1 00:00:01,800 --> 00:00:06,119 Speaker 1: From Mahart where innovation, money and power. Collie in Silicon 2 00:00:06,200 --> 00:00:07,080 Speaker 1: Vallet NBN. 3 00:00:07,440 --> 00:00:11,680 Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed loved Love. 4 00:00:26,520 --> 00:00:29,440 Speaker 3: I med Lolo in San Francisco. Caroline hides off today 5 00:00:29,480 --> 00:00:32,440 Speaker 3: this is Bloomberg Technology in my water show we have 6 00:00:32,560 --> 00:00:36,080 Speaker 3: for you coming up. Sam Outman returns to open Ai. 7 00:00:36,200 --> 00:00:39,120 Speaker 3: Will break down the changes at the artificial intelligence company. 8 00:00:39,320 --> 00:00:42,559 Speaker 3: As Outman takes the helm after a shock Ouster, we 9 00:00:42,560 --> 00:00:46,800 Speaker 3: speak to Vino Kosler, the first venture investor into open Ai. 10 00:00:47,159 --> 00:00:49,920 Speaker 3: Past the world's most valuable chipmaker and Nvidia tops earnings 11 00:00:50,000 --> 00:00:53,760 Speaker 3: estimates that fails to meet loftier expectations from investors. We 12 00:00:53,840 --> 00:00:57,320 Speaker 3: break down the results and will take a deep dive 13 00:00:57,400 --> 00:01:00,560 Speaker 3: into the world of crypto as cz pleads Gill to 14 00:01:00,680 --> 00:01:04,759 Speaker 3: criminal charges for anti money laundering and US sanctions violations. 15 00:01:04,800 --> 00:01:07,319 Speaker 3: All that and so much more ahead a very quick 16 00:01:07,400 --> 00:01:09,720 Speaker 3: check on the kind of public market perspective of what 17 00:01:09,800 --> 00:01:12,080 Speaker 3: is going on in the world. Nvidia smashes it in 18 00:01:12,080 --> 00:01:15,319 Speaker 3: the fiscal third quarter, gives a very strong outlook in 19 00:01:15,360 --> 00:01:19,240 Speaker 3: the fiscal fourth quarter ahead of the street consensus. The 20 00:01:19,360 --> 00:01:23,560 Speaker 3: story the impact of US technology curbs taking hold. It 21 00:01:23,600 --> 00:01:25,800 Speaker 3: will impact them in the fiscal fourth quarter. We will 22 00:01:25,800 --> 00:01:28,679 Speaker 3: go deep and bring you the analysis on that stock 23 00:01:29,000 --> 00:01:31,360 Speaker 3: and what the world of AI accelerators looks like going 24 00:01:31,400 --> 00:01:34,560 Speaker 3: into next year. The other publicly traded proxy for the 25 00:01:34,560 --> 00:01:38,600 Speaker 3: big story is Microsoft. Sam Altman is back at open Ai. 26 00:01:39,360 --> 00:01:41,840 Speaker 3: This is largely being seen as a big cluss for 27 00:01:41,880 --> 00:01:44,120 Speaker 3: Microsoft to stock up one point five percent. It's the 28 00:01:44,160 --> 00:01:46,880 Speaker 3: third time this week that Microsoft has hit a fresh 29 00:01:46,959 --> 00:01:50,720 Speaker 3: record high. There is some element that Microsoft gets what 30 00:01:50,800 --> 00:01:53,480 Speaker 3: it wants. We will discuss that throughout the program. We 31 00:01:53,520 --> 00:01:56,480 Speaker 3: have an excellent external voice coming right up. But first 32 00:01:56,600 --> 00:01:59,880 Speaker 3: our top story, Sam Outman's return to open Ai as CEO. 33 00:02:00,080 --> 00:02:03,160 Speaker 3: I want to bring in Sharen Gafari. Okay, let's start 34 00:02:03,160 --> 00:02:06,400 Speaker 3: with the basics. Sam Ountman is back as CEO, and 35 00:02:06,480 --> 00:02:10,840 Speaker 3: there are some temporary board changes. We don't know, let's 36 00:02:10,840 --> 00:02:12,360 Speaker 3: be honest, but what are those changes? 37 00:02:12,840 --> 00:02:13,000 Speaker 2: Right? 38 00:02:13,120 --> 00:02:15,760 Speaker 4: So, there are some new board members and you know, 39 00:02:15,840 --> 00:02:18,120 Speaker 4: it's unclear exactly the details, but it seems like there 40 00:02:18,160 --> 00:02:20,840 Speaker 4: may they may be appointing a new board long term. 41 00:02:21,160 --> 00:02:25,200 Speaker 4: For now, it is going to be Larry Summers. Adam 42 00:02:25,240 --> 00:02:26,920 Speaker 4: Dangelo is still on the board, who. 43 00:02:26,760 --> 00:02:28,680 Speaker 3: Was already a board member, who was already. 44 00:02:28,320 --> 00:02:29,040 Speaker 5: A board member. 45 00:02:30,080 --> 00:02:32,520 Speaker 3: And then we have Brett Taylor. 46 00:02:32,560 --> 00:02:35,640 Speaker 4: Brett Taylor, that's right, who was also a remember on 47 00:02:35,720 --> 00:02:36,919 Speaker 4: the board of Twitter, right. 48 00:02:36,919 --> 00:02:39,799 Speaker 3: He was chairman when Twitter now known as X was 49 00:02:39,840 --> 00:02:40,959 Speaker 3: sold to Elon Musk. 50 00:02:40,800 --> 00:02:43,720 Speaker 4: Correct, So he has experience with companies and crises, right 51 00:02:43,760 --> 00:02:47,679 Speaker 4: and during leadership changes. So that's a new board we're 52 00:02:47,720 --> 00:02:51,079 Speaker 4: seeing reported, right. But Tasha and Helen are out. 53 00:02:51,400 --> 00:02:54,320 Speaker 3: Yeah, I'm hearing that from sources as well. Yep, Tusha 54 00:02:54,320 --> 00:02:56,960 Speaker 3: and Helen, who were on the board that that fired 55 00:02:57,120 --> 00:03:00,560 Speaker 3: Sam Outman, excuse me, Friday are not as it stands 56 00:03:00,600 --> 00:03:03,200 Speaker 3: my understanding, and I think other outlets are reported they're 57 00:03:03,200 --> 00:03:04,360 Speaker 3: not on the board, correct. 58 00:03:04,360 --> 00:03:07,239 Speaker 4: And remember Tasha and Helen were both keyboard members who 59 00:03:07,320 --> 00:03:12,200 Speaker 4: ousted Sam Altman, right, And we're behind essentially this coup. 60 00:03:12,639 --> 00:03:15,120 Speaker 4: So it makes sense that with Sam returning, part of 61 00:03:15,120 --> 00:03:18,000 Speaker 4: that negotiation would involve having people who turned on him out. 62 00:03:18,360 --> 00:03:22,480 Speaker 3: For our audience worldwide disclosure, Larry Summers is a paid 63 00:03:22,600 --> 00:03:27,239 Speaker 3: contributor on Bloomberg Television, So that's that a lot of 64 00:03:27,240 --> 00:03:30,280 Speaker 3: people around the world ask why the drama? Why do 65 00:03:30,400 --> 00:03:32,720 Speaker 3: any of us around the world care about open AI 66 00:03:33,000 --> 00:03:37,680 Speaker 3: who leads it? The answer to me seems well, open 67 00:03:37,720 --> 00:03:40,840 Speaker 3: Ai is the face of AI, absolutely. 68 00:03:40,920 --> 00:03:44,040 Speaker 4: I mean, this is an industry leader. Remember that AI 69 00:03:44,200 --> 00:03:46,640 Speaker 4: has been something that Silicon Valley talked about for decades, 70 00:03:46,640 --> 00:03:49,680 Speaker 4: but it didn't really explode onto the market until Opening 71 00:03:49,680 --> 00:03:52,680 Speaker 4: Eye came out with Chatchipt just about a year ago. Right, 72 00:03:52,760 --> 00:03:55,280 Speaker 4: that was a breakthrough moment. So they are the ones 73 00:03:55,320 --> 00:03:57,240 Speaker 4: setting the tone for this industry. They are the ones 74 00:03:57,320 --> 00:04:00,680 Speaker 4: making AI relevant on a consumer level. They're the ones 75 00:04:00,680 --> 00:04:02,400 Speaker 4: who came out with products at one hundred you know, 76 00:04:02,400 --> 00:04:05,480 Speaker 4: one hundred million people are actually using So how AI go, 77 00:04:05,640 --> 00:04:07,360 Speaker 4: how open Ai go, as the rest of the industry 78 00:04:07,400 --> 00:04:09,040 Speaker 4: will go. And that's why I think people should care. 79 00:04:08,960 --> 00:04:09,640 Speaker 5: About this story. 80 00:04:09,840 --> 00:04:12,080 Speaker 3: I think it's important to recap that this will started 81 00:04:12,080 --> 00:04:16,960 Speaker 3: Friday lunchtime and we are now Wednesday, the day before Thanksgiving, 82 00:04:17,680 --> 00:04:21,760 Speaker 3: and we actually don't have a definitive end to this story. 83 00:04:21,880 --> 00:04:25,520 Speaker 3: There's a part of the resolution where there will be 84 00:04:25,560 --> 00:04:29,359 Speaker 3: an independent investigation into Sam Outman why he was fired. 85 00:04:29,440 --> 00:04:32,320 Speaker 3: Just explain the rest of what was announced late last 86 00:04:32,400 --> 00:04:33,240 Speaker 3: night by open Ai. 87 00:04:34,160 --> 00:04:37,240 Speaker 4: Correct, So we're going to see you know, and again, 88 00:04:37,279 --> 00:04:39,360 Speaker 4: remember this is a negotiation between two sides. 89 00:04:39,400 --> 00:04:41,040 Speaker 3: You have the old board who. 90 00:04:40,920 --> 00:04:43,039 Speaker 4: Was very skeptical of Sam Altman and pushed him out, 91 00:04:43,279 --> 00:04:46,400 Speaker 4: and then you have Sam having this prodigal return. So 92 00:04:47,600 --> 00:04:49,640 Speaker 4: on the other side, we sort of see this concession 93 00:04:49,640 --> 00:04:52,360 Speaker 4: and that there will be an investigation into Sam's. 94 00:04:53,560 --> 00:04:54,080 Speaker 1: Conduct. 95 00:04:54,920 --> 00:04:57,760 Speaker 4: So far, the only allegations we've seen raised against him 96 00:04:57,800 --> 00:04:59,640 Speaker 4: by the board or people close to the board are 97 00:05:00,080 --> 00:05:05,159 Speaker 4: pretty vague, right, just statements around that he essentially was 98 00:05:05,240 --> 00:05:07,080 Speaker 4: not candid with the board, but we don't know about 99 00:05:07,080 --> 00:05:10,480 Speaker 4: exactly what was he not candid allegedly. 100 00:05:10,560 --> 00:05:15,400 Speaker 3: Now you're maybe maybe a philosophical point of difference on 101 00:05:15,680 --> 00:05:18,719 Speaker 3: the existential threat of AI and I reported and you 102 00:05:18,839 --> 00:05:22,320 Speaker 3: reported that one reason Emmitt Sheer has added as the 103 00:05:22,360 --> 00:05:24,480 Speaker 3: CEO and interim basis is that he was an EA. 104 00:05:24,560 --> 00:05:25,760 Speaker 3: He shared that stential threat. 105 00:05:25,920 --> 00:05:27,640 Speaker 4: Yes, and that gets to a key detail that we 106 00:05:27,680 --> 00:05:31,080 Speaker 4: should mention, which is that you know, the interim CEO, 107 00:05:31,160 --> 00:05:33,800 Speaker 4: em Shear is stepping down right right, and so he's 108 00:05:33,839 --> 00:05:35,520 Speaker 4: being seen in the industry now and seeing a lot 109 00:05:35,560 --> 00:05:38,480 Speaker 4: of people react in texting that he he sort of 110 00:05:39,279 --> 00:05:42,800 Speaker 4: is actually not as maybe bad as people thought who 111 00:05:42,839 --> 00:05:44,800 Speaker 4: were pro Sam, because he's sort of giving up now 112 00:05:44,839 --> 00:05:46,360 Speaker 4: and letting Sam Altman come back. 113 00:05:46,240 --> 00:05:49,599 Speaker 3: All right, Bloomberg's sharing Gafara, You've been just an incredible 114 00:05:49,640 --> 00:05:51,880 Speaker 3: reporting over the last five days or so. Let's continue 115 00:05:51,880 --> 00:05:55,240 Speaker 3: the conversation. There is another party to this drama, Microsoft, 116 00:05:55,279 --> 00:05:57,800 Speaker 3: and we need to understand what this means for them. 117 00:05:57,839 --> 00:06:01,039 Speaker 3: Michael Pacter of Webbush joins us. Now someone this covied 118 00:06:01,080 --> 00:06:04,840 Speaker 3: Microsoft Clay State for a long time. Simple question, what 119 00:06:04,880 --> 00:06:06,120 Speaker 3: does this mean for Microsoft? 120 00:06:08,040 --> 00:06:10,000 Speaker 1: It's pretty huge, you know. 121 00:06:10,000 --> 00:06:14,200 Speaker 2: I think that if you think about why we haven't 122 00:06:14,240 --> 00:06:19,360 Speaker 2: had deep AI solutions for the last twenty years, it's 123 00:06:19,400 --> 00:06:23,919 Speaker 2: that computing power hadn't caught up. And open Ai is 124 00:06:24,040 --> 00:06:27,640 Speaker 2: integrated into Microsoft Cloud. Microsoft made a huge investment in 125 00:06:27,680 --> 00:06:31,880 Speaker 2: them to make sure that happens. And Microsoft Cloud is 126 00:06:32,279 --> 00:06:37,040 Speaker 2: building its scale. It's scaling all of its products, all 127 00:06:37,040 --> 00:06:40,160 Speaker 2: of its user interface, all of its developer and product 128 00:06:40,200 --> 00:06:43,120 Speaker 2: interfaces to make sure they work with open Ai. So 129 00:06:43,680 --> 00:06:47,360 Speaker 2: you need massive computing power. You know, if you were 130 00:06:47,400 --> 00:06:51,479 Speaker 2: to decide to write Charles Dickens novel and The Voice 131 00:06:51,480 --> 00:06:54,880 Speaker 2: of Stephen King, you need a product that's going to 132 00:06:54,920 --> 00:07:00,000 Speaker 2: read every tools Dickens ever and that requires massive cloud capabilities. 133 00:07:00,000 --> 00:07:05,160 Speaker 2: So Microsoft is leveraging something it's already built and integrating 134 00:07:05,200 --> 00:07:07,480 Speaker 2: it into what they consider it to be the up 135 00:07:07,480 --> 00:07:11,200 Speaker 2: and coming application and developers are going to be forced 136 00:07:11,240 --> 00:07:13,920 Speaker 2: to use Microsoft Cloud if they want to use up 137 00:07:13,920 --> 00:07:14,200 Speaker 2: in AI. 138 00:07:15,600 --> 00:07:18,840 Speaker 3: But Michael Pactor, this is not a Charles Dickens novel. 139 00:07:19,240 --> 00:07:21,400 Speaker 3: This is real life. For what it's worth, I've lived 140 00:07:21,400 --> 00:07:24,480 Speaker 3: it for the last five days. I want to go 141 00:07:24,520 --> 00:07:27,520 Speaker 3: to the point of what Satya Nadella told our Emily Chang, 142 00:07:27,920 --> 00:07:31,679 Speaker 3: which is, surprises are bad. And clearly, as we've reported 143 00:07:31,720 --> 00:07:36,960 Speaker 3: at Bloomberg, a priority for Microsoft was to address governance changes, 144 00:07:37,040 --> 00:07:41,480 Speaker 3: governance structure. Can Microsoft say with any certainty and you 145 00:07:41,520 --> 00:07:45,760 Speaker 3: know you're analyzing the stock right and it's in Microsoft's leadership, 146 00:07:46,040 --> 00:07:49,040 Speaker 3: but can they say with any certainty that this is 147 00:07:49,160 --> 00:07:51,600 Speaker 3: the end of the story, this is the outcome that 148 00:07:51,640 --> 00:07:52,200 Speaker 3: they wanted. 149 00:07:53,440 --> 00:07:53,960 Speaker 5: They meet a. 150 00:07:53,960 --> 00:07:57,720 Speaker 2: Lot of friends, I think by hiring Sam Mortman. And 151 00:07:57,800 --> 00:08:01,080 Speaker 2: you know, you saw that the letter, you know, demanding 152 00:08:01,080 --> 00:08:03,560 Speaker 2: the board resign was signed by seven hundred and fifteen 153 00:08:03,640 --> 00:08:07,000 Speaker 2: of the seven hundred and fifty employees they then offered 154 00:08:07,040 --> 00:08:10,360 Speaker 2: apparently offered all of those employees of job of Microsoft. 155 00:08:10,480 --> 00:08:15,080 Speaker 2: So you know, would they rather have rebuilt everything starting 156 00:08:15,120 --> 00:08:17,280 Speaker 2: from scratch with all the same employees or would they 157 00:08:17,400 --> 00:08:21,600 Speaker 2: rather just leverage what those employees have already built. And ultimately, 158 00:08:21,800 --> 00:08:25,360 Speaker 2: I think it's easier to just continue the partnership than 159 00:08:25,440 --> 00:08:28,000 Speaker 2: to try to rebuild. So I think that they won 160 00:08:28,120 --> 00:08:31,520 Speaker 2: either way, they win more. I think keeping things as 161 00:08:31,640 --> 00:08:35,200 Speaker 2: is it will require less of an investment. Nadella managed 162 00:08:35,240 --> 00:08:38,920 Speaker 2: this masterfully. I mean, he honestly was an honest broker 163 00:08:38,960 --> 00:08:42,040 Speaker 2: in the whole process, and he reaffirmed his commitment to 164 00:08:42,559 --> 00:08:45,600 Speaker 2: Altman and to the product and to the product team. 165 00:08:45,679 --> 00:08:49,599 Speaker 2: So I think everything that they did was just flawlessly executed. 166 00:08:49,880 --> 00:08:54,599 Speaker 3: Michael, how closely is Microsoft's valuation tied to the investment 167 00:08:54,640 --> 00:08:57,080 Speaker 3: it made in Microsoft a thesis outline on the show 168 00:08:57,559 --> 00:09:01,520 Speaker 3: yesterday that the ten billion investment they put into open 169 00:09:01,559 --> 00:09:04,640 Speaker 3: Ai at the beginning of the year has translated to 170 00:09:04,720 --> 00:09:08,920 Speaker 3: the one trillion valuation. It's direct. Do you agree with that? 171 00:09:10,280 --> 00:09:14,680 Speaker 2: I look, it's really it's hard to value Microsoft based 172 00:09:14,679 --> 00:09:19,800 Speaker 2: solely on a single investment. The company is worth the 173 00:09:19,880 --> 00:09:22,400 Speaker 2: sum of its future cash flows, and so if the 174 00:09:22,440 --> 00:09:26,400 Speaker 2: market is making a bet that Microsoft can leverage ten 175 00:09:26,520 --> 00:09:30,320 Speaker 2: or thirteen billion into a trillion of ultimate profit, then 176 00:09:30,400 --> 00:09:33,000 Speaker 2: the market's right. I mean, that's really what this comes 177 00:09:33,040 --> 00:09:35,680 Speaker 2: down to that the market thinks that this is going 178 00:09:35,720 --> 00:09:37,800 Speaker 2: to turn into let's say, one hundred billion to free 179 00:09:37,880 --> 00:09:41,360 Speaker 2: cash flow a year in perpetuity. You know, at some 180 00:09:41,480 --> 00:09:45,000 Speaker 2: point twenty thirty years from now. I'm not smart enough 181 00:09:45,040 --> 00:09:46,839 Speaker 2: to tell you what the market is thinking. I can 182 00:09:46,880 --> 00:09:49,080 Speaker 2: tell you that this is worth a lot to them. 183 00:09:49,120 --> 00:09:51,160 Speaker 3: And I as to say current market cap two point 184 00:09:51,280 --> 00:09:53,800 Speaker 3: eight trillion. Michael Packtive web Bits. Great to have you 185 00:09:53,840 --> 00:10:04,400 Speaker 3: on this program, Thank you so much. This is an 186 00:10:04,440 --> 00:10:08,040 Speaker 3: individual H one hundred GPU, or graphics processing unit in 187 00:10:08,160 --> 00:10:11,240 Speaker 3: videos AI accelerator, But in reality, it's not just a 188 00:10:11,320 --> 00:10:13,360 Speaker 3: chip that comes out of a plant. When we talk 189 00:10:13,360 --> 00:10:17,199 Speaker 3: about the h one hundred GPUs training AI models, we're 190 00:10:17,360 --> 00:10:22,319 Speaker 3: likely talking about DGXH one hundred in videos AI supercomputer. 191 00:10:22,600 --> 00:10:26,160 Speaker 3: That's eight h one hundred GPUs combined, capable of thirty 192 00:10:26,160 --> 00:10:31,760 Speaker 3: two quadrillion floating point operations per second, crazy computer performance. 193 00:10:31,960 --> 00:10:33,720 Speaker 3: It's a server design, and this is what it looks 194 00:10:33,760 --> 00:10:35,760 Speaker 3: like under the lid. It starts with an H one 195 00:10:35,800 --> 00:10:39,080 Speaker 3: hundred GPU seen here in the form of an SXM module. 196 00:10:39,160 --> 00:10:42,360 Speaker 3: Eight individual sxms are topped with heat six, designed to 197 00:10:42,360 --> 00:10:46,040 Speaker 3: dissipate heat generated from running big AI workloads. Those are 198 00:10:46,040 --> 00:10:49,520 Speaker 3: connected on a single baseboard by interconnectors, and that assembly 199 00:10:49,520 --> 00:10:52,880 Speaker 3: alone weighs sixty pounds. Add CPUs and other components, and 200 00:10:52,920 --> 00:10:56,200 Speaker 3: a finished DGX system weighs almost three hundred pounds. But 201 00:10:56,240 --> 00:10:59,360 Speaker 3: the scale in the real world is bigger still. Some 202 00:10:59,400 --> 00:11:01,520 Speaker 3: of the most power of four large language models are 203 00:11:01,520 --> 00:11:05,880 Speaker 3: trained on the Nvidia DGX super Pod. That is thirty 204 00:11:05,880 --> 00:11:09,520 Speaker 3: two DGX eight one hundred systems combined into what's called 205 00:11:09,559 --> 00:11:13,560 Speaker 3: a scalable unit. At its absolute most mind modeling scale, 206 00:11:13,640 --> 00:11:17,640 Speaker 3: DGX Superpod can be up to sixty four scalable units. 207 00:11:17,880 --> 00:11:22,760 Speaker 3: That's more than sixteen thousand individual h one hundred GPUs. 208 00:11:23,160 --> 00:11:27,640 Speaker 3: An AI company may use several superpods to train their LLLM. 209 00:11:27,880 --> 00:11:30,319 Speaker 3: In the end, the DGX infrastructure sent out to the 210 00:11:30,360 --> 00:11:34,120 Speaker 3: hyperscale cloud providers to put in their massive data centers. 211 00:11:36,480 --> 00:11:38,720 Speaker 3: We bring you that video something we put out before 212 00:11:38,720 --> 00:11:41,360 Speaker 3: because it was a point of discussion on the call 213 00:11:41,440 --> 00:11:45,240 Speaker 3: and video reporting third quarter results beating expectations in the 214 00:11:45,240 --> 00:11:47,920 Speaker 3: fiscal third quarter yesterday, giving an outlook for the fiscal 215 00:11:48,000 --> 00:11:51,400 Speaker 3: fourth which was strong on any account. The Chick Company 216 00:11:51,679 --> 00:11:54,160 Speaker 3: been a major beneficiary of the AI trade up more 217 00:11:54,160 --> 00:11:56,760 Speaker 3: than two hundred and forty percent this year on the stock, 218 00:11:57,160 --> 00:12:01,040 Speaker 3: prompting Wolf Research is Chris Casso to remain very bullish 219 00:12:01,080 --> 00:12:03,720 Speaker 3: and outperformed rating and a six hundred and thirty dollars 220 00:12:03,720 --> 00:12:07,319 Speaker 3: price target on that stock, and Chris Casso joins us 221 00:12:07,320 --> 00:12:12,000 Speaker 3: now welcome to the program, Wolf Research, Managing Director for Semiconductors. 222 00:12:12,360 --> 00:12:14,960 Speaker 3: So the stocks down, we go into this saying really 223 00:12:15,000 --> 00:12:18,719 Speaker 3: high hurdle. They didn't pass the really high herd or 224 00:12:18,760 --> 00:12:22,120 Speaker 3: based on the stock reaction. But what was the big 225 00:12:22,160 --> 00:12:25,560 Speaker 3: takeaway for you? What did you learn about in Video's 226 00:12:25,640 --> 00:12:26,600 Speaker 3: data center business. 227 00:12:27,800 --> 00:12:31,640 Speaker 6: Well, certainly the numbers were very strong and as you said, 228 00:12:32,640 --> 00:12:37,280 Speaker 6: expectations re elevated coming into the print. But the concern 229 00:12:37,320 --> 00:12:40,360 Speaker 6: that we heard from investors coming into this event was 230 00:12:40,800 --> 00:12:44,280 Speaker 6: not about how strong the numbers are right now. It's 231 00:12:44,320 --> 00:12:47,280 Speaker 6: really about where do we go from here? And I 232 00:12:47,320 --> 00:12:51,000 Speaker 6: think there's some concerns over just kind of peak revenue 233 00:12:51,040 --> 00:12:55,520 Speaker 6: here in calendar twenty four, precisely because in Vidia has 234 00:12:55,600 --> 00:13:00,480 Speaker 6: become such a large part of overall cloud capex, and 235 00:13:00,720 --> 00:13:03,040 Speaker 6: what we think they need to do next is give 236 00:13:03,080 --> 00:13:05,920 Speaker 6: people comfortable comfort that you know there's just going to 237 00:13:05,920 --> 00:13:10,480 Speaker 6: be enough dollars to be able to generate in video growth. Right, 238 00:13:11,040 --> 00:13:13,400 Speaker 6: what we think is of the next year, there's enough 239 00:13:13,440 --> 00:13:17,160 Speaker 6: product cycle catalyst, there's new products coming out, and most importantly, 240 00:13:17,200 --> 00:13:21,040 Speaker 6: the pricing of those products are substantially higher, which is 241 00:13:21,080 --> 00:13:21,840 Speaker 6: driving growth. 242 00:13:22,400 --> 00:13:23,599 Speaker 1: But the longer. 243 00:13:23,440 --> 00:13:25,400 Speaker 6: Term that I think kind of really moves to the 244 00:13:25,400 --> 00:13:28,480 Speaker 6: stock well over five hundred dollars is convincing people that 245 00:13:28,840 --> 00:13:31,600 Speaker 6: you know, there's enough dollars flowing into the data center 246 00:13:31,640 --> 00:13:33,040 Speaker 6: to be able to commodate this growth. 247 00:13:33,640 --> 00:13:35,680 Speaker 3: Okay, so let's go there. This is what Jensen Huang, 248 00:13:35,760 --> 00:13:39,079 Speaker 3: the CEO of the Video said on the call. Absolutely 249 00:13:39,440 --> 00:13:43,120 Speaker 3: he sees data center can grow through twenty twenty five. 250 00:13:43,240 --> 00:13:48,120 Speaker 3: Several factors or reasons. They're expanding their supply quite significantly. 251 00:13:48,240 --> 00:13:50,440 Speaker 3: Do you buy that and that's calendar year twenty five, 252 00:13:50,480 --> 00:13:51,960 Speaker 3: by the way, not fiscal twenty five. 253 00:13:53,040 --> 00:13:55,640 Speaker 6: Well, certainly that's the case, and you know we've seen 254 00:13:55,679 --> 00:13:58,400 Speaker 6: we speak to the suppliers and that, and certainly they're 255 00:13:58,400 --> 00:14:02,760 Speaker 6: Any capacity is a particular type of assembly back end 256 00:14:02,760 --> 00:14:06,600 Speaker 6: capacity that's very unique to Innvidia that nobody expected it 257 00:14:06,600 --> 00:14:08,559 Speaker 6: to be this large at this point. It takes some 258 00:14:08,679 --> 00:14:12,920 Speaker 6: time to add that capacity. That happens again. The other factor, 259 00:14:12,960 --> 00:14:15,920 Speaker 6: which I think is somewhat misunderstood with regard to the 260 00:14:15,920 --> 00:14:18,880 Speaker 6: stock is a large part of the growth is coming 261 00:14:18,920 --> 00:14:22,760 Speaker 6: from pricing, and that's a function of more's loss slowing down. 262 00:14:23,280 --> 00:14:27,120 Speaker 6: The chips themselves are more expensive. The H one hundred 263 00:14:27,160 --> 00:14:30,320 Speaker 6: of the current version is almost three times as expensive 264 00:14:30,360 --> 00:14:33,400 Speaker 6: as the prior version, but the benefit the Nvidia gives 265 00:14:33,440 --> 00:14:35,920 Speaker 6: you is that it's more than ten times the performance, 266 00:14:36,440 --> 00:14:36,960 Speaker 6: so you're. 267 00:14:38,320 --> 00:14:39,400 Speaker 1: Basically more of this. 268 00:14:39,400 --> 00:14:42,200 Speaker 6: This pricing is coming to in Nvidia because they're giving 269 00:14:42,200 --> 00:14:44,240 Speaker 6: you so much more performance for the same dollar. 270 00:14:45,640 --> 00:14:48,720 Speaker 3: So the big unknown is the long term ability to 271 00:14:48,840 --> 00:14:51,440 Speaker 3: sell chips into China. This is what collect Cres the 272 00:14:51,440 --> 00:14:55,560 Speaker 3: CFO said in the letter to shareholders that basically there 273 00:14:55,560 --> 00:14:57,680 Speaker 3: will be an impact in the fiscal for from US 274 00:14:57,720 --> 00:15:01,040 Speaker 3: technology curves right, and they will ship bless the China 275 00:15:01,480 --> 00:15:04,640 Speaker 3: in that quarter, but they will more than make up 276 00:15:04,760 --> 00:15:08,520 Speaker 3: for it in growth or offset by strong growth in 277 00:15:08,600 --> 00:15:11,960 Speaker 3: other regions. How do you price in the China risk 278 00:15:12,040 --> 00:15:12,640 Speaker 3: on this stock? 279 00:15:13,800 --> 00:15:17,040 Speaker 6: Well, for right now, for the January quarter guidance, there's 280 00:15:17,240 --> 00:15:20,760 Speaker 6: very little China in there right now, so you know, 281 00:15:20,840 --> 00:15:24,280 Speaker 6: to some extent that's been de risked already. We also 282 00:15:24,400 --> 00:15:26,680 Speaker 6: when a company talked on the call, and our own 283 00:15:26,760 --> 00:15:29,320 Speaker 6: checks have been indicating that there is a new chip 284 00:15:29,360 --> 00:15:31,520 Speaker 6: that will be compliant with China that will come out 285 00:15:31,560 --> 00:15:34,200 Speaker 6: in the first half of next year. You would imagine 286 00:15:34,240 --> 00:15:36,400 Speaker 6: that there's some pent up demand for that chip since 287 00:15:36,440 --> 00:15:39,080 Speaker 6: that you know, they can't ship it in the January quarter. 288 00:15:39,720 --> 00:15:42,720 Speaker 6: The question that management doesn't know is what's going to 289 00:15:42,720 --> 00:15:46,400 Speaker 6: be the reception of this chip in China. And it's 290 00:15:46,440 --> 00:15:49,000 Speaker 6: going to have less performance because that's what's required to 291 00:15:49,000 --> 00:15:54,160 Speaker 6: meet the new regulations, but you know, what are the 292 00:15:54,240 --> 00:15:56,840 Speaker 6: Chinese going to do with it? Our view is that 293 00:15:56,880 --> 00:15:59,200 Speaker 6: we think there's the Chinese customers are still going to 294 00:15:59,200 --> 00:16:01,680 Speaker 6: buy it because there's really no alternative in the marketplace 295 00:16:01,760 --> 00:16:06,520 Speaker 6: right now. And the problem is that there are local 296 00:16:07,080 --> 00:16:12,360 Speaker 6: Chinese alternatives from from folks like Huaweih for example, but 297 00:16:12,720 --> 00:16:16,960 Speaker 6: that's also a company with manufacturing restrictions on China. So 298 00:16:18,000 --> 00:16:20,840 Speaker 6: they can build an ANI chap, they can design an 299 00:16:20,880 --> 00:16:22,920 Speaker 6: AI chip, but they can't build it with leading edge 300 00:16:22,960 --> 00:16:27,760 Speaker 6: technology because Chinese manufacturing facilities don't have access to that. So, 301 00:16:28,160 --> 00:16:29,840 Speaker 6: you know, none of it is we think the Chinese 302 00:16:29,840 --> 00:16:31,760 Speaker 6: are going to have to buy in video product, even 303 00:16:31,840 --> 00:16:34,720 Speaker 6: if it's less performance, because that's all what's going to be. 304 00:16:34,680 --> 00:16:38,880 Speaker 3: A beltwright Chris Chris Casso, Wolf Research Managing director covering 305 00:16:38,880 --> 00:16:40,880 Speaker 3: Semis with tie on time. But we're grateful to have 306 00:16:40,920 --> 00:16:42,560 Speaker 3: you on the show. Thank you know. Coming up here 307 00:16:42,560 --> 00:16:47,240 Speaker 3: on b tech Binance, ceocz pleads guilty to anti money 308 00:16:47,440 --> 00:16:51,000 Speaker 3: laundering and US sanctions violations of Jilak. Joe Bamputra, founder 309 00:16:51,000 --> 00:16:53,840 Speaker 3: and managing partner of Future Perfect Ventures, is our guest 310 00:16:53,880 --> 00:17:13,399 Speaker 3: with the take. Next. This has been bog Technology. Another 311 00:17:13,480 --> 00:17:17,440 Speaker 3: story we're watching finance after its CEO, Cheng Peng Chao 312 00:17:17,720 --> 00:17:21,480 Speaker 3: pleaded guilty to anti monitoring money laundering in US sanctions 313 00:17:21,520 --> 00:17:24,719 Speaker 3: violations under a sweeping settlement with the US that allows 314 00:17:24,760 --> 00:17:29,520 Speaker 3: the crypto exchange to continue operating. Coinbased CEO Brian Armstrong, 315 00:17:29,560 --> 00:17:33,240 Speaker 3: a competitor, joined Bloomberg Tuesday to discuss. 316 00:17:33,400 --> 00:17:35,600 Speaker 7: Well, I think this is really a vindication of the 317 00:17:35,640 --> 00:17:38,359 Speaker 7: long term strategy that coinbase has taken to build a 318 00:17:38,400 --> 00:17:41,800 Speaker 7: trusted and regulated company, going back to twenty twelve. We 319 00:17:41,840 --> 00:17:44,439 Speaker 7: really decided to do that and got the licenses and 320 00:17:44,480 --> 00:17:46,880 Speaker 7: got the teams in place that were necessary to run 321 00:17:46,880 --> 00:17:49,560 Speaker 7: that type of company, and then every few years we 322 00:17:49,600 --> 00:17:51,720 Speaker 7: did see a new company come on the scenes that 323 00:17:51,760 --> 00:17:54,159 Speaker 7: didn't take that approach. Sometimes they would grow very quickly 324 00:17:54,680 --> 00:17:56,680 Speaker 7: because they were able to offer products that we didn't 325 00:17:56,720 --> 00:18:00,560 Speaker 7: think were legal. But inevitably they do come rashing down. 326 00:18:00,600 --> 00:18:03,240 Speaker 7: You know, regulators do eventually act even if they don't 327 00:18:03,240 --> 00:18:05,199 Speaker 7: act quickly, and that's what we saw here in this 328 00:18:05,280 --> 00:18:08,480 Speaker 7: case today. So it's not only been I think, an 329 00:18:08,520 --> 00:18:11,879 Speaker 7: opportunity for coinbase to step in, but it's also an 330 00:18:11,880 --> 00:18:13,919 Speaker 7: opportunity for the industry I think to turn the page 331 00:18:13,920 --> 00:18:16,600 Speaker 7: here and say that, yeah, some of the rules are 332 00:18:16,640 --> 00:18:19,880 Speaker 7: clear around AMLKYIC oh fact that the issues that Finance 333 00:18:19,960 --> 00:18:23,960 Speaker 7: really had you know, stepped over line on, but some 334 00:18:24,160 --> 00:18:25,760 Speaker 7: areas of the law are not yet clear. We need 335 00:18:25,800 --> 00:18:28,040 Speaker 7: to go get that regulatory clarity to make sure that 336 00:18:28,119 --> 00:18:30,200 Speaker 7: the future of this industry is built here in America, 337 00:18:30,320 --> 00:18:33,399 Speaker 7: not on offshore underregulated exchanges. And so that's what we 338 00:18:33,400 --> 00:18:35,240 Speaker 7: need to go do next, and I think it'll prevent 339 00:18:35,240 --> 00:18:36,720 Speaker 7: this kind of activity in the future. 340 00:18:36,840 --> 00:18:40,160 Speaker 8: Well, listen, even with this crackdown that you're seeing, there 341 00:18:40,200 --> 00:18:45,520 Speaker 8: were some really scathing allegations in the DJ's crackdown sanctions violations, 342 00:18:45,880 --> 00:18:47,679 Speaker 8: illegal trafficking of drugs. 343 00:18:47,920 --> 00:18:50,680 Speaker 3: You know, how do you know that this is it? 344 00:18:51,119 --> 00:18:52,960 Speaker 8: How do you know that there are not more bad 345 00:18:52,960 --> 00:18:56,320 Speaker 8: actors out there that would continue to stay in crypto? 346 00:18:56,680 --> 00:18:58,800 Speaker 7: Well, I can tell you the companies that I really 347 00:18:58,880 --> 00:19:01,439 Speaker 7: engage with, at least especially the ones here built in 348 00:19:01,440 --> 00:19:04,159 Speaker 7: the United States, they don't get to big headlines because 349 00:19:04,280 --> 00:19:07,639 Speaker 7: it's not salacious. They haven't you know, rocketed up because 350 00:19:08,080 --> 00:19:10,280 Speaker 7: you know they're not following the rules. But there are 351 00:19:10,440 --> 00:19:15,280 Speaker 7: dozens of really well intentioned and well funded and compliant 352 00:19:15,359 --> 00:19:17,639 Speaker 7: US based crypto companies that are building this industry. I mean, 353 00:19:17,680 --> 00:19:20,240 Speaker 7: you have to remember that fifty two million Americans have 354 00:19:20,400 --> 00:19:24,119 Speaker 7: used crypto now about four hundred million people globally. And 355 00:19:24,200 --> 00:19:27,200 Speaker 7: so while there is there are bad actors who try 356 00:19:27,240 --> 00:19:29,600 Speaker 7: to use crypto, the best data we have is that 357 00:19:29,600 --> 00:19:32,119 Speaker 7: that's less than one percent of the activity is for 358 00:19:32,119 --> 00:19:34,680 Speaker 7: illicit purposes. By the way, the US dollar cash is 359 00:19:34,720 --> 00:19:38,320 Speaker 7: about four percent illicted activity. So crypto is really not 360 00:19:38,440 --> 00:19:42,200 Speaker 7: uniquely crime ridden. And the centralized actors in crypto, they 361 00:19:42,240 --> 00:19:45,960 Speaker 7: need to follow these rules around transaction monitoring and kyc AML, 362 00:19:46,119 --> 00:19:47,919 Speaker 7: just that like coinbase has been doing for over a 363 00:19:47,960 --> 00:19:51,280 Speaker 7: decade now to make sure bad actors don't take advantage 364 00:19:51,280 --> 00:19:51,920 Speaker 7: of these systems. 365 00:19:52,160 --> 00:19:56,080 Speaker 3: That was Coinbase CEO Brian Armstrong along with Bloomberg Shnale Bassett. 366 00:19:56,160 --> 00:19:58,679 Speaker 3: Let's keep the conversation going. So much has happened in 367 00:19:58,720 --> 00:20:02,120 Speaker 3: the last twenty four ho job Bampuutra founder, a managing 368 00:20:02,160 --> 00:20:05,680 Speaker 3: partner of Future Perfect Ventures, early stage VC firm zeroed 369 00:20:05,680 --> 00:20:11,600 Speaker 3: in on blockchain, blockchain tech, CRYPTOAI, human computer interaction. Oppose 370 00:20:11,680 --> 00:20:15,600 Speaker 3: the question that Shanali put to Brian Armstrong, when you're 371 00:20:15,640 --> 00:20:18,679 Speaker 3: in this market and investing in this sector, how do 372 00:20:18,760 --> 00:20:21,240 Speaker 3: you know that that's it? That's all there is left 373 00:20:21,240 --> 00:20:21,720 Speaker 3: to come out? 374 00:20:21,880 --> 00:20:23,520 Speaker 9: Well, it's good to talk to you again. At We 375 00:20:23,880 --> 00:20:27,240 Speaker 9: spoke after the FTX ruling, and the way I look 376 00:20:27,280 --> 00:20:30,000 Speaker 9: at this right now is the other shoe has dropped. 377 00:20:30,480 --> 00:20:30,640 Speaker 5: Now. 378 00:20:30,680 --> 00:20:33,960 Speaker 9: We can't guarantee that there's nothing else out there, but 379 00:20:34,080 --> 00:20:36,480 Speaker 9: those of us in the industry have been waiting for 380 00:20:36,560 --> 00:20:39,720 Speaker 9: a while to see what happened with Finance. We know 381 00:20:39,800 --> 00:20:43,720 Speaker 9: that they've been under investigation for several years now. There 382 00:20:43,760 --> 00:20:46,960 Speaker 9: have been a number of allegations against them. CZ has 383 00:20:47,000 --> 00:20:51,280 Speaker 9: been notorious for moving the company to different jurisdictions, first 384 00:20:51,400 --> 00:20:55,159 Speaker 9: China and then Japan and then Malta and so we 385 00:20:55,280 --> 00:20:59,040 Speaker 9: knew something was coming, and the fact that this finally happened, 386 00:20:59,080 --> 00:21:04,320 Speaker 9: these allegations were proven, they've been find cz is out, 387 00:21:04,560 --> 00:21:07,280 Speaker 9: but the exchange is still running, and so I think 388 00:21:07,320 --> 00:21:11,200 Speaker 9: that is an indication that regulators also understand that crypto 389 00:21:11,320 --> 00:21:15,280 Speaker 9: is not going away, but they want to encourage the 390 00:21:15,680 --> 00:21:16,640 Speaker 9: good actors, the. 391 00:21:16,520 --> 00:21:17,960 Speaker 5: Ones that want to be compliant. 392 00:21:18,000 --> 00:21:21,200 Speaker 9: And our portfolio is full of those entrepreneurs and those 393 00:21:21,240 --> 00:21:25,679 Speaker 9: companies and we welcome this and we really want to 394 00:21:25,720 --> 00:21:26,240 Speaker 9: move forward. 395 00:21:26,720 --> 00:21:30,120 Speaker 3: So Jack, we have fifteen seconds. This impact your ability 396 00:21:30,160 --> 00:21:31,240 Speaker 3: to invest, yes or. 397 00:21:31,200 --> 00:21:34,920 Speaker 9: No, It makes it even more of an opportunity. We're 398 00:21:35,000 --> 00:21:37,520 Speaker 9: leveling the playing field for those that do want to 399 00:21:37,520 --> 00:21:41,200 Speaker 9: be compliant, and then we're looking forward to what happens 400 00:21:41,200 --> 00:21:45,760 Speaker 9: with the ETF and more adoption of cryptois. As Ryan 401 00:21:45,880 --> 00:21:47,160 Speaker 9: alluded to in this interviewing. 402 00:21:47,200 --> 00:21:49,560 Speaker 3: All right, jalak, Job and Boucher, we love having you 403 00:21:49,560 --> 00:21:52,560 Speaker 3: on the show. Founder managing partner of Future Perfect Ventures. 404 00:21:52,760 --> 00:22:05,760 Speaker 3: Another big news story is experimenting with AI. Last year, 405 00:22:05,800 --> 00:22:08,879 Speaker 3: Walmart launched a text to shop feature, allowing people to 406 00:22:08,920 --> 00:22:12,320 Speaker 3: pick what to buy, automatically, add it to their online card, 407 00:22:12,720 --> 00:22:15,960 Speaker 3: and check out right from a text message Wallart wants 408 00:22:16,000 --> 00:22:20,240 Speaker 3: to make its app and website just as conversational with AI. 409 00:22:20,480 --> 00:22:23,320 Speaker 3: It's working on a generative AI powered search where you 410 00:22:23,359 --> 00:22:25,600 Speaker 3: can ask a question similar to how you'd ask chat 411 00:22:25,640 --> 00:22:30,040 Speaker 3: GPT on Walwot's app or website and bring up product suggestions, 412 00:22:30,280 --> 00:22:33,720 Speaker 3: for example asking what daycore you need for a housewarming party. 413 00:22:33,760 --> 00:22:36,440 Speaker 3: There's also an AI shopping Assistant in the works where 414 00:22:36,480 --> 00:22:39,199 Speaker 3: customers can chat with a virtual assistant when deciding what 415 00:22:39,320 --> 00:22:41,760 Speaker 3: to buy, like getting a recommendation for what kind of 416 00:22:41,800 --> 00:22:43,840 Speaker 3: cell phone to buy for a ten year old. The 417 00:22:43,880 --> 00:22:47,560 Speaker 3: retailer also introduced augmented reality tools last year to try 418 00:22:47,560 --> 00:22:50,240 Speaker 3: on clothing virtually or see how furniture will look in 419 00:22:50,280 --> 00:22:52,359 Speaker 3: their home. Right now, you can test out how a 420 00:22:52,480 --> 00:22:54,720 Speaker 3: TV will look in your space. For example, you can 421 00:22:54,720 --> 00:22:57,160 Speaker 3: compare different sizes or product suggestions. 422 00:22:57,320 --> 00:22:58,640 Speaker 1: So soon Walmart will. 423 00:22:58,440 --> 00:23:01,040 Speaker 3: Add generative AI into the met You'll be able to 424 00:23:01,080 --> 00:23:04,080 Speaker 3: ask the AI assistant how to decorate a space and 425 00:23:04,119 --> 00:23:06,840 Speaker 3: get suggestions and frighting, as well as see the items 426 00:23:06,920 --> 00:23:10,159 Speaker 3: in the space using the AR technology. Walmar says it's 427 00:23:10,200 --> 00:23:12,840 Speaker 3: training these tools on a variety of AI models that 428 00:23:12,880 --> 00:23:16,520 Speaker 3: are currently available, not one specific large language model. The 429 00:23:16,560 --> 00:23:19,840 Speaker 3: generative AI tools are still in test phase, Walmart says, 430 00:23:19,920 --> 00:23:25,680 Speaker 3: but will be available to customers very soon. Okay, Walmart 431 00:23:25,760 --> 00:23:27,679 Speaker 3: is in the AI games. Let's get into it with 432 00:23:27,720 --> 00:23:31,760 Speaker 3: Walmart US Omni Platforms and Tech Executive Vice president Triny. 433 00:23:32,000 --> 00:23:35,680 Speaker 3: Then contestant Triny, welcome to the program. We outlined some 434 00:23:35,720 --> 00:23:38,240 Speaker 3: of the tools that you guys have been working on 435 00:23:38,400 --> 00:23:42,000 Speaker 3: over at Walmart. Of those that we outlined, what is 436 00:23:42,040 --> 00:23:45,159 Speaker 3: gaining most traction? Right this is about consumer behaviors and 437 00:23:45,200 --> 00:23:48,000 Speaker 3: how we shop. And I guess I'm just curious to 438 00:23:48,040 --> 00:23:50,560 Speaker 3: know which tool you think is going to change the 439 00:23:50,600 --> 00:23:53,840 Speaker 3: game in that respect, Dan. 440 00:23:53,760 --> 00:23:56,280 Speaker 5: Said, foving me on the show at one night. 441 00:23:56,320 --> 00:23:59,399 Speaker 10: We are at the custom dramatic changes that the customers 442 00:23:59,400 --> 00:24:03,160 Speaker 10: are main ways to discover, buy and shop goods right, 443 00:24:03,520 --> 00:24:06,520 Speaker 10: be the speed up delivery, beate the way that they 444 00:24:06,560 --> 00:24:08,879 Speaker 10: want to shop it in an online experience, which is 445 00:24:08,960 --> 00:24:09,880 Speaker 10: very simple for them. 446 00:24:10,320 --> 00:24:12,159 Speaker 5: It has been what we have been trying to do 447 00:24:12,240 --> 00:24:13,960 Speaker 5: is to make it very easy for them to do 448 00:24:14,080 --> 00:24:14,640 Speaker 5: that shopping. 449 00:24:15,440 --> 00:24:18,560 Speaker 10: To your question on what is really getting traction is 450 00:24:18,720 --> 00:24:22,200 Speaker 10: as we think about the GENAI decision assistant and search 451 00:24:22,400 --> 00:24:25,280 Speaker 10: our queries, those are things that the customers are really 452 00:24:25,320 --> 00:24:28,480 Speaker 10: starting to use more and we are seeing positive engagement 453 00:24:28,560 --> 00:24:28,920 Speaker 10: so far. 454 00:24:30,600 --> 00:24:32,520 Speaker 3: Really, given the events in the last five days, I 455 00:24:32,560 --> 00:24:35,359 Speaker 3: have to ask, where does your technology come from the 456 00:24:35,440 --> 00:24:37,920 Speaker 3: underlying large language model? The power is the tool. 457 00:24:39,359 --> 00:24:43,960 Speaker 10: So at Walmart we're always invested in actual intelligence, right, 458 00:24:44,080 --> 00:24:46,680 Speaker 10: or we have invested it in for transportation and other 459 00:24:46,800 --> 00:24:50,159 Speaker 10: our podcasting and other optimizations that has made us what 460 00:24:50,320 --> 00:24:52,000 Speaker 10: we are in our supply chain. 461 00:24:51,760 --> 00:24:53,800 Speaker 5: And in our transportation sector. 462 00:24:54,320 --> 00:24:57,200 Speaker 10: We have taken those learnings and then we now commented 463 00:24:57,200 --> 00:24:59,359 Speaker 10: that with the GENAI tools that are available out in 464 00:24:59,400 --> 00:25:02,560 Speaker 10: the public, not anyone spressit tools. We have done it 465 00:25:02,600 --> 00:25:05,479 Speaker 10: with all large language models, and we are combining that 466 00:25:05,520 --> 00:25:09,560 Speaker 10: with the extensive data with BI which is our Walmart 467 00:25:10,720 --> 00:25:15,160 Speaker 10: catalog and other data that we have seen changing behaviors 468 00:25:15,200 --> 00:25:17,840 Speaker 10: that we have seen, and that's how we have trained 469 00:25:17,840 --> 00:25:19,560 Speaker 10: our AI to make it really powerful. 470 00:25:20,840 --> 00:25:23,800 Speaker 3: Is there a technology relationship with open ai and their 471 00:25:23,840 --> 00:25:25,040 Speaker 3: GPT technology? 472 00:25:26,359 --> 00:25:26,600 Speaker 5: Now? 473 00:25:26,680 --> 00:25:29,800 Speaker 10: We try to be allla agnostic, right. What we're trying 474 00:25:29,840 --> 00:25:32,240 Speaker 10: to basically get at is how do we get the 475 00:25:32,480 --> 00:25:37,080 Speaker 10: language understanding correct? What pretty much every other provider we've 476 00:25:37,119 --> 00:25:38,160 Speaker 10: tried it with open ai. 477 00:25:38,280 --> 00:25:41,160 Speaker 5: We use Google tools and we also use other open 478 00:25:41,280 --> 00:25:44,760 Speaker 5: open source tools like Lama. What your phocused on is. 479 00:25:44,680 --> 00:25:48,399 Speaker 10: What we call walnot embeddings, which are our internal data 480 00:25:48,480 --> 00:25:51,280 Speaker 10: that we really train the models on which stumbled with 481 00:25:51,320 --> 00:25:52,160 Speaker 10: the query understanding. 482 00:25:52,240 --> 00:25:54,080 Speaker 5: That's it very powerful Twinny. 483 00:25:54,560 --> 00:25:57,919 Speaker 3: In the retail context, what are the biggest pitfalls and 484 00:25:58,040 --> 00:26:01,800 Speaker 3: risks with bringing generator to ai technology into the kind 485 00:26:01,840 --> 00:26:05,880 Speaker 3: of sales and transaction stage of your relationship with the customer. 486 00:26:06,400 --> 00:26:09,359 Speaker 10: I think there are twos you can look at again, 487 00:26:09,600 --> 00:26:11,520 Speaker 10: like the way that we have trying to frame it 488 00:26:11,560 --> 00:26:14,720 Speaker 10: as like what is the customer really looking for? Like 489 00:26:14,840 --> 00:26:16,920 Speaker 10: what are they really trying to do in a way 490 00:26:17,320 --> 00:26:20,240 Speaker 10: that makes the shopping experience better? So what we've seen 491 00:26:20,400 --> 00:26:23,520 Speaker 10: is the shoppers are doing multiple sessions and multiple things 492 00:26:23,640 --> 00:26:24,680 Speaker 10: to really. 493 00:26:24,560 --> 00:26:26,400 Speaker 5: Shop multiple products. 494 00:26:26,640 --> 00:26:28,280 Speaker 10: What we are really trying to honest, a lot of 495 00:26:28,320 --> 00:26:31,800 Speaker 10: genai is explaining my problem and I can get all 496 00:26:31,840 --> 00:26:34,439 Speaker 10: the multi products search at the same time. So I 497 00:26:34,480 --> 00:26:37,880 Speaker 10: think that is kind of people prow of genai. What 498 00:26:37,920 --> 00:26:41,120 Speaker 10: it does is it basically understands that very very much 499 00:26:41,119 --> 00:26:44,000 Speaker 10: more I easily, and it's actually able to make your 500 00:26:44,000 --> 00:26:47,760 Speaker 10: shopping experience much more simpler. Again, there are going to 501 00:26:47,760 --> 00:26:50,399 Speaker 10: be learning out of it as we discover our people 502 00:26:50,480 --> 00:26:53,199 Speaker 10: actually interact with it in a conversational way, and that 503 00:26:53,359 --> 00:26:55,840 Speaker 10: is where our model training and our improvements are going 504 00:26:55,880 --> 00:26:58,400 Speaker 10: to make sure that we are leaning on the right 505 00:26:58,440 --> 00:26:59,360 Speaker 10: side for the customer. 506 00:26:59,560 --> 00:27:04,120 Speaker 3: Boma US Omniplatforms Tech Executive Vice President Shriney then can 507 00:27:04,240 --> 00:27:06,639 Speaker 3: tassen thank you so much for your time here on 508 00:27:06,720 --> 00:27:08,760 Speaker 3: bloom Bag Technology. We have so much more head and 509 00:27:08,840 --> 00:27:11,640 Speaker 3: we get back. It's the big story of the week. 510 00:27:11,720 --> 00:27:23,080 Speaker 3: This is Blion Big Technology. 511 00:27:29,600 --> 00:27:31,840 Speaker 11: We continue to be committed to open ai, and we 512 00:27:31,880 --> 00:27:34,639 Speaker 11: continue to be committed to Sam and Greg and the 513 00:27:34,720 --> 00:27:36,760 Speaker 11: team in respect you where they are. 514 00:27:36,880 --> 00:27:39,800 Speaker 3: I've never seen this in my coverage attack in twenty years. 515 00:27:39,880 --> 00:27:42,879 Speaker 5: I think transparency is key. That's a lesson from this weekend. 516 00:27:42,960 --> 00:27:45,560 Speaker 1: My number one day is none doesn't twar. 517 00:27:45,760 --> 00:27:49,520 Speaker 4: The capped profit model that open ai was spearheading was 518 00:27:49,560 --> 00:27:50,720 Speaker 4: more of an experiment. 519 00:27:50,960 --> 00:27:53,760 Speaker 8: I haven't seen this specific structure anywhere else, and I 520 00:27:53,800 --> 00:27:55,439 Speaker 8: can't imagine we ever will again. 521 00:27:55,640 --> 00:27:57,360 Speaker 2: After the debacle that this all was. 522 00:27:57,359 --> 00:28:00,480 Speaker 11: We definitely will want some governance changes so they you know, 523 00:28:00,840 --> 00:28:01,920 Speaker 11: surprises are bad. 524 00:28:04,920 --> 00:28:07,560 Speaker 3: Just some of the many voices we've had on Bloomberg 525 00:28:07,600 --> 00:28:11,639 Speaker 3: this week reacting to the open Ai saga. For more, 526 00:28:12,280 --> 00:28:14,960 Speaker 3: Let's bring in the founder of Coasta Ventures, Vino Kosla, 527 00:28:15,960 --> 00:28:19,960 Speaker 3: the first venture check written to open AI. Mister Coasla, 528 00:28:20,000 --> 00:28:22,320 Speaker 3: good morning to you. Thank you for your time on 529 00:28:22,400 --> 00:28:23,560 Speaker 3: Bloomberg Technology. 530 00:28:23,760 --> 00:28:27,320 Speaker 11: Great to be here on a hopefully good occasion. 531 00:28:28,320 --> 00:28:31,600 Speaker 3: Well, I get the sense from your posts on X 532 00:28:31,720 --> 00:28:34,119 Speaker 3: that for you this is a good occasion. But just 533 00:28:34,680 --> 00:28:39,320 Speaker 3: start with your reaction to Sam Altman being reinstalled at 534 00:28:39,360 --> 00:28:39,920 Speaker 3: open AI. 535 00:28:41,200 --> 00:28:44,960 Speaker 11: I've stated this before and I'm con stated again. I'm 536 00:28:45,080 --> 00:28:49,920 Speaker 11: very happy to see Sam Beck. He's uniquely positioned to 537 00:28:51,120 --> 00:28:53,640 Speaker 11: for Stuard Chip after this very important company. 538 00:28:54,120 --> 00:28:56,080 Speaker 1: It's much more than just a company. 539 00:28:56,320 --> 00:29:00,720 Speaker 11: It is benefit b FAI to humanity you much larger 540 00:29:00,760 --> 00:29:04,120 Speaker 11: way over the next few decades, and I think we 541 00:29:04,280 --> 00:29:05,240 Speaker 11: restored the patch. 542 00:29:06,160 --> 00:29:10,840 Speaker 3: Mister Kosler, you outlined a thesis that when the board 543 00:29:10,960 --> 00:29:13,280 Speaker 3: on Friday, or the board as it was then on Friday, 544 00:29:13,400 --> 00:29:18,400 Speaker 3: fired Sam Outman, they set back artificial intelligence. Why was 545 00:29:18,400 --> 00:29:19,920 Speaker 3: that the conclusion that you reached? 546 00:29:20,680 --> 00:29:24,560 Speaker 11: Mostly because Sam is uniquely qualified to shepherd this and 547 00:29:24,600 --> 00:29:27,360 Speaker 11: he has a vision over the next decade or two 548 00:29:27,880 --> 00:29:32,040 Speaker 11: of what AI can do. I can't imagine somebody else 549 00:29:32,360 --> 00:29:36,640 Speaker 11: being able to step on those shoes easily and without 550 00:29:36,680 --> 00:29:40,440 Speaker 11: a lot of risks to the mission of what Opening Eye. 551 00:29:40,400 --> 00:29:43,719 Speaker 3: Was, Vinode. When I posted on x that you were 552 00:29:43,720 --> 00:29:45,440 Speaker 3: coming on the show, there was a lot of interest. 553 00:29:45,760 --> 00:29:49,600 Speaker 3: You were the first venture investor in open AI, and 554 00:29:49,640 --> 00:29:53,920 Speaker 3: there was this very specific question posed for you, which is, 555 00:29:54,400 --> 00:29:56,760 Speaker 3: and forgive the framing of the question, but this is 556 00:29:56,800 --> 00:30:00,880 Speaker 3: what the audience asks. What happens if Sam Altman gets 557 00:30:00,920 --> 00:30:05,000 Speaker 3: hit by a bus? What happens if Sam Altman is 558 00:30:05,040 --> 00:30:08,560 Speaker 3: discovered to have had some wrongdoing. What happens to open 559 00:30:08,600 --> 00:30:09,640 Speaker 3: AI in that scenario. 560 00:30:11,040 --> 00:30:14,400 Speaker 11: Here are other people at OPENINGI who are very qualified 561 00:30:14,440 --> 00:30:17,480 Speaker 11: to do that. Greg Brockman would be among my favorites 562 00:30:17,560 --> 00:30:20,760 Speaker 11: in the current Opening I team, and I think they 563 00:30:20,760 --> 00:30:23,360 Speaker 11: should de risk this by adding more people to the 564 00:30:23,400 --> 00:30:26,920 Speaker 11: team who can step in. But if he does get 565 00:30:26,960 --> 00:30:29,360 Speaker 11: hit by a bus, I think we would have to 566 00:30:30,280 --> 00:30:33,920 Speaker 11: do with Greg Brockman, who is very much after the 567 00:30:33,960 --> 00:30:36,560 Speaker 11: same vision and mission Vinode. 568 00:30:36,600 --> 00:30:38,920 Speaker 3: What we're talking about, I guess is key man risk 569 00:30:39,040 --> 00:30:42,640 Speaker 3: and just as you have you know, I've been reporting 570 00:30:42,680 --> 00:30:46,959 Speaker 3: on the story since Friday lunchtime, considering what's happening, But 571 00:30:47,200 --> 00:30:49,720 Speaker 3: the takeaway has been that the value of open Ai 572 00:30:49,840 --> 00:30:54,600 Speaker 3: appears to be the intellectual capital right of its people. 573 00:30:55,280 --> 00:31:01,520 Speaker 3: And when Microsoft reacted to the news, the idea was 574 00:31:01,640 --> 00:31:03,840 Speaker 3: in the kind of mutiny that was going on, that 575 00:31:04,480 --> 00:31:07,280 Speaker 3: those people would simply go and join Microsoft, And I 576 00:31:07,320 --> 00:31:10,360 Speaker 3: wondered what you thought about that eventuality, which to some 577 00:31:10,400 --> 00:31:12,800 Speaker 3: extent now is academic, but there is still a close 578 00:31:12,840 --> 00:31:13,800 Speaker 3: tie between the two. 579 00:31:14,280 --> 00:31:17,360 Speaker 11: I think the close eye helps make this make progress 580 00:31:17,360 --> 00:31:21,480 Speaker 11: in AI because it needs a lot of resources. And frankly, 581 00:31:21,600 --> 00:31:25,120 Speaker 11: I'm very pleased that open ai is there. Google is there, 582 00:31:25,400 --> 00:31:28,080 Speaker 11: and there's at least two major efforts a few other 583 00:31:28,680 --> 00:31:32,800 Speaker 11: credible efforts in the AI industry, So I do think 584 00:31:32,880 --> 00:31:38,120 Speaker 11: Microsoft's support. Microsoft supporting open Ai really helps it move 585 00:31:38,120 --> 00:31:42,560 Speaker 11: it along, give it the resources Google has internally, and more. 586 00:31:42,400 --> 00:31:44,520 Speaker 1: Competition is generally a good. 587 00:31:44,320 --> 00:31:48,920 Speaker 11: Thing, and more ais will make progress move faster. 588 00:31:49,280 --> 00:31:50,800 Speaker 1: So I'm very happy with that. 589 00:31:53,200 --> 00:31:56,520 Speaker 11: I won't comment on open Ai team becoming a part 590 00:31:56,560 --> 00:32:00,920 Speaker 11: of Microsoft Ai. I always believe we would find a resolution. 591 00:32:01,120 --> 00:32:03,840 Speaker 11: It was only a matter of time, so I was 592 00:32:04,160 --> 00:32:09,000 Speaker 11: I had complete faith in this solution. In fact, my 593 00:32:09,120 --> 00:32:12,600 Speaker 11: conversation with Sam around noon on Friday, and the first 594 00:32:12,640 --> 00:32:15,000 Speaker 11: one announced is that I don't think it's over. It 595 00:32:15,080 --> 00:32:20,440 Speaker 11: was my first comment back to Sam. 596 00:32:18,800 --> 00:32:21,760 Speaker 3: You didn't think it was over Friday lunchtime. It seems 597 00:32:21,760 --> 00:32:25,120 Speaker 3: like an eternity ago that it was Friday lunchtime when 598 00:32:25,160 --> 00:32:28,520 Speaker 3: the headlines broke. I mean it is an issue of 599 00:32:28,560 --> 00:32:31,120 Speaker 3: the board in corporate governance, right, And what we know 600 00:32:31,280 --> 00:32:34,840 Speaker 3: is that Brett Taylor, at least on an interim basis, 601 00:32:35,240 --> 00:32:37,920 Speaker 3: joins the board along with Larry Summers. For our audience, 602 00:32:38,000 --> 00:32:41,080 Speaker 3: Larry Summers is a paid contributor of Bloomberg Television. And 603 00:32:41,120 --> 00:32:44,800 Speaker 3: then my understanding is Adam DeAngelo stays at the board. 604 00:32:45,760 --> 00:32:48,440 Speaker 3: To your mind, as an investor in this company, you 605 00:32:48,600 --> 00:32:52,360 Speaker 3: know those names in Silicon Valley? Is this addressing the 606 00:32:52,440 --> 00:32:55,120 Speaker 3: corporate governance question enough? 607 00:32:58,280 --> 00:33:00,840 Speaker 11: I've been on a board with Larry Summer at Square 608 00:33:00,960 --> 00:33:07,120 Speaker 11: or now called Block, and I admired Larry. I think 609 00:33:08,200 --> 00:33:12,840 Speaker 11: over time the board will build up to more governance. 610 00:33:12,960 --> 00:33:15,360 Speaker 11: And I think three is a small board, but over 611 00:33:15,440 --> 00:33:18,640 Speaker 11: time there'll be more governance and better process. I think 612 00:33:18,680 --> 00:33:24,600 Speaker 11: we've learned an important lesson on governance here. And frankly, 613 00:33:24,760 --> 00:33:32,400 Speaker 11: I didn't, in my remote imagination imagine that something like 614 00:33:32,480 --> 00:33:36,120 Speaker 11: this could happen or the board would do this. There 615 00:33:36,120 --> 00:33:40,000 Speaker 11: were some errant people on the board who misinterpreted their 616 00:33:40,040 --> 00:33:47,640 Speaker 11: own religion around EA or effective altruism. I think this 617 00:33:47,880 --> 00:33:51,880 Speaker 11: was really arran surprising, shocking in every way it was, 618 00:33:53,080 --> 00:33:57,760 Speaker 11: but totally unexpected under almost any circumstance, and the employees 619 00:33:57,880 --> 00:34:02,040 Speaker 11: of Opening Eye spoke it by offering to join Sam 620 00:34:02,200 --> 00:34:03,320 Speaker 11: in whatever he did. 621 00:34:05,000 --> 00:34:08,120 Speaker 3: Vinod, I would love to get into the EA an 622 00:34:08,360 --> 00:34:10,880 Speaker 3: X threat debate. We will in just a moment. But 623 00:34:11,080 --> 00:34:15,320 Speaker 3: just you just mentioned what you see as bad actors. 624 00:34:15,640 --> 00:34:19,320 Speaker 3: Do you know definitively as an investor in this company, 625 00:34:19,600 --> 00:34:22,400 Speaker 3: and you said that you'd spoken to Sam Friday at midday? 626 00:34:22,960 --> 00:34:25,440 Speaker 3: Do you have a clear sense on why Sam was 627 00:34:25,480 --> 00:34:26,720 Speaker 3: fired in the first place. 628 00:34:27,440 --> 00:34:30,560 Speaker 11: I have not talked to the board members who participated 629 00:34:30,719 --> 00:34:35,719 Speaker 11: in that discussion. In frankly, a very little interest in 630 00:34:35,800 --> 00:34:39,439 Speaker 11: talking to the two members that left, but I think 631 00:34:39,440 --> 00:34:42,360 Speaker 11: it's certain behavior on their part. It was, of course, 632 00:34:42,600 --> 00:34:47,400 Speaker 11: as widely reported, triggered by Ilia or having some concerns. 633 00:34:47,400 --> 00:34:50,279 Speaker 11: And Ilia has since changed his mind, and I'm very 634 00:34:51,239 --> 00:34:54,680 Speaker 11: admire Ilia a lot for changing his mind publicly. 635 00:34:54,760 --> 00:34:57,080 Speaker 1: I think he deserves real kudos for that. 636 00:34:57,719 --> 00:35:00,880 Speaker 11: But no, I haven't talked to the board direct that 637 00:35:01,040 --> 00:35:05,600 Speaker 11: made this decision without Sam without Greg, so I couldn't 638 00:35:05,600 --> 00:35:06,480 Speaker 11: speak to it further. 639 00:35:06,960 --> 00:35:10,040 Speaker 3: And to be clear, you were in the school of 640 00:35:10,080 --> 00:35:13,920 Speaker 3: thought that Ilia deserves a second chance to carry on 641 00:35:14,040 --> 00:35:17,920 Speaker 3: or continue with open AI. Absolutely, So let's get to 642 00:35:17,960 --> 00:35:21,080 Speaker 3: the debate, the existential threat debate. You know, much of 643 00:35:21,120 --> 00:35:24,560 Speaker 3: what's been discussed is a philosophical point of difference. Right, 644 00:35:24,719 --> 00:35:28,719 Speaker 3: Sam as least, as I've reported, he's the products guy. Right, 645 00:35:28,840 --> 00:35:33,040 Speaker 3: he leads the global negotiation with policymakers. He is the 646 00:35:33,040 --> 00:35:36,719 Speaker 3: one that attracts the talent. And the board was as 647 00:35:36,719 --> 00:35:40,400 Speaker 3: a Friday, largely made up of academics who seemed to 648 00:35:40,640 --> 00:35:44,200 Speaker 3: have an emphasis on the existential threat that AI poses 649 00:35:44,320 --> 00:35:48,799 Speaker 3: to humankind. Where do you stand on that debate of 650 00:35:48,800 --> 00:35:53,640 Speaker 3: commercialization versus slowing down looking at what the risks are? 651 00:35:54,160 --> 00:35:58,719 Speaker 11: I published penderpiece for the Information at the Information dot 652 00:35:58,760 --> 00:36:03,839 Speaker 11: Com this week on this risk issue and what I 653 00:36:03,960 --> 00:36:09,240 Speaker 11: feel happened. Humanity face is the basket of risk sentient AI. 654 00:36:10,280 --> 00:36:14,359 Speaker 11: Existential risk is no different than an asteroid hitting the 655 00:36:14,360 --> 00:36:21,040 Speaker 11: planet either. There's risks that humanity faces. This basket of 656 00:36:21,160 --> 00:36:24,279 Speaker 11: risk has to be balanced against the basket of opportunity 657 00:36:24,800 --> 00:36:29,000 Speaker 11: to free humanity from the slavery of really bad hourly 658 00:36:29,120 --> 00:36:31,560 Speaker 11: jobs where you do the same thing for eight hours 659 00:36:31,600 --> 00:36:35,880 Speaker 11: a day reputatively for thirty years of your career, or 660 00:36:36,000 --> 00:36:42,160 Speaker 11: where you can have free doctors available to everybody on 661 00:36:42,200 --> 00:36:46,320 Speaker 11: the prompt planet, or near free doctors and near free tutors, 662 00:36:47,040 --> 00:36:51,560 Speaker 11: and my wife's nonprofits se K twelve dot org is 663 00:36:51,760 --> 00:36:56,160 Speaker 11: providing for free free tutors to everybody in conjunction with 664 00:36:56,239 --> 00:36:59,600 Speaker 11: open AI on their website. 665 00:37:00,760 --> 00:37:01,800 Speaker 1: And in the open app. 666 00:37:02,040 --> 00:37:09,080 Speaker 11: But chat GPT stored those kinds of benefits and including 667 00:37:09,360 --> 00:37:12,799 Speaker 11: half the people on the planet from the kind of 668 00:37:12,840 --> 00:37:19,040 Speaker 11: slavery that hourly repetitive jobs afford them, and enough GDP 669 00:37:19,200 --> 00:37:24,080 Speaker 11: growth to pay for that those people is what the 670 00:37:24,120 --> 00:37:28,400 Speaker 11: opportunity is. So risks have to be balanced against opportunity, 671 00:37:28,480 --> 00:37:32,000 Speaker 11: and that has been fundamentally missing. There's a very very 672 00:37:32,080 --> 00:37:38,200 Speaker 11: high risk of China having superior AI and interfering starting 673 00:37:38,239 --> 00:37:42,160 Speaker 11: next year in our twenty twenty four election with persuasive 674 00:37:42,239 --> 00:37:47,040 Speaker 11: AI that convinces voters to persuay save arguments in personal lives. 675 00:37:47,480 --> 00:37:50,400 Speaker 1: There are many many risks that have to be balanced. 676 00:37:50,840 --> 00:37:55,680 Speaker 11: Not just one exist from a movie science sci fi 677 00:37:55,840 --> 00:38:01,759 Speaker 11: movie Fantasy Gone Wild that says or robots takeover and 678 00:38:01,800 --> 00:38:08,200 Speaker 11: destroyed the humans. That's pretty silly in the basket of 679 00:38:08,360 --> 00:38:11,720 Speaker 11: risks we are actually dealing with, and there's serious risks 680 00:38:11,800 --> 00:38:14,960 Speaker 11: we need to address, and in both this weekend's paper, 681 00:38:15,120 --> 00:38:18,880 Speaker 11: in a blog I published on China as our principal 682 00:38:19,000 --> 00:38:23,520 Speaker 11: risk in AI a few weeks ago in medium dot com. 683 00:38:24,080 --> 00:38:26,520 Speaker 11: But what looking at and I think they need to 684 00:38:26,560 --> 00:38:29,479 Speaker 11: be treated seriously, but not this way. 685 00:38:30,880 --> 00:38:33,920 Speaker 3: Veno, thank you for outlining that thesis. I want to 686 00:38:33,920 --> 00:38:36,400 Speaker 3: get back to the corporate governance, the not for profit 687 00:38:36,520 --> 00:38:40,480 Speaker 3: versus the for profit. Yesterday we had Josh Wolf of 688 00:38:40,600 --> 00:38:42,759 Speaker 3: Lux Capital on the show. I think that's something you 689 00:38:42,800 --> 00:38:45,439 Speaker 3: probably know, and he said the first thing that Sam 690 00:38:45,480 --> 00:38:48,520 Speaker 3: Altman should do when he returns to open AI is 691 00:38:48,640 --> 00:38:52,879 Speaker 3: take open AI public. Do an IPO. Your response to that. 692 00:38:53,360 --> 00:38:55,319 Speaker 11: You know, I'm not going to comment on what they 693 00:38:55,320 --> 00:38:58,200 Speaker 11: should do. I think open Aie is in a good position. 694 00:38:58,480 --> 00:39:00,480 Speaker 11: It's a good financial position. 695 00:39:00,600 --> 00:39:03,719 Speaker 1: The only reason to go public would be. 696 00:39:05,400 --> 00:39:08,600 Speaker 11: Would be because it needs more resources, and I don't 697 00:39:08,600 --> 00:39:12,080 Speaker 11: think it needs more resources right now. What I would 698 00:39:12,160 --> 00:39:15,520 Speaker 11: say the structure is not as unusual that people make 699 00:39:15,600 --> 00:39:19,840 Speaker 11: it out to be. There's companies in Europe owned by nonprofits, 700 00:39:19,880 --> 00:39:24,880 Speaker 11: so at least significantly owned and controlled by nonprofits, So 701 00:39:25,000 --> 00:39:30,040 Speaker 11: that structure has existed in Europe before, and I think 702 00:39:30,760 --> 00:39:33,520 Speaker 11: there's nothing wrong with the structure. There was something wrong 703 00:39:33,600 --> 00:39:36,680 Speaker 11: with the government, and I hope or the next year 704 00:39:36,800 --> 00:39:37,680 Speaker 11: we can fix that. 705 00:39:38,239 --> 00:39:42,000 Speaker 3: Mister Coastler. Finally, a lot of people are thinking about 706 00:39:42,000 --> 00:39:45,160 Speaker 3: the seven hundred and seventy open AI employees. One point 707 00:39:45,320 --> 00:39:47,799 Speaker 3: was made to me by sources and the valley is 708 00:39:48,280 --> 00:39:52,960 Speaker 3: this pending tender presented potentially life changing amounts of money 709 00:39:52,960 --> 00:39:55,239 Speaker 3: for those people, and they were willing to put it 710 00:39:55,560 --> 00:39:59,160 Speaker 3: on hold or jeopardize it. In sticking with Sam, do 711 00:39:59,239 --> 00:40:01,600 Speaker 3: you know what the late on the tender is and 712 00:40:01,640 --> 00:40:02,800 Speaker 3: your thoughts on the staff. 713 00:40:03,920 --> 00:40:06,319 Speaker 11: I think it's too early to comment, Kanek, but I 714 00:40:06,440 --> 00:40:10,560 Speaker 11: don't know any reason the world will be any different 715 00:40:10,680 --> 00:40:13,280 Speaker 11: tomorrow than what it was on Thursday evening. 716 00:40:14,040 --> 00:40:17,560 Speaker 3: Okay, Coastla Ventures founder Vino Costa, I'm incredibly grateful for 717 00:40:17,640 --> 00:40:21,000 Speaker 3: your time. We asked all of your investor counterparts to 718 00:40:21,080 --> 00:40:23,399 Speaker 3: join us in the show. You said yes, and we're 719 00:40:23,400 --> 00:40:25,120 Speaker 3: grateful for it. Thank you for your time. This is 720 00:40:25,160 --> 00:40:36,880 Speaker 3: Bloomberg Technology, Okay. Also in the news talking tech first Up, 721 00:40:36,920 --> 00:40:40,359 Speaker 3: North Korea is claiming a victory that it successfully put 722 00:40:40,400 --> 00:40:44,400 Speaker 3: a spy satellite into orbit, moving Kim Jongen closer to 723 00:40:44,480 --> 00:40:46,920 Speaker 3: his pledge to keep an eye on the US forces 724 00:40:47,080 --> 00:40:49,360 Speaker 3: that are operating in the region. Officials in South Korea 725 00:40:49,680 --> 00:40:52,440 Speaker 3: say they've assessed the satellite launch, but added it was 726 00:40:52,440 --> 00:40:56,560 Speaker 3: still unclear if the device was operational, and Jack mar 727 00:40:56,680 --> 00:41:00,279 Speaker 3: is walking back plans to sell ten million shares. Ali 728 00:41:00,320 --> 00:41:03,400 Speaker 3: Barber Mah, who founded the internet company, will continue to 729 00:41:03,440 --> 00:41:06,040 Speaker 3: hold onto his stake, which is worth about eight hundred 730 00:41:06,040 --> 00:41:09,080 Speaker 3: and seventy million US dollars. Ali Barber shares recently faced 731 00:41:09,080 --> 00:41:12,080 Speaker 3: to sell off, resulting in a twenty two billion dollar 732 00:41:12,160 --> 00:41:15,600 Speaker 3: drop in market value in a single day, plus slim 733 00:41:15,640 --> 00:41:19,720 Speaker 3: pickings for the Thanksgiving box office weekend is working against 734 00:41:19,800 --> 00:41:24,080 Speaker 3: Disney's latest animated film Wish. In the past, Thanksgiving US 735 00:41:24,160 --> 00:41:27,799 Speaker 3: ranked among the most lucrative times for movie studios, but 736 00:41:27,840 --> 00:41:31,600 Speaker 3: in recent years a number of factors have conspired against that, 737 00:41:31,760 --> 00:41:35,719 Speaker 3: such as the rise of streaming services and scaled back 738 00:41:35,760 --> 00:41:40,440 Speaker 3: marketing due to the Hollywood strikes. It has been an 739 00:41:40,480 --> 00:41:43,960 Speaker 3: incredible week in Silicon Valley. That does it for this 740 00:41:44,160 --> 00:41:47,440 Speaker 3: edition of Bloomberg Technology. To those in the US, Happy 741 00:41:47,480 --> 00:41:50,920 Speaker 3: Thanksgiving around the world. Don't forget to recap on the podcast. 742 00:41:50,960 --> 00:41:53,440 Speaker 3: Wherever you get your podcasts, so many of you are 743 00:41:53,480 --> 00:41:56,600 Speaker 3: listening to it. Apple's Spotify, iHeart, and of course of 744 00:41:56,680 --> 00:42:00,840 Speaker 3: all the Bloomberg platforms. Again, Happy thanks thanks Giving here 745 00:42:00,840 --> 00:42:04,399 Speaker 3: to all Americans in the world. Stay tuned in. This 746 00:42:04,800 --> 00:42:06,000 Speaker 3: is Bloomberg Technology.