1 00:00:04,080 --> 00:00:07,020 Sean Aylmer: Welcome to the Fear & Greed daily interview. I'm Sean Aylmer. 2 00:00:07,230 --> 00:00:11,129 Sean Aylmer: Semiconductors are in almost everything these days from computers to 3 00:00:11,130 --> 00:00:14,309 Sean Aylmer: new cars. So it makes sense that the opportunities for 4 00:00:14,309 --> 00:00:18,389 Sean Aylmer: investors in this space are growing. According to Global Investment 5 00:00:18,389 --> 00:00:22,110 Sean Aylmer: Manager, Munro Partners, the rise of artificial intelligence could see 6 00:00:22,110 --> 00:00:26,220 Sean Aylmer: semiconductors become the new oil. Remember, this is general information 7 00:00:26,220 --> 00:00:29,129 Sean Aylmer: only. You should seek professional advice before making any investment 8 00:00:29,130 --> 00:00:32,608 Sean Aylmer: decisions. Nick Griffin is Munro Partner's founding partner and chief 9 00:00:32,670 --> 00:00:35,068 Sean Aylmer: investment Officer. Nick, welcome to Fair & Greed. 10 00:00:35,549 --> 00:00:36,690 Nick Griffin: Thanks very much for having me, Sean. 11 00:00:37,500 --> 00:00:41,070 Sean Aylmer: I tell you, I've realized how important semiconductors are only 12 00:00:41,070 --> 00:00:44,939 Sean Aylmer: in recent days when suddenly there's this flashpoint between the 13 00:00:44,940 --> 00:00:49,110 Sean Aylmer: US and China because the Taiwanese president is visiting and 14 00:00:49,110 --> 00:00:52,529 Sean Aylmer: they want a tax treaty on semiconductors, and it just hit 15 00:00:52,529 --> 00:00:57,750 Sean Aylmer: home how important the producer of a semiconductor chip has 16 00:00:57,750 --> 00:00:59,460 Sean Aylmer: become in 2023. 17 00:01:00,030 --> 00:01:02,190 Nick Griffin: Yeah, it's been going on for a little while, but 18 00:01:02,340 --> 00:01:04,289 Nick Griffin: yes, you're right. This is how the world's going to 19 00:01:04,289 --> 00:01:08,880 Nick Griffin: be for a while now. Taiwan makes 80% of what 20 00:01:08,880 --> 00:01:11,609 Nick Griffin: we call high performance semiconductors, or i. e., the best 21 00:01:11,609 --> 00:01:15,510 Nick Griffin: semiconductors, the fastest semiconductors in the world, and 80% of 22 00:01:15,510 --> 00:01:17,730 Nick Griffin: them are made in Taiwan and it's been that way 23 00:01:17,730 --> 00:01:21,389 Nick Griffin: for a while and people have suddenly realized how important 24 00:01:21,389 --> 00:01:24,780 Nick Griffin: these things are. And so now we sort of jostle 25 00:01:24,780 --> 00:01:27,209 Nick Griffin: around Taiwan the way we used to sort of worry 26 00:01:27,209 --> 00:01:30,479 Nick Griffin: about Saudi Arabia. Hence, the comm said that semiconductors are the 27 00:01:30,480 --> 00:01:30,899 Nick Griffin: new oil. 28 00:01:31,319 --> 00:01:35,640 Sean Aylmer: Okay, so for the people like me basically, I talk about 29 00:01:35,640 --> 00:01:37,980 Sean Aylmer: semiconductor chips as if I know exactly what they are. 30 00:01:38,039 --> 00:01:41,309 Sean Aylmer: Everyone needs a chip in everything they've got. But what 31 00:01:41,309 --> 00:01:43,920 Sean Aylmer: are they? They're actually, it's something that allows electrical currents, 32 00:01:43,920 --> 00:01:44,910 Sean Aylmer: is that what they are? 33 00:01:45,000 --> 00:01:48,839 Nick Griffin: Yeah. So basically if you think about computers, it's effectively, 34 00:01:48,840 --> 00:01:51,570 Nick Griffin: most of it's sort of binary code and they control 35 00:01:51,960 --> 00:01:55,530 Nick Griffin: the way the binary code flows on a semiconductor effectively. 36 00:01:55,620 --> 00:02:00,749 Nick Griffin: So they drive really simple things like your fridge to 37 00:02:00,929 --> 00:02:05,189 Nick Griffin: driving high- end hyperscale data centers that are effectively processing 38 00:02:05,190 --> 00:02:09,660 Nick Griffin: these AI applications like ChatGPT. And so depending on what you 39 00:02:09,660 --> 00:02:12,780 Nick Griffin: want to get processed, there's very simple, cheap ones that 40 00:02:12,780 --> 00:02:16,260 Nick Griffin: can cost as much as 10 cents to very complicated 41 00:02:16,260 --> 00:02:19,229 Nick Griffin: ones like the H- 100, which is the Nvidia product that 42 00:02:19,230 --> 00:02:22,260 Nick Griffin: they're using to power ChatGPT. And that costs roughly $35,000. 43 00:02:22,320 --> 00:02:26,638 Sean Aylmer: Okay. Where do they come from? As you said, 80% 44 00:02:26,669 --> 00:02:30,780 Sean Aylmer: of the high end chips come from Taiwan. Who else 45 00:02:30,780 --> 00:02:31,470 Sean Aylmer: produces them? 46 00:02:31,889 --> 00:02:36,389 Nick Griffin: Korea. So again, let's be really specific here. So semiconductors 47 00:02:36,389 --> 00:02:38,970 Nick Griffin: are made in many places all over the world. It's 48 00:02:39,179 --> 00:02:42,660 Nick Griffin: effectively a commoditized product, has been a commoditized product for 49 00:02:42,690 --> 00:02:45,419 Nick Griffin: a very long time. But at the high end or 50 00:02:45,419 --> 00:02:48,780 Nick Griffin: the bleeding edge of semiconductor development, when you're trying to 51 00:02:48,780 --> 00:02:52,500 Nick Griffin: process things very quickly, the real trick is to get 52 00:02:52,500 --> 00:02:55,679 Nick Griffin: more and more transistors or more and more ability to 53 00:02:55,679 --> 00:02:59,340 Nick Griffin: process code onto the one semiconductor chip. And so this 54 00:02:59,340 --> 00:03:02,430 Nick Griffin: is this concept of Moore's law. And unfortunately Gordon Moore 55 00:03:02,430 --> 00:03:05,100 Nick Griffin: died last week, but he was the CEO of Intel 56 00:03:05,100 --> 00:03:08,370 Nick Griffin: at the time when he pointed out that it appeared 57 00:03:08,370 --> 00:03:10,410 Nick Griffin: to him that every two years you could double the 58 00:03:10,410 --> 00:03:13,619 Nick Griffin: amount of transistors on an integrated circuit. And so what 59 00:03:13,620 --> 00:03:16,259 Nick Griffin: would happen back then in the '70s, you got roughly 2, 60 00:03:16,260 --> 00:03:20,010 Nick Griffin: 000 transistors on integrated circuit for the best, fastest one 61 00:03:20,400 --> 00:03:23,070 Nick Griffin: you could find in the world. And every two years 62 00:03:23,070 --> 00:03:28,229 Nick Griffin: they double it. The 2, 000 went to 4,000, the 4,000 went to 8,000, the 8,000 went to 16,000, 16 went to 63 00:03:28,230 --> 00:03:32,758 Nick Griffin: 32, and this year, Jensen Huang and Nvidia, which is 64 00:03:32,758 --> 00:03:35,909 Nick Griffin: now the premier semiconductor company in the world, put 84 65 00:03:35,910 --> 00:03:40,110 Nick Griffin: billion transistors on the one integrated circuit. And so what's 66 00:03:40,110 --> 00:03:42,330 Nick Griffin: happening at the bleeding edge, at the bleeding edge, at 67 00:03:42,330 --> 00:03:44,970 Nick Griffin: the really high performance end, they are using very, very 68 00:03:44,970 --> 00:03:48,929 Nick Griffin: complicated nanotechnology, which basically allows you to fit more and 69 00:03:48,929 --> 00:03:51,958 Nick Griffin: more transistors onto the same integrated circuit, which makes your computer 70 00:03:51,960 --> 00:03:55,410 Nick Griffin: faster. Faster your computer is, more things it can do. 71 00:03:55,920 --> 00:03:58,890 Nick Griffin: More things it can do, more valuable it is. And so 72 00:03:58,890 --> 00:04:00,300 Nick Griffin: that's what we're talking about when we talk about the 73 00:04:00,300 --> 00:04:00,840 Nick Griffin: bleeding edge. 74 00:04:01,530 --> 00:04:07,169 Sean Aylmer: Let's introduce artificial intelligence into this. I would imagine, given 75 00:04:07,170 --> 00:04:09,029 Sean Aylmer: what we've seen in the last few months, or at 76 00:04:09,030 --> 00:04:10,829 Sean Aylmer: least the general public has seen in the last few 77 00:04:10,830 --> 00:04:15,720 Sean Aylmer: months around artificial intelligence, the ChatGPTs of the world, et cetera, 78 00:04:16,260 --> 00:04:20,220 Sean Aylmer: that this is kind of a major step forward for 79 00:04:20,220 --> 00:04:23,279 Sean Aylmer: that industry, but also in the need for chips. 80 00:04:23,880 --> 00:04:26,219 Nick Griffin: Correct, yeah. So the other way to think about this, 81 00:04:26,219 --> 00:04:29,549 Nick Griffin: okay, so if Moore's law's been going since 1970 and 82 00:04:29,549 --> 00:04:33,180 Nick Griffin: it's still going today, as we've gone through this ability 83 00:04:33,180 --> 00:04:35,580 Nick Griffin: for computers to get faster, they can do more things 84 00:04:35,580 --> 00:04:38,700 Nick Griffin: and they hence create more value. So if you go 85 00:04:38,700 --> 00:04:41,820 Nick Griffin: back in time, you probably remember your first personal computer 86 00:04:41,820 --> 00:04:44,460 Nick Griffin: and you go, " Wow, that's pretty cool." Before that, there 87 00:04:44,460 --> 00:04:46,980 Nick Griffin: was just a mainframe computer. I remember my Apple IIe, 88 00:04:47,250 --> 00:04:50,789 Nick Griffin: that's how old I am. And then about 15, 20 years 89 00:04:50,790 --> 00:04:53,190 Nick Griffin: later, they got that computer onto a telephone called an 90 00:04:53,190 --> 00:04:56,339 Nick Griffin: iPhone. And that was your iPhone moment. You went, " Holy 91 00:04:56,339 --> 00:04:58,650 Nick Griffin: cow, I can get the internet on a telephone now." 92 00:04:59,130 --> 00:05:02,040 Nick Griffin: That can do more things and that creates Apple. And 93 00:05:02,040 --> 00:05:05,100 Nick Griffin: then on that phone, over time, Moore's law continued. We 94 00:05:05,100 --> 00:05:08,250 Nick Griffin: can share pictures and that creates social media and Facebook. 95 00:05:08,790 --> 00:05:11,640 Nick Griffin: And then over time, Moore's law continues, packet sizes get 96 00:05:11,640 --> 00:05:13,529 Nick Griffin: smaller, we can do more things, we can stream video. 97 00:05:13,529 --> 00:05:16,830 Nick Griffin: That creates Netflix. And then they create the cloud, and 98 00:05:16,830 --> 00:05:19,889 Nick Griffin: then software goes to the cloud, which reinvigorates Microsoft. And 99 00:05:19,889 --> 00:05:22,709 Nick Griffin: then suddenly, as I always joke about, my kids are 100 00:05:22,709 --> 00:05:25,620 Nick Griffin: tracking Ubers to their house to pick up food, and 101 00:05:25,620 --> 00:05:27,540 Nick Griffin: that's how we order food. And so all of this 102 00:05:27,540 --> 00:05:30,390 Nick Griffin: progress is happening because of Moore's laws continuing and computers 103 00:05:30,390 --> 00:05:34,319 Nick Griffin: are getting faster. So AI is just the next development 104 00:05:34,320 --> 00:05:36,330 Nick Griffin: in this, if that makes sense. So suddenly you've had, 105 00:05:36,330 --> 00:05:39,779 Nick Griffin: again, one of these iPhone moments, ChatGPTs come out and 106 00:05:39,779 --> 00:05:41,549 Nick Griffin: you're like, " Wow, this is really cool. I can do 107 00:05:41,549 --> 00:05:44,279 Nick Griffin: stuff with this." And now everyone's running around trying to 108 00:05:44,279 --> 00:05:46,170 Nick Griffin: work out, well, who's going to be the big winner 109 00:05:46,170 --> 00:05:47,610 Nick Griffin: here, who's going to be the Apple of AI? 110 00:05:48,600 --> 00:05:50,310 Sean Aylmer: Stay with me, Nick, we'll be back in a minute. 111 00:05:56,580 --> 00:05:59,190 Sean Aylmer: My guest this morning is Nick Griffin, founding partner and 112 00:05:59,190 --> 00:06:04,110 Sean Aylmer: chief investment officer at Munro Partners. So let's bring it 113 00:06:04,350 --> 00:06:08,070 Sean Aylmer: a little bit more towards that and towards investing opportunities. 114 00:06:08,820 --> 00:06:12,690 Sean Aylmer: Should we be thinking about specific companies in this space? 115 00:06:13,020 --> 00:06:16,379 Sean Aylmer: Do we actually go to, I don't know, resources company 116 00:06:16,379 --> 00:06:20,730 Sean Aylmer: that suddenly is better at adapting this sort of technology? 117 00:06:20,850 --> 00:06:22,560 Sean Aylmer: As an investor, how do you think about it? 118 00:06:23,250 --> 00:06:25,110 Nick Griffin: Yeah, so from my point of view, there's a couple of 119 00:06:25,110 --> 00:06:27,570 Nick Griffin: ways you can think about it. There's one, there's the 120 00:06:27,570 --> 00:06:29,938 Nick Griffin: simple, what we would call the weapons manufacturers in the 121 00:06:29,940 --> 00:06:33,299 Nick Griffin: war, or the shovels in the boom and the shovels 122 00:06:33,299 --> 00:06:35,068 Nick Griffin: in the mining boom. And the shovels in the mining 123 00:06:35,070 --> 00:06:37,830 Nick Griffin: boom for this company are those high end semiconductors. So 124 00:06:38,070 --> 00:06:41,428 Nick Griffin: that bleeding edge semiconductors, because the people who control the 125 00:06:41,430 --> 00:06:46,980 Nick Griffin: technology that allows you to get another 160 billion transistors 126 00:06:46,980 --> 00:06:49,619 Nick Griffin: onto an integrated circuit, they're the most important people in the 127 00:06:49,620 --> 00:06:52,589 Nick Griffin: world here because whoever's got the fastest semiconductors is going 128 00:06:52,589 --> 00:06:57,510 Nick Griffin: to win in AI. Why? Because you're basically processing reams 129 00:06:57,510 --> 00:07:00,720 Nick Griffin: and reams of data really, really quickly to create generative 130 00:07:00,720 --> 00:07:04,289 Nick Griffin: outcomes or predictive outcomes. So the shovels in that boom 131 00:07:04,290 --> 00:07:08,069 Nick Griffin: are companies like Nvidia that design the chips that a 132 00:07:08,070 --> 00:07:11,069 Nick Griffin: lot of this stuff runs on, or companies like, in 133 00:07:11,070 --> 00:07:13,890 Nick Griffin: our opinion, companies like TSMC, the foundries that make these 134 00:07:13,890 --> 00:07:17,130 Nick Griffin: chips. So that's where Taiwan comes in. Or companies like 135 00:07:17,160 --> 00:07:21,059 Nick Griffin: ASML in lithography, the Dutch company that actually builds the 136 00:07:21,059 --> 00:07:23,429 Nick Griffin: machines that allows us to get more and more transistors 137 00:07:23,429 --> 00:07:26,429 Nick Griffin: onto the integrated circuit. So that's the shovel, so to speak. 138 00:07:26,700 --> 00:07:28,920 Sean Aylmer: And just before we leave the shovel, so it's not 139 00:07:29,549 --> 00:07:31,980 Sean Aylmer: like that last one you talked about ASML, the Dutch 140 00:07:31,980 --> 00:07:35,610 Sean Aylmer: company. So it's not even necessarily specifically the person who 141 00:07:35,610 --> 00:07:38,970 Sean Aylmer: is manufacturing the chips, it's actually the person who is 142 00:07:39,179 --> 00:07:41,609 Sean Aylmer: manufacturing the infrastructure for the chips to work. 143 00:07:42,030 --> 00:07:43,920 Nick Griffin: The tools that create the chips. 144 00:07:44,099 --> 00:07:44,820 Sean Aylmer: Yes, right. 145 00:07:45,179 --> 00:07:48,149 Nick Griffin: And so the tools to shrink more and moron involves 146 00:07:48,480 --> 00:07:51,420 Nick Griffin: very advanced lithography. This is some pretty, sorry, this is 147 00:07:51,600 --> 00:07:54,690 Nick Griffin: heavy duty stuff to get into 12 minutes. But yeah, 148 00:07:54,690 --> 00:07:58,620 Nick Griffin: essentially the lithography that creates the stencil to put the 149 00:07:58,620 --> 00:08:02,069 Nick Griffin: 81 billion chips, which you now need to go to 161 150 00:08:02,070 --> 00:08:06,239 Nick Griffin: and eventually 320 billion. So that's ASML for tools, TSMC 151 00:08:06,240 --> 00:08:09,540 Nick Griffin: is the foundry, Nvidia is the designer. Those are the 152 00:08:10,680 --> 00:08:12,150 Nick Griffin: three players we're talking about there. 153 00:08:12,180 --> 00:08:15,929 Sean Aylmer: Can I just make a comment here, given how high- 154 00:08:15,929 --> 00:08:18,600 Sean Aylmer: tech we're talking, lithography is an ancient art. 155 00:08:18,929 --> 00:08:19,680 Nick Griffin: Yes, it is. 156 00:08:19,980 --> 00:08:23,969 Sean Aylmer: So that's pretty cool. Okay, so we can invest in 157 00:08:23,969 --> 00:08:26,970 Sean Aylmer: that way. Then what about beyond, so the next way 158 00:08:26,970 --> 00:08:27,510 Sean Aylmer: of investing? 159 00:08:27,720 --> 00:08:31,110 Nick Griffin: Okay, so that's the shovels. And we've looked at those 160 00:08:31,110 --> 00:08:33,570 Nick Griffin: companies for a long time and we've owned them in 161 00:08:33,570 --> 00:08:36,328 Nick Griffin: the fund for a long time. And as you said 162 00:08:36,330 --> 00:08:37,740 Nick Griffin: at the start, to be clear, this is not personal 163 00:08:37,740 --> 00:08:42,179 Nick Griffin: advice. These are things we like and hold. The second 164 00:08:42,179 --> 00:08:43,740 Nick Griffin: way to think about it is who's going to be 165 00:08:43,740 --> 00:08:47,130 Nick Griffin: able to harness this technology and use it? And the 166 00:08:47,130 --> 00:08:51,990 Nick Griffin: obvious recent winner here is Microsoft, in our opinion. Microsoft 167 00:08:52,860 --> 00:08:55,949 Nick Griffin: has the ability, has the data, has its partnership with 168 00:08:56,009 --> 00:08:58,799 Nick Griffin: OpenAI or the people who created ChatGPT, and they're going 169 00:08:58,799 --> 00:09:01,828 Nick Griffin: to create these products like Copilot, and they've already shown 170 00:09:01,830 --> 00:09:04,740 Nick Griffin: you these. And so AI to date has been a 171 00:09:04,740 --> 00:09:07,650 Nick Griffin: bit like autopilot. So you've actually been living with AI 172 00:09:07,650 --> 00:09:10,800 Nick Griffin: for at least seven or eight years now already. It's 173 00:09:10,800 --> 00:09:13,380 Nick Griffin: the recommendations that come up in your Amazon shopping feed. 174 00:09:13,380 --> 00:09:17,940 Nick Griffin: It's what Netflix thinks you should watch next, it's how 175 00:09:17,940 --> 00:09:20,699 Nick Griffin: they park your car, how you land your drone, but 176 00:09:20,700 --> 00:09:23,520 Nick Griffin: now it goes from autopilot, i. e., it's giving you 177 00:09:23,520 --> 00:09:26,130 Nick Griffin: stuff that you didn't ask for to copilot. And so 178 00:09:26,130 --> 00:09:29,280 Nick Griffin: the simple way Microsoft describes this is they could record 179 00:09:29,280 --> 00:09:32,969 Nick Griffin: this recording. So say we did this over Teams, Microsoft 180 00:09:32,969 --> 00:09:35,399 Nick Griffin: would record it and at the end it would summarize the meeting. 181 00:09:35,520 --> 00:09:38,040 Nick Griffin: It would say, Nick said this, Sean said that, et 182 00:09:38,040 --> 00:09:40,500 Nick Griffin: cetera. We could then get it to compose an email 183 00:09:40,500 --> 00:09:43,348 Nick Griffin: to do the follow- ups. We can now ask our 184 00:09:43,350 --> 00:09:46,889 Nick Griffin: office applications to search our previous emails to find summaries 185 00:09:46,889 --> 00:09:49,559 Nick Griffin: of certain things where we've discussed this, if that makes 186 00:09:49,559 --> 00:09:52,770 Nick Griffin: sense. So think about ChatGPT, but in office. So that's a 187 00:09:52,770 --> 00:09:54,720 Nick Griffin: great way to monetize it because I would probably pay 188 00:09:54,720 --> 00:09:57,840 Nick Griffin: an extra $ 10 for my Teams subscription if it summarized 189 00:09:57,840 --> 00:09:58,800 Nick Griffin: all my meetings for me. 190 00:09:58,920 --> 00:09:59,550 Sean Aylmer: Absolutely. 191 00:09:59,760 --> 00:10:02,249 Nick Griffin: Other winners here are other software companies who can do 192 00:10:02,250 --> 00:10:06,000 Nick Griffin: this, but they'll potentially be software losers. Google's probably a 193 00:10:06,000 --> 00:10:07,740 Nick Griffin: winner here because they've got the most data and they've 194 00:10:07,740 --> 00:10:09,780 Nick Griffin: got the best AI, but they probably don't know how 195 00:10:09,780 --> 00:10:13,410 Nick Griffin: to monetize it. But most importantly, I think it's a 196 00:10:13,410 --> 00:10:15,210 Nick Griffin: bit like your iPhone moment. It's just one of these 197 00:10:15,210 --> 00:10:16,920 Nick Griffin: great things that's going to come along that's going to 198 00:10:16,920 --> 00:10:19,199 Nick Griffin: make us all a bit more productive. And that's a 199 00:10:19,200 --> 00:10:19,530 Nick Griffin: good thing. 200 00:10:20,070 --> 00:10:22,649 Sean Aylmer: What about the risks? Where do you see, I'm sure 201 00:10:22,650 --> 00:10:27,149 Sean Aylmer: we've got the normal risks, security, privacy and over time 202 00:10:27,210 --> 00:10:30,840 Sean Aylmer: they will probably be addressed and hopefully adequately addressed, but 203 00:10:30,840 --> 00:10:33,450 Sean Aylmer: where do you see the big risks for where we 204 00:10:33,450 --> 00:10:33,840 Sean Aylmer: are going? 205 00:10:34,470 --> 00:10:37,020 Nick Griffin: So there's probably two big risks I'd flag. One is 206 00:10:37,020 --> 00:10:39,449 Nick Griffin: the geopolitical risks you said at the start. So this 207 00:10:39,450 --> 00:10:43,650 Nick Griffin: technology's highly sought after and the Americans are trying to 208 00:10:43,650 --> 00:10:45,599 Nick Griffin: do a pretty good job of making sure the Chinese 209 00:10:45,599 --> 00:10:48,450 Nick Griffin: can't get access to it, and that I suspect will 210 00:10:48,450 --> 00:10:51,540 Nick Griffin: upset them at some point. So there's that risk without 211 00:10:51,540 --> 00:10:53,820 Nick Griffin: a doubt that could affect the shovel side of the 212 00:10:53,820 --> 00:10:56,160 Nick Griffin: equation. The second risk is really around copyright. 213 00:10:56,161 --> 00:10:56,731 Sean Aylmer: Yeah. 214 00:10:57,389 --> 00:10:59,519 Nick Griffin: Yeah. And I think this is overcomable, but if you think 215 00:10:59,520 --> 00:11:01,919 Nick Griffin: about back when we didn't want to put our data 216 00:11:01,920 --> 00:11:02,549 Nick Griffin: in the cloud- 217 00:11:02,759 --> 00:11:05,309 Sean Aylmer: Sorry, hold on, Nick. Do you reckon that ChatGPT would 218 00:11:05,309 --> 00:11:05,821 Sean Aylmer: use the word overcomeable? 219 00:11:05,821 --> 00:11:10,560 Nick Griffin: Overcomeable? Probably not. It's a good point. 220 00:11:10,679 --> 00:11:12,059 Sean Aylmer: It's a copyright issue here, I think. Go on. 221 00:11:12,059 --> 00:11:15,330 Nick Griffin: We're going to use the, that's my thesaurus right there. 222 00:11:15,330 --> 00:11:20,220 Nick Griffin: But it can be overcome. From our point of view, 223 00:11:21,059 --> 00:11:22,769 Nick Griffin: if you think about when we moved to the cloud, 224 00:11:22,770 --> 00:11:25,080 Nick Griffin: everyone was worried about putting their data in the cloud 225 00:11:25,080 --> 00:11:27,000 Nick Griffin: and now we all happily put our data in the 226 00:11:27,000 --> 00:11:30,929 Nick Griffin: cloud. ChatGPT and generative AI is effectively mining your own 227 00:11:30,929 --> 00:11:34,469 Nick Griffin: data to give you predictive outcomes. Some people won't like 228 00:11:34,469 --> 00:11:38,520 Nick Griffin: that. They're reading your emails and that will take a 229 00:11:38,520 --> 00:11:41,129 Nick Griffin: little while for people to overcome or overcomeable. 230 00:11:42,960 --> 00:11:46,920 Sean Aylmer: Yes. Look, we're out of time, but at some point 231 00:11:46,920 --> 00:11:48,358 Sean Aylmer: we might come back and talk about some of those 232 00:11:48,360 --> 00:11:50,939 Sean Aylmer: risks because that whole copyright where the information and the 233 00:11:50,940 --> 00:11:53,550 Sean Aylmer: data comes from is going to be something we'll be 234 00:11:53,550 --> 00:11:56,789 Sean Aylmer: talking about for years, I dare say. But we are out 235 00:11:56,790 --> 00:11:59,760 Sean Aylmer: of time. So Nick, I can say genuinely this is 236 00:11:59,760 --> 00:12:02,190 Sean Aylmer: one of the more interesting, well, probably the most interesting 237 00:12:02,190 --> 00:12:05,699 Sean Aylmer: interview I've done all year, Nick. I say that genuinely 238 00:12:05,820 --> 00:12:08,218 Sean Aylmer: because it's not an area I know much about and 239 00:12:08,220 --> 00:12:11,820 Sean Aylmer: you explained it in language that I could understand. So 240 00:12:11,820 --> 00:12:13,950 Sean Aylmer: thank you for being part of Fear & Greed this morning. 241 00:12:14,130 --> 00:12:16,439 Nick Griffin: It is actually April, so hopefully I can hold that 242 00:12:16,440 --> 00:12:17,969 Nick Griffin: title for the rest of the year, but thanks very 243 00:12:17,969 --> 00:12:18,630 Nick Griffin: much for having me. 244 00:12:18,990 --> 00:12:22,050 Sean Aylmer: That was Nick Griffin, founding partner and chief investment officer 245 00:12:22,050 --> 00:12:25,078 Sean Aylmer: at Munro Partners. This is the Fear & Greed daily interview. 246 00:12:25,080 --> 00:12:27,690 Sean Aylmer: Remember, this is general information only and you should seek 247 00:12:27,690 --> 00:12:31,650 Sean Aylmer: professional advice before making investment decisions. Join us every morning 248 00:12:31,650 --> 00:12:34,500 Sean Aylmer: for the full episode of Fear & Greed, Australia's most popular 249 00:12:34,500 --> 00:12:37,260 Sean Aylmer: business podcast. I'm Sean Aylmer, enjoy your day.