1 00:00:02,600 --> 00:00:10,799 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Bloomberg Business 2 00:00:10,840 --> 00:00:14,080 Speaker 1: Week inside from the reporters and editors who bring you 3 00:00:14,120 --> 00:00:18,439 Speaker 1: America's most trusted business magazine, plus global business, finance and 4 00:00:18,520 --> 00:00:22,320 Speaker 1: tech news as it happens. Bloomberg Business Week with Carol 5 00:00:22,360 --> 00:00:25,920 Speaker 1: Messer and Tim Stenebek on Bloomberg Radio. 6 00:00:26,280 --> 00:00:29,120 Speaker 2: It is Bloomberg Business Week. Shares some meta platforms bouncing around, 7 00:00:29,160 --> 00:00:31,920 Speaker 2: but up about five percent in the after hours. Now, 8 00:00:32,000 --> 00:00:35,360 Speaker 2: the company did report second quarter revenue that beat estimates. 9 00:00:36,159 --> 00:00:39,600 Speaker 2: Revenue coming in at thirty nine point oh seven billion dollars. 10 00:00:39,600 --> 00:00:42,360 Speaker 2: That's a twenty two percent year over year increase, beating 11 00:00:42,440 --> 00:00:45,680 Speaker 2: estimates of thirty eight point three four billion dollars in 12 00:00:45,720 --> 00:00:48,240 Speaker 2: that family of apps revenue that is the core business 13 00:00:48,560 --> 00:00:50,840 Speaker 2: thirty eight point seven two billion dollars in the quarter, 14 00:00:50,880 --> 00:00:53,920 Speaker 2: up twenty two percent. Estimate was for thirty seven point 15 00:00:53,960 --> 00:00:58,800 Speaker 2: seven six Carol highlighted the capex, the company seeing total 16 00:00:58,840 --> 00:01:01,960 Speaker 2: capex thirty seven to forty billion where they sought where 17 00:01:01,960 --> 00:01:04,720 Speaker 2: investors saw thirty five to forty billion. The estimate was 18 00:01:04,720 --> 00:01:08,679 Speaker 2: for thirty seven point five to three billion dollars. So again, 19 00:01:08,840 --> 00:01:12,200 Speaker 2: what we saw from Microsoft and what we saw from Alphabet. 20 00:01:12,240 --> 00:01:13,800 Speaker 3: Here's what I'm going to say. Their bread and butter 21 00:01:13,920 --> 00:01:16,039 Speaker 3: is advertising. They did report better than a sales for 22 00:01:16,080 --> 00:01:20,559 Speaker 3: the second quarter, So again, are right through the Wagner 23 00:01:20,800 --> 00:01:23,720 Speaker 3: Carol offering evidence at the company's heavy investments in AI 24 00:01:23,880 --> 00:01:27,600 Speaker 3: helping itself more targeted and personal personalized advertisements. That is 25 00:01:27,600 --> 00:01:30,080 Speaker 3: still their bread and butter. So if they are saying 26 00:01:30,120 --> 00:01:32,200 Speaker 3: we are spending guys, and we're going to spend even more, 27 00:01:32,200 --> 00:01:34,440 Speaker 3: but look at the results from the past quarter. And 28 00:01:34,440 --> 00:01:36,840 Speaker 3: that's where I'm trying to make sense of the stock 29 00:01:36,880 --> 00:01:39,399 Speaker 3: being up here in the aftermarket, up five percent. It's 30 00:01:39,440 --> 00:01:41,039 Speaker 3: not like people are saying, oh my god, what are 31 00:01:41,040 --> 00:01:41,479 Speaker 3: you spending? 32 00:01:41,480 --> 00:01:43,600 Speaker 2: You all thought you all thought that AI was going 33 00:01:43,640 --> 00:01:46,679 Speaker 2: to make our jobs easier, when in reality it just 34 00:01:46,720 --> 00:01:49,120 Speaker 2: makes Facebook better at targeting ads to you. 35 00:01:49,320 --> 00:01:52,680 Speaker 3: Yeah, yeah, well done. All right, So let's get to it. 36 00:01:52,720 --> 00:01:55,480 Speaker 3: Our team coverage with Bloomberg News contributor John Earlekman joining 37 00:01:55,520 --> 00:01:58,400 Speaker 3: us from Toronto, along with Bloomberg News social media reporter 38 00:01:58,720 --> 00:02:01,640 Speaker 3: Asha Counts joining Usgosh, I want to start with you, 39 00:02:01,720 --> 00:02:02,400 Speaker 3: how did meta do? 40 00:02:03,920 --> 00:02:05,640 Speaker 4: I mean? I think you said it earlier. They beat 41 00:02:05,720 --> 00:02:09,720 Speaker 4: on everything right, The revenue beat expectations actually the top 42 00:02:09,840 --> 00:02:13,239 Speaker 4: end of what analysts expected. And they also beat on 43 00:02:13,240 --> 00:02:14,880 Speaker 4: the amount of users that they have. I mean, they 44 00:02:14,919 --> 00:02:17,000 Speaker 4: just they beat in every dimension. Now, the one thing 45 00:02:17,040 --> 00:02:19,079 Speaker 4: you did mention right with that capex, which is that 46 00:02:19,200 --> 00:02:20,960 Speaker 4: spending a lot of which is going to things like 47 00:02:21,000 --> 00:02:25,720 Speaker 4: a infrastructure. You're talking servers and data and hardware and 48 00:02:25,760 --> 00:02:29,760 Speaker 4: stuff like that. That increased a little bit. But because 49 00:02:29,800 --> 00:02:32,320 Speaker 4: it was that bottom range, right, like, their top line 50 00:02:32,400 --> 00:02:35,160 Speaker 4: level didn't increase. I don't think investors are going to 51 00:02:35,200 --> 00:02:37,080 Speaker 4: be that upset about that. So, yeah, they beat on everything, 52 00:02:37,680 --> 00:02:39,840 Speaker 4: changed a couple of things, but I think overall it's 53 00:02:39,840 --> 00:02:40,320 Speaker 4: good for them. 54 00:02:40,520 --> 00:02:42,680 Speaker 2: Hey, John, what sticks out to you here? You've had 55 00:02:42,680 --> 00:02:45,840 Speaker 2: a few minutes to go over these numbers. What sticks 56 00:02:45,840 --> 00:02:46,200 Speaker 2: out to you? 57 00:02:47,520 --> 00:02:50,880 Speaker 5: Just tim that Mark Zuckerberg and Metas seem to have 58 00:02:50,919 --> 00:02:51,919 Speaker 5: the script down. 59 00:02:51,720 --> 00:02:53,079 Speaker 6: Pretty cold at this point. 60 00:02:53,120 --> 00:02:55,880 Speaker 5: I mean, building on everything you've said, here's a company 61 00:02:55,960 --> 00:02:58,400 Speaker 5: that over the last couple of years, has learned its 62 00:02:58,520 --> 00:03:03,200 Speaker 5: lessons when it comes to what starts to make Wall 63 00:03:03,240 --> 00:03:06,680 Speaker 5: Street uncomfortable on the spending front. And I think that 64 00:03:07,000 --> 00:03:11,040 Speaker 5: the fact that the as you guys highlighted earlier, that 65 00:03:11,120 --> 00:03:14,480 Speaker 5: they can make the case that the revenue that came 66 00:03:14,520 --> 00:03:19,280 Speaker 5: in stronger than expected gets assistance from the investment that's 67 00:03:19,360 --> 00:03:21,440 Speaker 5: coming from all this AI focus. 68 00:03:22,080 --> 00:03:24,520 Speaker 6: That seems to be a helping hand here. 69 00:03:24,760 --> 00:03:26,840 Speaker 5: I would add though, that if you go back to 70 00:03:26,840 --> 00:03:29,919 Speaker 5: the last quarter, remember and by the way, this stock 71 00:03:29,960 --> 00:03:33,520 Speaker 5: always moves a lot. Generally, it moves a lot after earnings, 72 00:03:33,600 --> 00:03:36,560 Speaker 5: either up or down. But the shares got crushed because 73 00:03:36,720 --> 00:03:41,160 Speaker 5: investors had to do another reassessment on this AI spending. 74 00:03:41,240 --> 00:03:43,680 Speaker 5: So arguably we've had some time to fit with this 75 00:03:44,160 --> 00:03:45,880 Speaker 5: and even the stock price. I know it's up a 76 00:03:45,880 --> 00:03:49,640 Speaker 5: lot this year, but at last check it was coming 77 00:03:49,680 --> 00:03:50,800 Speaker 5: into this earnings. 78 00:03:50,480 --> 00:03:52,440 Speaker 6: Report a little bit lower than where it. 79 00:03:52,440 --> 00:03:55,600 Speaker 5: Was heading into the last quarter. So I don't think 80 00:03:55,640 --> 00:03:58,040 Speaker 5: anyone would have been surprised to see a big spending bill. 81 00:03:58,200 --> 00:04:01,680 Speaker 5: But you have stronger than expect did numbers. And remember 82 00:04:01,680 --> 00:04:04,240 Speaker 5: this is also the company that's starting to find shareholder 83 00:04:04,280 --> 00:04:07,200 Speaker 5: friendly tricks and it's playbook. They issued their first dividend 84 00:04:07,800 --> 00:04:09,760 Speaker 5: and they're buying back a lot of stocks, so they've 85 00:04:09,760 --> 00:04:12,280 Speaker 5: got the levers they can pull. But we still have 86 00:04:12,320 --> 00:04:14,160 Speaker 5: to see how all this AI spending nets out in 87 00:04:14,200 --> 00:04:16,160 Speaker 5: the long term. We don't quite know, but they're trying 88 00:04:16,200 --> 00:04:17,479 Speaker 5: to paint a good picture so far. 89 00:04:17,640 --> 00:04:20,040 Speaker 3: Yeah, and for a stock that bopped up I think 90 00:04:20,040 --> 00:04:22,039 Speaker 3: about ten percent here in the aftermarket, we're now just 91 00:04:22,080 --> 00:04:25,400 Speaker 3: up about three point six percent, still higher, but it 92 00:04:25,680 --> 00:04:28,240 Speaker 3: continues as I think investors and analysts continue to go 93 00:04:28,240 --> 00:04:29,880 Speaker 3: through the report and we'll wait to see what comes 94 00:04:29,880 --> 00:04:32,880 Speaker 3: out on the call. Having said that, John, how does 95 00:04:32,960 --> 00:04:36,159 Speaker 3: Meta square with some of the other companies that we 96 00:04:36,240 --> 00:04:40,800 Speaker 3: are so intently focused on their AI spending and their 97 00:04:40,839 --> 00:04:43,200 Speaker 3: AI ROI return on investment? 98 00:04:44,560 --> 00:04:46,760 Speaker 5: You know, everybody is in an arms race here, and 99 00:04:46,839 --> 00:04:48,400 Speaker 5: I think at the end of the day, Carol, you 100 00:04:48,400 --> 00:04:52,040 Speaker 5: could make an argument that because Alphabet came first and 101 00:04:52,200 --> 00:04:55,800 Speaker 5: investors got a little jittery on the roadmap for the 102 00:04:55,839 --> 00:04:59,880 Speaker 5: spending on AI and the return on investment. Remember that 103 00:05:00,160 --> 00:05:03,080 Speaker 5: to coming into this week, tech had been pretty roughed up, 104 00:05:03,440 --> 00:05:06,960 Speaker 5: So it almost dare I say, set the bar lower 105 00:05:07,360 --> 00:05:10,480 Speaker 5: for the tech giants that would be putting out numbers 106 00:05:10,520 --> 00:05:13,800 Speaker 5: this week. I think that at the end of the day, 107 00:05:14,480 --> 00:05:18,000 Speaker 5: longer term, and Mark Zuckerberg said it himself in his 108 00:05:18,040 --> 00:05:20,359 Speaker 5: interview with Emily Chang not that long ago, there is 109 00:05:20,400 --> 00:05:23,239 Speaker 5: a possibility that all the spending they are doing today 110 00:05:23,880 --> 00:05:28,280 Speaker 5: might be an overshoot, but they're right now trying to 111 00:05:28,400 --> 00:05:32,480 Speaker 5: build a future where engagement can be increased through AI, 112 00:05:33,360 --> 00:05:37,200 Speaker 5: that advertisers can have better, more targeted ads through AI, 113 00:05:37,320 --> 00:05:42,520 Speaker 5: that they can have a much cleaner thread between software 114 00:05:42,560 --> 00:05:44,960 Speaker 5: and hardware, like the glasses you're talking about. 115 00:05:45,480 --> 00:05:47,640 Speaker 6: I think they really like where this story is going. 116 00:05:47,720 --> 00:05:51,000 Speaker 5: Over the long term, they're probably getting a boost as well, 117 00:05:51,520 --> 00:05:54,040 Speaker 5: just because there's a lot of eyeballs on big events 118 00:05:54,160 --> 00:05:56,800 Speaker 5: right now like the Olympics, and so they can benefit 119 00:05:56,839 --> 00:05:57,240 Speaker 5: from that. 120 00:05:58,360 --> 00:06:00,839 Speaker 6: But there's the other side of that we don't know 121 00:06:00,880 --> 00:06:01,400 Speaker 6: a lot about. 122 00:06:01,440 --> 00:06:03,560 Speaker 5: Mark Zuckerbergs spent a lot of time in front of 123 00:06:03,880 --> 00:06:05,520 Speaker 5: lawmakers in Washington over. 124 00:06:05,320 --> 00:06:06,200 Speaker 6: The last decade. 125 00:06:06,320 --> 00:06:09,240 Speaker 5: People are still a little concerned, maybe more than a 126 00:06:09,240 --> 00:06:14,599 Speaker 5: little concerned about the ramifications of all this AI technology 127 00:06:14,640 --> 00:06:18,159 Speaker 5: that they're weaving into the Meta ecosystem. But you know, 128 00:06:18,200 --> 00:06:19,680 Speaker 5: at the end of the day, if they can keep 129 00:06:19,720 --> 00:06:24,400 Speaker 5: the bottom line in a relatively clean manner and keep 130 00:06:24,440 --> 00:06:27,159 Speaker 5: growing the revenue story, you know, Meta is in a 131 00:06:27,160 --> 00:06:30,640 Speaker 5: position to have a arguably a cleaner quarterly story than 132 00:06:30,680 --> 00:06:31,640 Speaker 5: some of its peers. 133 00:06:31,880 --> 00:06:33,400 Speaker 2: Hey, so can you talk a little bit about the 134 00:06:33,839 --> 00:06:39,320 Speaker 2: integration of LAMA and AI into meta platforms family of apps. 135 00:06:39,440 --> 00:06:41,800 Speaker 2: You know, Carol and I were joking about the idea 136 00:06:41,839 --> 00:06:45,080 Speaker 2: of the result of all this investment in AI is 137 00:06:45,120 --> 00:06:46,279 Speaker 2: just better targeted ads. 138 00:06:47,920 --> 00:06:50,240 Speaker 4: It's funny because Metta is one of those companies where 139 00:06:50,279 --> 00:06:53,560 Speaker 4: the AI is all behind the scenes, right. So obviously 140 00:06:53,560 --> 00:06:56,880 Speaker 4: they've been using AI for years, per decades to recommend 141 00:06:56,920 --> 00:06:59,960 Speaker 4: content on your feed, whether that's on Instagram or Facebook, 142 00:07:00,240 --> 00:07:02,760 Speaker 4: whether that's posts and images or videos, and so a 143 00:07:02,760 --> 00:07:05,240 Speaker 4: lot of it goes towards that. But then they've also 144 00:07:05,279 --> 00:07:08,720 Speaker 4: released new products like AI chatbot that you could talk to, right, 145 00:07:08,800 --> 00:07:11,000 Speaker 4: So meta AI, if you go on Instagram or Facebook, 146 00:07:11,040 --> 00:07:12,920 Speaker 4: it'll pop up and you can ask it questions and 147 00:07:13,200 --> 00:07:16,680 Speaker 4: things like that, so you see some product experiences. They 148 00:07:16,720 --> 00:07:19,400 Speaker 4: also had rolled out some things like celebrity chatbots, so 149 00:07:19,480 --> 00:07:23,240 Speaker 4: you could chat with a chatbot that looked and sounded like, 150 00:07:23,760 --> 00:07:25,560 Speaker 4: you know, Tom Brady, for example. 151 00:07:25,240 --> 00:07:29,200 Speaker 2: I knew you were gonna say Tom Brady, Yeah, I 152 00:07:29,200 --> 00:07:30,400 Speaker 2: remember he showed that off. 153 00:07:30,280 --> 00:07:33,480 Speaker 4: Right, Yes, yeah, they showed that off. But then they 154 00:07:33,560 --> 00:07:37,200 Speaker 4: shuddered it recently, and so it's like, how much are 155 00:07:37,240 --> 00:07:39,440 Speaker 4: those products and services really moving the needle for them 156 00:07:39,520 --> 00:07:41,440 Speaker 4: or is it really just again like you're saying, going 157 00:07:41,480 --> 00:07:44,680 Speaker 4: back to the core advertising business, going back to the feed, 158 00:07:44,720 --> 00:07:46,960 Speaker 4: and how do they recommend content that users actually want 159 00:07:46,960 --> 00:07:47,520 Speaker 4: to watch the view? 160 00:07:47,800 --> 00:07:50,160 Speaker 3: Can I help me out here? Is there something in 161 00:07:50,200 --> 00:07:53,600 Speaker 3: this release that sells specifically shows specifically is there a 162 00:07:53,760 --> 00:07:57,400 Speaker 3: number or something that says, Yep, here's our AI investing 163 00:07:57,560 --> 00:07:59,720 Speaker 3: and here's how it paid off? I mean, or John, 164 00:07:59,720 --> 00:08:03,760 Speaker 3: do we just assume that if the revenue is beating 165 00:08:03,960 --> 00:08:06,720 Speaker 3: that it's because of AI spending? You know what I mean? 166 00:08:07,840 --> 00:08:10,480 Speaker 6: Yeah, I absolutely know what you mean. 167 00:08:10,560 --> 00:08:13,000 Speaker 5: I mean, the first line in the press release itself 168 00:08:13,120 --> 00:08:15,760 Speaker 5: was really trying to talk more about how AI is 169 00:08:15,840 --> 00:08:17,640 Speaker 5: complementing the hardware that they've got. 170 00:08:17,840 --> 00:08:19,840 Speaker 6: Yeah, and that might just speak to the fact that 171 00:08:20,080 --> 00:08:21,440 Speaker 6: go back a couple of years. 172 00:08:21,240 --> 00:08:26,840 Speaker 5: Ago, as we were just highlighting like AI is technically 173 00:08:26,840 --> 00:08:29,280 Speaker 5: not a new thing for the company, but it is 174 00:08:29,320 --> 00:08:31,160 Speaker 5: the hot thing for the world to talk about. So 175 00:08:31,240 --> 00:08:32,800 Speaker 5: it is front and center right now. But a couple 176 00:08:32,800 --> 00:08:35,080 Speaker 5: of years ago what was front and center was quite 177 00:08:35,080 --> 00:08:37,640 Speaker 5: literally changing the name from Facebook to Meta and talking 178 00:08:37,679 --> 00:08:40,480 Speaker 5: about the metaverse and talking about you know, other VR 179 00:08:40,559 --> 00:08:43,040 Speaker 5: and AR opportunities. And so I think that there is 180 00:08:43,080 --> 00:08:47,400 Speaker 5: still because of the explosive spending in that area. You know, 181 00:08:47,520 --> 00:08:50,720 Speaker 5: maybe this is Mark Zuckerberg just wanted to put a 182 00:08:50,760 --> 00:08:53,640 Speaker 5: pin in the fact that they can actually make all 183 00:08:53,679 --> 00:08:56,400 Speaker 5: of this thing together. I would imagine, Carol, you get 184 00:08:56,480 --> 00:08:59,959 Speaker 5: more color on how they're connecting the advertising dots on 185 00:09:00,120 --> 00:09:04,040 Speaker 5: the quarterly conference call. But the revenue growing. I think 186 00:09:04,280 --> 00:09:08,079 Speaker 5: already analysts, in reaction to this as Bloomberg is reporting, 187 00:09:08,240 --> 00:09:09,400 Speaker 5: are suggesting that as the case. 188 00:09:09,520 --> 00:09:11,439 Speaker 3: Listen, both of you. Thank you so much. Bloomberg News 189 00:09:11,480 --> 00:09:14,360 Speaker 3: contributor John Arlokman out there in Toronto. Bloomberg News social 190 00:09:14,360 --> 00:09:17,560 Speaker 3: media reporter Asha Counts in Chicago shares a mediciin right 191 00:09:17,559 --> 00:09:18,960 Speaker 3: now up five point four percent,