1 00:00:00,280 --> 00:00:03,080 Speaker 1: Hello, and welcome to another episode of the Markmas Show, 2 00:00:03,080 --> 00:00:06,640 Speaker 1: where we talk about the decentralized revolution each and every week, 3 00:00:06,640 --> 00:00:08,840 Speaker 1: talking about the way the world is changing, and of 4 00:00:08,840 --> 00:00:11,240 Speaker 1: course we want to understand that, not just because it 5 00:00:11,240 --> 00:00:13,360 Speaker 1: brings us some peace, so we kind of understand what's 6 00:00:13,360 --> 00:00:15,560 Speaker 1: going on, but more importantly, we're trying to figure out 7 00:00:15,560 --> 00:00:18,400 Speaker 1: how to navigate this correctly. Where should we live, what 8 00:00:18,480 --> 00:00:20,759 Speaker 1: should we buy, how do we invest, what type of 9 00:00:20,800 --> 00:00:23,479 Speaker 1: business should we run? How do I plan for my family? 10 00:00:24,000 --> 00:00:26,079 Speaker 1: And all these things, and so as this world is 11 00:00:26,120 --> 00:00:29,240 Speaker 1: changing rapidly, we need to be in front of these things, 12 00:00:29,400 --> 00:00:33,720 Speaker 1: and so we're talking about the decentralized revolution. The world 13 00:00:33,840 --> 00:00:36,279 Speaker 1: changes on a pendulum about every two and fifty years 14 00:00:36,320 --> 00:00:39,600 Speaker 1: from the centralized structure to a decentralized structure, and we 15 00:00:39,680 --> 00:00:44,040 Speaker 1: look at it through the lens of politics, finance, and technology. 16 00:00:44,080 --> 00:00:45,640 Speaker 1: We look at through the lens of those three things, 17 00:00:45,680 --> 00:00:48,560 Speaker 1: because when you're looking at complex systems like the body, 18 00:00:49,000 --> 00:00:52,000 Speaker 1: complex systems like the economy, like the markets, like the 19 00:00:52,040 --> 00:00:56,160 Speaker 1: geopolitical world, you can't just look at one small piece 20 00:00:56,200 --> 00:00:58,960 Speaker 1: of it. That's the problem with modern medicine, right you 21 00:00:59,000 --> 00:01:03,760 Speaker 1: have these special going into be a specialist in cardiac care, 22 00:01:03,800 --> 00:01:06,720 Speaker 1: for example, But all they do, they're this specialist in that, 23 00:01:06,959 --> 00:01:09,280 Speaker 1: but they haven't looked at the total body overall, and 24 00:01:09,319 --> 00:01:11,319 Speaker 1: so a lot of times they miss things because they 25 00:01:11,360 --> 00:01:13,600 Speaker 1: don't have enough of the other information. And so the 26 00:01:13,600 --> 00:01:16,360 Speaker 1: body is complex, the markets are complex, and so we 27 00:01:16,360 --> 00:01:19,240 Speaker 1: look at through the lens of those three things, politics, finance, 28 00:01:19,400 --> 00:01:23,560 Speaker 1: and technology. Now, technology is the thing that changes the 29 00:01:23,560 --> 00:01:25,280 Speaker 1: world more than anything else. When we look back through 30 00:01:25,360 --> 00:01:28,080 Speaker 1: thousands of years of history, we see it's always technology 31 00:01:28,120 --> 00:01:32,880 Speaker 1: that changes things. And technology changes things, it changes us, 32 00:01:32,920 --> 00:01:35,480 Speaker 1: and then we're changed because of that, and then we 33 00:01:35,520 --> 00:01:38,039 Speaker 1: have different problems than technology comes to solve those. But 34 00:01:38,080 --> 00:01:41,640 Speaker 1: it also typically changes the way that we organize ourselves 35 00:01:42,000 --> 00:01:45,000 Speaker 1: from a decentralized world to a centralized world. And so 36 00:01:45,040 --> 00:01:47,880 Speaker 1: today I want to talk about that piece specifically, where 37 00:01:47,880 --> 00:01:49,760 Speaker 1: we're going to talk about the technology, and we normally 38 00:01:49,760 --> 00:01:55,160 Speaker 1: talk about the decentralized technology of bitcoin, the decentralized revolutionary technology, 39 00:01:55,440 --> 00:01:59,000 Speaker 1: and bitcoin is giving us this decentralization at a time 40 00:01:59,040 --> 00:02:02,240 Speaker 1: as the world is trending back towards decentralization, which is 41 00:02:02,880 --> 00:02:05,280 Speaker 1: very interesting. But I want to talk about a different 42 00:02:05,320 --> 00:02:08,440 Speaker 1: technology today and the different technology that I want to 43 00:02:08,440 --> 00:02:12,960 Speaker 1: talk about today is could potentially be the opposite, the 44 00:02:13,040 --> 00:02:18,000 Speaker 1: antithesis of bitcoin, and I'm talking about AI. So while 45 00:02:18,200 --> 00:02:21,519 Speaker 1: Bitcoin is a decentralized technology that will help us start 46 00:02:21,520 --> 00:02:24,760 Speaker 1: to decentralize how we store our value, how we communicate 47 00:02:24,800 --> 00:02:28,079 Speaker 1: our value, how we transfer value, all those things, AI 48 00:02:28,240 --> 00:02:33,000 Speaker 1: is almost this centralizing technology where we could all become 49 00:02:33,240 --> 00:02:38,280 Speaker 1: very dependent on one or two of these big AIS, 50 00:02:38,440 --> 00:02:40,320 Speaker 1: which could be a problematic. So we'll see this kind 51 00:02:40,320 --> 00:02:43,120 Speaker 1: of shaping up. Now. I got a lot to cover today. 52 00:02:44,120 --> 00:02:47,880 Speaker 1: I want to get to two main companies that are 53 00:02:47,880 --> 00:02:50,560 Speaker 1: really pushing this AI, and one of them is a 54 00:02:50,680 --> 00:02:54,239 Speaker 1: very centralizing company, and one of them is a decentralized AI. 55 00:02:54,600 --> 00:02:56,280 Speaker 1: So we're gonna talk about that. We'll get to that 56 00:02:56,360 --> 00:02:58,160 Speaker 1: in a little bit, but I want to cover it 57 00:02:58,200 --> 00:03:01,720 Speaker 1: from a different angle. Now you might have heard, or 58 00:03:02,000 --> 00:03:03,760 Speaker 1: you might be expecting me to start to cover like 59 00:03:04,120 --> 00:03:06,600 Speaker 1: what it does and how you can use it and 60 00:03:06,919 --> 00:03:09,240 Speaker 1: will it replace your job and how much money can 61 00:03:09,280 --> 00:03:11,480 Speaker 1: you make from it and all those things, which are 62 00:03:11,480 --> 00:03:13,560 Speaker 1: all good things, and we could discuss those. I did 63 00:03:13,600 --> 00:03:16,880 Speaker 1: do a video on my main YouTube channel recently and 64 00:03:16,919 --> 00:03:19,000 Speaker 1: I kind of covered a lot of those topics. So 65 00:03:19,040 --> 00:03:21,640 Speaker 1: if you go to my main YouTube challenge of search 66 00:03:21,760 --> 00:03:24,960 Speaker 1: Mark Moss, you can find that video and you'll see 67 00:03:25,280 --> 00:03:27,400 Speaker 1: kind of what it is, how we can use it, 68 00:03:27,520 --> 00:03:29,680 Speaker 1: what potential it has, things like that. But I want 69 00:03:29,680 --> 00:03:31,800 Speaker 1: to talk about it from a different angle today, and 70 00:03:31,840 --> 00:03:35,880 Speaker 1: I want to look at how it could work in 71 00:03:35,920 --> 00:03:39,800 Speaker 1: this decentralized world that we're transitioned into. As we go 72 00:03:39,880 --> 00:03:42,600 Speaker 1: from this unipolar world where basically the kind of have 73 00:03:42,640 --> 00:03:46,600 Speaker 1: this one world government right this United States homogene this 74 00:03:47,280 --> 00:03:50,960 Speaker 1: you know, one world currency, the dollar, so to speak. 75 00:03:51,200 --> 00:03:53,800 Speaker 1: But now as the world's breaking apart and China's spinning 76 00:03:53,840 --> 00:03:56,880 Speaker 1: off and Russias spinning off and etc. How does it 77 00:03:56,880 --> 00:04:00,880 Speaker 1: work then as the world moves away from peace and 78 00:04:01,040 --> 00:04:07,960 Speaker 1: more towards decentralization, deglobalization, unipolar to a multipolar world, there's 79 00:04:07,960 --> 00:04:10,360 Speaker 1: going to be the more friction. It's gonna be more battle, 80 00:04:10,400 --> 00:04:14,000 Speaker 1: more competition, which in itself is maybe a good thing 81 00:04:14,000 --> 00:04:16,800 Speaker 1: the competition side, not if it leads to warfare, obviously, 82 00:04:17,200 --> 00:04:19,880 Speaker 1: But I want to talk about the potential for the 83 00:04:19,960 --> 00:04:24,800 Speaker 1: AI to really speed up this decentralized transition and what 84 00:04:24,960 --> 00:04:28,560 Speaker 1: that means. We're gonna talk about the US, China, artificial 85 00:04:28,560 --> 00:04:32,400 Speaker 1: intelligence arms race. We're gonna talk about potentially the problems 86 00:04:32,400 --> 00:04:36,640 Speaker 1: of AIS fighting AIS, talking about the potential for this 87 00:04:36,760 --> 00:04:41,320 Speaker 1: to really escalate into a cyber security problem, which of 88 00:04:41,320 --> 00:04:42,920 Speaker 1: course we hear the world that I'm going form talking 89 00:04:42,920 --> 00:04:45,080 Speaker 1: about all the time. And then we'll talk about it 90 00:04:45,120 --> 00:04:48,240 Speaker 1: from an investment standpoint where some of these investments are 91 00:04:48,279 --> 00:04:50,400 Speaker 1: who's invested into it? And then, as I said, I 92 00:04:50,480 --> 00:04:52,839 Speaker 1: want to get into kind of this open AI versus 93 00:04:53,480 --> 00:04:56,719 Speaker 1: decentralized AI. So I got a lot to cover now. 94 00:04:56,760 --> 00:04:59,960 Speaker 1: To frame this up a little bit, there's two big 95 00:05:00,000 --> 00:05:04,560 Speaker 1: a very broad general categories for AI. We have what 96 00:05:04,920 --> 00:05:09,320 Speaker 1: would be considered narrow AI and then broader general AI. 97 00:05:09,880 --> 00:05:13,600 Speaker 1: And so narrow AI is artificial intelligence, so it's it's 98 00:05:13,640 --> 00:05:16,960 Speaker 1: really machine learning where the computer, you know, the machine 99 00:05:17,000 --> 00:05:20,040 Speaker 1: the software is learning how to do things. And in 100 00:05:20,040 --> 00:05:23,560 Speaker 1: this narrow AI, you can train it to do very 101 00:05:23,680 --> 00:05:27,720 Speaker 1: specific and narrow tasks. So you could teach it how 102 00:05:27,800 --> 00:05:31,919 Speaker 1: to play chess, for example, right, you could give it 103 00:05:31,960 --> 00:05:34,480 Speaker 1: a document and tell you to write a summary of 104 00:05:34,560 --> 00:05:37,240 Speaker 1: that document. So those are narrow tasks that I can do. 105 00:05:37,600 --> 00:05:41,039 Speaker 1: Then there's what would be considered broader general AI, and 106 00:05:41,120 --> 00:05:45,240 Speaker 1: that is where it has to have like intelligence and 107 00:05:45,279 --> 00:05:48,479 Speaker 1: creativity that a human could have where it could build 108 00:05:48,520 --> 00:05:53,200 Speaker 1: its own experiences and opinions. And as far as I know, 109 00:05:53,320 --> 00:05:54,839 Speaker 1: and I've done quite a bit of research on this. 110 00:05:54,880 --> 00:05:57,200 Speaker 1: As a matter of fact, I had the pleasure the 111 00:05:57,240 --> 00:06:00,760 Speaker 1: opportunity to actually sit down with the vall Ramakon, who 112 00:06:00,839 --> 00:06:06,520 Speaker 1: is a Silicon Valley you know, venture capital legend. Let's 113 00:06:06,520 --> 00:06:08,279 Speaker 1: just say that I had a chance to sit down 114 00:06:08,400 --> 00:06:10,240 Speaker 1: and have this conversation with him face to face, and 115 00:06:10,279 --> 00:06:13,960 Speaker 1: according to my research, according to him, we are really 116 00:06:14,120 --> 00:06:18,000 Speaker 1: no closer into getting this broad general AI moving forward 117 00:06:18,000 --> 00:06:20,479 Speaker 1: than we have been in the last fifty years. So 118 00:06:20,520 --> 00:06:24,600 Speaker 1: we're making massive progress in this narrow AI, but not 119 00:06:24,680 --> 00:06:27,760 Speaker 1: so much progress in the general AI. And the reason 120 00:06:27,800 --> 00:06:29,440 Speaker 1: why I just want to lay that part out is 121 00:06:29,480 --> 00:06:31,080 Speaker 1: because a lot of people are very scared of this 122 00:06:31,200 --> 00:06:34,680 Speaker 1: AI where it's you know, the singularity moment where it's 123 00:06:34,680 --> 00:06:37,720 Speaker 1: going to become smarter than humans. We go into this 124 00:06:38,160 --> 00:06:41,600 Speaker 1: terminator like you know from the movie Terminator, where the 125 00:06:41,680 --> 00:06:44,560 Speaker 1: AI gets smarter than humans and then realize that, well, 126 00:06:44,600 --> 00:06:47,560 Speaker 1: humans are the problem, and let's just kill all the humans. Right. 127 00:06:47,720 --> 00:06:50,080 Speaker 1: That's kind of this narrative that's been brought out by 128 00:06:50,120 --> 00:06:54,000 Speaker 1: this singularity moment and by these terminator movies. I think 129 00:06:54,040 --> 00:06:58,719 Speaker 1: that is overblown. It's certainly overblown for now. For now, 130 00:06:58,760 --> 00:07:01,280 Speaker 1: we're certainly no closer to that becoming a reality than 131 00:07:01,279 --> 00:07:05,039 Speaker 1: we ever have been. Now, some people are saying maybe 132 00:07:05,040 --> 00:07:08,040 Speaker 1: by twenty forty, twenty fifty, we could be making progress 133 00:07:08,040 --> 00:07:10,040 Speaker 1: on that. So you know, we'll check back in on 134 00:07:10,080 --> 00:07:11,920 Speaker 1: that in twenty or thirty years from now. I probably 135 00:07:11,960 --> 00:07:13,600 Speaker 1: won't be here on the radio in twenty or thirty 136 00:07:13,680 --> 00:07:15,480 Speaker 1: years from now, but we'll check back in on that. 137 00:07:16,640 --> 00:07:18,560 Speaker 1: But for now, we have this narrow AI and it's 138 00:07:18,640 --> 00:07:22,840 Speaker 1: making massive, massive progress, and so there appears to be 139 00:07:23,080 --> 00:07:25,600 Speaker 1: an arms race happening right now. There's an article that 140 00:07:25,640 --> 00:07:28,560 Speaker 1: came out this week from a Harvard researcher warning that 141 00:07:28,600 --> 00:07:33,280 Speaker 1: the AI arms race could actually destroy civilization, which is 142 00:07:33,320 --> 00:07:36,400 Speaker 1: a pretty big claim. Now, it's obviously no surprise that 143 00:07:36,440 --> 00:07:39,600 Speaker 1: the US and China have been in a competitive war. 144 00:07:39,640 --> 00:07:42,080 Speaker 1: At least we'll say, I believe it's actually a financial war, 145 00:07:42,360 --> 00:07:44,400 Speaker 1: probably kicked off by the Trump era teriffs that we're 146 00:07:44,440 --> 00:07:48,559 Speaker 1: put into place. But there's this arms race going on now. 147 00:07:49,520 --> 00:07:52,160 Speaker 1: Each country is trying to spend more and more money 148 00:07:52,480 --> 00:07:56,200 Speaker 1: trying to get this AI going. In the year twenty 149 00:07:56,480 --> 00:08:00,640 Speaker 1: twenty one, the US government spent ten billion on AI 150 00:08:00,880 --> 00:08:04,560 Speaker 1: R and D nine point three, which came from the 151 00:08:04,600 --> 00:08:09,760 Speaker 1: Department of Defense. It's a pretty big number. Of course, 152 00:08:09,920 --> 00:08:13,200 Speaker 1: the Chinese public expenditures for AI is less transparent. They're 153 00:08:13,200 --> 00:08:15,200 Speaker 1: not transparent about anything, so we really don't know how 154 00:08:15,240 --> 00:08:18,240 Speaker 1: much money they spent. However, analysts are saying it's probably 155 00:08:18,280 --> 00:08:20,880 Speaker 1: about the same amount of money. So kind of racing 156 00:08:20,960 --> 00:08:23,560 Speaker 1: for this, it's trying to see which could go on, 157 00:08:23,880 --> 00:08:27,000 Speaker 1: which one could lead lead the pace here. But this 158 00:08:27,160 --> 00:08:30,480 Speaker 1: AI arms race carries potentially huge risk for both countries. 159 00:08:30,480 --> 00:08:33,880 Speaker 1: Of course, any arms race poses huge risk for any country. 160 00:08:34,840 --> 00:08:37,280 Speaker 1: The race to nuclear weapons or any weapons for that matter, 161 00:08:37,360 --> 00:08:40,680 Speaker 1: poses huge risk. But we're at this interesting point in 162 00:08:40,760 --> 00:08:46,439 Speaker 1: time where as we've seen arms races and warfare change, 163 00:08:46,840 --> 00:08:50,199 Speaker 1: it's become a lot more critical, a lot more dangerous 164 00:08:50,240 --> 00:08:52,000 Speaker 1: for all of humanity. So I'm gonna talk about that. 165 00:08:52,200 --> 00:08:56,240 Speaker 1: We'll get into this AI versus AI and cyberspace, cyber pandemics, 166 00:08:56,640 --> 00:08:58,199 Speaker 1: and some of the investment stuff. We'll come back with 167 00:08:58,240 --> 00:08:59,760 Speaker 1: all that. If you're just tuning in, you're listening to 168 00:09:00,040 --> 00:09:03,400 Speaker 1: the Mark Moss Show talking about the decentralized Revolution, talking 169 00:09:03,440 --> 00:09:07,520 Speaker 1: specifically about how this new artificial intelligence boom it's really 170 00:09:07,520 --> 00:09:10,960 Speaker 1: been accelerating the last about ninety days, is changing things 171 00:09:10,960 --> 00:09:12,440 Speaker 1: on that front. So I got a lot to cover 172 00:09:12,480 --> 00:09:14,480 Speaker 1: when I come back. Don't go away. I'll be right 173 00:09:14,520 --> 00:09:18,640 Speaker 1: back in just a minute. We're back, all right, Welcome back. 174 00:09:18,640 --> 00:09:20,360 Speaker 1: If you just tune in, you're listening to the Mark 175 00:09:20,480 --> 00:09:23,040 Speaker 1: Moss Show. We're talking about, of course, each and every week, 176 00:09:23,080 --> 00:09:25,400 Speaker 1: the decentralized revolution as we look at it through the 177 00:09:25,440 --> 00:09:29,160 Speaker 1: lens of politics, finance, and technology. Today we are diving 178 00:09:29,200 --> 00:09:32,920 Speaker 1: into the technology bucket and we're looking at how artificial 179 00:09:32,960 --> 00:09:36,720 Speaker 1: intelligence is playing a very crucial role as this world 180 00:09:36,760 --> 00:09:41,000 Speaker 1: continues to decentralize. Now we're talking about specifically how AI 181 00:09:41,080 --> 00:09:43,439 Speaker 1: could lead to this a new form of arms race. 182 00:09:43,520 --> 00:09:46,720 Speaker 1: It's a new weapon that could be used both both 183 00:09:47,400 --> 00:09:52,080 Speaker 1: defensively and offensively. Of course, we're yet to see how 184 00:09:52,120 --> 00:09:55,080 Speaker 1: this could play out. But part of the reason why 185 00:09:55,240 --> 00:09:58,000 Speaker 1: is because humans are no good at imagine in the future. 186 00:09:58,520 --> 00:10:01,439 Speaker 1: What humans do is we imagine better versions of what 187 00:10:01,480 --> 00:10:05,000 Speaker 1: we have today. We have cars today, we'll have flying 188 00:10:05,040 --> 00:10:08,400 Speaker 1: cars in the future. But we can't imagine or envision 189 00:10:08,800 --> 00:10:12,240 Speaker 1: new things because we don't have the building blocks to 190 00:10:12,360 --> 00:10:15,360 Speaker 1: build those things yet today, and so we just kind 191 00:10:15,360 --> 00:10:18,280 Speaker 1: of imagine things. So when we can sit here and speculate, 192 00:10:18,320 --> 00:10:19,760 Speaker 1: as I said, I was kind of reading this article 193 00:10:19,800 --> 00:10:25,440 Speaker 1: from this Harvard researcher talking about how it could destroy civilization. Well, 194 00:10:25,679 --> 00:10:27,800 Speaker 1: we don't really know how it could destroy civilization. He 195 00:10:27,800 --> 00:10:30,440 Speaker 1: doesn't really point any ways in how that could do that. 196 00:10:30,679 --> 00:10:33,160 Speaker 1: We just sort of have this speculation that, well, I 197 00:10:33,200 --> 00:10:35,160 Speaker 1: guess I saw the movie Terminator when I was a kid, 198 00:10:35,160 --> 00:10:37,800 Speaker 1: and so it could just destroy civilization like that, And 199 00:10:38,160 --> 00:10:40,440 Speaker 1: maybe it could. I just don't think we're there yet, 200 00:10:40,640 --> 00:10:43,000 Speaker 1: going back to that kind of narrow versus broad AI. 201 00:10:43,160 --> 00:10:46,040 Speaker 1: But another article that came out this week plenty of 202 00:10:46,040 --> 00:10:52,360 Speaker 1: fearmongrain here it says that soon AI will battle other 203 00:10:52,440 --> 00:10:56,760 Speaker 1: AI in cyberspace. This is from an Israeli expert. He's 204 00:10:56,800 --> 00:11:01,160 Speaker 1: predicting this, saying that artificial intelligence is expected to lead 205 00:11:01,679 --> 00:11:04,880 Speaker 1: to a spike in cyber attacks. Now, one reason why 206 00:11:04,920 --> 00:11:07,960 Speaker 1: I think this is important is because, of course, the 207 00:11:08,080 --> 00:11:11,720 Speaker 1: World Economic Forum, good old cloud schwabing buddies, they just 208 00:11:11,800 --> 00:11:13,800 Speaker 1: met in Davos a few weeks ago and the one 209 00:11:13,840 --> 00:11:18,680 Speaker 1: thing they kept talking about, well, climate change, misinformation, and 210 00:11:19,240 --> 00:11:21,880 Speaker 1: cyber attacks. That's what they keep talking about. Cyber attacks, 211 00:11:21,880 --> 00:11:24,680 Speaker 1: cyber attacks, cybertecks. They're coming, they're coming, they're coming, They're planning, 212 00:11:24,679 --> 00:11:27,560 Speaker 1: they're planning, they're planning, and oh now they're here. So 213 00:11:27,600 --> 00:11:29,400 Speaker 1: we're starting to see this really start to pick up 214 00:11:29,400 --> 00:11:32,440 Speaker 1: a lot of steam. And so is it that they're 215 00:11:32,440 --> 00:11:36,800 Speaker 1: sort of conditioning for this to happen, so we're prepared 216 00:11:36,840 --> 00:11:40,040 Speaker 1: for it when it happens. So we're prepared to give 217 00:11:40,240 --> 00:11:45,280 Speaker 1: them the opportunity to save us from these cyber pandemics. 218 00:11:45,520 --> 00:11:47,680 Speaker 1: We'll see. But basically they're saying that AI could lead 219 00:11:47,720 --> 00:11:50,480 Speaker 1: to an increase in that The reason why is because 220 00:11:50,480 --> 00:11:54,760 Speaker 1: AI can create an infinite amount of content in seconds. Okay, 221 00:11:55,240 --> 00:11:58,440 Speaker 1: but experts are already warning of an AI based cyber 222 00:11:58,440 --> 00:12:04,480 Speaker 1: attack and they predict these experts, supposedly experts, predict that 223 00:12:04,600 --> 00:12:07,360 Speaker 1: only other AIS will be able to put a stop 224 00:12:07,360 --> 00:12:10,800 Speaker 1: to them. So again, back to the Terminator movie, the 225 00:12:10,840 --> 00:12:12,880 Speaker 1: only way to stop the terminator sent back in time 226 00:12:12,920 --> 00:12:15,560 Speaker 1: was to send another AI terminator back in time. And 227 00:12:15,559 --> 00:12:19,199 Speaker 1: that's kind of what they're saying here. AI could create 228 00:12:19,280 --> 00:12:21,480 Speaker 1: these cyber attacks but the only way to stop this 229 00:12:21,600 --> 00:12:24,640 Speaker 1: AI from cybertacking would be to create another AI to 230 00:12:24,920 --> 00:12:29,560 Speaker 1: put a stop to them, says there's this event called 231 00:12:29,600 --> 00:12:33,120 Speaker 1: Cybertech tel Aviv in twenty twenty three. It just took place, 232 00:12:33,120 --> 00:12:35,559 Speaker 1: and they said, the world's top cybersecurity leaders came together 233 00:12:36,280 --> 00:12:40,160 Speaker 1: to look at the problems and the solutions to combat 234 00:12:40,320 --> 00:12:44,880 Speaker 1: these types of threats. So some of the things, for example, 235 00:12:45,040 --> 00:12:48,440 Speaker 1: is like chat GPT which we were talking about, which 236 00:12:48,840 --> 00:12:52,200 Speaker 1: could basically write essays, right, It can write summaries, it 237 00:12:52,240 --> 00:12:55,240 Speaker 1: can write emails, it can write all these things, and 238 00:12:55,440 --> 00:12:58,640 Speaker 1: they've put kind of gates or restrictions onto what chat 239 00:12:58,679 --> 00:13:02,440 Speaker 1: gbt can do. So for example, you can't ask it 240 00:13:02,520 --> 00:13:06,160 Speaker 1: to write hate speech, you can't ask it to write 241 00:13:06,160 --> 00:13:10,280 Speaker 1: like racist things and things like that. And you also 242 00:13:10,400 --> 00:13:14,520 Speaker 1: can't supposedly ask it to do things like create viruses 243 00:13:14,559 --> 00:13:17,440 Speaker 1: and malware and things like that. So they've put these 244 00:13:17,480 --> 00:13:21,480 Speaker 1: restrictions with these gateways on it to try to prevent 245 00:13:21,480 --> 00:13:25,040 Speaker 1: it from being used for bad But what this group found, 246 00:13:25,080 --> 00:13:28,640 Speaker 1: cyber arc found was that with a little bit of persistence, 247 00:13:29,320 --> 00:13:33,840 Speaker 1: you could get chat gbt to actually create malware, so 248 00:13:34,000 --> 00:13:36,520 Speaker 1: like viruses for computers, which of course it's not supposed 249 00:13:36,559 --> 00:13:39,559 Speaker 1: to be able to do it. Says that the researchers 250 00:13:39,600 --> 00:13:42,320 Speaker 1: managed to get chat gbt to create malicious code, but 251 00:13:42,440 --> 00:13:45,320 Speaker 1: also they found a way to hide that malicious code 252 00:13:45,320 --> 00:13:47,880 Speaker 1: from your standard anti virus system in a way that 253 00:13:48,000 --> 00:13:51,600 Speaker 1: is quite original. So not only do they use it 254 00:13:51,640 --> 00:13:54,559 Speaker 1: to create a new one, but they also used it 255 00:13:54,720 --> 00:13:57,240 Speaker 1: to create a new one that could be hidden from 256 00:13:57,280 --> 00:14:02,040 Speaker 1: all known malware anti virus systems today. The thing that 257 00:14:02,160 --> 00:14:05,680 Speaker 1: you know, we have to understand is that technology is 258 00:14:05,720 --> 00:14:08,840 Speaker 1: a tool. It's no different than a set of tools 259 00:14:08,840 --> 00:14:13,120 Speaker 1: to fix a car, a pair of scissors, a fork, right, 260 00:14:13,120 --> 00:14:16,800 Speaker 1: and that, and that screwdriver could be used for many things. 261 00:14:17,160 --> 00:14:19,720 Speaker 1: It comes down to who picks that screwdriver up and 262 00:14:19,760 --> 00:14:22,760 Speaker 1: how they decide to use it. You could obviously attack 263 00:14:22,840 --> 00:14:24,800 Speaker 1: somebody and cause a lot of damage and harm with 264 00:14:24,840 --> 00:14:28,640 Speaker 1: a screwdriver, or you could open up a bottle, or 265 00:14:28,680 --> 00:14:31,400 Speaker 1: you could fix something with it. That's what really comes 266 00:14:31,400 --> 00:14:33,600 Speaker 1: down to it. And so when we have tools like this, 267 00:14:33,680 --> 00:14:36,800 Speaker 1: the tools themselves are neutral. And this is why it 268 00:14:36,880 --> 00:14:39,200 Speaker 1: kind of goes to this gun debate that's been raging forever, 269 00:14:39,680 --> 00:14:42,680 Speaker 1: and a gun is also a tool. The proponents of 270 00:14:42,800 --> 00:14:45,760 Speaker 1: guns would say that it's not what's in a man's hand, 271 00:14:46,800 --> 00:14:50,560 Speaker 1: it's what's in a man's heart. Right. If somebody wants 272 00:14:50,600 --> 00:14:52,800 Speaker 1: to kill somebody with a gun and you take away 273 00:14:52,800 --> 00:14:55,360 Speaker 1: the gun, well they could find any number of ways, 274 00:14:55,400 --> 00:14:59,080 Speaker 1: any number of hundreds of other ways to kill somebody, right, 275 00:14:59,120 --> 00:15:02,160 Speaker 1: I mean this obviously there's we all drive big vehicles. 276 00:15:02,240 --> 00:15:04,480 Speaker 1: That's pretty dangerous. I mean, you can get any type 277 00:15:04,480 --> 00:15:06,680 Speaker 1: of thing from hardware stores and I'm not going to 278 00:15:06,760 --> 00:15:09,600 Speaker 1: list those here, but you understand that you can't really 279 00:15:09,640 --> 00:15:11,200 Speaker 1: stop someone. I mean you can do it with your 280 00:15:11,200 --> 00:15:13,360 Speaker 1: bare hands. And so it really always comes back down 281 00:15:13,400 --> 00:15:15,680 Speaker 1: to what's in a man's heart, not what's in a 282 00:15:15,680 --> 00:15:18,120 Speaker 1: man's hand. And so when we start looking at tools 283 00:15:18,160 --> 00:15:22,320 Speaker 1: like this, they can put all types of gateways and 284 00:15:22,440 --> 00:15:24,520 Speaker 1: checkpoints on there, but it also limits what we can 285 00:15:24,560 --> 00:15:26,960 Speaker 1: do for good as well. If you go up to 286 00:15:27,000 --> 00:15:28,760 Speaker 1: the mountains at all, I like to go snowboarding. I 287 00:15:28,840 --> 00:15:32,760 Speaker 1: was just up in Vancouver snowboarding last week, and at 288 00:15:33,520 --> 00:15:35,160 Speaker 1: the where the chairlifts are where you getting on and 289 00:15:35,240 --> 00:15:37,880 Speaker 1: off the mountain, they have tools so you can adjust 290 00:15:37,880 --> 00:15:40,720 Speaker 1: your bindings and things like that, right, But the screwdrivers 291 00:15:40,720 --> 00:15:43,880 Speaker 1: have a chain and their chain to the bench there, 292 00:15:44,360 --> 00:15:47,320 Speaker 1: and so they could chain that screwdriver down so I 293 00:15:47,320 --> 00:15:50,760 Speaker 1: couldn't go attack people in the line with it. But 294 00:15:50,800 --> 00:15:52,680 Speaker 1: then it also limits what I'm able to do if 295 00:15:52,680 --> 00:15:56,000 Speaker 1: I needed to work on like a car, like a 296 00:15:56,040 --> 00:15:58,880 Speaker 1: SnowCat that came over a snowmobile, the chain isn't long 297 00:15:59,000 --> 00:16:01,680 Speaker 1: enough to go do that. So we can put these checks, 298 00:16:01,680 --> 00:16:03,840 Speaker 1: these gateways in, but then it limits what we're able 299 00:16:03,880 --> 00:16:08,520 Speaker 1: to do in the potential chance that maybe a couple 300 00:16:08,520 --> 00:16:11,520 Speaker 1: of people might try to do something crazy like create 301 00:16:11,640 --> 00:16:14,120 Speaker 1: malicious code. Most of us would never even think about that. 302 00:16:14,320 --> 00:16:16,600 Speaker 1: What they're saying is that there's even greater threats to 303 00:16:16,720 --> 00:16:20,360 Speaker 1: cybersecurity because of this. Now. They said that according to 304 00:16:20,360 --> 00:16:23,920 Speaker 1: the World Incomic Forum, cyber attacks already increased by almost 305 00:16:24,080 --> 00:16:28,800 Speaker 1: forty percent last year. Forty percent now. Of course, right 306 00:16:29,240 --> 00:16:32,840 Speaker 1: more people are using computers, more bad actors, and we're 307 00:16:32,880 --> 00:16:35,680 Speaker 1: going to have more cyber attacks, I guess, But they're 308 00:16:35,680 --> 00:16:38,840 Speaker 1: saying that they could rise exponentially over the coming year 309 00:16:39,200 --> 00:16:43,280 Speaker 1: because of these AI models, because the average person now 310 00:16:43,360 --> 00:16:47,200 Speaker 1: could write their own code and do this. And it 311 00:16:47,240 --> 00:16:49,240 Speaker 1: says that the primary challenge for cybersecurity is that the 312 00:16:49,240 --> 00:16:54,120 Speaker 1: attackers seem to be one step ahead. I've always wondered 313 00:16:54,120 --> 00:16:57,000 Speaker 1: about this. Right, here's a quote here. AI based attacks 314 00:16:57,000 --> 00:16:59,080 Speaker 1: are going to be much more pervasive, much more adaptable, 315 00:16:59,080 --> 00:17:00,680 Speaker 1: and much more rapid than they were in the past, 316 00:17:00,880 --> 00:17:05,840 Speaker 1: and human defenders can't keep up with the pace. So 317 00:17:06,000 --> 00:17:11,680 Speaker 1: think about that. The anti virus, the cybersecurity experts are 318 00:17:11,720 --> 00:17:15,280 Speaker 1: trying to stay one step in front of the exploiters, 319 00:17:15,440 --> 00:17:18,600 Speaker 1: but they can't do that. I've always wondered, how does 320 00:17:18,640 --> 00:17:23,200 Speaker 1: the anti virus software stay in business if there aren't 321 00:17:23,280 --> 00:17:29,639 Speaker 1: actually viruses? Could it be plausible that they could release 322 00:17:29,720 --> 00:17:31,720 Speaker 1: the virus and then release the software. Of course that 323 00:17:31,760 --> 00:17:33,439 Speaker 1: would just be you know, I mean, that would be 324 00:17:33,480 --> 00:17:35,800 Speaker 1: really really bad, apparently. Right. If you're just tune in, 325 00:17:35,800 --> 00:17:38,080 Speaker 1: you're listening to the Markmas Show. We're talking about the 326 00:17:38,119 --> 00:17:41,159 Speaker 1: Decentralized Revolution, talking about how AI plays a pivol role 327 00:17:41,200 --> 00:17:43,480 Speaker 1: in this. I got a lot to cover. I needed 328 00:17:43,480 --> 00:17:46,200 Speaker 1: to start getting faster here, so don't miss it. I'll 329 00:17:46,240 --> 00:17:48,280 Speaker 1: be right back. Don't go away, all right, welcome back. 330 00:17:48,280 --> 00:17:50,280 Speaker 1: If you're just tune in, you're listening to the Markmas Show. 331 00:17:50,280 --> 00:17:54,920 Speaker 1: We're talking about the Decentralized Revolution. We're talking about how AI. 332 00:17:55,240 --> 00:17:58,760 Speaker 1: We always talk about the decentralized revolution as through the 333 00:17:58,840 --> 00:18:02,240 Speaker 1: lens of politics, finance, and technology technologies what changes things. 334 00:18:02,480 --> 00:18:06,359 Speaker 1: Typically we're talking about technology in regards to bitcoin, but 335 00:18:06,480 --> 00:18:11,040 Speaker 1: we're talking about technology in regards to AI, and they're 336 00:18:11,080 --> 00:18:13,680 Speaker 1: talking about how the cybersecurity experts are saying that AI 337 00:18:13,720 --> 00:18:18,159 Speaker 1: could make it easier and more efficient for attackers to 338 00:18:18,880 --> 00:18:21,560 Speaker 1: do these cyber type of crimes, and how hard it 339 00:18:21,560 --> 00:18:24,960 Speaker 1: will be for them to keep up the pace with this. Basically, 340 00:18:24,960 --> 00:18:28,400 Speaker 1: what they're saying here is that a human defender won't 341 00:18:28,440 --> 00:18:30,840 Speaker 1: be able to figure out what's going on, find the 342 00:18:31,440 --> 00:18:36,639 Speaker 1: right countermeasures, and react fast enough because the AI attack 343 00:18:36,680 --> 00:18:40,040 Speaker 1: would have already reached this destination. So what they're saying 344 00:18:40,119 --> 00:18:41,720 Speaker 1: is that we're gonna have to fight fire with fire 345 00:18:42,000 --> 00:18:45,240 Speaker 1: and assign the defense task to an AI based system. 346 00:18:46,200 --> 00:18:49,520 Speaker 1: So we have to create machines to battle the machines, 347 00:18:49,760 --> 00:18:53,760 Speaker 1: is what they're saying. The problem is that when you 348 00:18:53,800 --> 00:18:56,959 Speaker 1: start leaving all of this up to AI, is AI 349 00:18:57,200 --> 00:19:02,080 Speaker 1: able to make these types of decisions? It says, here 350 00:19:02,080 --> 00:19:06,040 Speaker 1: are AI knows how to autonomously classify information, saving months 351 00:19:06,080 --> 00:19:09,640 Speaker 1: and sometimes years of work for an organization, and so 352 00:19:10,400 --> 00:19:13,920 Speaker 1: we should be able to classify these types of changes 353 00:19:13,920 --> 00:19:16,719 Speaker 1: and know if they're malicious or not. We'll see how 354 00:19:16,760 --> 00:19:18,960 Speaker 1: this shapes up. But like I said, I want what 355 00:19:19,040 --> 00:19:21,920 Speaker 1: I'm interested in is like we're hearing more and more 356 00:19:21,920 --> 00:19:26,359 Speaker 1: and more about this cyber pandemic and is this again, 357 00:19:26,960 --> 00:19:30,080 Speaker 1: is it picking up because of what the World that 358 00:19:30,080 --> 00:19:33,800 Speaker 1: Eccamyforum has been talking about. We saw that just after 359 00:19:33,840 --> 00:19:36,160 Speaker 1: the world that Recament Forum was talking about these potential 360 00:19:36,200 --> 00:19:39,000 Speaker 1: cyber attacks, we started getting more of them, including we 361 00:19:39,040 --> 00:19:42,719 Speaker 1: saw in the United States the FAA computers were attacked 362 00:19:42,720 --> 00:19:47,200 Speaker 1: and shutdown cars, causing the largest blackout of flights or 363 00:19:47,240 --> 00:19:50,280 Speaker 1: the largest shutdown of flights I believe in US history. 364 00:19:50,800 --> 00:19:52,600 Speaker 1: And it didn't just happen in the US. It happened 365 00:19:52,640 --> 00:19:55,720 Speaker 1: in I believe, Canada and maybe it was Australia a 366 00:19:55,720 --> 00:19:58,080 Speaker 1: few other places as well. So it happened right after 367 00:19:58,160 --> 00:20:00,439 Speaker 1: of course the WEF was talking about it, and we 368 00:20:00,520 --> 00:20:04,040 Speaker 1: also just saw that it also happened in Italy. Italy 369 00:20:04,080 --> 00:20:08,280 Speaker 1: had its Internet restored after having a nationwide outage on 370 00:20:08,320 --> 00:20:12,239 Speaker 1: the Internet. There's reports of a global ransomware attack that 371 00:20:12,320 --> 00:20:17,680 Speaker 1: was happening. And again, is this just all coincidence or 372 00:20:17,720 --> 00:20:21,600 Speaker 1: sometimes is it too coincidental. It is it. When there's smoke, 373 00:20:21,680 --> 00:20:24,280 Speaker 1: there's fire, And that's sort of what we're seeing right here. 374 00:20:25,160 --> 00:20:29,560 Speaker 1: We saw that this Italy's National Cybersecurity Agency warned about 375 00:20:29,600 --> 00:20:33,960 Speaker 1: these ransomware attacks and how they were targeting servers worldwide 376 00:20:34,280 --> 00:20:38,439 Speaker 1: and they're looking to exploit a software vulnerability. You know. 377 00:20:39,040 --> 00:20:43,920 Speaker 1: Part of the thing with centralized software versus decentralized software 378 00:20:44,640 --> 00:20:46,760 Speaker 1: is I think you could with decentralized software, you can 379 00:20:46,760 --> 00:20:49,320 Speaker 1: get a lot more people working on the software. Potentially, 380 00:20:50,440 --> 00:20:52,080 Speaker 1: you can get a lot more eyes on it. You 381 00:20:52,080 --> 00:20:56,320 Speaker 1: can find a lot more of these bugs. Maybe that's 382 00:20:56,320 --> 00:21:01,120 Speaker 1: a benefit, trying to find these exploitations before they become 383 00:21:01,119 --> 00:21:05,480 Speaker 1: a problem. But a lot of people were talking about 384 00:21:05,520 --> 00:21:08,680 Speaker 1: this over the week over on social media, talking about 385 00:21:09,440 --> 00:21:13,320 Speaker 1: is this the first of like what to expect about 386 00:21:13,960 --> 00:21:17,880 Speaker 1: lockdowns happening on the internet? Was this a dry run? 387 00:21:19,040 --> 00:21:21,359 Speaker 1: Could this have been coincident all that the WEFF was 388 00:21:21,400 --> 00:21:24,040 Speaker 1: just talking about it and then it's happening, And I 389 00:21:24,040 --> 00:21:26,560 Speaker 1: don't know, that's just conspiratorial talk. We don't really have 390 00:21:26,600 --> 00:21:31,040 Speaker 1: any evidence of that, but it is certainly again very 391 00:21:31,080 --> 00:21:36,119 Speaker 1: coincident all that that's happening right now now. On another side, 392 00:21:36,200 --> 00:21:40,440 Speaker 1: back to kind of the economic side of things. One 393 00:21:40,480 --> 00:21:45,800 Speaker 1: of the kind of famous technology stockpickers Cathy Wood. She 394 00:21:45,920 --> 00:21:49,000 Speaker 1: runs a firm or an ETF called ARC and it 395 00:21:49,040 --> 00:21:52,440 Speaker 1: basically has all the tech companies in this ETF, which 396 00:21:52,440 --> 00:21:55,920 Speaker 1: of course is famously down. She's lost so much money 397 00:21:55,920 --> 00:21:58,119 Speaker 1: it's a wonder that people still listen to her. But 398 00:21:58,200 --> 00:22:02,159 Speaker 1: she's now talking about how hour. She's predicting that Amazon 399 00:22:02,520 --> 00:22:08,320 Speaker 1: would have more robot workers than human workers by twenty thirty. 400 00:22:08,400 --> 00:22:12,680 Speaker 1: And that's not surprising. It's not surprising at all. It says, 401 00:22:12,680 --> 00:22:14,560 Speaker 1: if you compare the number of robot Amazon has to 402 00:22:14,600 --> 00:22:17,760 Speaker 1: the number of employees, it's about a third right now, 403 00:22:17,960 --> 00:22:20,400 Speaker 1: and we believe that by the year twenty thirty, Amazon 404 00:22:20,480 --> 00:22:23,720 Speaker 1: will have more. So Amazon already has what would be 405 00:22:23,760 --> 00:22:26,480 Speaker 1: considered robots. But what do you consider robots? Anytime a 406 00:22:26,520 --> 00:22:29,159 Speaker 1: machine does one thing like picks up a package and 407 00:22:29,200 --> 00:22:31,560 Speaker 1: moves it somewhere else, like, that's not happening all over 408 00:22:31,600 --> 00:22:32,879 Speaker 1: the place. It's not happening all the time. Well, of 409 00:22:32,920 --> 00:22:34,359 Speaker 1: course it is. It's happening about a third of the 410 00:22:34,680 --> 00:22:39,000 Speaker 1: people right now. But they're saying that by twenty thirty 411 00:22:39,280 --> 00:22:42,679 Speaker 1: it could replace all of them. Now is that a 412 00:22:42,720 --> 00:22:45,760 Speaker 1: bad thing. That Amazon currently has more than five hundred 413 00:22:45,800 --> 00:22:49,720 Speaker 1: and twenty thousand robots in use and could potentially get 414 00:22:49,760 --> 00:22:52,919 Speaker 1: over to about one point six million employees over the 415 00:22:52,920 --> 00:22:56,640 Speaker 1: next seven years, is that a bad thing. It could 416 00:22:56,680 --> 00:22:59,560 Speaker 1: be bad if you were one of those warehouse workers 417 00:22:59,560 --> 00:23:03,240 Speaker 1: that got your job replaced, unless you went and found 418 00:23:03,240 --> 00:23:07,800 Speaker 1: a better job. So, since the dawn of time, technology 419 00:23:08,280 --> 00:23:11,200 Speaker 1: always puts people out of work, that's the whole point. 420 00:23:12,040 --> 00:23:16,560 Speaker 1: That's the entire point. If I was carrying one brick 421 00:23:16,560 --> 00:23:19,160 Speaker 1: at a time, it would take me very long to 422 00:23:19,200 --> 00:23:23,280 Speaker 1: move these bricks over distance, right, So then using my 423 00:23:23,400 --> 00:23:28,000 Speaker 1: brain and human ingenuity, I would say, well, instead of 424 00:23:28,040 --> 00:23:31,200 Speaker 1: having ten people all carrying bricks back and forth, why 425 00:23:31,240 --> 00:23:33,560 Speaker 1: don't I make a wheelbarrow and then I can put 426 00:23:33,640 --> 00:23:35,840 Speaker 1: all the bricks into a wheelbarrow, and then I could 427 00:23:35,920 --> 00:23:38,840 Speaker 1: do the work of ten men carrying all the bricks 428 00:23:38,880 --> 00:23:41,639 Speaker 1: at once in a wheelbarrow. That was a piece of technology, 429 00:23:41,960 --> 00:23:44,080 Speaker 1: and it replaced the work of those ten people that 430 00:23:44,080 --> 00:23:47,680 Speaker 1: were needed to carry those bricks. Was that bad, Well, 431 00:23:47,680 --> 00:23:49,520 Speaker 1: it was if that was your only way to make money, 432 00:23:49,520 --> 00:23:52,040 Speaker 1: it was carrying those bricks. But it wasn't bad because 433 00:23:52,160 --> 00:23:54,400 Speaker 1: ultimately what it does is it freed those people up 434 00:23:54,680 --> 00:23:59,160 Speaker 1: to go focus on higher value things. Now, the world 435 00:23:59,160 --> 00:24:01,800 Speaker 1: had stayed pretty much dirt. The world had stayed pretty 436 00:24:01,880 --> 00:24:05,960 Speaker 1: much with no real technological advancements for most of history. 437 00:24:06,600 --> 00:24:11,159 Speaker 1: Things really got interesting in the late seventeen hundred in 438 00:24:11,200 --> 00:24:15,320 Speaker 1: the eighteenth century, which was the start of the industrial Revolution, 439 00:24:16,000 --> 00:24:18,800 Speaker 1: And all of a sudden, a new technological revolution happened, 440 00:24:19,000 --> 00:24:22,359 Speaker 1: and we created machines, and all of a sudden, a 441 00:24:22,400 --> 00:24:27,880 Speaker 1: machine could do the work of five thousand men. The horror, 442 00:24:28,320 --> 00:24:30,680 Speaker 1: what's going to happen to all those five thousand men? 443 00:24:30,720 --> 00:24:34,439 Speaker 1: They got their jobs replaced by one machine. And of 444 00:24:34,440 --> 00:24:36,879 Speaker 1: course the answer is, well, those men would go on 445 00:24:37,000 --> 00:24:43,040 Speaker 1: to do science and medicine and further improve the world. 446 00:24:43,880 --> 00:24:45,720 Speaker 1: So we can talk about this all the time. Technology 447 00:24:45,800 --> 00:24:49,880 Speaker 1: always replaces the need for human power, but it allows 448 00:24:49,920 --> 00:24:53,760 Speaker 1: those humans to go work on higher level tasks. We 449 00:24:53,800 --> 00:24:57,359 Speaker 1: could have ten thousand guys out there digging roads, or 450 00:24:57,400 --> 00:24:59,840 Speaker 1: we could bring in one tractor and just do the 451 00:25:00,040 --> 00:25:01,719 Speaker 1: work of all those people. But what are all those 452 00:25:01,720 --> 00:25:04,000 Speaker 1: people going to go do. Well, they're going to find 453 00:25:04,320 --> 00:25:07,240 Speaker 1: new things to go work on, like creating new forms 454 00:25:07,240 --> 00:25:10,119 Speaker 1: of tractors and all these service businesses based around tractors 455 00:25:10,160 --> 00:25:12,480 Speaker 1: and making parts for tractors, and on and on and on, 456 00:25:13,000 --> 00:25:17,200 Speaker 1: designing AI for example. And so we could look back 457 00:25:17,200 --> 00:25:20,400 Speaker 1: through time and look at any piece of technology and 458 00:25:20,600 --> 00:25:24,680 Speaker 1: how it's made us more efficient. That's the whole point. 459 00:25:25,119 --> 00:25:27,200 Speaker 1: It makes us more efficient, so we don't need as 460 00:25:27,280 --> 00:25:30,960 Speaker 1: many hours to go into that, and then those hours 461 00:25:31,000 --> 00:25:33,720 Speaker 1: freed up allows us to go work on other things. Now, 462 00:25:34,000 --> 00:25:36,600 Speaker 1: the only way that you're really affected by this is 463 00:25:36,640 --> 00:25:40,720 Speaker 1: if I hate to say it, but you're too should 464 00:25:40,720 --> 00:25:44,120 Speaker 1: I say lazy, to pour into your own self, into 465 00:25:44,119 --> 00:25:47,679 Speaker 1: your own education. For the lazy and uninitiated, it's a 466 00:25:47,720 --> 00:25:52,040 Speaker 1: bad thing. But for the smart and for the people 467 00:25:52,119 --> 00:25:54,800 Speaker 1: willing to take on this new technology and use it, 468 00:25:54,800 --> 00:25:59,399 Speaker 1: it's powerful. What's happening is that as this technology has 469 00:25:59,440 --> 00:26:02,120 Speaker 1: continue to change things. As I say all the time, 470 00:26:02,160 --> 00:26:04,560 Speaker 1: technology is what changes the way the world works and 471 00:26:04,600 --> 00:26:08,480 Speaker 1: how we organize ourselves. And so really, about two hundred 472 00:26:08,480 --> 00:26:11,480 Speaker 1: and fifty years ago, at the start of this Industrial Revolution, 473 00:26:11,560 --> 00:26:14,879 Speaker 1: it started to centralize us and put us into cities 474 00:26:15,320 --> 00:26:17,640 Speaker 1: with factories, and we had these big factories and these 475 00:26:17,640 --> 00:26:23,639 Speaker 1: big cities, and it became very centralized. In nineteen o eight, 476 00:26:23,880 --> 00:26:29,720 Speaker 1: we had that the third or fourth the fourth Industrial Revolution, 477 00:26:30,000 --> 00:26:35,399 Speaker 1: which was automobiles and mass production or assembly lines. Now 478 00:26:35,440 --> 00:26:40,000 Speaker 1: that change things drastically, and it is also part of 479 00:26:40,000 --> 00:26:42,280 Speaker 1: this American story of this middle class in the shrinking 480 00:26:42,280 --> 00:26:43,960 Speaker 1: middle class. I'm gonna break that down for you, and 481 00:26:43,960 --> 00:26:46,199 Speaker 1: then we'll talk about these different types of AI, the 482 00:26:46,280 --> 00:26:48,919 Speaker 1: open source versus closed source. If you're just tuning in, 483 00:26:48,960 --> 00:26:50,960 Speaker 1: you're listening to the markmas Show. Of course we talk 484 00:26:51,000 --> 00:26:53,560 Speaker 1: about the decentralized revolution, talking about the way the world 485 00:26:53,680 --> 00:26:56,880 Speaker 1: is changing, and today we're talking about it specifically through 486 00:26:57,080 --> 00:26:59,639 Speaker 1: the technology piece, which is of course always the biggest 487 00:26:59,640 --> 00:27:02,119 Speaker 1: piece talking about AI. I got a whole lot to 488 00:27:02,160 --> 00:27:04,200 Speaker 1: cover when I come back in a minute. You don't 489 00:27:04,240 --> 00:27:06,040 Speaker 1: want to miss it, so don't go away. I'll be 490 00:27:06,200 --> 00:27:09,480 Speaker 1: right back, all right, Welcome back. If you just tune in, 491 00:27:09,520 --> 00:27:11,680 Speaker 1: you're listening to the Mark Moss Show, we're talking about 492 00:27:11,680 --> 00:27:16,240 Speaker 1: the decentralized Revolution. We're talking specifically about the technology piece. 493 00:27:17,119 --> 00:27:19,760 Speaker 1: We're talking about AI. Now, what I was saying is 494 00:27:19,800 --> 00:27:22,919 Speaker 1: that since the beginning of time, every time there's been 495 00:27:22,920 --> 00:27:25,439 Speaker 1: a new piece of technology, people are worried about it 496 00:27:25,720 --> 00:27:29,080 Speaker 1: because it replaces jobs, and it does, but it also 497 00:27:29,160 --> 00:27:32,320 Speaker 1: opens up new jobs, and so as humans, we have 498 00:27:32,720 --> 00:27:38,120 Speaker 1: unlimited potential, unlimited And the reason why we have unlimited 499 00:27:38,160 --> 00:27:42,360 Speaker 1: potential is because we have ingenuity and we have creativity. 500 00:27:42,880 --> 00:27:46,000 Speaker 1: And as long as we have creativity, we're always going 501 00:27:46,040 --> 00:27:48,440 Speaker 1: to see problems that need to be solved, and we're 502 00:27:48,480 --> 00:27:50,600 Speaker 1: always going to come up with new solutions to solve 503 00:27:50,640 --> 00:27:53,200 Speaker 1: those problems, and we're always going to have progress, and 504 00:27:53,240 --> 00:27:56,119 Speaker 1: we're always going to have advancement, and there's never going 505 00:27:56,200 --> 00:27:59,399 Speaker 1: to be a lack or a shortage of things to 506 00:27:59,480 --> 00:28:05,080 Speaker 1: work on. The problem is, if you're not creative, if 507 00:28:05,080 --> 00:28:07,920 Speaker 1: you're not ambitious, if you're not looking at those things well, 508 00:28:07,920 --> 00:28:09,359 Speaker 1: and all you want to do is the one task, 509 00:28:09,400 --> 00:28:11,040 Speaker 1: you could have a hard time. So an example would 510 00:28:11,080 --> 00:28:14,960 Speaker 1: be in the Pacific Northwest, we had all these logging 511 00:28:15,000 --> 00:28:19,480 Speaker 1: towns and entire towns were built just for logging there. 512 00:28:20,400 --> 00:28:23,080 Speaker 1: But now that's all been basically shut down. Most of 513 00:28:23,200 --> 00:28:25,840 Speaker 1: us move up to Canada or other countries, and these 514 00:28:25,880 --> 00:28:28,560 Speaker 1: logging towns that used to be robust and busy and 515 00:28:28,800 --> 00:28:31,320 Speaker 1: have lots of jobs have now shriveled up and died. 516 00:28:32,080 --> 00:28:35,280 Speaker 1: Now some of these towns want to supply or provide 517 00:28:35,359 --> 00:28:37,919 Speaker 1: welfare or UBI or whatever you want to call it 518 00:28:37,960 --> 00:28:40,320 Speaker 1: to these people, because what are they going to do? 519 00:28:41,240 --> 00:28:44,600 Speaker 1: I mean, they were a logger and now there's no logging, 520 00:28:44,680 --> 00:28:46,840 Speaker 1: and now they're in this town and all they'd know 521 00:28:46,880 --> 00:28:49,200 Speaker 1: how to do is logging, and there's no logging jobs, 522 00:28:49,520 --> 00:28:50,960 Speaker 1: and so they have nothing to do, so we have 523 00:28:50,960 --> 00:28:53,440 Speaker 1: to give them money. Well, I can tell you what 524 00:28:53,440 --> 00:28:57,040 Speaker 1: they should do. They should learn a new skill and 525 00:28:57,120 --> 00:29:01,240 Speaker 1: they should move somewhere else. Right, that's exactly the point here. 526 00:29:01,320 --> 00:29:07,400 Speaker 1: So we have this situation where computers are yes replacing jobs. 527 00:29:08,000 --> 00:29:09,840 Speaker 1: You imagine how many people used to take to sit 528 00:29:09,840 --> 00:29:12,360 Speaker 1: there and transcribe books by hand, and then we came 529 00:29:12,400 --> 00:29:14,360 Speaker 1: up with the printing press. But what about all those 530 00:29:14,360 --> 00:29:17,040 Speaker 1: people that are transcribing books though they do something else. 531 00:29:17,280 --> 00:29:21,080 Speaker 1: So Amazon's helping. Amazon says that they've committed about one 532 00:29:21,160 --> 00:29:26,560 Speaker 1: point two billion dollars to provide employees with educational programs, 533 00:29:27,160 --> 00:29:33,400 Speaker 1: one point two billion offering megatronics, mechatronics, robotics, all these programs. 534 00:29:33,400 --> 00:29:36,719 Speaker 1: And so hopefully these people who see that, you know, 535 00:29:36,760 --> 00:29:39,600 Speaker 1: there's this potential for their job to get replaced, could 536 00:29:39,600 --> 00:29:42,760 Speaker 1: take advantage of this and move up higher on the 537 00:29:42,800 --> 00:29:45,440 Speaker 1: food chain rights. That's what we want them to do. Now, 538 00:29:45,840 --> 00:29:48,760 Speaker 1: this is a big, big piece because what happened is, 539 00:29:49,040 --> 00:29:51,680 Speaker 1: you know, after back to nineteen o eight, Henry Ford 540 00:29:51,760 --> 00:29:54,960 Speaker 1: invented the automobile and the mass production the assembly line. 541 00:29:55,200 --> 00:29:58,520 Speaker 1: What happened is that led to massive abundance and prosperity 542 00:29:58,520 --> 00:30:02,400 Speaker 1: for the United States got this very robust middle class, 543 00:30:03,040 --> 00:30:05,120 Speaker 1: not just the United States, the developed world that was 544 00:30:05,200 --> 00:30:10,320 Speaker 1: embracing this industrial revolution. We got this massive growth and 545 00:30:10,400 --> 00:30:14,320 Speaker 1: this robust middle class. And the reason why is because 546 00:30:14,400 --> 00:30:19,000 Speaker 1: the assembly line like equalizes everybody. So you could be 547 00:30:19,040 --> 00:30:20,600 Speaker 1: the smartest person in the world, that could be the 548 00:30:20,640 --> 00:30:22,720 Speaker 1: dumbest person in the world. And we're next to each 549 00:30:22,760 --> 00:30:24,920 Speaker 1: other on the assembly line, and I plug in my 550 00:30:25,000 --> 00:30:27,160 Speaker 1: part and you plug in your part, and we've done 551 00:30:27,160 --> 00:30:30,840 Speaker 1: the exact same work. Even though you're smarter and I'm 552 00:30:30,880 --> 00:30:34,000 Speaker 1: not as smart as you, we've provided the same value. 553 00:30:34,480 --> 00:30:37,320 Speaker 1: We've each plugged in our part, and we each get 554 00:30:37,360 --> 00:30:39,720 Speaker 1: paid equally. And basically, what it did is it took 555 00:30:39,760 --> 00:30:42,640 Speaker 1: all these people who were not motivated and not smart 556 00:30:43,040 --> 00:30:46,280 Speaker 1: and didn't want to work smarter, and it pushed them 557 00:30:46,360 --> 00:30:48,600 Speaker 1: up and made them on an even playing field as 558 00:30:48,600 --> 00:30:52,120 Speaker 1: the people who were smarter and more ambitious, and that 559 00:30:52,160 --> 00:30:54,719 Speaker 1: worked pretty well, but the middle class has obviously been 560 00:30:54,720 --> 00:30:56,640 Speaker 1: hollowed out. You hear about stories all the time. Now. 561 00:30:56,640 --> 00:30:58,120 Speaker 1: Part of it is because we shipped a bunch of 562 00:30:58,200 --> 00:31:01,640 Speaker 1: jobs overseas. Apparently we did, so that's part of it. 563 00:31:02,680 --> 00:31:06,200 Speaker 1: But the reason why is because those types of jobs 564 00:31:07,400 --> 00:31:10,000 Speaker 1: don't require people to be very smart or hard working 565 00:31:10,080 --> 00:31:13,200 Speaker 1: or innovative, and so let's just give those two other 566 00:31:13,240 --> 00:31:15,880 Speaker 1: countries that can do the much cheaper. There's there's other 567 00:31:15,880 --> 00:31:17,240 Speaker 1: reasons why. I don't want to dig into that, but 568 00:31:17,320 --> 00:31:19,000 Speaker 1: the part that I want to dig into is that 569 00:31:19,960 --> 00:31:22,680 Speaker 1: we've moved into a new We've moved into into the 570 00:31:22,760 --> 00:31:29,280 Speaker 1: information age. So the technological revolutions of the seventeen to 571 00:31:29,360 --> 00:31:33,400 Speaker 1: eighteen hundreds and the early nineteen ndards were all transportation based. 572 00:31:33,600 --> 00:31:36,760 Speaker 1: So that was where the big technologies were steam engines 573 00:31:36,800 --> 00:31:40,000 Speaker 1: to move stuff across continents, steel and steam engines to 574 00:31:40,040 --> 00:31:43,320 Speaker 1: move stuff across the oceans, the automobiles. It was all 575 00:31:43,360 --> 00:31:46,840 Speaker 1: transportation based. When we got into nineteen seventy one, we 576 00:31:46,880 --> 00:31:50,240 Speaker 1: had the new innovation, the technological revolution, which was a microprocessor, 577 00:31:50,320 --> 00:31:56,880 Speaker 1: which brought us computers and telecommunications and the internet. We 578 00:31:57,200 --> 00:32:01,720 Speaker 1: entered the information age. And the problem is now we 579 00:32:01,800 --> 00:32:04,600 Speaker 1: don't need to depend so much on the physical and 580 00:32:04,640 --> 00:32:07,240 Speaker 1: the transportation side. I mean, of course we still need that, 581 00:32:07,640 --> 00:32:10,960 Speaker 1: but now we're working more on the information age, and 582 00:32:11,040 --> 00:32:15,040 Speaker 1: that now puts the preference back to people who are smarter, 583 00:32:15,640 --> 00:32:18,560 Speaker 1: who are building their own education, who are taking time 584 00:32:18,600 --> 00:32:22,160 Speaker 1: to educate themselves, who are taking time to think creatively, 585 00:32:22,800 --> 00:32:25,480 Speaker 1: looking for problems and coming up with solutions and things 586 00:32:25,480 --> 00:32:28,520 Speaker 1: like that. And that difference of us moving from an 587 00:32:28,840 --> 00:32:32,880 Speaker 1: assembly line where everybody was equal to the information age, 588 00:32:32,920 --> 00:32:35,640 Speaker 1: where they're smarter, people are really able to start pulling 589 00:32:35,640 --> 00:32:39,680 Speaker 1: out ahead, is really led to this massive difference in 590 00:32:39,720 --> 00:32:43,400 Speaker 1: the income. So you hear about this income inequality, which 591 00:32:43,440 --> 00:32:45,960 Speaker 1: I think is a wrong metric to look at, but 592 00:32:46,120 --> 00:32:47,760 Speaker 1: you look at you know how much people at the 593 00:32:47,800 --> 00:32:50,040 Speaker 1: top are making versus how much people to bottom and 594 00:32:50,240 --> 00:32:54,640 Speaker 1: AI And as we continue to move into the information age, 595 00:32:54,920 --> 00:32:57,959 Speaker 1: as we continue to have tools to help with the 596 00:32:57,960 --> 00:33:00,800 Speaker 1: information age, like I and all the other ones that 597 00:33:00,800 --> 00:33:03,120 Speaker 1: will come in after it, we're going to continue to 598 00:33:03,160 --> 00:33:08,080 Speaker 1: get a bigger gap. Now we shouldn't. I would hope 599 00:33:08,080 --> 00:33:10,880 Speaker 1: that you listening, I would hope that everybody would step 600 00:33:11,000 --> 00:33:13,600 Speaker 1: up and go shoot I better learn this new stuff. 601 00:33:13,600 --> 00:33:15,960 Speaker 1: I'd better learn to start thinking creatively. I better start 602 00:33:15,960 --> 00:33:18,280 Speaker 1: paying attention. I should start watching videos. I should start 603 00:33:18,280 --> 00:33:21,080 Speaker 1: playing with this stuff. But instead most people would rather 604 00:33:21,120 --> 00:33:25,600 Speaker 1: watch the Kardashians and play with TikTok. And that's fine. 605 00:33:26,120 --> 00:33:28,840 Speaker 1: You should have the ability and the right to do that. 606 00:33:29,440 --> 00:33:32,960 Speaker 1: Just don't complain when your job gets replaced, right, because 607 00:33:32,960 --> 00:33:36,120 Speaker 1: we always have to be providing more value to the world, 608 00:33:36,160 --> 00:33:38,240 Speaker 1: and as the world changes, we have to stay on 609 00:33:38,280 --> 00:33:40,560 Speaker 1: top of that. It's happened since the beginning of time 610 00:33:40,880 --> 00:33:43,360 Speaker 1: and it's always going to continue to happen. It's called 611 00:33:43,360 --> 00:33:47,760 Speaker 1: creative destruction. It destroys some things, but it creates new ones. 612 00:33:48,080 --> 00:33:51,320 Speaker 1: And we're humans, We're able to learn things. This old 613 00:33:51,360 --> 00:33:53,959 Speaker 1: dogs can't learn new tricks. We're not dogs. We can 614 00:33:54,080 --> 00:33:56,080 Speaker 1: learn new things. We can learn new skills, and we should. 615 00:33:56,840 --> 00:34:00,080 Speaker 1: Let's talk about the two different types of a I. 616 00:34:00,600 --> 00:34:02,600 Speaker 1: So the big one is this open AI that's the 617 00:34:02,680 --> 00:34:04,520 Speaker 1: name of the company, is called open AIE. But the 618 00:34:04,880 --> 00:34:08,200 Speaker 1: irony there is that it's not open. Open AI is 619 00:34:08,239 --> 00:34:12,719 Speaker 1: a closed AI that's been trained. Somebody gave them all 620 00:34:12,800 --> 00:34:17,120 Speaker 1: the information, but who gave it to them, who built 621 00:34:17,200 --> 00:34:19,960 Speaker 1: up the AI? Who told it what it can and 622 00:34:20,040 --> 00:34:23,759 Speaker 1: can't do. It can't provide malicious code, It can't write 623 00:34:23,800 --> 00:34:27,120 Speaker 1: hate speech. Well, what is hate speech? What qualifies? And 624 00:34:27,160 --> 00:34:31,680 Speaker 1: so who controls that? It's a big deal. It's a 625 00:34:31,800 --> 00:34:35,960 Speaker 1: dangerous problem. The founder of Open Ai, Sam Altman, he 626 00:34:36,000 --> 00:34:38,400 Speaker 1: came out and said this week that AI is poised 627 00:34:38,400 --> 00:34:44,200 Speaker 1: to break capitalism. Now, whatever that means, I don't even 628 00:34:44,200 --> 00:34:45,360 Speaker 1: I don't even know what that means. I've tried to 629 00:34:45,440 --> 00:34:49,480 Speaker 1: understand it. Capitalism isn't something to be broken human nature. 630 00:34:49,960 --> 00:34:54,320 Speaker 1: We all are. We all are capitalists. We have private property, 631 00:34:54,800 --> 00:34:57,800 Speaker 1: our own private body, our own ideas, and our labor, 632 00:34:58,520 --> 00:35:01,720 Speaker 1: and we have our resources that we acquire our private property, 633 00:35:02,000 --> 00:35:04,480 Speaker 1: and we always work to try to be more efficient 634 00:35:04,640 --> 00:35:08,319 Speaker 1: with those resources, those scarce resources that we have, and 635 00:35:08,480 --> 00:35:10,840 Speaker 1: we do that through a number of ways, innovation and 636 00:35:10,920 --> 00:35:16,319 Speaker 1: also through free and voluntary exchange. And everywhere there's capitalism. 637 00:35:16,560 --> 00:35:20,320 Speaker 1: Little kids in preschool are trading sandwiches for crackers, in prison, 638 00:35:20,360 --> 00:35:22,879 Speaker 1: they're trading, you know, onions for cigarettes, and in North 639 00:35:22,960 --> 00:35:26,360 Speaker 1: Korea they're trading stuff. Right, We're always trading. We're always 640 00:35:26,400 --> 00:35:28,719 Speaker 1: trying to be more efficient with the scarce resources. That's 641 00:35:28,800 --> 00:35:32,799 Speaker 1: capitalism and AI is just one more tool that will 642 00:35:32,840 --> 00:35:37,640 Speaker 1: help us to use our resources more efficiently. So I 643 00:35:37,680 --> 00:35:39,160 Speaker 1: don't even know where he gets off saying that it's 644 00:35:39,160 --> 00:35:41,360 Speaker 1: going to break capitalism. You can't break capitalism. It's going 645 00:35:41,440 --> 00:35:44,279 Speaker 1: to break ingenuity. It's going to break the desire to 646 00:35:44,400 --> 00:35:46,920 Speaker 1: be more efficient with our scarce resources. It's going to 647 00:35:47,040 --> 00:35:50,320 Speaker 1: break the desire to freely trade with one another. Like 648 00:35:50,440 --> 00:35:53,400 Speaker 1: that's never going to happen. Now, on the other side, 649 00:35:53,440 --> 00:35:57,120 Speaker 1: we have stable Diffusion, and Stable Diffusion is poised to 650 00:35:57,160 --> 00:36:00,239 Speaker 1: be an open source AI which is in contract us 651 00:36:00,239 --> 00:36:03,520 Speaker 1: to open a HI which is actually closed. I'm running 652 00:36:03,520 --> 00:36:04,879 Speaker 1: out of time. I don't have time to get into 653 00:36:04,920 --> 00:36:08,279 Speaker 1: stable diffusion, but I would ask you to go do 654 00:36:08,320 --> 00:36:10,960 Speaker 1: your own research on that. Just search stable diffusion, check 655 00:36:11,000 --> 00:36:12,640 Speaker 1: that out. If you're just tuning in you're listening to 656 00:36:12,680 --> 00:36:15,920 Speaker 1: the Markmas Show. We're talking about the decentralized revolution and 657 00:36:16,040 --> 00:36:19,680 Speaker 1: the role that AI as a technology is playing in 658 00:36:19,719 --> 00:36:23,600 Speaker 1: this new revolution as it will lead to more decentralization. 659 00:36:23,880 --> 00:36:25,880 Speaker 1: That's what I got. Thanks so much for listening.