1 00:00:01,400 --> 00:00:05,720 Speaker 1: From Marhart where Innovation, Money and power Collie in Silicon 2 00:00:05,800 --> 00:00:06,680 Speaker 1: Vallet NBN. 3 00:00:07,040 --> 00:00:10,480 Speaker 2: This is Bloomberg Technology with Caroline Hyde. 4 00:00:10,160 --> 00:00:11,280 Speaker 3: And Ed Loved Love. 5 00:00:25,239 --> 00:00:27,800 Speaker 4: Live from New York and San Francisco. This is Bloomberg 6 00:00:27,840 --> 00:00:31,560 Speaker 4: Technology coming up in videop is the Price of lofty expectations. 7 00:00:31,840 --> 00:00:36,400 Speaker 4: CEO Jensen One tries to boost confidence in a Bloomberg exclusive. 8 00:00:36,680 --> 00:00:40,040 Speaker 5: Past the Telegram. CEO is charged and out on bail 9 00:00:40,200 --> 00:00:42,839 Speaker 5: in France. So the crimes committed on the app. We 10 00:00:42,840 --> 00:00:44,320 Speaker 5: go live to Paris. 11 00:00:43,960 --> 00:00:45,159 Speaker 6: And California advances. 12 00:00:45,200 --> 00:00:49,000 Speaker 4: It's controversial AI safety bill that has divided tech leaders. 13 00:00:49,120 --> 00:00:51,519 Speaker 6: We'll discuss the law as it heads to the state Senate. 14 00:00:51,880 --> 00:00:54,400 Speaker 4: That is so much more coming up, but first which 15 00:00:54,440 --> 00:00:56,800 Speaker 4: I can on the key name that we are all 16 00:00:56,800 --> 00:00:59,880 Speaker 4: watching today in video of by two point eight percent, 17 00:01:00,200 --> 00:01:02,680 Speaker 4: the three trillion dollar company not living up to the 18 00:01:02,760 --> 00:01:05,240 Speaker 4: hype in terms of its forecasts and particularly Blackwell, which 19 00:01:05,280 --> 00:01:07,560 Speaker 4: will dig into ed but it's not dragging down the 20 00:01:07,560 --> 00:01:08,520 Speaker 4: rest of the indices. 21 00:01:10,000 --> 00:01:12,679 Speaker 5: Mark it up in vidio down. I caught up with 22 00:01:12,760 --> 00:01:16,959 Speaker 5: Nvidia CEO Jensen Wang after the results. He addressed concerns 23 00:01:17,200 --> 00:01:20,960 Speaker 5: about the company's latest generation Blackwell chips. 24 00:01:20,840 --> 00:01:23,080 Speaker 7: We're expecting Q three to have more supply than Q two, 25 00:01:23,319 --> 00:01:25,640 Speaker 7: We're expecting Q four to have more supplier than Q three, 26 00:01:25,720 --> 00:01:27,440 Speaker 7: and we're expecting Q one to have more supply than 27 00:01:27,480 --> 00:01:30,240 Speaker 7: Q four, And so I think our supply, our supply 28 00:01:30,360 --> 00:01:32,800 Speaker 7: condition going into next year will be in will be 29 00:01:33,280 --> 00:01:35,280 Speaker 7: a large improvement over this last year. 30 00:01:37,920 --> 00:01:42,160 Speaker 5: Congensabani of Bloomberg Intelligence joins us now in San Francisco. 31 00:01:42,840 --> 00:01:46,600 Speaker 5: You said it in Vidio's strong expectations stronger. 32 00:01:46,959 --> 00:01:48,640 Speaker 8: What's your thesis this morning. 33 00:01:48,680 --> 00:01:51,000 Speaker 9: When they've fallen victim to their own strength and on 34 00:01:51,080 --> 00:01:54,280 Speaker 9: realistic expectations. When we look about the top concerns going 35 00:01:54,280 --> 00:01:57,560 Speaker 9: into the prink blackwell, the several billion in Q four 36 00:01:57,560 --> 00:01:59,920 Speaker 9: put a lid on uncertainties in twenty twenty five. 37 00:02:00,200 --> 00:02:04,320 Speaker 5: Demand sustainability, just real quick, because several billion doesn't mean anything. 38 00:02:04,720 --> 00:02:07,440 Speaker 9: Well, it still is solid in terms of what we 39 00:02:07,520 --> 00:02:10,000 Speaker 9: expected or given the last four weeks of what we've 40 00:02:10,000 --> 00:02:12,600 Speaker 9: been hearing the issues. So that's still impressive that they 41 00:02:12,600 --> 00:02:15,959 Speaker 9: are able to pull it off so soon. Second, demand sustainability, 42 00:02:16,000 --> 00:02:19,600 Speaker 9: we saw demand broadening and in fact getting stronger beyond. 43 00:02:19,320 --> 00:02:20,480 Speaker 10: Just the large cloud guys. 44 00:02:20,600 --> 00:02:23,200 Speaker 9: And finally, when we put it all together our estimates, 45 00:02:23,240 --> 00:02:25,440 Speaker 9: and I believe most of the street estimates are actually 46 00:02:25,440 --> 00:02:27,519 Speaker 9: going up after this earnings than they were before. 47 00:02:28,400 --> 00:02:31,399 Speaker 4: Quin John, Yes, perhaps it's a victim of its own 48 00:02:31,400 --> 00:02:35,440 Speaker 4: success and analyst investors' exuberance around the name. But is 49 00:02:35,440 --> 00:02:39,280 Speaker 4: it also a victim of its own ambitions setting itself 50 00:02:40,000 --> 00:02:44,399 Speaker 4: terms of time that just aren't able to be hit 51 00:02:44,560 --> 00:02:47,240 Speaker 4: When we see that people aren't disappointed by a Q 52 00:02:47,360 --> 00:02:49,800 Speaker 4: four and later ramp up for Q one Q two 53 00:02:49,880 --> 00:02:50,440 Speaker 4: of next year. 54 00:02:50,560 --> 00:02:54,640 Speaker 9: Fiscally, I mean definitely, it's part of two things. The 55 00:02:54,800 --> 00:02:58,959 Speaker 9: execution they have performed over the last two years have 56 00:02:59,040 --> 00:03:02,280 Speaker 9: been nothing but phenomenal. It's very hard to continue with 57 00:03:02,400 --> 00:03:06,400 Speaker 9: this annual cadence reiterating the new chip designs at time, 58 00:03:06,639 --> 00:03:08,920 Speaker 9: bringing in the supply not just at scale but at 59 00:03:09,000 --> 00:03:11,680 Speaker 9: new technology module. So it's definitely a high bar. 60 00:03:11,800 --> 00:03:13,959 Speaker 5: They have said, I actually want to talk about new 61 00:03:14,000 --> 00:03:16,959 Speaker 5: technology model. There was a question on the Analyst score 62 00:03:17,240 --> 00:03:19,560 Speaker 5: which I also try to get into a Jensen Wang 63 00:03:20,000 --> 00:03:24,840 Speaker 5: about generational upgrades. Right now, H two hundred is ramping 64 00:03:24,880 --> 00:03:27,000 Speaker 5: being deployed in the real world, and before we know it, 65 00:03:27,080 --> 00:03:30,000 Speaker 5: Blackwell's here. So if you're a data center operator, you 66 00:03:30,120 --> 00:03:32,920 Speaker 5: have the option of both potentially at the same time. 67 00:03:33,160 --> 00:03:34,240 Speaker 8: How do you model for that? 68 00:03:34,800 --> 00:03:37,000 Speaker 9: I mean, each data center operator is at a different 69 00:03:37,040 --> 00:03:39,960 Speaker 9: technology stack and a different phase in this journey, right, 70 00:03:40,000 --> 00:03:42,040 Speaker 9: so there has been a pent up demand. So I 71 00:03:42,080 --> 00:03:44,760 Speaker 9: think right now this sort of tier two and low 72 00:03:44,960 --> 00:03:47,600 Speaker 9: enterprises and the new up and comers who are installing 73 00:03:47,600 --> 00:03:49,640 Speaker 9: this base would choose to go for the H two 74 00:03:49,680 --> 00:03:52,160 Speaker 9: hundred and Blackwell is not really for everyone. 75 00:03:52,320 --> 00:03:54,560 Speaker 3: You really need a. 76 00:03:53,840 --> 00:03:58,160 Speaker 9: Significant ROI, significant investment to implement Blackwell. 77 00:03:58,400 --> 00:04:02,520 Speaker 4: What about geographic reach here? Were you worried in any 78 00:04:02,560 --> 00:04:03,800 Speaker 4: way about the China pullback? 79 00:04:06,200 --> 00:04:07,280 Speaker 3: No, I mean there was. 80 00:04:07,480 --> 00:04:10,640 Speaker 9: This is the first time we saw the US decline sequentially. 81 00:04:11,480 --> 00:04:13,600 Speaker 9: We don't think there's a lot to read into it, 82 00:04:13,640 --> 00:04:16,840 Speaker 9: but it definitely outlines that the demand is broadening outside 83 00:04:16,839 --> 00:04:18,760 Speaker 9: of the US. When we look at rest of the 84 00:04:18,800 --> 00:04:21,440 Speaker 9: world other than US over the last few years, the 85 00:04:21,520 --> 00:04:24,560 Speaker 9: growth there has been significantly faster, and that leads to 86 00:04:24,600 --> 00:04:28,320 Speaker 9: that sort of low double digit so and billion dollars 87 00:04:28,360 --> 00:04:29,560 Speaker 9: that Jensen outlined. 88 00:04:30,520 --> 00:04:33,599 Speaker 4: Congen Shavani and has been a busy twenty four hours 89 00:04:33,600 --> 00:04:33,760 Speaker 4: for you. 90 00:04:33,800 --> 00:04:35,600 Speaker 6: We appreciate you pre meg intelligence. 91 00:04:35,640 --> 00:04:38,840 Speaker 4: Meanwhile, let's get a broader market reaction Anthony Singramany is 92 00:04:38,880 --> 00:04:41,120 Speaker 4: with US chief Market stretches that Ameral Price Financial. 93 00:04:41,279 --> 00:04:44,000 Speaker 6: Who would have thought it with all of the handwringing. 94 00:04:43,640 --> 00:04:45,240 Speaker 4: In video is so important to the S and P, 95 00:04:45,400 --> 00:04:49,040 Speaker 4: to the NASDAC of eight percent. Waiting benchmarks are higher 96 00:04:49,120 --> 00:04:50,120 Speaker 4: even though the name is down. 97 00:04:51,400 --> 00:04:53,000 Speaker 1: Yeah, you know, at the beginning of the week we 98 00:04:53,279 --> 00:04:56,320 Speaker 1: kind of said move over power. Here comes Jensen Wong, 99 00:04:57,200 --> 00:04:59,720 Speaker 1: and you're really kind of seeing the markets just kind 100 00:04:59,720 --> 00:05:03,680 Speaker 1: of not really react in videos earnings last night. And 101 00:05:03,720 --> 00:05:07,840 Speaker 1: I think it's because earnings were positive. As Kanja mentioned, 102 00:05:07,960 --> 00:05:10,159 Speaker 1: you know, the wow factor is starting to come down 103 00:05:10,200 --> 00:05:11,920 Speaker 1: because the hurdle rates are getting higher. 104 00:05:12,040 --> 00:05:13,600 Speaker 2: It's getting harder to achieve that. 105 00:05:14,080 --> 00:05:18,840 Speaker 1: But overall, the delivery of profits and outlooks last night 106 00:05:18,880 --> 00:05:21,640 Speaker 1: from in video, we're solid, and so I think the 107 00:05:21,680 --> 00:05:24,880 Speaker 1: market is starting to kind of look forward and say, hey, 108 00:05:24,920 --> 00:05:28,320 Speaker 1: everything's okay with big tech. We're going to move over 109 00:05:28,440 --> 00:05:31,320 Speaker 1: the next couple of quarters. Macro is obviously going to 110 00:05:31,360 --> 00:05:34,159 Speaker 1: be a concern coming here over the next few weeks 111 00:05:34,200 --> 00:05:36,480 Speaker 1: and as we get rate cuts from the FED later 112 00:05:36,560 --> 00:05:39,840 Speaker 1: next month. But I think the story in big tech 113 00:05:40,360 --> 00:05:44,360 Speaker 1: is less homogeneous trading a little bit more focus on 114 00:05:44,800 --> 00:05:48,120 Speaker 1: you know where's the payoff or AI what's the supply 115 00:05:48,240 --> 00:05:51,320 Speaker 1: and demand build for companies like in video moving forward? 116 00:05:51,680 --> 00:05:54,800 Speaker 1: And I think it will likely provide opportunities when when 117 00:05:54,839 --> 00:05:58,400 Speaker 1: we get some of these pullbacks for investors to reassess 118 00:05:58,440 --> 00:06:01,480 Speaker 1: and maybe look at stocks that got away from them 119 00:06:01,520 --> 00:06:02,400 Speaker 1: earlier this year. 120 00:06:02,920 --> 00:06:04,920 Speaker 6: Would you say that in video? I don't want to 121 00:06:04,920 --> 00:06:06,120 Speaker 6: go into individual names. 122 00:06:05,920 --> 00:06:10,760 Speaker 4: But would you say these sorts of valuations when today Apple, Microsoft, Amazon, Meta, Google, 123 00:06:10,839 --> 00:06:13,800 Speaker 4: Tesla are all the top performers in terms of points 124 00:06:13,800 --> 00:06:16,159 Speaker 4: in the S and P five hundred, should you be 125 00:06:16,320 --> 00:06:17,840 Speaker 4: wrapping up more in technology? 126 00:06:17,880 --> 00:06:20,560 Speaker 6: With valuations at these levels, you. 127 00:06:21,040 --> 00:06:23,960 Speaker 1: At the top, as you said, like equal weights in 128 00:06:24,000 --> 00:06:27,600 Speaker 1: these companies, and in technology just holding an equal weight 129 00:06:27,800 --> 00:06:30,560 Speaker 1: is thirty forty percent of the S and P five hundred. 130 00:06:30,640 --> 00:06:32,400 Speaker 1: So I don't think you need to get over your 131 00:06:32,440 --> 00:06:37,720 Speaker 1: skis around you extending psitioning in these areas. But when 132 00:06:37,800 --> 00:06:42,800 Speaker 1: we do see pullbacks in these big tech leaders, this 133 00:06:42,880 --> 00:06:45,119 Speaker 1: is the time to start looking at them, at least 134 00:06:45,520 --> 00:06:48,760 Speaker 1: if you've underweighted the area. Our view is that there 135 00:06:48,839 --> 00:06:52,080 Speaker 1: is a broader group of stocks that are more attractive. 136 00:06:52,600 --> 00:06:56,600 Speaker 1: They're particularly more attractive as earnings growth expectations are moving 137 00:06:56,680 --> 00:07:00,000 Speaker 1: higher for outside for areas outside of the big tech. 138 00:07:00,200 --> 00:07:03,120 Speaker 1: The economy seems to be on firm footing. The GDP 139 00:07:03,200 --> 00:07:06,400 Speaker 1: grew by three percent in the second quarter, and the 140 00:07:06,440 --> 00:07:10,200 Speaker 1: Fed is likely to start their you know, their moves 141 00:07:10,240 --> 00:07:12,360 Speaker 1: to lower rates over the next few months and a 142 00:07:12,400 --> 00:07:15,760 Speaker 1: few quarters. So the outlook for the rest of the 143 00:07:15,800 --> 00:07:19,000 Speaker 1: four hundred and ninety three stocks that aren't the Magnificent 144 00:07:19,120 --> 00:07:22,040 Speaker 1: seven are starting to look more attractive. And that's what 145 00:07:22,040 --> 00:07:25,960 Speaker 1: we're seeing this month. Consumer staples, healthcare utilities. They're all 146 00:07:26,000 --> 00:07:28,800 Speaker 1: at the top of the charts for August, and that 147 00:07:28,920 --> 00:07:31,800 Speaker 1: might be because September is a pretty poor month for 148 00:07:31,840 --> 00:07:32,320 Speaker 1: the market. 149 00:07:33,560 --> 00:07:36,360 Speaker 5: And see that's a pretty sweet Bloomberg terminal chot over 150 00:07:36,360 --> 00:07:40,000 Speaker 5: your left shoulder. What is that that's in video quarterly revenues. 151 00:07:40,840 --> 00:07:42,000 Speaker 2: That's right, that's right. 152 00:07:42,040 --> 00:07:44,040 Speaker 1: And as the chart if you can see it in 153 00:07:44,080 --> 00:07:47,679 Speaker 1: the back, it shows the actuals and the estimates starting 154 00:07:47,720 --> 00:07:48,400 Speaker 1: to get closer. 155 00:07:48,480 --> 00:07:50,320 Speaker 2: And I think that's why you're seeing A. 156 00:07:51,840 --> 00:07:55,160 Speaker 1: Get more trouble start moving higher, even though they had 157 00:07:55,160 --> 00:07:56,360 Speaker 1: great results last night. 158 00:07:56,760 --> 00:07:59,040 Speaker 5: So bear with me. I have a chot of my own. 159 00:07:59,160 --> 00:08:01,680 Speaker 5: Let's bring it up. This is the beat in the 160 00:08:01,760 --> 00:08:05,920 Speaker 5: quarter relative to expectations, and I think the point is 161 00:08:06,600 --> 00:08:08,680 Speaker 5: that it was a It was a four percent beat 162 00:08:08,720 --> 00:08:11,400 Speaker 5: against consensus, right, four percent upside surprise. 163 00:08:13,120 --> 00:08:14,840 Speaker 8: Have you ever experienced a quarter like. 164 00:08:14,800 --> 00:08:18,440 Speaker 5: This where everyone has just lost their absolute minds over 165 00:08:18,480 --> 00:08:21,320 Speaker 5: a single name in a week where we had Central 166 00:08:21,360 --> 00:08:24,440 Speaker 5: Bank speakers left, right and center and more economic data 167 00:08:24,440 --> 00:08:27,360 Speaker 5: that we can fit into a one hour program. 168 00:08:27,960 --> 00:08:30,320 Speaker 1: Yeah, no, I mean I think the last and you 169 00:08:30,320 --> 00:08:32,720 Speaker 1: started at volatility spike in early August. 170 00:08:32,760 --> 00:08:35,800 Speaker 2: Some of that was the japan Yen Carrie trade. 171 00:08:35,960 --> 00:08:40,200 Speaker 1: But I do think expectations are really high in these 172 00:08:40,320 --> 00:08:43,840 Speaker 1: big tech, magnificent names, and so not only do they 173 00:08:43,880 --> 00:08:47,360 Speaker 1: have to surpass and kind of meet the perfection standards 174 00:08:47,360 --> 00:08:49,800 Speaker 1: that investors put on it, but they actually need to 175 00:08:49,800 --> 00:08:53,200 Speaker 1: surpass them by even more. That's getting harder and so 176 00:08:53,400 --> 00:08:55,800 Speaker 1: as as my earlier comments said, I think you're going 177 00:08:55,880 --> 00:08:59,439 Speaker 1: to see more less homogeneous trading between some of these 178 00:08:59,480 --> 00:09:02,240 Speaker 1: big tech leaders, and it's really going to come down 179 00:09:02,240 --> 00:09:06,600 Speaker 1: to fundamentals and capital spending and what's the revenue outlook, how. 180 00:09:06,559 --> 00:09:07,600 Speaker 2: Much are you beating? 181 00:09:07,960 --> 00:09:11,080 Speaker 1: Those things will play a much more dominant role in 182 00:09:11,120 --> 00:09:14,160 Speaker 1: moving share prices around. But at the same at the 183 00:09:14,240 --> 00:09:16,920 Speaker 1: same you know, the same brath. You have a lot 184 00:09:16,960 --> 00:09:19,560 Speaker 1: of stocks that have not kept pace with these big 185 00:09:19,600 --> 00:09:23,960 Speaker 1: tech companies that remain attractive in an environment where we're growing. 186 00:09:24,040 --> 00:09:26,760 Speaker 1: And so if the FED is cutting interest rates and 187 00:09:26,800 --> 00:09:30,200 Speaker 1: they can kind of engineer that soft landing, there's a 188 00:09:30,240 --> 00:09:33,600 Speaker 1: lot of sectors of the economy that are more attractive today. 189 00:09:34,400 --> 00:09:38,160 Speaker 5: So let's finish here in aggregate Nvidia and everything else. 190 00:09:37,960 --> 00:09:38,880 Speaker 8: That you've outlined. 191 00:09:39,600 --> 00:09:44,120 Speaker 5: Do you believe that this cycle, the investment cycle around 192 00:09:44,160 --> 00:09:46,720 Speaker 5: AI is intact and it continues. 193 00:09:47,920 --> 00:09:50,920 Speaker 1: Yeah, I think you know, and from your interview with 194 00:09:51,000 --> 00:09:54,760 Speaker 1: Jensen Wong, I think it's very clear the AI infrastructure 195 00:09:54,800 --> 00:09:57,320 Speaker 1: build and the architecture around that is in the very 196 00:09:57,360 --> 00:10:02,800 Speaker 1: early innings. Some of these companies like Microsoft, Amazon, Meta Alphabet, 197 00:10:03,080 --> 00:10:05,959 Speaker 1: they spent almost sixty billion dollars in the prior quarter 198 00:10:06,120 --> 00:10:09,280 Speaker 1: on AI investment. They said they were going to continue 199 00:10:09,280 --> 00:10:12,560 Speaker 1: that over the next several quarters. And so as these 200 00:10:12,679 --> 00:10:17,120 Speaker 1: companies and as sovereign AI that Nvidia mentioned last night, 201 00:10:17,160 --> 00:10:21,000 Speaker 1: as these countries start to build that infrastructure, there is 202 00:10:21,080 --> 00:10:24,679 Speaker 1: a lot of opportunities still left in AI. However, like 203 00:10:24,840 --> 00:10:27,760 Speaker 1: the like the tech boom in their early late nineties 204 00:10:27,760 --> 00:10:31,360 Speaker 1: early two thousand we go through periods where expectations get 205 00:10:31,400 --> 00:10:34,560 Speaker 1: really high, they need to reset, and then maybe stocks 206 00:10:34,600 --> 00:10:36,720 Speaker 1: can move higher from there. And I think we're starting 207 00:10:36,760 --> 00:10:39,800 Speaker 1: to see that now with big tech and the AI theme. 208 00:10:40,920 --> 00:10:44,599 Speaker 5: Ansney sagem Bene, chief market strategist in Americaprise Financially you 209 00:10:44,640 --> 00:10:48,560 Speaker 5: believe thank you now, coming out of a conversation with 210 00:10:48,679 --> 00:10:52,760 Speaker 5: Max Levchin, CEO of a firm following yesterday's pretty strong 211 00:10:52,760 --> 00:10:54,839 Speaker 5: earnings report, car you're looking at another name. 212 00:10:55,280 --> 00:10:58,880 Speaker 4: I AM firms up, CrowdStrike up as well, more than 213 00:10:58,920 --> 00:11:02,199 Speaker 4: five percent. This isn't reporting second quarter sales that basically 214 00:11:02,240 --> 00:11:04,400 Speaker 4: top tenas estimates. Remember we were all worrying about the 215 00:11:04,440 --> 00:11:07,800 Speaker 4: global IT outage back in July, but it doesn't seem 216 00:11:07,880 --> 00:11:11,960 Speaker 4: to have had an immediate, as bad a result impact. 217 00:11:12,400 --> 00:11:13,120 Speaker 6: We're currently higher. 218 00:11:13,200 --> 00:11:28,320 Speaker 5: Sublombo Technology, a firm delivering better than expected earning, sending 219 00:11:28,360 --> 00:11:31,920 Speaker 5: shares upwards. The company's fourth quarter revenue and first quarter 220 00:11:32,280 --> 00:11:36,560 Speaker 5: revenue forecast both coming in ahead of estimate, CEO Max 221 00:11:36,640 --> 00:11:41,160 Speaker 5: Levchin saying the company had quote a killer quarter. 222 00:11:42,120 --> 00:11:43,720 Speaker 8: Max joins us now here in San Francisco. 223 00:11:43,800 --> 00:11:46,680 Speaker 5: I spent enough time with you to know that when 224 00:11:46,720 --> 00:11:50,280 Speaker 5: you say something like that, you mean it. I wouldn't 225 00:11:50,280 --> 00:11:53,800 Speaker 5: say that you're prone to superlatives like that. Why why 226 00:11:53,840 --> 00:11:54,600 Speaker 5: a killer quarter? 227 00:11:56,200 --> 00:11:57,360 Speaker 3: Numbers speak for themselves. 228 00:11:58,320 --> 00:11:59,319 Speaker 8: I'll go beyond that. 229 00:11:59,360 --> 00:12:01,640 Speaker 5: Come on, tell me the story of what's happening behind 230 00:12:01,640 --> 00:12:03,280 Speaker 5: your platform and your user base. 231 00:12:04,320 --> 00:12:05,800 Speaker 3: I think there's a real momentum. 232 00:12:05,920 --> 00:12:09,840 Speaker 11: You can tell by looking at our metrics and the 233 00:12:10,040 --> 00:12:13,040 Speaker 11: qualitative measures that we take, and just the fact that 234 00:12:13,200 --> 00:12:16,160 Speaker 11: we've outperformed the credit card industry, which is our direct 235 00:12:16,160 --> 00:12:19,360 Speaker 11: competitor in terms of managing credit, and just the sheer 236 00:12:19,440 --> 00:12:22,320 Speaker 11: number of launchers and merchant signings. Every metric that I 237 00:12:22,320 --> 00:12:25,040 Speaker 11: could cast my eye on, say, wow, that is a 238 00:12:25,080 --> 00:12:25,840 Speaker 11: really good quarter. 239 00:12:26,040 --> 00:12:27,600 Speaker 3: So you know, sometimes we got to take a bath. 240 00:12:29,320 --> 00:12:32,440 Speaker 5: Let's say the buy now pay Lata space is let's 241 00:12:32,440 --> 00:12:35,400 Speaker 5: say more competitive since last year on the program. Maybe 242 00:12:35,400 --> 00:12:37,640 Speaker 5: in that time. Caroline and I spoke with the Klan, 243 00:12:37,679 --> 00:12:41,560 Speaker 5: the CEO, for example. They seem very optimistic, particularly about 244 00:12:41,600 --> 00:12:45,880 Speaker 5: the United States. Yet you continue to grow. I don't 245 00:12:45,920 --> 00:12:48,560 Speaker 5: have the data for market share, but could you just 246 00:12:48,640 --> 00:12:51,280 Speaker 5: contextualize your performance in that sense? 247 00:12:51,840 --> 00:12:54,640 Speaker 11: Well, I think we are outpacing them reasonably well in 248 00:12:54,720 --> 00:12:56,600 Speaker 11: terms of our growth relative to there is at least 249 00:12:56,600 --> 00:13:00,600 Speaker 11: according to the stated numbers, not that I am competitive, 250 00:13:01,040 --> 00:13:06,079 Speaker 11: but I'm very competitive, let's be honest. But the reality 251 00:13:06,120 --> 00:13:08,160 Speaker 11: is it's a giant market and all of us together 252 00:13:08,200 --> 00:13:10,080 Speaker 11: at up to less than ten percent of e commerce, 253 00:13:10,280 --> 00:13:12,520 Speaker 11: and all of us are now looking at offline and 254 00:13:12,600 --> 00:13:17,000 Speaker 11: so just the real share taking that's taking place is 255 00:13:17,000 --> 00:13:20,600 Speaker 11: happening against cash, against credit cards, against debit cards, all 256 00:13:20,640 --> 00:13:23,280 Speaker 11: the other payment types, and so there's just an incredible 257 00:13:23,320 --> 00:13:25,520 Speaker 11: amount of road available to all of us. 258 00:13:25,520 --> 00:13:27,480 Speaker 3: And a firm in particular, what. 259 00:13:27,440 --> 00:13:31,200 Speaker 4: Does that mean in terms of the macro context? Then, Max, 260 00:13:31,400 --> 00:13:34,640 Speaker 4: how confident are you of the US consumer the global 261 00:13:34,679 --> 00:13:35,600 Speaker 4: consumer right now? 262 00:13:37,120 --> 00:13:39,240 Speaker 11: Well, we're about to launch in the UK, so we'll 263 00:13:39,240 --> 00:13:41,920 Speaker 11: find out exactly how confident I should be about the 264 00:13:41,960 --> 00:13:45,360 Speaker 11: UK consumer. But the US consumer again, look at our 265 00:13:45,559 --> 00:13:49,920 Speaker 11: investor supplement. Credit card companies have built and built and 266 00:13:49,960 --> 00:13:53,440 Speaker 11: built up their delinquencies, and ours remained very firmly in control. 267 00:13:53,880 --> 00:13:57,520 Speaker 11: Our consumer is borrowing and shopping and paying back, which 268 00:13:57,600 --> 00:13:59,120 Speaker 11: is really important for our credit business. 269 00:13:59,640 --> 00:14:02,880 Speaker 3: But so far, so good. We do not see a 270 00:14:02,920 --> 00:14:03,720 Speaker 3: major slowdown. 271 00:14:03,760 --> 00:14:06,760 Speaker 11: We do not see a significant pullback and demand there's 272 00:14:06,760 --> 00:14:09,839 Speaker 11: always new industries. A quarter or two ago, I was 273 00:14:09,960 --> 00:14:12,680 Speaker 11: lamenting the loss of interest and electronics. It came back 274 00:14:12,800 --> 00:14:16,840 Speaker 11: roaring through the last quarter, travels a little bit softer. 275 00:14:16,960 --> 00:14:19,400 Speaker 3: I think people got their COVID post COVID fix. 276 00:14:19,800 --> 00:14:25,880 Speaker 11: But all in all, consumer is effectively shopping and buying 277 00:14:25,920 --> 00:14:28,280 Speaker 11: and paying back and I don't see problems. 278 00:14:28,720 --> 00:14:31,240 Speaker 4: Meanwhile, you're taking a bow and the market in particular 279 00:14:31,840 --> 00:14:35,840 Speaker 4: likes the focus on profitability. Now I hate to bring 280 00:14:35,840 --> 00:14:38,520 Speaker 4: them up again, but Karner actually did post a profit, 281 00:14:38,800 --> 00:14:40,600 Speaker 4: even though they're still a private company that eying a 282 00:14:40,600 --> 00:14:44,280 Speaker 4: twenty billion dollar valuation and they're cunning costs by leaning 283 00:14:44,360 --> 00:14:46,280 Speaker 4: into AI. Is that something that you look at, Max, 284 00:14:46,360 --> 00:14:47,920 Speaker 4: something that you feel you have to compete into. 285 00:14:50,040 --> 00:14:53,000 Speaker 11: Well, good news is that we've been in the AI 286 00:14:54,000 --> 00:14:58,160 Speaker 11: business since inception. So one percent of our loans are 287 00:14:58,280 --> 00:15:02,160 Speaker 11: underwritten individually. Every single time I'm entirely buying machines, and 288 00:15:02,200 --> 00:15:04,920 Speaker 11: so we've been on the machine learning and AI training 289 00:15:05,040 --> 00:15:05,880 Speaker 11: since base Eero. 290 00:15:06,040 --> 00:15:07,200 Speaker 3: And we don't think of. 291 00:15:07,200 --> 00:15:09,920 Speaker 11: It as a way to replace humans or to get 292 00:15:10,000 --> 00:15:11,840 Speaker 11: rid of humans. We think of it as a great 293 00:15:11,880 --> 00:15:16,000 Speaker 11: tool for increasing productivity, to give us an edge in 294 00:15:16,160 --> 00:15:19,160 Speaker 11: underwriting customer service, et cetera. 295 00:15:19,280 --> 00:15:21,120 Speaker 3: And so yes, we're very, very active in AI. 296 00:15:21,160 --> 00:15:23,760 Speaker 11: We have lots of really fun things happening, both visible 297 00:15:23,840 --> 00:15:27,280 Speaker 11: and not to the investor eye. But it's a huge 298 00:15:27,280 --> 00:15:30,720 Speaker 11: part of what we do in terms of profitability. You know, 299 00:15:31,200 --> 00:15:32,600 Speaker 11: I said it last night on the Earning Skull, and 300 00:15:32,600 --> 00:15:34,640 Speaker 11: I just want to make sure I repeated this was 301 00:15:34,720 --> 00:15:38,120 Speaker 11: not a contortionist thing we just did when we said, hey, 302 00:15:38,480 --> 00:15:40,360 Speaker 11: profitability is on the horizon. 303 00:15:40,720 --> 00:15:42,560 Speaker 3: It is very much part of the plan. It's always 304 00:15:42,560 --> 00:15:43,280 Speaker 3: been part of the plan. 305 00:15:43,760 --> 00:15:46,040 Speaker 11: It's just now close enough where I can say, here's 306 00:15:46,040 --> 00:15:48,120 Speaker 11: a date with history. We're going to get Gap profitable 307 00:15:48,160 --> 00:15:49,640 Speaker 11: and move right past it and do more. 308 00:15:50,640 --> 00:15:53,400 Speaker 5: Max and Carol also bear with me that I am 309 00:15:53,560 --> 00:15:55,840 Speaker 5: a firm customer in the sense that you know, I 310 00:15:55,960 --> 00:15:58,960 Speaker 5: used the firm to finance a specific thing for what 311 00:15:59,000 --> 00:16:01,440 Speaker 5: it's worth. It was the Peloton tread. But the reason 312 00:16:01,480 --> 00:16:03,640 Speaker 5: I did it is actually emphsis some point of sale. 313 00:16:03,880 --> 00:16:05,840 Speaker 5: So when you go through the audience issubmitted, if you 314 00:16:05,840 --> 00:16:08,640 Speaker 5: go and try buy something from Peloton, it's kind of 315 00:16:08,680 --> 00:16:10,880 Speaker 5: a weird transaction, but you're presented with the firm as 316 00:16:10,920 --> 00:16:15,240 Speaker 5: an option almost straight away. Do you negotiate that aggressively 317 00:16:15,840 --> 00:16:20,640 Speaker 5: for those kind of bigger ticket items, I'm. 318 00:16:20,520 --> 00:16:24,840 Speaker 11: Not sure individual deals are worth commenting on. But every 319 00:16:24,960 --> 00:16:27,000 Speaker 11: deal where we are presented at the point of sale, 320 00:16:27,520 --> 00:16:30,320 Speaker 11: and every deal where you see it up funnel as 321 00:16:30,440 --> 00:16:32,760 Speaker 11: what might call it before you even get into the checkouts, 322 00:16:33,320 --> 00:16:36,840 Speaker 11: are absolutely directly integrated. So we go to the merchant, 323 00:16:37,000 --> 00:16:38,920 Speaker 11: we spend a lot of time with them making sure 324 00:16:38,960 --> 00:16:42,359 Speaker 11: that we are as helpful as possible to their ability 325 00:16:42,520 --> 00:16:46,280 Speaker 11: to sell, be it a Pelton tread or a mattress or. 326 00:16:46,200 --> 00:16:48,960 Speaker 3: Anything in between. And that is what gives us a 327 00:16:49,040 --> 00:16:49,640 Speaker 3: huge advantage. 328 00:16:49,680 --> 00:16:52,480 Speaker 11: The consumer has the confidence and the clarity of what 329 00:16:52,520 --> 00:16:54,480 Speaker 11: it might cost them to borrow money to buy something. 330 00:16:54,760 --> 00:16:55,000 Speaker 8: Max. 331 00:16:55,360 --> 00:16:57,080 Speaker 5: While you're here, could I please ask you, as a 332 00:16:57,120 --> 00:17:00,240 Speaker 5: story out from Blomberg Law about a firm face sing 333 00:17:00,240 --> 00:17:04,840 Speaker 5: a class action suit after the Evolved bank breach situation, 334 00:17:06,480 --> 00:17:07,439 Speaker 5: comment on that please. 335 00:17:07,920 --> 00:17:11,480 Speaker 11: Probably a very bad idea to comment and ongoing or 336 00:17:11,560 --> 00:17:13,880 Speaker 11: potential future litigation, so I'm not sure I have anything 337 00:17:13,920 --> 00:17:16,480 Speaker 11: to say on that. You know, I said it the 338 00:17:16,600 --> 00:17:20,960 Speaker 11: day of Evolved news, which is certainly unfortunate that the 339 00:17:20,960 --> 00:17:23,320 Speaker 11: firm card numbers were all safe. We did not need 340 00:17:23,359 --> 00:17:26,560 Speaker 11: to rotate them and give people new cards. That is 341 00:17:26,600 --> 00:17:29,520 Speaker 11: now confirmed no card numbers have been leaked and our 342 00:17:29,560 --> 00:17:31,639 Speaker 11: consumers are safe. If you have your firm card, please 343 00:17:31,640 --> 00:17:32,520 Speaker 11: continue using it. 344 00:17:32,520 --> 00:17:33,240 Speaker 3: It works just fine. 345 00:17:33,359 --> 00:17:33,679 Speaker 8: Thank you. 346 00:17:34,320 --> 00:17:36,119 Speaker 4: Thanks Love Chin, It's always great to have you on 347 00:17:36,160 --> 00:17:38,879 Speaker 4: the show. We appreciate it. It's taking about the CEO 348 00:17:39,000 --> 00:17:39,800 Speaker 4: of a firm today. 349 00:17:48,320 --> 00:17:52,640 Speaker 5: Telegram ceo Pavel durov was charged in France for complicity 350 00:17:53,040 --> 00:17:56,360 Speaker 5: in the spread of sexual images of children and other crimes. 351 00:17:56,400 --> 00:17:58,040 Speaker 8: It's a rare example of. 352 00:17:57,960 --> 00:18:00,879 Speaker 5: A tech leader being held liable for the way their 353 00:18:01,040 --> 00:18:03,359 Speaker 5: platform is used. I want to get right to the 354 00:18:03,400 --> 00:18:06,679 Speaker 5: details with Bloomberg's Allan Katz or Paris bureau chief, and 355 00:18:06,720 --> 00:18:09,760 Speaker 5: I think fill in the details. My understanding is Duroff 356 00:18:09,880 --> 00:18:12,280 Speaker 5: is out on a significant bail and there is a 357 00:18:12,320 --> 00:18:13,280 Speaker 5: process to come. 358 00:18:16,080 --> 00:18:19,440 Speaker 12: So he is out of the sort of a holding 359 00:18:19,440 --> 00:18:21,600 Speaker 12: cells the way they do it in France. From that 360 00:18:21,640 --> 00:18:24,800 Speaker 12: four day interrogation that he had before being presented to 361 00:18:24,840 --> 00:18:27,760 Speaker 12: the judge, he had to post a five million euro 362 00:18:28,000 --> 00:18:30,480 Speaker 12: bond for that, so that's about five and a half 363 00:18:30,520 --> 00:18:32,960 Speaker 12: million dollars, so it's a lot of money. That said, 364 00:18:33,640 --> 00:18:37,760 Speaker 12: he's according to Bloomberg's you know, wealth ranking, he's quite 365 00:18:37,760 --> 00:18:39,680 Speaker 12: a wealthy fellow, and so he could certainly afford it. 366 00:18:40,560 --> 00:18:43,800 Speaker 12: And from here on out, at least according to the 367 00:18:43,800 --> 00:18:46,600 Speaker 12: initial ruling from what's called a jugually liberte, he has 368 00:18:46,640 --> 00:18:49,800 Speaker 12: to check in twice a week with authorities to make 369 00:18:49,840 --> 00:18:51,480 Speaker 12: sure that he's still in France and he's not allowed 370 00:18:51,480 --> 00:18:52,440 Speaker 12: to leave the country. 371 00:18:53,000 --> 00:18:53,720 Speaker 3: So that's sort of. 372 00:18:53,640 --> 00:18:56,160 Speaker 12: The process in the immediate future. And now it goes 373 00:18:56,200 --> 00:18:58,879 Speaker 12: to an investigation where the investigating magistrate will continue to 374 00:18:58,880 --> 00:19:02,440 Speaker 12: look into the case, and that could take months, could 375 00:19:02,480 --> 00:19:06,320 Speaker 12: take a year longer, Like, it's really unclear how long 376 00:19:06,600 --> 00:19:08,399 Speaker 12: the rest of this process might take beyond that. 377 00:19:09,000 --> 00:19:13,159 Speaker 4: And really the case here is that dura off Telegram, 378 00:19:13,200 --> 00:19:17,600 Speaker 4: which is CEO of basically in no way helps when 379 00:19:17,640 --> 00:19:20,600 Speaker 4: it comes to investigations. They refuse, it said, to run 380 00:19:20,680 --> 00:19:24,240 Speaker 4: legal wire taps on suspects, particularly when it comes to 381 00:19:24,680 --> 00:19:29,440 Speaker 4: organized criminals and particularly sexual exploitation of children. Is that 382 00:19:29,480 --> 00:19:31,719 Speaker 4: really wants at heart here, the fact that he doesn't 383 00:19:31,760 --> 00:19:33,920 Speaker 4: want to take any movement, any action as a leader 384 00:19:33,960 --> 00:19:36,960 Speaker 4: of a social media platform. 385 00:19:37,359 --> 00:19:41,800 Speaker 12: Well, yes, The action though that you're talking about is 386 00:19:41,880 --> 00:19:46,600 Speaker 12: he doesn't he deliberately, according to French officials, he deliberately 387 00:19:46,640 --> 00:19:50,160 Speaker 12: did not respond to or applied to what they call 388 00:19:50,320 --> 00:19:54,960 Speaker 12: legitimate requests for informational for help in other investigations that 389 00:19:55,040 --> 00:19:57,560 Speaker 12: were running in criminal activities that they saw on the 390 00:19:57,640 --> 00:20:01,320 Speaker 12: Telegram network. And that's different than the way that most 391 00:20:01,440 --> 00:20:06,320 Speaker 12: other messaging services operate, and that's really why they issued 392 00:20:06,320 --> 00:20:07,879 Speaker 12: the arrest warrant for him in the first place. And 393 00:20:07,920 --> 00:20:10,760 Speaker 12: the prosecutor made a point of that in the statement 394 00:20:10,840 --> 00:20:14,159 Speaker 12: last night, saying that was really what was particular about 395 00:20:14,240 --> 00:20:18,199 Speaker 12: Telegram as a platform, and not just in France, but 396 00:20:18,560 --> 00:20:21,360 Speaker 12: she specifically mentioned Belgium as well as having the same 397 00:20:21,440 --> 00:20:23,960 Speaker 12: issues with Telegram. 398 00:20:23,280 --> 00:20:27,080 Speaker 4: A near complete lack of response, as pass prosecutor put it, 399 00:20:27,119 --> 00:20:36,800 Speaker 4: we appreciate it. Alan Katz, thank you, Welcome back to 400 00:20:36,800 --> 00:20:39,400 Speaker 4: Blue meg Technology. And Caroline Hide in New York and. 401 00:20:39,359 --> 00:20:41,560 Speaker 8: I met Ludlow in San Francisco, and I. 402 00:20:41,480 --> 00:20:43,280 Speaker 4: Just want to point out what is happening on the 403 00:20:43,280 --> 00:20:46,919 Speaker 4: markets today because we've had so much anxiety around this 404 00:20:47,040 --> 00:20:50,199 Speaker 4: one name, all around Nvidia, the fact that it was 405 00:20:50,240 --> 00:20:52,240 Speaker 4: the most crucial that it had ever been to the market. 406 00:20:52,320 --> 00:20:54,879 Speaker 4: It's eight percent waiting in the NASDAC, it's six percent 407 00:20:54,920 --> 00:20:57,520 Speaker 4: waiting in the SMP would mean that the direction of 408 00:20:57,560 --> 00:21:00,639 Speaker 4: travel after earnings would dictate that for the benchmark, not 409 00:21:00,880 --> 00:21:03,159 Speaker 4: so we're currently up one point one percent, but then 410 00:21:03,200 --> 00:21:06,439 Speaker 4: has that one hundred despite it's fourteen percent waiting in 411 00:21:06,480 --> 00:21:09,119 Speaker 4: the socks. We're up one point four percent and it 412 00:21:09,160 --> 00:21:11,480 Speaker 4: is lower by three point six percent. The reason is lower, 413 00:21:11,560 --> 00:21:14,560 Speaker 4: of course, d is what you poured over yesterday was 414 00:21:14,560 --> 00:21:17,199 Speaker 4: the fact that, yes, it's still beat in its quarter 415 00:21:17,280 --> 00:21:19,720 Speaker 4: that was just announced, and the fact that its forecast 416 00:21:19,760 --> 00:21:22,240 Speaker 4: looked pretty decent. But it was some of the issues 417 00:21:22,240 --> 00:21:25,159 Speaker 4: that ramp up in Blackwell in particular that caused a 418 00:21:25,200 --> 00:21:26,480 Speaker 4: little bit of uncertainty. 419 00:21:26,520 --> 00:21:28,120 Speaker 6: And you spoke to the CEO just about that. 420 00:21:28,920 --> 00:21:29,280 Speaker 3: I did. 421 00:21:29,359 --> 00:21:32,480 Speaker 5: I did speak with Nvidia CEO Jensen Wang following what 422 00:21:32,600 --> 00:21:34,919 Speaker 5: was kind of seen as a disappointing earnings report, so 423 00:21:35,040 --> 00:21:37,639 Speaker 5: bizarre to say that out loud. He laid out his 424 00:21:37,840 --> 00:21:41,880 Speaker 5: and the company's expectations for next year surrounding the production 425 00:21:42,160 --> 00:21:43,080 Speaker 5: of Blackwell chips. 426 00:21:43,119 --> 00:21:43,560 Speaker 8: Listen to this. 427 00:21:46,200 --> 00:21:49,400 Speaker 7: We made a mass change to improve the yield. Functionality 428 00:21:49,440 --> 00:21:52,639 Speaker 7: of Blackwell is wonderful. We're sampling Blackwell all over the 429 00:21:52,680 --> 00:21:58,919 Speaker 7: world today. We show people giving tours to people of 430 00:21:59,000 --> 00:22:02,280 Speaker 7: the Blackwall systems we have up and running. You could 431 00:22:02,359 --> 00:22:06,520 Speaker 7: find pictures of Blackwell systems all over the web. We 432 00:22:06,600 --> 00:22:11,960 Speaker 7: have started volume production volume. Production will ship in Q four. 433 00:22:12,520 --> 00:22:15,879 Speaker 7: Q four, we will have billions of dollars. 434 00:22:15,440 --> 00:22:18,080 Speaker 2: Of Blackwell revenues and. 435 00:22:19,480 --> 00:22:22,320 Speaker 3: We will ramp from there. We will ramp from there. 436 00:22:22,800 --> 00:22:28,080 Speaker 7: The demand for Blackwell far exceeds its supply, of course 437 00:22:28,160 --> 00:22:31,919 Speaker 7: in the beginning, because the demand is so great. But 438 00:22:32,200 --> 00:22:34,880 Speaker 7: we're going to have lots and lots of supply and 439 00:22:35,240 --> 00:22:38,359 Speaker 7: we will be able to ramp. Starting in Q four 440 00:22:39,080 --> 00:22:41,840 Speaker 7: we have billions of dollars of revenues, and we will 441 00:22:41,880 --> 00:22:43,960 Speaker 7: ramp from there into Q one, into Q two and 442 00:22:44,000 --> 00:22:44,680 Speaker 7: two next year. 443 00:22:45,000 --> 00:22:46,520 Speaker 10: We're going to have a great next year as well. 444 00:22:47,680 --> 00:22:50,920 Speaker 5: Jensen, what is the demand for accelerated computing beyond the 445 00:22:51,000 --> 00:22:52,760 Speaker 5: hyperscalers and meta. 446 00:22:54,359 --> 00:22:59,119 Speaker 7: Hyperscalers represent about forty five percent of our total data 447 00:22:59,160 --> 00:23:04,520 Speaker 7: center business. We're relatively diversified today. We have hyperscalers, we 448 00:23:04,600 --> 00:23:10,879 Speaker 7: have Internet service providers, we have sovereign ais, we have 449 00:23:12,200 --> 00:23:18,840 Speaker 7: industries enterprises, so it's fairly fairly diversified a site outside 450 00:23:18,840 --> 00:23:21,000 Speaker 7: of hyperscalers. 451 00:23:21,600 --> 00:23:22,760 Speaker 3: The other fifty five percent. 452 00:23:23,720 --> 00:23:28,320 Speaker 7: Now, the application use across all of that, all of 453 00:23:28,359 --> 00:23:34,199 Speaker 7: that data center starts with accelerated computing. Accelerated computing does everything, 454 00:23:34,240 --> 00:23:39,000 Speaker 7: of course, from Well the models the things that we 455 00:23:39,040 --> 00:23:42,840 Speaker 7: know about, which is generative AI, and that gets most 456 00:23:42,880 --> 00:23:45,800 Speaker 7: of the attention. But at the core we also do 457 00:23:46,760 --> 00:23:53,239 Speaker 7: database processing, pre and post processing of data before you 458 00:23:53,840 --> 00:23:59,679 Speaker 7: use it for generative AI, trans coding, scientific simulations, computer 459 00:23:59,720 --> 00:24:03,200 Speaker 7: graph of course, image processing of course, and so there's 460 00:24:03,520 --> 00:24:08,080 Speaker 7: tons of applications that people use are accelerated computing for, 461 00:24:08,840 --> 00:24:10,920 Speaker 7: and one of them is generative AI. 462 00:24:13,600 --> 00:24:16,239 Speaker 5: That was in Vidia c Jensen one speaking mate with 463 00:24:16,320 --> 00:24:19,880 Speaker 5: me last night, Cara, and yeah, I mean body language, 464 00:24:19,920 --> 00:24:20,600 Speaker 5: what he's wearing. 465 00:24:20,640 --> 00:24:21,760 Speaker 8: There's a lot to talk about. 466 00:24:22,440 --> 00:24:25,359 Speaker 4: No lever ed no lever who wore a vomber jacket. 467 00:24:25,400 --> 00:24:27,840 Speaker 4: But look, there is a lot of deep diving on 468 00:24:27,880 --> 00:24:30,359 Speaker 4: the numbers in particular, and let's get some of that 469 00:24:30,400 --> 00:24:32,280 Speaker 4: reaction from our guests on Bloomberg TV. 470 00:24:33,480 --> 00:24:34,320 Speaker 10: I'm not concerned. 471 00:24:34,359 --> 00:24:37,360 Speaker 1: I think if you look at Nvidia, they still control 472 00:24:37,440 --> 00:24:40,520 Speaker 1: this market and will continue to I would say, dominate 473 00:24:40,560 --> 00:24:42,240 Speaker 1: this space over the next three to five years. 474 00:24:42,359 --> 00:24:47,360 Speaker 13: Delivering chips at this rate, at this scale is fantastic 475 00:24:47,400 --> 00:24:50,520 Speaker 13: and unprecedented. I don't think there's much of a revenue 476 00:24:50,520 --> 00:24:53,399 Speaker 13: issue here, of a growth issue here. I think a 477 00:24:53,440 --> 00:24:56,600 Speaker 13: little bit of a pushback is probably more around the 478 00:24:56,640 --> 00:24:58,720 Speaker 13: margin situation, that type. 479 00:24:58,520 --> 00:25:01,280 Speaker 5: Of growth isn't necessarily re realistic or sustainable in the 480 00:25:01,280 --> 00:25:04,640 Speaker 5: long term. Two it's not necessary the long term either. 481 00:25:04,760 --> 00:25:07,440 Speaker 14: At the end of the day, we still sense enormous 482 00:25:07,640 --> 00:25:10,560 Speaker 14: an urgent demand across the board, and that really mitigates, 483 00:25:10,600 --> 00:25:13,320 Speaker 14: in order of you, the risk of opposed in shipments 484 00:25:13,520 --> 00:25:15,720 Speaker 14: as customers wait for the next generation of chips to 485 00:25:15,720 --> 00:25:17,840 Speaker 14: be available in volumes. 486 00:25:17,880 --> 00:25:20,760 Speaker 4: Not enough, we need more reaction, I coo Yoshioka joins 487 00:25:20,800 --> 00:25:23,840 Speaker 4: us now senior portfolio manager at Wealth Enhancement Group the 488 00:25:23,880 --> 00:25:26,640 Speaker 4: market seemingly thinking it's a disappointment. 489 00:25:27,080 --> 00:25:27,720 Speaker 6: Did you think it was. 490 00:25:27,680 --> 00:25:32,320 Speaker 15: A disappointment, Hi, Kroly, You know I was not disappointed 491 00:25:32,359 --> 00:25:33,800 Speaker 15: with the actual numbers here. 492 00:25:34,119 --> 00:25:37,000 Speaker 16: I think, you know, expectations were. 493 00:25:36,760 --> 00:25:41,119 Speaker 15: Very high going into this particular print, and you know, 494 00:25:41,240 --> 00:25:45,400 Speaker 15: especially when you're here, things like events in New York 495 00:25:45,480 --> 00:25:48,440 Speaker 15: in which you know, bars were being rented out to 496 00:25:48,480 --> 00:25:51,080 Speaker 15: see what the earnings report was going to be. 497 00:25:51,440 --> 00:25:54,320 Speaker 16: You know, it gets to do and more. I was 498 00:25:54,400 --> 00:25:57,080 Speaker 16: not in one. I was at my desk looking at 499 00:25:57,080 --> 00:25:57,640 Speaker 16: the numbers. 500 00:25:58,160 --> 00:26:02,320 Speaker 4: Joe Wisenthal, I saw open reporter was indeed out. 501 00:26:02,119 --> 00:26:03,040 Speaker 6: There in the bars. 502 00:26:03,080 --> 00:26:07,520 Speaker 4: But I'm interested, I co and even though you did 503 00:26:07,640 --> 00:26:11,640 Speaker 4: see this overall disappointment in very high expectations, was there 504 00:26:11,680 --> 00:26:14,000 Speaker 4: any cause for concern? Do you still think is ed 505 00:26:14,040 --> 00:26:16,840 Speaker 4: put to our previous guest, Anthony, that the AI trade 506 00:26:16,920 --> 00:26:17,440 Speaker 4: is intact. 507 00:26:19,400 --> 00:26:22,040 Speaker 15: The AI trade is intact. I think we have to 508 00:26:22,080 --> 00:26:24,679 Speaker 15: put this in the longer term context. You know, in 509 00:26:24,800 --> 00:26:28,439 Speaker 15: Video was generating revenues of about twenty seven billion about 510 00:26:28,440 --> 00:26:32,119 Speaker 15: two years ago. They're on pace to generate revenues of 511 00:26:32,200 --> 00:26:35,280 Speaker 15: over one hundred and twenty five billion this year. That's 512 00:26:35,400 --> 00:26:39,000 Speaker 15: just enormous. Is that growth rates sustainable? 513 00:26:39,320 --> 00:26:41,840 Speaker 16: You know, it clearly is not. 514 00:26:42,760 --> 00:26:46,280 Speaker 15: But they're continuing to grow and the expectations are for 515 00:26:46,400 --> 00:26:49,400 Speaker 15: growth of over forty percent in revenues for next year. 516 00:26:50,040 --> 00:26:52,639 Speaker 15: And Blackwell is just going to be another step up 517 00:26:52,760 --> 00:26:54,320 Speaker 15: in allowing that to happen. 518 00:26:56,160 --> 00:26:59,119 Speaker 5: Oko Wealth Enhancement Group has like what seven point eight 519 00:26:59,160 --> 00:27:01,960 Speaker 5: million in video shares, like a billion dollars worth of stock. 520 00:27:02,000 --> 00:27:04,920 Speaker 5: I know that you were part of our kind of 521 00:27:04,960 --> 00:27:07,200 Speaker 5: watch party last night watching the interview. 522 00:27:07,680 --> 00:27:10,040 Speaker 8: You lead research, right, you use. 523 00:27:09,920 --> 00:27:12,239 Speaker 5: Your expertise to try and work out what's going on. 524 00:27:13,040 --> 00:27:15,760 Speaker 5: What did you work out during the course of that conversation? 525 00:27:17,680 --> 00:27:19,760 Speaker 16: You know, I think this is a long game. 526 00:27:19,800 --> 00:27:23,679 Speaker 15: I think we're still in the early innings of AI deployment, 527 00:27:24,440 --> 00:27:28,960 Speaker 15: the hyperscalers, meta, there's so much use from all of 528 00:27:28,960 --> 00:27:33,600 Speaker 15: these It is table stakes for these large cloud providers, 529 00:27:34,160 --> 00:27:38,399 Speaker 15: and they're seeing productivity gains from the use of AI. 530 00:27:38,720 --> 00:27:41,200 Speaker 16: So I think that's going to continue. It's going to proliferate. 531 00:27:41,480 --> 00:27:44,119 Speaker 15: It is going to take time, but you know, the 532 00:27:44,200 --> 00:27:48,160 Speaker 15: Internet took time as well, and twenty years later, it's 533 00:27:48,200 --> 00:27:49,000 Speaker 15: still evolving. 534 00:27:50,440 --> 00:27:53,560 Speaker 5: Were you convinced by what Jensen Wong just said we 535 00:27:53,680 --> 00:27:56,560 Speaker 5: played in that clip just then that their business has 536 00:27:56,640 --> 00:28:00,320 Speaker 5: broadened out beyond the hyperscalers. 537 00:28:00,840 --> 00:28:04,240 Speaker 15: Yes, I mean they mentioned about, you know, sovereign entities 538 00:28:05,119 --> 00:28:09,080 Speaker 15: purchasing and being in that low double digit billions of 539 00:28:09,160 --> 00:28:10,520 Speaker 15: dollars in terms of revenues. 540 00:28:10,760 --> 00:28:12,680 Speaker 16: You know, that was exciting to see. 541 00:28:13,200 --> 00:28:15,800 Speaker 15: And you know, hyper scalers were forty five percent, which 542 00:28:15,840 --> 00:28:18,639 Speaker 15: means fifty five percent is other revenues. 543 00:28:18,760 --> 00:28:22,240 Speaker 16: So that is a nice diversification as well. 544 00:28:22,800 --> 00:28:26,080 Speaker 15: But that consistency from the hyper spit scalers is likely 545 00:28:26,119 --> 00:28:26,879 Speaker 15: to continue. 546 00:28:27,119 --> 00:28:29,000 Speaker 16: It's just going to be choppy year to year. 547 00:28:29,480 --> 00:28:33,840 Speaker 15: You know, many of these companies, Apple, Microsoft, Amazon, Google, 548 00:28:33,880 --> 00:28:37,280 Speaker 15: they're all going to be evaluating their cap X budgets 549 00:28:37,359 --> 00:28:40,320 Speaker 15: for next year and each year it's not going to 550 00:28:40,360 --> 00:28:43,280 Speaker 15: be the same and so we have to be diligent 551 00:28:43,360 --> 00:28:45,920 Speaker 15: about that. But for the most part, they will be 552 00:28:46,040 --> 00:28:50,400 Speaker 15: spending in order to get that productivity enhancement going forward. 553 00:28:50,960 --> 00:28:52,560 Speaker 6: What about competition? 554 00:28:53,040 --> 00:28:54,840 Speaker 4: A lot of people feeling that if there is just 555 00:28:54,880 --> 00:28:58,520 Speaker 4: a slight blip in this annual cadence of innovation, maybe 556 00:28:58,560 --> 00:29:01,000 Speaker 4: AMD can start to work its way in a little 557 00:29:01,040 --> 00:29:01,440 Speaker 4: bit more. 558 00:29:01,680 --> 00:29:03,080 Speaker 6: Do you agree? 559 00:29:04,000 --> 00:29:04,280 Speaker 16: Sure? 560 00:29:04,360 --> 00:29:07,280 Speaker 15: You know, I think from a high per scaler perspective 561 00:29:07,400 --> 00:29:10,400 Speaker 15: or from the cloud providers, the Internet service providers, you 562 00:29:10,440 --> 00:29:13,680 Speaker 15: always want to have more than just one provider of 563 00:29:13,720 --> 00:29:17,080 Speaker 15: your chips, so you know, there is room for competition, 564 00:29:17,240 --> 00:29:20,280 Speaker 15: I think, you know, that's always something that we have 565 00:29:20,320 --> 00:29:23,480 Speaker 15: to keep in mind. You know, let's not forget that 566 00:29:23,640 --> 00:29:28,720 Speaker 15: Intel had the majority of data center server share for many, 567 00:29:28,760 --> 00:29:33,000 Speaker 15: many years, and here we are with Nvidia really coming 568 00:29:33,000 --> 00:29:36,280 Speaker 15: out and taking share AMD as well. So competition is 569 00:29:36,360 --> 00:29:39,080 Speaker 15: always something that we look for and watch out for. 570 00:29:39,400 --> 00:29:40,240 Speaker 6: Cautionary tail. 571 00:29:40,560 --> 00:29:43,960 Speaker 4: What's interesting is you have holds on Texas instruments on 572 00:29:44,080 --> 00:29:47,920 Speaker 4: Broadcom what many of thought perhaps hasn't moved. 573 00:29:47,640 --> 00:29:49,840 Speaker 6: At the pace that we're expecting. 574 00:29:49,440 --> 00:29:52,080 Speaker 4: Was that these hyperscalers would make their own chips to 575 00:29:52,120 --> 00:29:54,560 Speaker 4: compete in quite the same way, using a Texas instruments, 576 00:29:54,680 --> 00:29:59,720 Speaker 4: using CSMC for example. I'm interested in if ever you 577 00:29:59,760 --> 00:30:01,600 Speaker 4: see that really coming in as a competition. 578 00:30:03,360 --> 00:30:05,160 Speaker 16: You know, it's tough. 579 00:30:05,240 --> 00:30:08,880 Speaker 15: You know, the design part of those chips is you 580 00:30:08,920 --> 00:30:12,920 Speaker 15: know where Nvidia has the advantage along with the software 581 00:30:12,760 --> 00:30:15,120 Speaker 15: associated with AI. 582 00:30:15,440 --> 00:30:16,960 Speaker 16: So you know they're Kuda. 583 00:30:17,720 --> 00:30:20,040 Speaker 15: You know, all the chips are built off of Kuda, 584 00:30:20,080 --> 00:30:23,840 Speaker 15: and that really provides them with the benefit that many 585 00:30:24,240 --> 00:30:26,960 Speaker 15: other chip providers and chip manufacturers just don't have. 586 00:30:29,520 --> 00:30:33,640 Speaker 5: Can you define what Nvidia is, what it actually is. 587 00:30:35,920 --> 00:30:39,760 Speaker 15: You know, Nvidia is a chip maker at the end 588 00:30:39,760 --> 00:30:42,840 Speaker 15: of the day, right, but it is a chip maker 589 00:30:43,200 --> 00:30:48,000 Speaker 15: and is a primary beneficiary for artificial intelligence and how 590 00:30:48,200 --> 00:30:51,560 Speaker 15: computing will go forward in the coming decade. 591 00:30:53,440 --> 00:30:54,040 Speaker 8: Good attempt. 592 00:30:54,280 --> 00:30:56,560 Speaker 5: I think Jensen one might disagree with you and say 593 00:30:56,600 --> 00:30:57,320 Speaker 5: it's more than that. 594 00:30:57,880 --> 00:30:59,720 Speaker 8: We'll get another stab at it incoming. 595 00:30:59,760 --> 00:31:03,960 Speaker 5: Call is Ayoka yoshiok, senior port Lafolio manager, a wealth 596 00:31:04,000 --> 00:31:04,680 Speaker 5: enhancement group. 597 00:31:04,720 --> 00:31:05,080 Speaker 8: Thank you. 598 00:31:05,320 --> 00:31:08,080 Speaker 5: Another story we've been watching is May twan stock jumping 599 00:31:08,080 --> 00:31:11,440 Speaker 5: the most in about six months after China's meal delivery 600 00:31:11,520 --> 00:31:15,360 Speaker 5: leader posted strong earnings ununveiled a one billion dollar buyback. 601 00:31:15,360 --> 00:31:18,520 Speaker 5: It's a positive signal for investors who are increasingly worried 602 00:31:18,520 --> 00:31:22,160 Speaker 5: about domestic consumer malaise in China. It signals may Twan 603 00:31:22,560 --> 00:31:26,160 Speaker 5: is beating rivals like byte Dance, which joined Ali Barber 604 00:31:26,480 --> 00:31:28,040 Speaker 5: in its main market character. 605 00:31:28,360 --> 00:31:31,160 Speaker 4: Coming up, we've got more of a conversation on AI 606 00:31:32,000 --> 00:31:35,240 Speaker 4: about the regulation. Russell Wold, deputy director of Stanford's Institute 607 00:31:35,240 --> 00:31:38,560 Speaker 4: for Humans Centered AI, joins US. Let's get a quick 608 00:31:38,600 --> 00:31:41,480 Speaker 4: check on AI. Another area meta at one point six percent. 609 00:31:41,720 --> 00:31:45,640 Speaker 4: They have an announcement. LAMA foundational model was downloaded over 610 00:31:45,680 --> 00:31:48,560 Speaker 4: twenty million times in the past month, approaching three hundred 611 00:31:48,560 --> 00:31:51,680 Speaker 4: and fifty million total downloads. Basically, it shows traction, so 612 00:31:51,800 --> 00:31:55,920 Speaker 4: as Bloomberg Intelligence says, maybe some new licensing. 613 00:31:55,480 --> 00:32:08,240 Speaker 6: Revenue stream in the horizon. This is Blomberg Technology. 614 00:32:10,280 --> 00:32:14,360 Speaker 5: Sources telling Bloomberg Open Ai is getting closer to raising 615 00:32:14,480 --> 00:32:18,400 Speaker 5: funding at evaluation of more than one hundred billion dollars 616 00:32:18,440 --> 00:32:21,880 Speaker 5: in a round led by Frive Capital, Bloomberg Sharene Gafari 617 00:32:22,600 --> 00:32:25,200 Speaker 5: joins us now for more and kind of you about this. 618 00:32:25,280 --> 00:32:27,719 Speaker 5: Back in December, you and I reported about the idea 619 00:32:27,760 --> 00:32:31,680 Speaker 5: of like a primary more secondaries by some pretty big number. 620 00:32:31,840 --> 00:32:35,080 Speaker 8: More details please, that's right. 621 00:32:35,200 --> 00:32:38,280 Speaker 17: So open ai is advancing talks to raise a new 622 00:32:38,360 --> 00:32:41,320 Speaker 17: round of financing that would value it at one hundred 623 00:32:41,400 --> 00:32:43,760 Speaker 17: billion dollars, and that round of financing would be for 624 00:32:43,840 --> 00:32:46,360 Speaker 17: one billion led by Thrive Capital. 625 00:32:47,240 --> 00:32:49,920 Speaker 6: Do we know why they're raising funding? 626 00:32:52,760 --> 00:32:55,600 Speaker 17: Developing AI is incredibly expensive? 627 00:32:55,800 --> 00:32:56,000 Speaker 5: Right? 628 00:32:56,040 --> 00:33:02,160 Speaker 17: So, according to an employee memo written by obeniic Foe yesterday, 629 00:33:02,280 --> 00:33:04,200 Speaker 17: you know the company is doing this because they need 630 00:33:04,240 --> 00:33:07,920 Speaker 17: to cover their operating and computing costs, right, the incredible 631 00:33:07,920 --> 00:33:11,360 Speaker 17: costs of GPUs that they need to keep scaling up 632 00:33:11,400 --> 00:33:14,600 Speaker 17: their large language models to reach their goal of achieving 633 00:33:14,640 --> 00:33:18,200 Speaker 17: some kind of artificial general intelligence. That is a project 634 00:33:18,240 --> 00:33:21,560 Speaker 17: that just demands sort of an endless pile of cash. 635 00:33:21,760 --> 00:33:25,360 Speaker 4: With all of Microsoft backing Sharhan KAfari, they still need more. 636 00:33:25,360 --> 00:33:25,800 Speaker 6: We thank you. 637 00:33:25,920 --> 00:33:29,840 Speaker 4: Meanwhile, California's state Assembly approved a controversial AI safety bill 638 00:33:29,840 --> 00:33:33,080 Speaker 4: that requires companies to make sure their technology doesn't cause 639 00:33:33,240 --> 00:33:36,400 Speaker 4: major harm. Now, the bill SB ten forty seven would 640 00:33:36,480 --> 00:33:39,880 Speaker 4: require companies to take precautions such as implementing a kill 641 00:33:39,920 --> 00:33:42,760 Speaker 4: switch that can turn off their technology at any time. 642 00:33:43,240 --> 00:33:46,800 Speaker 4: Russell Wold as deputy director of the Stanford HI and 643 00:33:46,880 --> 00:33:49,920 Speaker 4: you're discussing the bill and larger AI landscape with us 644 00:33:50,000 --> 00:33:53,880 Speaker 4: because Russell many would say, well, that's a good thing, 645 00:33:54,400 --> 00:33:57,479 Speaker 4: being able to control technology that perhaps some are fearful of. 646 00:33:57,680 --> 00:34:00,800 Speaker 4: Why is this a threat to your academic Wesse such. 647 00:34:01,880 --> 00:34:04,760 Speaker 18: Well, good morning, Caroline, and thank you for having me. 648 00:34:05,840 --> 00:34:09,440 Speaker 18: I think what's really important about good policy is it 649 00:34:09,480 --> 00:34:11,919 Speaker 18: should solve for the harm that it's trying to solve 650 00:34:12,000 --> 00:34:14,520 Speaker 18: for in the case of SB ten forty seven, and 651 00:34:14,600 --> 00:34:19,320 Speaker 18: unfortunately does not do that. However, what is most concerning 652 00:34:19,360 --> 00:34:21,640 Speaker 18: from my perspective is that harms academia. 653 00:34:22,160 --> 00:34:24,520 Speaker 10: Harms academia because it hurts. 654 00:34:24,360 --> 00:34:27,680 Speaker 18: The open source community and makes it very difficult for 655 00:34:27,719 --> 00:34:32,160 Speaker 18: the open source community, startups or other industry or large 656 00:34:32,160 --> 00:34:35,640 Speaker 18: players like Meta who puts out the Lama model for 657 00:34:35,800 --> 00:34:38,880 Speaker 18: us to be able to dissect understand how that works, 658 00:34:39,320 --> 00:34:42,560 Speaker 18: what its impact will be for society. And we need 659 00:34:42,600 --> 00:34:44,680 Speaker 18: to be able to train the next generation to be 660 00:34:44,840 --> 00:34:47,239 Speaker 18: AI leaders. And if we can't be able to have 661 00:34:47,360 --> 00:34:50,759 Speaker 18: access to this because this could hurt this entire community, 662 00:34:51,120 --> 00:34:54,240 Speaker 18: then I think SB ten forty seven is actually counterproductive. 663 00:34:55,160 --> 00:35:00,359 Speaker 4: Now, what those who have written SB ten and would 664 00:35:00,400 --> 00:35:02,520 Speaker 4: come back with and indeed we did have Scott Wiener 665 00:35:02,600 --> 00:35:05,880 Speaker 4: on the show previously is saying, look, we're not taxing, 666 00:35:05,920 --> 00:35:09,040 Speaker 4: we're not asking those that are running smaller models. We're 667 00:35:09,040 --> 00:35:12,479 Speaker 4: spending less than ten million or so. We are only 668 00:35:12,520 --> 00:35:16,000 Speaker 4: after the big players. Why is it such a crucial impact? 669 00:35:16,040 --> 00:35:18,120 Speaker 4: For example, when Lama seems to be going great, we 670 00:35:18,200 --> 00:35:20,360 Speaker 4: just had numbers out of Meta that there's twenty million 671 00:35:20,400 --> 00:35:22,120 Speaker 4: times downloads in the past month. 672 00:35:21,920 --> 00:35:25,760 Speaker 10: Alone, right, And that's precisely the point. 673 00:35:26,440 --> 00:35:29,560 Speaker 18: Meta alone right now is looking at maybe restricting Lama's 674 00:35:29,640 --> 00:35:34,920 Speaker 18: use in the EU because of the overly stringent areas. 675 00:35:35,120 --> 00:35:36,960 Speaker 10: SB ten forty seven is by. 676 00:35:36,880 --> 00:35:40,040 Speaker 18: Far more far reaching than this when it comes to 677 00:35:40,080 --> 00:35:43,239 Speaker 18: the liability issues related to that, and the problem with 678 00:35:43,280 --> 00:35:46,239 Speaker 18: that is is companies like Meta won't be releasing this 679 00:35:46,360 --> 00:35:49,240 Speaker 18: if there are such strong liability that can come against 680 00:35:49,320 --> 00:35:51,960 Speaker 18: them for this, and without that, we won't be able 681 00:35:52,040 --> 00:35:55,080 Speaker 18: to understand and interrogate these models and see how they 682 00:35:55,160 --> 00:35:58,400 Speaker 18: work the way academia does and how we do that 683 00:35:58,520 --> 00:36:01,359 Speaker 18: very well, so that will off an entire choke point 684 00:36:01,400 --> 00:36:05,560 Speaker 18: to us. For second, I would also add that academia 685 00:36:05,560 --> 00:36:09,160 Speaker 18: itself well resourced universities do want to look into how 686 00:36:09,200 --> 00:36:12,440 Speaker 18: to build these, and so there's consortiums of universities that 687 00:36:12,560 --> 00:36:14,920 Speaker 18: might want to spend more money in building these so 688 00:36:14,960 --> 00:36:17,600 Speaker 18: we can train the next generation on how this works. 689 00:36:17,800 --> 00:36:19,800 Speaker 10: And we won't be able to do that because we won't. 690 00:36:19,560 --> 00:36:21,719 Speaker 18: Be able to afford all of the lawyers and the 691 00:36:21,840 --> 00:36:24,560 Speaker 18: legal fees that will be required to be able to 692 00:36:24,560 --> 00:36:25,520 Speaker 18: stay in compliance. 693 00:36:27,480 --> 00:36:30,280 Speaker 5: Something that you just said, Russell about sort of academic 694 00:36:30,360 --> 00:36:33,800 Speaker 5: access to technology. You know, we had Nvidia's earnings last 695 00:36:33,880 --> 00:36:36,680 Speaker 5: night and a discussion with Jensen Wong I had was 696 00:36:36,719 --> 00:36:39,600 Speaker 5: about the broadening out of the use of AI accelerators 697 00:36:39,600 --> 00:36:44,800 Speaker 5: beyond the hyperscalas can Stamford Institute for Human Centered AI 698 00:36:45,040 --> 00:36:49,640 Speaker 5: get access to a cluster like is this a situation 699 00:36:49,719 --> 00:36:50,480 Speaker 5: that works for you? 700 00:36:52,840 --> 00:36:54,960 Speaker 10: It's actually a significant challenge for us. 701 00:36:55,000 --> 00:36:58,719 Speaker 18: We actually just were able to secure thirty h one hundreds, 702 00:36:58,719 --> 00:37:02,920 Speaker 18: and that sounds one, but it's unfortunate because the reality 703 00:37:03,080 --> 00:37:06,439 Speaker 18: is is if you look at what Meta has tried 704 00:37:06,480 --> 00:37:08,760 Speaker 18: to secure, they're trying to secure three hundred thousand. 705 00:37:09,200 --> 00:37:10,520 Speaker 10: So the reality is. 706 00:37:10,360 --> 00:37:13,799 Speaker 18: Is academia is constrained as to what it can do 707 00:37:14,040 --> 00:37:17,839 Speaker 18: in this particular space, and we are very limited, and 708 00:37:17,880 --> 00:37:19,440 Speaker 18: what we need to do is have. 709 00:37:19,800 --> 00:37:22,080 Speaker 10: Congress past the Create AI Act. 710 00:37:22,320 --> 00:37:26,960 Speaker 18: That is a government a subsidizing compute and data for 711 00:37:27,040 --> 00:37:29,720 Speaker 18: academic research, and it's desperately needed. 712 00:37:29,920 --> 00:37:31,440 Speaker 10: And academia also needs to. 713 00:37:31,400 --> 00:37:34,480 Speaker 18: Consider how to reform here and put greater degree of 714 00:37:34,520 --> 00:37:36,960 Speaker 18: investment in this so that we can be able to 715 00:37:36,960 --> 00:37:40,280 Speaker 18: train students so that they can be the next DAI leaders. 716 00:37:41,600 --> 00:37:43,719 Speaker 5: SB ten forty seven. Sorry to go back to it. 717 00:37:43,760 --> 00:37:45,200 Speaker 5: Is this the end of the story or do you 718 00:37:45,200 --> 00:37:48,640 Speaker 5: think you'll continue to be consulted as this moves forward. 719 00:37:50,480 --> 00:37:53,160 Speaker 10: We are being continually consulted on this. 720 00:37:53,239 --> 00:37:55,879 Speaker 18: But the reality is is there's a chorus of people 721 00:37:55,920 --> 00:37:59,520 Speaker 18: who are deeply concerned about this. It's not just academia. 722 00:37:59,560 --> 00:38:03,840 Speaker 18: It is deed, small businesses that are startups that are 723 00:38:03,920 --> 00:38:05,640 Speaker 18: afraid of what this will mean for them. 724 00:38:05,880 --> 00:38:07,480 Speaker 10: And there's this ironic side of this. 725 00:38:07,800 --> 00:38:11,520 Speaker 18: It bizarrely will entranch er make the most powerful companies 726 00:38:12,160 --> 00:38:15,440 Speaker 18: even more secure in this space because they can afford 727 00:38:15,440 --> 00:38:18,480 Speaker 18: the legal fees, they can afford all the compliance fees 728 00:38:18,520 --> 00:38:23,480 Speaker 18: and things that come from this. Startups in academia cannot. 729 00:38:25,120 --> 00:38:29,240 Speaker 5: Russell Wald of Stanford Institute for Human Centered Artificial Intelligence, thank. 730 00:38:29,200 --> 00:38:39,759 Speaker 4: You just check in on shares of Salesforce arising after 731 00:38:39,800 --> 00:38:42,280 Speaker 4: the company delivered in earnings forecus look that top estimates 732 00:38:42,280 --> 00:38:44,280 Speaker 4: and announced some changes at the c suite. 733 00:38:44,320 --> 00:38:46,720 Speaker 6: Amy Weaver stepping down a CFO. 734 00:38:46,680 --> 00:38:49,880 Speaker 4: After four years in the job, numerks Brady Ford across it. 735 00:38:50,120 --> 00:38:52,440 Speaker 4: What else do we hear other than executive shake up? 736 00:38:52,960 --> 00:38:57,040 Speaker 19: What we really learned is that software companies and cumbents 737 00:38:57,080 --> 00:38:59,440 Speaker 19: are not sure where they fit in the AI moment. 738 00:39:00,040 --> 00:39:03,560 Speaker 19: Last night, Salesforce rebranded it's AI tools not as assistants, 739 00:39:03,600 --> 00:39:05,839 Speaker 19: but as agents. And we heard this word over one 740 00:39:05,880 --> 00:39:08,280 Speaker 19: hundred times. They kept saying, we are making agents. 741 00:39:08,320 --> 00:39:09,480 Speaker 3: Now, how is. 742 00:39:09,480 --> 00:39:12,280 Speaker 19: That different from the assistance we've seen with Microsoft and others. 743 00:39:12,960 --> 00:39:16,280 Speaker 19: No one's sure yet, but we are learning that software 744 00:39:16,320 --> 00:39:18,160 Speaker 19: companies continue to trying to find their place in this 745 00:39:18,239 --> 00:39:20,839 Speaker 19: AI moment and the revenue is not here yet. 746 00:39:20,880 --> 00:39:22,479 Speaker 8: But hey, just wait a year or two. 747 00:39:23,640 --> 00:39:26,440 Speaker 5: I saw Amy Weavers post on LinkedIn She's been CFO 748 00:39:26,520 --> 00:39:30,160 Speaker 5: for four years but Salesforce for eleven. How's the market 749 00:39:30,280 --> 00:39:31,520 Speaker 5: taking that departure? 750 00:39:32,280 --> 00:39:32,520 Speaker 3: Yeah? 751 00:39:32,560 --> 00:39:35,880 Speaker 19: The market, I think is reading this as wait a second, 752 00:39:35,960 --> 00:39:40,400 Speaker 19: is that everlasting Salesforce succession stories starting to kind of 753 00:39:40,440 --> 00:39:43,480 Speaker 19: get rolling again right, four years is a relatively short 754 00:39:43,480 --> 00:39:44,520 Speaker 19: CFO tenure. 755 00:39:45,600 --> 00:39:46,640 Speaker 10: She was well liked. 756 00:39:46,719 --> 00:39:49,160 Speaker 19: She's not leaving for another opportunity, it doesn't seem so 757 00:39:49,200 --> 00:39:52,000 Speaker 19: it's hey, is this another phase of Salesforce's growth. They're 758 00:39:52,040 --> 00:39:55,439 Speaker 19: doing more consumption based pricing, the business model's changing a bit, 759 00:39:55,840 --> 00:39:57,400 Speaker 19: and maybe they just feel they need to bring some 760 00:39:57,480 --> 00:39:58,319 Speaker 19: fresh blood in. 761 00:39:58,320 --> 00:39:59,000 Speaker 10: At the top. 762 00:39:59,320 --> 00:40:02,000 Speaker 19: Because again, that idea of who will one day replace 763 00:40:02,080 --> 00:40:04,680 Speaker 19: Bernieoff is a kind of everlasting question. 764 00:40:05,640 --> 00:40:07,960 Speaker 4: I mean who has been there a significant amount of 765 00:40:07,960 --> 00:40:10,480 Speaker 4: time that people feel can step into that void. 766 00:40:10,920 --> 00:40:14,040 Speaker 19: Third Chief operating Officer Brian Millum. He has been there 767 00:40:14,040 --> 00:40:16,640 Speaker 19: for very long and has taken on a much wider 768 00:40:16,719 --> 00:40:20,960 Speaker 19: expanded role. I would say if tomorrow bernnioff a I'm 769 00:40:21,000 --> 00:40:23,080 Speaker 19: done with this, would probably be him. But at the 770 00:40:23,160 --> 00:40:25,319 Speaker 19: end of the day, investors would probably like to see 771 00:40:25,320 --> 00:40:28,839 Speaker 19: a bit more new talent coming in, maybe from the outside. 772 00:40:29,080 --> 00:40:30,120 Speaker 19: That's something that I hear. 773 00:40:30,040 --> 00:40:32,839 Speaker 4: Of them, and an AI boost that can't come quick 774 00:40:32,920 --> 00:40:36,000 Speaker 4: enough to five momentum, so says Barkley's pretty ford all 775 00:40:36,040 --> 00:40:36,600 Speaker 4: over these. 776 00:40:36,440 --> 00:40:38,560 Speaker 6: Earnings, we thank him for it. Now? 777 00:40:38,600 --> 00:40:40,920 Speaker 4: That does it for this edition of Bloomberg Technology A 778 00:40:40,920 --> 00:40:41,480 Speaker 4: big one. 779 00:40:42,080 --> 00:40:44,719 Speaker 5: Yeah, it was a big one. Recap it on the podcast. 780 00:40:44,760 --> 00:40:48,000 Speaker 5: You know where to find the Bloomberg Technology Podcast on Apple, Spotify, 781 00:40:48,040 --> 00:40:51,759 Speaker 5: iHeart and all the Bloomberg platforms. Big thanks from everyone 782 00:40:51,800 --> 00:40:55,319 Speaker 5: here in San Francisco, Caitly and Jackie and Carr in 783 00:40:55,320 --> 00:40:57,440 Speaker 5: New York City. There's one day to go in this 784 00:40:57,520 --> 00:41:00,399 Speaker 5: busy tech week. This is Bloomberg Technology. 785 00:41:00,440 --> 00:41:01,560 Speaker 8: It don't