1 00:00:02,480 --> 00:00:07,720 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. 2 00:00:10,000 --> 00:00:13,760 Speaker 2: This is the Bloomberg Daybreak Asia podcast. I'm Brian Curtis 3 00:00:13,760 --> 00:00:16,479 Speaker 2: along with Doug Krisner, join us each day for the 4 00:00:16,560 --> 00:00:19,920 Speaker 2: stories making news and moving markets in the Asia Pacific. 5 00:00:20,120 --> 00:00:22,560 Speaker 2: You can subscribe to the show anywhere you get your 6 00:00:22,600 --> 00:00:26,520 Speaker 2: podcasts and always on Bloomberg Radio, the Bloomberg Terminal, and 7 00:00:26,560 --> 00:00:27,920 Speaker 2: the Bloomberg Business app. 8 00:00:28,400 --> 00:00:32,040 Speaker 1: Jonathan Gardner with US Chief Asia and em strategist at 9 00:00:32,120 --> 00:00:36,720 Speaker 1: Morgan Stanley, joining us from the line city of Singapore. Jonathan, 10 00:00:36,760 --> 00:00:38,559 Speaker 1: thanks for taking the time to chat with us. I 11 00:00:38,640 --> 00:00:41,239 Speaker 1: was noting earlier that the MSCI China Index since that 12 00:00:41,800 --> 00:00:45,720 Speaker 1: January low is up about twenty seven percent. A lot 13 00:00:45,760 --> 00:00:49,080 Speaker 1: of this may be due to some rotation into cheaper valuations. 14 00:00:49,200 --> 00:00:51,959 Speaker 1: Would you chase this move or do you think it's 15 00:00:51,960 --> 00:00:53,120 Speaker 1: pretty much run its course? 16 00:00:53,360 --> 00:00:55,560 Speaker 3: Well, in a word, we wouldn't chase the move. We 17 00:00:55,600 --> 00:00:58,600 Speaker 3: wrote a note on that last week, myself, Laura Wang, 18 00:00:58,840 --> 00:01:01,840 Speaker 3: and the team. I think it's important to remember just 19 00:01:01,920 --> 00:01:05,200 Speaker 3: how volatile China equities are now relative to the rest 20 00:01:05,280 --> 00:01:08,679 Speaker 3: of global equities. They're about two and a half times 21 00:01:08,680 --> 00:01:11,280 Speaker 3: as volatile, and we've seen some of these short bursts 22 00:01:11,319 --> 00:01:14,400 Speaker 3: of performance within an overall secular bear market on a 23 00:01:14,440 --> 00:01:17,240 Speaker 3: number of occasions in the past. I think the reason 24 00:01:17,280 --> 00:01:20,920 Speaker 3: that the bear market ultimately resumes is the very weak 25 00:01:20,959 --> 00:01:24,520 Speaker 3: fundamentals that exist in China. And over the weekend we 26 00:01:24,600 --> 00:01:28,919 Speaker 3: had some really quite bad numbers on the inflation side 27 00:01:29,000 --> 00:01:31,560 Speaker 3: and the money supply and lending side, which really for 28 00:01:31,640 --> 00:01:34,640 Speaker 3: US confirm our thesis that it's still trapped in debt deflation. 29 00:01:36,360 --> 00:01:39,319 Speaker 2: And you have US Gina relations as well, that sort 30 00:01:39,319 --> 00:01:44,119 Speaker 2: of looms. Jennet Yellen gave kind of tacit confirmation that 31 00:01:44,319 --> 00:01:48,560 Speaker 2: higher US tariffs and Chinese products are coming, Jonathan. She said, 32 00:01:48,600 --> 00:01:52,320 Speaker 2: basically she hoped China wouldn't retaliate. Doubtful she'd be talking 33 00:01:52,360 --> 00:01:55,280 Speaker 2: about that if this wasn't coming. But even if they 34 00:01:55,360 --> 00:01:59,360 Speaker 2: do retaliate on the Chinese side, does this have real 35 00:01:59,480 --> 00:02:03,520 Speaker 2: teeth for investors or is it more symbolic for both 36 00:02:03,560 --> 00:02:05,600 Speaker 2: sides Domestic audiences. 37 00:02:05,560 --> 00:02:09,320 Speaker 3: Well, the China equity market is driven mainly by a 38 00:02:09,440 --> 00:02:13,280 Speaker 3: domestic consumer stocks the big major internet e commerce names, 39 00:02:13,480 --> 00:02:16,080 Speaker 3: so it doesn't have a lot of exporters directly in 40 00:02:16,120 --> 00:02:18,720 Speaker 3: the index, though there are some large firms in the 41 00:02:18,760 --> 00:02:22,760 Speaker 3: ashare market in things like electric vehicles and battery technology. 42 00:02:23,280 --> 00:02:26,320 Speaker 3: So what really matters for the domestic stock market is 43 00:02:26,440 --> 00:02:29,680 Speaker 3: just ultimately how weak the consumer continues to be. And 44 00:02:29,680 --> 00:02:32,760 Speaker 3: there's plenty of evidence that the consumer's paying down mortgage 45 00:02:32,800 --> 00:02:37,040 Speaker 3: debt for the first time ever. Big ticket spending is diminished, 46 00:02:37,080 --> 00:02:39,520 Speaker 3: and so people they're out and about and spending, but 47 00:02:39,639 --> 00:02:42,359 Speaker 3: much more on smaller ticket items. And we just think 48 00:02:42,400 --> 00:02:44,720 Speaker 3: this is in stark contrast to some other parts of 49 00:02:44,760 --> 00:02:47,440 Speaker 3: our coverage universe, for example India, where the trends are 50 00:02:47,440 --> 00:02:48,760 Speaker 3: almost completely different. 51 00:02:49,240 --> 00:02:51,679 Speaker 1: We were talking earlier on the program about the move 52 00:02:51,760 --> 00:02:54,080 Speaker 1: on the part of Beijing to begin selling the first 53 00:02:54,160 --> 00:02:58,320 Speaker 1: round of ultra long special sovereign bonds. I think the 54 00:02:58,360 --> 00:03:00,359 Speaker 1: sale will begin on Friday, and we're looking at the 55 00:03:00,360 --> 00:03:02,880 Speaker 1: first tranche of about one hundred and thirty eight billion. 56 00:03:03,400 --> 00:03:05,040 Speaker 1: Do you think there's going to be strong demand for 57 00:03:05,120 --> 00:03:05,720 Speaker 1: something like this. 58 00:03:06,720 --> 00:03:08,840 Speaker 3: Well, I'm not a bond market expert, but what I 59 00:03:08,880 --> 00:03:11,440 Speaker 3: would say is that that number is not very large 60 00:03:11,560 --> 00:03:14,240 Speaker 3: in relation to the size of the Chinese economy, which 61 00:03:14,280 --> 00:03:17,639 Speaker 3: is around about eighteen trillion dollars, and we don't think 62 00:03:17,639 --> 00:03:21,679 Speaker 3: that it represents an aggregate net fiscal stimulus. Rather, what's 63 00:03:21,680 --> 00:03:25,600 Speaker 3: happening is the central government is in a sense backstopping 64 00:03:25,680 --> 00:03:28,800 Speaker 3: some of the provincial local government debt to stop a 65 00:03:28,840 --> 00:03:32,240 Speaker 3: sort of cascading default cycle spreading out of the property developers. 66 00:03:32,680 --> 00:03:35,440 Speaker 3: And that's the context in which this bond insurance is happening. 67 00:03:35,480 --> 00:03:39,200 Speaker 3: It's not a net fiscal injection into the economy. 68 00:03:40,880 --> 00:03:43,680 Speaker 2: Jonathan, I wanted to ask you briefly about rate cuts. 69 00:03:44,120 --> 00:03:46,400 Speaker 2: We haven't had a lot of action on that front. 70 00:03:46,960 --> 00:03:50,880 Speaker 2: Bloomberg Economics is saying that without rate cuts, the PBOC 71 00:03:51,120 --> 00:03:52,840 Speaker 2: is just pushing on a string. 72 00:03:53,280 --> 00:03:55,520 Speaker 4: It needs to be sooner rather than later. 73 00:03:56,680 --> 00:03:59,240 Speaker 2: Is that another thing that doesn't really affect equity flows 74 00:03:59,240 --> 00:03:59,920 Speaker 2: that much or does it? 75 00:04:00,760 --> 00:04:00,960 Speaker 5: Well? 76 00:04:01,000 --> 00:04:03,960 Speaker 3: It is actually really key points. I'm glad you mentioned 77 00:04:03,960 --> 00:04:06,520 Speaker 3: it in this sense. It's quite reminiscent of what was 78 00:04:06,560 --> 00:04:09,040 Speaker 3: going on in Japan thirty years ago in the early 79 00:04:09,080 --> 00:04:12,720 Speaker 3: part of their debt deflation bust. That the authorities are 80 00:04:12,760 --> 00:04:15,360 Speaker 3: looking back with regret at the amount of leveraging up 81 00:04:15,400 --> 00:04:19,440 Speaker 3: in the prior decade or so, and they're not choosing 82 00:04:19,640 --> 00:04:23,520 Speaker 3: to flood the system with liquidity at this occasion. There 83 00:04:23,520 --> 00:04:26,560 Speaker 3: is an important difference, however, with Japan that may partly 84 00:04:26,600 --> 00:04:29,719 Speaker 3: explain this behavior, and that is that ultimately China is 85 00:04:29,800 --> 00:04:33,600 Speaker 3: not a developed market sovereign. It is ultimately an em 86 00:04:33,640 --> 00:04:37,000 Speaker 3: sovereign in terms of its credit rating. And were it 87 00:04:37,120 --> 00:04:40,159 Speaker 3: to slash interest rates, let's say, to zero, or try 88 00:04:40,200 --> 00:04:43,920 Speaker 3: to launch a QE program, it would unlock probably currency weakness, 89 00:04:43,960 --> 00:04:47,719 Speaker 3: currency declines. And that's why those kinds of policies haven't 90 00:04:47,720 --> 00:04:52,640 Speaker 3: been open to typical em in for example, that the past, 91 00:04:53,080 --> 00:04:56,480 Speaker 3: whereas for develop markets, including for Japan, Japan was ultimately 92 00:04:56,520 --> 00:04:59,880 Speaker 3: able to reflate because it found a path substantially neg 93 00:05:00,120 --> 00:05:03,159 Speaker 3: of real interest rates finally over the last decade, but 94 00:05:03,240 --> 00:05:04,760 Speaker 3: that may not be open to China. 95 00:05:05,520 --> 00:05:08,400 Speaker 1: So there's no way then that you see China repeating 96 00:05:08,440 --> 00:05:11,120 Speaker 1: that kind of the lost three decades that Japan was 97 00:05:11,160 --> 00:05:14,279 Speaker 1: miird in where you get in just so deeply entrenched 98 00:05:14,279 --> 00:05:18,360 Speaker 1: in a deflationary cycle and just stagnant activity. 99 00:05:18,600 --> 00:05:20,800 Speaker 3: Well, I think there is a recentably high chance that 100 00:05:20,920 --> 00:05:24,240 Speaker 3: China can remain in difficulties for the foreseeable future. We 101 00:05:24,320 --> 00:05:26,680 Speaker 3: are in year four of this if you date the 102 00:05:26,680 --> 00:05:29,719 Speaker 3: beginning of it to early twenty twenty one, when leverage 103 00:05:29,720 --> 00:05:32,520 Speaker 3: peaked in the overall economy and property prices peaked, and 104 00:05:32,600 --> 00:05:36,360 Speaker 3: there was also a mini stock market bubble, and there's 105 00:05:36,480 --> 00:05:39,920 Speaker 3: very little sign that the macro is actually turning around again. 106 00:05:39,960 --> 00:05:42,160 Speaker 3: I just want to emphasize these numbers. At the weekend 107 00:05:42,279 --> 00:05:46,720 Speaker 3: PPI minus two and a half CPI essentially zero aggregate 108 00:05:46,760 --> 00:05:50,000 Speaker 3: financing negative month or month. That's very unusual. 109 00:05:51,520 --> 00:05:52,800 Speaker 4: I wanted to finish up on. 110 00:05:53,279 --> 00:05:55,200 Speaker 2: I know you look back at the last fifteen or 111 00:05:55,200 --> 00:05:58,960 Speaker 2: twenty years or so of investing in these markets, and 112 00:05:59,000 --> 00:06:02,480 Speaker 2: you drew some conclude in about thirty or forty seconds 113 00:06:02,480 --> 00:06:06,960 Speaker 2: some what are among those chief among your observations. 114 00:06:07,200 --> 00:06:09,920 Speaker 3: I think it's really about the importance of quality in 115 00:06:09,920 --> 00:06:13,120 Speaker 3: investing in an asset class that is quite volatile. So 116 00:06:13,160 --> 00:06:15,760 Speaker 3: if you find business models that have superior are we 117 00:06:17,000 --> 00:06:20,479 Speaker 3: and strong balance sheets versus their industry peers, and you 118 00:06:20,560 --> 00:06:24,120 Speaker 3: control for valuation, that's really the answer to successful investing 119 00:06:24,160 --> 00:06:27,200 Speaker 3: in a difficult top down environment that you often find 120 00:06:27,200 --> 00:06:27,880 Speaker 3: in EM. 121 00:06:28,400 --> 00:06:30,599 Speaker 1: Jonathan will leave it there. It's a pleasure today have 122 00:06:30,720 --> 00:06:33,440 Speaker 1: you on the program and benefit from your insight. Jonathan 123 00:06:33,480 --> 00:06:37,600 Speaker 1: Garner is a chief Asia and EM strategist at Morgan Stanley. 124 00:06:44,400 --> 00:06:44,599 Speaker 4: Well. 125 00:06:44,640 --> 00:06:48,360 Speaker 2: Apple is getting set to sell its Vision pro in 126 00:06:48,520 --> 00:06:53,000 Speaker 2: markets outside the United States, trying to see whether the 127 00:06:53,160 --> 00:06:57,400 Speaker 2: roughly thirty five hundred dollars mixed reality headset has brought appeal. 128 00:06:57,480 --> 00:07:00,440 Speaker 2: Joining us in our studios is Mark German, Bloomberg, Chief 129 00:07:00,480 --> 00:07:05,000 Speaker 2: correspondent on Global Technology. So this is really the biggest, 130 00:07:05,560 --> 00:07:09,840 Speaker 2: biggest device, or the newest big device for Apple in 131 00:07:09,880 --> 00:07:12,920 Speaker 2: a period of time from your own channel, checks Mark, 132 00:07:13,160 --> 00:07:14,960 Speaker 2: what are you seeing? I mean, are people going to 133 00:07:14,960 --> 00:07:16,840 Speaker 2: be willing to pay thirty five hundred bucks for this? 134 00:07:17,200 --> 00:07:17,400 Speaker 5: Yeah? 135 00:07:17,440 --> 00:07:19,320 Speaker 6: Thank you for having me. It's awesome to be here 136 00:07:19,320 --> 00:07:22,400 Speaker 6: with you in Hong Kong. The Vision Pro. Like you said, 137 00:07:22,440 --> 00:07:25,440 Speaker 6: it's Apple's first major new product release in nearly a 138 00:07:25,480 --> 00:07:27,800 Speaker 6: decade since the Apple Watch came out in twenty fifteen, 139 00:07:28,120 --> 00:07:31,680 Speaker 6: and at thirty five hundred dollars with limited applications technology 140 00:07:31,680 --> 00:07:34,880 Speaker 6: that has very early appeal. It's a very much an 141 00:07:34,880 --> 00:07:38,040 Speaker 6: early adopter device. It did really well out of the gate. 142 00:07:38,160 --> 00:07:40,600 Speaker 6: I'm talking about the first two weeks or so when 143 00:07:40,680 --> 00:07:43,320 Speaker 6: people who wanted to get the device lined up for it, 144 00:07:43,360 --> 00:07:45,720 Speaker 6: the first pre orders arrived, the first people walking into 145 00:07:45,720 --> 00:07:47,720 Speaker 6: Apple Source to try it out and buy it. But 146 00:07:47,840 --> 00:07:49,960 Speaker 6: since then it has really tapered out. 147 00:07:50,160 --> 00:07:50,360 Speaker 5: Right. 148 00:07:50,400 --> 00:07:52,480 Speaker 6: You normally see this when a new iPhone comes out, 149 00:07:52,520 --> 00:07:54,960 Speaker 6: you get a ton of sales and it tapers a 150 00:07:55,000 --> 00:07:57,120 Speaker 6: little bit, but there is still quite a bit of 151 00:07:57,160 --> 00:08:00,200 Speaker 6: demand over the life cycle of the product. But I'd 152 00:08:00,240 --> 00:08:03,400 Speaker 6: say Vision Pro sales have completely fallen flat. Some stores 153 00:08:03,440 --> 00:08:06,360 Speaker 6: told me that they've had as many returns over the 154 00:08:06,440 --> 00:08:09,960 Speaker 6: last three months as they've had purchases over the first 155 00:08:10,000 --> 00:08:12,040 Speaker 6: two weeks. There are other stores who tell me they're 156 00:08:12,040 --> 00:08:14,760 Speaker 6: only selling, you know, one to two or three units 157 00:08:14,800 --> 00:08:16,880 Speaker 6: per week. Some stories telling me they don't even sell 158 00:08:17,240 --> 00:08:20,360 Speaker 6: one Vision Pro within one particular week. It's unclear for 159 00:08:20,560 --> 00:08:24,240 Speaker 6: ninety nine point nine nine percent of people why you 160 00:08:24,280 --> 00:08:24,760 Speaker 6: need one. 161 00:08:24,680 --> 00:08:25,200 Speaker 5: Of these things. 162 00:08:25,360 --> 00:08:28,440 Speaker 1: Yeah, the so are Apple devotees, right, I mean that 163 00:08:28,600 --> 00:08:31,400 Speaker 1: the early adopters. When you look at the distribution of innovation, 164 00:08:31,920 --> 00:08:35,440 Speaker 1: is this device manufactured by fox Conn? Are they the 165 00:08:35,480 --> 00:08:39,320 Speaker 1: main manufacturing powerhouse behind the Vision Pro? 166 00:08:40,440 --> 00:08:44,080 Speaker 6: No, the vision Pro is actually not produced by fox Conn. 167 00:08:44,120 --> 00:08:49,439 Speaker 6: It's produced by Quanta. Sorry, it's it's produced by lux 168 00:08:49,440 --> 00:08:54,719 Speaker 6: Share luck Share Precision based in Taiwan, I believe, and 169 00:08:55,000 --> 00:08:58,880 Speaker 6: lux Share Precision they have been working with Apple for 170 00:08:59,080 --> 00:09:01,400 Speaker 6: some number of years on this device. The plan for 171 00:09:01,440 --> 00:09:05,160 Speaker 6: Apple is to move some production over time to fox 172 00:09:05,240 --> 00:09:08,439 Speaker 6: Con to sort of differentiate with a cheaper model at 173 00:09:08,440 --> 00:09:11,120 Speaker 6: some point, and fox Conn likely would get in on that. 174 00:09:11,840 --> 00:09:14,280 Speaker 6: Maybe there'll be more suppliers like Quanta in the future 175 00:09:14,320 --> 00:09:17,880 Speaker 6: as well, but it's still very early days for this product. 176 00:09:17,960 --> 00:09:20,240 Speaker 6: And obviously, as we're talking about, the next big thing 177 00:09:20,280 --> 00:09:22,240 Speaker 6: for the Vision Pro is expansion mark. 178 00:09:22,320 --> 00:09:25,400 Speaker 2: You mentioned in your story that it takes as much 179 00:09:25,400 --> 00:09:28,080 Speaker 2: as four days to be trained up on this thing, 180 00:09:28,960 --> 00:09:31,880 Speaker 2: so it's obviously a niche product. Is this meant to 181 00:09:31,880 --> 00:09:35,760 Speaker 2: be like a lost Leader or do they actually expect 182 00:09:35,760 --> 00:09:37,160 Speaker 2: to sell a lot of these? 183 00:09:37,559 --> 00:09:39,200 Speaker 4: What's the essential purpose of this? 184 00:09:39,760 --> 00:09:43,520 Speaker 6: You know, it's funny. When they initially were planning to 185 00:09:43,559 --> 00:09:45,440 Speaker 6: release the Vision Pro, they were looking at a price 186 00:09:45,480 --> 00:09:49,120 Speaker 6: point around three thousand dollars and that basically put it 187 00:09:49,160 --> 00:09:53,240 Speaker 6: as no margin, and the idea was to get people 188 00:09:53,240 --> 00:09:56,560 Speaker 6: in the ecosystem, eventually, bring the bill of materials down 189 00:09:56,600 --> 00:09:59,520 Speaker 6: over time, get the cost down over time to build, 190 00:09:59,559 --> 00:10:01,319 Speaker 6: and then make a profit. But they priced it at 191 00:10:01,320 --> 00:10:03,120 Speaker 6: thirty five hundred dollars and then you have a two 192 00:10:03,200 --> 00:10:06,600 Speaker 6: hundred dollars up charge per additional storage capacity, and the 193 00:10:06,640 --> 00:10:10,440 Speaker 6: margins on flash for Apple for storage is probably north 194 00:10:10,480 --> 00:10:13,640 Speaker 6: of seventy percent, and so they're making a margin on this, 195 00:10:13,679 --> 00:10:16,000 Speaker 6: so they are making some money, but it's going to 196 00:10:16,040 --> 00:10:19,800 Speaker 6: take at the current rate of the amount of people 197 00:10:19,880 --> 00:10:21,960 Speaker 6: purchasing this product, is going to take them a decade 198 00:10:22,000 --> 00:10:24,720 Speaker 6: to make a return on their investment. So they're certainly 199 00:10:24,760 --> 00:10:26,120 Speaker 6: going to have to get the price down get more 200 00:10:26,160 --> 00:10:28,760 Speaker 6: people buying it to get back on their investment. 201 00:10:28,760 --> 00:10:28,960 Speaker 5: Here. 202 00:10:29,240 --> 00:10:31,520 Speaker 1: The last time that Brian and I were speaking with you, Mark, 203 00:10:31,559 --> 00:10:35,319 Speaker 1: you were giving us information. You're reporting on open Ai 204 00:10:35,480 --> 00:10:39,080 Speaker 1: striking a deal with Apple for the iPhone. Looks like 205 00:10:39,120 --> 00:10:41,280 Speaker 1: you were spot on there. What do we know? 206 00:10:42,440 --> 00:10:45,520 Speaker 6: Yeah, So about two months ago, I reported that Apple 207 00:10:45,520 --> 00:10:50,240 Speaker 6: had held discussions with open Ai about integration into the iPhone, 208 00:10:50,480 --> 00:10:54,680 Speaker 6: and then about three weeks ago it appeared that Google 209 00:10:55,000 --> 00:10:56,640 Speaker 6: was in the lead for a deal with Apple on 210 00:10:56,720 --> 00:10:59,360 Speaker 6: Ai with Gemini integration into the new iPhone this year, 211 00:11:00,000 --> 00:11:02,600 Speaker 6: and I reported that talks are back on with open Ai, 212 00:11:02,920 --> 00:11:06,800 Speaker 6: and then just last week they reached the deal. And 213 00:11:06,880 --> 00:11:09,920 Speaker 6: so open Ai will be part of the iOS eighteen 214 00:11:10,000 --> 00:11:13,040 Speaker 6: launch later this year, and we'll be supporting features like 215 00:11:13,040 --> 00:11:16,200 Speaker 6: a chatbot. Whether that's integration into Siri, into the Spotlight 216 00:11:16,240 --> 00:11:18,840 Speaker 6: search in the phone is to be seen, but open 217 00:11:18,880 --> 00:11:20,640 Speaker 6: Ai is going to be a part of the new 218 00:11:20,720 --> 00:11:24,360 Speaker 6: version of iOS, alongside large language models in GENAI tech 219 00:11:24,400 --> 00:11:25,160 Speaker 6: from Apple itself. 220 00:11:25,320 --> 00:11:27,840 Speaker 2: I suppose it doesn't rule out a deal with Gemini 221 00:11:28,280 --> 00:11:31,600 Speaker 2: of Google down the road. But in terms of AI 222 00:11:32,040 --> 00:11:34,920 Speaker 2: and its application, if we go back here to the 223 00:11:35,000 --> 00:11:40,040 Speaker 2: Vision Pro, is there any AI functionality in this? 224 00:11:40,400 --> 00:11:40,600 Speaker 5: Yeah? 225 00:11:40,640 --> 00:11:42,760 Speaker 6: I mean they say that the Vision Pro uses a 226 00:11:42,760 --> 00:11:46,000 Speaker 6: lot of artificial intelligence to do on device processing, to 227 00:11:46,440 --> 00:11:50,440 Speaker 6: mirror your eyes to create a virtual representation of you, 228 00:11:50,600 --> 00:11:52,480 Speaker 6: And sure that is AI, but that's not the AI 229 00:11:52,520 --> 00:11:54,880 Speaker 6: we're talking about the AI or anyone cares about right now. 230 00:11:55,400 --> 00:11:58,079 Speaker 6: I would anticipate they get some GENAI features onto the 231 00:11:58,120 --> 00:12:00,120 Speaker 6: Vision Pro, maybe a couple of features this year, but 232 00:12:00,120 --> 00:12:01,800 Speaker 6: I would say that's probably more of a next year 233 00:12:01,840 --> 00:12:04,840 Speaker 6: thing or the year after. The priority first and foremost 234 00:12:04,920 --> 00:12:07,920 Speaker 6: is to get jenai based into the iPhone, then the iPad, 235 00:12:07,960 --> 00:12:10,280 Speaker 6: than the Mac, then the Apple Watch, and then I 236 00:12:10,320 --> 00:12:13,360 Speaker 6: would say Vision Pro comes last, probably alongside the Apple 237 00:12:13,400 --> 00:12:17,200 Speaker 6: TV and the App Store. There. The big news I 238 00:12:17,200 --> 00:12:20,360 Speaker 6: think though, regarding the Vision Pro itself is expansion. So 239 00:12:20,559 --> 00:12:22,199 Speaker 6: it's been in the US now for about three and 240 00:12:22,240 --> 00:12:25,679 Speaker 6: a half months, and so they're now bringing in employees 241 00:12:25,720 --> 00:12:29,520 Speaker 6: from its retail stores in Asia and in Europe and 242 00:12:29,760 --> 00:12:33,240 Speaker 6: Australia to come to the US to learn how to 243 00:12:33,280 --> 00:12:35,400 Speaker 6: sell the Vision Pro, how to pitch the Vision Pro 244 00:12:35,480 --> 00:12:38,040 Speaker 6: to customers. And so you'll see the Vision Pro launch 245 00:12:38,120 --> 00:12:45,400 Speaker 6: after early June in places like Japan, Korea, China, Hong Kong, Singapore. 246 00:12:46,040 --> 00:12:50,079 Speaker 6: You'll see France, You'll see Germany, Australia, and I anticipate 247 00:12:50,160 --> 00:12:52,559 Speaker 6: you'll see Canada and the UK at some point this year. 248 00:12:52,720 --> 00:12:54,760 Speaker 1: As you know Marca, China is a big market when 249 00:12:54,800 --> 00:12:57,640 Speaker 1: it comes to gaming. Is there an intersection here between 250 00:12:57,720 --> 00:13:00,000 Speaker 1: the gaming environment and the Vision Pro? Very quick? 251 00:13:00,920 --> 00:13:04,599 Speaker 6: I think the Vision Pro most interesting market for the 252 00:13:04,679 --> 00:13:06,920 Speaker 6: Vision Pro is probably China because of the gaming interest there. 253 00:13:06,920 --> 00:13:09,720 Speaker 6: But Apple really needs to boost its gaming capabilities for 254 00:13:09,720 --> 00:13:11,360 Speaker 6: the device before it really will take off there. 255 00:13:11,440 --> 00:13:13,080 Speaker 4: The Apple Watch had a slow start. 256 00:13:13,679 --> 00:13:16,080 Speaker 2: Does the Vision Pro eventually get there or does this 257 00:13:16,120 --> 00:13:16,559 Speaker 2: one fail? 258 00:13:17,120 --> 00:13:19,320 Speaker 6: I think the first model the Vision Pro, will be 259 00:13:19,400 --> 00:13:21,439 Speaker 6: recalled as a failure, but I think if they get 260 00:13:21,440 --> 00:13:24,160 Speaker 6: the price down in half, it'll ultimately be a very 261 00:13:24,160 --> 00:13:25,319 Speaker 6: successful product for Apple. 262 00:13:25,640 --> 00:13:27,600 Speaker 2: All right, Mark, thank you very much for coming in. 263 00:13:27,720 --> 00:13:30,840 Speaker 2: We could talk a whole half hour. I suppose even longer. 264 00:13:31,240 --> 00:13:41,880 Speaker 2: Mark German, Bloomberg chief correspondent on global technology. Joining us 265 00:13:41,880 --> 00:13:44,400 Speaker 2: now for a closer look at markets is Victoria Bill's 266 00:13:44,520 --> 00:13:49,240 Speaker 2: chief investment strategist at Bantery and Capital Management. Victoria, thank 267 00:13:49,280 --> 00:13:52,400 Speaker 2: you for joining us. We're seeing a lack of direction 268 00:13:52,840 --> 00:13:57,880 Speaker 2: in US equities for sure. Elsewhere as well, what's rally 269 00:13:57,920 --> 00:14:01,679 Speaker 2: the most of late has been and Hong Kong equities, 270 00:14:02,160 --> 00:14:06,440 Speaker 2: US utilities and staples, So hard to find a thread 271 00:14:06,679 --> 00:14:09,480 Speaker 2: through that other than you know, those are the most 272 00:14:09,520 --> 00:14:13,400 Speaker 2: bombed out sectors late last year, and people have been 273 00:14:13,440 --> 00:14:16,560 Speaker 2: selling megacap tech and have been buying there. 274 00:14:17,040 --> 00:14:18,640 Speaker 4: When are we going to get some direction? 275 00:14:20,320 --> 00:14:20,600 Speaker 2: Yeah? 276 00:14:20,840 --> 00:14:23,680 Speaker 5: Direction, honestly is very hard to come by these days. 277 00:14:23,760 --> 00:14:25,440 Speaker 5: I think a lot of what we are seeing in 278 00:14:25,480 --> 00:14:28,800 Speaker 5: the market right now is just if we try to 279 00:14:29,040 --> 00:14:31,920 Speaker 5: create a single thread. There's a lot of noise when 280 00:14:31,920 --> 00:14:34,479 Speaker 5: it comes to what the markets are looking at. For example, 281 00:14:34,800 --> 00:14:40,120 Speaker 5: ETFs are a very common resp solution for the comment 282 00:14:40,240 --> 00:14:43,840 Speaker 5: for the average investor and for the average consumer investor, 283 00:14:44,400 --> 00:14:48,920 Speaker 5: and whether that's ETFs or whether that's through volatility trades particularly, 284 00:14:49,320 --> 00:14:51,760 Speaker 5: there's a lot of noise in terms of what we're 285 00:14:51,760 --> 00:14:54,640 Speaker 5: seeing just from the consumer side of the market now. 286 00:14:54,720 --> 00:14:57,520 Speaker 5: If we're looking at fundamentals, or if we're looking at 287 00:14:57,720 --> 00:15:00,720 Speaker 5: different types of industries in particular, I think a lot 288 00:15:00,760 --> 00:15:03,120 Speaker 5: of the common threads that we should be looking towards 289 00:15:03,200 --> 00:15:07,920 Speaker 5: are within the technology sector, specifically within AI, web three, 290 00:15:08,120 --> 00:15:10,800 Speaker 5: machine learning, and so those are a lot of things 291 00:15:10,840 --> 00:15:13,200 Speaker 5: that I'm looking for to or the things that I'm 292 00:15:13,240 --> 00:15:16,360 Speaker 5: looking to when it comes to market direction at this time. 293 00:15:16,520 --> 00:15:18,640 Speaker 1: So talk to us a little bit about the way 294 00:15:18,640 --> 00:15:22,240 Speaker 1: that you play artificial intelligence. Is it through a company 295 00:15:23,320 --> 00:15:26,720 Speaker 1: like a chip maker, let's say Nvidia obviously maybe to 296 00:15:26,760 --> 00:15:29,600 Speaker 1: a lesser extent some of the memory chip manufacturers, like 297 00:15:29,640 --> 00:15:32,360 Speaker 1: if Samsung, or do you go to a company like 298 00:15:32,520 --> 00:15:37,840 Speaker 1: Alphabet or Microsoft, or are there upstarts maybe publicly traded 299 00:15:37,880 --> 00:15:42,600 Speaker 1: companies small market cap focused on AI that could be 300 00:15:43,040 --> 00:15:46,040 Speaker 1: acquisition targets. I'm trying to understand the way that you 301 00:15:46,120 --> 00:15:48,440 Speaker 1: evaluate and put money to work in this space. 302 00:15:49,680 --> 00:15:51,480 Speaker 5: I think there's a a few different ways or a 303 00:15:51,480 --> 00:15:54,080 Speaker 5: few different scenarios of which you can talk about or 304 00:15:54,160 --> 00:15:56,960 Speaker 5: do all of the companies that you're talking about. So, 305 00:15:57,120 --> 00:15:59,680 Speaker 5: whether that's a data play when it comes to Meta 306 00:15:59,800 --> 00:16:03,560 Speaker 5: or Alphabet, data is a crucial component when it comes 307 00:16:03,600 --> 00:16:06,200 Speaker 5: to AI and machine learning, and especially when we think 308 00:16:06,200 --> 00:16:10,760 Speaker 5: about like the transference of that data and information from 309 00:16:10,880 --> 00:16:15,200 Speaker 5: larger computer systems to individuals, individuals stant hands or even 310 00:16:15,280 --> 00:16:20,320 Speaker 5: through like individual means, if you want to do a 311 00:16:20,360 --> 00:16:24,360 Speaker 5: computer or a microchip or a GPU play, I would 312 00:16:24,360 --> 00:16:27,680 Speaker 5: say that that's definitely a Nvidia or even a Samsung company. 313 00:16:28,440 --> 00:16:32,280 Speaker 5: The thing about Navidia is that they manufacture majority of 314 00:16:32,400 --> 00:16:35,400 Speaker 5: the GPU chips that are used in AI as well 315 00:16:35,440 --> 00:16:38,600 Speaker 5: as in sorry I'm thinking I'm blinking out in the 316 00:16:38,640 --> 00:16:42,880 Speaker 5: world right now, but sorry crypto plays as well. So 317 00:16:43,240 --> 00:16:46,080 Speaker 5: when we're thinking about companies that are within those spaces, 318 00:16:46,240 --> 00:16:48,960 Speaker 5: those are some of the primary industries that we're looking at. 319 00:16:49,400 --> 00:16:51,760 Speaker 5: And then the other thing that I like to think 320 00:16:51,800 --> 00:16:54,840 Speaker 5: about is machine learning. And so again we're looking at 321 00:16:54,960 --> 00:16:58,320 Speaker 5: Navidia or even Samsung a lot of the chips that 322 00:16:58,360 --> 00:17:00,440 Speaker 5: they're creating right now, and especially if we talk about 323 00:17:00,880 --> 00:17:06,080 Speaker 5: Samsung or even Nvidia, Samsung particularly the they're hopefully going 324 00:17:06,160 --> 00:17:09,439 Speaker 5: to like further their partnership with Nvidia and provide some 325 00:17:09,480 --> 00:17:11,840 Speaker 5: of the some of the chips that they're using for 326 00:17:11,920 --> 00:17:15,840 Speaker 5: their Web three and AI plays. So Samsung only has 327 00:17:15,840 --> 00:17:20,040 Speaker 5: an upboards or upworts tailwinds to gain from continuing to 328 00:17:20,080 --> 00:17:22,840 Speaker 5: partner with companies such as Nvidia right now, well. 329 00:17:22,760 --> 00:17:25,399 Speaker 2: There's so many derivative bets on this. So we mentioned 330 00:17:25,400 --> 00:17:28,479 Speaker 2: that companies like Nvidia and Broadcom are well off their highs, 331 00:17:28,480 --> 00:17:30,879 Speaker 2: so people have been selling that and they've been buying 332 00:17:30,920 --> 00:17:34,080 Speaker 2: into some of these derivative plays, even utilities. You know 333 00:17:34,119 --> 00:17:36,960 Speaker 2: that raises a few eyebrows, but you know, these data 334 00:17:36,960 --> 00:17:40,480 Speaker 2: centers need a ton of electrification, so you know people 335 00:17:40,480 --> 00:17:44,080 Speaker 2: have even spread there. They're buying HVAC companies because you know, 336 00:17:44,119 --> 00:17:47,159 Speaker 2: you need cooling systems for all the all the power 337 00:17:47,240 --> 00:17:48,600 Speaker 2: that AI needs. 338 00:17:48,960 --> 00:17:50,800 Speaker 4: So there's been a lot of bets. I'm wondering. 339 00:17:51,040 --> 00:17:53,040 Speaker 2: You know, some of those companies have gone up even 340 00:17:53,080 --> 00:17:56,280 Speaker 2: more in the last month or two than the NVIDIAs 341 00:17:56,280 --> 00:17:59,720 Speaker 2: of the world. So I'm thinking that maybe now money 342 00:17:59,720 --> 00:18:03,159 Speaker 2: flows back into the peer plays because have already spread out. 343 00:18:03,960 --> 00:18:07,639 Speaker 5: I mean, that's definitely it. I remember back in last 344 00:18:07,720 --> 00:18:10,880 Speaker 5: year in November, I was very much pro super Microcomputer, 345 00:18:11,480 --> 00:18:16,000 Speaker 5: and that company was originally in the small cap like 346 00:18:16,200 --> 00:18:20,399 Speaker 5: small cap index, but now it's trading at almost triple 347 00:18:20,480 --> 00:18:22,199 Speaker 5: or double what I would recommend in terms of a 348 00:18:22,240 --> 00:18:25,800 Speaker 5: price for purchase. So when it comes to small cap 349 00:18:25,840 --> 00:18:28,920 Speaker 5: plays or even companies that are like I would say, 350 00:18:28,960 --> 00:18:33,240 Speaker 5: more fairly priced in this arena, there's a very slim 351 00:18:33,280 --> 00:18:35,480 Speaker 5: picking in terms of companies that you could look at 352 00:18:35,520 --> 00:18:38,439 Speaker 5: to get into the AI world. And going off of 353 00:18:38,480 --> 00:18:41,240 Speaker 5: what you were saying earlier, a lot of this requires 354 00:18:41,400 --> 00:18:44,640 Speaker 5: like a lot of manufacturing power in order to create 355 00:18:44,680 --> 00:18:48,760 Speaker 5: these microchips in order to create these processors semiconductor processors 356 00:18:48,800 --> 00:18:52,159 Speaker 5: as well, which helped to process that data. So I 357 00:18:52,359 --> 00:18:55,440 Speaker 5: honestly that's where the larger plays come in, because these 358 00:18:55,480 --> 00:18:57,879 Speaker 5: are the companies that are well equipped in order to 359 00:18:57,960 --> 00:19:00,920 Speaker 5: create those processes and create that data, create that information. 360 00:19:01,440 --> 00:19:04,800 Speaker 1: Brian raised an interesting point. They're talking about the demand 361 00:19:04,880 --> 00:19:08,320 Speaker 1: for electricity to power a lot of this processing, whether 362 00:19:08,359 --> 00:19:12,120 Speaker 1: it's you know, a server farm or you know individual 363 00:19:12,160 --> 00:19:16,600 Speaker 1: companies that are set up to kind of run AI applications. 364 00:19:16,720 --> 00:19:18,920 Speaker 1: Is that a play that interests you in any way? 365 00:19:19,320 --> 00:19:21,760 Speaker 1: I know it may sound boring to put money to 366 00:19:21,760 --> 00:19:24,720 Speaker 1: work into utility, but maybe it's not a utility. Maybe 367 00:19:24,760 --> 00:19:28,239 Speaker 1: it's something connected to a form of energy that attracts you. 368 00:19:29,320 --> 00:19:32,399 Speaker 5: Oh. Absolutely, The thing is like energy is going to 369 00:19:32,440 --> 00:19:35,000 Speaker 5: be the energy is the number one resource when we 370 00:19:35,040 --> 00:19:38,000 Speaker 5: think about the play that's going to be in the 371 00:19:38,119 --> 00:19:42,000 Speaker 5: AI and machine learning space, Like these are very high 372 00:19:42,320 --> 00:19:45,800 Speaker 5: energy intensive processes in order to not only just create 373 00:19:45,800 --> 00:19:49,040 Speaker 5: these microchips, but also to run them and operate them. 374 00:19:49,359 --> 00:19:53,080 Speaker 5: So whether you're thinking about crypto mining, that is a 375 00:19:53,240 --> 00:19:57,320 Speaker 5: very energy intensive sector. But the chips, for example, that 376 00:19:57,440 --> 00:20:00,959 Speaker 5: Nvidia creates for like GPU process as saying, those have 377 00:20:01,920 --> 00:20:05,560 Speaker 5: additional cooling factors that allow for them to not process 378 00:20:05,600 --> 00:20:09,200 Speaker 5: as much energy. But with the crypto having that happened 379 00:20:09,280 --> 00:20:12,680 Speaker 5: last month, essentially what happens is that the supply of crypto, 380 00:20:12,840 --> 00:20:15,520 Speaker 5: for example, has now gone down, so that means but 381 00:20:15,680 --> 00:20:17,920 Speaker 5: still continuing with the demand. 382 00:20:17,560 --> 00:20:18,040 Speaker 2: That we have. 383 00:20:18,560 --> 00:20:22,520 Speaker 5: So therefore the logical explanation is that either these crypto 384 00:20:22,560 --> 00:20:26,399 Speaker 5: mining companies need to add more additional computers and processors 385 00:20:26,400 --> 00:20:29,320 Speaker 5: in order to meet that demand, or it's just kind 386 00:20:29,320 --> 00:20:31,120 Speaker 5: of you're just going to resign yourself to the fact 387 00:20:31,160 --> 00:20:32,760 Speaker 5: that maybe you're not going to be able to mine 388 00:20:32,760 --> 00:20:34,439 Speaker 5: as much crypto as you might have been able to 389 00:20:34,480 --> 00:20:35,000 Speaker 5: in the past. 390 00:20:35,600 --> 00:20:39,280 Speaker 2: But let's get to the broader market briefly. People are 391 00:20:39,320 --> 00:20:41,359 Speaker 2: worried about, you know what's out there. The market near 392 00:20:41,400 --> 00:20:43,439 Speaker 2: all time highs would seem to be telling us that 393 00:20:43,840 --> 00:20:46,960 Speaker 2: six to nine months out things will still be okay. 394 00:20:47,760 --> 00:20:51,639 Speaker 2: It's the nervous commentators that are suggesting that stagflation is 395 00:20:51,680 --> 00:20:54,000 Speaker 2: a risk this year. The market seems to be saying, sure, 396 00:20:54,200 --> 00:20:58,119 Speaker 2: anything's possible. Stagflation is not happening anytime soon. Your thoughts 397 00:20:58,119 --> 00:20:59,720 Speaker 2: on that, I. 398 00:21:00,040 --> 00:21:03,040 Speaker 5: Thinks stiflation is happening anytime soon. I think that again, 399 00:21:03,160 --> 00:21:06,520 Speaker 5: labor markets remain pretty strong, and while inflation rates are 400 00:21:06,560 --> 00:21:09,800 Speaker 5: pretty high, but there's no reason to believe that CPI 401 00:21:09,800 --> 00:21:13,119 Speaker 5: and PPI particularly won't come near or close to the 402 00:21:13,160 --> 00:21:16,400 Speaker 5: consensus that we currently have right now. When we think 403 00:21:16,400 --> 00:21:19,119 Speaker 5: about what the Fed is doing, we're basically in a 404 00:21:19,160 --> 00:21:21,760 Speaker 5: process right now, or in a race to try and 405 00:21:21,920 --> 00:21:26,159 Speaker 5: temper inflation or temper consumer sentiments in order to basically 406 00:21:26,200 --> 00:21:30,240 Speaker 5: combat that inflation. What we've seen, however, is that consumer 407 00:21:30,280 --> 00:21:33,879 Speaker 5: savings has gone down overall for the past quarter. I 408 00:21:33,920 --> 00:21:37,960 Speaker 5: believe consumer spending has also gone up. And then the 409 00:21:38,000 --> 00:21:41,040 Speaker 5: other part of that is that wages have also have 410 00:21:41,200 --> 00:21:46,640 Speaker 5: not matched savings, but they're basically they're not outpacing consumer spending. 411 00:21:46,920 --> 00:21:50,119 Speaker 5: So what we're seeing, so the overarching message of that 412 00:21:50,440 --> 00:21:52,200 Speaker 5: is that what the FED is doing is working. 413 00:21:52,520 --> 00:21:55,160 Speaker 2: Okay, Victoria, thank you so much for being with us here. 414 00:21:55,560 --> 00:21:59,040 Speaker 2: Enjoyed it, Victoria Bills, chief investment strategist, said vander and 415 00:21:59,080 --> 00:22:00,000 Speaker 2: Capital Management. 416 00:22:02,280 --> 00:22:05,240 Speaker 1: This has been the Bloomberg Daybreak Asia podcast, bringing you 417 00:22:05,280 --> 00:22:08,400 Speaker 1: the stories making news and moving markets in the Asia Pacific. 418 00:22:08,920 --> 00:22:12,040 Speaker 1: Visit the Bloomberg Podcast channel on YouTube to get more 419 00:22:12,080 --> 00:22:15,679 Speaker 1: episodes of this and other shows from Bloomberg. 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