1 00:00:02,560 --> 00:00:09,520 Speaker 1: Bloomberg Audio studios, podcasts, radio news. 2 00:00:12,560 --> 00:00:16,000 Speaker 2: A single best idea. Caroline I called me up and said, 3 00:00:16,000 --> 00:00:19,280 Speaker 2: what are you doing? Bloomberg technology? That's what it felt like, 4 00:00:19,840 --> 00:00:23,520 Speaker 2: Caroline Heid and Ed Ludlow always wonderful every day grinding 5 00:00:23,520 --> 00:00:26,680 Speaker 2: out Bloomberg technology. And we didn't do it one hundred percent. 6 00:00:26,760 --> 00:00:30,680 Speaker 2: We had a a real bent Todaten, Nvidia and all 7 00:00:30,760 --> 00:00:33,600 Speaker 2: this up. We're about AI major shot out. Jonathan Torone 8 00:00:33,760 --> 00:00:39,280 Speaker 2: in Vienna, Austria is expert at Bloomberg a nuclear war, 9 00:00:40,080 --> 00:00:43,239 Speaker 2: the processing of it, the worry about it. And he 10 00:00:43,440 --> 00:00:47,560 Speaker 2: was riveting today on the show about Iran and about 11 00:00:47,560 --> 00:00:51,000 Speaker 2: the deployment of all of our military assets across the 12 00:00:51,040 --> 00:00:54,480 Speaker 2: Middle East. We thank Jonathan Troon for really making some 13 00:00:54,520 --> 00:00:57,880 Speaker 2: effort to be on the show today. Dan I's always 14 00:00:57,920 --> 00:01:00,760 Speaker 2: on the show. He's in scott Sail, Arizona. Today. Life 15 00:01:00,800 --> 00:01:05,280 Speaker 2: is tough. Dan ives here on in videos. Results. 16 00:01:05,640 --> 00:01:08,640 Speaker 3: These are Michael Jordan like numbers. I mean, if you 17 00:01:08,680 --> 00:01:10,959 Speaker 3: look on the data center side, I mean you're talking 18 00:01:11,000 --> 00:01:15,960 Speaker 3: about five to seven hundred BIPs above street whisper numbers 19 00:01:15,959 --> 00:01:19,400 Speaker 3: into next quarter seventy percent growth, it's seventy seven percent. 20 00:01:19,760 --> 00:01:21,520 Speaker 3: I mean you talk about law of large numbers. It 21 00:01:21,560 --> 00:01:25,600 Speaker 3: doesn't apply with Nvidio, and I think as it plays out, 22 00:01:25,920 --> 00:01:29,360 Speaker 3: this is showing the five hundred billion they talked about 23 00:01:29,400 --> 00:01:33,080 Speaker 3: with Blackwell and Rubin. It's conservative, and I think his 24 00:01:33,200 --> 00:01:36,840 Speaker 3: numbers look out thirty percent growth next year probably goes 25 00:01:36,920 --> 00:01:39,280 Speaker 3: close to forty percent. And that's why I think there's 26 00:01:39,319 --> 00:01:41,840 Speaker 3: a stock that should be up significantly as we look 27 00:01:41,880 --> 00:01:43,280 Speaker 3: in the coming weeks and months. 28 00:01:43,760 --> 00:01:48,320 Speaker 2: Dan Ives of Wedbush Securities. Drew Manis was in today 29 00:01:48,360 --> 00:01:52,440 Speaker 2: with MetLife. He is wonderful, of course, formerly with Maury 30 00:01:52,480 --> 00:01:58,200 Speaker 2: Harris at UBS doing legit macroeconomics and market economics, now 31 00:01:58,280 --> 00:02:03,160 Speaker 2: looking at the entire mix of a folio four Metropolitan Life. 32 00:02:03,200 --> 00:02:05,640 Speaker 2: He sent me in a note before we went to 33 00:02:05,720 --> 00:02:11,320 Speaker 2: air that was heated on artificial intelligence and the uproar. 34 00:02:11,400 --> 00:02:16,880 Speaker 2: Now the fear and the panic for MetLife. Drew Madis, this. 35 00:02:16,919 --> 00:02:20,040 Speaker 1: Is not the AI jobs apocalypse. You know, we are 36 00:02:20,040 --> 00:02:22,959 Speaker 1: thinking about this the wrong way. When I came into 37 00:02:22,960 --> 00:02:24,800 Speaker 1: work today, I've got fifty things I want to do, 38 00:02:25,360 --> 00:02:28,680 Speaker 1: and if AI can help me do thirty of them right, 39 00:02:28,760 --> 00:02:31,040 Speaker 1: my constraint is still how many people I have working 40 00:02:31,240 --> 00:02:33,480 Speaker 1: for me and with me? Who can kind of engage 41 00:02:33,520 --> 00:02:36,520 Speaker 1: with me and discuss things with me, and how much 42 00:02:36,520 --> 00:02:40,720 Speaker 1: technology I have available. Right, and that's anyone anywhere. If 43 00:02:40,840 --> 00:02:44,320 Speaker 1: I somehow use AI to discover fifty new things about 44 00:02:44,320 --> 00:02:48,040 Speaker 1: the universe or my job, right, I'm going to get 45 00:02:48,080 --> 00:02:50,359 Speaker 1: one hundred new questions from that knowledge. 46 00:02:50,639 --> 00:02:53,840 Speaker 2: Drew Madis met Life. I should note that we've launched 47 00:02:53,960 --> 00:02:57,480 Speaker 2: this week on Bloomberg, very terminal centric. This is for 48 00:02:57,520 --> 00:03:03,520 Speaker 2: the Bloomberg terminal. Ask b askb askb go, which is 49 00:03:03,760 --> 00:03:08,640 Speaker 2: artificial intelligence summarize again all of the Bloomberg terminal world 50 00:03:08,960 --> 00:03:12,880 Speaker 2: into one quick look on the Bloomberg. It's getting initial response. 51 00:03:12,919 --> 00:03:17,080 Speaker 2: It's plus plus plus. Our podcasts are out of Apple 52 00:03:17,120 --> 00:03:23,919 Speaker 2: Let's Spotify on YouTube podcasts. It's single best idea.