, but I’ve lived through the dot

[01:32:18] Tony: com boom and I’ve looked

[01:32:20] Tony: at product, this.

[01:32:21] Cameron: time

[01:32:21] Cameron: it’s different, Tony. but I’ve decided it’s different.

[01:32:26] Cameron: no, here’s the thing that I think most people don’t get when they’re, when we’re talking about AI, if Sam Altman and Bill Gates and everyone in between are right about what’s coming next with this, the next version of ChatGPT, so called ChatGPT 5, which is supposed to be, Going public later on this year is going to be a massive improvement over ChatGPT 4.

[01:32:58] Cameron: One of the analogies that I saw the CTO of Microsoft use the other day, he said, is ChatGPT 4 has about the equivalent intelligence of a high school senior in most things. ChatGPT 5 is basically a PhD. in everything. Sam Altman has said that it will solve most of the complaints and problems that people have with GPT 4 in terms of its ability not to make stuff up, to back up everything that it says with, um, sources and actual verified data, etc.

[01:33:35] Cameron: But push it out another couple of years. And, you know, again, Sam Altman, people like him are saying they don’t see any end in the runway of being able to significantly increase the intelligence. of the systems in the foreseeable future. Uh, imagine that we have a version of this technology in the next, let’s say, five years, where it is, uh, as smart as the smartest person in every subject that is out there, because it’s consumed all of the data.

[01:34:15] Cameron: Um, you know, a lot of people, we, we sort of call that AGI, Artificial General Intelligence, where it’s smarter than the smartest human on every topic. And, you know, a lot of the people that are working at OpenAI and places like that are saying, they’re sort of forecasting 2027 for AGI at this stage. So we’re three years away, maybe.

[01:34:36] Cameron: Let’s give it another couple of years, let’s say it’s five years. What happens when we have. When we apply that kind of intelligence to scientific problems, the major issues that the world is facing today, not just scientific problems, but all the thinking about the major issues. Like it’s the explosion of intelligence. walking into that we’ve never seen before. What happens to cancer when you have a million new scientists working on curing cancer in the next decade?

[01:35:09] Cameron: And they’re AI scientists running virtual experiments and virtual environments and coming up with the short list of things to, to do. Test in a lab. What happens when you have a million new therapists, a billion new therapists, where every iPhone is a therapist that knows everything about everybody and can help you with your mental health issues during the day?

[01:35:34] Cameron: What happens when we have a million new scientists working on climate change? What happens when we have a million new scientists working on economic inequality? What happens when we have a million new scientists working on geopolitical tensions or peace in the Middle East or whatever it is? This explosion of intelligence that AI is going to enable, that we will be able to apply to all of the major problems facing society.

[01:36:05] Cameron: Uh, and enhancing all of the, the way that we live together, the way that we operate. Millions of new scientists working on business ideas, or business models, or forms of, uh, socio economic cooperation, governance, whatever it is. Um, then Add to that, what happens when your devices are listening to all of your conversations 24 7, uploading them to the cloud, indexing them, analyzing them?

[01:36:40] Cameron: What happens when no one can lie to anyone anymore? because their devices are all recording every conversation. What happens to the legal system? What happens to relationships? What happens to politicians and governments when everything is being recorded and indexed? What happens to society when all of this technology and monitoring hits us in the next few years?

[01:37:06] Cameron: I think the implications are absolutely Extraordinary. And I said to Tony off air and he laughed at me. This is the technological singularity because life as we know it is going to fundamentally change in the next five years and I don’t think any of us even begin to accurately predict what life is going to look like.

[01:37:28] Cameron: What happens when you have millions of new teachers for children that are available on phones and iPads and computers that can have the patience to teach a three year old and the ability to teach a PhD level, uh, student doing their doctorate, that are smarter than any PhD out there on every subject.

[01:37:52] Cameron: They’re smarter on every subject. Yeah, you have a, you know, somebody who’s taking you through your doctorate on something today, they might be an expert on, you know, Endocrinology, but they’re not, they don’t have a PhD in quantum mechanics. Your AI will have a PhD in everything and will be able to be your teacher.

[01:38:09] Cameron: What happens when there’s just millions of teachers available at 20 a month that are experts on every subject? Languages, sciences, the humanities. What does the world look like when there’s millions and millions of these intelligences that are just proliferating on every device?

[01:38:29] Tony: I can’t predict it. I don’t know. What I do know is human nature. There’s no fucking way that politicians are going to let all of their telephone calls and emails, etc. be monitored. They’ll bring in privacy legislations way before that happens. There’s still the institutional imperative, as we’ve written about, in, in, you know, our Psychopath Epidemic book.

[01:38:54] Tony: Um, but it’s still going to apply. AI is not going to change that. AI is going to be a huge productivity tool. Um, and I think some of what you said makes a lot of sense. Like, if you have lots of people scanning cells for cancer and can come up with some patterns that scientists haven’t found before, I think that’s a great thing.

[01:39:13] Tony: Um, but they’re still going to face the bottleneck of then human trials. You know, you still got it. You can’t, you can’t just test something on an AI chip and say it’s going to work. It’s got to then be put into the same sort of human trial process that’s used today. So it’s going to be bottlenecks. So it’s, it’s going to be productive and we’re going to leapfrog in certain areas.

[01:39:33] Tony: Um, but human. Human frailty, human characteristics are still going to be the bottleneck in anything that’s going to change society. And like I said, I don’t want Siri telling me what to do with my calendar or my smartphone, she can fuck off. Um, but it’s going to be very, it’s going to be a very long time before I even need any sort of automation upgrade.

[01:39:59] Tony: In my life in that respect. So yeah, it’d be great if you talk to a teacher and ask them whether having a PhD knowledge in biochemistry is going to make them a better teacher. They’ll say no, they’ll say crowd control is going to make me a better teacher. So just because you’ve got a screen in front of people doesn’t mean they’re not going to, you know, Take it down the corner and sell it for crack in a lot of cases.

[01:40:21] Tony: It’s, there’s the, I think the, I think the flights of fantasy that people get into when they’re predicting the singularity, nor the human element to it all and, and self interest and human nature. And I think a lot of what you say is going to happen, but a lot of what you say is going to be thwarted and won’t happen

[01:40:39] Tony: as well. Like what? Which bits won’t happen? Do you think?

[01:40:42] Tony: I think there’ll be, It’ll be, see AI being a great educator. And people like you and I, who are naturally curious and look things up. Yeah, well, it’ll improve our ability to source. I can still go to Google and find most things that I’m after. Um, I’ll get some productivity improvements. As I said, that it will help my coding.

[01:41:03] Tony: It’ll help my use of Excel. Um, may, it may refine the checklist, may even do investing for me. Um, I don’t think it’s going to do that. Disrupt the stock market. I don’t see that going away because as we just spoke about this, the stocks very rarely trade at what they should trade at because there’s human nature is involved.

[01:41:23] Cameron: I’ll tell you how it’s going to disrupt the stock market. So it’s going to replace jobs. Um, it’s going to replace lots of jobs. Businesses will start to replace employees with AI and then robots, you know, the next 10 years. Goldman Sachs are predicting, uh, just the, an explosion of humanoid robotics replacing manual labor jobs.

[01:41:47] Cameron: But at first it’ll be AI replacing information worker, knowledge worker, creative worker, then management, because you’ll get rid of, you’re going to get rid of swathes of, you know, Knowledge Workers, which means there’s less people to manage, so middle managers jobs are going to go, there’s going to be competition for psychologists, for teachers.

[01:42:08] Cameron: Then you’ve, so the problem we’re going to have is large percentages of the population out of work. They don’t have work, they don’t have money, they don’t have money, they can’t use it to spend stuff. What happens to

[01:42:20] Cameron: the economy when people don’t have an income?

[01:42:23] Tony: see again, I’ve been, we’ve been through this, right? It was like when I first started working in the IT department at Shell, we were putting clerks out of jobs, you know, because they weren’t taking pieces of paper and stamping them and passing them on after checking them. But those people got

[01:42:39] Tony: jobs and there’s the same thing.

[01:42:42] Tony: The same thing will happen with

[01:42:43] Tony: this.

[01:42:43] Cameron: what jobs are people going to get that won’t be taken

[01:42:46] Cameron: by AI? I went through this exercise with ChatGPT over the weekend. I said, it was like, oh, well, people will have to be re skilled. Like, really, what are they, what jobs are they going to be re skilled to

[01:42:57] Tony: So, okay, some examples. So, you’re in court, and, um, are you really going to trust the iPad that they give you for free, that says here’s, you know, here’s how the case is going to go, here’s how the legal precedent sits, or are you going to want to

[01:43:16] Tony: pay a barrister who thinks on their feet to get you off?

[01:43:20] Cameron: I think initially you’re right, you’ll probably have human lawyers representing you in court, but a lot of the paralegal work that gets done to lead up to that point will be done largely by AI, which means all the paralegals are out of jobs.

[01:43:35] Tony: yeah, but if you talk

[01:43:36] Tony: to a para, a lot of paralegals will say my jobs is boring as shit anyway, I wish I didn’t have to

[01:43:40] Tony: do it. So

[01:43:41] Cameron: but what are they going to

[01:43:41] Tony: not necessarily

[01:43:42] Tony: a bad

[01:43:42] Tony: thing. Well, I’ll find something else. I’ll find something

[01:43:46] Cameron: What?

[01:43:47] Tony: Well, teachers,

[01:43:49] Tony: you’re not going to replace, you’re not going to replace all of these human interaction jobs, frontline worker jobs with AI,

[01:43:57] Cameron: Why not? It’s not

[01:43:58] Tony: like I just said, a three year old, first of all, they’re talking about banning access to social media for three year olds and kids under 14.

[01:44:07] Tony: It’s happening in some states in the U S now, it’s going to be hard to, to then say, no, you can have access to it to do your studies. They’re not going to sit still

[01:44:16] Tony: for it. social media, it’s AI. It was a different thing,

[01:44:19] Tony: No, I know. They are different things, but it’s, it’s the same thing. I can’t see, um, well, look at the, look at the experience during COVID, you know, I talked to teachers who were teaching, relatives of mine who were teaching during COVID, and they said, we know the kids were playing games, they weren’t, they weren’t learning, um, that, okay, it was sort of stuck together with, Sticky tape and chewing gum during COVID, but you couldn’t run a society on that basis.

[01:44:47] Tony: No one would learn anything. They’d just slack off. Who’s, who’s checking and making sure? Who’s, who’s disciplining

[01:44:52] Tony: them? AI?

[01:44:54] Cameron: yeah, the AI is, yeah. How? How does AI discipline

[01:44:56] Tony: a

[01:44:57] Cameron: if you think, that the approach to educating children is

[01:44:59] Cameron: disciplining them, I think there’s a fundamental problem with the approach to education.

[01:45:06] Tony: Well, no, but it’s a component of education. I mean, you know, I remember when I went through school, I was interested and curious, but I looked around

[01:45:12] Tony: and the rest of the class was mucking up, and sometimes I

[01:45:14] Tony: was

[01:45:15] Tony: mucking up. Yeah, that’s sort of an teaching takes a lot more

[01:45:18] Tony: than,

[01:45:18] Cameron: though. But then, okay, so teachers don’t teach them. They’re just

[01:45:22] Cameron: disciplinarians is what you’re saying. You need, you need adults forcing, and it’s, it’s an age thing too, right? Kids at a certain age are going to have lower concentration levels. But, and one of the problems. Oh, one of my scripts just kicked in. One of my, one of the problems with, um, uh, teaching these days is the teacher to student ratios that are economically justifiable for schools. So maybe instead of one teacher for every twenty five kids, we will have one teacher for every twenty five kids. Three kids, if teachers, uh, can be more, spend more of their time, I don’t know, monitoring and the AI is doing more of the teaching, but

[01:46:06] Cameron: if you Yeah, I think you’re right. I think it’s, I think AI is you should.

[01:46:10] Tony: okay, so where I’m coming from it is I think AI will get used in teaching, but it’ll be for things like grading exams or teacher admin support, um, which will free up teacher teaching times and will reduce the student to staff ratios, but not perhaps in the way you’re suggesting.

[01:46:25] Tony: So I think it’s, it’s going to be a huge productivity improvement. I don’t think it’s going to be a

[01:46:30] Tony: huge displacement of jobs, um, overall.

[01:46:34] Cameron: It’s going to be a one to

[01:46:36] Tony: into other

[01:46:37] Tony: areas.

[01:46:37] Cameron: one to one teacher to student

[01:46:39] Cameron: engagement relationship. Every kid will have their own AI teacher that understands the kid, understands pedagogy, And understands how to entertain and educate the kid at the same time. And it’s gonna,

[01:46:57] Tony: I think, I think that’s a shame if kids

[01:46:59] Tony: only talk to a screen all day. They’re not going to develop in the way that

[01:47:02] Tony: kids should develop.

[01:47:04] Cameron: they’ll have time

[01:47:05] Cameron: they’ll have time to develop, talk to kids, other kids.

[01:47:10] Cameron: But what if, what if the, what if the avatar on their screen that they’re talking to is a hyper realistic avatar that looks like a human, sounds like a human.

[01:47:20] Tony: the stage where it’s a hologram in class, for sure. And looks like a robot in class, which could potentially come for sure. I think there’s a lot of bridges that have to be crossed before we get there. Not saying it’s not the end game. I’m not drinking the Kool Aid yet that there’s going to be millions of teachers out of work and

[01:47:40] Tony: who then can’t find work in other industries

[01:47:42] Tony: yet. well, the other industries

[01:47:45] Cameron: thing is the challenging bit. Like, I’ve tried to find an industry that won’t be impacted by I was asking GPT, tell me industries that won’t be impacted in the short term by And they’re like, oh, well, like a Chief Executive Officer. Like, oh, really? So Millions of teachers are going to retrain to be chief executive officers or neurosurgeons, like everything is going to be impacted when you have a super intelligence or a highly intelligent, let’s say AI, making its way into the workforce.

[01:48:21] Cameron: And we know, again, We talked about this in the book, businesses, uh, institutions are trying to compete, uh, with each other for survival. One of the ways of doing that is reducing cost or increasing profit. Uh, they’re going to be looking for ways to leverage AI. To do both of those things, which is going to create competitive forces in the marketplace, which will force other businesses and other sorts of institutions to do that as well.

[01:48:49] Cameron: It’s going to be a No. No doubt. effect

[01:48:51] Tony: I, I think it’s gonna be a bit like, um, when it took off. It’s gonna be a productivity tool and God knows we need one in the economy. We have now, we haven’t had productivity gains for a long time, which will be a benefit to, um, to society, which would be good. But like, and sure people will be de displaced into other roles, but I don’t see, I see AI as the tool which checks things and which a, you know, improves admin.

[01:49:16] Tony: Um, maybe improves research, um, legal processes, conveyancing, wills will become automated, more automated than they are now. But I don’t, but someone still has to check it, right? I don’t, I don’t think people are going to trust AI at the

[01:49:31] Tony: start, not for a long

[01:49:32] Tony: time.

[01:49:33] Cameron: No, not for a long time.

[01:49:34] Cameron: within a couple of years. Look, I

[01:49:36] Tony: And you can’t you can’t afford to.

[01:49:38] Cameron: You can’t

[01:49:39] Tony: You can’t afford to let AI fly the plane, right?

[01:49:41] Tony: It’s going to still need a pilot for a long time.

[01:49:45] Cameron: Flying a plane, maybe, um, same with self driving cars for a time, but, you know, for a lot of other things, I think it’ll be a fairly quick process. It’ll be a couple of years until it’s been tested and is determined to be as trustworthy, if not more trustworthy, than a human in the job, and then there’ll be a pretty quick replacement period.

[01:50:14] Tony: I mean, I, I hate to make predictions like this, but I can’t see teachers being replaced for 20 years. It’ll be, there’ll be testing, there’ll be trials, there’ll be processes that, you know, get checked off, but it’ll take a long time.

[01:50:28] Cameron: gotta put money on it?

[01:50:29] Tony: sure.

[01:50:31] Cameron: If, if I had any money, I’d, I’d

[01:50:33] Cameron: put money on

[01:50:34] Tony: Yeah, well, I mean, my argument is that no one can predict the future. So it’s, I’m not going to back, I’m happy to back my predictions with you, but my predictions are worthless as well. Um, actually the only person I reckon who’s been good at it is Kurzweil. So what’s he saying

[01:50:48] Tony: about AI? I haven’t looked into what

[01:50:50] Tony: he says. Oh yeah, he’s, he’s balls to the wall. All, all, it’s changing singularity by 2029, man. Like it’s, Yeah. And Kurzweil is saying what I’m saying. People don’t realize what the implications are of an explosion of intelligence. We, we, we struggle to get our head around what that means, an explosion of intelligence in our society.

[01:51:16] Cameron: We haven’t seen that ever.

[01:51:19] Cameron: Uh, Well, yeah, it’s a great,

[01:51:22] Tony: it’s a great concept, but again, it butts up against human nature. You said before, you know, what would a million climate scientists look like? Well, I think they look like the few thousand we have now. They’ll be ignored largely by the population who are fed bullshit by Rupert Murdoch.

[01:51:37] Tony: So, um,

[01:51:40] Tony: there’s a lot that has to

[01:51:41] Tony: happen. To bring in AI to rule the world. And the climate don’t think humans would ever see that.

[01:51:47] Cameron: The climate scientists will be working on better ways

[01:51:50] Cameron: to extract carbon out of the atmosphere, better ways to create higher efficiencies for green forms of energy production, or for, you know, having

[01:52:00] Cameron: clean carbon, And, and you know what

[01:52:02] Tony: will happen, but it’s always the secondary effects, right? So let’s, let’s, I agree with you that they, you have lots of climate scientists working on ways to extract carbon, then we’ll extract carbon. That’s just, you know, like the, the moon landing, let’s throw a thousand scientists at getting a man to the moon in 10 years and bringing him back again.

[01:52:20] Tony: Safely. That’s. You know, that’s, we’ve seen that before and I hope it does happen with climate action, but you know what’s likely to happen if we extract carbon out of the atmosphere quicker and better than what we do now, more efficient than what we do now? We’ll burn more coal, right? Because that’s the business imperative.

[01:52:36] Tony: It may not actually help the climate.

[01:52:39] Cameron: well, as long as we’re extracting as much as we’re burning, it doesn’t matter.

[01:52:44] Tony: Yeah, as long as we are,

[01:52:46] Cameron: Yeah. but then, but then Rupert Murdoch will hire a million AI

[01:52:49] Tony: climate scientists to deny the fact

[01:52:51] Tony: that we are 97, man. Like,

[01:52:54] Cameron: Rupert’s not going to be around for

[01:52:55] Cameron: this. Whatever.

[01:52:57] Tony: he’s, he’s, he’s stacking up the next wife, he’s, look, he’s got, ha ha, he might marry AI, right? He’s married into

[01:53:03] Tony: the Russian mafia this time, he might marry AI next, ha ha

[01:53:07] Tony: ha, And then, I mean, nanotechnology, breakthroughs in

[01:53:10] Cameron: nanotechnology is the next part of it that I really want to see happen. So then, we take that carbon and we reutilize it in our nanofabricators to build new things out of the carbon, so we don’t have to sequester it. under the ocean or in the ground, we actually start to build stuff with the carbon, along with everything else that we are dismantling.

[01:53:31] Cameron: All of our waste products get dismantled into carbon, oxygen, hydrogen, nitrogen, copper, gold, iron, whatever it is. And

[01:53:40] Cameron: we, we

[01:53:41] Tony: yeah, and they’re, they’re great new industries, and they’re not going to be completely employee less, so that’s where the teachers will

[01:53:47] Tony: go.

[01:53:48] Cameron: No, they will be, it’ll be, AI and

[01:53:51] Cameron: robots.

[01:53:52] Tony: I I don’t see it. There’s got to be some

[01:53:54] Tony: form of human checking and human

[01:53:56] Tony: intervention in

[01:53:56] Cameron: Why? If the AI is smarter than every human, why are you going to have a human check something that’s smarter than it? Doesn’t make sense. Why would you spend money getting a human to check somebody that’s smarter than it? Would you get a university student to check somebody with a PhD’s work? No.

[01:54:15] Tony: um, I wouldn’t.

[01:54:16] Tony: I think all of it needs to be checked. There’s peer review

[01:54:20] Tony: for a start for Well, you have one AI check the other AI. I already

[01:54:24] Cameron: do but if you don’t I get ChatGPT, I get ChatGPT to write code and then I give it to

[01:54:29] Cameron: Claude or Gemini and say, check this code for me. And then I give it back to ChatGPT.

[01:54:35] Cameron: Have,

[01:54:36] Tony: And that’s going to be enough of consequences, is there’s going to be an AI war.

[01:54:40] Tony: You know, which, which one do you believe? So that’s got to happen as well.

[01:54:44] Cameron: that’ll be part of it. There’ll be

[01:54:45] Cameron: propaganda created by one set of AIs. And then other people will be using their AI to, you know, fact check the propaganda. And they’ll say, well, you can’t believe that AI. It’s owned by liberals,

[01:54:59] Cameron: you know. Yeah.

[01:55:01] Tony: Yeah. It’ll be Elon’s AI and

[01:55:03] Cameron: Elon Donald Trump’s AI

[01:55:07] Tony: and Rupert Murdoch’s AI and Jack Dorsey’s AI that will be fighting

[01:55:09] Tony: each other. tweeted today that if Apple integrate ChatGPT into their phones, he’s going to ban iPhones from all of his factories and businesses because it’ll be spying on him and stuff like

[01:55:22] Cameron: that.

[01:55:23] Tony: It will be. That’s part of it. Yeah. Do I really want the AI to spy on me? No.

[01:55:30] Cameron: Hmm. Okay. I think one thing we’ve learned is that people are happy to trade privacy and security for convenience and benefits.

[01:55:41] Tony: Yeah, they’re happy to trade. Yeah, I

[01:55:42] Tony: agree. They’re That’s why we sign,

[01:55:44] Tony: cash.

[01:55:46] Cameron: we sign user agreements with software companies every day without reading them. We don’t we don’t. Yeah, exactly. Yeah. Oh, I agree with you. So, but AI’s got to prove itself to that level of standard, which I

[01:55:57] Tony: think is still, still has to happen. And it won’t be as quick as

[01:56:01] Tony: people think. you know, but no, it’ll be faster than people think.

[01:56:08] Tony: Oh, look, you paint a nice picture and I hope you’re right. It’d be great to cure cancer and, and take carbon out of the atmosphere quickly and all that. But I reckon we all got, all that’s going to happen is that we’re going to get inundated with Elon Musk’s point of view and Rupert Murdoch’s point of view, and, and we’ll be putting carbon into the atmosphere

[01:56:23] Tony: because it sells more coal for the coal companies, if we believe AI.

[01:56:28] Cameron: Well, uh, fortunately this is recorded and it will be indexed and analyzed by AI. And five years from now, I’ll be able to say,

[01:56:35] Cameron: Hey, pull up. When, when was it that Tony told me that he wasn’t going to be

[01:56:39] Cameron: using AI for anything and that teachers wouldn’t be put out of jobs? He was going to pull that Ha ha ha ha ha. Yeah, sure. Yeah, look, you said I was a cynic. I’m probably more sceptical than a cynic. But, I think there’s, No, a lot of change coming.

[01:56:57] Tony: No I can, I can buy into the AI argument, it will improve productivity. But I think there’s a lot of, a lot of water under the bridge before we see the complete control AI, because it’s smarter than us.

[01:57:09] Tony: It won’t happen.

[01:57:11] Tony: It won’t happen.

[01:57:13] Tony: won’t happen. In fact, I can build a case which says that AI won’t be allowed to develop to that level because people will be scared of it being smarter than humanity and

[01:57:25] Tony: taking over. It’ll be kept at a certain level of

[01:57:28] Tony: intelligence. That is an argument that’s already been pushed in the last year or so by guys like Eliezer Yudovsky, who I interviewed. Do you remember my interview with him 20 years ago on G’day World? When I was doing my early Singularity series with Kurtzweil, et cetera, I did Eliezer Yudovsky on. Um, he’s been an AI sort of Thinker for decades.

[01:57:51] Cameron: And he’s been one of the prominent voices about, we need to shut down AI for the last year. He’s like, this is going to kill us all. Um, but the argument, the counter argument against that, it’s okay. Let’s say all of the Western governments decided to put a moratorium on AI. Do you think China’s going to stop developing AI when it offers the massive competitive advantage?

[01:58:11] Cameron: So therefore the advocates against this will say, well, we can’t. Put a moratorium on AI, because we won’t stop China from developing it. We don’t want to be, you know, have a world that’s run by China’s AI, so we have to do it. The forces of capitalism, uh, will push this forwards. It’s very hard to stop it, I think, now.

[01:58:36] Cameron: I can’t see anything. Unless there are unforeseen technological hurdles, or we run out of service space, or we run out of electricity, or some fundamental Infrastructure, floor,

[01:58:52] Cameron: I Yeah, but I think there could

[01:58:54] Tony: be, there could be,

[01:58:55] Tony: just flaws in the model too. We don’t know why AI

[01:58:58] Tony: hallucinates now.

[01:59:00] Cameron: We don’t know why AI works. yeah. This is the thing that most people don’t understand. I have to explain this to people all the time. Even the people who built it.

[01:59:11] Tony: Hmm.

[01:59:11] Tony: Hmm. people who built OpenAI and ChatGPT don’t know how it works or why it works. So I remember an interview with Ilya Sutskever like last year before he got kicked out of the company.

[01:59:26] Cameron: He was like the lead tech dev of ChatGPT. And the interviewer, I think it was Jensen Huang, the CEO of NVIDIA, said, What has surprised you most with this? And he said, What surprised me most is that this works. I had no idea. That this would work, you know, they were like, uh, what happens if we throw a lot of compute at this language model?

[01:59:49] Cameron: Oh my God. It understands language and it develops a world model and it seems to understand things like they hadn’t, they had a hunch that if they threw a lot of compute at this, something interesting might happen, but we don’t know why it works. How does it understand the world? Geoffrey Hinton, who was Ilya’s professor.

[02:00:11] Cameron: and business partner before Ilya went to OpenAI. I watched an interview with Hinton just a couple of weeks ago. He said the same thing. Hinton’s been, he’s the godfather of all of this, of, of transformer models, etc. He’s like, we don’t know how this works. This shouldn’t work. That is the most jaw dropping, mind blowing thing for me, is the people who built it don’t know how it works or why it works.

[02:00:40] Tony: Well, we don’t know

[02:00:41] Tony: how our intelligence works or how our consciousness

[02:00:44] Tony: works.

[02:00:44] Cameron: Yeah, but we didn’t build It

[02:00:45] Cameron: It built itself.

[02:00:48] Tony: Yeah.

[02:00:49] Cameron: They built this and they don’t know how it works. Like, you think about the implications of that.

[02:00:55] Cameron: We have built this thing that could become a superintelligence and we don’t know how it works or why. People are like, oh, but it’s not perfect and it has hallucinations.

[02:01:04] Cameron: Like, yeah, no, no, you’re missing the point. We don’t know how it works! Like it’s, um, you know, we, I was explaining this to Chrissy the other day, like for the last 50 years, AI research has mostly been around. Well, the way that humans developed is we had some sort of, um, world model that was pre language.

[02:01:29] Cameron: You hold up a banana. This is something I can eat, but you didn’t have words for it. And then words, Came secondary to the model and symbolic logic came secondary. And then they built a new meta layer of understanding and constructs and concepts came out of language, but we had this world model first. So the thinking was, okay, you have to build a world model inside of an AI first, and then you give it language to articulate the world model.

[02:01:53] Cameron: But LLM does. It just gives it words,

[02:01:56] Cameron: words Well, it predicts, doesn’t it? Doesn’t it predict what the next word is based

[02:02:00] Tony: on the context of what’s had, it’s already

[02:02:03] Tony: passed? Yeah, I mean that’s a highly simplistic version of what it does, yeah, but that’s how it started, and it kind of does that at a token level, but it also has somehow, in order to do that effectively has had to build a world model. In order to predict the next word it has to understand the world,

[02:02:28] Cameron: or else it can’t predict the next word effectively.

[02:02:31] Cameron: Like, you can go type a, you know, a semantic problem into ChatGPT, which has never been asked before, doesn’t exist in any of the training material. How does it predict? How does it construct a coherent and articulate response to your

[02:02:46] Tony: right.

[02:02:47] Cameron: It has to have developed a way I was saying this about programming, like a year ago, when people were going, oh, it’s just a, it’s a skitastic parrot.

[02:02:56] Cameron: Um, like, well, hold on a second. Statastic Parrot. I was like, I’m asking it programming questions or, you know, write a formula for this in Excel. No one has ever, in the history of the world, asked it this particular question for a formula for a QAV spreadsheet thing, and yet it’s giving me the answer. It’s not just pulling this out of its database or knowing what word to place next because that’s how it’s seen done before.

[02:03:28] Cameron: It has to understand conceptually what the question is and it has to understand Excel and it has to understand, you know, the stock market and it has to understand all these bits and pieces in order to articulate the formula that it then gives me. How does it do that? No one knows,

[02:03:49] Tony: Yeah.

[02:03:51] Tony: That’s crazy, isn’t it?

[02:03:54] Cameron: I’ve Yeah, which, and that may, that may be the limitation on AI, but it, it works to a point, it can do like fix my formula in Excel, but maybe it can’t solve climate change or it can’t cure

[02:04:06] Tony: cancer. Maybe.

[02:04:10] Cameron: maybe, but why not, I mean, the way that humans do it is we read the language and we understand the language and then we solve the problems based on what the language and the reports and the studies and the textbooks say, right? If it understands language it should be able to understand anything a human can understand.

[02:04:26] Tony: So, um, probably not articulating what I’m trying to say. There’s a lot of serendipity in science. You know, think about Alexander Fleming and the Petri dish of mould that was left on this, you know, left on the sill of the window when he went away for the weekend. Um, if he hadn’t done that, you could throw any, any amount of, Computing grunt at the, you know, the solution for

[02:04:51] Tony: bacteria, and you may not solve it.

[02:04:53] Tony: So,

[02:04:55] Tony: there’s, is you can run

[02:04:57] Cameron: billions and billions of virtual models. This is what Kurzweil was saying last year about COVID. You know, he said, like, we developed the, you know, Marina developed the MRNA COVID vaccine quickly. Uh, Modena, not

[02:05:15] Cameron: Marina. Modena, yeah,

[02:05:17] Cameron: Marina is, uh, Moderna. Marina’s the thing that women get in their arms to stop them getting pregnant.

[02:05:24] Cameron: Um, Moderna developed the mRNA vaccine

[02:05:27] Tony: used to be a great of marine oil when I was working at Shell too, Marina,

[02:05:32] Tony: uh quickly, but

[02:05:36] Cameron: we still had to do human trials. He said what we should have done and what we will do in the future is just run a billion virtual human trials and then say, okay, here is the, you know, here is the results of a billion virtual trials. Trials that have been done and you can run those in a day.

[02:05:57] Cameron: And it spits out the results. You know,

[02:06:00] Cameron: if you’re trying to and that’s great if, if the FDA, you know, gets enough, um, enough evidence to say that that’s an

[02:06:08] Tony: acceptable replacement for human trials, and, yeah, that is progress, that, that would be great.

[02:06:13] Cameron: and, you know, they’ll, they’ll do a couple of things, I’m sure we will run a billion virtual trials and then we’ll get the short list of things to try and human trials and they do it. And if it works, you do that enough times and you go, okay, well, let’s skip the eight months of human trials. Now, like we’re confident that the model works.

[02:06:31] Cameron: Same as, Self driving cars, right? We just keep running it and keep running it and keep running it until it’s more effective than human until it

[02:06:42] Cameron: Well,

[02:06:42] Cameron: human drivers kill Yeah, look, I am skeptical about you, about self, about driverless cars. I’ve, I’ve, again, I’ve heard

[02:06:49] Tony: that it’s coming in 18 months for the last 10 years. So,

[02:06:53] Cameron: Yeah, but we didn’t have AI for the

[02:06:55] Cameron: last 10 years. It may happen.

[02:06:58] Tony: but it’s still coming.

[02:06:59] Tony: So Yeah, but we didn’t have AI for the

[02:07:01] Cameron: last 10 years. AI changes everything. This time it’s different,

[02:07:05] Cameron: Tony. ha

[02:07:05] Cameron: ha ha Well, that’s, that’s the red flag for me.

[02:07:11] Cameron: ha!

[02:07:13] Cameron: I know.

[02:07:14] Tony: Because we know it probably isn’t.

[02:07:16] Cameron: Alright, that’s the show. Thanks,

[02:07:18] Cameron: Tony. a good conversation. Thank you.

 

 

 

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