Select Page

This week on the Futuristic podcast – Neuralink patient playing chess, Claude Opus outperforms GPT4, Nvidia announces robot framework “Project GR00T” and Blackwell platform, Microsoft and OpenAI plan supercomputer project worth $100 billion called ‘Stargate’, Amazon audio books using AI, OpenAI Voice cloning tool, Apple is in talks to build Google’s Gemini AI engine into the iPhone, Stability AI and Inflection (Pi) CEO’s quit and join Microsoft, Altman / Jensen predict AGI in about five years, Currency is a technology, and we ask – what does the world look like with AGI? 


FUT 23


[00:00:00] Cameron: Mr. Sammartino, Mr. Bob Sammartino. That’s the best intro I’ve still got! It’s

[00:00:14] Cameron: I was listening to that just before you came on. Futuristic, Episode 23, 1st of April, April Fool’s Day, and here we are, the two greatest fools,

[00:00:24] Cameron: Cameron Reilly and Steve Sammartino, to talk

[00:00:26] Cameron: about the future. Oh my god, Steve, it has been a crazy, crazy couple of weeks since we last recorded.

[00:00:35] Steve: getting faster. Acceleration. It really,

[00:00:38] Cameron: it really, it is, yeah. And things building on things, building on things,

[00:00:43] Cameron: um, But before we get into the news of the last week or two, tell me something. Of note that you did that’s futuristic in the last couple of weeks, Steve O.

[00:00:55] Steve: Yeah, I’ve been making clones of myself.

[00:00:58] Cameron: Oh my God. Like one Steve Sammartino is already too much. How can the

[00:01:03] Cameron: world handle more

[00:01:05] Steve: Can you see, can you see there’s one of me in the picture up the back? An old school clone of me.

[00:01:09] Cameron: I

[00:01:10] Steve: There’s a cushion. I got that as a

[00:01:11] Steve: gift. At a keynote that I did

[00:01:13] Steve: once where they made cushions with the person’s face on all the speakers. And I did like it. It’s, it’s, it’s, uh, yeah,

[00:01:21] Steve: it’s, uh, interesting. So I’ve, um, been on stage, uh, showing my Steve Sammartino AI, where we ask me a question, then we ask the AI a question just to see what the different answers are.

[00:01:35] Steve: And they’re pretty close. They’re pretty good actually. And, and then I’ve been saying, well, the next stage is to me, my clone of, of me and get. Myself to answer it. So I’ve been mucking around with HeyJen, which is pretty good. And that can not only make a client of yourself where you just type in what you want it to say after a few minutes of video.

[00:01:53] Steve: It’s not perfect around the mouth, but it’ll make a version of you saying something, you give it some dialogue and it’ll just say it as a video of you. Um, and I think it’s really interesting how we can use language now. Anyone has access to global markets. I mean, it’s another phase of globalization, which occurs because you can.

[00:02:16] Steve: Put yourself out there in a multitude of languages, and I know MrBeast does this with his videos, he has like Spanish versions of it, and you think about the power languages out there, the exposure that you can have to global markets if you’re any form of content creator now, which was once the bastion of You know, major studios, you know, doing VOs, you know, there’s a Tom Cruise actor that always does Tom Cruise in Italian and so on, but now all of us have access to that, and not just Netflix, we can expand our reach, uh, through language, and you know, the modern day Babelfish has arrived.

[00:02:52] Cameron: So I haven’t played with HeyJen for a while. So go into more detail about what you’ve actually been doing with this

[00:02:57] Steve: Yeah, so, I made a version of me, uh, in my voice. And speaking to it so

[00:03:04] Steve: it can do two things now. And this is the paid version and they’ve just had an upgrade in the last month. So it’s a lot better than the pre the previous one. I did a Spanish one for a surfing keynote that I was doing down at, um, urban surf, cause there’s a lot of, uh, a lot of Brazilian and, and, uh, you know, Spanish and all that kind of stuff.

[00:03:21] Steve: So I did mine, it was actually, sorry, it was Portuguese. I did it in not Spanish, um, for the Brazilian surfers and sent a message out. And it was pretty cool. Um, but it was a bit glitchy, a lot better now, a lot better now in your own language. And just a couple of minutes of talking to video and it’s got your footprint.

[00:03:37] Steve: It’s got your, uh, your bio prints and it can make a version of you. And

[00:03:41] Cameron: it’s a video, It’ll make a video. of you saying whatever you want it to say. In your

[00:03:47] Steve: ways. So I can say, Hi, it’s Steve. Welcome to the Futuristic. Great to have you today. And

[00:03:53] Steve: it’ll upload

[00:03:53] Cameron (2): that. And it used to take about a week before you’d get it back.

[00:03:57] Cameron: Oh, wow. Cause

[00:03:58] Steve: I don’t, I’m not sure if it’s there, you know, the demand on their servers or what have you.

[00:04:03] Steve: Now you get it back pretty quick, you know, within an hour and you can do a version of you and you can choose your language. They’ve got like about 12 languages. And it’ll say it back in the language, or you can do one where it takes your video in your primary language and you type it in and then it’ll do it.

[00:04:21] Cameron: Mm

[00:04:21] Steve: kind of two options, pretty cool.

[00:04:23] Cameron: Wow, that’s incredible stuff. Um, Well, for me, I’ve been doing, I know I say this every episode, but a lot more coding, um, you know, I know I’ve said this before, but the more coding you do, the more coding ideas you have. I had this situation, I was trying, I’ve got this long script for QAV, my investing show, that’s doing regression testing.

[00:04:47] Cameron: One of our listeners actually built it. It’s about 2, 600 lines of Python code and I wanted to add a bunch of logging into it and I’m not going to do that myself, so I tried to upload it first into GPT 4, then into Claude Opus, which I’ll talk more about, uh, it’s just to say insert a lot more coding into this, uh, sort of coding, logging into this, so it was, it was getting some things wrong and I wanted to find out why.

[00:05:10] Cameron: But of course the, the files were too big for them to, too, too many, um, Uh, tokens for them to process, and so you have to break it down into smaller chunks and upload them sequentially. So I just, I just wrote a script. I said to, I think it was Claude Opus, which I’ve been using for my coding lately, I said, write me a Python script that’ll take a large file, large file of coding, split it up into smaller sizes in some sort of rational way, That I can then upload to an AI tool to do stuff.

[00:05:44] Cameron: And it goes, yep, no worries. So what we’ll do is we’ll just split it between functions where there’s a, uh, an empty line, a blank line in between functions. We’ll split it there. We’ll call it chunk one, chunk two, chunk three, chunk four. So I just then, it just wrote me a Python script to break this file up.

[00:05:58] Cameron: Then I said, okay. So now write me a file, uh, write me some code that will merge all of the chunks back together again. Yep, no worries, boom, there you go. So, you know, you can just do the stuff. I had another one where I was up, I was dragging a bunch of photos out of Apple’s photo app onto my backup drive so I could stream them to my TV, cause LG smart TVs aren’t that smart.

[00:06:22] Cameron: And, uh, A lot of the files ended up as HEIC or HEIF files, which the TV couldn’t read. And I know I could probably get an app. Or I could probably open them all up in Preview or something like that, or an Adobe tool and convert them. But, you know, because I’ve got a coding mindset on, I just said to one of my, uh, Claude, Write me a script that’ll convert a directory of HEIC images to JPEGs.

[00:06:49] Cameron: Yeah, no problem. So here you go, here’s the script, point it at the directory, a

[00:06:53] Cameron: minute later it’s converted all of them to JPEGs for me. Just, it’s like, it’s faster than going and looking for a tool to do it, and cheaper, because most of those tools you’re going to have to pay. 10 bucks for, 20 bucks

[00:07:05] Steve: So many of these tools, um, that are, you know, let’s call them plugins

[00:07:09] Steve: or, you know, AI is built on APIs. They’re all dead. I mean, they’re already

[00:07:13] Steve: dead. You know, the funeral just hasn’t happened

[00:07:15] Steve: yet, you know, but they’re

[00:07:18] Cameron: Because the next step will be, I won’t have to write code, I’ll just have to say, Hey, can you

[00:07:22] Cameron: do this for me, and it’ll just do it.

[00:07:24] Steve: Yeah.

[00:07:25] Cameron: I didn’t put this in the

[00:07:27] Cameron: notes, but did you see the Open Interpreter? Oh, one launch, uh, a week or so ago,

[00:07:34] Steve: The which one? The, I looked at all

[00:07:35] Cameron: the little, the little ball that you hold and

[00:07:38] Steve: yeah, yeah, yeah, yeah, yeah. I did see that.

[00:07:41] Cameron: So for people that haven’t seen it, Open Interpreter is a startup out of the US. They hit my radar sometime in the last six to 12 months, cause they had a, A version of an AI that you could download and install on your computer and it will basically integrate with your operating system and run your computer.

[00:08:00] Cameron: I couldn’t get it to work then, I couldn’t, I tried it again last week, I couldn’t get it to work. But they launched their first product about a week ago, they call it the Open Interpreter 01. And it’s uh, A little device that you carry around with you and it’ll connect to your phone, I think, or it’ll connect to Wi Fi if you’re in a Wi Fi area.

[00:08:19] Cameron: You press a button on this thing and talk to it and it’ll control your computer back at the office or back at home. You can, and, and you can do things like say, uh, the demo that the founder does. He says, um, what’s the weather going to be like on the weekend? It’ll tell him, he goes, are there any concerts in Seattle on the weekend?

[00:08:37] Cameron: It goes, yeah, you got these. He goes, okay. Um, make a note in my calendar to go to this concert, uh, or the dates, and then find the email address for Steve Sammartino and my contacts and flick Steve an email, send him a link to it, and ask him if he wants to go. And then you see the computer just doing all of that kind of stuff.

[00:08:56] Cameron: It’s still a bit Clunky, uh, I couldn’t get Open Interpreter running on my Mac as I said, but

[00:09:04] Cameron: you know, easy to see that in the next couple of years that’s where we’ll

[00:09:08] Cameron: be. It’ll be built into your operating system and you’ll just be able to say, oh, can you, uh, do X, Y, and Z? And it’ll just, it’ll just do it for you.

[00:09:16] Cameron: You won’t have

[00:09:16] Steve: be, it’ll be Google, Microsoft, and Apple.

[00:09:19] Cameron: Yeah, yeah, yeah, it’ll

[00:09:20] Steve: Yeah, so it won’t be one of those guys. They’re doing all the research for free and they’ll either be acquired or killed, one of the two.

[00:09:26] Cameron: Yeah, that’s definitely where we’re going. Um, so I mentioned Claude Opus, so one of the, this is in the news stories, but just to jump ahead a little bit, um, Claude, which is the AI tool produced by a company called Anthropic, Been around for a while. Uh, their latest version, Claude Opus, is now beating GPT 4 on all of the benchmarks, which is pretty amazing.

[00:09:49] Cameron: Um, I, it’s a premium subscription. I’ve got one. It’s a bit more expensive than ChatGPT 4. I think it’s like 30 bucks a month instead of 20. Uh, but it’s pretty good and I’ve been using it almost exclu exclusively for my coding in the last week. Uh, and initially it was doing a much better job at coding than GPT 4.

[00:10:11] Cameron: does even GPT 4 through the API, which I use as well. Uh, cause GPT 4 tends to not give, if you give it a bunch of code and you say, change this, you know,

[00:10:22] Cameron: change X, it won’t give you the full code back. It’ll give you some changed lines and then tell you to integrate it yourself. And I’m like, well, what am I fucking paying you for?

[00:10:31] Cameron: I’m not going to do that.

[00:10:33] Steve: I love that. Stop, stop. What am I

[00:10:35] Steve: fucking paying you for? I mean, I love that as an AI. It’s like, what are you doing here? What am I paying you for? Like, classic employee relationship, here it is again, just with AI. You know, and I say that on stage. I say, you’ll be in a whip a year from now. And they say, how’s that project going, Cam?

[00:10:52] Steve: You say, look, my agent’s working on it. It should be ready 2pm Friday. You’re going to say that? I

[00:10:59] Cameron: It is annoying when, you know, you know, look, you could fucking do this with a few more cycles of compute. Just do it. Like, why are you asking me to? Anyway, Claude Opus was giving me the full script. Initially, of everything, every time I asked for something to give me the full script. Then it started to get lazy.

[00:11:14] Cameron: A week into it, it’d be like, ah, you can integrate it yourself. I’m like, no, I don’t think so. The other thing I’ve been doing for the last week, which has been fun, is, um, I’ve been studying maths, Steve.

[00:11:25] Steve: saw that.

[00:11:25] Steve: I’m like, talk me through this.

[00:11:28] Cameron: Well, you know, when Charlie Munger died a few months ago, I was rereading, um, Charlie’s Almanac, and Oh, it’s great. You know, I’ve read it a few years ago. I was reading, I mean, I read it 10 years ago, and I read it a few years ago. I’m reading it again. But one of the things, here’s this thing about, there’s a hundred things that people, everyone should understand.

[00:11:50] Cameron: Like a hundred frameworks that everyone should have a basic knowledge of in order to understand how the world works. And one of them was probability. You need to have a good understanding. You see, most people don’t understand how probability works. So I, I got a textbook on probability. I thought, yeah, I could probably get a better understanding of probability.

[00:12:06] Cameron: But every textbook I read on probability was assuming an apro, uh, um, uh, And shit, I can’t even talk. Was assuming a level of knowledge that I should have about some basic, basic mathematical concepts that I didn’t have or I’ve forgotten. You know, it’s been 35 years since I left school. So anyway, I ended up getting this, uh, Basic Maths Textbook.

[00:12:27] Cameron: It’s called, like, A Complete Guide to Maths

[00:12:29] Cameron: I think it’s out of Columbia or one of the, you know, Princeton or somewhere in the US. Very, very basic. Like, it goes from, like, how addition works

[00:12:37] Steve: See, that’s, most books don’t do that.

[00:12:40] Steve: Books either, they start somewhere or they finish too early. I think like great investing

[00:12:45] Steve: books should really start on, you know, what is money? How does it work? How does money grow? What

[00:12:50] Steve: are growth, like real, but none of them do that.

[00:12:54] Cameron: Yeah.

[00:12:54] Cameron: Well, Tony and I are working on the QAV book at the moment. I should suggest that to him. We’ll go right back to the beginning.

[00:13:01] Steve: You should.

[00:13:01] Cameron: it goes right from the beginning all the way through to, you know, advanced mathematics, but I’ve been doing a whole bunch of stuff.

[00:13:08] Cameron: Like I tell you, I’ve been loving it.

[00:13:10] Cameron: Absolutely. Having a ball. I’ve been doing things like regular polygons and working out the, the angles of polygons, the, uh,

[00:13:20] Steve: all that stuff. I did maths at uni and I forget it.

[00:13:24] Cameron: Right. You know, you forget, right? And it’s, and it’s activating a part of my brain, which I haven’t had to use in so long. And I’m really, really enjoying it. But anyway, I get stuck on things where it tells me I get the answer wrong.

[00:13:37] Cameron: I look at the answer goes, you got it wrong. And but it doesn’t tell me why. I got it wrong. So I can just plug it into GPT or Claude and say, yeah, help me understand this, like I’ve been doing with my Italian for the last year. And it just walks me through it step by step. I go, Oh, I don’t understand why I have to do it this way, not that way.

[00:13:55] Cameron: And it’ll explain it. It gives me analogies. I was talking about tessellating. I posted on Facebook this thing. I asked it about why you can’t tessellate, um, nine sided polygons, nonagons. And it gave me this analogy. It’s like trying to organize cats in a bag. Like if you try, there’s always going to be one

[00:14:14] Cameron: that’s going to try and jump out.

[00:14:15] Cameron: They’re never going to fit perfectly, or there’s going to be an empty space or

[00:14:18] Cameron: something. It’s using like funny analogies, just the

[00:14:21] Cameron: greatest maths tutor ever. You know, it’s

[00:14:23] Steve: think about some of the basics in maths. When you learn division, right? They’ll give you three balls or nine balls And say, you’ve got to divide them evenly with people. And numbers are such an abstraction. We forget that they represent physicality. And when you learn the basic levels, they’ll say, divide them evenly between your three friends.

[00:14:42] Steve: And you can physically see, well, There’s more here versus there, whereas numbers become abstractions. And it’s so easy to forget that. And, you know, teaching by analogy, we do it in the very early stages in life, but then when we get to more senior things, whether it’s economics or business, Or code, we drop the analogies away, which is a real error.

[00:15:03] Steve: You know, when I communicate on stage, I’m always using analogies because I know that if you teach someone something new via something they already intuitively understand, then you will take them to that level of understanding again. And most people forget that.

[00:15:17] Cameron: And people have different learning modalities that.

[00:15:19] Steve: Yeah, absolutely. Yeah, school was really bad at putting you down a certain, you know, medical numbers based and understanding of English and, you know,

[00:15:28] Steve: people are kinetic learners, physical learners. I had a terrible drum teacher.

[00:15:32] Steve: Terrible, right? and he was, Yeah, I play drums. Yeah, poorly because of this teacher.

[00:15:39] Steve: But yeah, I was in bands and stuff when I was, you know, a teenager. Um, and he was obsessed with, I want to teach you this, but I’m not going to show you how it sounds. I want you to look at the music to read the score. Which is fine if you want to be someone who’s going to be a drummer in an orchestra, but I just wanted to be Kurt Cobain.

[00:16:00] Steve: I just wanted to be Dave Grohl, right, in a band. And I was much better at listening and hearing it and then translating it to my hands, and he would never teach me that way. And in hindsight, I should have said, listen, pal, I’m playing you here. Just show me a way that gets me there. Don’t worry that you want me to learn that way.

[00:16:17] Steve: People have different learning modalities and it’s such an important thing that just gets forgotten.

[00:16:22] Cameron: And as we’re learning more and more, you, you know, you and I both have neurodivergent kids and y and we’re learning more about neurodivergency. I guess in the modern world. We are realizing, like everyone has a brain that’s a little bit different from everybody else’s, and they need different ways of tackling things.

[00:16:39] Cameron: And one of the

[00:16:40] Cameron: exciting things about, you know, uh, uh, uh, the world we’re moving into is everyone’s gonna have. Their individual tutor teacher for every subject that’s totally customized to their brain, their

[00:16:53] Steve: ever.

[00:16:54] Cameron: Oh, it’s fantastic. It’s incredible. Anyway, speaking about incredible things We’ve talked about Neuralink.

[00:17:00] Cameron: Elon Musk, your favorite guy, and his brain chip.

[00:17:05] Steve: man who’s done extraordinary things. Just a bit weird. That’s the price.

[00:17:10] Cameron: We mentioned, I think, late last year that they were getting ready to do human trials. We mentioned when they did their first human operation. And in the last week or two, they released a video of that patient. He’s a young guy who, about, I think, 8 or 9 years ago, had a diving accident. Diving, like, dived into a pool, broke his spine.

[00:17:32] Cameron: and has been a quadriplegic ever since they put the chip in his head and they’ve had videos of him playing chess and other games just using his mind but the thing the the biggest thing I got out of the video was just the giddy joy that this guy has for what this technology

[00:17:52] Cameron: has enabled Him, in terms of improving his quality of life, already, the first fucking patient, and he’s

[00:17:59] Cameron: like, just giddy as

[00:18:01] Steve: You know,

[00:18:02] Cameron: what this is doing

[00:18:03] Steve: I was wondering what you’d say and, and the thing that I noticed, It’s just the joy and the story that he stayed up till four in the morning playing video games. I was like,

[00:18:12] Steve: gee, I mean, that, that’s, you know, the, the emancipating power of technology. It really is extraordinary. Um, so sort of, I noticed that, uh, the fact that it was in hospital for a day.

[00:18:24] Steve: And one of the other things that I thought interesting in his, interview was how at first when he was moving the chest part in his mind he was saying move one up right two left and then in the end he realized he didn’t even have to give it these verbal instructions he just had to intuit it as in where he wanted it to go without in his mind saying the steps of the exact you know x goes across y up like that that was really cool for me that and you just think

[00:18:55] Steve: okay this is early days if you can intuit To move things with your mind? where where this goes? I mean, let’s be honest, this is pretty extraordinary, right? Where this could go.

[00:19:06] Cameron: And he did talk about the fact that there was sort of a bit of a learning curve when it was in his head, like, I’m not sure, I couldn’t tell from what he was saying if it was he needed to learn how to use the chip or the chip and the brain were melding together and it took a little while for it to all come together, like with new neurons growing that were

[00:19:31] Cameron: figuring out how to do this neuroplasticity type stuff.

[00:19:35] Cameron: But anyway, like for the first human experiment to be that successful, now the guy might.

[00:19:43] Steve: Look, Ham, there was, there was 86 people that died in the operation, but they weren’t in the video, right? I mean, that, that is what they leave out. They always leave out the testing, Cameron. We saw the one guy, let’s

[00:19:56] Cameron: Elon’s, Elon’s got one of those, like, he’s got an underground bunker with those tubes in sci fi films with all the failed experiments that are all like, they’re still alive, but they’re like,

[00:20:08] Steve: Yeah, it’s like that movie Moon Where? he had like a hundred clones of himself,

[00:20:12] Cameron: yeah, yeah, that was a, good movie. Sam Rockwell, love Sam Rockwell, um, directed by David Bowie’s son. Duncan, um, Jones, I, me, apparently, I did,

[00:20:24] Steve: um, there

[00:20:26] Cameron: I, I happened to re watch the, uh, Black Mirror episode from the first season of Black Mirror the other day, it’s the one where everyone has memory implants, and the guy thinks his wife’s having an affair, and then he, he, he Um, you know, gets the guy he thinks she’s sleeping with to delete all of the videos and then he gets her to play back her videos of fucking this guy and it’s, it’s, it’s pretty gruesome.

[00:20:51] Cameron: The two things that really jumped out at me at it, one was, you know, they’ve got a little chip behind their ear and this episode came out. I probably, what, 10 years ago? And, and I’m like, wow. And so it’s like in the same week, I watched the Neuralink video guy and then this, and I’m like, oh shit, we’re so

[00:21:09] Cameron: close to that.

[00:21:12] Steve: uh, Twilight Zone. Uh, episode, there’s two of them, the rehash version in the late 80s, early 90s and way back in the 60s, there was one where you could sell memory. So you would go into a place and you would sell cool things that you did that other people would upload to experience the things that you had that they hadn’t experienced.

[00:21:33] Steve: And he had sold so much and poor people sold the memory, like, you know, poor people sell blood, like it was classic dystopian thing.

[00:21:38] Cameron: You lose it when you sell it. You’re

[00:21:40] Steve: Yeah, you lose it. You lose it, right? You don’t get to keep it. There was no, there was no, um, you know, copy and paste. It was like, copy and delete, right? And this guy sells all of

[00:21:50] Steve: his memory to stay alive because he’s poor.

[00:21:52] Steve: And then he gets some money, he goes, I want my memories back, right? I go, we can do it, but it’s not perfect. He goes, it’s not perfect. So he comes in and they upload some memories and then they show him at a job interview and he goes, wow, when I was a 12 year old girl, I studied ballet. And then when I studied physics and it’s all like these other memories of people that just bashed into his world, pretty, it’s pretty cool.

[00:22:12] Steve: I mean, it’s interesting that it’s interesting that this has been an idea that we’ve been playing around with for a long time, because. If we think about, you know, even Sagan, you know, calls it in Cosmos, which you gave me the first copies of. I was, you gave it to me to, to, to watch that. You burnt it on DVD for me back in the day and I watched it.

[00:22:30] Steve: Um, and he calls it the persistence of memory and that through history, we’ve created different ways for memories to persist through song, you know, through storytelling, through cave wall drawings, all the way up to the internet era. And it’s so interesting that this is Part of that still,

[00:22:45] Cameron: Mm Yeah. I, I was rereading the Epic of Gilgamesh recently.

[00:22:52] Steve: have you got 73 hours in each day? Because it seems like you read, you know, 73 times a week. You’re doing maths. You’re learning Italian. You’re busting out code. Look, can you just throw me a couple of those extra hours that you have in your day that I seem not to have? Because I reckon you’re pulling 72 hours in every daylight cycle.

[00:23:12] Cameron: I just, I chunk of my time down, um, to like 15, 20 minute. Segments. I’m going to do 15, 20 minutes of this, 15, 20 minutes of that.

[00:23:20] Steve: Now you’re starting to sound like one of these TikTok efficiency hackers who I’m really no fan of, just quietly.

[00:23:27] Cameron: I don’t know

[00:23:28] Steve: What I, I love the, I’m sorry we’re going off piste here, but I love, uh, the guys who take the piss out of these efficiency and life hackers. It’s like, what I do is I get up at two in the morning and I’m going to swim four kilometers in an ice cold pool that I made with my billions of dollars that I did on TikTok.

[00:23:44] Steve: It’s an ice cold pool. I’ve got ice blocks in the pool and I swim four kilometers. Then I get up and I have 16 egg whites. By this time, it’s 4. 33 in the morning.

[00:23:55] Cameron: It’s like Mark, um, Marky Mark. And he’s always doing stuff like that.

[00:23:59] Steve: saw a video of him the other day saying all the things that he eats and working out and

[00:24:04] Cameron: Second thing that I took away from the Black Mirror episode is how bad the AI voices are. Whenever they’re activating their memory chip system, it says, I’m sorry, but I can’t find the AI, but it looks like this. It was kind of human, but kind of robotic, and like, they’ve got this advanced neural chip technology, but the voices, like, and by the way, this episode was written by Jesse Armstrong, the creator of Succession, one of my favorite TV shows of recent

[00:24:32] Steve: great show.

[00:24:34] Cameron: Um, so a great writer, but even when they were predicting this really advanced memory technology, they still didn’t think computer voices would be flawless. And it still is amazing to me, and we’ve got a couple of stories on voice technology, uh, coming up today, how quickly that was one of the first things to fall.

[00:24:55] Cameron: One of the things that science fiction writers thought was going to be the hardest to nail, computers having human voices, except for Hal. Hal, the original computer voice was perfect. Um, and one of the things that the sci fi filmmakers, TV makers have always thought was going to be obviously very difficult, turned out to be one of the easiest things to do.

[00:25:15] Cameron: One of the first bricks to

[00:25:17] Cameron: fall. Um, I’ve mentioned Claude Opus. Um,

[00:25:22] Cameron: NVIDIA, oh, NVIDIA had their developer day, their conference, developer

[00:25:29] Steve: mean concert, you mean rock concert with 10, 000 people in the audience.

[00:25:33] Cameron: Yeah.

[00:25:35] Steve: that, that, that came back as

[00:25:38] Steve: That was, that was the thing that was most notable to me. I mean, oh, there was two things. The first one was kind of, there’s been the touted end of Moore’s law for some time. And I noticed that in the video, he, he, he talked about how they’ve had a thousand X gain in a year, which kind of, Never happens.

[00:25:57] Steve: It’s pretty much been a doubling impact. So that’s, that’s significant. Of course, it’s not available to everyone. So you could say it’s a different regime of, of exponential improvement. So that was really important. But for me, you know, the biggest thing wasn’t, it wasn’t the chips. It wasn’t the, what do they call it?

[00:26:13] Steve: The, is it the, is it the Blackwell chip? Um,

[00:26:17] Cameron: Not a chip, Jensen says. It’s a

[00:26:20] Cameron: framework,

[00:26:21] Steve: framework. Okay.

[00:26:22] Cameron: platform.

[00:26:23] Steve: Platform.

[00:26:24] Cameron: It’s an architecture.

[00:26:26] Steve: Okay.

[00:26:26] Cameron: Anyway, keep going.

[00:26:28] Steve: For me, it was just Rockstar in a Stadium. For me, the thing that came out is the religiosity.

[00:26:38] Steve: Technology is really tapping into, uh, price earnings ratios, which are irrational, as irrational as religion, leaders who, uh, you know, vaunted up on the stage, laughing at jokes, which aren’t funny because of who said them.

[00:26:56] Steve: Uh, you know, the mystery of the unknown of the all knowing being, which is AI, it sort of has this God like thing to it. That, that was, I know that’s not what was meant to be the key takeout, but that was mine.

[00:27:10] Cameron: That’s not new, right? We saw that with Steve Jobs and the reality distortion field and all that kind of stuff. This is, Yeah. like there is something with humans where we do, we

[00:27:20] Steve: stadium? A stadium?

[00:27:22] Steve: Yeah,

[00:27:23] Cameron: yeah.

[00:27:24] Steve: I was waiting for Jimmy Swagger to come out and say, I have sinned against you, father. Send

[00:27:29] Steve: 5 for my new private jet. 5. Just 5 from everyone. The new private jet, Gulfstream 650.

[00:27:36] Cameron: Oh man, I have sat in a stadium at two o’clock in the morning with Steve Barmer. On stage and 40, 000 people in the room. Steve Ballmer going, developers, developers, developers, developers, developers, developers, developers, developers. I love this comp tree, no, company. I love this company, developers, developers.

[00:27:58] Cameron: Yeah, I’ve been there. I lived it. Um, anyway, back to Nvidia. So they, they, they announced Blackwell. Which is basically, um, I had to, I had to go to Bing co pilot to get it to explain it to me. Uh, this is what co pilot said, NVIDIA has just announced its new AI chip, the Blackwell, which is set to revolutionize the field of artificial intelligence.

[00:28:20] Cameron: The Blackwell platform is designed to power real time generative AI on trillion parameter large language models with significantly reduced cost. Cost and energy consumption compared to its predecessor. I think he was saying massive performance increase with about 25%. of the power requirement. They’ve managed with this and they’ve taken two, uh, silicon layers and merged them very closely together.

[00:28:47] Cameron: So they operate like one, doubling the performance of it, or more than doubling, because they’ve, you know, Done a whole bunch of stuff inside of the silicon. The Blackwell GPU architecture introduces six transformative technologies for accelerated computing, which are expected to drive breakthroughs in various fields, such as data processing, engineering simulation, electronic design, automation, computer aided drug design, quantum computing, and generative AI.

[00:29:16] Cameron: So it’s a big deal, but that wasn’t the only thing they announced. They announced a ton of things, including Project Groot.

[00:29:22] Steve: Yes.

[00:29:23] Cameron: is a general purpose foundation model for humanoid robots.

[00:29:31] Cameron: So, as

[00:29:32] Steve: I mean It was really

[00:29:34] Steve: impressive. I mean, I did think how much of it has been gamed. Uh, one of the things that we’ve noticed with a lot of demos, especially with humanoid robots, you know, Boston Dynamics famously made it look as though the robots were just doing this, but they had, you know, programmed them to do exactly that thing that you saw on the video.

[00:29:54] Steve: Uh, And, and I do wonder, and of course, if you can program it, eventually it can do it itself, but it was very, very interesting to see how LLMs are going to impact robotics. For me, that’s the super interesting thing. And you’ve spoken about using your natural language to generate code, which you can do on the screen.

[00:30:11] Steve: And if you can do it on the screen, you can do it via a humanoid. Robot, which then drops the code inside the bot to do what it does. And there is a sense of biomimicry about this because this is what we do. And we don’t exactly know how it works, but we use language to code our brains to do physical things with our arms and legs, right?

[00:30:31] Steve: It’s what we don’t know how that interface works, but, but it does. And this has a real strong sense of biomimicry about it. So the overlap with LLMs and robotics, you know, for me, I’m thinking this is almost. Like a blast from the past where we had mechanical structures for a really long time in farming and, you know, various elements, you know, in the agrarian era.

[00:30:54] Steve: And then when we added fossil fuels and internal combustion to the mechanics, you had this overlap with mechanical and fossil fuel and, and, and energy and power, and then you had a whole new era of, uh, Industrialization, which married mechanical and fossil fuel ability. So it feels like LLMs and robotics are going to do the same thing with humanoid robots and yeah, the fact that anyone can code it by visually showing it again, just like we do with humans or telling it verbally how to do something.

[00:31:30] Steve: You know, when I saw it, you know, from playing drums to juicing, it was interesting

[00:31:36] Cameron: Well, I think the, the, the key takeaway from this project group, which is being led by Dr. Jim Fan and Yuka Zhu at, um, NVIDIA is, so we, we, we’ve talked about this in the past, so we’ve had videos of robots, that have received some training data, usually watching a video of somebody making a coffee with a coffee pod or something like that.

[00:31:58] Cameron: And then it will train itself through trial and error over the next 12, 24 hours to do that and, and optimize its attempts until it gets it right, has a neural network built into it that’s helping it figure out which Which actions actually deliver the desired result and which don’t. What they, what they’re doing with Project Groot is using trillions of simulations.

[00:32:24] Cameron: So it, it enables robot developers to take the physical manifestation of their robot, you know, what it’s, what it looks like. It’s, it’s, it’s, uh, hardware, put that into. Uh, a GPU architecture, then give it the physical tasks, the training data that they want it to do, it then doesn’t have to run the

[00:32:48] Cameron: simulations or run the

[00:32:50] Cameron: exercise, the neural network training in the real world, it just runs it through it.

[00:32:56] Cameron: Millions of simulations, virtually, you, with the,

[00:33:02] Steve: It’s not doing, it’s just simulating, simulating, simulating, until it feels like what it’s got here, it can match there.

[00:33:08] Cameron: yeah, well it just, instead of having to do it in the real world, it just runs a million simulations, virtually, finds out what the right combination of physical actions is going to be to, to, to realize the outcome, and then it just does that one, straight off the bat, first time,

[00:33:28] Steve: crazy. Wouldn’t

[00:33:29] Cameron: and they’re, they’re providing the architecture to do that, so, Essentially, you know, in theory, you’ll have a general purpose robot.

[00:33:36] Cameron: You want it to do a new task. You’ll show it what the task is. It’ll, it’ll be like, uh, Trinity in the first Matrix film. When Neo points at the Black Hawk helicopter, says, can you fly that? She goes, now I can, I can now, right? So you go, Hey robot, can you cut my hair? And it goes, it just runs a million

[00:34:00] Cameron: virtual simulations in its head or in the cloud there, and then goes, yeah, okay, boom, sit down.

[00:34:07] Cameron: I know what to do. Doesn’t have to learn on the job. It learns through millions of

[00:34:11] Cameron: virtual

[00:34:12] Steve: what we should call this though? Because it has to go through it in its mind. We should call this meatloafing. Baby, baby, let me sleep on it.

[00:34:19] Steve: Baby, baby, let me sleep on it.

[00:34:20] Steve: And it’s going to sleep on it. overnight.

[00:34:22] Cameron: Let me sleep on it. Baby, baby, let me sleep on it.

[00:34:26] Cameron: Let

[00:34:27] Cameron: me sleep on it. I’ll give you an answer in the morning. I gotta know right now, do you love me? Will you love me forever? Will you leave me? Will you Oh man, another Meatloaf fan. Dude, we are brothers.

[00:34:42] Steve: sleep on it.

[00:34:44] Cameron: My wife’s

[00:34:45] Cameron: number one

[00:34:45] Cameron: hate.

[00:34:46] Steve: think they need to program into it when you show it something. It’s just a baby, baby, let me sleep. That’s what it needs. That would be a robot I would mortgage my house for. What? What?

[00:34:56] Cameron: like, one rule that we’ve had

[00:34:58] Cameron: in our relationship for 16 years is I’m never allowed to play meatloaf around her. If I, if I want to blast meatloaf in the car, I’ve got, yeah, no, hates

[00:35:05] Cameron: meatloaf. Hates, hates

[00:35:07] Steve: That, that is one of the greatest songs ever. And I went to a Catholic school, I just, it’s just, it was perfection. Paradise by The Dashboard Light, I mean, you cannot, you cannot. No,

[00:35:21] Cameron: Do you ever see him live?

[00:35:23] Steve: only on the, I only saw that terrible version of him at the AFL Grand Final.

[00:35:27] Cameron: Do you remember, um, You know where

[00:35:29] Cameron: the Tennis Center is in Melbourne? There used to be like a swimming pool right next to it.

[00:35:33] Steve: yes.

[00:35:35] Cameron: Uh, I saw Meatloaf play there.

[00:35:37] Steve: pool, on, on a pink flamingo. On a, was he on one of those Instagram worthy pink flamingos, with a glass of champagne and bikinis on? Please tell me he was.

[00:35:47] Cameron: It was circa, I’m guessing, 1989, 1990, somewhere like that. And it was killer, and the thing about it was, like, you could tell that he was so just overjoyed by the fact that he still had an audience. He did like four ENCORES, and just, he was like, really? You love me? You really love me? And we did, like, it was, it was epic.

[00:36:11] Steve: All need love, man. All you need is.

[00:36:14] Cameron: Uh, anyway, moving on from NVIDIA, um, Another big announcement in the last week or so. Microsoft, well it’s not an announcement really, it’s a rumor. Microsoft and OpenAI planned supercomputer

[00:36:25] Cameron: project worth a hundred billion dollars called Stargate,

[00:36:32] Steve: See,

[00:36:33] Cameron: up of millions of AI chips.

[00:36:36] Steve: wasn’t, didn’t, um, didn’t Sammy Altman come out and say we’re gonna need a trillion dollars for what we need

[00:36:44] Steve: to do with AI

[00:36:46] Steve: Uh, have you ever seen the movie Pixel? The short,

[00:36:50] Cameron: I haven’t seen.

[00:36:52] Steve: there’s a short film called, it was an eight minute movie. That was, uh, and it’s totally worth watching. It just, the world turns into a big video game.

[00:37:02] Steve: And in the end, the globe just turns into a big block that it’s just so, and everything becomes pixelated in the physical world and it’s a nice

[00:37:11] Cameron: Like a Minecraft block.

[00:37:12] Steve: Yeah, basically. But the thing that opened up to me on this is that, you know, corporations, again, we spoke about it before the podcast, you know, the level of power that corporations

[00:37:22] Steve: have. Uh, you know, this is. Nation state level investments by private corporations. Geez. I mean, you, I feel like you are in some way turning me into a Marxist, but I just can’t, I just can’t see this. I just cannot see the most powerful technology ever invented and governments with lack of courage to do what needs to be done, like we did in the Gilded Era.

[00:37:47] Steve: Where it’s. Irresponsible for private companies to, well, public private, yeah. Non state owned companies, let’s use that verbiage, to be in control of something so powerful, you know, making investments that are bigger than GDPs of countries. I mean, this is pretty significant stuff.

[00:38:08] Cameron: The proposed project costs about a hundred times more than some of the largest data centers today, and Microsoft executives want to launch it as soon as 2028, according to the information four years away. Now, interesting thing is we know that Nvidia, uh, unable to meet the demand

[00:38:28] Cameron: for their current ship sets like the A one hundreds, but, uh, meta Zuck.

[00:38:35] Cameron: Zuckerschmuck, as I think Trump calls him now, has said that they’re

[00:38:39] Steve: The Tim Apple, I love Tim Apple. We got here, uh, Tim Apple is here with us from Tim Apple and, and Elon Musk.

[00:38:50] Cameron: he’s gonna, he reckons they’re going to have 600, 000, I think it’s A100s, uh, by the end of this year, which will make that the biggest AI data center out there, but they’re talking about Taking this to a whole new level in the next few years. Millions of AI chips. Now, where are they going to come from?

[00:39:10] Cameron: Well, you assume this is what Sam’s trying to raise the money to do so they can build their own. But, like, what they’re going to do with this, uh, what that’s going to be capable of, who knows. But, This is, this is the world that we’re living in now. It’s the new space race. It’s the AI race. Who can build the biggest data centers that are going to require energy, power.

[00:39:33] Cameron: They’re going to require cooling.

[00:39:36] Cameron: Uh, I know Microsoft’s already struggling with cooling their data centers in places like Arizona, the amount of water that they need to use and

[00:39:45] Cameron: get into the desert.

[00:39:47] Steve: on a flip note. The wave pool that I surf in, in Melbourne, you know, artificially generated waves, artificial intelligence. I’m working with the guys there on a local data center that needs cooling, where we’ll take the cold water from the pool, circulate it through there to warm up the pool and cool down their, uh, their data center at the same time.

[00:40:08] Steve: It’s a really, really cool idea.

[00:40:11] Cameron: powered. Supercomputer.

[00:40:14] Steve: Yeah. But that’s, that’s kind of interesting because that’s basically where most energy goes. It goes into heating or cooling things. Basically, you know, thermodynamics is what climate change is built upon and we just need to do both in both directions, which is what we don’t do. We tend to heat something up and then just let it all go or cool something down and just let it all go.

[00:40:39] Steve: But what you need is this cyclical nature of where you heat and cool things. Anyway, just a little bit of a tip for the listeners there.

[00:40:46] Cameron: Well, Sam is, uh, in recent interviews, Sam Altman is predicting we’ll have AGI roughly in the next five years, maybe a little bit longer, he says, but roughly around

[00:40:58] Steve: We’ve got it now. Anyway, I’ve said that a few times. We have AGI. We don’t have SGI.

[00:41:04] Cameron: Well, it depends on your definition of AGI as we’ve discussed. I mean, the definition I think guys like Sam are using is when

[00:41:13] Cameron: the AI can do every task at the same or better.

[00:41:20] Cameron: level than a highly qualified human could do it at.

[00:41:24] Steve: That’s an SGI in my view, but okay, let’s, let’s just go with AGI. I get it. The definitions

[00:41:28] Steve: are important, but that’s significant, man. I mean, if that’s three, even if it’s

[00:41:33] Steve: 10 years, like hold

[00:41:36] Cameron: saying they’re actually saying ASI in 10 years, AGI in 5, ASI in 10. Um, Jensen Huang, I’ve seen some interviews with him recently, the CEO of NVIDIA. He’s saying the same sort of timeline. And when people, uh, he’s quite funny and snarky. When people ask him about Oh, what about hallucinations?

[00:41:58] Cameron: And what about this? And what about that? He’s like, that’s nothing. We’re going to solve that easily. It’s just, you know, these guys seem to be convinced that it’s just the level of compute that they’re able to throw at this thing. It’s no, no biggie. It’s just a level of compute. It’s about looking at the architecture that they put into the LLM engines.

[00:42:15] Cameron: Again, basically the suggestion is. All of the problems that people

[00:42:20] Cameron: see with LLM based AIs at the

[00:42:22] Cameron: moment are just teething issues that we haven’t even got to sorting

[00:42:25] Cameron: out yet, but we’ll, we’re going to nail them. It’s not going to be a big

[00:42:27] Cameron: deal. Just, it’s just time, money, compute.

[00:42:31] Steve: We were there with a couple of other things. I mean, one of the areas that that was present in the fifties and the sixties with fossil fuels with it’s an interesting analogy, and maybe this is different and it is definitely a different technology, but with air travel, it was like, wow, we’re just going to be traveling at 10 times the speed of sound because it’s just a matter of just engineering.

[00:42:53] Steve: And they, and they believed that. And then we,

[00:42:57] Cameron: Did the engineers believe that, or was it just the media,

[00:43:00] Steve: oh, I don’t know, I’m not sure, but that, that was a strong narrative which didn’t turn out, we sort of got to a point where it flattened out. But on the long arc of computational history, and I always love what Kurzweil did where he says what people don’t realize with Moore’s Law is that we’re already in the fourth phase of it, you know, first it was punch cards, then it was vacuum tubes, then it was transistors, and, um, yeah, but it’ll be

[00:43:24] Cameron: First it was clay tablets,

[00:43:25] Steve: there, there you go, yeah.

[00:43:27] Steve: Yeah. And it’s, it’s basically, yeah, there’s all these different curve jumps and epochs of technology, which are now allowed more information to be stored and translate and so on. Um, so maybe

[00:43:39] Cameron: Well, Elon says three

[00:43:41] Cameron: years. He says we’re three years from AGI. So he also thinks we’d all have electric cars like five years ago, but you know, he should take it or

[00:43:49] Steve: he said by 2019, they’d have a million robo taxis on the road and I am still waiting.

[00:43:55] Cameron: Well, either way, like the timelines for AGI, like these guys are. Let’s say Jensen and Sam. We’ll leave Elon out of it for a second. But Sam and Jensen are talking like it’s a done deal. Next five, six years, it’s basically

[00:44:13] Cameron: gonna happen. Um, and in, in our futuristic forecast later on, I want to talk about, a little bit about what that might mean.

[00:44:21] Cameron: In the meantime, open, uh, I mean, oh, look, so many news stories,

[00:44:24] Steve: There’s a lot.

[00:44:25] Cameron: We’re going to do them all?

[00:44:26] Steve: three real quick. Let’s just go real quick through them Just, just bam.

[00:44:30] Cameron: Amazon, I’ve launched a new tool for creating AI based audiobooks, putting a whole industry of people basically on their arses. Maybe not tomorrow because it’s still not perfect. Seen some of the early people reviewing it saying they don’t do emotion very well. But basically, you know, very good, uh,

[00:44:49] Cameron: content.

[00:44:49] Cameron: Quality AI generated voices. If you’ve written a book, you want to turn it into an audio book, you don’t need to pay someone to read it. You just pick from a range of voices and it’ll read the book and

[00:44:59] Steve: I like it. Look, it’s put some people out of work, but I think it’s going to give more independent authors, a bigger audience. And I think that’s better.

[00:45:07] Cameron: If anyone’s going to read books, like I personally think books, I mean, already people don’t read books. I mean, the stats say that you and I are part of the only generation left that really read books. Most, most people don’t read books. And, you know, my, my, my boys.

[00:45:24] Cameron: Hunter and

[00:45:24] Cameron: Taylor don’t read whenever I say, what are you, what are you reading?

[00:45:28] Cameron: They go, if I want to learn anything, I’ll watch a YouTube. I don’t need to read a

[00:45:32] Cameron: book. I’m like, really? That’s like, so

[00:45:34] Steve: do wonder if you, if you get, and I don’t know if there’s been studies on it, if you get more knowledge by staying in an idea in a different form than, than video, I don’t know. And again, this comes to different ways that people learn and maybe our brains will adapt to learn through video and absorption.

[00:45:49] Steve: I find that I listen to a lot of things now that I would have read in the past, even long articles. I’ll just get Siri to read it to me while I’m driving, because I haven’t got time to read all the articles, so I just get them read to me while I’m driving, um, which is cool, but I like that, I think that’s a good thing. Next.

[00:46:07] Cameron: before that, OpenAI have just started talking about their voice cloning tool, which they said they used to build the text to speech generation, which is, still blows me away, in their, uh, They seem to have that ready to go. They reckon it can take 15 seconds of

[00:46:26] Cameron: your voice and perfectly replicate your voice.

[00:46:29] Cameron: A bit like Haygen’s stuff, but they’re reluctant to release it, release it publicly, uh, in this election cycle. Um,

[00:46:37] Steve: late, that’s not gonna, I mean, we can do it anyway, I mean, they might be able to do it quicker,

[00:46:41] Steve: but there’s some pretty good versions of it right now.

[00:46:44] Steve: Yeah, Synthesia does a pretty good version of it as well, and HeyJen can do it pretty well.

[00:46:49] Cameron: Yeah, um, and the, the tool Descript that I use to edit podcasts with does a, has its own, it needs about 60 seconds of audio, but it does a pretty good job. I’ve

[00:46:59] Steve: of your

[00:47:00] Cameron: of times. Yeah, of my voice, if I’m editing a podcast and I go, Oh, I forgot to say this, or I should have used this word instead of that word, instead of re recording it, I just type in the

[00:47:12] Cameron: word or the sentence that I want to say, and it just does it in my

[00:47:15] Cameron: voice. It’s not perfect.

[00:47:17] Cameron: Descript, D E S C R I P T.

[00:47:22] Steve: You sure it’s not a triple T.

[00:47:23] Steve: Like a triple D dig? Just checking.

[00:47:27] Cameron: No, it’s not 1998, man. If it was 2005. Um, more on the news. Apple.

[00:47:35] Cameron: There’s rumors that Apple’s going to put Google’s Gemini app into the next version of the iPhone. Now,

[00:47:43] Steve: idea.

[00:47:44] Cameron: terrible.

[00:47:45] Steve: That is, that would be one of the worst

[00:47:48] Steve: corporate strategies you’ve ever met. We’re talking about a company with more money in the bank than God. Who has every resource, can go and take any AI developer anywhere from the world, has everything at their disposal, and they’re going to hand it to one of their biggest competitors?

[00:48:06] Steve: Like, think about it, the iPhone versus Android, that would be the worst corporate decision that Tim Apple could ever make. Like,

[00:48:12] Cameron: It suggests to me, though, that they’re not ready.

[00:48:16] Steve: Get

[00:48:17] Cameron: That they,

[00:48:18] Steve: Get ready. No, no, it’s

[00:48:19] Steve: simply Well, It’s But isn’t it? We live

[00:48:23] Cameron: No, because you can’t get, you can’t get NVIDIA chips. You just cannot get them unless they

[00:48:31] Cameron: buy out Microsoft or buy out OpenAI and get their chips. You, NVIDIA literally can’t sell you any. They’re, they’re booked 18

[00:48:42] Cameron: months

[00:48:43] Steve: alright, so if we had to say, it’s an infrastructure challenge, or a

[00:48:49] Steve: software challenge, you

[00:48:50] Steve: would put infrastructure at the top of

[00:48:52] Steve: that challenge.

[00:48:53] Cameron: It’s a combination of infrastructure and.

[00:48:57] Steve: Development time?

[00:48:59] Cameron: Developers. Like, where do you get a thousand top level AI

[00:49:05] Cameron: developers from?

[00:49:06] Steve: Well, you get them from one of those three places you mentioned. Yeah, that’s where you get them? Or you buy, or you

[00:49:12] Cameron: They’re already getting on salaries of millions of dollars in options and all that kind

[00:49:17] Steve: Yeah, Apple could do that. I mean, I don’t think that the economics of it would stop Apple. You’ve got to put that aside. You just literally have to because they could pay whatever they needed to.

[00:49:28] Cameron: the next story is that the CEOs of Stability AI, the guys behind Stable Diffusion,

[00:49:34] Cameron: and the CEO behind Inflection, the Pi app, that we’ve talked about a few times have both left their companies along with some of their other senior execs to join Microsoft.

[00:49:45] Steve: my point. Money will get anyone.

[00:49:49] Cameron: Well, no, but it’s not money. It’s that their apps are failing. They’re, we’re already in the Stage where some of the biggest AI plays that have received hundreds of millions of dollars

[00:50:03] Cameron: of venture capital are already giving up the ghost and going, can’t compete. They can’t

[00:50:10] Cameron: compete with OpenAI, with Google, with Meta,

[00:50:14] Steve: the problem is if, if, if Apple lets, uh, Gemini do it, they’re going to have the same

[00:50:22] Steve: problem they’ve got with

[00:50:23] Steve: Apple Maps on a smaller scale, where someone else had it, it has it reinforced learning, it gets into that cycle. It’s taking the data from Apple users. Now, whether or not it’s a general AI that is Let’s say, like a ChatGPT that is native to the iPhone, or whether it’s not the personal AI that you and I have spoken about a number of times.

[00:50:43] Steve: Imagine your personal AI which has your data and becomes your personal co pilot or assistant. Um, it depends on what area of the market they approach with that. Uh, maybe if they approach the general one and work on their own personal AI, which I think they have to do, Like they have to otherwise, cause if they don’t have that in the long run, then I think their entire iPhone, uh, regime is at risk because that’s what we’re heading towards where you have a personal AI, which integrates with your operating system.

[00:51:14] Steve: And if they don’t have one of those, then, then they lose the operating system game.

[00:51:20] Steve: Maybe Microsoft makes a comeback with a, uh, a device. Yeah. Maybe they come back with a phone or something up. No, I’m, I’m serious.

[00:51:28] Cameron: Yeah,

[00:51:30] Cameron: it’s possible. I know OpenAI, as Sam’s been

[00:51:33] Cameron: talking about, like he’s supposedly got a project with, um, Johnny Ives. Yeah, to develop something. Haven’t heard anything about that for a while. Well, uh, you wanted to talk a bit about Bitcoin before Yeah. Well, well this is the deep dive, right? So let’s just.

[00:51:49] Steve: Pull into the deep dive and Bitcoin has had record prices. You’ve seen

[00:51:53] Steve: it’s was 73, 000 USD, which, which is extraordinary. I had a look at when I first wrote about Bitcoin on my blog, and I bought my first Bitcoin, some of which I’ve got still, um, and some of which I really, really wish I could find, uh, was 2013, 2013.

[00:52:13] Steve: It was 13. It was 13 for one Bitcoin. Yeah. Anyway, um, so I noticed a story in Wired magazine that they said, you know, what’s behind the record prices of Bitcoins and their heading was vibes mostly, which I loved, right? Because our Australian listeners would know about, you know, it’s Mabo, it’s the vibe of it all from the castle.

[00:52:37] Steve: And it just, I just wanted to deep dive into what is currency and currency really is a form of technology. It always has been. Every epoch of human technology has resulted in a new currency. We go through times, um, you know, barter economies had cowrie shells, uh, the agrarian state had grain receipts, uh, during the age of discovery had bills of exchange, uh, we had ferrous coins at the start of the industrial era, and then fiat currency, which is our current epoch.

[00:53:07] Steve: And all of these had prominence during certain tech eras. I wonder if we’re in crossover mode now where most currency is digital, it’s just numbers in a machine and a new form of digitized promissory notes. Um, I mean, we’ve only got about, I think in Australia it’s about 8 percent of all money that there is a claim to actually exist in the physical state. And it’s, you know, generally single digits anywhere around the world in the modern economy. But I just can’t think, can’t help but think that Bitcoin will never really be a currency.

[00:53:38] Steve: Uh, because we have to have a number of things for, for a currency to succeed. Scarcity, it’s got that. Um, fungibility, you know, any currency, any Bitcoin is equal to any other currency. It’s got that. Durability, I guess it’s got that. Divisibility, portability, I’d put a question mark around and acceptance, I’d put a question mark around.

[00:53:57] Steve: Um, it also has high transaction costs, which are a problem. So I’m just, I just wanted to dive into what. Currency is, I do think that we’ll end up with GovCoins, which are programmable currencies, where different currency you get from the government has different rules around it. Some of it will be open and some of it will be closed.

[00:54:17] Steve: And that’s a great way to do transfer payments so that money doesn’t get squandered. For example, let’s say someone is on, uh, unemployment benefits. You could say, well, it can’t be spent on alcohol or gambling, which would be great. You got to put that money in, And it saves people. I mean, it sounds draconian, but it makes sure that kids get fed and money goes to the right places.

[00:54:37] Steve: Uh, I think the programmable currency will be interesting, but another one is it needs to be a store of value, which Bitcoin isn’t. A store of value isn’t just about something going up over time. It shouldn’t go down at any point in time either. The reason it’s called a store of value is if you have a, Uh, you know, a silo of grain is still a silo of grain.

[00:54:55] Steve: You know, the bugs and the birds might get a few, but they don’t get it all. Right. There’s it’s a store of value. So

[00:55:01] Cameron: people call gold a store of value and it goes up and down.

[00:55:06] Steve: you’re not, not as dramatically right. Not as.

[00:55:09] Cameron: No, nothing goes up and down

[00:55:11] Steve: Well,

[00:55:11] Cameron: dramatically as

[00:55:12] Steve: The volatility, it’s, it’s the level of volatility that

[00:55:15] Steve: is the main issue. And I just wanted to know, I mean, I’ve obviously given my deep dive on what a currency is, on what your thoughts are on Bitcoin, where it is now,

[00:55:23] Steve: and, and and we may as well just weigh in on it, given that it’s, it’s had hit another all time high.

[00:55:30] Cameron: Well, I liked, you know, Tony and I talk about Bitcoin a lot, um, on our QAV show, because obviously a lot of people

[00:55:37] Cameron: tout it as an investment and the, and Torsten Hoffman, the guy who produced my documentary, uh, also produced a documentary, two documentaries. on Bitcoin. He’s done over the last five or

[00:55:49] Steve: I’ve watched them, they’re both really Good. Yes,

[00:55:54] Cameron: with him. I’ve been having it with him for three or four years now where he tries to advocate for Bitcoin as an investment, not as a currency, but as an investment. And I keep coming back to my fundamental question. I’ve been asking this for four years. How do I determine the value of a single Bitcoin?

[00:56:14] Cameron: And he says, well, you know, it’s going up. And now the answer is always there’s a limited number of them and the wide article that you pointed to I think made a really good point, which is if you accept the basic premise of economic theory that we have these days, it’s that the scarcity value of it, the known, which is the scarcity value of it, has already been factored into the price.

[00:56:42] Cameron: Basically, when you’re, when you’re investing in shares, I mean, I don’t subscribe to. the idea of perfect knowledge and rational markets because, you know, I think behavioral economics, oh, RIP Daniel Kahneman, by the way, the sort of one of the fathers of behavioral economics, he passed away age 90 this week.

[00:57:02] Cameron: You’ve read Thinking Fast and Slow, I assume, one of the, one of the greatest books I’ve ever read. Um, you know, we know that people don’t make purely rational decisions, but leaving that aside, the, the, idea that the value of a Bitcoin is going to be worth more in the future than it is today, because there’s a limited number of them ever going to be made should already be factored into the price.

[00:57:27] Cameron: But you know, in terms of an investment, I think, you know, it basically survives on the greater fool theory. People just think if I buy it today, I’ll be able to sell it to some idiot next year for more money. What’s the intrinsic value of a single coin? No one can tell me that. So, you know, you know, the basic The way that Tony has taught me to invest over the last five years or so we’ve been doing the show is that the, there are, there

[00:57:52] Cameron: are two kinds of

[00:57:54] Cameron: investors.

[00:57:56] Cameron: People that have a rational thesis for how they invest. And Punters.

[00:58:03] Steve: Yeah, sure. And punters get richer every now and again. This

[00:58:08] Steve: is

[00:58:08] Cameron: they do.

[00:58:09] Steve: that

[00:58:09] Steve: and this is the problem. Because you can and have got rich on Bitcoin, they can say, yeah, but look, yeah, but look over here,

[00:58:16] Cameron: But then survivor bias kicks in, and you look at the one guy that made money out of it, and you ignore the 99 guys that lost money. So, but, the starting point, if I talk to anyone about investing these days, it’s, okay, there are two kinds of investors. Somebody with a rational thesis, And somebody who’s a punter.

[00:58:35] Cameron: Which one do you want to be? If you want to be a punter, can’t help you. If you want to be the rational investor, you need to have a framework that, that informs your investing. You need to have a rational theory that informs your investing. And the basic theory that Tony has taught me, the value investing theory, is only buy shares.

[00:58:57] Cameron: in companies that have a good track record of

[00:58:59] Cameron: generating cash and only buy them when you can get them in a discount to their intrinsic value and then hold them until they break one of your sell triggers. And you

[00:59:10] Cameron: know, we, we have a range

[00:59:12] Steve: Benji Graham,

[00:59:13] Cameron: It’s Benjamin Graham, Buffett, Munger. Very, very

[00:59:17] Cameron: basic.

[00:59:17] Cameron: It’s worked for a long time. Theoretically, it should continue to work. Uh, so when you try and, determine the intrinsic value of a Bitcoin, no one’s been able to give

[00:59:28] Cameron: me

[00:59:28] Cameron: a model,

[00:59:29] Steve: and, and, and never be able to. I mean, it comes down to, to, um, it doesn’t generate cash and never will,

[00:59:34] Steve: because currencies don’t. And people have been speculating on currencies and metals

[00:59:38] Steve: and pink sheets and all that for a really long time, right? So that is going to continue. Uh, but you know, the thing that And speculation, people say, oh yeah, but I make money when I sell at a higher price.

[00:59:51] Steve: And I use the example often, you know, I love looking at nature as an allegory for investing. And I say, look, if you, if I planted a lemon tree and it never had any lemons, would you want that tree, no matter how tall it gets? And they go, well, you can chop it down and sell the wood. You can, but I don’t think that’s a good strategy.

[01:00:09] Steve: You know, for me, it’s like, show me the yield and all investing, like you say, the value of that and the cash flow is the yield. That’s what it comes down to. And while you can make money out of things that never have yield and some powerful companies don’t have dividends, but they still have yield because they’re still generating cash.

[01:00:26] Steve: Right. And that’s the thing that’s important. And if there’s no yield, then I’m just not interested because yes, you can make money, but not the way I go about it. And that’s really interesting.

[01:00:36] Cameron: and it comes down to, do you want to be able to sleep at night? You know, do you?

[01:00:40] Steve: It’s one of my favorites.

[01:00:41] Cameron: So anyway,

[01:00:41] Steve: And

[01:00:42] Cameron: I look.

[01:00:43] Steve: afternoon.

[01:00:44] Cameron: I want to ask you about this idea of government crypto. Um, I like your idea of programmable currency. I’ve never really

[01:00:49] Cameron: been able to understand, though, what a cryptocurrency would offer, say, the Australian government over and above fiat currency that we

[01:00:59] Steve: so a

[01:00:59] Cameron: the advantages and disadvantages?

[01:01:01] Steve: this is what the Ethereum network was built

[01:01:03] Steve: upon and why I think that that is a currency that might be able to be

[01:01:06] Steve: used through the internet of things and various forms of trading, energy trading, the

[01:01:11] Steve: energy internet. the

[01:01:12] Steve: idea is basically that a currency, if it’s Turing complete and has programmability, um, not all currencies are the same.

[01:01:19] Steve: So they’re not fungible. One, one Gov coin isn’t the same as one other. They’re not exactly exchange like. They’re not exactly the same. So the idea is that the government would be able to give you currency with certain rules or protocols built into it. So if I earn money in my job, that money goes to me and that money, let’s call it AUC, Australian Crypto.

[01:01:43] Steve: It’s one for one with the Australian dollar or USC. And what would happen is we would have different types of money that we have. In our apps and our banks where we have different balances for different types of money. The money that you earn and you get in the open market is an open currency. It can be spent on anything that you want to spend it on.

[01:02:04] Steve: But then on the flip side you might have currency which is closed currency that can only be spent on certain things and it would be programmable where you can only transact. with certain organizations. Now each organization that is registered and accepting money through digital forums, whether it’s FPOS or credit cards, is Uh, we know what type of organization that is.

[01:02:27] Steve: It sells foodstuffs, for example, or it’s transport. Like, we already do this. Like, this already happens in the marketplace. So, every, every form of trading, the government knows the type of business that you’re trading with or the product type that you’re getting. So, let’s say, uh, kids get allowances, uh, you have like a child endowment.

[01:02:46] Steve: It used to be called that when I was a kid. I don’t know what it is now, but people get payments. Uh, for their children to spend on certain things. Now the government, if it was clever, would say, Okay, here’s your child endowment for the month. It can be spent on transport, clothing, food, electricity. Can’t be spent on these other things.

[01:03:03] Steve: Or if it’s just a kid getting Austudy. Can only be spent on, uh, transport, books, school fees. That’s it. That’s it. That’s what it gets spent on. And then that way, uh, you would reduce the leakage and the wastage of things getting spent on the wrong things and what they were unintended for by using this code.

[01:03:23] Steve: And you can see how this could be translated to many different things. Like, for example, during COVID. All of these companies got given a whole lot of money. Well, if the government had given the money for the JobKeeper, that money can only be transferred to an employee as staff. And at the end of it, if it isn’t, then we have to give, take, we take that money back.

[01:03:42] Steve: So all of a sudden, you get a far more efficient use of the tax base. By allocating money for where it is meant to go. At the moment, what we say is, what person are you and do you qualify? Here’s the money. And then you cross your fingers that they spend it in the right spot. GovCoins that are programmable allows that ability, which I think would be great.

[01:04:02] Steve: Now, there’s danger could become Particularly draconian and, and, and you can see the obvious downsides, but I think it would be a really good use of a crypto style currency.

[01:04:13] Cameron: Sounds like a whole new level of complexity and central planning required to drive it, But

[01:04:19] Steve: no, but we already do that now. No, I’ll, I’ll, I say that that already happens now, but what we have is, Decisions made with that complexity on who gets the money.

[01:04:31] Steve: We just don’t know if it gets spent in the right places and goes to the right people. So that complexity already exists, but instead of just filling out paperwork and then sending the money to someone, you just add a layer to that currency, which basically says.

[01:04:44] Steve: What it spent on. And all it does is when you go to spend it and you wave your card, it goes beepp or it goes ding, ding, access denied. That’s it. It’s not that hard.

[01:04:55] Cameron: Except you gotta go, okay, well, how much money do I have? Well, I’ve got this amount of money, but I can only spend it on these things, and that amount of money, but I can only spend it on these things,

[01:05:03] Steve: Well then, again, that’s not that hard. Let’s say there’s 10 categories

[01:05:07] Steve: of things you can, you can just say, can I spend it on this

[01:05:10] Steve: or that? How much have I got in open currency? How much have I got in education? This, this, what the other things are? There’s probably only 10

[01:05:16] Cameron: there any other? Any other advantages to governments moving to crypto than allocation

[01:05:23] Steve: Yeah.

[01:05:23] Steve: um, where you, you get a whole different way that you can inject money into the

[01:05:28] Steve: economy. At the moment, the way that we do, uh,

[01:05:30] Steve: liquidity is we sell bonds, which is incredibly inefficient. Bonds get bought, uh, and then get transferred and you hope that that money goes into the right area of the economy.

[01:05:43] Steve: You can just release money to people to the right, straight away. And this is part of modern monetary theory. Cause I don’t, I don’t believe in the idea of using, uh, I think that there’s a whole lot of other benefits where it can get to the market more quickly and efficiently than going through selling money to, to companies with government bonds.

[01:06:06] Steve: Yeah, that’s what I think. But this is a big and developing area of economics. You know, crypto programmable currency and modern monetary theory, which says also that it doesn’t matter how much debt that the government is in, if it gives itself sovereign debt, it should never really sell to private corporations government bonds.

[01:06:27] Steve: If you have sovereign debt to build infrastructure, the danger with sovereign debt is they might spend it on transfer payments, which creates inflation. If it goes to a transfer payments, you get inflation. But if you have sovereign government debt that goes into infrastructure, which has a multiplier effect, you never have to pay your debt back.

[01:06:44] Steve: It doesn’t matter because you’ve built a new asset, which then gets used to create further revenue within the economy. It’s called Modern Monetary Theory. It’s really interesting. I’m into it. We should do a, you and, you and Tony should, should explore, yeah.

[01:06:59] Cameron: we did some shows about it back in the early

[01:07:01] Cameron: COVID years where it was being used to justify all the money that governments were printing

[01:07:06] Steve: But they weren’t, but they weren’t, but they were using it for transfer payments.

[01:07:10] Cameron: they used it wrong

[01:07:12] Steve: Yeah, they’ve

[01:07:12] Cameron: because they said that doesn’t matter. We can print money. It’ll never come back to bite us on the ass. And now we’ve had two years of interest rates going up and economies crumbling around the

[01:07:23] Steve: well, that’s the thing about interest rates. You know how the government, uh, the, the banks, there’s one of

[01:07:28] Steve: my favorite things people don’t realize is the interest rates go up and you’ve got a variable

[01:07:32] Steve: interest rate. That’s right. And then your interest rate goes up. I think 10 people would believe, well, now that the interest rates are 4%, the bank has to pay 4 percent out, so they have to charge me 6%.

[01:07:44] Steve: No, they already gave you the money. They gave it to you at 1%. That’s why their margins are so huge. People just don’t really think through just basic money in, money out. That’s what most investing in business and finance and economics is. It’s just like, Where did the money go in and where did it come out of?

[01:08:00] Steve: Like, just really basic in and out.

[01:08:04] Cameron: They got it when it was cheap. Now it’s more expensive. It doesn’t really matter because you got it from them when they got it when it was cheap.

[01:08:11] Steve: right, but then they charge you the expensive amount, but you’ve already been given the money. It’s like they changed the price after you bought the product.

[01:08:18] Cameron: After you bought it. Yeah. Yeah. Great scam. Um, well, I dunno, Steve, the whole, the whole crypto thing. Um, apart from the fact that I don’t think there’s a rational basis for using it as an investment, I, you know, I don’t really understand much about how it’s going to change the world of actual currency.

[01:08:40] Cameron: Um, I think the, the, the best argument I’ve heard for it is, um, um, Using it to prevent crime and fraud because it’s more traceable, where the money came from, the hands it goes through, how it ends up, like, makes it hard, would make it harder to use

[01:09:01] Cameron: shelf companies in the Bahamas, uh, to filter money through different levels.

[01:09:06] Cameron: You can, whenever some money gets spent, you know exactly where that money came from and who it went

[01:09:12] Cameron: to.

[01:09:12] Steve: well, the wallet can be anonymous. It’s the onboarding and offboarding. So, the KYC protocol, the know your customer. When someone gets into crypto, you have to use a fiat currency to get in. All right, unless you meet someone in a dark alleyway, which you can do, who gives you the code and you hand them cash, you can do that.

[01:09:29] Steve: And there’s some real like dark crypto believers who do that. They literally give cash to get like their 64 digit alphanumerical code to own that Bitcoin. Some people do do that so that they can be fully anonymous. But 99. 9 percent of people have come on board into crypto. Using a credit card or a traditional financial system. Once you’re in there, you can transact inside it anonymously. All I can tell is you’re on board and you’re off board, but inside there, it’s dark. You can be anonymous or you can be transparent.

[01:10:03] Cameron: There’s no way of tracing, um, the, so if, if money gets spent, let’s say, by a company that’s registered in the Cayman Islands to buy a, uh, an apartment building in Miami. Um, and you want to trace

[01:10:20] Cameron: where that money came from. There’s no way of, in crypto, of looking at the identification of that coin or those coins and tracing it back to its starting point.

[01:10:32] Steve: Nah, well you can trace back when someone bought a crypto, if they bought it in and it

[01:10:36] Steve: was the same wallet that sold or bought something inside it. But if you get inside the ecosystem and you’re trading

[01:10:42] Steve: inside it with different wallets and numbers, then whatever happens in there, the upside and downside can be.

[01:10:46] Steve: Fully opaque. It’s only onboarding and offboarding you can go.

[01:10:51] Cameron: so.

[01:10:51] Cameron: no real security advantages

[01:10:53] Cameron: then from a fraud

[01:10:54] Cameron: perspective. Because that’s what we, that’s, that’s really what we need to be able to do better, is to stop people using shelf companies,

[01:11:04] Steve: but I don’t think we do want that, because if we wanted that, because if you wanted that, you just stop it. You say, you’re not allowed to ever transfer money from here over to there. The end. Thanks for coming. It’s like multinational tax rorting. They act like it’s hard. It’s really easy. You just go,

[01:11:19] Steve: here, we do revenue assessment tax, same as land tax.

[01:11:23] Steve: It’s a percentage of revenue. It’s not, it’s not what you say profit is because you rented out your logo from yourself in a related party transaction. The fact that anyone acts like multinational tax avoidance is a hard issue to solve is fucking laughable. It’s an absolute joke. They’ve done it with land tax for 500 years.

[01:11:42] Steve: They just go, we assess the value of your land. Here’s your bill. Congratulations. Hi Google, you turned over 11 billion dollars in Australia. Here’s your 1 billion tax bill. You don’t like it? Leave. Bye. It’s

[01:11:55] Cameron: Only 1 billion out of 11 billion, really

[01:11:57] Steve: Well, no, that’s their tax bill.

[01:11:59] Cameron: Yeah.

[01:12:00] Steve: Well, 10 percent of turnover would be reasonable probably, let’s say.

[01:12:05] Cameron: For Google, really? I

[01:12:06] Steve: Yeah,

[01:12:06] Steve: probably not. But anyway, at the moment, you know, Google paid 200, 000 last year.

[01:12:10] Steve: I paid more tax than Google. I’m so much more successful than them.

[01:12:16] Cameron: All right, well, moving right along. Technology Time Warp, Steve.

[01:12:21] Steve: Well, we did that, didn’t we? No, we didn’t, we didn’t. Real quick one. My TikTok has been filled with 40 years

[01:12:28] Steve: ago, just everything, everything on pop culture. Uh, just two weeks ago was the Saturday that the Breakfast Club were on Saturday Detention, which I loved, but I thought I’m just going to throw real quick three tech things from 40 years ago.

[01:12:42] Steve: The 3. 5 inch floppy diskette was introduced. Reminds me of, remember there was the five inch floppy and the three and a half inch floppy. And the three and a half inch one was a stiffer plastic case. And I remember everyone used to get confused. There’s a floppy disk and a hard disk, which is one of my favorite things.

[01:13:02] Steve: Everyone used to say, no, I don’t want a floppy. I want a hard. It’s like, well, they’re both floppy. But anyway, let’s not get into it. The 3D printer was invented by Chuck Hull. In 1984, and he had a patent on it for a long time. He got two patents cause he had an evolution in it. And it was only in the 2009, I think that the patent came off and that’s when the market went crazy,

[01:13:24] Cameron: Wow.

[01:13:25] Steve: printing and the first digital projector.

[01:13:28] Steve: And I just want to say 40 years of digital projectors in corporate meetings, and they still don’t work. So I’m just asking some serious questions. So that was my time warper. Have you got one there for us, Cam?

[01:13:39] Cameron: Yeah, I’ve been reading a biography on Deng Xiaoping, um, recently as well, and, um, you know, just fascinated. It was about, it was like 1979 when Deng Xiaoping, uh, was the top man in China, took over from Mao Zedong. And, you know, you look at what has happened to China as an economy in the last 45

[01:14:02] Cameron: years, it’s really, uh, Astounding.

[01:14:05] Cameron: I was doing some research, um, last week, just looking at the GDP growth of China in the last 40 years. Um, yeah, go to the tape. You, you look at, um, I’ve got this article from, uh, science, uh, uh, business. net, Gross Domestic Expenditure and R& D in the billions by country. And you look at, you know, China, how quickly China has just blasted, just in the last 20 years, let alone the last 45 years, it’s just blasted through every other country, uh, except the United States.

[01:14:47] Cameron: If you look at Japan, uh, China’s R& D. In the year 2000 per annum was about 30 odd billion dollars. Um, at the time the United States’ r and d as a country was about $268 billion. In 2021, the US was 806 billion. So it grew, yeah, a little bit less than four times, say more like three times, grew three times in that period of time, China’s went from about.

[01:15:20] Cameron: 25, 30 billion to 670 billion in

[01:15:25] Steve: Wow.

[01:15:27] Cameron: in 2021. And I’ve been following the news, uh, from their recent two sessions where they all

[01:15:34] Cameron: get together and, you know, sort of figure out the next roadmap for China. They’re still talking about having a goal of a 10 percent year on year increase

[01:15:44] Cameron: in R& D.

[01:15:45] Steve: I thought you were going to say GDP, which they did. But that’s unsustainable.

[01:15:50] Cameron: 10%, you think? Why?

[01:15:53] Steve: Well, the R& D is possible and sustainable. They can definitely do that with their economy. I think it’s starting to

[01:15:59] Cameron: Uh, GDP. Yeah, GDP It No GDP growth. I think? their goal is six to 7%.

[01:16:04] Steve: was 10 for a doing about five to six.

[01:16:06] Steve: Yeah, well in 1985 it was 310 billion and at the moment it’s

[01:16:13] Steve: just around about the 20 trillion mark, it’s

[01:16:16] Steve: just about 3 trillion under the US, but as you know there’s been a lot of talk, and I don’t know how much of it is true, that, you know, things are imploding a fair bit, In China, in terms of production, we’ve got a bit of de globalization where things are moving away.

[01:16:32] Steve: And I think that things that we’ve discussed with soft robotics and humanoid robots is going to take away their low cost labor advantage in many realms, um, especially with dexterous manufacturing. Um, it’s, it’s interesting though. I mean, it’s an absolute. Unbelievable how they turned around that economy.

[01:16:52] Cameron: I got a report from the U S national science board that came out recently that says China has now surpassed us in STEM talent production, which is Research Publications, Patents, and Knowledge and Technology Intensive Manufacturing. China has set the goal of being the world’s leading science and engineering nation, and these NSB reports demonstrate that the United States is on the verge of allowing them to realize that objective.

[01:17:17] Cameron: We already see this in Artificial Intelligence, Where China out publishes us, has more patents, and produces more students than the United States. I, I saw this, uh, TikTok, uh, video or YouTube video the other day of a guy, American guy, who was in China, he was in Shanghai, and he was saying that he’s been traveling regularly there for the last 10 or 15 years, but this is the first time he’d been back since COVID.

[01:17:44] Cameron: Um, and he was saying just the change that he saw in Shanghai in

[01:17:50] Cameron: the, those like four or five years since he was last there, he said, it’s just incredible. He said, five years ago, you couldn’t see the sky because of the smog. Now look, completely, completely

[01:18:00] Steve: wow. Okay. That’s a really important thing, right? You

[01:18:05] Cameron: electric vehicles?

[01:18:06] Cameron: He said, there are just. Purely electric vehicles everywhere here. You can buy a top of the line electric vehicle for 10, 000 US dollars in China. They’re just churning them out. Um, you know, he was just talking about, he said like the seven main things

[01:18:23] Cameron: that he noticed going back, um, in the first time in five years, he said, like,

[01:18:28] Cameron: he said, the US is going backwards in a lot of areas, China’s just quantum leaping itself

[01:18:35] Cameron: every year,

[01:18:35] Cameron: right?

[01:18:36] Cameron: It’s really fascinating. if their economic growth rates You know, flatten off to an extent or aren’t as strong. I think,

[01:18:43] Cameron: Which is deliberate, by the

[01:18:45] Steve: well, yeah, right. So you get to a point where, yeah, well, I’m interested to see your point on where you think America is, because it seems to me that it’s imploding, you know, the disparity of income is, is, is a big thing that the crony capitalism, they’re not really investing in, and The political division. The political division is tearing the country apart.

[01:19:08] Steve: it really is.

[01:19:09] Steve: And even if you think about what seems to be valued in the New York Times, uh,

[01:19:17] Steve: you know, divisive politics

[01:19:19] Steve: and who’s upset and who is instead of real things, instead of real issues like, you know, feeding people, moving towards renewable and all of the things that really matter. And it seems to me from the outside that they’re overly focused on divisive politics and who’s right and who’s offended and they’re just eating themselves on issues which are unimportant in the grand scheme of the direction.

[01:19:47] Steve: I’m not talking about, of course we want equality and all of that, but it seems as though, uh, yeah, they’re focused on things that, uh, All about ideological groups instead of progression for everyone.

[01:20:05] Cameron: And yeah, just, I mean, I read the New York times every day. It’s one of the, about 12 newspapers that I read every morning, including, I read newspapers

[01:20:13] Steve: 72 hour, any 72 hour, you know, um, circumvention of,

[01:20:17] Steve: the sun.

[01:20:18] Cameron: I read newspapers coming out of China, Russia, the Middle East, as well as BBC, New York times and the ABC, et cetera. But when I say read them, like I scanned them for important things and just, it’s always interesting to me to see the different, coverage of big global stories coming out from different newspapers from different parts of the world.

[01:20:41] Cameron: But, um, you know, the, the, the focus on Russia and China in the New York times, there’s never a positive story about anything that China’s ever does in Western media. Try and find a single positive story about China in any mainstream media in the West. You know, you’ve got a country

[01:21:01] Cameron: That is just killing it on, you know, it’s not perfect, but it’s killing it on so many metrics right now.

[01:21:09] Cameron: Try and find a single positive story about that in Western

[01:21:12] Steve: Hey, I can tell you the single negative story that they love. The single negative story is the lack of democracy. And it does seem to be getting

[01:21:18] Steve: worse. And, you know, the social scoring and all of that. I know that we’ve talked about that and you’re like, is that bad? I’m like, it just feels like it can’t end well.

[01:21:25] Steve: Maybe like programmable currency. I don’t know. But,

[01:21:29] Cameron: You were saying to me off air before the show, you know, I think maybe, you know, if you do, if

[01:21:34] Cameron: you contribute to society, you should get taxed less than people who don’t

[01:21:38] Cameron: contribute to

[01:21:38] Cameron: society. Isn’t that.

[01:21:39] Cameron: a social scoring system?

[01:21:41] Steve: It is, but not based on being, uh, surveilled 24 seven. So yeah, my, my, and we, and we may as well

[01:21:51] Steve: raise it now. My, my idea was that because the market has failed in allocating the right amount of resources to people’s jobs, who create a social contribution, you know, nurses, teachers, doctors, what have you versus investment bankers and corporate lawyers.

[01:22:05] Steve: I think tax rates should vary based on the social contribution of the work that you do. I’m going to do it. I’m going to write up a piece about it.

[01:22:12] Cameron: think it’s a great idea. But look, you know, um, democracy in China, uh, is a whole other, you know, story. I mean, the funny thing about that, if you, from the perspective of the Western media, is we criticize China all the time for not having the kind of democracy that we think they should have. But we loved Lee Kuan Yew when he was the dictator of Singapore, that had exactly the

[01:22:36] Cameron: same kind of democracy, which was really a meritocracy.

[01:22:40] Cameron: In Singapore, we loved Lee Kuan Yew. When Lee Kuan Yew died, you know, it was like, uh, Jesus died, you know, the Because he doesn’t have any nuclear bombs. I

[01:22:51] Cameron: his praises. And yet, you know, he was a dictator of Singapore for, you know, whatever, 35, 40 years. And his son took over, you know, and, and I, I just recently read a book of interviews of Lee Kuan Yew that were done just before he passed away, a book by Graham Allison.

[01:23:10] Cameron: Lee Kuan Yew said that Xi Jinping was the new Nelson Mandela. He said he struck him as the same sort of integrity, vision, as a Nelson Mandela.

[01:23:25] Cameron: But you won’t hear the Western

[01:23:26] Cameron: media compare Xi Jinping to Nelson Mandela. Anyway, moving right along, Futurist Forecast, Steve,

[01:23:35] Steve: Yes,

[01:23:35] Cameron: you just wrote AI in a note.

[01:23:37] Steve: No, no. What if I did? No, no. Did I write that?

[01:23:42] Cameron: That’s just AI. I’m

[01:23:43] Cameron: like, that’s broad. There will be

[01:23:47] Steve: We’ve been going for

[01:23:47] Steve: two hours. I don’t have one. If you have one, then I’m happy to go into it.

[01:23:50] Cameron: Hour and 20. Well, listen, okay, just quickly. Um, we talked about AGI in five years, six years earlier on. Again, the thing that I think, I’m not seeing enough people talking about, which is crazy. What does a world look like with AGI in five years? You know, like, just think about a world with millions of new AI research scientists.

[01:24:16] Cameron: That are as good, if not better, than the best human scientists working on research on cancer, on nanotech, on climate change, carbon sequestration, cold fusion, fairer economic models, robotics. What does the world look like today? When we have a thousand times the number, like I was talking to, I was talking to Chrissy, you know, you and I were talking about neurodivergent kids and whatever before, and Chrissy’s been on this thing, you know, lately talking about how Western, uh, medicine hasn’t done a good enough job at, at, uh, identifying mental health issues and GPs don’t do a good enough job.

[01:25:01] Cameron: And I was, I was pushing back on it the other day. I was saying, look. Just in Australia, leave the US out because their medical system is obviously a clusterfuck. But we have mental health professionals here. We have psychologists, we have psychiatrists, we have therapists. The entry point to those is the GPs.

[01:25:18] Cameron: You sit with your GP, you tell them you’re having mental health issues, they’ll get you, you know, uh, uh, uh,

[01:25:24] Steve: Yeah,

[01:25:25] Cameron: Yeah, they’ll point you in the right direction. Um, uh, but the, the, the problem is, A, we don’t have enough GPs. B, we don’t have enough psychologists or psychotherapists, psychiatrists for the population, particularly as people are becoming more and more comfortable with admitting they have a mental health issue.

[01:25:47] Cameron: But the difference I said between like somebody with a pain in their And somebody with a mental health issue is you, you know, the, the pain in the stomach presents differently. You know, you got a bad pain, you go to a doctor, you say, I’ve got a pain in the stomach and the GP goes, okay, you need to go to the ER or you need to go get an x ray or

[01:26:04] Cameron: whatever it is.

[01:26:06] Cameron: But the people need to go to the GP in the first place and say, I have the issue. They don’t come and knock on your door and say, are you having any pains today,

[01:26:12] Steve: How are you feeling today, Steve? We’re just checking in yeah. And it’s even worse with mental health, right? You need to, it’s not the GP’s job to identify that you have a mental health issue.

[01:26:23] Cameron: You need to go to the GP and say, I think I need help. Then they can get you on the, the right stream for that help. It’s, and, but people don’t do that because, you know, our parents generation Traditionally wouldn’t get therapy, you know, particularly men are really bad at saying, yeah, yeah, I’ve got a mental health issue, I need help.

[01:26:43] Cameron: It’s still seen, less now than I think it was a generation ago, but it’s still seen as a sign of weakness or whatever it is. But the problem, even if we had everybody go to the GP tomorrow and say, I need mental health help, is we just don’t have enough GPs for a start, which is why they try and push you through in five minutes, is because they’ve got a queue and they can’t see everybody.

[01:27:02] Cameron: B, we don’t have enough psychologists and, you know, if you try and get your kid into a child psychologist or you try and get your kid diagnosed for ADHD, which we’ve been trying to do with Fox for 12 months, it costs a fortune and it takes forever to get an appointment because

[01:27:16] Steve: pediatrician, it

[01:27:17] Cameron: the waiting lists are crazy because we just literally We don’t have enough people.

[01:27:22] Cameron: You just, and you can’t train people by snapping your fingers. But you know, you need kids at university willing to go and do these things instead of going and doing corporate finance. You need to, it takes years to train them and qualify them and all that kind of stuff. But imagine a world where we have a million people.

[01:27:41] Cameron: Psychotherapists that are on your

[01:27:42] Cameron: phone, that you could talk to, that, that understand you, they listening, they read your emails, they’re listening to every conversation and every phone call you the site. Did they see my web browser history?

[01:27:56] Cameron: yes, particularly they need to see your web browser history, even in incognito.

[01:28:00] Cameron: Steve, what, why your fascination with stepbrothers and stepsister porn?

[01:28:05] Cameron: They’re going to want to know that. Like, can you get, can you get porn that isn’t about stepbrothers and stepsisters.

[01:28:11] Steve: I had no these days? so many frisky stepsisters there.

[01:28:19] Cameron: it’s for some reason,

[01:28:20] Steve: for some every. Every porn video needs to have the word step in it I know, It’s crazy, isn’t it? I do not understand why that is the thing these days, but somebody decided that’s the, that’s the go to thing. So we’re also going to have, you know, uh, uh, lots of AI generated content, most of which will be fucking awful, but hopefully we’ll also have AI tools that’ll help us find the good stuff.

[01:28:49] Cameron: So you won’t, it’ll know your tastes. It’ll know your preferences. Um, uh, you know, uh, a version of, you know, The Netflix algorithm, the record with the YouTube or the TikTok algorithm that recommends more stuff that it knows I already like, but that on steroids for all of the AI content. But this, here’s my, the thing I really wanted to drill down on is if Sam Altman is right, if Jensen Huang is right, If Elon Musk is right, even if they’re remotely close to being right, if this is what the world looks like in the next five, six, seven years, millions of

[01:29:26] Cameron: scientists, millions of

[01:29:28] Cameron: tutors, millions of

[01:29:30] Cameron: therapists, why aren’t we talking more about that right now?

[01:29:35] Cameron: And what does that world look like? I’m talking 2030.

[01:29:39] Steve: everything with AI, everything with AI right now is kind of like This other than humanoid robots, everything is just more efficient versions of what we did yesterday.

[01:29:53] Cameron: Yeah, slightly better versions of what we did yesterday.

[01:29:55] Steve: That’s it. And you’re right. And this is the exciting part of AI is, I mean, and this is kind of why it

[01:30:04] Steve: circles back to the, do we want these hundred billion dollar nation state level infrastructure projects managed by private companies, because what they’re going to want to do is just sell this to corporations, but what we probably

[01:30:14] Cameron: no one, no one else is going to do

[01:30:16] Cameron: it, Steve. It has to be Microsoft and Elon Musk and Sam Altman and Google doing this. Countries aren’t doing it.

[01:30:25] Steve: well they aren’t, and

[01:30:26] Steve: and they should be,

[01:30:27] Cameron: Except China.

[01:30:28] Steve: except China, right, so countries are doing it, so one third of the world is doing

[01:30:32] Steve: it,

[01:30:33] Cameron: yeah, China’s doing it.

[01:30:34] Steve: right, so countries are doing

[01:30:35] Steve: it, just the clever ones, and why don’t we just

[01:30:39] Steve: leave it at that, the clever country, as, as two citizens of the purported clever country.

[01:30:48] Cameron: The CCP, Clever Country Party. That’s what it

[01:30:51] Cameron: stands didn’t know that. What a great note to end this thing on.

[01:30:55] Cameron: Thank you, Steve. Good to chat.

[01:30:56] Steve: we went deep, wide, and the listeners, they are very lucky

[01:31:01] Steve: people.