1 00:00:02,520 --> 00:00:09,360 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Daniel Ives 2 00:00:09,400 --> 00:00:13,360 Speaker 1: of Webbush first of all, rocketed out of Las Vegas 3 00:00:13,400 --> 00:00:15,840 Speaker 1: with Aston Martin. For those of you on radio, he's 4 00:00:15,840 --> 00:00:19,120 Speaker 1: got the real jacket on, like the kind of land Alonzo. 5 00:00:19,440 --> 00:00:22,160 Speaker 1: We're in all that. What in Formula one with all 6 00:00:22,160 --> 00:00:26,000 Speaker 1: the excitement Apple taking over the broadcast, Cadillac coming in 7 00:00:26,360 --> 00:00:29,200 Speaker 1: next year, when you're in the pit like you were, 8 00:00:29,320 --> 00:00:32,640 Speaker 1: What's what's the thing that you don't know when you 9 00:00:32,680 --> 00:00:33,440 Speaker 1: watch on TV? 10 00:00:33,960 --> 00:00:35,920 Speaker 2: I think, I mean my experience at that point. I 11 00:00:35,920 --> 00:00:38,560 Speaker 2: think the thing that peopleon't realize not just how loud 12 00:00:38,600 --> 00:00:40,839 Speaker 2: it is, but especially like when you're in there and 13 00:00:40,880 --> 00:00:43,879 Speaker 2: you actually have like the headphones on and you hear 14 00:00:43,920 --> 00:00:47,479 Speaker 2: them talking to the drivers. Just a complexity. I mean, 15 00:00:47,479 --> 00:00:49,640 Speaker 2: that's the thing. It's like, it's it's really amazing. 16 00:00:49,800 --> 00:00:50,880 Speaker 1: Did you change a tire? 17 00:00:51,680 --> 00:00:54,680 Speaker 2: I did, but I will tell you at at indy 18 00:00:54,800 --> 00:00:59,000 Speaker 2: five hundred, I came close to almost change the entire Okay, 19 00:00:59,120 --> 00:01:02,040 Speaker 2: Dan Eyes secure Liberty Media. 20 00:01:02,160 --> 00:01:05,839 Speaker 3: You can own Formula one fw NK is the ticker 21 00:01:06,240 --> 00:01:08,480 Speaker 3: Liberty Media. You can own it as a public Why is. 22 00:01:08,480 --> 00:01:11,560 Speaker 1: Apple doing that? Explain? Just go to Jes Paul's dying 23 00:01:11,600 --> 00:01:14,560 Speaker 1: to get do Nvidia and you know the Google thing 24 00:01:14,600 --> 00:01:18,679 Speaker 1: and all that. Why is Apple doing Apple TV? It's 25 00:01:18,720 --> 00:01:21,119 Speaker 1: called dad TV because no one watches it. They got 26 00:01:21,120 --> 00:01:24,839 Speaker 1: some product out, they've had some successes, but why waste 27 00:01:24,880 --> 00:01:25,720 Speaker 1: their time on that? 28 00:01:25,959 --> 00:01:28,880 Speaker 2: Yeah? I mean to me, it's really it's all about 29 00:01:29,080 --> 00:01:31,720 Speaker 2: where they're ultimately going to take this. I mean in 30 00:01:31,760 --> 00:01:35,320 Speaker 2: the future. And we'll see as Apple ultimately goes down 31 00:01:35,360 --> 00:01:38,039 Speaker 2: the past with Gemini and in terms of the AI future, 32 00:01:38,520 --> 00:01:41,199 Speaker 2: they need to have as wide of a content lens 33 00:01:41,200 --> 00:01:43,920 Speaker 2: as possible. And I think when you look at Apple TV, 34 00:01:44,480 --> 00:01:48,280 Speaker 2: it's all part of Look, the quality speaks for itself. 35 00:01:48,440 --> 00:01:50,840 Speaker 2: Kuwannie has been the issue. But for them, it's just 36 00:01:50,880 --> 00:01:52,840 Speaker 2: they're going to continue to have irons in the fire. 37 00:01:52,880 --> 00:01:53,840 Speaker 2: That's what they're going to do. 38 00:01:53,880 --> 00:01:56,880 Speaker 1: The TV show Pluribus, it's a sci fi thing. She's 39 00:01:56,960 --> 00:02:00,920 Speaker 1: home all alone. Everybody around her is like a droid surveillance. 40 00:02:01,040 --> 00:02:03,480 Speaker 1: It is great. Why don't you get to video right? Example? 41 00:02:03,920 --> 00:02:05,960 Speaker 3: So, Dan, the AI story here took a little bit 42 00:02:05,960 --> 00:02:07,920 Speaker 3: of return over the last a couple of days. Here 43 00:02:08,200 --> 00:02:12,760 Speaker 3: Meta placing a big chip order with Google, further calling 44 00:02:12,840 --> 00:02:16,400 Speaker 3: to question the position or the dominance position of Nvidia. 45 00:02:16,520 --> 00:02:17,760 Speaker 3: Give us your thoughts about that one. 46 00:02:17,800 --> 00:02:21,160 Speaker 2: I mean, look Google TPU if you especially with wait, 47 00:02:21,200 --> 00:02:24,399 Speaker 2: Broadcom and TSMC is the is the builder that's been 48 00:02:24,440 --> 00:02:27,240 Speaker 2: around for over a decade, right, So it's not that 49 00:02:27,320 --> 00:02:30,680 Speaker 2: it's new per se. I think the issue comes down 50 00:02:30,720 --> 00:02:33,600 Speaker 2: to demand supply from video chips to twelve to one, 51 00:02:34,080 --> 00:02:35,520 Speaker 2: so the reality. 52 00:02:35,480 --> 00:02:37,320 Speaker 3: To supply of Nvidio chips twelve to one. 53 00:02:37,560 --> 00:02:40,000 Speaker 2: So look, when you look at Meta, like, they're not 54 00:02:40,120 --> 00:02:43,120 Speaker 2: going to be able to get everything they need from 55 00:02:43,160 --> 00:02:46,280 Speaker 2: in video, so they got to look outside. When you 56 00:02:46,320 --> 00:02:49,919 Speaker 2: look with googleized, i'd say it's really it's about three 57 00:02:49,960 --> 00:02:53,400 Speaker 2: to four years behind where Nvidio is, but again on 58 00:02:53,800 --> 00:02:57,639 Speaker 2: some certain instances it could be good enough. And look 59 00:02:57,639 --> 00:02:59,760 Speaker 2: at that's where we're going. I mean, the reality is 60 00:02:59,800 --> 00:03:02,280 Speaker 2: when it comes to AMD, when it comes to big tech, 61 00:03:02,560 --> 00:03:05,120 Speaker 2: eventually you gonna see Apple, you gonna see Meta, you're 62 00:03:05,120 --> 00:03:07,400 Speaker 2: gonna see Microsoft. They'll building own chips as well. But 63 00:03:07,480 --> 00:03:09,880 Speaker 2: there's one chip in the world feeling the AI revolution 64 00:03:10,040 --> 00:03:10,680 Speaker 2: that's in video. 65 00:03:11,280 --> 00:03:12,880 Speaker 3: So that's kind of how I thought about yesterday. I 66 00:03:12,919 --> 00:03:14,560 Speaker 3: was kind of surprised to see the cell off in 67 00:03:14,720 --> 00:03:17,440 Speaker 3: Vidio because my thought was all I hear from guys 68 00:03:17,520 --> 00:03:19,839 Speaker 3: like you and technology folks coming in here is that 69 00:03:19,919 --> 00:03:23,200 Speaker 3: the demand for AI is just I'm not saying satial, 70 00:03:23,240 --> 00:03:26,200 Speaker 3: but boy, it's outstripping supply for sure. And you gotta 71 00:03:26,639 --> 00:03:28,040 Speaker 3: get what you can get when you can get it. 72 00:03:28,080 --> 00:03:32,000 Speaker 2: Look, just spending three weeks in Asia, I mean, we've 73 00:03:32,040 --> 00:03:35,960 Speaker 2: seen demand accelerate thirty percent in the last six months 74 00:03:35,960 --> 00:03:38,600 Speaker 2: for AI. So it comes down to like it's easy 75 00:03:38,720 --> 00:03:42,240 Speaker 2: to call say AI is a bubble in the spreadsheet 76 00:03:42,360 --> 00:03:44,560 Speaker 2: and twenty fifty four of New York City office building, 77 00:03:44,560 --> 00:03:47,880 Speaker 2: but when you actually see what's happening there. Look, only 78 00:03:47,920 --> 00:03:50,160 Speaker 2: three percent of enterprise in the US have gone down 79 00:03:50,200 --> 00:03:54,360 Speaker 2: the AI path, None in Europe, Asia, ex China, and 80 00:03:54,400 --> 00:03:56,440 Speaker 2: now you've seen sovereigns in Middle East, and for the 81 00:03:56,480 --> 00:03:58,680 Speaker 2: first time in thirty years, US is headed China. When 82 00:03:58,680 --> 00:04:01,120 Speaker 2: it comes tech on. 83 00:04:00,960 --> 00:04:03,280 Speaker 1: Wall Street, people love to go after you on Twitter. 84 00:04:03,320 --> 00:04:06,480 Speaker 1: It's the close, it's the act and all that underneath it. 85 00:04:06,520 --> 00:04:09,360 Speaker 1: We know, folks, not only Dan Eyes but Webbush, there's 86 00:04:09,360 --> 00:04:13,040 Speaker 1: some prodigious tech chips. Like going to Asia, like actually 87 00:04:13,120 --> 00:04:16,440 Speaker 1: walking in a factory, find out what's going on. Here's 88 00:04:16,480 --> 00:04:21,520 Speaker 1: the reality for our listeners. Our viewers worldwide. April three, 89 00:04:22,279 --> 00:04:26,640 Speaker 1: a leading newspaper just reporting the news. Apple Shells shares 90 00:04:26,680 --> 00:04:29,839 Speaker 1: fell more than nine percent in response to the President's 91 00:04:29,839 --> 00:04:34,599 Speaker 1: plan for steep tariffs on products made abroad. Let as 92 00:04:34,640 --> 00:04:38,320 Speaker 1: sharp set off in tech stocks, which is loaded with technology. 93 00:04:38,560 --> 00:04:43,080 Speaker 1: OMG April thirds sank nearly six percent. Apple is up 94 00:04:43,240 --> 00:04:48,560 Speaker 1: sixty five percent, printing two to eighty yesterday. How do 95 00:04:48,720 --> 00:04:53,479 Speaker 1: our listeners in viewers digest the news in the day 96 00:04:53,520 --> 00:04:57,640 Speaker 1: to day panic and yet stay on board this historic 97 00:04:57,760 --> 00:04:58,640 Speaker 1: American path. 98 00:04:58,800 --> 00:05:00,960 Speaker 2: Look, and we've talked about so much on the show 99 00:05:01,000 --> 00:05:03,520 Speaker 2: over the years, right, I mean, the reality is is 100 00:05:03,520 --> 00:05:07,080 Speaker 2: that there's no bigger consumer install based in the world 101 00:05:07,160 --> 00:05:10,320 Speaker 2: than Apple two point four billion iOS devices, one point 102 00:05:10,360 --> 00:05:13,040 Speaker 2: five billion iPhones. And it comes down besides just the 103 00:05:13,080 --> 00:05:16,840 Speaker 2: cash generating machine everything we see in the services. When 104 00:05:16,880 --> 00:05:19,640 Speaker 2: you look at the AI revolution, Okay, they've looked, they've 105 00:05:19,640 --> 00:05:22,680 Speaker 2: watched it from the stands so far, but now they're 106 00:05:22,720 --> 00:05:25,400 Speaker 2: about to get into the field and actually do it 107 00:05:25,440 --> 00:05:29,080 Speaker 2: and monetize the install based the consumer AI revolution comes 108 00:05:29,080 --> 00:05:31,560 Speaker 2: to Apple, and I think that's something that we're going 109 00:05:31,640 --> 00:05:34,120 Speaker 2: to see with Google Partnership and others and Tom I 110 00:05:34,240 --> 00:05:37,000 Speaker 2: just continue view it as like seventy five to one 111 00:05:37,120 --> 00:05:41,760 Speaker 2: hundred hours per share incremental will be added to Apple 112 00:05:41,839 --> 00:05:44,919 Speaker 2: for AI And that's my view. They've David and also 113 00:05:44,960 --> 00:05:47,560 Speaker 2: look at this iPhone seventeen. It's been a surprise upgrade 114 00:05:47,560 --> 00:05:51,160 Speaker 2: cycle that no one expected with Gemini. 115 00:05:51,839 --> 00:05:55,479 Speaker 1: Is Apple under less pressure to do something this whole 116 00:05:55,760 --> 00:05:57,039 Speaker 1: do something, do something? 117 00:05:57,240 --> 00:06:00,640 Speaker 2: I'd say more pressure, but they couldn't do it till 118 00:06:00,760 --> 00:06:05,600 Speaker 2: Google ultimately won the dojsuit Wednesday won the dojsuit. That's 119 00:06:05,640 --> 00:06:08,919 Speaker 2: where the cando idenner between sun Dar and cook Start. 120 00:06:08,960 --> 00:06:12,880 Speaker 2: And I think that's that ultimately is now where that's 121 00:06:12,960 --> 00:06:17,000 Speaker 2: tracking to what can be a deal that couldn't have 122 00:06:17,080 --> 00:06:19,920 Speaker 2: been until they won that deal. And I think that's 123 00:06:20,080 --> 00:06:22,880 Speaker 2: that's where they're gonna go. They're not buying Purplexity, They're 124 00:06:22,920 --> 00:06:25,800 Speaker 2: going with Google. They're gonna go down bet heavily on them. 125 00:06:25,960 --> 00:06:27,520 Speaker 1: Day I was with Red Bush with us here on 126 00:06:27,600 --> 00:06:30,800 Speaker 1: Wednesday before Thanksgiving? Is you get ready to travel? The 127 00:06:30,880 --> 00:06:33,360 Speaker 1: Horde comes over to the house. We say good morning 128 00:06:33,800 --> 00:06:36,080 Speaker 1: all the different ways you listen to us, thank you 129 00:06:36,160 --> 00:06:40,839 Speaker 1: for discovering Bloomberg's surveillance in two thousand and twenty five. 130 00:06:40,880 --> 00:06:43,839 Speaker 1: Will be here Friday Paul Sweeney your people. It was 131 00:06:43,839 --> 00:06:47,279 Speaker 1: a big argument. People went back and forth. Yes, yeah, 132 00:06:47,560 --> 00:06:49,880 Speaker 1: but we'll be here Friday after Thanksgiving. 133 00:06:50,000 --> 00:06:52,040 Speaker 3: Paul Dan talks us about Meta a little bit. I 134 00:06:52,040 --> 00:06:54,280 Speaker 3: think that's one of the ones the market's unsure of 135 00:06:54,360 --> 00:06:56,760 Speaker 3: as it relates to the AI play. 136 00:06:56,800 --> 00:06:56,960 Speaker 1: There. 137 00:06:57,000 --> 00:07:00,120 Speaker 3: Stocks down about twenty percent from its recent high. Some 138 00:07:00,160 --> 00:07:01,640 Speaker 3: concerns there. How do you position that? 139 00:07:01,960 --> 00:07:06,280 Speaker 2: I think, I mean it's a table pounder by because 140 00:07:06,320 --> 00:07:08,880 Speaker 2: the reason that stocks off is because Zuck right now 141 00:07:08,960 --> 00:07:13,840 Speaker 2: Wartime CEO, focus on increasing capacs over the next year 142 00:07:13,960 --> 00:07:17,240 Speaker 2: in this arms race, and you're and you're seeing obviously 143 00:07:17,320 --> 00:07:20,560 Speaker 2: pressure in terms of earnings and cashle but that's that's 144 00:07:20,560 --> 00:07:22,640 Speaker 2: what you want to see them do. You were talking 145 00:07:22,640 --> 00:07:25,960 Speaker 2: about monetizing the AI revolution over the coming years, the 146 00:07:25,960 --> 00:07:29,559 Speaker 2: three billion users that they basically have when it comes 147 00:07:29,560 --> 00:07:32,560 Speaker 2: to their consumer ECOSYSM, and that's the smart move I 148 00:07:32,600 --> 00:07:36,320 Speaker 2: think right now, investors, it's very easy knee jerk with 149 00:07:36,480 --> 00:07:40,120 Speaker 2: the bury, the AI bubble, all the worries. The reality 150 00:07:40,240 --> 00:07:42,560 Speaker 2: is that there's two more years that Leise left in 151 00:07:42,560 --> 00:07:45,080 Speaker 2: this tech bow market. You're in year three of an 152 00:07:45,080 --> 00:07:47,960 Speaker 2: eight to ten year building. It's truly a fourth industrial revolution, 153 00:07:48,320 --> 00:07:49,840 Speaker 2: and I think meta is going to be proven that 154 00:07:49,920 --> 00:07:51,320 Speaker 2: this is the right move. 155 00:07:51,800 --> 00:07:54,800 Speaker 1: What they're doing in the zeitgeist this weekend is the 156 00:07:54,880 --> 00:07:59,640 Speaker 1: partition that, yes, we appear to be using AI for 157 00:07:59,720 --> 00:08:03,200 Speaker 1: certain stuff. And Paul Sweeney the other day goes, should 158 00:08:03,200 --> 00:08:05,960 Speaker 1: I go with the ocean space cranberry or something homemade, 159 00:08:06,000 --> 00:08:10,400 Speaker 1: you know that kind of stuff, or like task driven AI? 160 00:08:10,880 --> 00:08:14,960 Speaker 1: When do you perceive America makes the shift to a 161 00:08:15,040 --> 00:08:17,280 Speaker 1: more sophisticated use of AI. 162 00:08:17,400 --> 00:08:20,160 Speaker 2: Yeah, it's a great quest. But today it's enterprise. I mean, 163 00:08:20,200 --> 00:08:23,800 Speaker 2: the reality is the consumer AI revolution hasn't started. Chat 164 00:08:23,880 --> 00:08:26,840 Speaker 2: GPT and we see that, but it's all enterprise. I mean, 165 00:08:27,200 --> 00:08:30,720 Speaker 2: the spending we're talking about called next two to three trillions, 166 00:08:30,800 --> 00:08:33,839 Speaker 2: just the enterprise. When it talks about consumer, it's our 167 00:08:34,160 --> 00:08:39,480 Speaker 2: autonomous humanoid robotics. It's the future of the consumer. 168 00:08:39,840 --> 00:08:42,199 Speaker 1: Goddamn robot to make my Cranberry sauce. 169 00:08:42,400 --> 00:08:46,439 Speaker 2: Listen, you're again and I continue to meet the call. 170 00:08:47,040 --> 00:08:52,160 Speaker 2: Keen will be in a ROBOTAXI in. 171 00:08:50,400 --> 00:08:54,360 Speaker 1: The other day into that, I thought lovelow. 172 00:08:55,160 --> 00:08:57,040 Speaker 2: And again you never know, it could be ledlow. 173 00:08:57,360 --> 00:08:59,360 Speaker 3: So all right, let's go to that robotics and all 174 00:08:59,360 --> 00:09:01,560 Speaker 3: that kind stuff. Because that's kind of the story behind 175 00:09:01,920 --> 00:09:05,080 Speaker 3: Teslaly these days, it's not about bending steel and making 176 00:09:05,120 --> 00:09:08,040 Speaker 3: cars and things like that. So the stocks up four 177 00:09:08,040 --> 00:09:11,240 Speaker 3: percent here today, so it's really lagging the market. It's 178 00:09:11,320 --> 00:09:14,840 Speaker 3: come back from I guess the biggest concerns where we 179 00:09:14,840 --> 00:09:17,400 Speaker 3: were several months ago. But when you talk to your 180 00:09:17,400 --> 00:09:19,120 Speaker 3: institutional list or clients, what are they telling you. 181 00:09:19,280 --> 00:09:23,800 Speaker 2: I mean, it's all about the future. I believe Autonomous 182 00:09:23,800 --> 00:09:27,440 Speaker 2: and ultimately optimists are will be the most important chapter 183 00:09:27,520 --> 00:09:31,360 Speaker 2: ever in Tesla's growth story. And I think now must 184 00:09:31,400 --> 00:09:35,439 Speaker 2: being wartime CEO, having the compackage, you know, potentially trillion 185 00:09:35,440 --> 00:09:40,040 Speaker 2: dollar man, this will now define Tesla. And I also 186 00:09:40,120 --> 00:09:42,520 Speaker 2: think you're gonna see a regulatory road map that's going 187 00:09:42,600 --> 00:09:46,440 Speaker 2: to ease when it comes to Autonomous, specifically on the 188 00:09:46,520 --> 00:09:49,439 Speaker 2: Robotaxi build out, you're gonna have thirty thirty five cities. 189 00:09:49,880 --> 00:09:52,040 Speaker 2: And I think WIMA is basically gonna be a round 190 00:09:52,040 --> 00:09:53,920 Speaker 2: the era a relative to where I see Tesla. 191 00:09:54,400 --> 00:09:56,880 Speaker 1: Let's go to our three radio stations. Good Morning ninety 192 00:09:56,880 --> 00:09:59,760 Speaker 1: two nine FM, Boston ninety nine one FM, Nathan Hager 193 00:10:00,120 --> 00:10:03,680 Speaker 1: Radio in Washington here Bloomberg eleventh zero. How is a 194 00:10:03,760 --> 00:10:08,439 Speaker 1: robotaxi get across the Charles River right by Mi T. 195 00:10:09,120 --> 00:10:11,920 Speaker 1: How does a robot get turn left there? And the sport? 196 00:10:12,080 --> 00:10:15,880 Speaker 1: How does a robotaxi get around DuPont Circle? How does 197 00:10:15,920 --> 00:10:20,960 Speaker 1: a robotaxi get down Fifth Avenue right outside the Trump Tower. 198 00:10:21,080 --> 00:10:21,800 Speaker 1: I don't get it. 199 00:10:22,200 --> 00:10:24,880 Speaker 2: Look I mean, do you look at it's it's data driven. 200 00:10:24,920 --> 00:10:27,360 Speaker 2: I mean the reality is is that is. 201 00:10:27,320 --> 00:10:33,440 Speaker 1: Your proof of concept that they can handle normal urban traffic. 202 00:10:33,920 --> 00:10:37,160 Speaker 2: What everything I've seen, and obviously we've been there in Austin, 203 00:10:37,600 --> 00:10:39,600 Speaker 2: You're going to continue to see to expand, you know, 204 00:10:40,000 --> 00:10:44,200 Speaker 2: across many cities over the next few months. I believe 205 00:10:44,520 --> 00:10:47,280 Speaker 2: we're there now. I'm not saying that there's you're going 206 00:10:47,360 --> 00:10:50,040 Speaker 2: to see the geofense area continue to expand. But it's 207 00:10:50,120 --> 00:10:54,440 Speaker 2: my view next few years, twenty percent of cars on 208 00:10:54,480 --> 00:10:57,480 Speaker 2: the road when you're whether it's New York City, whether 209 00:10:57,520 --> 00:11:00,120 Speaker 2: it's Boston, whether it's scott you're gonna look around and 210 00:11:00,160 --> 00:11:02,440 Speaker 2: you're gonna and you're not gonna see a driver enough chat. 211 00:11:02,559 --> 00:11:04,720 Speaker 1: What's your single best buy right now? Is it matter 212 00:11:04,840 --> 00:11:05,800 Speaker 1: or is this something different? 213 00:11:05,920 --> 00:11:07,960 Speaker 2: I mean to me, single best buy writ or is 214 00:11:08,040 --> 00:11:10,480 Speaker 2: Microsoft the relative to what we see in terms of 215 00:11:10,520 --> 00:11:15,760 Speaker 2: the stock, I sit down because the view that now Google, 216 00:11:15,920 --> 00:11:19,000 Speaker 2: now Amazon and others on the hyper scale are gonna 217 00:11:19,040 --> 00:11:21,439 Speaker 2: sort of eat their lunch. Look what's happened to Oracle 218 00:11:21,480 --> 00:11:24,400 Speaker 2: as well? It just look New York City cab driver 219 00:11:24,520 --> 00:11:28,440 Speaker 2: was bearish on Alphabet and Google start the year. Today 220 00:11:28,800 --> 00:11:31,440 Speaker 2: they're barish on Microsoft. And I think that's why that 221 00:11:31,480 --> 00:11:32,720 Speaker 2: has one hundred hour upside. 222 00:11:33,120 --> 00:11:40,000 Speaker 1: Okay on Microsoft just is one example. Are they Open Ai? 223 00:11:40,200 --> 00:11:41,760 Speaker 1: Sam what's his name, Sam Altman? 224 00:11:41,880 --> 00:11:42,280 Speaker 3: Sam Almon? 225 00:11:42,360 --> 00:11:46,000 Speaker 1: Yeah? Are they down because they're affiliated with Sam Altman? 226 00:11:46,400 --> 00:11:49,800 Speaker 2: I think just like, just like Oracle, there's that too 227 00:11:49,920 --> 00:11:53,680 Speaker 2: big to fail concept right where anyone that touches Open 228 00:11:53,760 --> 00:11:57,560 Speaker 2: AI that's ultimately been an overhang. But it comes down 229 00:11:57,600 --> 00:12:00,520 Speaker 2: to like that would be like me being like, Okay, 230 00:12:00,600 --> 00:12:03,480 Speaker 2: if I could have more Peter Luger Steak, would I 231 00:12:03,600 --> 00:12:05,880 Speaker 2: have it? Or would I rather own White Castle? 232 00:12:08,760 --> 00:12:08,960 Speaker 1: Yeah? 233 00:12:09,040 --> 00:12:11,360 Speaker 2: Again, you gotta go Lugers. But the reality is that 234 00:12:11,520 --> 00:12:15,160 Speaker 2: Open AI it's the Peter Lugers of technology. You want 235 00:12:15,160 --> 00:12:17,760 Speaker 2: to be associated with it, not not associated. 236 00:12:17,760 --> 00:12:20,079 Speaker 1: Those are on YouTube. The interns are in our ears. 237 00:12:20,080 --> 00:12:23,839 Speaker 1: We got these holiday interns and Sweeney's interns from Penn State. 238 00:12:23,880 --> 00:12:27,199 Speaker 1: I'm shocked we are. Nobody cares we are. Paul Dan, 239 00:12:27,520 --> 00:12:29,000 Speaker 1: Penn State, go Paul. 240 00:12:29,240 --> 00:12:30,200 Speaker 3: Who's going to be the coach? 241 00:12:30,240 --> 00:12:30,600 Speaker 1: Do you think? 242 00:12:30,800 --> 00:12:34,040 Speaker 2: I mean, look, I think we'll see it probably Monday. 243 00:12:34,480 --> 00:12:38,000 Speaker 2: That was I continue to think it's you know, it's 244 00:12:38,000 --> 00:12:43,240 Speaker 2: either Chesney from JMU that you know, or there could 245 00:12:43,240 --> 00:12:46,200 Speaker 2: be a mystery candidate that will see how that emerged 246 00:12:46,240 --> 00:12:47,320 Speaker 2: over the coming days. 247 00:12:47,679 --> 00:12:48,560 Speaker 1: So I think a big. 248 00:12:49,880 --> 00:12:57,040 Speaker 2: Mystery can no, not no, not no, please we better 249 00:12:57,160 --> 00:12:59,560 Speaker 2: days are ahead for Penn State after a dark year. 250 00:13:00,400 --> 00:13:03,000 Speaker 1: All I ask was, you're such a hitter and you're 251 00:13:03,040 --> 00:13:05,160 Speaker 1: so f one. Next time you go to F one, 252 00:13:05,640 --> 00:13:10,240 Speaker 1: take young John farroll with you. First, I played the. 253 00:13:12,040 --> 00:13:16,839 Speaker 2: Reason I got into F one. It was Netflix and farah. 254 00:13:16,520 --> 00:13:18,440 Speaker 3: Ye yeah, yeah, I mean. 255 00:13:18,520 --> 00:13:21,880 Speaker 1: I mean he wears he's like head to toe in Ferrari. 256 00:13:22,080 --> 00:13:23,719 Speaker 3: Sure, I mean you know, I mean, you know he's 257 00:13:24,000 --> 00:13:24,679 Speaker 3: that's how you roll. 258 00:13:24,880 --> 00:13:27,800 Speaker 1: The whole thing's where's your next F one you're going to? 259 00:13:28,080 --> 00:13:31,280 Speaker 2: I mean I have a few, but uh a few 260 00:13:31,360 --> 00:13:34,160 Speaker 2: on the docket, you know, mid Middle East and and 261 00:13:34,200 --> 00:13:35,040 Speaker 2: some other ones. 262 00:13:35,720 --> 00:13:38,079 Speaker 1: Dan, I was thank you to extended a conversation a 263 00:13:38,120 --> 00:13:40,760 Speaker 1: lot of good information there with his single best buy, 264 00:13:41,240 --> 00:13:43,120 Speaker 1: The Gentleman from Microsoft