1 00:00:05,640 --> 00:00:08,440 Speaker 1: Welcome to the Fear and Greed Business Interview. I'm Sean Alm. 2 00:00:08,480 --> 00:00:11,360 Speaker 1: The arrival of a new player in the AI space 3 00:00:11,720 --> 00:00:16,200 Speaker 1: has sent a major shockwaves through financial markets. Chinese AI 4 00:00:16,360 --> 00:00:19,360 Speaker 1: company dep Sik has only founded about eighteen months ago, 5 00:00:19,400 --> 00:00:22,560 Speaker 1: but its new large language model app has been downloaded 6 00:00:22,600 --> 00:00:24,919 Speaker 1: millions of times in just the last few days and 7 00:00:25,239 --> 00:00:29,040 Speaker 1: the market response has been swift. On Monday night, Australian 8 00:00:29,080 --> 00:00:33,240 Speaker 1: time chip maker and Video fell seventeen percent, wiping five 9 00:00:33,360 --> 00:00:36,520 Speaker 1: hundred and eighty nine billion US dollars. That's not far 10 00:00:36,560 --> 00:00:39,560 Speaker 1: off a trillion Aussie dollars from its market cap, the 11 00:00:39,600 --> 00:00:42,960 Speaker 1: biggest one day value wipeout of any company in history. 12 00:00:43,440 --> 00:00:46,479 Speaker 1: While in all likely n Video will rebound and this 13 00:00:46,560 --> 00:00:49,600 Speaker 1: interview is being recorded on Tuesday afternoon. The emergence of 14 00:00:49,600 --> 00:00:53,040 Speaker 1: a Chinese competitor producing an AI model at a fraction 15 00:00:53,120 --> 00:00:55,800 Speaker 1: of the cost has raised plenty of questions, and not 16 00:00:56,080 --> 00:00:59,440 Speaker 1: just for Nvidia. As always, this podcast contains general information 17 00:00:59,560 --> 00:01:02,800 Speaker 1: only and you should seek professional advice before making investment decisions. 18 00:01:02,880 --> 00:01:05,720 Speaker 1: We speak regularly to Roger Montgomery, founder and chief investment 19 00:01:05,760 --> 00:01:09,320 Speaker 1: officer at Montgomery Investment Management. October last year, we talked 20 00:01:09,319 --> 00:01:13,080 Speaker 1: about AI and Roger's own concerns that it was being overhyped, 21 00:01:13,120 --> 00:01:16,040 Speaker 1: with the real benefits to come in later waves. Roger, 22 00:01:16,080 --> 00:01:17,760 Speaker 1: welcome back to Fear and Greed. 23 00:01:18,520 --> 00:01:20,480 Speaker 2: Great to be with you, Sean, thanks for having me 24 00:01:20,520 --> 00:01:21,440 Speaker 2: on the program again. 25 00:01:21,840 --> 00:01:26,520 Speaker 1: So very quickly, what has Deep Seek done and why 26 00:01:26,560 --> 00:01:27,400 Speaker 1: are we so worried? 27 00:01:28,480 --> 00:01:35,399 Speaker 2: Well, evidently, I might even say apparently, Yeah, they've developed 28 00:01:35,760 --> 00:01:40,400 Speaker 2: a large language model, an AI powered large language model 29 00:01:40,959 --> 00:01:47,080 Speaker 2: for six million US dollars that is reportedly superior to chat, 30 00:01:47,120 --> 00:01:50,000 Speaker 2: GPT and some of the other versions that are out there. 31 00:01:50,560 --> 00:01:55,880 Speaker 2: That really is quite disruptive. And because valuations were so 32 00:01:56,080 --> 00:02:00,720 Speaker 2: extreme for these AI related stocks, there's been a bit 33 00:02:00,760 --> 00:02:03,680 Speaker 2: of a reckoning or a bit of a realignment of expectations. 34 00:02:04,360 --> 00:02:08,640 Speaker 1: Okay, so just let's dive into that. It's not so 35 00:02:08,800 --> 00:02:13,320 Speaker 1: much the actual technology that's been that it's emerged. It's 36 00:02:13,320 --> 00:02:16,840 Speaker 1: the fact that it's been done so cheaply. Is that 37 00:02:16,880 --> 00:02:18,799 Speaker 1: what was really hit markets? 38 00:02:19,080 --> 00:02:21,280 Speaker 2: Well, how do we even know that the Chinese haven't 39 00:02:21,320 --> 00:02:26,919 Speaker 2: just copied chatch ept you know? So? So, I mean, 40 00:02:27,600 --> 00:02:30,359 Speaker 2: more technically savvy people might know that there's a difference 41 00:02:30,440 --> 00:02:33,440 Speaker 2: or might be able to appraise a distinction between these 42 00:02:33,520 --> 00:02:38,239 Speaker 2: large language models, But that's not my capability. It is remarkable, 43 00:02:38,600 --> 00:02:41,000 Speaker 2: I think, and I don't know if anyone's talking about this, 44 00:02:41,080 --> 00:02:45,000 Speaker 2: but I think that the timing of the announcement has 45 00:02:45,080 --> 00:02:49,000 Speaker 2: something to do with undermining Donald Trump's stargate five hundred 46 00:02:49,000 --> 00:02:52,720 Speaker 2: billion dollar investment announcement over the last week or two. 47 00:02:53,320 --> 00:02:56,120 Speaker 2: And consequently, you know, when you start to think, if 48 00:02:56,120 --> 00:02:58,160 Speaker 2: you can, if you can build a large language model 49 00:02:58,160 --> 00:03:02,120 Speaker 2: that's aipowered for six million US dollars, why does anyone 50 00:03:02,160 --> 00:03:05,080 Speaker 2: need to invest five hundred billion US dollars in the 51 00:03:05,160 --> 00:03:10,919 Speaker 2: United States. So there's potentially an undermining element to this announcement. 52 00:03:11,600 --> 00:03:14,160 Speaker 2: And I don't know whether or not that matters to investors. 53 00:03:14,240 --> 00:03:18,280 Speaker 2: Probably doesn't. What does matter to investors is that the 54 00:03:18,400 --> 00:03:21,240 Speaker 2: US S and P five hundred and the Nasdaq, the 55 00:03:21,280 --> 00:03:24,480 Speaker 2: gains in those markets have been very concentrated on the 56 00:03:24,480 --> 00:03:28,160 Speaker 2: back of this AI theme. And consequently, you know, the 57 00:03:28,560 --> 00:03:32,000 Speaker 2: US market leadership might change now, and so might the 58 00:03:32,480 --> 00:03:34,560 Speaker 2: potential returns for investors. 59 00:03:34,720 --> 00:03:38,360 Speaker 1: And so take end video. Is the point here that 60 00:03:38,680 --> 00:03:42,360 Speaker 1: not as many Nvidia chips may be needed in the 61 00:03:42,400 --> 00:03:46,520 Speaker 1: future if you can have a Chinese startup effectively creating 62 00:03:46,600 --> 00:03:51,600 Speaker 1: a chat GPT equivalent and using They've used the Nvidia chips, 63 00:03:51,600 --> 00:03:54,160 Speaker 1: so that's true, but they didn't even use the latest 64 00:03:54,240 --> 00:03:57,320 Speaker 1: version according to reports. And we keep having all these 65 00:03:57,400 --> 00:04:00,760 Speaker 1: qualifiers on this, but that the case, Maybe we don't 66 00:04:00,800 --> 00:04:02,960 Speaker 1: need as many Nvidio chips, Maybe we don't need as 67 00:04:03,000 --> 00:04:06,680 Speaker 1: many data centers, Maybe we don't need the uranium stocks 68 00:04:06,680 --> 00:04:08,600 Speaker 1: that sold off yesterday, because maybe we don't need the 69 00:04:08,760 --> 00:04:11,480 Speaker 1: energy that we thought were going to Is that what 70 00:04:11,480 --> 00:04:13,760 Speaker 1: we're talking about, then how do we get our head 71 00:04:13,760 --> 00:04:15,040 Speaker 1: around that as an investor? 72 00:04:15,480 --> 00:04:18,240 Speaker 2: Well, that's what everyone's talking about, So you know, there 73 00:04:18,240 --> 00:04:22,520 Speaker 2: are all the consequences of building too much optimism into 74 00:04:22,600 --> 00:04:27,240 Speaker 2: share prices. And you might remember, Sean, we were talking 75 00:04:27,320 --> 00:04:30,000 Speaker 2: about this either last year or the year before. You 76 00:04:30,080 --> 00:04:32,880 Speaker 2: might remember I gave the example. We did a special 77 00:04:33,120 --> 00:04:37,560 Speaker 2: I think and I talked about commercial air travel, cars 78 00:04:37,760 --> 00:04:42,080 Speaker 2: and the television as examples of technology where investors lost 79 00:04:42,120 --> 00:04:46,320 Speaker 2: out but consumers won. And this could very well be 80 00:04:46,360 --> 00:04:51,919 Speaker 2: another example of that. Where we've got new technology, consumers 81 00:04:52,040 --> 00:04:56,000 Speaker 2: are the beneficiaries and shareholders who paid too much and 82 00:04:56,080 --> 00:05:00,159 Speaker 2: invested too much without knowing who the winner was going 83 00:05:00,160 --> 00:05:02,719 Speaker 2: to be and how the competitive landscape was going to 84 00:05:02,720 --> 00:05:05,040 Speaker 2: look in the future, which is always the great difficulty 85 00:05:05,320 --> 00:05:07,880 Speaker 2: with new technology. They lose out. 86 00:05:08,440 --> 00:05:10,400 Speaker 1: Stay with me, Roger, we'll be back in a minute. 87 00:05:17,080 --> 00:05:21,800 Speaker 1: I'm speaking to Roger Montgomery from Montgomery Investment Management. Okay, 88 00:05:22,160 --> 00:05:24,040 Speaker 1: So one of the things I think we sort of 89 00:05:24,080 --> 00:05:27,359 Speaker 1: worked out before the break is that there's not great 90 00:05:27,400 --> 00:05:32,560 Speaker 1: certainty about exactly what has been developed in China. What 91 00:05:32,600 --> 00:05:35,880 Speaker 1: does it say about the S and P five hundred 92 00:05:36,080 --> 00:05:38,600 Speaker 1: magnificent seven, the fact that they are such a big 93 00:05:38,680 --> 00:05:42,680 Speaker 1: chunk of that market, big chunk of the Misky World Index, 94 00:05:43,640 --> 00:05:48,320 Speaker 1: the whole priced perfection argument, It looks a little bit 95 00:05:48,320 --> 00:05:49,159 Speaker 1: frail at the moment. 96 00:05:49,880 --> 00:05:55,960 Speaker 2: Yeah. Look, whenever financial market performance and valuations hinge on 97 00:05:55,720 --> 00:05:59,760 Speaker 2: you on a handful of outperforming stocks, then you know, 98 00:05:59,800 --> 00:06:03,840 Speaker 2: even even a minor disturbance can lead to the narrative 99 00:06:04,080 --> 00:06:07,360 Speaker 2: you have something where the narrative changes, it can lead 100 00:06:07,400 --> 00:06:11,240 Speaker 2: to traumatic consequences. And that's what we're seeing here now. 101 00:06:12,000 --> 00:06:14,440 Speaker 2: Neither you, nor I nor anyone else knows whether or 102 00:06:14,440 --> 00:06:17,520 Speaker 2: not this is temporary or a permanent shift. But what 103 00:06:17,600 --> 00:06:21,200 Speaker 2: I do know that happens time and time again is 104 00:06:21,240 --> 00:06:26,520 Speaker 2: that you have expectations that are often too optimistic built 105 00:06:26,520 --> 00:06:30,160 Speaker 2: into share prices of leadership stocks, and particularly when new 106 00:06:30,160 --> 00:06:33,800 Speaker 2: technology is emerging, and you don't need much to disrupt 107 00:06:33,839 --> 00:06:36,600 Speaker 2: that narrative. And that's what's happened here. The narrative has 108 00:06:36,640 --> 00:06:39,400 Speaker 2: been disrupted. And because the S and P five hundred, 109 00:06:39,400 --> 00:06:42,720 Speaker 2: the Nasdaq, the MISKY are all of the gains over 110 00:06:42,760 --> 00:06:45,599 Speaker 2: the last few years have largely been driven or a 111 00:06:45,680 --> 00:06:47,880 Speaker 2: large percentage of those gains have been driven by just 112 00:06:47,880 --> 00:06:50,599 Speaker 2: a handful of these stocks. When the narrative for the 113 00:06:50,640 --> 00:06:54,480 Speaker 2: outlook of those companies changes, then so does the returns. 114 00:06:54,880 --> 00:06:57,960 Speaker 2: Which is why you know, last year I was suggesting 115 00:06:58,040 --> 00:07:02,279 Speaker 2: that investors look at caps rather than looking at these 116 00:07:02,320 --> 00:07:05,560 Speaker 2: big cap stocks, and that the gap between the pe 117 00:07:05,720 --> 00:07:10,200 Speaker 2: ratios of these megacaps and small caps would narrow. Now, 118 00:07:10,240 --> 00:07:12,120 Speaker 2: what we don't know is whether or not narrow is 119 00:07:12,120 --> 00:07:15,560 Speaker 2: because the small caps rally, which they have done since 120 00:07:15,560 --> 00:07:18,920 Speaker 2: we talked about that, and or the pees of the 121 00:07:19,000 --> 00:07:21,280 Speaker 2: large caps or the megacap starts to come down, which 122 00:07:21,320 --> 00:07:22,000 Speaker 2: is now happening. 123 00:07:22,600 --> 00:07:26,120 Speaker 1: Okay, leaving aside the investment case, here, is this an 124 00:07:26,200 --> 00:07:32,640 Speaker 1: example of commoditization of an apparent technology breakthrough happening really fast. 125 00:07:33,600 --> 00:07:35,720 Speaker 2: Look, I think that's a really good way of describing it. 126 00:07:35,880 --> 00:07:39,239 Speaker 2: This is not the first technology where this has happened. 127 00:07:39,280 --> 00:07:41,720 Speaker 2: I mean, we've got to remember that US leadership has 128 00:07:41,720 --> 00:07:44,360 Speaker 2: been challenged in the past, that it was the Soviets 129 00:07:44,400 --> 00:07:47,520 Speaker 2: that put the first satellite into space. You know, in 130 00:07:47,520 --> 00:07:52,400 Speaker 2: the US leadership in military technologies constantly being challenged. So 131 00:07:52,440 --> 00:07:55,560 Speaker 2: this is the first time. But this development, what it 132 00:07:55,600 --> 00:07:59,920 Speaker 2: does is that if it's caviate in place, if it's 133 00:08:00,280 --> 00:08:03,400 Speaker 2: as legitimate as it appears, then it does pose a 134 00:08:03,440 --> 00:08:06,800 Speaker 2: direct challenge to Invidia because you know, their chips are 135 00:08:06,800 --> 00:08:10,520 Speaker 2: over forty US thousand dollars each, their GPUs, and they 136 00:08:10,640 --> 00:08:15,680 Speaker 2: have been assumed to be the backbone of AI training worldwide. 137 00:08:16,320 --> 00:08:18,560 Speaker 2: Maybe they're not needed, and certainly the new and more 138 00:08:18,560 --> 00:08:20,600 Speaker 2: expensive chips might not be needed. 139 00:08:21,000 --> 00:08:24,880 Speaker 1: So both Nvidia's boss, Jensen Huang and Donald Trump, the 140 00:08:25,000 --> 00:08:27,320 Speaker 1: US predecedent, have effectively in last twenty four hours come 141 00:08:27,320 --> 00:08:29,520 Speaker 1: out and said, hey, this is good news. Is it 142 00:08:29,600 --> 00:08:32,560 Speaker 1: possible that it is good news because it just makes 143 00:08:32,600 --> 00:08:35,280 Speaker 1: things cheaper by the time it gets to someone like 144 00:08:35,320 --> 00:08:37,559 Speaker 1: you or I do you know one of the. 145 00:08:37,520 --> 00:08:41,400 Speaker 2: Most reliable cell signals that I've ever come across as 146 00:08:41,400 --> 00:08:46,320 Speaker 2: a professional investor has been a competitor emerged, and I 147 00:08:46,400 --> 00:08:48,920 Speaker 2: went and spoke to the CEO about the new competitor, 148 00:08:49,679 --> 00:08:52,880 Speaker 2: and the classic answer from the CEO is on of 149 00:08:52,920 --> 00:08:55,319 Speaker 2: this is great. This expands the market, This brings more 150 00:08:55,360 --> 00:08:58,120 Speaker 2: people to the market. This is great. No, No, your 151 00:08:58,160 --> 00:09:03,120 Speaker 2: company was priced leadership. Your company, the PE ratio put 152 00:09:03,160 --> 00:09:06,960 Speaker 2: on your stock was assuming that you would remain the 153 00:09:07,080 --> 00:09:10,920 Speaker 2: leader for infinity, and that is now not the case. 154 00:09:11,360 --> 00:09:13,880 Speaker 2: So there's a new PE regime that needs to be 155 00:09:13,920 --> 00:09:16,640 Speaker 2: applied to your stock. And that's what I think we're 156 00:09:16,640 --> 00:09:20,720 Speaker 2: seeing here. So Trump's comments and the CEO of Nvidia's comments, 157 00:09:21,360 --> 00:09:25,760 Speaker 2: you know, they are a classic response to saving face. 158 00:09:26,360 --> 00:09:28,680 Speaker 2: You know, it's an example of saving face when really 159 00:09:29,040 --> 00:09:31,199 Speaker 2: your leadership is potentially being undermined. 160 00:09:32,240 --> 00:09:35,600 Speaker 1: So we can expect some serious volatility in the next 161 00:09:35,640 --> 00:09:38,240 Speaker 1: week's months, Roger, positive or negative. 162 00:09:38,440 --> 00:09:41,200 Speaker 2: I don't know, Sean, you know, but I think if 163 00:09:41,240 --> 00:09:44,560 Speaker 2: there's any legitimacy to the Chinese claim, and I'm not 164 00:09:44,640 --> 00:09:47,160 Speaker 2: saying there is, you know, I have a very skeptical 165 00:09:47,240 --> 00:09:52,120 Speaker 2: hat on whenever I listen to Chinese announcements, and so 166 00:09:52,520 --> 00:09:56,800 Speaker 2: you know, assuming that it is genuine, then there will 167 00:09:56,840 --> 00:10:00,440 Speaker 2: have to be a change to the optimism narrative that's 168 00:10:00,480 --> 00:10:04,559 Speaker 2: been built into the prices of the megacap stocks in 169 00:10:04,600 --> 00:10:06,840 Speaker 2: the US that rely on the AI story. 170 00:10:07,600 --> 00:10:09,280 Speaker 1: Roger, thank you for talking to Fear and Greed. 171 00:10:09,520 --> 00:10:10,400 Speaker 2: It's always a pleasure. 172 00:10:10,400 --> 00:10:13,640 Speaker 1: Sean as Roger Montgomery, founder and Chief investment Officer at 173 00:10:13,679 --> 00:10:17,160 Speaker 1: Montgomery Investment Management. This is the Fear and Greed Business Interview. 174 00:10:17,240 --> 00:10:19,680 Speaker 1: Remember this is general information only, and you should seek 175 00:10:19,679 --> 00:10:23,200 Speaker 1: professional advice before making investment decisions. Join us every morning 176 00:10:23,240 --> 00:10:25,360 Speaker 1: for the full episode of Fear and Greed. Daily business 177 00:10:25,400 --> 00:10:28,120 Speaker 1: news for people who make their own decisions. I'm Sean Elmer. 178 00:10:28,520 --> 00:10:29,120 Speaker 1: Enjoy your day.