1 00:00:02,520 --> 00:00:16,360 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:14,080 --> 00:00:17,600 Speaker 2: A single best idea sliding into an interesting holiday. The 3 00:00:17,640 --> 00:00:22,040 Speaker 2: news in Britain today just suddenly a Prime Minister Starmer 4 00:00:22,120 --> 00:00:26,159 Speaker 2: and his labor government some real confidence issues. Something to 5 00:00:26,239 --> 00:00:31,240 Speaker 2: watch into Thursday and into the long United States a weekend. 6 00:00:31,240 --> 00:00:34,720 Speaker 2: This is where the colonies beat the home team and 7 00:00:34,800 --> 00:00:38,280 Speaker 2: that's probably why Britain is suffering right now. We'll see 8 00:00:38,400 --> 00:00:40,880 Speaker 2: on that of course Jobs Day tomorrow on a Thursday, 9 00:00:41,159 --> 00:00:43,600 Speaker 2: I will have complete coverage both Paul Sweeney and I 10 00:00:43,680 --> 00:00:46,800 Speaker 2: will be in to give you all of that market 11 00:00:46,840 --> 00:00:52,839 Speaker 2: moving effort at eight thirty Thursday morning. On the budget 12 00:00:53,000 --> 00:00:56,040 Speaker 2: and on the House vote. Maam mcguinnis with us, with 13 00:00:56,120 --> 00:00:59,960 Speaker 2: the Committee for a Responsible Federal Budget, and we looked 14 00:01:00,520 --> 00:01:04,080 Speaker 2: very simply where we are now with the vote. 15 00:01:04,400 --> 00:01:07,160 Speaker 1: You can't even say the Republicans and mean one thing 16 00:01:07,319 --> 00:01:09,840 Speaker 1: at this point. There's so many different factions to the 17 00:01:09,880 --> 00:01:12,640 Speaker 1: Republican Party. It's true for the Democrats as well, but 18 00:01:12,680 --> 00:01:15,600 Speaker 1: the spotlight is on them and their differences right now. 19 00:01:15,880 --> 00:01:19,560 Speaker 1: It's been really interesting to watch the development of this 20 00:01:19,760 --> 00:01:24,039 Speaker 1: reconciliation package because you have the old Republicans, those who 21 00:01:24,080 --> 00:01:26,880 Speaker 1: believed in lowering tax rates and believe that would funnel 22 00:01:26,959 --> 00:01:30,039 Speaker 1: enough growth to offset significant amounts of this. You have 23 00:01:30,160 --> 00:01:33,399 Speaker 1: the maga Republicans who are really much more populist and 24 00:01:33,480 --> 00:01:37,199 Speaker 1: are worried about these changes to entitlement benefits. Remember Republicans 25 00:01:37,280 --> 00:01:40,320 Speaker 1: used to acknowledge we needed to fix entitlements. Now they're 26 00:01:40,360 --> 00:01:42,600 Speaker 1: running away from Social Security and Medicare, which are the 27 00:01:42,600 --> 00:01:45,479 Speaker 1: two we need to focus on. And there's disagreements about 28 00:01:45,560 --> 00:01:47,760 Speaker 1: how far we should go with food stamps or Medicaid, 29 00:01:48,680 --> 00:01:52,760 Speaker 1: And there is just a huge disagreement within the party. 30 00:01:53,040 --> 00:01:55,960 Speaker 1: Are they the tech leaders, are they the populace? Have 31 00:01:56,040 --> 00:01:59,000 Speaker 1: they taken many from the Democrats who want entirely different things? 32 00:01:59,320 --> 00:02:01,360 Speaker 1: And I hope that the tough thing with fiscal policy 33 00:02:01,440 --> 00:02:04,720 Speaker 1: is nobody really wants the policies that we have to 34 00:02:04,800 --> 00:02:06,920 Speaker 1: contend with in order to fix our debt and deficit, 35 00:02:07,200 --> 00:02:10,400 Speaker 1: which is getting more revenues, controlling our spending and fixing 36 00:02:10,400 --> 00:02:11,160 Speaker 1: our entitlements. 37 00:02:11,440 --> 00:02:13,720 Speaker 2: Min McGinnis on fire, I wish that was a one 38 00:02:13,760 --> 00:02:19,320 Speaker 2: hour conversation today. She was just absolutely outstanding. The founder 39 00:02:19,360 --> 00:02:23,079 Speaker 2: of Bloomberg News, our editor in chief emeritus, Matthew Winkler 40 00:02:23,760 --> 00:02:27,400 Speaker 2: dark in the door today on Tesla we spoke about Tesla, 41 00:02:27,520 --> 00:02:29,480 Speaker 2: but it took a moment to speak to him about 42 00:02:29,480 --> 00:02:32,480 Speaker 2: the great change for all of us and particularly for 43 00:02:32,600 --> 00:02:35,639 Speaker 2: his journalism, Artificial intelligence. 44 00:02:35,840 --> 00:02:39,200 Speaker 3: We're very lucky at Bloomberg News because we already have 45 00:02:39,400 --> 00:02:45,760 Speaker 3: AI summaries on much of our content. Yeah, However, what 46 00:02:45,880 --> 00:02:48,000 Speaker 3: is missing is, in fact what you just said, the 47 00:02:48,080 --> 00:02:52,079 Speaker 3: names making news. You get a narrative in the AI, 48 00:02:52,280 --> 00:02:55,840 Speaker 3: so but you don't get that. You don't get the 49 00:02:55,919 --> 00:02:59,520 Speaker 3: names leading the news right away. And that to me 50 00:02:59,840 --> 00:03:04,400 Speaker 3: is where there's a fundamental difference, because if you follow 51 00:03:04,400 --> 00:03:07,280 Speaker 3: the Bloomberg way, you're absolutely right. Names make news. There's 52 00:03:07,280 --> 00:03:12,160 Speaker 3: a protagonist, there's a subject. That's what we're drawn to always, 53 00:03:12,680 --> 00:03:17,120 Speaker 3: and that's news judgment. And AI doesn't yet have the 54 00:03:17,120 --> 00:03:20,000 Speaker 3: Bloomberg way. Maybe it will, but it doesn't yet have it. 55 00:03:20,080 --> 00:03:25,000 Speaker 2: Matthew Winkler, they're talking about artificial intelligence, which I tell you, folks, 56 00:03:25,000 --> 00:03:29,120 Speaker 2: it's a moving target and having really profound impacts. I'm 57 00:03:29,160 --> 00:03:32,679 Speaker 2: trying to read in on it each and every day 58 00:03:32,720 --> 00:03:36,960 Speaker 2: as I can. In our technology, it's about YouTube. I 59 00:03:37,040 --> 00:03:40,440 Speaker 2: just can't say enough about the first half of twenty 60 00:03:40,520 --> 00:03:43,680 Speaker 2: twenty five and the growth of this digital experiment for 61 00:03:43,760 --> 00:03:49,440 Speaker 2: Bloomberg surveillance that is YouTube, Subscribe to Bloomberg podcasts and 62 00:03:49,560 --> 00:03:52,560 Speaker 2: on YouTube podcasts. This is single best idea 63 00:04:00,600 --> 00:04:03,000 Speaker 1: During lauding m