We talk about the LUI ( Linguistic User Interface), Steve’s 3D printed house, using ChatGPT to automate your day with AppleScript, updates on LK99, Cold Fusion and Worldcoin, Robot Taxis, Amara’s Law, De-Globalisation and ask the question – is stealing things the best business plan of all time?
FULL TRANSCRIPT
FUT10
[00:00:00] Cameron: Welcome back To the Futuristic Podcast. This is episode 10. My name is Cameron Reilly. With me as always, my mate down in Melbourne, Steve Sammartino. How are you, Mr. Sammartino?
[00:00:18] Steve: morning, Cam. I’m wonderful. I’m glad we’re back. We need to be more frequent. If you can hear some noises in the background, it’s it’s a pest removal guy who’s just decided to be super noisy right
[00:00:32] Steve: at
[00:00:32] Cameron: that’s, that’s real life, real life podcasting. We didn’t do one last week because I didn’t actually have much to talk about last week, but there’s a few things to talk about in the world of emerging technologies this week. Some good, some bad, let’s get into it. I’m going to talk about some of the highlights of my week.
[00:00:52] Cameron: Steve, I’ve been using GPT to write more scripting. Steve, AppleScript. Now, you know, I’m a Mac [00:01:00] guy for years I’ve, I’ve wanted to do more to automate repetitive processes on my Mac. There’s a tool called Keyboard Maestro. Do you, do you ever use that, Keyboard Maestro?
[00:01:11] Steve: No,
[00:01:12] Steve: I don’t. You better tell me what it is real quick.
[00:01:13] Cameron: It’s a, it’s been around a long
[00:01:15] Cameron: time, it’s a great… Mac app that enables you to automate a whole bunch of different things on your app. And it has the ability to use AppleScript. It can run AppleScripts and, you know automate different processes. But the problem is I don’t know how to write AppleScript. And over the last 10 or 15 years, I’ve gone through periods where I’ve tried to learn how to write script and, you know, I just spent hours and hours trying to figure it out and it never works and you Google stuff and you try and…
[00:01:46] Cameron: Anyways. Now, I just I had this idea the other day, I have, you know, in my investing podcast, I have a bunch of portfolios that I run, we’ve got about a hundred stocks in those portfolios, and I needed to monitor [00:02:00] those in case one of them becomes a sell, breaches one of our sell triggers, and the way that I normally do that is I have a spreadsheet that tracks it all, and I have to Remember to open it and look at it several times during the day.
[00:02:11] Cameron: I had this idea. I wonder if I could write a script that’ll just pop up a box and tell me if I need to sell anything. Jumped into GPT, said, could you help me do this? Absolutely. Wrote me an Apple script that I put into Keyboard Maestro, told me everything I needed to do. And now, Keyboard Maestro just opens that spreadsheet in the background every couple of hours during the day.
[00:02:34] Cameron: And then if there’s anything, it checks a couple of columns. If anything has changed in those columns, it pops up a little box on my computer and says, Hey, you need to action this. You need to sell that. Like, for me, fantastic. It’s just one less thing I have to worry about checking during the day. You know, a lot of, a lot of, I think stress during the day is when you’re trying to keep stuff in your head that you have to remember to do and my to do list is big enough as it [00:03:00] is.
[00:03:00] Cameron: This just pops up and tells me if something needs actioning and it’s all because GPT now enables me to be a coder. Yeah, I can write scripts, I can write code now that I could never do before. So that was that was a big thing for me this week. On the downside, I’ve been using this AI tool, Descript, to edit my podcast for the last couple of weeks.
[00:03:24] Cameron: And the way that it does it, it does a transcription of the podcast, and it does a pretty good job. And then instead of auditing the WAV files, I may have talked to you about this in other episodes, you just audit the text. So you edit the text, you delete a word in the text, and it’ll delete it in the sound file.
[00:03:40] Cameron: Or you can grab a block of text and move it around. I can even write text. You know, and then say, Oh, Steve would have said this and it will replace that with your voice. It’ll listen to your voice and it’ll, it’ll create basically it’ll code your voice. It knows what you sound like and it can [00:04:00] replicate your voice anyway.
[00:04:02] Cameron: But the transcript, because the way that we talk and in the other shows that I do, it’s, it’s, you know, we. We, we talk in half sentences and we and we are, and we, you know, it’s a bit loose and that kind of stuff. That’s what the transcription looks like. So I had this idea, what if I threw the transcriptions into…
[00:04:22] Cameron: GPT and said to it, just clean this up, you know, clean it up so it reads better than it does currently. Thinking that would be pretty easy for an LLM to do.
[00:04:33] Steve: because you’re reading it, me interrupting you just then, that doesn’t read the same way that it sounds. And so you clean that up, but the red version should be slightly differentiated to the verbal one, because
[00:04:46] Steve: they’re different syntaxes,
[00:04:47] Steve: different types of
[00:04:48] Steve: communication.
[00:04:49] Cameron: Yeah. And, and it, you know, the transcription doesn’t need to be, and in fact, I would argue shouldn’t be an exact replication of the audio experience. And so I said, clean [00:05:00]it up, take out any. Ums and Ahs or any repeated words or half sentences and excellent could not get GPT to do a good job of that, tried Bard, tried Claude, tried a number of different LLM apps, none of them could do a good job on it, they just kept failing, falling over, something that I would have thought was a really easy job for an LLM to do.
[00:05:25] Cameron: completely
[00:05:26] Cameron: butchered it. Would either edit it too much or would move stuff around. I couldn’t get it to follow my instructions. Tried a whole bunch of different prompts and lots of detail. Couldn’t get it to work. The other major fail I had is I’m trying to do my RG146 at the moment, my financial services license for the investing podcast.
[00:05:43] Cameron: A lot of documentation, there are hundreds and hundreds of. Pages of PDFs of stuff that I need to know. Again, threw it into GPT and said, can you summarize this document for me? Give me, pull out the key topics, bullet point it for me. Again, something I would have thought [00:06:00] is just really easy for an LLM to do.
[00:06:03] Cameron: Could not do it. GPT couldn’t do it. Barred. Again, Claude too, none of the major LLMs seem to be able to deal with summarising PDFs. They would summarise the first couple of pages or summarise a 50 page PDF down to like 10 bullet points. I’m going, no, no, no, that’s not what I want. I want all of the detail.
[00:06:27] Cameron: Just take out all of the unnecessary verbiage and give me the, the real key points. I get the feeling that GPT could have done that six months ago. but it’s been dumbed down for reasons we don’t quite understand over the last few months. And now I can’t even do what you would have thought was sort of LLM 101.
[00:06:49] Cameron: Anyway. So that’s my highlights of my lowlights for the last week. Steve, what about you?
[00:06:55] Steve: Oh, just one I’ll add that I didn’t have in there, but I’ve been using some [00:07:00]video editing tools where you just upload an entire video and what it’ll do is it’ll find that have the best hooks that you can use for social media edits. So Uh, one’s called Runway another one is called Opus Clips, and you can upload up to 60 minutes of video or 30 minutes of video for free, and it’ll go, here’s what we think is a great soundbite, and it even weaves together different paths to create what would be a nice clip to put on a TikTok or a social.
[00:07:32] Steve: So pretty, pretty interesting tools and, and, I don’t know how it does it. I wonder if it’s the inflection in the voice tells you that it might be an insight because I don’t think it’s analyzing the language to find what the great insights are. I think it’s the intonation in the voices because you can see that when you get it forward.
[00:07:50] Steve: But instead of you trolling through and us looking through what we’re doing here and going, Oh, that’s a little good bit where we had some, a good little dialogue that is interesting for social. And given that short form [00:08:00] video is so important, I thought those two tools are really, really,
[00:08:03] Steve: interesting. So, that’s another
[00:08:06] Cameron: what video are you running them over,
[00:08:08] Cameron: Steve?
[00:08:10] Steve: So you upload a video,
[00:08:11] Cameron: Yeah. But what,
[00:08:12] Steve: my video.
[00:08:13] Cameron: you know, what, what video are you uploading? Is it stuff where you’re cause I’ve seen videos of you on TikTok when you’re on other podcasts and you’re.
[00:08:21] Steve: On other podcasts, those, those types of things. So if I’m on a podcast I’ve got a couple of keynotes. I just got videos of doing keynotes and keynotes are really hard to find interesting bits because they’re long story arcs, they’re longitudinal things. And it’s not easy to get a good bit on a keynote for a, for a short form video that don’t come that well.
[00:08:40] Steve: Podcasts come across well.
[00:08:41] Steve: because you’re in that phase and it suits social better. So that’s, that’s what I’m uploading like little videos
[00:08:47] Steve: of podcasts
[00:08:48] Steve: and
[00:08:50] Cameron: So you’ll upload like the full half hour or the full hour of the
[00:08:53] Cameron: video and it will pick up
[00:08:55] Steve: pick up,
[00:08:56] Steve: you know, a handful of pieces.
[00:08:57] Cameron: I’ll have to try
[00:08:58] Steve: they’re really cool tools. Yeah, they’re good.
[00:08:59] Steve: I’ll [00:09:00] send you a link to them. The other one is I’ve been working with a major car company one of The biggest in the world. And one of the that it reminded, we’re working on EV charger strategy. And one of the things that for me is really interesting is that we always assume big companies are further advanced than they are.
[00:09:16] Steve: Often, and this is a great message for anyone involved in startups or businesses. You say, you know what company X should do? They should do this and that. And you think, Oh, I’m sure they’ve done it. Don’t be so sure.
[00:09:28] Steve: Don’t be so sure. The number of large companies always say, have you done this part, which is you’re implementing this technology here.
[00:09:35] Steve: What you need is this thing over here, electric vehicles. You’re starting to sell those. You really need 3000 charges. We know Tesla’s got it, but you need these. They just don’t have it. They just, and this is the classic example of big companies serve their infrastructure. If they need a new infrastructure, very rarely have they done what is required.
[00:09:55] Steve: So that was a really strong insight. Don’t assume the big company’s done it. Knock on their door. [00:10:00] You might surprise yourself. And the other one is, I just finished 3D printing my first house in Blanchetown. So that’s really cool. I mean, we printed a house. This is a startup, which didn’t exist in January.
[00:10:12] Steve: In that time, we built a robot, self funded, got a customer and printed a house. That’s, you know, half a year. That shows you how quick you can do something and we’re talking about a physical startup with robotics, material science, deals uh, going to build a house on site,
[00:10:29] Cameron: And how big is the house?
[00:10:31] Steve: date work. The house is about five meters square.
[00:10:33] Steve: It’s not really a house. It’s being, it’s a building which is being used as a gym
[00:10:38] Cameron: Right,
[00:10:39] Steve: at a, at a at a chicken farm.
[00:10:42] Cameron: a,
[00:10:42] Cameron: gym at a chicken
[00:10:43] Cameron: farm.
[00:10:44] Steve: Yes, it’s a gym at a chicken farm. Look, I don’t think there’s enough of
[00:10:47] Steve: that in modern
[00:10:48] Steve: society. They, they do all the, the, the,
[00:10:50] Cameron: There’s a
[00:10:51] Steve: for for Steggles and KFC, believe it or
[00:10:54] Cameron: That reminds me, in the original Rocky film, there’s a scene where part of his [00:11:00] training is he has to run around and try and catch chickens. It’s part of his like, cardio exercise. Is that what they’re doing there? Are they just
[00:11:07] Steve: Yeah. Yeah. Well, that’s what I was doing. I was chasing chickens
[00:11:10] Steve: with a Robot
[00:11:11] Steve: Robot
[00:11:12] Steve: robot, chicken. That was a
[00:11:13] Cameron: chicken, yeah.
[00:11:15] Steve: Robot chicken. Jeez. I’ll tell you what we’ve circled back. Here, here’s what’s crazy. no one wants to know us. When it comes to investing, we had so many meetings with the government who talk a big game on low cost housing and help
[00:11:28] Steve: everyone.
[00:11:28] Steve: Here we are, part of
[00:11:29] Steve: the solution. Yeah, how hard
[00:11:31] Cameron: I read, I read a story in the ABC in the last like week or so about how the Victorian government has like the largest or one of the largest venture capital operations in Australia that no one’s heard of, but they’ve got this massive amount of money that they’re investing in tech startups.
[00:11:49] Steve: You better give me a link. We actually pitched to one of the government’s companies on advanced manufacturing, and they said, no, you don’t fit into advanced manufacturing. Well, if manufacturing a house with a robot is not manufacturing, [00:12:00] I don’t know what it is. And here’s the getup. Our first robot we bought secondhand from the closed down Holden factory and reconfigured.
[00:12:09] Cameron: Wow.
[00:12:11] Steve: So if that’s not manufacturing, I don’t know what is. If you’re listening from the government or you know anyone, hit us up because you know what I’m sick of? Talk. And they said, Oh, we’ll provide some services to you and some people. Look, if we needed help intellectually, we wouldn’t have built the robot and
[00:12:25] Steve: printed the house.
[00:12:26] Steve: We need fucking money.
[00:12:28] Cameron: Do you watch, do you watch Rob Sitch’s show, Utopia?
[00:12:32] Steve: Oh, that’s, I can’t because it just, it upsets me too much. It grates on my soul. I
[00:12:40] Steve: find it unwatchable.
[00:12:41] Cameron: I’ve heard Rob Sitch in interviews say that they get people come up to them all the time, coming out of government saying you have no idea how close this is to the truth. Yeah, just the, the bureaucracy
[00:12:53] Steve: not, it’s not a, I mean, mockumentaries are one of the great things in society and comedy. You and I have discussed [00:13:00] this. You want to watch the news, watch a comedian. I’ve always said that. But mock, that’s not a
[00:13:04] Steve: mockumentary. That is
[00:13:05] Steve: a full documentary. I swear to God.
[00:13:07] Cameron: And the sad thing is, you know, I was a big fan of Frontline when it first came out in the
[00:13:12] Steve: it’s genius.
[00:13:13] Cameron: 80s, early, late 80s, early 90s, I think.
[00:13:16] Steve: Yeah. nineties.
[00:13:18] Cameron: it, at the time, it seemed almost a little bit ridiculous. Looking back on it now, re watching it now, it was prophetic because
[00:13:26] Steve: Oh, it was.
[00:13:27] Cameron: like the entire news industry watched that and said, oh, okay, this is what we need to do and just adopted the Frontline model of
[00:13:35] Steve: it’s got worse since then. I mean, you know, the thing that you think is news and, and the fact that current affair, you know, chases some poor guy who. I shouldn’t say poor guy. Yeah, chases a dodgy mechanic. Like, seriously, no one goes after the big beast. It’s
[00:13:49] Steve: soft and easy
[00:13:50] Steve: targets,
[00:13:51] Cameron: Yeah. Alright, well thanks for those stories, Steve. That’s pretty cool, printing a house. Let’s talk about some news stories that have [00:14:00] happened recently. This isn’t a news story as such, but something that had a big impact on me this week. Do you know who Stephen Wolfram is?
[00:14:11] Steve: I do. I do.
[00:14:12] Steve: Wolfram Alpha fame.
[00:14:14] Cameron: Wolfram Alpha, he wrote a
[00:14:15] Cameron: book about 20 years ago called A New Kind of Science. which didn’t have a big impact in the scientific community, but had a big impact on me. I bought it, read the whole thing cover to cover basically where he was suggesting that we need to move away from mathematics as the foundation of all of our sciences and move towards computation.
[00:14:35] Cameron: And he was arguing that the, the basis of the entire universe he thinks is something akin to computer code and everything runs on a version of cellular automata. Anyway, he’s a very, very smart cookie and he gave a talk at MIT’s Department of Physics, I think about two weeks ago, about LLMs. Now part of WolframAlpha for, I think, 10 years has [00:15:00] been what they call Wolfram Language.
[00:15:02] Cameron: So for people who aren’t familiar with WolframAlpha, Alpha. It’s basically now it’s an online science slash mathematics slash world history, geography, fact based engine, has all of this hard scientific data in it. And you can, you can, I mean, it’s been available as an app on the iPhone forever, and you can get through it through a web, get to it through a web interface.
[00:15:28] Cameron: It enables you to interrogate it for hard scientific data, you can, it’ll solve math problems, it’ll answer scientific questions, etc, etc. Graphing, visualization of, of complicated mathematical functions and that kind of stuff. And they have built their own natural language interface into it. They call Wolfram language.
[00:15:51] Cameron: They’ve had that for, as I said, about 10 years, does a pretty good job. So you can ask it a question in plain English and it’ll figure out what you’re asking and [00:16:00] we’ll come up with the answers. And when it first came out 10 years ago, That was pretty revolutionary as a natural language interface. So obviously he’s got a big interest in LLMs and he’s written some really great white papers and done some really good videos over the last six months about LLMs.
[00:16:17] Cameron: He gave this talk at MIT recently talking about LLMs and what’s happening with them and why they’re important. Now you remember on it, one of, I think on our last episode. I said to you that I think the general public, and even people in like nerdy subreddits talking about LLMs and
[00:16:36] Steve: Same.
[00:16:36] Cameron: Yeah, like the nerdy
[00:16:38] Cameron: ones I follow, kind of have got LLMs wrong, when people are talking about AI, AGI, they seem to think that LLMs are going to be the AI, everything is going to happen inside of an LLM of some sort, and I made the argument on our show a few weeks ago that I don’t think that’s how it’s going [00:17:00] to play out.
[00:17:01] Cameron: And I was using chess engines as the, as the sort of example back then, like, we already have chess engines. You don’t need to teach an LLM how to play chess, it just needs to be able to talk to the chess engine. Well, he was saying something similar about Wolfram Alpha. You don’t need to teach and LLM to do everything that WolframAlpha can do.
[00:17:23] Cameron: It just needs to be able to interface with WolframAlpha and get the information out of it. But there’s a couple of things I wanted to just pull out of his talk. The first thing is, he had this great term. He referred to LLMs as a linguistic user interface. He said, we’ve had a graphical user interface for decades and that revolutionized computing, you know, for the, for the people too young to remember worlds before graphical unit interfaces.
[00:17:53] Cameron: When I, when I was in high school and we were learning about computers in the early 80s, you had to [00:18:00] type in some sort of understandable computer code. into the computer, into a green phosphorus screen, you would type in what you wanted to do, and it would then hopefully go do it.
[00:18:14] Steve: need to press print to make it. happen,
[00:18:16] Cameron: exactly, and this is before,
[00:18:18] Steve: which I love because no one’s
[00:18:19] Steve: printing anything. But
[00:18:20] Steve: anyway.
[00:18:20] Cameron: this is before the Mac, this is before Windows.
[00:18:24] Cameron: Graphical user interfaces revolutionized computing. He’s saying the linguistic user interface is the, the next level. And I thought, oh wow, that’s, that’s perfect terminology for what I was trying to say a couple of weeks ago. So now he… You can talk to the
[00:18:40] Cameron: computer, tell it what you want, it can understand what you’re saying, it can then go out and interrogate expert systems, which will also probably have a linguistic user interface on their front end.
[00:18:53] Cameron: So your linguistic user interface is talking to that, it’ll reply back in a way that yours can understand, [00:19:00] your LUI. And it’ll then communicate the
[00:19:03] Steve: Tell you why.
[00:19:03] Cameron: back to you. Yeah. So we’re moving from a GUI to an LUI. And I thought that was a really terrific way of
[00:19:11] Steve: synopsis of
[00:19:11] Steve: where we are. That’s beautiful, man.
[00:19:13] Cameron: The other key point that he made towards the end of the talk, which I thought was fantastic.
[00:19:17] Cameron: He was talking about the fact that we don’t understand how LLMs work. We’ve mentioned this before, Sam Altman and Ilya, his chief technology officer, have said this. And he, and, and, and Wolfram said it as well. And he said, this is the quote, the fact that LLMs. can extrapolate meaningful sentences that don’t already exist, is a non trivial scientific result, and suggests neural networks are closely modeling how human brains work.
[00:19:47] Cameron: They have worked out the syllogistic logic of language. And, you know, he was saying, look, if you, if you type into an LLM, the cat sat on the, and ask it to finish it, It’s [00:20:00]not hard to figure out how it’s coming up with Matt, right? It’s out there in millions of books and websites, etc. But if you ask it to answer a scientific question or a mathematical question where the sentence…
[00:20:15] Cameron: doesn’t already exist. The, the answer isn’t already out there. It has to figure out what the correct answer is. As he points out, that’s a non trivial result. The fact that a computer can work out the right answer to these questions. And, you know, we know they don’t do it perfectly. all of the time. But the fact that they can do it all at all, he says, is a non trivial, non trivial scientific result.
[00:20:40] Cameron: And his point was, we need to understand how these things work, and we need to invest a lot of time and effort into understanding how they work. And his prediction is that when we do understand how they work, why they work. It will do a couple of things. Number one, it’ll revolutionize our [00:21:00] understanding of the brain and how the brain works.
[00:21:03] Cameron: But secondly, he said, I think we’ll find that we don’t need to train them on such enormous data sets. We’re probably over engineering these things. His guess is that the data sets that they need to be trained on to do what they do is probably far smaller, far simpler than what we’re currently doing with them.
[00:21:26] Cameron: And, you know, the result of that is something else that we’ve talked about on the show. You know, we will all have LLMs running quickly and efficiently on our personal devices. You won’t, they won’t need to be interrogating this massive data center the size of a country that’s, that’s taking the power of an entire country.
[00:21:47] Cameron: Just to, Because we’re not going to be building them to be the font of all knowledge. We’re just building them to understand language. And then they can go and interrogate all of the [00:22:00] expert systems that are out in the cloud. So we’ll be able to run them more efficiently. We’ll be able to run more of them in low power devices, local devices, and all that kind of stuff.
[00:22:09] Cameron: So it’s a
[00:22:09] Steve: I heard, I heard a,
[00:22:11] Cameron: good, good
[00:22:11] Steve: heard a really good. Yeah. I’ll watch that. I heard a really good insight. There was an interview with a guy called Mo Gawdat, who was used to work at Google AI One of the ones who’s super concerned, really smart, but he said it’s, it’s non trivial, the intelligence that it’s got.
[00:22:27] Steve: He said that the intelligence of an owl of chat GPT four is about 155 IQ, but it knows. Which is a bit of a misnomer, because it knows more than any human, and it is general in nature. But he said one of the things you can do is you can ask it to provide you with a sentence which is ironic. That has never been said before and it’ll do it and then you can do a reverse search and you won’t find a Google link to it.
[00:22:54] Steve: And it comes up with the ideas that have never been come up with before. So it doesn’t just regurgitate what’s [00:23:00] out there. It can actually come up with intellectual proses and ideas which have never been thought of. And that’s a beautiful way to do it. Like to ask ChatGPT X, Y, Z that has never been written or no one has ever said before.
[00:23:14] Steve: or a phrase or an idea or, you know, a maxim or a philosophical thought and it can do it.
[00:23:21] Steve: That’s, I would say, non trivial as well.
[00:23:24] Cameron: Yeah, it’s calling bullshit on this, this idea of it being a stochastic parrot. It’s not just parroting stuff back
[00:23:32] Steve: It does do that a lot, as humans do, as humans do. We do that a lot too, right?
[00:23:38] Steve: But we have
[00:23:39] Steve: original ideas as well.
[00:23:40] Cameron: Yeah. But our original ideas are formed by. words and ideas that exist in our database,
[00:23:47] Steve: the database? Exactly. It’s the same thing. I think
[00:23:49] Steve: it’s really similar. All
[00:23:51] Steve: right. Onto the next, Cam.
[00:23:53] Cameron: Well do you want me to do my next one or do you have something you want to do?
[00:23:57] Cameron: Or that looks like all the news stories are mine. Oh no, you’ve got one down [00:24:00] there. Yeah. Do that
[00:24:00] Cameron: one.
[00:24:01] Steve: one. down
[00:24:01] Cameron: So it’s not just me talking all
[00:24:02] Cameron: the time.
[00:24:03] Steve: Nah, it’s not just you all the time, Cameron. It’s Steve Sammartino. Glasses on. Intellectual moment. Well, I think that robo taxis are finally here. I’ve had a friend who is San Francisco sending me a heap of videos of robo taxis that are on the road.
[00:24:23] Steve: Three cities in the U. S. have many now, so San Francisco, Austin, and Phoenix. You’ve got three companies doing it, Waymo, which is Google or Alphabet, Cruise, which is General Motors, and Zoox, which is a startup. No Uber in the game. there’s been some really interesting hacks which have been happening.
[00:24:45] Steve: I love it when artists hack technology. One of my favorite ones ever was when an artist got a little trolley filled with old phones and put Google Maps in them to cause fake traffic jams. [00:25:00] Which I just love that idea, right? That’s really interesting. And so there’s been some artists going around creating patterns for the Waymos where they’re putting witches hats in the middle of roads.
[00:25:11] Steve: Now the normal human driver will drive around it and continue on their merry way. Not the Waymo driver goes around backs, reverses, and they’ve been hacking them on where they go. So I thought that was kind of interesting. Another one which has popped up is, Cam, have you heard of the new Mile High
[00:25:28] Steve: Club?
[00:25:29] Cameron: No, I haven’t even been able to join the original Mile High Club yet.
[00:25:33] Steve: Yeah, I’m not a member of the original Mile High Club either. I imagine it’s easier on a private jet, but private being the key word. I’m no member of the Mile High Club, but now, the latest thing is you’ve gotta get the job done.
[00:25:46] Steve: in a taxi without a driver because you know there’s no taxi driver that could get upset so that’s been a big thing that people have been social posting on and doing and it’s
[00:25:54] Steve: a again
[00:25:55] Steve: an unexpected externality
[00:25:57] Cameron: know, I think it’s totally
[00:25:58] Cameron: expected. But of course, [00:26:00] everything inside of these robot taxis is being videoed and
[00:26:03] Cameron: live streamed somewhere. So, you know, the companies behind them are watching all of your sex tapes. I mean, if you’re happy with that, if you don’t have a problem with that, that’s fine.
[00:26:11] Steve: it’s fine but it’s pretty funny isn’t it I mean And then you’ve got this whole new mobile only fans kind of thing happening. But I just, I just found that was interesting. Also in Australia, we had auto trucks had a successful trial on Transurban, which is the city link in Melbourne. And I think that what we’ve got here is that, you know, after 10 years of promises and we all got seduced by the idea that autonomous vehicles will be here yesterday because of all the stats and the numbers, but it does feel like they’re finally arriving in no doubt, like cities.
[00:26:44] Steve: Certain areas, and I think we’ll see between interstate highways where the risks are low with trucks real soon. I feel like that has happened, and when we go into the the last [00:27:00] I want to go deep into the technology time warp where I give something on that. So that was for me an interesting one that the robo
[00:27:06] Steve: taxis have arrived.
[00:27:08] Cameron: It’s sort of something to do with Rule 34, isn’t it? Like Rule 34 on the internet is there is porn of it, no exceptions. I think sort
[00:27:18] Steve: yeah.
[00:27:18] Steve: is it called Rule 34? Yeah. Well, in fact, doesn’t it almost happen first there? A lot of the leading edge technologies arrived in porn. And I always say that porn has been the most inclusive of all, of all industries because every, it’s got every category covered, everything
[00:27:35] Steve: you can think of.
[00:27:36] Steve: Every idea, religion, race, whatever.
[00:27:38] Cameron: Yeah, if it exists,
[00:27:39] Steve: Apparently, that’s what I, so I’ve been told, Cameron. I mean, I don’t know
[00:27:42] Steve: personally, but people have informed me of
[00:27:44] Cameron: If it exists, people will
[00:27:45] Cameron: have sex in it, or on it, or near it, or around it.
[00:27:48] Steve: or with it, or, Yeah, yeah,
[00:27:50] Cameron: yeah, yeah. So let’s talk,
[00:27:52] Steve: we really
[00:27:53] Cameron: I’ve seen people posting
[00:27:54] Cameron: videos on TikTok of their experiences in Waymo’s, etc. So let’s [00:28:00] talk a little bit about the implications of that, Steve. Like, as our leading futurist, what are the short, medium, and long term implications of robot taxis to society?
[00:28:16] Steve: You know, I think the really simple implication, I mean, there’s a lot of externalities. The first one is, I mean, obviously, it’s gonna be really hard for anyone who drives in a business. to make money out of it. And I’m talking about Uber drivers. I mean, the limo drivers will still exist. They, they go and they sit and they wait out
[00:28:35] Steve: the front for two hours
[00:28:36] Steve: until you hop back in the car. So I think that that’ll
[00:28:39] Cameron: limo do that?
[00:28:43] Steve: Yeah, but I think people want someone to open the door for them, especially people on, you know, movies like Succession. You know, it’s, it’s about the fact that you’ve, you’ve got someone sitting there waiting at your beck and call is I think. The thing that they want more than the actual transport.
[00:28:58] Cameron: Right. [00:29:00] It’s
[00:29:00] Steve: All right.
[00:29:00] Steve: So
[00:29:01] Cameron: the, the proxy
[00:29:02] Cameron: slave experience.
[00:29:04] Steve: slave, it is proxy slavery. And the other one is that it doesn’t make traffic better. There’s been a lot of calls for there’s too many cars on the road and traffic jams. Well, if you have robo taxis, then theoretically you get double ended traffic where it goes both ways, right? So you get, if you’re getting it to drive you to the city, you get a lot of empty cars driving around.
[00:29:26] Steve: And so managing. That becomes a difficult thing where the is harder to manage. I think it, it, it changes. The shape of our roads in our cities, it’ll need to change it because they’re currently set up for people in cars and car parks. You know, the average city has 30% of its spaces allocated or 30% of its ground space is allocated to where cars stop and rest.
[00:29:52] Steve: And we don’t need that. So you can potentially green up the cities, have more space. I think that’s a really good thing. And a long term implication of [00:30:00] robo taxis, I think is that it be It creates a new entrepreneurial industry where people can invest in cars and they become like little mini businesses.
[00:30:08] Steve: And imagine if a car becomes sentient and it knows where to go and it knows that there’s a festival in Sydney. So overnight it drives itself up to Sydney to make money there. And then it gives birth to a new car and it goes a new car itself because it goes, I’m, I’m getting really busy as it can do kind of interesting things.
[00:30:24] Steve: So I think. There’s going to be a lot of opportunity that comes with it and I think it’ll change the shape of cars. Cars are really configured for driving, and I think the shape of what they’re going to look like, they’re going to become like little minivans that are more lounge room esque, and we’ve seen some of the future cars or concept cars look like that. going to be really interesting.
[00:30:49] Cameron: If it’s just, if I
[00:30:50] Cameron: just need a car for me, one person to pick me up and take me into the city, I don’t need a big sedan or a minivan. I just need [00:31:00] a. tiny little box that has, you know, some crash zones around it, but doesn’t need space for a driver in theory, just needs to get me, you know, a little, little, very small pocket sized car that gets me from point A to point B.
[00:31:18] Cameron: I can fit a lot more of those on the road.
[00:31:21] Steve: this is where the data becomes interesting. So what percentage of rides have a single person? It’s probably a lot more than we think. And then maybe the shape of cars needs to change radically as well. So once we get the database on, and I imagine companies like Uber know this, you know, their shared rides.
[00:31:35] Steve: I’ve never done an Uber share. It’s always me by myself in the back seat. And I wonder , and this is a guess, At least 80% of rides, it’d have to be a single person. So maybe you need to
[00:31:45] Steve: reshape what vehicles look like.
[00:31:47] Cameron: So obviously if we, if we get to a world of robot taxis, you know, ubiquitous everywhere, of different sizes of vehicles. [00:32:00] Yeah, you’re probably not gonna, like, I’m not going to drive up to visit my mum in Bundaberg in a robot taxi, or maybe I will. I mean, why not? I’m just wondering about car ownership.
[00:32:12] Cameron: What, at what point do people say, oh, I don’t need to buy a car anymore? I mean, we know that in places like New York City, car ownership is a lot lower than it is in lots of other cities, but let’s take
[00:32:23] Steve: on the setup. It depends on the setup of the geography that you’re in largely, right? And geographies that have been set up around cars, it’s quite
[00:32:31] Steve: obvious to see, isn’t it? Especially Australia.
[00:32:33] Cameron: Yeah. So Australia, we tend to have at least one, if not two, three, four cars per household. You know, I very rarely use my car for anything beyond a short trip. Like it’s school runs and it’s groceries, going out to a coffee, going to Kung Fu five times a week. It’s, you know, it’s, it’s very
[00:32:58] Steve: You go five times a week. Wait a minute. Do you [00:33:00] go to Kung Fu five times a week?
[00:33:01] Cameron: Four to five times a week. Yeah. Nearly.
[00:33:03] Steve: that. I’m going to
[00:33:04] Steve: start Kung Fu this weekend. That’s it. I’m starting.
[00:33:06] Cameron: And sometimes, you know, we go like tonight we’ll be going at four o’clock and we’ll finish at eight. So it’s like four, three to four hours, some nights. Some days it’s just an hour. Some days it’s like three to four hours of kung fu. Tomorrow it’ll be four hours.
[00:33:18] Cameron: Tomorrow morning. Anyway. So, but it’s mostly short trips. You know, Chrissy’s the same. We only have one car, Chrissy drives it more than I do. She’s out and about during the day, but it’s mostly just to the shops or to go have coffee with friends or that kind of stuff, a couple of times a year though. We will do, you know, on the weekends, we might go drive out of town to go to the beach, go for a hike.
[00:33:41] Cameron: A couple of times a year, I’ll drive up to Bundaberg to visit my mom, which is like a four or five hour drive. Maybe once a year, we’ll drive down to Sydney to visit friends down there. So that, you know, take a couple of days to drive down there. So I wonder, you know, five years from now, ten years from now, in a world of ubiquitous robot taxis, will there be, will I need [00:34:00] to own, like, will it be more cost effective to just, you know, hire a robot taxi to get me to Sydney or to Bundaberg?
[00:34:08] Cameron: Then own a car and have to maintain a car and pay for petrol and all that kind of stuff. Like, what, what, where, where does
[00:34:15] Steve: Awesome. Well, it won’t be petrol, but
[00:34:17] Cameron: it’ll be
[00:34:17] Steve: the economics, yeah, electric, the economics of car ownership are pretty clear. It’s not, it’s not really that good if, especially if you don’t have high asset utilisation. If you have high asset utilisation, it’s definitely worth it. It’s more economic, but I think we’re going to move to a subscription of mobility.
[00:34:33] Steve: A lot of the, a lot of the major car companies that. I know GM trailed for a period where you could subscribe to a car for, I’m just going to make this number up. Let’s say it’s a thousand bucks a month. Yeah. And if you’re going to the snow for the weekend, you can change it to a four wheel drive.
[00:34:48] Steve: Or if you were, if you needed to move house, you could get a van. You could just come in and just, you subscribe to a number of their vehicles. I think that is going to be one of the models. I know that Toyota has [00:35:00] Kinto, which is kind of like an, a ride share and and hire car business. So they want you to subscribe to Toyota services where you might buy a car and it gives you access.
[00:35:12] Steve: to different forms of mobility within their ecosystem. We’ll see that a lot. And, and, and it’s, it could be better financially for the organization and the end user. And
[00:35:22] Steve: that’s, that’s when you get big
[00:35:23] Steve: shifts when those two things align.
[00:35:25] Cameron: The last time I spoke to Robert Scoble in depth, which was probably… A year and a half ago, maybe, yeah, about that. We were talking about this. He was telling me that Tesla was going to move towards that kind of a rental model where you just, a subscription model, you just have a car, robot car just turns up whenever you want one, you, you pay your 50 bucks a month or whatever, a hundred bucks a month subscription, we should actually get Robert on the show.
[00:35:56] Cameron: He’d be a, he’d be a fun guest to have on. [00:36:00] But, you know, obviously, in a world like that, car ownership goes down, means car dealerships disappear, to a large extent petrol stations disappear change the shape
[00:36:13] Cameron: yeah, will change to become charging stations maybe, but if I’m, if I’m just catching a robot taxi everywhere, the robot taxi will just go charge itself at some sort of remote location, yeah, wherever it needs to be.
[00:36:25] Cameron: Right. Out
[00:36:27] Steve: Yeah. And 90, 90% of charges happen at work or home anyway. You don’t
[00:36:30] Steve: really do them unless you
[00:36:31] Steve: drive into Bundaberg.
[00:36:32] Cameron: right. And you know, if it’s a robot taxi, I imagine they’ll, their charging stations will be out near the airport, industrial areas. They don’t need to be in the CBD or in suburbs. Like we have petrol stations everywhere. You know, the ability to it’s really interesting to think about long term implications of that kind of world.
[00:36:51] Cameron: By the way, I saw somebody posted on TikTok yesterday, a fleet like a, Truck carrier with a fleet of Tesla’s [00:37:00] trucks on it. What do they call their truck? The robot truck thing? Tesla? Cybertruck!
[00:37:09] Steve: my wife is just crawling under to go around into that room. She just crawled under. Jen, you can walk past. It’s me and Cam. We got this. It’s mostly, it’s not really visual. I know we’re recording,
[00:37:20] Steve: but
[00:37:20] Cameron: You don’t make a crawl everywhere in your presence under hands in there. She wasn’t genuflecting while she was going past or anything.
[00:37:27] Steve: what are you doing?
[00:37:31] Cameron: Alright, let’s move on. Different stories. So we talked a couple of weeks ago about LK99.
[00:37:41] Steve: Yeah. been debunked?
[00:37:43] Cameron: well it kind of has been debunked?
[00:37:46] Cameron: A lot of the, the latest testing of it has debunked it. Now, couple of things. The original experiments done by the [00:38:00] Koreans haven’t been peer reviewed. Neither have the debunking studies been peer reviewed.
[00:38:06] Cameron: But the,
[00:38:06] Steve: It’s a debunking war. It’s spy versus spy, Cold War style with Cam Reilly here. The
[00:38:12] Steve: debunkers versus
[00:38:13] Steve: the debunkers versus the
[00:38:15] Cameron: so the latest thinking is that it’s sort of dead in the water. Now, if it’s not a superconductor, why did the original researchers think it was? According to one study, it might have been the result of an impurity in the original LK99 samples they were using, cuprosulfide, which can experience a large and sudden change in resistance at a certain temperature.
[00:38:42] Cameron: But that temperature is around 127 degrees Celsius. Now they were talking about this happening at room temperature, not at 127 degrees Celsius.
[00:38:51] Steve: debunkers. My room is
[00:38:52] Steve: slightly cooler than 127
[00:38:54] Cameron: That’s good to know.
[00:38:55] Steve: now.
[00:38:56] Steve: Yeah, I’m glad.
[00:38:58] Cameron: And, you know, it [00:39:00] did, you know, we saw various people playing around with LK99 in those first couple of weeks. It seemed to be exhibiting something that looked like magnetics flux pinning, where it was sort of partially levitating. The latest study seemed to suggest that could have just been boring old ferromagnetism.
[00:39:19] Cameron: That’s when certain materials, and there’s a lot of them, iron, nickel, cobalt, etc, some alloys can exhibit it. Basically in ferromagnetic materials, the magnetic moments of the individual atoms align in the same direction. It creates a really strong overall magnetic effect. So it has been pretty much debunked.
[00:39:39] Cameron: However, After I wrote those notes yesterday in preparation for this show, late, last night, I saw some late breaking news.
[00:39:51] Steve: And these notes were copious, May. I just, the audience can’t see this necessarily, but goodness me,
[00:39:56] Cameron: Yeah, yeah,
[00:39:57] Steve: Cam Riley does his, Cam Riley does his
[00:39:59] Steve: [00:40:00] homework.
[00:40:00] Cameron: you should see my notes from my other shows, man, where I write 10, 000 words for an episode. Anyway, the original Korean outfit known as the Q Center, it’s the Quantum Energy Research Center from Korea University, have just come out with more information. and a patent around this kind of stuff.
[00:40:26] Cameron: And what they’re saying is that there was just a very thin layer of their original material that was superconductive. They say it was 48. 9%, so less than half of the original material, was a thin film of lead apatite that was superconductive. And they’re basically you know, my reading of the paper that they’ve just come out with seems to argue that everyone else who didn’t get [00:41:00] the same result that they got was building it incorrectly.
[00:41:03] Cameron: A bit like when, you know, the early iPhones were blocking telephone signal and Steve Jobs told everyone they were holding their iPhone incorrectly. Same sort of thing.
[00:41:14] Steve: that. I love that. Hey, listen,
[00:41:16] Cameron: You’re doing
[00:41:16] Steve: I don’t know if you know, no, no, listen, listen everyone here. Look, I’ve got turtleneck black jumper on, jeans with no belt. And what are those sneakers that they love to wear? I don’t know.
[00:41:30] Steve: You know, the
[00:41:30] Steve: brand of sneakers, New Balance,
[00:41:33] Steve: New Balance, New Balance sneakers. New Balance
[00:41:36] Steve: Sneakers, and I think, I think all of you Luddites have been holding your phone the wrong way.
[00:41:40] Steve: I just want to let you know that. My name’s Steve Jobs, and everything I say is righteous and
[00:41:44] Steve: good.
[00:41:45] Cameron: do look a bit Steve Joby, man, you know, you, you got the same
[00:41:49] Steve: This is a 10 Uniqlo top, by the way, with my 10 Uniqlo
[00:41:53] Cameron: Looking good man, looking ripped. Look at you. Not realistic.
[00:41:58] Cameron: so these original, the Koreans admit [00:42:00] dire magnetism. They admit ferro magnetism. They say, yeah, yeah, the material has these things, but it also exhibits the meiser effect, the fluxx pinning.
[00:42:09] Cameron: If you get the right. material built in the right way. So late breaking news, Korea strikes back. They’ve said, no, no, no, no, no, no, no, no. You’re all doing it wrong. And they’re sticking to their guns. So the general consensus in the world up until last night was they fucked it up. They’re, they’re fighting back and saying, nah, we’re going to prove you’re wrong.
[00:42:35] Cameron: Speaking of proving everyone wrong. What are the reasons we started this show? And one of the, when you and I were first talking about doing this a few months ago, the two things that had me really excited at the time were the emergence of CHAT GPT and ColdFusion, the successful ColdFusion experiment that happened in December last year.
[00:42:55] Cameron: Both CHAT GPT was launched in December and the ColdFusion [00:43:00]experiment at the National Ignition Facility at Lawrence Livermore National University, a laboratory in the United States of America. Now, we haven’t really talked much about ColdFusion in this show, but what’s happened in the last couple of weeks is they did it again and with even better numbers.
[00:43:20] Cameron: The same operation at Lawrence Livermore. So do we need to explain what Cold, what Fusion is? Everyone knows what Fusion is,
[00:43:31] Steve: Fusion is the opposite of a nuclear, thermonuclear reaction, isn’t it?
[00:43:35] Cameron: No.
[00:43:36] Steve: It’s putting things,
[00:43:37] Steve: it’s putting together
[00:43:39] Steve: instead of splitting, right?
[00:43:40] Cameron: Well, okay, so we do
[00:43:41] Cameron: need to explain this. So, the first, very quickly, the first nuclear bombs, the atom bombs that were dropped on Japan for no good reason other than just to demonstrate that they had them and to scare Russia, were,
[00:43:57] Steve: the people in Hiroshima, and [00:44:00] I’ll tell you what, it did more than
[00:44:01] Steve: scare
[00:44:01] Steve: people. Yeah, yeah,
[00:44:03] Cameron: But, a lot of
[00:44:05] Cameron: people, including a lot of Americans, think that’s what ended World War II. It had nothing to do with ending World War II. It’s misunderstood. The Japanese…
[00:44:15] Steve: that until you told me this
[00:44:16] Steve: just
[00:44:16] Steve: now.
[00:44:16] Cameron: Yeah, Japanese didn’t surrender because of the atom bombs. The Japanese surrendered because the Russians declared war on them that week.
[00:44:26] Cameron: In between the first and the second bombs being dropped, the Russians that had had a treaty with Japan since the beginning of World War II declared war on them and was launching an invasion in Manchuria. Which had been agreed to in advance between the Soviet Union and the United States, that the, the, the non-aggression pact was gonna expire in the, in August, 1945, which meant the, the Soviet Union was gonna attack Japan.
[00:44:56] Cameron: Japanese had been trying to renegotiate something with the Soviet Union. [00:45:00] Couldn’t, couldn’t do it. And they knew they couldn’t fight a two front war. That’s why they surrendered. Had nothing to do with the bombs. Anyway. Historians know that. Yeah, people don’t. So the first bombs that were dropped were fission bombs.
[00:45:12] Cameron: Fission bombs, you pull a, you pull an atom apart and it creates a chain reaction. It creates a lot of energy. Big boom, right?
[00:45:22] Cameron: The fusion bombs were the bombs that, you know, Oppenheimer, I haven’t seen the film yet, but I’ve done lots of podcasts about Oppenheimer. Oppenheimer led the fission bomb project.
[00:45:34] Cameron: After they dropped the bombs on Japan, he felt horrible about his contribution to it. But America wanted to push on and build even more powerful bombs. Oppenheimer didn’t want to have anything to do with it. He tried to talk Truman out of it. Truman called him a crybaby. It was led mostly by a guy called Edward Teller.
[00:45:53] Cameron: One of, one of the guys from the original team. And those were the hydrogen bombs, and the hydrogen bombs use fusion, [00:46:00] not fission. Fusion is when you force the nucleuses together, which also releases even more energy, as it turns
[00:46:07] Steve: Okay. I did. There you go.
[00:46:09] Cameron: So that’s
[00:46:10] Steve: I dropped out of nuclear physics in high school. I dropped out.
[00:46:14] Steve: I just thought economics is my get
[00:46:15] Steve: up.
[00:46:16] Cameron: Yeah, pays better. So we’ve had fusion since the fifties, but the problem with that kind of fusion is it releases all of its energy all at once, hence the using of the word bomb in the title. And that’s not very effective as a source of energy blowing shit up. It’s good if you want to blow shit up, but it’s not really good to run your toaster.
[00:46:38] Steve: Not really good to distribute it to run a toaster. I love how you just said it’s great to blow shit up. Not so good
[00:46:45] Steve: at, at, at running a toaster.
[00:46:47] Cameron: Yeah. So
[00:46:48] Steve: That’s, that is, you don’t know how great that was. That was so great.
[00:46:53] Cameron: glad you liked it, Steve.
[00:46:54] Steve: Just pause and just, I want to absorb how great that was.
[00:46:58] Cameron: I appreciate it. [00:47:00] So, the ultimate goal for fusion, because that’s, this is what the sun does. The sun creates energy by fusion. We’ve always wanted to create a form of fusion that can be controlled and where we can come up with discrete units of energy that it releases slowly over time. It’s clean, there’s no waste product, there’s no, you know nuclear waste material.
[00:47:24] Cameron: None of that kind of stuff that we associate with nuclear fission. The problem is that we haven’t been able to work out how to do it. Scientists have been trying to do this since the fifties with no success. And what we call cold fusion is where you can do it in a controlled environment. Now. We know how to do it. Let me, let me say, let me step back go back a step. We know how to do it. We just don’t know how to do it in a efficient fashion. I, for a, for a fusion [00:48:00] experiment to be useful, the energy given out needs to be more than the energy used to create the You know, the chemical effect in the first place, the atomic effect, right?
[00:48:14] Steve: Yes,
[00:48:15] Cameron: So this is what Lawrence Livermore did for the first time in December last year, they created more energy out of the reaction than it cost them to create the reaction. They basically shot a whole bunch of lasers at some atoms and created some energy out of it. Now. They just did the experiment again at the end of July and produced even a higher energy yield than they did in December.
[00:48:44] Cameron: So, this is the beginnings of a clean energy economy, if we can scale this up and get it right.
[00:48:53] Steve: cleaner than lithium mining.
[00:48:56] Cameron: Yeah, lithium mining, [00:49:00] yeah, don’t get me started on
[00:49:02] Steve: one of the
[00:49:02] Steve: smartest.
[00:49:03] Steve: Yeah, exactly.
[00:49:04] Cameron: So, Here’s the problem though, the break, when scientists talk about the break even point with this kind of stuff, they use that word in a different way than we do in common parlance. Like a scientific theory, it means something different to scientists than the word theory means in everyday language.
[00:49:24] Cameron: The break even point, in the way that they think about it, is The amount of energy that goes into the specific step to cause the reaction that releases energy. Not everything that goes into creating that reaction behind the scenes. So, when they’re shooting lasers at… light elements, hydrogen and helium, to create the fusion event.
[00:49:49] Cameron: They’re just measuring the energy in the lasers themselves, not everything that goes into building the systems that create the energy to generate the lasers. [00:50:00] If you look at it from that perspective, it takes way more energy. to cause the reaction that we’re getting out of it, like by a factor of thousands.
[00:50:10] Cameron: So we’ve got a long way to go before this is something that’s practical for everyday use. Everyone knows that, but it’s the, you know, it’s a really exciting beginning. And the other key point I wanted to make here is that as a planet, we’ve invested very little money into this. In 19, since 1954, when they came up with the bomb, the US has invested only about 500 million dollars a year on fusion research.
[00:50:42] Cameron: All up, I think, about 34 billion dollars since
[00:50:46] Cameron: 1954. Last year, guess how much Climate change related weather events cost the US economy last year.
[00:50:55] Steve: Oh, extraordinary amounts, I’m certain.
[00:50:58] Cameron: One estimate that [00:51:00] you hear a lot is about 165 billion and that was last year alone. Fires, floods, etc. Not to mention the global impact of all of those things. And we know it’s just going to get worse. From here on in. Not to mention the hundred billion dollars they pulled out of their ass to fund the war in Ukraine.
[00:51:19] Cameron: You know, it’s easy for the U. S. to come up with hundreds of billions of dollars out of nowhere if they need it, like we did during COVID, etc. But very little
[00:51:30] Steve: In a subsequent episode, we need to go through modern monetary theory
[00:51:35] Cameron: Oh, yeah. Yeah. Speaking of
[00:51:37] Steve: Yeah, because, well, it’s not magic voodoo. It’s, if it’s used right, it’s almost an infallible way to, to, it’s how all the economy grows. It’s all just based on perception. But anyway, we’re going to go
[00:51:48] Steve: through that next episode, modern monetary theory.
[00:51:50] Cameron: Well, we’ll balance that
[00:51:51] Cameron: up with communism. If it’s just done right, cause that’d be my same argument for communism. Anyway, let’s move. So it’s very [00:52:00] exciting news. We, we need to, we need to invest way more money in this, I think. Now that these guys have replicated it twice, hasn’t been peer reviewed yet, they haven’t released a lot of information about what happened in the July experiment.
[00:52:14] Cameron: Very credible association, been around a long time, pretty trustworthy. The last
[00:52:18] Steve: This is, this is, this is one of your ideas though, that you had earlier. When you talked about the fact that everyone’s worried about PDoOM and AI, and your contention was that AI can solve the problems that we may not be able to, and that it’s required for us to make it through the next century. And it’s things like medical science and it having different understandings where it can solve some of those final pieces of the puzzle to technology that we haven’t been able to solve yet.
[00:52:44] Steve: So what can an AI find within these? research papers and moves forward with things like cold fusion that humans can’t, remembering that it’s exponentially improving
[00:52:53] Steve: on what it can understand.
[00:52:55] Cameron: Yeah, I mean, that’s one of the hopes for AI is that, you know, we throw it at [00:53:00] all of this sort of stuff and do a lot more basic research ourselves. We need to throw a lot of money at basic research, science, basic science, and then we can give the data that comes out of that to the AI to help us process it.
[00:53:11] Steve: That’s yeah, and different science from different areas. We’ve got 10 to go, Cam. 10 minutes to go, we’ve
[00:53:16] Steve: got. So we’re
[00:53:17] Steve: gonna, we’re gonna zip through from here.
[00:53:20] Cameron: there are a lot of vested interests that probably don’t want to
[00:53:22] Cameron: see coal fusion succeed because not very good for the fossil fuel industry, but anyway, that’s another story. Quick one to finish with, again, late breaking news, don’t know if you saw this yet this morning, but a guy called Nadir Hajarabi, who is allegedly a former employee of WorldCoin, Sam
[00:53:40] Steve: Dystopia. Dystopia. crypto,
[00:53:43] Cameron: UBI, thing that we talked about a couple of weeks ago.
[00:53:48] Steve: Techno Dystopia.
[00:53:50] Cameron: Hajarabi, posted a video on the last 24 hours where he is calling himself a whistleblower, a world coin whistleblower. [00:54:00] He is alleging that their execution has been sloppy and or illegal. He said, great vision, great mission, but horrendous execution. He said that he is cooperating with various jurisdictions.
[00:54:14] Cameron: To help them look into what’s going on at World Coin. Said he can’t say much more. His lawyers have told him not to say much more, he just wanted to go on record to say that he is no longer associated with the project. He doesn’t want his name attached to it. When I say, hey, his, I mean they, I think he prefers they them.
[00:54:30] Cameron: Sorry about that. NAJE Nadir, they said that they had problems with the token white paper when it came out. That was sort of the turning point. A lot of problems with how it was represented that they were aware of and they suggested that everybody thoroughly read what you’re signing up to if you’re rushing out there to join WorldCoin.
[00:54:58] Cameron: I also notice in the news that [00:55:00] Kenya has shut down the operation of Worldcoin in their country. They’ve created an investigative committee. Following a review from Kenyan regulatory bodies, Worldcoin was deemed to have a number of legitimate regulatory concerns that require urgent attention, and the government suspended the project.
[00:55:21] Cameron: So, I don’t have any more
[00:55:23] Steve: been super dodgy. Yeah, I have. They’ve been super dodgy in the way they’re going out. On average, you get 35 allegedly. You get 30. No, they’ve been super dodgy. Listen, if I’ve learned anything from a history and tech company saying they’re about to save the world, there’s dodginess underneath that bonnet, I tell you.
[00:55:38] Steve: And this is one that nothing is clearer. If you need to go out and pay people 35 US, In developing markers to get them to stare into your orb so that you can scan their iris on some sort of a coin that they’ll never use. That’ll never be legal tender in any country, any time ever. Mate, that, that is, that has got dodgy written [00:56:00] all over it.
[00:56:00] Steve: And there’s nothing that is more annoying than technology utopians claiming to save the world with their vision. And of course they’re in charge of it. Unelected gods in charge of our future. Seriously, this, this world coin, the moment I heard about it, I’m like, yeah, nah, we actually don’t need a tech company to create a global coin that has biometric measures in it because you’re just a self elected savior.
[00:56:27] Steve: Seriously.
[00:56:29] Steve: Do you want me to tell you what I really think?
[00:56:31] Cameron: ha ha ha! ha ha ha ha ha ha ha ha! Yeah, well, I take your point, a lot of what you said there is true, Steve, but, you know, who else is going to save us if it’s not self appointed saviors? Who do you think is going to save us from our doom? It ain’t the governments that we’ve elected, Steve. They’re just digging the hole deeper and deeper every passing year.
[00:56:56] Cameron: Who, who is going to save us?
[00:56:59] Steve: [00:57:00] Well, I unelected.
[00:57:06] Steve: Yeah, the people that save anything or make anything better is usually the people that come with pitchforks. It’s actually when the populace understands in the first instance, which they don’t and I mean you’ve enlightened me a lot today on You know Cold War and you know what happened with the bombs being dropped on Japan I think we need to know what’s going on in the first instance And once we understand that and we get angry enough, then we come and we demand something different Right, and I think we’ve seen that historically.
[00:57:35] Steve: It’s very rarely, it’s very rarely a saviour that’s either from some commercial interest or some political interest. It’s usually the people uprising and then the so called leaders or those in positions
[00:57:46] Steve: to change things
[00:57:47] Steve: responding to what the populace wants.
[00:57:50] Cameron: Well, the people have to be led though,
[00:57:52] Cameron: usually by
[00:57:53] Steve: They have to, they have to be led, of course, by usually someone who comes from within the ranks, I think [00:58:00] and sometimes they lead us into into the right place, but the problem is, is that, you asleep at the wheel here.
[00:58:07] Steve: Everyone’s just scrolling their life away into their own algorithm of their existential belief systems. You know, one of the big problems is that we don’t have a common narrative that everyone can buy into that embraces all of the challenges, whether they’re economic or
[00:58:20] Steve: climate related or
[00:58:21] Steve: environmental at the moment.
[00:58:24] Cameron: Because the merchants of doubt spending inordinate amounts of money every year to spread doubt and propaganda to, you know, muddy the waters and confuse the story.
[00:58:37] Steve: Yeah. Okay. So let’s go on to, we’ve got a couple of quick things. We’re going to go three minutes on each of these. We’re going to go into the deep dive, where then we’re going to do the technology time warp on the futurist forecast. And we’ve got 10 minutes to do it. Well, the deep dive is really easy. The deep dive for me is the most profitable strategy of all time has been to steal [00:59:00]things.
[00:59:00] Steve: Right, if you steal something and you take it without asking, you make a lot of money. We saw that with the East India Company that just stole resources from countries. We saw it with oil. They just dug it up and said, yeah, this is ours now and went into the Middle East and took stuff. And we’re seeing it.
[00:59:17] Steve: We saw it with data and big tech. They just said, Oh, that data. Yeah, it’s not worth anything to you. Here’s a shiny video you can watch. Let us just take all your data. And now we’re seeing it with the training databases in AI. The most profitable strategy of all time is not to pay or not pay much for your raw materials.
[00:59:33] Steve: It’s always been that way. And here we are again. And the big trick, the big trick. Of big tech, the big trick of big tech has always been to take things that have little value isolated, but a ton of value in the aggregate. And the writer’s strike is an interesting one because you know, the, the database that’s going to train script writing and movie and video visuals that won’t need [01:00:00]actors or writers is come from all the little tiny pieces of what people have contributed over the years to train the database.
[01:00:07] Steve: So I just. Wanted to point out that idea that the most profitable thing of all time is just to take
[01:00:12] Steve: stuff.
[01:00:13] Steve: Isn’t that sad?
[01:00:15] Cameron: Yeah, to, well, to see value before other people see value in
[01:00:21] Steve: that’s a good
[01:00:22] Cameron: and to
[01:00:22] Steve: It’s being early, isn’t it
[01:00:24] Cameron: Yeah, and to stitch
[01:00:25] Cameron: it up before other people realize the value inherent in whatever the asset is, the underlying asset. I said to you off air that when the British stitched up all of the oil industry in Iran in 1905 for, you know, very little money.
[01:00:41] Steve: 20 cents in a Mars bar it
[01:00:43] Steve: was.
[01:00:43] Cameron: They did that at a time when, you know, the value of oil as an asset, or oil reserves in a country as an asset, weren’t fully appreciated because it was at the beginning of the revolution towards oil based engines. Yeah, [01:01:00] if you can get in there and stitch something up before people appreciate the value, then you can, as you say, make a, make a shit ton of money.
[01:01:06] Cameron: And these days we’re seeing it done in, in the tech industry in terms of data or you know, content.
[01:01:13] Steve: I think we’re going to see a lot of AI based strikes, which are a little bit like what happened during the manufacturing realm where things were taken and used. Okay, Tech Time Warp. For me, I just want to point out this idea of Amara’s Law. which Roy Amara, who was a technologist and scientist from Stanford, and he founded the Institute of the Future in the early seventies, I think.
[01:01:37] Steve: And his adage about forecasting technology trends states that we tend to overestimate the effect of a technology in the short run, but underestimate its effect in the long run. And I think that It might be a little bit of an Amara’s Law for robo taxis and autonomous vehicles. You know, it’s been 10 years in the making, a good decade, we were all seduced thinking next [01:02:00]year our kids will just hop in a robo taxi and go to school and we can sleep in.
[01:02:03] Steve: Didn’t happen, but I think we might be back and this might be a great example of Amara’s Law. He’s got some really good research that everyone can look at, so I just thought that was a really interesting tech time warp. That adage has been around a long time and I think it happens a lot. I think when the internet came, people saying you’re just going to point a button and buy this and you’ll be able to watch a movie and just stream any movie from 10, 000 years TV to see it.
[01:02:26] Steve: And everyone’s like, yeah, yeah, nah, it’s 2006 and I’m still going to blockbuster. And here we are. So we tend to overestimate in the short run, but the long run, the impact often
[01:02:35] Steve: it does
[01:02:35] Steve: arrive and it’s sometimes bigger than we think.
[01:02:38] Cameron: I’ve never actually heard of that as a Amara’s Law, but, you know, Bill Gates often says statements similar to that. I remember in, I think, Business at the Speed of Thought, he would talk about how technology usually takes longer to be implemented than we want it to be, but not as long as people think it’s going to be.
[01:02:58] Cameron: Amara’s Law. Good one. Thank you for [01:03:00] bringing that
[01:03:00] Cameron: to my
[01:03:01] Steve: Oh, that’s good. First time I’ve taught you anything. It’s usually the other way around. the absorber. And the Futurist forecast. This one’s interesting. Look, I think that we’re going to see a period of de globalization. Now, I want to preface that by saying it doesn’t mean all globalization things get shot, but the world kind of breathes where it has periods where it expands globally and some parts contract.
[01:03:27] Steve: I think we’re going to see manufacturing of sensitive issues, infrastructure, technology, chips, those types of things to go back to sovereign markets. Huawei was just got accused of building a secret microchip factory with funding from the CCP overnight. I And I think smart governments will take back critical infrastructure.
[01:03:47] Steve: We’ve already seen it in Australia where electricity is going back into the SEC in Victoria. Communications, water, we’re going reshore manufacturing of technology inputs which have [01:04:00] important implications geopolitically for better security. And segments of the global economy will decline. Sure, let China make our who cares?
[01:04:10] Steve: But when it comes to critical infrastructure, I think that smart governments will be careful and they’ll bring a lot of that back. In house, it’ll be a great way to redistribute income and provide high paid jobs as technology displaces a lot of people, I think as well. And I think that the smart money is to bring back natural monopolies in house and de globalize manufacturing of things like chips, computers, cars, those types of things.
[01:04:38] Steve: Yeah, that’s my forecast, Cam. I’d love to know what your thoughts are on that, because one of the challenges is the supply chain isn’t as thick or as strong
[01:04:48] Steve: as it was
[01:04:49] Steve: 20 or 30 years ago, so it’s not easy to
[01:04:50] Steve: do.
[01:04:51] Cameron: Well, people have been talking about this idea for a few years now. You know, part of the whole US China trade [01:05:00] war has been the suggestion that the US wants to re domesticize some of the manufacturing of its more sensitive products. Obviously, they’re trying to prevent China from being able to get access to advanced chip technology and designs.
[01:05:15] Cameron: And, and trying to stop them getting access to the raw materials, the rare earth metals that are used to build a lot of these things. One of the reasons why, if people don’t know this, the war in, well, the, the, the tensions around a potential complete takeover of Taiwan by China has been ramping up is.
[01:05:34] Cameron: Well, it’s also because
[01:05:36] Steve: manufacturing
[01:05:36] Cameron: it’s where all the microchips are being manufactured
[01:05:38] Steve: made.
[01:05:39] Cameron: Taiwan. And that’s, you know,
[01:05:41] Cameron: that’s a key pivot point for the future and the US are trying to make it difficult for China to get access to this stuff. By the way, moving into geopolitics, Taiwan is part of China.
[01:05:55] Cameron: Everyone agrees with that, including the
[01:05:57] Steve: Including Australia.
[01:05:58] Cameron: Including Taiwan. [01:06:00] The constitution of Taiwan says that there is only one China and Taiwan is part of China. Of course, when they wrote that, they thought that they actually ran China, even though they’d been kicked out and were hiding in Taiwan. But the US agrees that Taiwan is part of China.
[01:06:16] Cameron: Australia agrees that Taiwan is part of China. The United Nations agrees that Taiwan is part of China. You wouldn’t know that from reading… the Western media, because whenever, even when the ABC, drives me nuts about the ABC, the ABC, whenever they talk about it, which they do on a weekly basis, say,
[01:06:32] Steve: is in a, in a rapid
[01:06:34] Steve: state of decline, just
[01:06:34] Steve: quietly on, on, on their agenda.
[01:06:37] Cameron: even that the ABC always says China claims ownership of Taiwan, claims, okay, no,
[01:06:44] Steve: does Australia.
[01:06:45] Cameron: everyone, everyone claims.
[01:06:48] Cameron: I think maybe the Vatican is the only country that doesn’t. What did you hold your
[01:06:54] Cameron: finger up for? So we got to go?
[01:06:57] Steve: Yeah. I’ve got a, I’ve got a 1030 hard stop, but [01:07:00] I’ll tell you what, if there was ever a time to hard stop on the futuristic episode 10, I feel like this has been, it might be the
[01:07:07] Steve: best yet. I know I say that
[01:07:09] Steve: every time.
[01:07:10] Cameron: Well, my, my final point on deglobalization is going to be how are we going to pay for it? We’ve spent decades moving manufacturing offshore and it’s made prices cheaper and cheaper and cheaper. The prices are going to go through the roof if we try and bring everything back on shore. Inflation’s going to go through the roof.
[01:07:31] Steve: Old Bit of old school inflation.
[01:07:34] Cameron: where MMT comes in. We’ll just print money to
[01:07:36] Steve: Exactly. MMT and inflation we’re going to talk about
[01:07:40] Steve: next episode.
[01:07:41] Cameron: Thank you, Steve O. Good to chat, buddy. Have a good week.
[01:07:45] Steve: You too champ. All