1 00:00:00,160 --> 00:00:02,520 Speaker 1: US tech stocks have been taking a hammering after the 2 00:00:02,640 --> 00:00:04,680 Speaker 1: debut of AI's new kid on the block, and it's 3 00:00:04,720 --> 00:00:08,520 Speaker 1: called deep Seek. Deep Seek as a Chinese tech firm 4 00:00:08,520 --> 00:00:11,800 Speaker 1: that's created its own budget AI model look at Ai 5 00:00:12,200 --> 00:00:14,840 Speaker 1: done by Temu Maybe, and it's said to be more 6 00:00:14,880 --> 00:00:17,680 Speaker 1: efficient and significantly cheaper compared to others on the market. 7 00:00:17,920 --> 00:00:20,200 Speaker 1: And it had impact on the New Zealand Superfund. It 8 00:00:20,280 --> 00:00:24,760 Speaker 1: caused Nvidia's stocks to dive seventeen percent yesterday. So I'm 9 00:00:24,840 --> 00:00:28,760 Speaker 1: joined by Inframetric CEO and principal economist Brad Olson. Hello, Brad, 10 00:00:29,480 --> 00:00:32,320 Speaker 1: good morning. Wow. Who saw this coming? This is a 11 00:00:32,320 --> 00:00:32,840 Speaker 1: bold move. 12 00:00:34,120 --> 00:00:36,360 Speaker 2: Oh, it's huge. And I'll tell you what yesterday was 13 00:00:36,360 --> 00:00:38,720 Speaker 2: a very easy way to lose money on the markets 14 00:00:38,720 --> 00:00:41,040 Speaker 2: without doing anything at all. So I mean it was 15 00:00:41,400 --> 00:00:43,400 Speaker 2: it was a bit of a market blood bath. I mean, 16 00:00:43,440 --> 00:00:46,479 Speaker 2: if you look at what had been happening though really 17 00:00:46,520 --> 00:00:49,159 Speaker 2: over the last year, last two years, is everyone has 18 00:00:49,200 --> 00:00:53,840 Speaker 2: been plowing some serious, serious money into AI and tech stocks. 19 00:00:53,880 --> 00:00:56,280 Speaker 2: This was the next big thing. It was the area 20 00:00:56,320 --> 00:00:58,320 Speaker 2: that the more that you put into which the more 21 00:00:58,320 --> 00:00:59,920 Speaker 2: you return, you were going to get out the other 22 00:01:00,320 --> 00:01:03,440 Speaker 2: because it was going to change everything. And then effectively 23 00:01:03,480 --> 00:01:07,200 Speaker 2: overnight you had deep Seek that came out and it 24 00:01:07,360 --> 00:01:10,679 Speaker 2: was purported that it costs six million dollars to train 25 00:01:10,880 --> 00:01:14,039 Speaker 2: compared to something like open AI's Chat GPT, which was 26 00:01:14,120 --> 00:01:17,320 Speaker 2: like one hundred million, and it was producing just as good, 27 00:01:17,319 --> 00:01:20,039 Speaker 2: if not better results, and everyone went, well, geez, why 28 00:01:20,080 --> 00:01:22,280 Speaker 2: am I investing these big sums? I better pull it 29 00:01:22,319 --> 00:01:25,080 Speaker 2: out now. So within the space of a day you'd 30 00:01:25,120 --> 00:01:28,480 Speaker 2: seen the likes of in Video with its big chip 31 00:01:28,600 --> 00:01:32,400 Speaker 2: and AI sort of focus lost six hundred billion US. 32 00:01:32,440 --> 00:01:36,960 Speaker 2: That's over a trillion New Zealand dollars, biggest single drop 33 00:01:37,040 --> 00:01:39,959 Speaker 2: that we've seen ever in terms of dollar terms. But 34 00:01:40,040 --> 00:01:43,560 Speaker 2: it's also interesting how quickly this has changed. Around Yesterday, 35 00:01:43,600 --> 00:01:46,720 Speaker 2: twenty four hours ago, the numbers were looking absolutely awful. 36 00:01:46,760 --> 00:01:49,080 Speaker 2: The likes that S and P five hundred was down 37 00:01:49,440 --> 00:01:53,160 Speaker 2: two percent. By today right here, right now, that market's 38 00:01:53,200 --> 00:01:57,000 Speaker 2: already recovered in general terms about half of that drop. 39 00:01:57,080 --> 00:02:00,520 Speaker 2: So still down, but really some big market reaction. Everyone 40 00:02:00,600 --> 00:02:02,880 Speaker 2: now trying to get a handle on how big is 41 00:02:02,920 --> 00:02:05,200 Speaker 2: AI and how much money do they want to put 42 00:02:05,240 --> 00:02:05,600 Speaker 2: into it. 43 00:02:05,760 --> 00:02:07,520 Speaker 1: Was it a surprise that China came up with such 44 00:02:07,520 --> 00:02:08,560 Speaker 1: a good little model. 45 00:02:09,560 --> 00:02:11,880 Speaker 2: Well, it seemed to be for a lot of the markets, 46 00:02:12,000 --> 00:02:15,000 Speaker 2: especially because there has been a much greater level of 47 00:02:15,040 --> 00:02:18,280 Speaker 2: control on some of the chips and some of the technology, 48 00:02:18,400 --> 00:02:21,440 Speaker 2: the semiconductors and the likes that have been going into 49 00:02:21,480 --> 00:02:24,720 Speaker 2: supporting greater and greater AI investment. And so the view 50 00:02:24,840 --> 00:02:28,000 Speaker 2: was that China shouldn't be able to do this, shouldn't 51 00:02:28,000 --> 00:02:29,919 Speaker 2: be able to come up with something nearly as good 52 00:02:29,960 --> 00:02:33,160 Speaker 2: because there are restrictions on this technology, which is again 53 00:02:33,240 --> 00:02:36,400 Speaker 2: why everyone went well, if China has managed to achieve 54 00:02:36,760 --> 00:02:40,519 Speaker 2: a superior product for cheaper with all of these restrictions 55 00:02:40,520 --> 00:02:43,799 Speaker 2: in place, then maybe it's not worth these companies that 56 00:02:43,840 --> 00:02:47,840 Speaker 2: are making these chips and semiconductors. Maybe they're not worth 57 00:02:47,840 --> 00:02:50,720 Speaker 2: the money that everyone's pumped into them. And I think 58 00:02:50,760 --> 00:02:52,600 Speaker 2: this is going to be probably one of the challenges 59 00:02:52,639 --> 00:02:55,280 Speaker 2: for the next couple of years, is that everyone's trying 60 00:02:55,320 --> 00:02:57,760 Speaker 2: to figure out just how big or how important a 61 00:02:57,800 --> 00:03:01,280 Speaker 2: new category is. It to be clear, Andrew, we saw 62 00:03:01,320 --> 00:03:04,800 Speaker 2: this last year in January where during the World Economic 63 00:03:04,840 --> 00:03:07,440 Speaker 2: Forum and Davos, a lot of business leaders were saying, look, 64 00:03:07,480 --> 00:03:10,280 Speaker 2: AI's big. AI is important, but I don't quite know 65 00:03:10,320 --> 00:03:12,600 Speaker 2: how to use it in my company. All of a Sudden. 66 00:03:12,600 --> 00:03:14,320 Speaker 2: We had a big sell off them as well, which 67 00:03:14,360 --> 00:03:16,120 Speaker 2: recovered in a couple of months. So it's just a 68 00:03:16,160 --> 00:03:19,200 Speaker 2: bit of recalibration going on where people are going. Look, 69 00:03:19,240 --> 00:03:24,480 Speaker 2: we've probably overestimated just how absolutely amazing we think AI is. 70 00:03:24,520 --> 00:03:27,399 Speaker 2: We've just got to sort of now recalibrate just how 71 00:03:27,480 --> 00:03:29,880 Speaker 2: important and how much money we're willing to put in. 72 00:03:30,040 --> 00:03:32,320 Speaker 1: Good Toods, Brad Olsen from Informatrics, I thank you so 73 00:03:32,400 --> 00:03:33,080 Speaker 1: much for your time. 74 00:03:34,120 --> 00:03:37,080 Speaker 2: For more from Early Edition with Ryan Bridge, listen live 75 00:03:37,240 --> 00:03:40,240 Speaker 2: to news Talks it'd be from five am weekdays, or 76 00:03:40,280 --> 00:03:42,200 Speaker 2: follow the podcast on iHeartRadio.