1 00:00:02,520 --> 00:00:09,240 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:13,240 --> 00:00:17,119 Speaker 2: Single best idea and just a window into how we 3 00:00:17,200 --> 00:00:21,120 Speaker 2: make the sausage. I'm a big believer from my childhood 4 00:00:22,040 --> 00:00:27,160 Speaker 2: of delegating authority. I have no idea who the guests 5 00:00:27,200 --> 00:00:31,200 Speaker 2: are going to be. A day before, two days before, 6 00:00:31,880 --> 00:00:35,760 Speaker 2: and most importantly, ten minutes before we go to air. 7 00:00:35,920 --> 00:00:40,239 Speaker 2: I purposely, purposely stay away from it. We have a 8 00:00:40,320 --> 00:00:45,159 Speaker 2: wonderful team want on, Eric driving that forward, who invent 9 00:00:45,479 --> 00:00:50,800 Speaker 2: the show every day. So today we've got wind Thin 10 00:00:51,040 --> 00:00:56,800 Speaker 2: definitive at the Bank of Nassau, Columbia, PhD, just expert 11 00:00:56,880 --> 00:01:00,480 Speaker 2: on foreign exchange and particularly the Pacific RIM. And then 12 00:01:00,520 --> 00:01:03,360 Speaker 2: we got man Deep sing and by chance they're sitting 13 00:01:03,360 --> 00:01:06,520 Speaker 2: in the studio together. Why not have the two of 14 00:01:06,560 --> 00:01:12,399 Speaker 2: them together on AI this day of Nvidia. It was magical. 15 00:01:12,840 --> 00:01:18,000 Speaker 2: Here's the economist Win Thin on what AI is doing 16 00:01:18,040 --> 00:01:19,320 Speaker 2: to us from. 17 00:01:19,120 --> 00:01:20,960 Speaker 1: A top down macro stampoint. 18 00:01:20,959 --> 00:01:24,280 Speaker 3: I think the investment in AI is certainly sort of 19 00:01:24,280 --> 00:01:26,880 Speaker 3: I think papering over sort of what I think are 20 00:01:26,920 --> 00:01:28,800 Speaker 3: cracks in the consumer into the labor market. 21 00:01:28,920 --> 00:01:30,240 Speaker 1: So we're getting very unbalanced. 22 00:01:30,720 --> 00:01:32,559 Speaker 3: If you look at the headline, you know, going somewhere 23 00:01:32,560 --> 00:01:35,600 Speaker 3: two and a half percent in GDP, but it's very unbalanced. 24 00:01:35,840 --> 00:01:39,200 Speaker 3: I think mix. I'd like to see the consumer feeling 25 00:01:39,200 --> 00:01:40,280 Speaker 3: a little bit better. You know, we've seen all the 26 00:01:40,400 --> 00:01:43,120 Speaker 3: Seamer sentiment numbers and all that. But you know, I 27 00:01:43,480 --> 00:01:45,679 Speaker 3: think now a question I think you always get asked us, well, 28 00:01:45,680 --> 00:01:46,160 Speaker 3: where's AI? 29 00:01:46,200 --> 00:01:47,880 Speaker 1: Really? Well, how do you monetize it? 30 00:01:47,920 --> 00:01:47,960 Speaker 3: Is? 31 00:01:48,000 --> 00:01:48,040 Speaker 4: It? 32 00:01:48,080 --> 00:01:50,360 Speaker 1: Really? Is all this investment going to pay off? Went thin? 33 00:01:50,440 --> 00:01:52,760 Speaker 2: They're talking to Mandeep Singing, and of course man Deep 34 00:01:52,800 --> 00:01:56,760 Speaker 2: had a brilliant answer. But here's Mandeep Singing with electrical 35 00:01:56,800 --> 00:02:01,240 Speaker 2: engineering just absolutely definitive at Bloomberg Intelligence on almost from 36 00:02:01,280 --> 00:02:06,840 Speaker 2: a system's analysis basis the machinery of our modern technology 37 00:02:07,120 --> 00:02:11,400 Speaker 2: of AI. And frankly how Invidio redounds back aside, he 38 00:02:11,520 --> 00:02:15,720 Speaker 2: may clear Gemini three. Thanks James Benika for a wonderful 39 00:02:15,880 --> 00:02:19,960 Speaker 2: essay on LinkedIn today on the new Gemini three, Mandeep 40 00:02:20,000 --> 00:02:23,000 Speaker 2: Singh said that Gemini three is a threat to in 41 00:02:23,120 --> 00:02:25,760 Speaker 2: Vidio because they don't use nvidio chips over at Google. 42 00:02:26,080 --> 00:02:30,119 Speaker 2: Little things like that. Here men Deep sing on artificial 43 00:02:30,360 --> 00:02:32,399 Speaker 2: intelligence in the world. 44 00:02:32,120 --> 00:02:34,600 Speaker 4: Of tech, I would argue, you know, we have been 45 00:02:34,680 --> 00:02:39,040 Speaker 4: constantly retraining people. If you think of a knowledge worker, 46 00:02:39,120 --> 00:02:42,960 Speaker 4: you know, using software, whether it's Excel or any other 47 00:02:43,040 --> 00:02:46,880 Speaker 4: type of productivity software. The number of features that keep 48 00:02:46,919 --> 00:02:50,200 Speaker 4: coming which you have to train yourself on to be 49 00:02:50,320 --> 00:02:53,880 Speaker 4: more productive. That's been the constant theme over the last 50 00:02:53,919 --> 00:02:57,320 Speaker 4: thirty forty years. What's changed now is some of this 51 00:02:57,480 --> 00:03:00,760 Speaker 4: productivity software is going to change, and the tools are 52 00:03:00,760 --> 00:03:04,040 Speaker 4: going to change in a profound way in terms of 53 00:03:04,680 --> 00:03:07,880 Speaker 4: AI agents or some of the things that get thrown around. 54 00:03:08,240 --> 00:03:11,480 Speaker 2: Bendeep Singer of Bloomberg Intelligences, and of course he and 55 00:03:11,720 --> 00:03:14,079 Speaker 2: rag Rana and the rest of our team will provide 56 00:03:14,120 --> 00:03:18,120 Speaker 2: copious coverage here of what we see from Nvidia this 57 00:03:18,240 --> 00:03:23,239 Speaker 2: afternoon and your podcast on Apple, on Spotify, on YouTube podcasts. 58 00:03:23,639 --> 00:03:28,080 Speaker 2: It's single best idea