1 00:00:02,400 --> 00:00:16,520 Speaker 1: Bloomberg Audio Studios, podcasts, radio news, single best idea and 2 00:00:16,600 --> 00:00:19,239 Speaker 1: a plothora of people to speak to on a Monday 3 00:00:19,680 --> 00:00:21,759 Speaker 1: team doing a great job over the weekend and even 4 00:00:21,840 --> 00:00:25,079 Speaker 1: during the show of you know, ripping things up. We 5 00:00:25,160 --> 00:00:27,319 Speaker 1: cancel people when you come on surveillance, you know you 6 00:00:27,320 --> 00:00:30,920 Speaker 1: could get canceled based on breaking news at Ken leon 7 00:00:31,080 --> 00:00:36,920 Speaker 1: On from CFIA just brilliant on the shareholder loss potential 8 00:00:37,080 --> 00:00:41,000 Speaker 1: at Paramount. I really don't understand the transaction other than 9 00:00:41,000 --> 00:00:44,120 Speaker 1: there's a whole private party with a Redstone family and 10 00:00:44,120 --> 00:00:46,600 Speaker 1: they're public shareholders that are a little bit upset, to 11 00:00:46,640 --> 00:00:51,280 Speaker 1: say the least. Thanks to Ken leon for that. Lets 12 00:00:51,320 --> 00:00:53,360 Speaker 1: to choose from today, we had to go Dan I's 13 00:00:53,400 --> 00:00:56,279 Speaker 1: He's a pinata and a bright colorful one at that. 14 00:00:57,240 --> 00:01:00,360 Speaker 1: For a lot of people that are tepping on technology, 15 00:01:00,480 --> 00:01:04,360 Speaker 1: gloomy on technology, he is the uber bull on technology. 16 00:01:04,360 --> 00:01:07,440 Speaker 1: And of course on a broad perspective of three years, 17 00:01:07,480 --> 00:01:10,399 Speaker 1: five years, ten years, he's been right, right, right, right right. 18 00:01:11,160 --> 00:01:15,240 Speaker 1: I asked Dan, i'ves about AI and I get it 19 00:01:15,280 --> 00:01:21,520 Speaker 1: that it's going to be enterprise chet GPT computer people productive, 20 00:01:22,080 --> 00:01:27,319 Speaker 1: But when does retail like through APPLESERI, actually use AI. 21 00:01:27,319 --> 00:01:31,479 Speaker 2: For legends like Keen. You won't see that till twenty 22 00:01:31,560 --> 00:01:36,360 Speaker 2: twenty five. From a consumer perspective, the enterprise is where 23 00:01:36,400 --> 00:01:40,040 Speaker 2: the AI revolutions happen today. But ultimately, Tom, I think 24 00:01:40,040 --> 00:01:44,080 Speaker 2: the important thing is when Apple embraces AI as Google 25 00:01:44,120 --> 00:01:47,960 Speaker 2: embrace AI. That's where you're going to now start to 26 00:01:48,120 --> 00:01:51,080 Speaker 2: see that to consumer from an app perspective, from a 27 00:01:51,160 --> 00:01:54,680 Speaker 2: technology and ultimately even from an AI perspective. Things I 28 00:01:54,720 --> 00:01:55,600 Speaker 2: got fsd. 29 00:01:55,760 --> 00:01:59,760 Speaker 1: Our Apple coverage Thursday. Look for that Amazon on Tuesday 30 00:02:00,360 --> 00:02:03,840 Speaker 1: as well. See the shock of Google and Microsoft and 31 00:02:03,960 --> 00:02:06,800 Speaker 1: even the rebound of Tesla off the last couple of 32 00:02:06,840 --> 00:02:10,639 Speaker 1: days in Misterer Musk's trip to China, Tesla up sharply 33 00:02:11,200 --> 00:02:14,400 Speaker 1: as well. So Amazon on Tuesday, and then Thursday we 34 00:02:14,480 --> 00:02:17,680 Speaker 1: get to Apple as well. It was a joy to 35 00:02:17,720 --> 00:02:21,760 Speaker 1: speak with Tina Fordham. She's a Fordham Global Insight and 36 00:02:21,840 --> 00:02:25,200 Speaker 1: she is I mentioned this during the interview. The only 37 00:02:25,280 --> 00:02:28,840 Speaker 1: equivalency I can see is Leslie van Ja Murray at Chathamhouse, 38 00:02:29,440 --> 00:02:34,960 Speaker 1: where these are Americans in Britain with a true visceral 39 00:02:35,120 --> 00:02:39,720 Speaker 1: Transatlantic feel. Another person that has that is Christine Lagarde 40 00:02:40,440 --> 00:02:44,600 Speaker 1: at the excuse me, European Central Bank with her work 41 00:02:44,639 --> 00:02:49,399 Speaker 1: obviously for her France, her schooling in high school around Washington, 42 00:02:49,919 --> 00:02:52,680 Speaker 1: and of course with Baker Mackenzie. I believe it was 43 00:02:52,760 --> 00:02:56,600 Speaker 1: the law firm in Chicago years ago. So the transatlantic 44 00:02:56,680 --> 00:03:01,080 Speaker 1: thing helps. And I asked Tina Fordham about the protests 45 00:03:01,080 --> 00:03:04,760 Speaker 1: at schools with all the heritage of nineteen sixty eight, 46 00:03:04,880 --> 00:03:08,919 Speaker 1: some of us, the memories of nineteen sixty eight and 47 00:03:08,960 --> 00:03:13,960 Speaker 1: beyond to Kent State the emotion right now of those protests, 48 00:03:14,520 --> 00:03:17,919 Speaker 1: how she perceived the college protests. It is. 49 00:03:19,400 --> 00:03:21,480 Speaker 3: Quite a spectacle. I mean, first of all, I'm a 50 00:03:21,560 --> 00:03:25,720 Speaker 3: Columbia alum, and I'm on the advisory board for SIPA, 51 00:03:25,800 --> 00:03:29,600 Speaker 3: the School of International and Public Affairs, which is also 52 00:03:29,720 --> 00:03:33,520 Speaker 3: caught up in these other it's mainly the college. I 53 00:03:33,560 --> 00:03:36,160 Speaker 3: don't think this is nineteen sixty eight, right. I think 54 00:03:36,200 --> 00:03:39,400 Speaker 3: that this is identity politics in the United States that 55 00:03:39,520 --> 00:03:44,080 Speaker 3: has now incorporated a foreign policy angle. I think it's 56 00:03:44,160 --> 00:03:51,680 Speaker 3: incredibly difficult for the university administrations to balance their commitment 57 00:03:51,760 --> 00:03:55,480 Speaker 3: to free speech and to the community that is a 58 00:03:55,600 --> 00:04:00,960 Speaker 3: university with their Title six obligations. They've got to protect 59 00:04:01,040 --> 00:04:05,960 Speaker 3: students and the whole sorry spectacle seems to me, and 60 00:04:06,160 --> 00:04:09,000 Speaker 3: you know, I sit in London, where I have for 61 00:04:09,040 --> 00:04:13,000 Speaker 3: a long time to be a culmination of the culture 62 00:04:13,040 --> 00:04:18,640 Speaker 3: wars and in some ways the tiktokification of very complex issues. 63 00:04:18,960 --> 00:04:21,440 Speaker 1: Tina fordhaman We thank her for those comments and her 64 00:04:21,440 --> 00:04:26,560 Speaker 1: commitment to Columbia University. She's with Fordham Global Insight. It's 65 00:04:26,560 --> 00:04:29,840 Speaker 1: a start to an eventful week. I mentioned Amazon on Tuesday, 66 00:04:29,880 --> 00:04:34,080 Speaker 1: Apple on Thursday. Sandwiched in between is a small matter 67 00:04:34,200 --> 00:04:37,360 Speaker 1: of a FED meeting. We'll do the FED decides, Lisa Briant, 68 00:04:37,360 --> 00:04:41,800 Speaker 1: what's John Farron? Myself? Well, wax philosophical, no dot plot adjustment, 69 00:04:41,880 --> 00:04:45,039 Speaker 1: no forecasts, so what can be had there? And Matt 70 00:04:45,120 --> 00:04:48,679 Speaker 1: Miskin I'm sorry today with John Hancock, he was heated 71 00:04:48,680 --> 00:04:52,159 Speaker 1: that this is a place for Powell to really reset 72 00:04:52,240 --> 00:04:56,080 Speaker 1: in his comments what he believes in, not so much 73 00:04:56,120 --> 00:04:59,640 Speaker 1: the way he tilts or the prediction of hawkish and dubbish, 74 00:05:00,279 --> 00:05:03,480 Speaker 1: but just simply to say what does he believe in. 75 00:05:03,520 --> 00:05:06,440 Speaker 1: There'll be some economic data along through the week is well. 76 00:05:06,480 --> 00:05:09,359 Speaker 1: Of course. Out of the FED meeting, we'll get FED speakers, 77 00:05:09,560 --> 00:05:13,000 Speaker 1: not that we really follow them carefully because there's four 78 00:05:13,120 --> 00:05:17,520 Speaker 1: hundred FED speakers now. Couple program notes, single best idea. 79 00:05:17,600 --> 00:05:20,520 Speaker 1: We are thrilled with the response. You go out, you 80 00:05:20,560 --> 00:05:25,400 Speaker 1: search for Bloomberg Surveillance on Bloomberg Podcasts really under business 81 00:05:25,440 --> 00:05:28,640 Speaker 1: news and under business. Thank you for that. We've been 82 00:05:29,200 --> 00:05:32,520 Speaker 1: humbled by the response. I should point out many have 83 00:05:32,640 --> 00:05:38,680 Speaker 1: requested the entire show seven to ten am replayed. We 84 00:05:38,839 --> 00:05:41,200 Speaker 1: have that out now and in the next couple of 85 00:05:41,240 --> 00:05:44,200 Speaker 1: days I'll be showing you the way you get that 86 00:05:44,320 --> 00:05:47,840 Speaker 1: on YouTube. YouTube not all our fault, but Google as well. 87 00:05:47,839 --> 00:05:50,560 Speaker 1: It's a little confusing, so we're going to get out 88 00:05:50,800 --> 00:05:54,280 Speaker 1: still the live broadcast on YouTube and then Eric, what 89 00:05:54,320 --> 00:05:57,640 Speaker 1: time roughly do we get the three hour out nuonish 90 00:05:58,960 --> 00:06:01,480 Speaker 1: nunish one ish two wish out there with all the 91 00:06:01,520 --> 00:06:03,480 Speaker 1: different tests that we have and they got to download 92 00:06:03,480 --> 00:06:06,360 Speaker 1: it and all that. But that's been a huge request 93 00:06:06,440 --> 00:06:11,800 Speaker 1: on Apple cardplay on YouTube search Bloomberg podcasts. This is 94 00:06:12,040 --> 00:06:15,120 Speaker 1: single best idea on Apple podcasts.