1 00:00:02,480 --> 00:00:08,720 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. The headlines third quarter 2 00:00:09,200 --> 00:00:12,520 Speaker 1: revenue x tax seventy point fifty five billion. That's a beat. 3 00:00:12,600 --> 00:00:15,200 Speaker 1: Seventy two point eighty eight was the estimate. Third quarter 4 00:00:15,320 --> 00:00:19,159 Speaker 1: Google Cloud revenue also beat over eleven billion dollars. The 5 00:00:19,160 --> 00:00:20,960 Speaker 1: street estimate was about ten point eight ten. 6 00:00:21,120 --> 00:00:24,400 Speaker 2: All right, let's I think we should bring in Man Deep. 7 00:00:24,440 --> 00:00:26,119 Speaker 1: So I think we should definitely bring He's. 8 00:00:26,040 --> 00:00:29,560 Speaker 2: Been watching these numbers very closely. He joins us here 9 00:00:29,720 --> 00:00:34,280 Speaker 2: in the Bloomberg Interactive Brokers studio. A beat pretty much 10 00:00:34,440 --> 00:00:38,360 Speaker 2: across the board, Man Deep, you cover this company and 11 00:00:38,360 --> 00:00:39,559 Speaker 2: many others. We're going to get to some of the 12 00:00:39,560 --> 00:00:43,760 Speaker 2: others in just a second. For Bloomberg Intelligence. What's really 13 00:00:43,760 --> 00:00:44,440 Speaker 2: sticks out to you? 14 00:00:44,680 --> 00:00:47,640 Speaker 3: I mean, the Google Cloud beat is quite impressive because 15 00:00:47,680 --> 00:00:51,200 Speaker 3: the thirty five percent growth rate is a nice acceleration. 16 00:00:51,360 --> 00:00:54,120 Speaker 3: I mean, we are talking about thirty percent being the bogie. 17 00:00:54,840 --> 00:00:57,000 Speaker 3: They really hit it out of the park when it 18 00:00:57,040 --> 00:00:58,240 Speaker 3: comes to the Google Cloud. 19 00:00:58,440 --> 00:01:00,280 Speaker 2: So what does that tell you about their client. 20 00:01:00,960 --> 00:01:05,559 Speaker 3: That the clients are deploying their AI workloads on Google Cloud. Remember, 21 00:01:05,600 --> 00:01:08,240 Speaker 3: Google Cloud is the third when it comes to the 22 00:01:08,319 --> 00:01:09,880 Speaker 3: cloud ranking. 23 00:01:10,000 --> 00:01:11,840 Speaker 2: You've got Aws, Azure. 24 00:01:11,800 --> 00:01:15,240 Speaker 3: Azure and Google Cloud has an und rate of forty 25 00:01:15,240 --> 00:01:18,640 Speaker 3: four billion. Now with this print, Azure is about eighty 26 00:01:18,680 --> 00:01:21,680 Speaker 3: billion and AWS is one hundred and five billion. So 27 00:01:22,280 --> 00:01:25,200 Speaker 3: I think what you will see is Google Cloud growing 28 00:01:25,319 --> 00:01:28,319 Speaker 3: much faster than the other two. Most likely Microsoft will 29 00:01:28,319 --> 00:01:31,480 Speaker 3: be around thirty percent. AWS is more twenty percent. So 30 00:01:31,520 --> 00:01:34,280 Speaker 3: clearly that thirty five percent growth rate is very impressive, 31 00:01:34,800 --> 00:01:38,440 Speaker 3: and the cloud profitability actually was much better than expected, 32 00:01:38,680 --> 00:01:40,880 Speaker 3: which is why you see the operating margin bead here. 33 00:01:41,000 --> 00:01:45,399 Speaker 1: How low was the bar going into this report for Alphabet. 34 00:01:44,800 --> 00:01:46,800 Speaker 3: It was I think low in the sense that the 35 00:01:46,840 --> 00:01:50,240 Speaker 3: overall top line road of thirteen percent was quite low, 36 00:01:50,600 --> 00:01:53,640 Speaker 3: and they beat on. You know, the certain numbers were 37 00:01:53,640 --> 00:01:56,440 Speaker 3: in line. The YouTube ad numbers were in line. The 38 00:01:56,480 --> 00:02:00,920 Speaker 3: YouTube subscriptions continues to be the standout. They keep delivering 39 00:02:01,000 --> 00:02:04,760 Speaker 3: quarter after quarter, and now YouTube plus cloud is one 40 00:02:04,800 --> 00:02:07,480 Speaker 3: hundred billion dollar rundread business. They guide it to that 41 00:02:07,800 --> 00:02:10,040 Speaker 3: and they are showing it in the in the sprint. 42 00:02:10,000 --> 00:02:12,400 Speaker 2: And YouTube alone is a fifty billion dollar business over 43 00:02:12,400 --> 00:02:14,919 Speaker 2: the last four quarters, according to the release from the company. 44 00:02:15,200 --> 00:02:18,160 Speaker 3: I would say if you add the subscriptions, yeah, to 45 00:02:18,280 --> 00:02:22,520 Speaker 3: the ads, it's closer to sixty simply because they bundle 46 00:02:22,600 --> 00:02:25,320 Speaker 3: YouTube subscriptions in the other segment and they've got some 47 00:02:25,440 --> 00:02:28,560 Speaker 3: other revenue in there as well. So that's why that 48 00:02:28,680 --> 00:02:32,880 Speaker 3: subscription number continues to be very impressive, the YouTube premium 49 00:02:32,960 --> 00:02:35,959 Speaker 3: and the YouTube TV. Yeah, and most likely it is 50 00:02:36,000 --> 00:02:36,680 Speaker 3: margin increased. 51 00:02:36,760 --> 00:02:39,560 Speaker 2: A quick reminder, Google bought YouTube back in two thousand 52 00:02:39,560 --> 00:02:42,080 Speaker 2: and six for one point sixty five billion dollars. 53 00:02:41,960 --> 00:02:44,880 Speaker 1: Which is pretty amazing. Listen, we watch a lot of YouTube, 54 00:02:45,800 --> 00:02:46,760 Speaker 1: two different programs. 55 00:02:46,800 --> 00:02:47,839 Speaker 2: We're on YouTube right now. 56 00:02:47,960 --> 00:02:48,720 Speaker 1: We are on YouTube. 57 00:02:48,800 --> 00:02:50,960 Speaker 2: You want everybody she's not watching you tube. 58 00:02:50,919 --> 00:02:53,320 Speaker 1: I'm not watching it. You know, it's interesting. We did 59 00:02:53,320 --> 00:02:56,440 Speaker 1: some reporting kicked off our broadcast couple of hours ago 60 00:02:56,560 --> 00:03:02,880 Speaker 1: about the overhang, the anti trust action scrutiny over where 61 00:03:02,880 --> 00:03:05,480 Speaker 1: their alphabet's dominant market share and Internet search is at 62 00:03:05,520 --> 00:03:09,239 Speaker 1: a risk as other players in AI come in. How 63 00:03:09,280 --> 00:03:13,560 Speaker 1: do you kind of factor those overhanging elements in. 64 00:03:13,760 --> 00:03:16,000 Speaker 3: Yeah, Look, there is no doubt if you're a regulator 65 00:03:16,080 --> 00:03:18,799 Speaker 3: right now and looking at the search market, there's more 66 00:03:18,840 --> 00:03:23,359 Speaker 3: competition this chat GPT, there are other large anguage players 67 00:03:23,400 --> 00:03:26,120 Speaker 3: and Tropic even Meta is talking about getting into search. 68 00:03:26,360 --> 00:03:29,080 Speaker 3: So there is definitely perplexity being another one there is 69 00:03:29,120 --> 00:03:32,400 Speaker 3: more competition for sure. Now, the thing that's impressed me 70 00:03:32,480 --> 00:03:36,080 Speaker 3: this quarter was they continue to execute on search. So 71 00:03:36,200 --> 00:03:39,360 Speaker 3: even though the search volumes are going down, they still 72 00:03:39,400 --> 00:03:41,600 Speaker 3: had an inline forty nine point one. 73 00:03:41,840 --> 00:03:43,160 Speaker 1: Is very amazing. 74 00:03:43,200 --> 00:03:44,800 Speaker 2: Why are search volumes going down? 75 00:03:45,360 --> 00:03:48,880 Speaker 3: Because if chat GPT is taking some of your traffic 76 00:03:49,000 --> 00:03:52,520 Speaker 3: for informational queries, that Google search volume, I would say, 77 00:03:52,640 --> 00:03:55,720 Speaker 3: is going down. But the ROI on their ad spend 78 00:03:55,800 --> 00:03:58,000 Speaker 3: is so high that they can make it up on 79 00:03:58,080 --> 00:04:00,800 Speaker 3: the ad pricing site. So even involves are going down, 80 00:04:01,280 --> 00:04:03,520 Speaker 3: ad pricing continues to be stronger. 81 00:04:03,680 --> 00:04:05,280 Speaker 1: Why because they're the dominant player. 82 00:04:05,360 --> 00:04:08,320 Speaker 3: They are the dominant player, and they have the best 83 00:04:08,440 --> 00:04:10,880 Speaker 3: kind of mode when it comes to the ads stack 84 00:04:11,240 --> 00:04:15,680 Speaker 3: around keyword searches. There's no better a platform for you know, 85 00:04:15,840 --> 00:04:20,080 Speaker 3: navigational searches or transactional searches. If you're an e commerce player, 86 00:04:20,080 --> 00:04:22,760 Speaker 3: you have to advertise YouTube. There's no way out of it. 87 00:04:23,560 --> 00:04:26,159 Speaker 1: So what's the question that you would want to know 88 00:04:26,200 --> 00:04:27,640 Speaker 1: from them on the earnings call? I mean, the stacks 89 00:04:27,680 --> 00:04:29,880 Speaker 1: know up four point two percent in the aftermarket, so 90 00:04:29,960 --> 00:04:31,159 Speaker 1: the momentum just building. 91 00:04:31,279 --> 00:04:33,560 Speaker 3: They give you so little in terms of guidance that 92 00:04:33,640 --> 00:04:36,080 Speaker 3: I almost want to, you know, plead the management to 93 00:04:36,640 --> 00:04:39,920 Speaker 3: give us more details around their CAPEX plans like every 94 00:04:39,960 --> 00:04:41,520 Speaker 3: other company gives us so much more. 95 00:04:41,640 --> 00:04:43,880 Speaker 1: Well, this is the thing that going into this week 96 00:04:44,040 --> 00:04:45,800 Speaker 1: right with all of these guys reporting, and what it 97 00:04:45,800 --> 00:04:48,080 Speaker 1: would tell us about the AI spend. What did you 98 00:04:48,120 --> 00:04:50,599 Speaker 1: what so far have you heard about or are you 99 00:04:50,640 --> 00:04:51,760 Speaker 1: feeling like you're going I mean. 100 00:04:51,600 --> 00:04:55,159 Speaker 3: If the cloud number was a blowout, which it looks 101 00:04:55,240 --> 00:04:58,240 Speaker 3: like in this print, then clearly you know the spend 102 00:04:58,279 --> 00:05:01,960 Speaker 3: on AI is translated into cloud revenue, and so to 103 00:05:02,040 --> 00:05:06,440 Speaker 3: my mind, I think that AI Kapex investment is showing 104 00:05:06,560 --> 00:05:08,680 Speaker 3: up in the cloud revenue. And that's why I want 105 00:05:08,720 --> 00:05:12,120 Speaker 3: to know the Capex guide. Are they overspending because at 106 00:05:12,120 --> 00:05:14,720 Speaker 3: this pace, you know, with the fifty billion dollar capex, 107 00:05:15,040 --> 00:05:18,080 Speaker 3: they're way lower than Microsoft at around eighty billion. So 108 00:05:18,160 --> 00:05:20,000 Speaker 3: that's why that Capex guide is very important. 109 00:05:20,160 --> 00:05:21,800 Speaker 2: Is it apples to apples when it comes to the 110 00:05:21,839 --> 00:05:25,359 Speaker 2: way these companies are investing. Can we can we really say, okay, 111 00:05:25,360 --> 00:05:30,200 Speaker 2: the Microsoft AI spend or Microsoft capex we can compare 112 00:05:30,200 --> 00:05:32,839 Speaker 2: it directly to Alphabet. 113 00:05:32,560 --> 00:05:34,800 Speaker 3: You can, and Alphabet has got a different set of 114 00:05:34,880 --> 00:05:39,240 Speaker 3: businesses along with AI and cloud. They've got weimo that's 115 00:05:39,240 --> 00:05:41,680 Speaker 3: a big investment. I mean that that's a big call 116 00:05:41,720 --> 00:05:45,680 Speaker 3: option on the company overall. That revenue line could be huge, 117 00:05:45,680 --> 00:05:48,279 Speaker 3: and they are investing on the Vemo side. But look, 118 00:05:48,320 --> 00:05:52,039 Speaker 3: when it comes to Capex, it's all about training of 119 00:05:52,360 --> 00:05:55,760 Speaker 3: large angwid models. Can you maintain the lead when it 120 00:05:55,800 --> 00:06:00,560 Speaker 3: comes to you know, Microsoft OpenAI partnership and where stacks 121 00:06:00,640 --> 00:06:01,280 Speaker 3: up against them? 122 00:06:01,520 --> 00:06:03,960 Speaker 2: Where are we in the race? You said can If 123 00:06:03,960 --> 00:06:05,840 Speaker 2: they can maintain the lead, it has me where are 124 00:06:05,839 --> 00:06:06,440 Speaker 2: we in the race? 125 00:06:06,640 --> 00:06:09,400 Speaker 3: I mean, some would argue the open ai model is 126 00:06:09,440 --> 00:06:12,360 Speaker 3: still better for some of the large angrid model. 127 00:06:12,200 --> 00:06:14,440 Speaker 2: Use and open Ai is using Microsoft Azer. 128 00:06:14,560 --> 00:06:18,080 Speaker 3: They are using Microsoft Azor. So from that perspective, Google 129 00:06:18,160 --> 00:06:20,640 Speaker 3: is playing catch up. But they have been releasing a 130 00:06:20,680 --> 00:06:23,680 Speaker 3: lot more products lately than they were before. And that's 131 00:06:23,680 --> 00:06:27,040 Speaker 3: where I think owning the chips. Remember Google has their 132 00:06:27,120 --> 00:06:29,880 Speaker 3: own chips when it comes to training these models. They're 133 00:06:29,880 --> 00:06:33,160 Speaker 3: not even reliant on Nvidia for a large portion of training. 134 00:06:33,360 --> 00:06:36,360 Speaker 3: They do that in house, and that could the reason 135 00:06:36,400 --> 00:06:39,400 Speaker 3: why their Capex spend could be much lower than Microsoft. 136 00:06:39,440 --> 00:06:42,360 Speaker 1: Can we ask you? We've got Reddit? While we've got you. 137 00:06:42,400 --> 00:06:45,680 Speaker 1: Reddit is surging in the aftermarket. It's up about seventeen percent. 138 00:06:45,760 --> 00:06:49,599 Speaker 1: Also out with their earnings, c's signal strong holiday quarter 139 00:06:49,640 --> 00:06:52,720 Speaker 1: to come fourth quarter revenue three hundred and eighty five 140 00:06:52,760 --> 00:06:55,080 Speaker 1: to four hundred million. The street estimate was three fifty 141 00:06:55,120 --> 00:06:58,400 Speaker 1: six point two. So the outlook is upbeat. What do 142 00:06:58,440 --> 00:06:59,240 Speaker 1: we need to know here? 143 00:06:59,400 --> 00:07:02,560 Speaker 3: I mean, this just ipeoed at the perfect time. And 144 00:07:02,600 --> 00:07:04,920 Speaker 3: look when it comes to Reddit, all that timing. They 145 00:07:04,960 --> 00:07:09,200 Speaker 3: are one of the beneficiaries of llms, you know, implementing search, 146 00:07:09,520 --> 00:07:12,160 Speaker 3: because where do you drive that traffic when you show 147 00:07:12,200 --> 00:07:14,720 Speaker 3: a result in an LLLM. A lot of that traffic 148 00:07:14,760 --> 00:07:16,760 Speaker 3: goes to Reddit. And that's why a lot of the 149 00:07:16,800 --> 00:07:19,240 Speaker 3: Google traffic is now going to Reddit, A lot of 150 00:07:19,240 --> 00:07:19,800 Speaker 3: the chat che. 151 00:07:20,120 --> 00:07:22,000 Speaker 1: I guess say, when I search in different things, like 152 00:07:22,040 --> 00:07:23,000 Speaker 1: a lot of things goes. 153 00:07:22,840 --> 00:07:25,320 Speaker 2: Back go back to it. I also like, I spend 154 00:07:25,320 --> 00:07:27,600 Speaker 2: more time on Reddit than any other single you know, 155 00:07:27,680 --> 00:07:30,840 Speaker 2: quote unquote social media site like it's and I was 156 00:07:30,880 --> 00:07:32,040 Speaker 2: such a late adopter. 157 00:07:31,840 --> 00:07:34,480 Speaker 3: To Yeah, yeah, right, I mean, think of what these 158 00:07:34,600 --> 00:07:37,800 Speaker 3: lllms are trained on. They're trained on. Reddit data is 159 00:07:37,880 --> 00:07:41,200 Speaker 3: one of the corpus that is common across all the lllms, 160 00:07:41,400 --> 00:07:44,520 Speaker 3: and that's why when you search for something, it takes 161 00:07:44,600 --> 00:07:46,520 Speaker 3: you back to one of the Reddit posts, which is. 162 00:07:46,520 --> 00:07:49,040 Speaker 1: Kind of what they said right when they were ipoing, 163 00:07:49,120 --> 00:07:51,000 Speaker 1: right that this was going to be what was so 164 00:07:51,120 --> 00:07:53,000 Speaker 1: valuable about it, And it's playing out that way. 165 00:07:53,080 --> 00:07:55,520 Speaker 3: It is they ipeoed at the perfect time. I mean, 166 00:07:55,560 --> 00:07:57,160 Speaker 3: that acceleration is just amazing. 167 00:07:57,320 --> 00:07:59,600 Speaker 1: Can we ask you about Snap too? Snap is up 168 00:07:59,640 --> 00:08:03,040 Speaker 1: about ten eleven percent here in the aftermarket, So another 169 00:08:03,080 --> 00:08:04,560 Speaker 1: one that's surging. Let's go to the. 170 00:08:04,560 --> 00:08:06,720 Speaker 2: Outlook, thirty six percent so far this year. 171 00:08:06,800 --> 00:08:08,800 Speaker 1: Yeah, okay, so perspective. Sorry about that. I was getting 172 00:08:08,800 --> 00:08:12,280 Speaker 1: a little exciting fourth quarter revenue one in one point 173 00:08:12,320 --> 00:08:14,560 Speaker 1: five to one point five to one to one point 174 00:08:14,560 --> 00:08:16,440 Speaker 1: five six billion. The estimate on the street is one 175 00:08:16,440 --> 00:08:18,320 Speaker 1: point five six billion, so it sounds like that's a 176 00:08:18,320 --> 00:08:21,120 Speaker 1: little bit of a range. So they projecting slower holiday 177 00:08:21,160 --> 00:08:23,480 Speaker 1: advertising sales. Why are they up well? 178 00:08:23,800 --> 00:08:26,360 Speaker 3: In the case of Snap, like Tim said, you know, 179 00:08:26,800 --> 00:08:29,480 Speaker 3: they are up twenty percent one quarter, then down twenty 180 00:08:29,520 --> 00:08:32,640 Speaker 3: and in this case, I think overall what you're seeing 181 00:08:32,720 --> 00:08:37,479 Speaker 3: is the lower interest rates now I mean we have obviously, Yeah, 182 00:08:37,600 --> 00:08:39,520 Speaker 3: it's it helps the add companies. 183 00:08:39,200 --> 00:08:41,200 Speaker 1: There are buying back I should say, up to half 184 00:08:41,200 --> 00:08:41,640 Speaker 1: a billion. 185 00:08:42,120 --> 00:08:44,160 Speaker 3: Yeah, I don't know what to make of it, because 186 00:08:44,200 --> 00:08:47,280 Speaker 3: for a company of Snap size, doing a buyback right 187 00:08:47,320 --> 00:08:49,800 Speaker 3: now is not the best use of their cash. But 188 00:08:50,720 --> 00:08:52,120 Speaker 3: maybe the investors like that. 189 00:08:52,160 --> 00:08:53,600 Speaker 2: What should they be doing with their cash? 190 00:08:53,920 --> 00:08:58,040 Speaker 3: They should be deploying generative AI. Every platform right now 191 00:08:58,120 --> 00:09:01,680 Speaker 3: should be looking to add more feess that helps you 192 00:09:01,720 --> 00:09:05,160 Speaker 3: know their engagement. And generative AI is what every social 193 00:09:05,240 --> 00:09:07,800 Speaker 3: media platform is doing. Look at Meta, They're using it 194 00:09:07,840 --> 00:09:08,559 Speaker 3: at scale. 195 00:09:08,960 --> 00:09:11,000 Speaker 1: What an interesting kind of drop of earnings and we're 196 00:09:11,000 --> 00:09:12,760 Speaker 1: focusing on a lot of these kind of I feel 197 00:09:12,800 --> 00:09:16,440 Speaker 1: like high tech interesting. Google Alphabet up still three point 198 00:09:16,440 --> 00:09:18,600 Speaker 1: four percent in the aftermarket. Does it tell you anything 199 00:09:18,679 --> 00:09:23,520 Speaker 1: potentially about what's to come from Meta? From Amazon, from Microsoft? 200 00:09:23,559 --> 00:09:25,560 Speaker 1: Is there anything that we can infer here or now? 201 00:09:25,720 --> 00:09:27,920 Speaker 3: Yeah? I think Meta. For Meta, the bar is slightly 202 00:09:28,000 --> 00:09:31,200 Speaker 3: higher twenty percent growth rates, so I think they will 203 00:09:31,240 --> 00:09:34,120 Speaker 3: beat and raised, but clearly the bar is higher. And 204 00:09:34,200 --> 00:09:37,280 Speaker 3: for Microsoft, the Cloud number will blow out. I mean, 205 00:09:37,480 --> 00:09:40,520 Speaker 3: if Google Cloud did so well, I wouldn't be surprised 206 00:09:40,520 --> 00:09:43,160 Speaker 3: if Microsoft's growth is around that thirty four to thirty 207 00:09:43,160 --> 00:09:44,160 Speaker 3: five percent as well. 208 00:09:44,240 --> 00:09:46,880 Speaker 2: All right, Reddit shares up seventeen and a half percent 209 00:09:46,960 --> 00:09:48,959 Speaker 2: right now, I know I know, I know. I mean, 210 00:09:48,960 --> 00:09:51,720 Speaker 2: look we're talking, you know, and hundreds of millions of dollars, 211 00:09:51,760 --> 00:09:55,400 Speaker 2: not billions of dollars. Here, last question, what dos What 212 00:09:55,440 --> 00:09:57,640 Speaker 2: does all of this mean? Man Deep? For what we 213 00:09:57,679 --> 00:10:00,880 Speaker 2: get tomorrow and Thursday when we hear Amazon and Apple? 214 00:10:01,280 --> 00:10:03,640 Speaker 3: I mean for Amazon and Apple, I think. 215 00:10:03,600 --> 00:10:04,720 Speaker 2: They're meta platforms too. 216 00:10:04,800 --> 00:10:07,520 Speaker 3: Yeah, Look, meta I think should do well. I mean, 217 00:10:08,160 --> 00:10:11,679 Speaker 3: ads continue to be strong, and they should probably beat 218 00:10:11,760 --> 00:10:15,319 Speaker 3: and raise and their large angrid model LAMA is a 219 00:10:15,360 --> 00:10:21,080 Speaker 3: big strategic advantage. So in the case of Apple or Amazon, 220 00:10:21,200 --> 00:10:25,040 Speaker 3: they're very different. I think with Amazon, the AWS business 221 00:10:25,160 --> 00:10:29,120 Speaker 3: is growing slower than Microsoft and Google, so that may 222 00:10:29,200 --> 00:10:32,480 Speaker 3: weigh on them. And for Apple it's about China. I mean, 223 00:10:32,520 --> 00:10:35,440 Speaker 3: if they can counter that China risk, I think they 224 00:10:35,440 --> 00:10:36,240 Speaker 3: are a well position. 225 00:10:36,400 --> 00:10:37,800 Speaker 1: All right, We're gonna leave it on that note, Man 226 00:10:37,840 --> 00:10:42,079 Speaker 1: Deep saying the best Bloomberg intelligence breaking down those alphabet earnings. 227 00:10:42,080 --> 00:10:43,720 Speaker 1: Do you want to mention too a couple of others 228 00:10:43,720 --> 00:10:46,400 Speaker 1: that have crossed. AMD is down more than five percent 229 00:10:46,480 --> 00:10:50,960 Speaker 1: here in the aftermarket. They're forecast falling short, suggesting a 230 00:10:51,000 --> 00:10:54,960 Speaker 1: slower pace of AI growth advanced micro devices, giving a 231 00:10:55,000 --> 00:10:57,559 Speaker 1: lackluster revenue forecast for the current period, so there is 232 00:10:57,600 --> 00:11:02,640 Speaker 1: some concerns that it's aises are growing more slowly than anticipated. 233 00:11:02,720 --> 00:11:04,640 Speaker 1: And then Chippotle also at with results. 234 00:11:04,960 --> 00:11:08,880 Speaker 2: All right, shares of Chipotle ticker CMG in the after 235 00:11:08,960 --> 00:11:11,360 Speaker 2: hours right now, I'm just waiting for the. 236 00:11:11,280 --> 00:11:14,880 Speaker 1: Turn down about seven percent liter the after market. Their 237 00:11:14,960 --> 00:11:18,000 Speaker 1: sales falling short of investor expectations as well. 238 00:11:18,320 --> 00:11:21,240 Speaker 2: Yeah, for sales, look at this. The measure of locations 239 00:11:21,240 --> 00:11:23,760 Speaker 2: open for at least thirteen months rose six percent, was 240 00:11:23,800 --> 00:11:26,480 Speaker 2: below the average analyst estimate of six point four percent. 241 00:11:27,520 --> 00:11:30,120 Speaker 2: The stocks advanced so far thirty two percent this year, 242 00:11:30,200 --> 00:11:32,320 Speaker 2: so it's done better than the S and P five hundred. 243 00:11:32,840 --> 00:11:35,280 Speaker 2: The company did maintain its full year view that same 244 00:11:35,320 --> 00:11:37,319 Speaker 2: store sales will rise in the mid to high single 245 00:11:37,360 --> 00:11:37,960 Speaker 2: digit range. 246 00:11:38,000 --> 00:11:40,360 Speaker 1: All right, let's go back to though alphabet obviously the 247 00:11:40,360 --> 00:11:42,320 Speaker 1: big one and the one that we've been really focusing 248 00:11:42,360 --> 00:11:45,360 Speaker 1: on again, up about four percent here in the after market. 249 00:11:45,400 --> 00:11:48,440 Speaker 1: Caroline Hyde is here with us in studio, co host 250 00:11:48,440 --> 00:11:51,920 Speaker 1: of Bloomberg Technology on Bloomberg TV eleven am Wall Street Time. 251 00:11:52,000 --> 00:11:52,520 Speaker 3: Every day. 252 00:11:52,840 --> 00:11:54,679 Speaker 1: You're welcome, You're welcome. You guys are going to be 253 00:11:54,720 --> 00:11:55,560 Speaker 1: talking a lot about this. 254 00:11:56,040 --> 00:11:58,920 Speaker 4: What do you make oh, the cloud. Cloud revenue up 255 00:11:58,960 --> 00:12:00,760 Speaker 4: thirty five percent. I had you call it out when 256 00:12:00,800 --> 00:12:03,760 Speaker 4: they broke after the closing bell. And really that is 257 00:12:04,240 --> 00:12:07,880 Speaker 4: where the metal roots the road, really, doesn't it, Because 258 00:12:07,920 --> 00:12:10,280 Speaker 4: this is where the investment, the capex of over thirteen 259 00:12:10,320 --> 00:12:13,400 Speaker 4: billion dollars is vindicated. Because they're able to grow revenue 260 00:12:13,440 --> 00:12:16,440 Speaker 4: to such a significant extent. Why are they winning new clients? 261 00:12:16,440 --> 00:12:18,319 Speaker 4: Why are they getting the startups that are ex Google 262 00:12:18,400 --> 00:12:20,199 Speaker 4: is coming to them for their compute power, for their 263 00:12:20,240 --> 00:12:23,640 Speaker 4: services and their software, because they've got AI prowess that's 264 00:12:23,679 --> 00:12:26,360 Speaker 4: able to win yet more customers, more money, and more revenue. 265 00:12:26,480 --> 00:12:30,240 Speaker 2: Better AI prowess than Microsoft, who's in second place when 266 00:12:30,240 --> 00:12:33,720 Speaker 2: it comes to the cloud, or AWS who has the 267 00:12:33,800 --> 00:12:34,920 Speaker 2: crown for first place. 268 00:12:35,200 --> 00:12:37,439 Speaker 4: Many would say that the need for computers so vast 269 00:12:37,600 --> 00:12:40,240 Speaker 4: that you go wherever you can take it. But ultimately, 270 00:12:40,280 --> 00:12:42,680 Speaker 4: I think it's about whether they've got this suppliability and 271 00:12:42,720 --> 00:12:44,440 Speaker 4: whether they are able to cater to it. I think 272 00:12:44,600 --> 00:12:47,480 Speaker 4: people aren't. People do feel that even though from a 273 00:12:47,559 --> 00:12:51,240 Speaker 4: narrative perspective, in the consumer's mindset, maybe we suddenly thought 274 00:12:51,320 --> 00:12:54,560 Speaker 4: that open AI had run away with artificial intelligence generative 275 00:12:54,600 --> 00:12:57,200 Speaker 4: AI and leading the charge I'm sorry. DeepMind has been 276 00:12:57,200 --> 00:13:01,120 Speaker 4: there since twenty ten with Google as an an extraordinary 277 00:13:01,200 --> 00:13:04,720 Speaker 4: lab that has sophisticated AI prowess, and I think therefore 278 00:13:04,760 --> 00:13:07,040 Speaker 4: they're able to start showing that even if the narrative 279 00:13:07,120 --> 00:13:09,440 Speaker 4: moved on them, the actual reality is they're locking in 280 00:13:09,720 --> 00:13:13,080 Speaker 4: customers and they're able to generate their own revenue from this, 281 00:13:13,400 --> 00:13:16,120 Speaker 4: and that's why they're able to also drive up profitability. 282 00:13:16,120 --> 00:13:18,120 Speaker 4: They're managing to be cost focused at the same time 283 00:13:18,120 --> 00:13:19,080 Speaker 4: as driving up revenue. 284 00:13:19,120 --> 00:13:21,880 Speaker 1: You know, we talk about you know that they're advertising business, right, 285 00:13:21,920 --> 00:13:24,200 Speaker 1: it's a massive one. It's a big one, but there's 286 00:13:24,240 --> 00:13:26,880 Speaker 1: a maturation aspect of it, right, and so it's important 287 00:13:26,920 --> 00:13:29,400 Speaker 1: to see the cloud business continue to grow or the 288 00:13:29,440 --> 00:13:31,520 Speaker 1: YouTube business continue to grow. I mean, these are important 289 00:13:31,559 --> 00:13:32,559 Speaker 1: to see these aspects. 290 00:13:32,760 --> 00:13:34,640 Speaker 4: It is, and actually we manage to live up to 291 00:13:34,679 --> 00:13:36,880 Speaker 4: expectations when it came to the juggernaut that is the 292 00:13:36,920 --> 00:13:42,200 Speaker 4: ad business YouTube considerable addition there. And look, this is 293 00:13:42,200 --> 00:13:44,880 Speaker 4: where people have been worried about generative AI encroaching on 294 00:13:44,920 --> 00:13:47,160 Speaker 4: that part of the business model too. Would suddenly I 295 00:13:47,280 --> 00:13:50,360 Speaker 4: not go to Google, Would I instead go to chatchypt? 296 00:13:50,559 --> 00:13:53,800 Speaker 4: Would I be using perplexity people aren't, and my way, 297 00:13:53,920 --> 00:13:56,800 Speaker 4: I love Google AI overviews. I think it's really easy 298 00:13:56,800 --> 00:13:59,280 Speaker 4: and it keeps me using what I'm used to using 299 00:13:59,520 --> 00:14:00,480 Speaker 4: right exactly. 300 00:14:00,559 --> 00:14:03,440 Speaker 2: This is so remarkable to me. YouTube's total ads and 301 00:14:03,480 --> 00:14:07,640 Speaker 2: subscription revenues surpass fifty billion dollars over the past four 302 00:14:07,720 --> 00:14:10,600 Speaker 2: quarters for the first time. I was marveling thinking back 303 00:14:10,640 --> 00:14:12,880 Speaker 2: to two thousand and six when YouTube was, yeah, an 304 00:14:12,920 --> 00:14:15,640 Speaker 2: independent company. Google bought it for what one point six 305 00:14:15,720 --> 00:14:17,199 Speaker 2: billion dollars or something. 306 00:14:17,200 --> 00:14:20,160 Speaker 4: And now they can move from freemium to premium and 307 00:14:20,200 --> 00:14:23,480 Speaker 4: suddenly we're all still completely using addicted it. They've got 308 00:14:23,480 --> 00:14:25,800 Speaker 4: live sports, and no wonder that we're returning to YouTube 309 00:14:25,800 --> 00:14:28,400 Speaker 4: time and time again. I mean, they own market share 310 00:14:28,400 --> 00:14:30,960 Speaker 4: when it comes to our eyeballs, and they can start 311 00:14:31,040 --> 00:14:33,200 Speaker 4: charging us for it. So they're able to contribute more 312 00:14:33,200 --> 00:14:35,400 Speaker 4: than eight billion dollars in terms of overall revenue for 313 00:14:35,440 --> 00:14:39,240 Speaker 4: the business. And it's more about us paying for it 314 00:14:39,280 --> 00:14:41,600 Speaker 4: as consumers than it is about advertising. At the moment. 315 00:14:41,600 --> 00:14:43,600 Speaker 4: People will worry that might run a little very light, 316 00:14:43,720 --> 00:14:44,920 Speaker 4: but they're able to get us to pay. 317 00:14:45,000 --> 00:14:47,880 Speaker 1: Caroline, I think about you and ed and your coverage, 318 00:14:48,840 --> 00:14:51,200 Speaker 1: you know, going into tomorrow, what's kind of top of 319 00:14:51,240 --> 00:14:53,920 Speaker 1: mind for you when it comes to Alphabet and what 320 00:14:54,080 --> 00:14:55,520 Speaker 1: it maybe says to us about some of the other 321 00:14:55,560 --> 00:14:58,200 Speaker 1: big megacaps to report, which it's a massive week. 322 00:14:58,360 --> 00:15:00,960 Speaker 4: What does it signal for Avatar housing resilience for the 323 00:15:01,080 --> 00:15:03,240 Speaker 4: likes of Meta, for the likes of other players, But 324 00:15:03,280 --> 00:15:05,160 Speaker 4: what does it mean in terms of Nvidia? We don't 325 00:15:05,200 --> 00:15:06,960 Speaker 4: we have to wait until November. 326 00:15:06,600 --> 00:15:07,840 Speaker 1: To get in video amazing. 327 00:15:08,240 --> 00:15:10,240 Speaker 4: All of the hyperscales are going to be coming this week, 328 00:15:10,280 --> 00:15:12,120 Speaker 4: and we want to know that that thirteen billion dollars 329 00:15:12,160 --> 00:15:14,320 Speaker 4: is still there. What willston our pitch I'd talk about 330 00:15:14,480 --> 00:15:17,400 Speaker 4: in terms of future capex spend, but also he's got 331 00:15:17,400 --> 00:15:21,560 Speaker 4: to take questions on anti anti competitive, anti trust issues. 332 00:15:21,720 --> 00:15:24,240 Speaker 4: That's the overhang on the stock. We can see that 333 00:15:24,320 --> 00:15:27,000 Speaker 4: the numbers are there, but what about the future business 334 00:15:27,000 --> 00:15:29,920 Speaker 4: model and how he has to basically pivot and change 335 00:15:30,280 --> 00:15:33,000 Speaker 4: to be able to take the pressure off himself from 336 00:15:33,040 --> 00:15:35,320 Speaker 4: the DOJ here in the United States, the FTC and 337 00:15:35,360 --> 00:15:36,160 Speaker 4: over in Europe too. 338 00:15:36,240 --> 00:15:38,680 Speaker 1: Yeah, it's kind of how we started off a couple 339 00:15:38,680 --> 00:15:40,600 Speaker 1: of hours ago. Like the overhang of this one. 340 00:15:40,640 --> 00:15:42,800 Speaker 2: I'm looking at chairs of Meta Platforms. They were hired 341 00:15:42,840 --> 00:15:45,520 Speaker 2: today in the trade, but also hired by eight tenths 342 00:15:45,520 --> 00:15:48,080 Speaker 2: of one percent in the after hours that company reporting 343 00:15:48,120 --> 00:15:49,320 Speaker 2: tomorrow aftermarket. 344 00:15:49,360 --> 00:15:51,440 Speaker 1: All Right, grit steffis always thank you, Thank you, Joe 345 00:15:51,600 --> 00:15:54,440 Speaker 1: Day for you really appreciate it. Caroline Hyde, of course, 346 00:15:54,520 --> 00:15:58,080 Speaker 1: co host of Blueberg Technology on Bloomberg TV with Ed Ludlows. 347 00:15:58,080 --> 00:16:00,400 Speaker 1: So catch them at eleven am Wall Street Time everyday, 348 00:16:00,440 --> 00:16:01,160 Speaker 1: Monday through Friday.