WEBVTT - Walmart Adds Share as Value Perception Builds 0:00:01.360 --> 0:00:05.680 This is Bloomberg Business Wait inside from the reporters and 0:00:05.880 --> 0:00:09.440 editors who bring you America's most trusted business magazine, plus 0:00:09.520 --> 0:00:13.680 global business finance and tech news. The Bloomberg Business Week 0:00:13.720 --> 0:00:19.000 podcast with Carol Messer and Tim Stenebeck from Bloomberg Radio. 0:00:20.320 --> 0:00:22.640 Among those stops on the decline today two point six 0:00:22.680 --> 0:00:26.680 percent lower. In fact, is Walmart's staying at its worst levels. 0:00:26.880 --> 0:00:30.600 That despite the world's largest retailer lifting its annual profit 0:00:30.640 --> 0:00:34.400 outlook again. But you know what else was with it? Tim, 0:00:34.560 --> 0:00:35.720 a bit of a cautious tone. 0:00:35.840 --> 0:00:37.839 Yeah, it's always good to look at the commentary, and 0:00:37.880 --> 0:00:40.960 perhaps this is why the stock is lower. The cautious 0:00:40.960 --> 0:00:43.240 tone on consumers in the US economy. Walmart said that 0:00:43.520 --> 0:00:46.000 the rising borrowing costs, Okay, we know that those are 0:00:46.080 --> 0:00:48.880 hitting consumers. Look at what's happening to you know, credit 0:00:48.920 --> 0:00:50.800 card loans, people having to pay off those, and then 0:00:50.840 --> 0:00:53.159 of course mortgage rates as well, and the resumption of 0:00:53.159 --> 0:00:56.160 student loan repayments will add to the strain on US 0:00:56.160 --> 0:00:58.840 household budgets in the coming months. We've got a great 0:00:58.840 --> 0:01:00.640 guest with us this afternoon. It is with more on 0:01:00.680 --> 0:01:03.200 the results outlook and on the company that is the 0:01:03.200 --> 0:01:06.560 world's largest retailer. We got Bloomberg Intelligence senior retail staples 0:01:06.560 --> 0:01:09.920 and packaged food analysts Jen bartashis. She is joining us 0:01:10.040 --> 0:01:13.080 from New Jersey this afternoon. So why are shares of 0:01:13.080 --> 0:01:13.680 Walmart lower? 0:01:13.760 --> 0:01:16.440 Jen? Well, I think you nailed it when you were 0:01:16.440 --> 0:01:18.600 talking about this in the intro, and it's really just 0:01:18.680 --> 0:01:21.800 that conservative outlook. And you have to remember, for retail, 0:01:22.000 --> 0:01:25.720 back to school and holiday are the most important seasons 0:01:25.720 --> 0:01:29.600 of the year. So if Walmart's striking a cautious tone 0:01:29.760 --> 0:01:33.440 headed into those key seasons, that's probably what's pulling the 0:01:33.440 --> 0:01:34.920 stock down a little bit this afternoon. 0:01:34.959 --> 0:01:37.480 It's like one of those like, uh, what was the 0:01:37.480 --> 0:01:39.199 cautious Was the cautionary? 0:01:39.360 --> 0:01:41.880 Was the caution with the actual outlook when it came 0:01:41.920 --> 0:01:44.800 to numbers, or was it the commentary that we repeated 0:01:44.800 --> 0:01:47.600 there about student loan repayments and borrowing costs. 0:01:48.280 --> 0:01:50.720 It's more about the commentary about the state of the consumer. 0:01:51.160 --> 0:01:55.040 Because Walmart's numbers were great, and you know, the appeal 0:01:55.120 --> 0:01:58.400 of their value proposition is continuing to grow. So when 0:01:58.440 --> 0:02:01.120 you listen to what management's talking about their gaining share 0:02:01.240 --> 0:02:05.040 in some critical areas like grocery, and you know, but 0:02:05.360 --> 0:02:08.480 it's that cautious tone. And the problem is that grocery 0:02:08.480 --> 0:02:10.840 is a great business, but it's not a high margin business. 0:02:10.960 --> 0:02:13.760 And so for Walmart to really be successful, they want 0:02:13.800 --> 0:02:16.560 to incorporate some of more of that general merchandise sales. 0:02:16.600 --> 0:02:18.160 And those are the things that are important to back 0:02:18.200 --> 0:02:19.120 to school and holidays. 0:02:19.160 --> 0:02:20.760 And for those who missed, and I bet Jen heard 0:02:20.760 --> 0:02:24.720 at first hand the CEO Doug McMillan of Walmart said 0:02:24.760 --> 0:02:27.799 on that conference call with investors and analysts, the good stuff, jobs, wages, 0:02:27.800 --> 0:02:30.720 and pockets of a disinflation are helping our customers. That's 0:02:30.760 --> 0:02:33.840 the good stuff. The bad stuff, but rising energy prices, 0:02:33.880 --> 0:02:37.160 resuming student loan payments, higher borrowing costs and tightening lending 0:02:37.200 --> 0:02:40.920 standards and a draw down in excess savings mean that 0:02:40.960 --> 0:02:43.280 household budgets are still under pressure. I mean, Jen, that's 0:02:43.320 --> 0:02:47.160 a big laundry list. And especially for customers that typically 0:02:47.160 --> 0:02:49.639 shop at Walmart, I mean, you're talking about a lot 0:02:49.639 --> 0:02:53.400 of Americans. This is where they shop and that's a big, 0:02:53.639 --> 0:02:54.880 you know, stress list, if you. 0:02:54.880 --> 0:02:58.760 Will, It really is. And what we're seeing and what 0:02:58.880 --> 0:03:01.400 the patterns so far the year has been is that 0:03:01.480 --> 0:03:04.040 people do want to spend, but they're being super selective 0:03:04.080 --> 0:03:06.160 on where they're doing it, which means that they're saving 0:03:06.280 --> 0:03:09.920 everywhere else that they can. And so where you know, 0:03:10.040 --> 0:03:12.480 you do see that people are still going on trips, 0:03:12.520 --> 0:03:14.920 they're still going on vacation, they're still going out to 0:03:14.919 --> 0:03:18.600 dinner for special occasions. That's where they're choosing to do 0:03:18.639 --> 0:03:20.640 that little bit of splurge. But they're making up for 0:03:20.720 --> 0:03:24.360 that splurge by saving and saving, saving, cutting down on 0:03:24.440 --> 0:03:28.120 other expenditures. And that's part of what the behavior that 0:03:28.120 --> 0:03:29.600 we're seeing happen at Walmart as well. 0:03:30.040 --> 0:03:32.679 Go ahead, Carol, Well, Tim and I constantly talk about, well, 0:03:32.760 --> 0:03:35.520 you know Amazon, I need something, go to Amazon. I 0:03:35.560 --> 0:03:37.120 just did a big thing last night because I know 0:03:37.120 --> 0:03:38.800 it's easy to return and stuff. 0:03:39.240 --> 0:03:41.080 But tell us what, Well, I was going to say, 0:03:41.120 --> 0:03:43.160 I heard Jen, I heard you this morning on surveillance 0:03:43.160 --> 0:03:44.800 and you were like speaking to me. I think you 0:03:44.840 --> 0:03:47.320 said everybody goes to Walmart for something? Is that what 0:03:47.360 --> 0:03:47.760 you said? 0:03:48.480 --> 0:03:48.840 It is? 0:03:49.040 --> 0:03:49.320 It is? 0:03:49.360 --> 0:03:51.440 And it's true, so true, Carol, because I do the 0:03:51.480 --> 0:03:55.800 vast majority of our shopping at Amazon. But because I 0:03:55.840 --> 0:03:58.360 have American Express, I'm able to join like the Walmart 0:03:58.880 --> 0:04:01.360 Amazon Prime thing whatever it's called for free, like you 0:04:01.360 --> 0:04:04.040 can join that for free, and if we need something 0:04:04.040 --> 0:04:06.560 that's not available on Amazon, we do it at Walmart. 0:04:06.600 --> 0:04:07.640 And it's like the same thing as Prime. 0:04:07.800 --> 0:04:09.920 So Jen talked to us about Walmart Plus, how big 0:04:10.000 --> 0:04:11.600 a deal is it and how much of a growth 0:04:11.600 --> 0:04:15.040 engine it potentially is or will be for Walmart. 0:04:15.840 --> 0:04:18.600 So Walmart Plus started about two years ago, so it's 0:04:18.600 --> 0:04:20.880 still a pretty new program, but it does compete with 0:04:20.920 --> 0:04:23.640 Amazon Prime, and I think it is going to really 0:04:23.680 --> 0:04:26.800 become a very powerful driver for both sales and profit 0:04:26.839 --> 0:04:29.360 for the company over the next five years. We actually 0:04:29.360 --> 0:04:32.880 published a research piece on this earlier this week where 0:04:32.920 --> 0:04:34.719 we think over the next five years it can add 0:04:34.720 --> 0:04:37.520 one hundred to one hundred and sixty billion dollars in 0:04:37.600 --> 0:04:41.880 revenue for Walmart. And that's just on that's just on 0:04:41.920 --> 0:04:46.280 that on that program, and if you put it in perspective, 0:04:46.360 --> 0:04:50.479 that's the size of target, right. So it has the 0:04:50.520 --> 0:04:54.400 potential to really be a differentiator for Walmart. And part 0:04:54.400 --> 0:04:57.200 of the reason for that is that it appeals exactly 0:04:57.240 --> 0:05:00.960 to what people want, which is convenience and access to 0:05:01.000 --> 0:05:04.200 low prices. And so the fact that you can have 0:05:04.279 --> 0:05:07.000 deliveries of groceries or things that are in store to 0:05:07.040 --> 0:05:10.039 your house on the same day with no fee associated 0:05:10.080 --> 0:05:12.919 with it is a pretty powerful engine for them to 0:05:12.920 --> 0:05:13.479 build off of. 0:05:14.160 --> 0:05:17.000 Can they do it in a way that gives them margins? 0:05:18.520 --> 0:05:21.359 Yeah? And you know, if you think about the way 0:05:21.600 --> 0:05:25.080 a retailer makes the most margin, it's when somebody comes 0:05:25.080 --> 0:05:27.039 into the store, buy something and takes it out to 0:05:27.040 --> 0:05:30.080 their current takes it home themselves. The next most profitable 0:05:30.120 --> 0:05:32.480 thing is when somebody comes and they pick it up 0:05:32.480 --> 0:05:35.159 at the store curbside and then take it home. And 0:05:35.200 --> 0:05:37.960 then the third is one it's shipped to your house. Right, 0:05:38.040 --> 0:05:41.360 So what Walmart has done is that part of the 0:05:41.480 --> 0:05:45.320 value proposition is that curbside pickup and so that business 0:05:45.320 --> 0:05:48.560 has been growing very quickly for Walmart and is getting 0:05:48.560 --> 0:05:52.560 a lot of adoption. So that's actually a pretty a 0:05:52.600 --> 0:05:55.800 pretty good way to engage digital customers without having a 0:05:55.839 --> 0:05:58.400 margin drag that you would associate with things that have 0:05:58.440 --> 0:05:59.440 to be shipped to your home. 0:05:59.640 --> 0:06:02.880 We live so Caroly and I live in Carroll's in 0:06:02.880 --> 0:06:06.160 New Jersey. I'm in Brooklyn, which just outside, so you're 0:06:06.160 --> 0:06:07.599 in the sun. What I'm saying is you're in the city, 0:06:07.640 --> 0:06:10.360 You're not like driving to these places to actually pick 0:06:10.360 --> 0:06:13.320 stuff up. Now, when I was on printal leave while 0:06:13.320 --> 0:06:16.040 we were visiting my parents in California, and my sister 0:06:16.200 --> 0:06:18.680 was like ordering stuff from Target and we'd go, we'd 0:06:18.760 --> 0:06:20.800 drive there, they would I mean, anyone listening who has 0:06:20.839 --> 0:06:22.560 a car is actually laughing at me the fact that 0:06:22.560 --> 0:06:24.720 I'm like talking about this. But it's such a we're 0:06:24.720 --> 0:06:26.960 such strange animals in New York City because we don't 0:06:27.000 --> 0:06:29.400 take advantage of these programs. But I will tell you 0:06:29.560 --> 0:06:32.320 it is so easy to order something on one of 0:06:32.320 --> 0:06:34.839 these apps and then drive up to the curb and 0:06:34.880 --> 0:06:36.400 they literally bring it out to your car. 0:06:36.560 --> 0:06:38.760 I will tell you my daughter who goes to school 0:06:39.120 --> 0:06:43.120 six hours outside of New York City in a southern state, 0:06:43.440 --> 0:06:46.559 it's much more like residential and so and so forth. 0:06:46.760 --> 0:06:48.600 I remember one of the years we were driving to 0:06:48.640 --> 0:06:51.440 her school and Jen along the way, we kept ordering 0:06:51.480 --> 0:06:53.039 from Target, like she's like, oh, I need this, So 0:06:53.080 --> 0:06:54.520 we'll be like, okay, well in an hour, we'll be 0:06:54.560 --> 0:06:57.720 at this Target and we would just pick up curbside, 0:06:57.800 --> 0:06:59.000 and it was incredible. 0:07:00.320 --> 0:07:04.200 And it's that convenience that's really driving the success of 0:07:04.279 --> 0:07:08.400 these retailers because they're not only offering value, but it's convenience. 0:07:08.520 --> 0:07:11.880 And this is where for Walmart's perspective. You know, Amazon 0:07:12.000 --> 0:07:14.880 is a behemoth and they're very good at what they do. 0:07:15.480 --> 0:07:18.600 But Walmart has been building out the size of its marketplace. 0:07:18.640 --> 0:07:22.280 The number of sellers on its marketplace is becoming more competitive, 0:07:22.440 --> 0:07:24.840 and that powerful engine of being able to pick things 0:07:24.880 --> 0:07:27.280 up at the store at your convenience or have it 0:07:27.280 --> 0:07:31.119 delivered to your home same day is a pretty good 0:07:31.160 --> 0:07:32.400 strategy that they're following. 0:07:32.480 --> 0:07:35.080 What's that stat Jen with the X percentage of the 0:07:35.240 --> 0:07:37.640 US population lives within you know, just a couple miles 0:07:37.680 --> 0:07:38.680 of a Walmart. 0:07:38.960 --> 0:07:42.080 It's like over eighty five percent of the US population 0:07:42.200 --> 0:07:44.560 lives within a ten mile radius of a Walmart. 0:07:44.600 --> 0:07:46.560 I believe is what incredible the company has said. 0:07:46.640 --> 0:07:48.720 All right, so you were sitting down with Doug McMillan 0:07:48.800 --> 0:07:51.000 and you wanted to I don't know, you had two 0:07:51.080 --> 0:07:53.040 minutes with him. What would be the question you would 0:07:53.080 --> 0:07:54.240 ask him? 0:07:54.880 --> 0:07:57.160 Well, I would ask him about things for the company 0:07:57.200 --> 0:07:59.320 hasn't really given a lot of disclosure. I would ask 0:07:59.360 --> 0:08:02.000 him about the size of their membership for Walmart. Plus, 0:08:02.120 --> 0:08:04.560 I would ask him about the current profitability level of 0:08:04.640 --> 0:08:07.520 their of their online business. These are things that we 0:08:07.600 --> 0:08:10.400 know they're building, things that we know that they're working on, 0:08:11.120 --> 0:08:13.520 but we don't have a lot of detail behind it 0:08:13.600 --> 0:08:16.360 yet to understand how profitable it is or will be 0:08:16.440 --> 0:08:17.600 for the company long term. 0:08:17.680 --> 0:08:19.440 Ye, and it's matth I'm like, look at your research 0:08:19.520 --> 0:08:23.080 to about you know, advertising revenue at Walmart. Like it's 0:08:23.280 --> 0:08:26.880 just this company that the broad reach by just evolving. 0:08:27.080 --> 0:08:29.560 Jen, you're the best you've been up since, like you know, 0:08:29.720 --> 0:08:31.920 the crack of dawn covering this stuff. We love it 0:08:31.920 --> 0:08:34.079 when you join us and we get to talk. Also, 0:08:34.200 --> 0:08:35.839 just be honest, do Carol and I just sound like 0:08:35.840 --> 0:08:38.000 complete luttites the fact that we just found out about 0:08:38.000 --> 0:08:39.400 this curb side pickup. 0:08:39.040 --> 0:08:41.119 At a little while. 0:08:41.120 --> 0:08:41.800 Not in the least. 0:08:41.880 --> 0:08:44.599 Okay, goody, Jen, And no worry, it's just back to 0:08:44.640 --> 0:08:47.480 school shopping is next and oh yeah the holiday shopping season, 0:08:47.559 --> 0:08:51.600 so you'll get plenty of rest or not listen, we do. 0:08:52.040 --> 0:08:53.640 I think it's going to be a busy second half 0:08:53.679 --> 0:08:54.880 of the year, let's put it that way. 0:08:54.960 --> 0:08:56.719 Well, we'll be checking in with you, no doubt about it. 0:08:56.760 --> 0:08:59.760 Jen Bartasha's she's Bloomberg Intelligence Senior Retail Stables and package 0:08:59.760 --> 0:09:03.320 food analysts really a must read among our Bloomberg Intelligence team, 0:09:03.320 --> 0:09:05.880 and so appreciate her finding some time Walmart chairs, though 0:09:06.000 --> 0:09:07.880 still under pressure. In today's straight. 0:09:08.080 --> 0:09:11.640 You're listening to the Bloomberg Business Week podcast. Catch us 0:09:11.679 --> 0:09:15.000 Live weekday afternoons from three to six Eastern Listen on 0:09:15.080 --> 0:09:19.120 Bloomberg dot com, the iHeartRadio app, and the Bloomberg Business App, 0:09:19.400 --> 0:09:21.720 or watch us Live on YouTube. 0:09:22.360 --> 0:09:24.079 I don't know if he would pall, but Bill Gates 0:09:24.080 --> 0:09:29.040 back in March talked about seeing an artificial intelligence system 0:09:29.080 --> 0:09:33.160 ac tricky medical examination and how it represented the most 0:09:33.240 --> 0:09:37.080 important advance in technology since the graphical user interface. The 0:09:37.120 --> 0:09:40.840 guy uh. He said that software that, of course lets 0:09:40.880 --> 0:09:43.240 people to more easily interact with computers, and in the 0:09:43.320 --> 0:09:47.120 nineteen eighty set the standard for modern operating systems, including 0:09:47.160 --> 0:09:48.120 Microsoft's Windows. 0:09:48.200 --> 0:09:49.839 That's the gooey Carol, that gooey gewey. 0:09:49.920 --> 0:09:51.719 I said that, I know, gueye wooey. 0:09:51.600 --> 0:09:54.679 Gooey wooey, but keep it in mind. Incredible statement. 0:09:54.920 --> 0:09:57.400 Well, it is right you think about how game changing 0:09:57.440 --> 0:10:00.319 that was. Keep in mind, Microsoft has an app. It's 0:10:00.360 --> 0:10:03.240 called the DAX app. It's powered by AI. It's from 0:10:03.240 --> 0:10:07.040 the company's Nuanced division, and it transcribes doctors and patients comments, 0:10:07.280 --> 0:10:10.360 then creates a clinical physician summary formatted for an electronic 0:10:10.440 --> 0:10:13.560 health record. So AI in helping out doctors. 0:10:13.920 --> 0:10:16.760 It's an episode actually of the Bloomer Originals video series 0:10:16.800 --> 0:10:19.120 AI I RL earlier this year. It can be found 0:10:19.280 --> 0:10:22.240 on our streaming surface service. With more on the topic 0:10:22.360 --> 0:10:24.960 and curious if AI is yet penetrating his world, We 0:10:25.000 --> 0:10:27.760 got back with us doctor Ian Luspader. He's clinical professor 0:10:27.760 --> 0:10:30.600 of Medicine at NYU Lango and Medical Center. He joins 0:10:30.679 --> 0:10:33.120 us on Zoom from New York City, Doctor Lusbater, How 0:10:33.160 --> 0:10:33.560 are you. 0:10:35.160 --> 0:10:39.120 Great to see you guys, Carol and Tim. Tim, congratulations 0:10:39.160 --> 0:10:41.440 on the new born. Hope ball is going well. 0:10:41.520 --> 0:10:43.760 Yeah, all is going well. Thank you very much. Hey, 0:10:43.840 --> 0:10:46.480 how is that AI hitting your world? I mean, the 0:10:46.520 --> 0:10:48.480 medical community is one where I got to tell you 0:10:49.080 --> 0:10:50.920 sometimes I'm still required to send faxes. 0:10:52.960 --> 0:10:53.160 Right. 0:10:53.720 --> 0:10:57.840 Well, well, we're not there yet, but AI has tremendous potential, 0:10:58.360 --> 0:11:02.839 and AI functions in many ways like a person or 0:11:02.880 --> 0:11:07.360 a doctorate takes a lot of data points, analyzes it 0:11:07.600 --> 0:11:12.320 and process it and comes up with some conclusions. We're 0:11:12.400 --> 0:11:16.080 still not quite there integrating in every way. But the 0:11:16.160 --> 0:11:22.480 potential is enormous, from scheduling appointments, to pre interviewing patients 0:11:22.480 --> 0:11:26.800 to find out what they're coming in for, assisting with 0:11:26.880 --> 0:11:28.840 a diagnosis in the exam room. 0:11:28.880 --> 0:11:31.640 Well, talk about that part, assisting with the diagnosis. That's 0:11:31.640 --> 0:11:34.240 that's really interesting to me because what you guys as 0:11:34.280 --> 0:11:36.120 doctors try to do. And look, I didn't go to 0:11:36.160 --> 0:11:39.520 medical school, but I've been to plenty of doctors. You 0:11:39.640 --> 0:11:43.839 ask so many questions about symptoms, and each time somebody 0:11:43.840 --> 0:11:47.960 answers a question about that symptom, you know, there's sort 0:11:47.960 --> 0:11:50.600 of this calculation that goes on inside a doctor's head. Okay, 0:11:50.640 --> 0:11:51.840 it could be this, or it could be this, and 0:11:51.880 --> 0:11:54.680 you keep investigating. So how do you use how do 0:11:54.720 --> 0:11:58.560 you use you know, first the internet or databases right now? 0:11:58.800 --> 0:12:00.559 And how do you think that can be aided AI. 0:12:02.720 --> 0:12:06.079 So we, in a very similar way, extract information. A 0:12:06.160 --> 0:12:09.000 patient comes in with a complaint or an issue. We 0:12:09.080 --> 0:12:12.839 review a variety of questions that helps us hone in 0:12:13.120 --> 0:12:17.400 eliminate certain things and gives us the most likely diagnosis 0:12:17.400 --> 0:12:20.560 based on history, and then we get additional information from 0:12:20.640 --> 0:12:24.080 tests or labs to try and make a specific diagnosis. 0:12:24.080 --> 0:12:27.800 And then a specific treatment. AI can be very helpful 0:12:27.840 --> 0:12:31.360 because it can also process a lot of questions, either 0:12:32.200 --> 0:12:38.600 interrogate the patient or review lab data and kind of 0:12:38.640 --> 0:12:44.120 synthesize the information. And we see this most helpfully for example, 0:12:44.160 --> 0:12:47.560 with X rays. If you're comparing a series of cat scans, 0:12:47.880 --> 0:12:52.200 tremendous amount of data and subtle abnormalities can be picked up. 0:12:52.720 --> 0:12:57.400 Same for lab data we're using it for example with colonoscopy, 0:12:57.800 --> 0:13:01.240 where AI picks up subtle abnormality such as a polyp. 0:13:01.640 --> 0:13:04.880 Now it can't really tell if that is a polyp 0:13:05.040 --> 0:13:09.160 or necessarily maybe a clump of mucus. The doctor still 0:13:09.200 --> 0:13:12.360 has to irrigate it away and say, oh, yes, you're right, 0:13:12.600 --> 0:13:16.040 and is pursuing it. So AI can be very helpful 0:13:16.080 --> 0:13:19.839 to say, hey, have you thought about this? Is this relevant? 0:13:20.720 --> 0:13:23.640 Do we need to explore it further? And whether it's 0:13:23.679 --> 0:13:27.240 developing new drugs, whether it's processing a lot of lab 0:13:27.360 --> 0:13:30.240 data to say, hey, it looks like this blood count 0:13:30.280 --> 0:13:33.400 has slowly been trickling down. Do we have to worry 0:13:33.400 --> 0:13:37.400 about bleeding somewhere? Could there be a cancer? So it's 0:13:37.480 --> 0:13:41.520 not really integrated yet into the medical record system. It's 0:13:41.600 --> 0:13:45.000 not in the office helping us. Yet it's really more 0:13:45.400 --> 0:13:49.920 scheduling appointments. It's more helping with cat scans or diagnostic tests, 0:13:50.160 --> 0:13:53.960 even robotic surgery. But eventually, I think it will come 0:13:53.960 --> 0:14:00.000 into the office to really help extract important questions from patients, 0:14:00.000 --> 0:14:03.360 tact important data, and help us make a diagnosis and 0:14:03.440 --> 0:14:04.240 a treatment plan. 0:14:04.760 --> 0:14:06.520 Ian how long does it take for it to come 0:14:06.520 --> 0:14:08.640 in you think in a really significant way. 0:14:11.320 --> 0:14:15.040 You know, a lot of that is based on doing trials, 0:14:15.080 --> 0:14:17.360 A lot of it is based on the developer of 0:14:17.440 --> 0:14:22.360 the electronic medical record. We spend probably fifty percent of 0:14:22.400 --> 0:14:27.760 our time documenting, so if we can expand our patient 0:14:27.840 --> 0:14:33.080 contact time and thinking time and reducing our documentation time, 0:14:33.520 --> 0:14:38.040 that will definitely improve our ability to get information. I 0:14:38.080 --> 0:14:40.280 think within the next few years it's going to be 0:14:40.320 --> 0:14:43.600 in the office, but it's not certainly next month. 0:14:44.160 --> 0:14:47.960 Do you see this from the incumbent players in medicine 0:14:48.000 --> 0:14:49.880 right now? And I think of one, I mean Epic 0:14:49.960 --> 0:14:53.640 Medical Systems is like, if you go anywhere EPIC owns, 0:14:53.800 --> 0:14:56.840 the room is are they going to do it? 0:14:56.920 --> 0:14:57.240 Epic? 0:14:57.240 --> 0:14:59.560 It is the behemor it's the behemor well. 0:14:59.400 --> 0:15:03.000 They're talking about it, yep, it's the behemoth. All the 0:15:03.040 --> 0:15:06.000 major medical centers. They've been able in a few short 0:15:06.040 --> 0:15:09.520 years to really dominate it, and basically everyone has to 0:15:09.640 --> 0:15:11.920 join now because all the big players are on it 0:15:12.240 --> 0:15:15.520 and it is actually a pretty good medical record system. 0:15:15.960 --> 0:15:18.760 They are working on it and we're working with them 0:15:19.280 --> 0:15:24.120 to develop different algorithms. But it is not yet interviewing 0:15:24.160 --> 0:15:28.160 the patient. It is not yet documenting helping us document. 0:15:28.240 --> 0:15:30.800 We still have to dictate the charter or type the note, 0:15:31.200 --> 0:15:32.840 and it is not at the end of the day 0:15:32.880 --> 0:15:36.680 helping us process the information and say, hey, you missed 0:15:36.720 --> 0:15:40.440 this low blood count or high liver enzyme. Maybe we 0:15:40.480 --> 0:15:43.120 should look into it. I think that's going to happen, 0:15:44.000 --> 0:15:46.240 but I don't think it's going to happen in the 0:15:46.280 --> 0:15:46.800 next year. 0:15:47.000 --> 0:15:49.960 Do we need one system though, for this to really work. 0:15:52.240 --> 0:15:55.520 Yes, we've talked about this before for many years, having 0:15:55.560 --> 0:15:58.760 a national system where if someone goes to a hospital 0:15:58.800 --> 0:16:01.920 across the street or us the country, we have all 0:16:01.960 --> 0:16:06.120 the information integrated so we can do less tests and 0:16:06.320 --> 0:16:09.200 have to be less redundant in what we do. But 0:16:09.280 --> 0:16:15.200 that is a problem with administration and hip and privacy violations. 0:16:15.480 --> 0:16:17.760 We really would need the government to say, look, we're 0:16:17.800 --> 0:16:22.760 mandating that everyone have one system that puts everyone on 0:16:22.760 --> 0:16:25.960 one platform. So that's also a few years away. But 0:16:26.040 --> 0:16:28.160 we should have done that years ago. It's really been 0:16:28.200 --> 0:16:30.840 a waste of time having all these separate systems that 0:16:30.920 --> 0:16:32.320 don't really talk to each other. 0:16:32.760 --> 0:16:35.120 So, doctor Lespater, how does this end up in the 0:16:35.520 --> 0:16:36.800 operating room in the future. 0:16:38.600 --> 0:16:41.600 Well, we're already doing it for robotic surgery, which is 0:16:41.600 --> 0:16:45.840 a tremendous advance small incisions. The robots really help us 0:16:45.840 --> 0:16:50.480 do very technically delicate procedures. There are better outcomes. It's 0:16:50.520 --> 0:16:54.400 helping with drug development, it's helping with analyzing studies, so 0:16:54.560 --> 0:16:56.280 it can take all our information. 0:16:56.680 --> 0:17:00.680 So Carol, go back to what you were saying. When 0:17:00.720 --> 0:17:03.320 it comes to medical imaging, right, you know, it's only 0:17:03.320 --> 0:17:05.600 as perfect as the person reading the image. 0:17:05.680 --> 0:17:07.879 Right, What if somebody has a bad day or is tired, 0:17:08.600 --> 0:17:10.600 or they just miss it. It's not judge. I'm not 0:17:10.640 --> 0:17:11.200 being judgy. 0:17:11.320 --> 0:17:11.880 It happens. 0:17:12.000 --> 0:17:12.520 It's life. 0:17:13.000 --> 0:17:16.200 It happens. Happens to people in my family, like and 0:17:16.440 --> 0:17:19.520 you know what happens is there can be serious consequences 0:17:19.560 --> 0:17:21.280 to that. What if you were able to use AI 0:17:21.400 --> 0:17:22.719 and I know they're working on this. There was an 0:17:22.760 --> 0:17:24.960 article in times just a few months ago when it 0:17:25.000 --> 0:17:27.760 comes to mammograms using AI technology to try to find 0:17:28.440 --> 0:17:30.080 masses and mammograms. 0:17:29.520 --> 0:17:31.159 And just if it's a case of able to go 0:17:31.200 --> 0:17:32.919 through stuff and then just say listen, we got some 0:17:33.000 --> 0:17:36.040 questions about this, and then a radiologist or a doctor 0:17:36.040 --> 0:17:38.520 comes in and says, okay, let me take another look 0:17:38.560 --> 0:17:41.840 at this, and just it's another layer of really making 0:17:41.880 --> 0:17:46.000 sure that you don't miss something that's truly truly important. 0:17:46.000 --> 0:17:49.560 I mean it's in a hybrid way, right, working hand 0:17:49.560 --> 0:17:50.399 in hand, right. 0:17:50.240 --> 0:17:53.360 And in terms of medicine, right, it's never necessarily an 0:17:53.359 --> 0:17:55.800 exact science. So if you are able to have some 0:17:55.880 --> 0:17:58.320 kind of database that pulls in all the kind of 0:17:58.320 --> 0:18:01.639 different variations, if either an A or reading on a 0:18:01.720 --> 0:18:04.840 scan that shows when there could be potential problems, I think, 0:18:04.960 --> 0:18:07.240 think about how valuable and important that could be. Ian 0:18:07.280 --> 0:18:09.239 ls Beta, We always look forward to it. Doctor Ian 0:18:09.280 --> 0:18:11.760 las Beta over at NYU Lango Medical Center. 0:18:13.280 --> 0:18:16.840 You're listening to the Bloomberg Business Week podcast. Catch us 0:18:16.880 --> 0:18:20.879 live weekday afternoons from three to six Eastern on Bloomberg Radio, 0:18:21.080 --> 0:18:24.359 the Bloomberg Business app, and YouTube. You can also listen 0:18:24.480 --> 0:18:27.560 live on Amazon Alexa from our flagship New York station 0:18:28.040 --> 0:18:30.760 just say Alexa Play Bloomberg eleven. 0:18:30.520 --> 0:18:35.000 Thirty tim Some data last month a came out from 0:18:35.040 --> 0:18:38.479 the research from Pitchbook. It showed VC venture capital funding 0:18:38.600 --> 0:18:41.520 globally almost halved in the first six months of twenty 0:18:41.560 --> 0:18:45.399 twenty three, so showing investors just not interested. Also some 0:18:45.520 --> 0:18:48.760 less demand amid sharply higher interest rates. And this is though, 0:18:48.800 --> 0:18:52.720 despite huge interest in AI startups sparked by the success 0:18:52.720 --> 0:18:55.200 of open AI's Chatchipe. That's where money is going. 0:18:55.320 --> 0:18:58.160 Yeah, Investors report more than forty billion dollars into AI 0:18:58.200 --> 0:19:00.440 startups in the past six months. That's according to the data, 0:19:00.480 --> 0:19:03.080 including the ten billion dollar investment by Microsoft and open 0:19:03.119 --> 0:19:05.840 Ai and one point three billion dollars in funding for 0:19:05.960 --> 0:19:07.399 rival Inflection AI. 0:19:08.119 --> 0:19:10.520 All right, so let's get to it. Because back with 0:19:10.600 --> 0:19:13.200 us to talk about what's going on when it comes 0:19:13.280 --> 0:19:15.159 to the VC world. And we're delighted to have her 0:19:15.160 --> 0:19:17.800 back with us. Shila Patel. She's vice chairgeneral partner of 0:19:17.800 --> 0:19:21.320 b Capital. She's former chairman of Goldman Saccesset Management. She's 0:19:21.320 --> 0:19:23.840 with us on Zoom from Park City, Utah. Sheila, Nice 0:19:23.880 --> 0:19:25.760 to be talking with you again. Last time I think 0:19:25.800 --> 0:19:31.000 it was at the Milken Institute Global Conference in May. 0:19:31.160 --> 0:19:32.840 How are you and talk to us about your world 0:19:32.880 --> 0:19:34.080 and how things have changed. 0:19:35.680 --> 0:19:37.640 I'm great, Thank you so much, and it's so great 0:19:37.640 --> 0:19:40.040 to chat with you again. You know, I think the 0:19:40.080 --> 0:19:43.080 world since Milkin has had some good news, had some 0:19:43.160 --> 0:19:46.399 rougher news, but overall, I think it's been a fascinating 0:19:46.440 --> 0:19:51.399 period to see how investor sentiment hasn't necessarily responded to 0:19:51.440 --> 0:19:53.480