WEBVTT - Solid Payrolls Print Belies Labor-Market Softening 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 --> 0:00:18.960 Podcast with Carol Messer and Tim Stenebeck from Bloomberg Radio. 0:00:19.520 --> 0:00:23.880 And we've been talking about this morning's Labor Department report 0:00:24.079 --> 0:00:27.080 mixed in terms of non farm payrolls coming in really strong, 0:00:27.080 --> 0:00:29.960 but the unemployment employment rate excuse me, rising to three 0:00:30.000 --> 0:00:36.959 point seven percent. Wage growth also was Gosha, Yeah, why 0:00:37.000 --> 0:00:38.519 did my notes I don't know. For some reason, my 0:00:38.560 --> 0:00:41.120 notes were weird. I mean it was a lot of 0:00:41.240 --> 0:00:43.480 it was a lot of moving parts that didn't necessarily yes, 0:00:43.479 --> 0:00:44.720 it can take for your picture. 0:00:45.400 --> 0:00:48.879 It was I think Julia Cornado called it a squirrely report, 0:00:49.360 --> 0:00:52.600 right that a few of those, as we've been talking about, 0:00:53.720 --> 0:00:57.240 the household survey and the establishment survey go in completely 0:00:57.280 --> 0:01:01.080 different directions. So it's hard to really get a grasp 0:01:01.200 --> 0:01:01.960 on what is. 0:01:01.920 --> 0:01:03.480 Happening with this labor market. 0:01:03.680 --> 0:01:07.360 Is it just bursting at the seams with growth or 0:01:07.959 --> 0:01:11.760 is it starting to finally shrivel up under intense interest 0:01:11.840 --> 0:01:13.600 rate hikes. 0:01:13.280 --> 0:01:16.080 Which is why we rely on people like Julia Pollock exactly. 0:01:16.160 --> 0:01:18.399 She's chief economis at zip Recruiter. She's on Zoom from 0:01:18.560 --> 0:01:20.640 a Los Angeles Julia. Hey, good to have you back 0:01:20.640 --> 0:01:24.760 with us. Yeah, it is a little bit confusing, safe 0:01:24.760 --> 0:01:26.360 to say. And as Matt said, you know, he's been 0:01:26.400 --> 0:01:28.520 talking about the two different surveys, and we've gotten different 0:01:28.560 --> 0:01:31.480 reports from that monthly labor report. 0:01:31.360 --> 0:01:32.360 And even anecdotally. 0:01:32.440 --> 0:01:35.119 You know, we hear about big We hear about big 0:01:35.160 --> 0:01:37.399 tech companies firing people all the time. I know a 0:01:37.440 --> 0:01:39.720 ton of twenty something year old kids that are looking 0:01:39.760 --> 0:01:41.480 for a job and they say it's not easy. We 0:01:41.520 --> 0:01:43.640 had a story about a Harvard grad who sent out 0:01:43.800 --> 0:01:46.080 one hundred resumes before she got a job. 0:01:46.360 --> 0:01:46.720 Correct. 0:01:46.920 --> 0:01:50.360 So you know, at the same time, fourteen months in 0:01:50.400 --> 0:01:53.280 a row, we've beaten the estimate with non farm payrolls. 0:01:53.280 --> 0:01:54.480 So what is going on? 0:01:56.200 --> 0:02:01.120 Well, first the good the establishment survey was strong. Job 0:02:01.160 --> 0:02:06.160 growth was very, very broad based, and the economy seems 0:02:06.200 --> 0:02:10.080 to be adding not just low wage leading hospitality jobs, 0:02:10.080 --> 0:02:14.440 but high wage jobs in professional and business services. There 0:02:14.440 --> 0:02:19.040 were even job gains in the most unlikely places like construction, 0:02:19.240 --> 0:02:21.560 which we know has been hit hard by the housing 0:02:21.639 --> 0:02:25.560 downturn and high interest rates, and in transportation and warehousing, 0:02:25.720 --> 0:02:30.520 where recently businesses are reporting a freight recession. They're calling 0:02:30.560 --> 0:02:35.600 it truckers can't find loads to drive. So that was 0:02:35.639 --> 0:02:38.680 sort of the surprising positive in this report. That was 0:02:39.080 --> 0:02:44.160 extraordinarily positive even within dis establishment survey, though there are 0:02:44.200 --> 0:02:45.520 some warning signs. 0:02:45.600 --> 0:02:48.480 So I'm sorry, I interrupted, Please continue. 0:02:48.240 --> 0:02:50.680 No, I'll just say that not even the establishment survey 0:02:50.800 --> 0:02:56.520 is not a slam dunk. Wage growth cooled, working hours shrank, 0:02:57.480 --> 0:02:59.520 And then the two sectors that we know are having 0:02:59.520 --> 0:03:04.080 the most troubble, information and manufacturing continued to post job 0:03:04.120 --> 0:03:07.120 losses and I don't think we're at the end of 0:03:07.160 --> 0:03:11.040 those yet. The manufacturing reports that came out this week 0:03:11.240 --> 0:03:14.680 showed a steep drop in new orders, and that suggests 0:03:14.720 --> 0:03:18.000 that further job losses are coming down the pike because 0:03:18.120 --> 0:03:19.520 new activity is slowing up. 0:03:20.240 --> 0:03:25.760 So okay, So it was an extraordinarily strong report, but 0:03:25.919 --> 0:03:28.320 with some weakness in it. And then when you look 0:03:28.360 --> 0:03:33.320 at the household survey, three hundred and thirteen thousand jobless 0:03:33.480 --> 0:03:37.320 claims and four hundred and forty thousand job seekers and 0:03:37.680 --> 0:03:40.160 an unemployment rate that rose from three point four percent 0:03:40.200 --> 0:03:42.880 to three point seven percent, even worse. If you look at, 0:03:42.920 --> 0:03:47.960 for example, black employment was at a record love I 0:03:47.960 --> 0:03:50.240 think four point seven percent and has or four point 0:03:50.280 --> 0:03:52.560 six percent has risen to five point seven percent. 0:03:53.800 --> 0:03:55.840 That seems to be worrying. 0:03:57.440 --> 0:04:00.800 It is worrying. And what past research shows is that 0:04:00.840 --> 0:04:04.480 the household survey tends to be more sensitive when the 0:04:04.480 --> 0:04:08.200 economy is entering a downturn at sort of turning points. 0:04:08.520 --> 0:04:13.040 The Establishment Survey can get it wrong because its birth 0:04:13.040 --> 0:04:16.000 and death model doesn't sort of capture the fact that 0:04:16.040 --> 0:04:21.160 businesses are closing. The household survey, those ratios, the lake 0:04:21.240 --> 0:04:26.120 force participation ratio, and the employment rates for different population groups, 0:04:26.360 --> 0:04:30.760 those don't typically change. They're very sort of revealing, and 0:04:30.800 --> 0:04:33.039 that increase in the unemployment rate is very large. It 0:04:33.040 --> 0:04:35.200 puts it in the sort of top ten percent of 0:04:35.400 --> 0:04:40.320 any increases we've ever seen. It is concerning, and it's 0:04:40.400 --> 0:04:43.960 not just driven by good news for good reasons like 0:04:44.080 --> 0:04:47.800 increased participation that maybe explains about thirty percent of the increase. 0:04:47.960 --> 0:04:50.840 It's also driven by bad news, by an uptick in 0:04:52.240 --> 0:04:52.960 job losses. 0:04:53.640 --> 0:04:56.440 So is there any kind of net takeaway from this 0:04:56.520 --> 0:04:57.440 morning's release. 0:04:58.800 --> 0:05:02.160 I think the net takeaway is that the truth is 0:05:02.440 --> 0:05:07.159 probably softer than these blockbuster top line numbers would suggest. 0:05:08.279 --> 0:05:11.480 Many lave market indicators have come all the way back 0:05:11.520 --> 0:05:15.240 to their pre pandemic levels. Job switching is all the 0:05:15.279 --> 0:05:19.960 way back, according to the household survey. The quits rate 0:05:20.080 --> 0:05:22.680 and the jolt support also came pretty much all the 0:05:22.720 --> 0:05:24.920 way back to where it was before the pandemic. That's 0:05:24.960 --> 0:05:27.960 not really consistent with more than ten million job openings 0:05:28.200 --> 0:05:32.520 and continued blockbuster job gains like this. It's more consistent 0:05:32.560 --> 0:05:34.479 with sort of the kinds of gains we saw before 0:05:34.480 --> 0:05:37.320 the pandemic one hundred and hundred and ninety thousand jobs 0:05:37.320 --> 0:05:40.200 a month, and that's probably where we're headed, you know, 0:05:41.600 --> 0:05:44.360 if we managed to avoid a steeper downturn in tech 0:05:44.400 --> 0:05:47.560 and manufacturing and the cascading downturn. 0:05:50.040 --> 0:05:54.120 You mentioned information as one of the sectors that is losing. 0:05:54.240 --> 0:05:55.359 I guess do you mean it? 0:05:55.880 --> 0:05:59.839 Information technology is that you know, the Microsofts and the 0:06:00.000 --> 0:06:01.080 facebooks of the world. 0:06:02.120 --> 0:06:04.880 So the information sector contains a bunch of things in 0:06:04.920 --> 0:06:10.240 it tech, so software publishing, but also the media, and 0:06:11.320 --> 0:06:16.120 often the two go together because the tech sector uses 0:06:16.520 --> 0:06:21.360 advertising to expand its sales, which really depend on network 0:06:21.360 --> 0:06:26.359 effects and the all of the industries that rely on 0:06:26.440 --> 0:06:29.880 advertising spending then get hit when when tech is a 0:06:29.880 --> 0:06:30.960 bit of in the crosshairs. 0:06:31.240 --> 0:06:32.840 No, but you can see if you can see from 0:06:32.839 --> 0:06:35.520 the household sector essentially that we're at a turning point, 0:06:35.839 --> 0:06:39.320 that we're ahead of a downturn. Can you see also 0:06:39.400 --> 0:06:43.280 from the data, which industries are going to be, you know, 0:06:43.600 --> 0:06:44.960 losing the most jobs. 0:06:44.960 --> 0:06:47.600 Where are we going to see the most firings. 0:06:49.960 --> 0:06:52.680 So that's hard to know now because this downturn is 0:06:52.720 --> 0:06:57.479 so different from what we usually see. This is more 0:06:57.560 --> 0:07:01.560 of a white collar recession than past downturns have been, 0:07:01.600 --> 0:07:03.120 to the extent that there was a slow down. Right, 0:07:03.160 --> 0:07:06.480 this is still a very very strong labor market, but 0:07:06.760 --> 0:07:09.320 the weakness is not popping up where it usually does. 0:07:10.600 --> 0:07:14.520 That said, the interest rates sensitive industries are very vulnerable, 0:07:14.960 --> 0:07:19.040 and unless mortgage rates come down and there's an uptick 0:07:19.080 --> 0:07:22.880 in housing, we will likely see a downturn in constructor 0:07:23.040 --> 0:07:28.440 in construction employment soon, and manufacturing could still have quite 0:07:28.440 --> 0:07:31.800 a long way to go. Many retailers have reported in 0:07:31.840 --> 0:07:35.520 their earnings calls the last few weeks that they've seen 0:07:36.040 --> 0:07:38.720 much more softening in demand in the first few months 0:07:38.760 --> 0:07:41.200 of the year than they had expected, and that that 0:07:41.400 --> 0:07:43.119 is going to reduce their orders going forward. 0:07:43.280 --> 0:07:44.680 Hey, Jillie, you just got about a minute and a 0:07:44.680 --> 0:07:46.240 half or so left here. One of the reasons we 0:07:46.360 --> 0:07:48.000 like to talk with you is, you know, we get 0:07:48.120 --> 0:07:52.000 data points, certainly from private firms, we get it from 0:07:52.000 --> 0:07:55.360 the government. You guys are an employment marketplace, right, so 0:07:55.400 --> 0:07:58.280 you are seeing things in real time. Tell us what 0:07:58.400 --> 0:08:00.400 you are seeing on the platform in terms terms of 0:08:00.840 --> 0:08:04.280 demand for jobs openings and what it tells you. 0:08:05.680 --> 0:08:09.280 Right, So we see that job postings are still above 0:08:09.320 --> 0:08:11.880 their pre pandemic level, but that they've softened a lot 0:08:11.960 --> 0:08:16.480 more than the official job openings report from the Labor 0:08:16.480 --> 0:08:20.720 Department suggests job openings of down sixteen percent from their 0:08:20.760 --> 0:08:23.680 peak in the jaults report from the Labor Department, but 0:08:23.760 --> 0:08:26.960 about thirty six percent down from their peak online across 0:08:27.000 --> 0:08:30.640 the web. And job seekers are noticing a change in 0:08:30.640 --> 0:08:32.480 the dynamics and they're starting to feel a bit more 0:08:32.520 --> 0:08:33.480 nervous about the album. 0:08:34.640 --> 0:08:36.560 So what does that mean that people are probably less 0:08:36.600 --> 0:08:39.760 likely leaving jobs for new jobs? Are they more willing 0:08:39.800 --> 0:08:42.000 to go into the office rather than work from home? 0:08:42.679 --> 0:08:44.400 I'm just curious what that means. 0:08:44.760 --> 0:08:47.520 Right, And so one reason for the discrepancy between the 0:08:47.559 --> 0:08:52.000 payroll number and the employment level number is because the 0:08:52.000 --> 0:08:55.160 household survey kepture his gig employment and gig workers have 0:08:55.240 --> 0:08:58.880 been losing jobs the last few months or shifting from 0:08:58.880 --> 0:09:01.560 gigwork into payroll work. So there does seem to be 0:09:01.679 --> 0:09:07.920 a shift happening where workers are prioritizing security increasingly over flexibility. 0:09:08.559 --> 0:09:10.120 All right, we're gonna leave it on that note, Julia, 0:09:10.120 --> 0:09:12.400 Thank you so much. Julia Pollack, she's chief economist ever 0:09:12.400 --> 0:09:15.480 at zip recruiter on Zoom from Los Angeles, breaking down 0:09:15.520 --> 0:09:17.800 what they are seeing on their platform and how it 0:09:17.880 --> 0:09:19.839 kind of meshes with what we're seeing in the monthly 0:09:19.920 --> 0:09:21.520 jobs report. You seem worked out. 0:09:22.160 --> 0:09:25.679 I well, no, I feel like I've found an answer. Essentially. 0:09:25.760 --> 0:09:29.280 I was worried about the discrepancy all day, or I 0:09:29.360 --> 0:09:31.120 was thinking about it and talking about it all day. 0:09:31.320 --> 0:09:35.319 But I think Julie's explanation is great that before turn 0:09:35.720 --> 0:09:38.960 a downturn, for example, the household survey is more sensitive 0:09:38.960 --> 0:09:40.920 and shows you what's happening. It kind of shines the 0:09:40.960 --> 0:09:41.840 light in the right direction. 0:09:41.880 --> 0:09:43.040 You have to kind of look at the cycles and 0:09:43.080 --> 0:09:43.800 kind of where we are. 0:09:44.640 --> 0:09:48.240 You're listening to the Bloomberg Business Week podcast. Catch us 0:09:48.240 --> 0:09:51.600 live weekday afternoons from three to six Eastern Listen on 0:09:51.679 --> 0:09:55.720 Bloomberg dot com, the iHeartRadio app and the Bloomberg Business app, 0:09:56.000 --> 0:09:58.240 or watch us live on YouTube. 0:09:58.840 --> 0:10:01.400 I saw this Mattic interesting story. It was about cran 0:10:01.480 --> 0:10:04.959 based Global, which is the largest used digital asset exchange, 0:10:04.960 --> 0:10:08.800 saying the intersection of AI, artificial intelligence and crypto represents 0:10:08.800 --> 0:10:12.520 an important opportunity for entrepreneurs, including helping to prevent some 0:10:12.559 --> 0:10:15.600 of the excesses cited by critics of the technology. That 0:10:15.720 --> 0:10:17.560 to me is interesting. 0:10:17.760 --> 0:10:17.920 Yeah. 0:10:18.000 --> 0:10:22.960 No, I think it's absolutely fascinating. The intersection between blockchain 0:10:23.520 --> 0:10:28.760 technology or distributed letter of technology and artificial intelligence is 0:10:28.800 --> 0:10:32.960 something that we focus on on Bloomberg Crypto, which is 0:10:33.280 --> 0:10:36.600 every Tuesday at one pm on Bloomberg Television. 0:10:36.640 --> 0:10:39.280 Shameless problem. Yeah, but all right, so let's get into 0:10:39.320 --> 0:10:41.520 it with our guests. Jack o'holleran is co founder and 0:10:41.559 --> 0:10:44.559 ceof Scale Labs. He joins us on Zoom from San Francisco. 0:10:44.640 --> 0:10:46.960 Jack also co founder of Actana I hope I'm saying 0:10:46.960 --> 0:10:50.160 it correctly, co founder of incent a Line, and has 0:10:50.160 --> 0:10:54.280 held some executive positions at companies like Good Technology, and Motorola. 0:10:54.400 --> 0:10:54.640 Jack. 0:10:54.840 --> 0:10:57.960 Nice to have you here talk to us about blockchain 0:10:57.960 --> 0:10:59.920 and AI. What's the potential? 0:11:01.000 --> 0:11:03.839 Yeah, pleasure to be here today. So I think we're 0:11:03.840 --> 0:11:07.240 at the very early stages of what will be perhaps 0:11:07.280 --> 0:11:10.320 the most transformational technology movement of the last twenty years. 0:11:11.200 --> 0:11:13.640 We're already seeing impact today and I think, you know, 0:11:13.640 --> 0:11:14.720 we're still in the early days. 0:11:15.200 --> 0:11:17.400 Well, what do you mean specifically that's big and broad. 0:11:18.720 --> 0:11:22.040 Yeah, yeah, So diving in a little deeper, I think 0:11:22.160 --> 0:11:25.160 the headlines are always about this amazing intersection where we 0:11:25.240 --> 0:11:30.320 have artificially intelligent bots that are making purchase decisions for us, 0:11:30.320 --> 0:11:32.800 that are managing our wallets, that are you know, this 0:11:32.920 --> 0:11:36.959 fully connected AI and blockchain ecosystem. But today what's happening 0:11:37.040 --> 0:11:40.760 is the first immediate impact is that applications are actually 0:11:40.800 --> 0:11:44.640 being developed Web three applications in particular, at an alarmingly 0:11:44.720 --> 0:11:47.240 fast rate with the help of AI. So it's actually 0:11:47.320 --> 0:11:50.160 AI is playing a role in blockchain development at the 0:11:50.160 --> 0:11:53.080 application level, at the infrastructure level, at the QA level. 0:11:53.400 --> 0:11:56.959 So blockchain devs are using AI to build applications faster. 0:11:57.040 --> 0:11:59.680 So we're probably my sense of what I'm seeing is 0:12:00.120 --> 0:12:02.760 we'll have at least a ten x growth and applications 0:12:02.760 --> 0:12:05.400 built in the web three space thanks to the support 0:12:05.400 --> 0:12:07.320 and help of AI. So that's the first piece and 0:12:07.480 --> 0:12:09.400 happy to kind of go into the other pieces as well. 0:12:09.640 --> 0:12:09.840 Well. 0:12:09.880 --> 0:12:14.600 I just wonder, you know, who's using these applications because 0:12:14.600 --> 0:12:18.680 I was looking, for example, recently at the Solana phone 0:12:19.360 --> 0:12:24.000 and it's got all of these you know, decentralized apps 0:12:24.040 --> 0:12:25.880 on it. But I just don't know what I would 0:12:25.880 --> 0:12:28.760 do with all this stuff. It's like, we have this 0:12:28.880 --> 0:12:33.959 technology looking for a problem to solve. I get what 0:12:34.000 --> 0:12:37.040 you can do with with cryptocurrency, and I love the 0:12:37.120 --> 0:12:42.000 idea of trustless decentralized currency, but I just don't understand, 0:12:43.720 --> 0:12:47.880 you know, who's using the applications the other applications that 0:12:47.920 --> 0:12:49.800 we put on the blockchain yet. 0:12:49.920 --> 0:12:51.760 Yeah, and you know what you're calling out the That 0:12:51.920 --> 0:12:54.160 is the elephant in room. That is the problem that 0:12:54.200 --> 0:12:56.360 we at Scale are working on solving every single day. 0:12:56.400 --> 0:13:00.120 And for example, I worked in mobile back in two 0:13:00.120 --> 0:13:02.520 thousand and five, six seven, two thousand and eight, and 0:13:02.800 --> 0:13:05.600 I have to tell you the amount of applications utilized 0:13:05.679 --> 0:13:09.040 was just you know, sparse, no one. The device speeds 0:13:09.080 --> 0:13:11.440 were horrible, the UX was horrible, the battery, live, the 0:13:11.440 --> 0:13:15.040 compute power. All of a sudden in twenty ten, millions 0:13:15.040 --> 0:13:18.040 of people simultaneously playing each other in games across the 0:13:18.080 --> 0:13:20.439 world unmobile, And we're at one of those moments, I 0:13:20.480 --> 0:13:23.200 believe in Web three where right now there's there's some 0:13:23.240 --> 0:13:26.480 phenomenal use cases out there, but the UX is horrible, 0:13:26.640 --> 0:13:31.160 the transaction costs are high, the access points and accessibility 0:13:31.200 --> 0:13:32.400 you have to be an engineer to use a lot 0:13:32.440 --> 0:13:36.280 of these applications, and so within the Ethereum ecosystem in particular, 0:13:36.640 --> 0:13:39.160 there's just been some I think some amazing pushes on 0:13:39.200 --> 0:13:41.680 the UX level. They're going to make these apps easier 0:13:41.760 --> 0:13:44.400 to use because to your point, we are not seeing 0:13:44.480 --> 0:13:47.800 the actual throughput in users and and it's in large 0:13:47.800 --> 0:13:50.040 part the similar gating issue we had in mobile. 0:13:50.760 --> 0:13:53.160 By the way, talk to us for a moment about scale, 0:13:53.600 --> 0:13:57.960 because what you guys are doing is addressing a real 0:13:58.080 --> 0:14:02.760 problem in the Theorium ecosystem, which is gas fees that 0:14:02.800 --> 0:14:03.680 are out of control. 0:14:03.800 --> 0:14:06.720 Right, yeah, exactly, And I think it kind of like 0:14:06.760 --> 0:14:08.839 it goes back to your point earlier, where if you 0:14:08.960 --> 0:14:13.040 build applications with really cool use cases, but they're incredibly 0:14:13.080 --> 0:14:15.200 cumbersome to use, they're incredibly expensive to use. 0:14:15.240 --> 0:14:16.080 Who's going to use them? 0:14:16.120 --> 0:14:18.360 Well, the answer is the same people that use out 0:14:18.360 --> 0:14:21.400 Web three apps today and it's probably like ten thousand developers. 0:14:21.960 --> 0:14:24.480 And so Scales set out to build a it's almost 0:14:24.520 --> 0:14:27.480 a Web two like business model where application developers are 0:14:27.520 --> 0:14:30.320 able to pay in advance for the gas fees and 0:14:30.360 --> 0:14:32.360 then take the burden off the end user for the fees. 0:14:32.400 --> 0:14:35.400 It also creates better unit economics and also creates for 0:14:35.600 --> 0:14:39.320 you know, faster processing, faster blockchain execution. So our goal 0:14:39.360 --> 0:14:40.800 at the end of the day is to open up 0:14:40.920 --> 0:14:45.080 Web three to normal users and help application developers actually 0:14:45.080 --> 0:14:47.480 fulfill these big promises and hype that we've been reading about. 0:14:47.600 --> 0:14:49.680 So is it all developers that are using that are 0:14:49.680 --> 0:14:52.280 on scale at this point? Who who is using it 0:14:52.320 --> 0:14:53.120 and who's on it? 0:14:53.440 --> 0:14:55.960 So the largest use case, which is probably not a 0:14:56.000 --> 0:14:59.080 surprise to people in terms of actual end users, are games. 0:14:59.160 --> 0:15:02.480 So game are a phenomenal early use case for any technology. 0:15:02.520 --> 0:15:05.280 I mentioned earlier mobile and you know, the first you know, 0:15:05.800 --> 0:15:07.440 you know, and I worked at Good Technology and we 0:15:07.480 --> 0:15:09.560 had ninety two of the top one hundred Fortune one 0:15:09.640 --> 0:15:12.320 hundred companies as customers. And you know what the only 0:15:12.520 --> 0:15:16.240 application anyone even used was email, and everyone remembers those days. 0:15:16.280 --> 0:15:19.120 But we're going through a similar thing here in blockchain, 0:15:19.160 --> 0:15:22.640 where games are the leading frontier because it makes a 0:15:22.680 --> 0:15:24.720 lot of sense and they can operate on the back end. 0:15:25.760 --> 0:15:30.240 It fits the profile and the social demographics of the users. 0:15:30.760 --> 0:15:33.600 And the next phase from I believe my view is 0:15:33.640 --> 0:15:36.880 our web three social applications that are disrupting this whole 0:15:37.080 --> 0:15:40.480 creator economy space and content space, and we're just seeing 0:15:40.480 --> 0:15:42.880 a lot of growth there as well. But the developers 0:15:43.040 --> 0:15:47.280 utilize scale to your question, to create applications and to 0:15:47.360 --> 0:15:49.480 run applications faster. But at the end of the day, 0:15:49.480 --> 0:15:50.840 we all want to service the end user. 0:15:51.400 --> 0:15:53.240 It's funny. 0:15:53.400 --> 0:15:56.000 I don't know, Jack, if you're familiar with the Bloomberg terminal, 0:15:56.600 --> 0:16:00.840 but you can do so much it's mine boggling what 0:16:00.880 --> 0:16:03.400 you can do with this terminal. And the most used function, 0:16:03.480 --> 0:16:08.880 of course is message. Like email is the killer app here. 0:16:10.200 --> 0:16:10.640 Let's talk. 0:16:10.720 --> 0:16:12.720 Let's get back to AI for a minute, because I 0:16:12.720 --> 0:16:16.120 think it's really interesting that we see open AI doing 0:16:16.160 --> 0:16:18.720 well and there's clearly going to be a battle between 0:16:18.760 --> 0:16:21.560 the biggest players to see whose. 0:16:21.320 --> 0:16:23.200 Model can learn the most. 0:16:23.280 --> 0:16:28.600 And but you are looking forward to a decentralized AI model, 0:16:28.600 --> 0:16:32.320 and I wonder if that somehow takes the danger out 0:16:32.320 --> 0:16:32.520 of it. 0:16:32.560 --> 0:16:32.720 You know. 0:16:32.800 --> 0:16:36.280 Alex Karp from Pallenteer the other day said, man, the 0:16:36.280 --> 0:16:38.440 products we make are so powerful, I don't even know 0:16:38.440 --> 0:16:39.800 if we should be selling. 0:16:39.480 --> 0:16:41.600 Them, which I thought was pretty interesting. 0:16:42.040 --> 0:16:44.520 Is a decentralized AI going to solve a lot of 0:16:44.520 --> 0:16:45.160 those issues? 0:16:46.160 --> 0:16:48.720 You know it is, But my personal feeling is that 0:16:48.760 --> 0:16:52.800 we're going to see the actual trustless decentralization come later, 0:16:53.280 --> 0:16:56.000 and the first piece will be, you know, seeing Web 0:16:56.040 --> 0:16:59.239 three applications where we actually have the power and benefits 0:16:59.240 --> 0:17:02.160 of AI and terms of automation and help and writing 0:17:02.240 --> 0:17:07.200 and recommendations and conversation, connecting with you know, NFT gating 0:17:07.280 --> 0:17:10.959 and in programmable currencies and smart contracts, and then you know, 0:17:11.000 --> 0:17:12.680 eventually we're going to get to this point where people 0:17:12.680 --> 0:17:15.239 are saying, hey, well, why are we again trusting the 0:17:15.280 --> 0:17:19.359 world's three largest companies to essentially make ninety percent of 0:17:19.400 --> 0:17:21.840 the decisions that are made on the Internet. And that's 0:17:21.840 --> 0:17:24.080 when you're going to start seeing those models start living 0:17:24.080 --> 0:17:27.560 in a more open source, transparent, trustless manner and seeing 0:17:27.600 --> 0:17:32.200 that that kind of like ultimate nirvana blockchain and AI synergy. 0:17:32.200 --> 0:17:34.480 But it's still always often rightly. 0:17:34.440 --> 0:17:36.720 You know, I'm thinking of people me who are listening 0:17:36.840 --> 0:17:40.000 and just you know, normal people, regular people who maybe 0:17:40.040 --> 0:17:43.879 aren't as meshed in this world or the you know, 0:17:44.000 --> 0:17:48.320 blockchain world. So how does it, you know, practically impact 0:17:48.359 --> 0:17:51.280 us potentially the stuff that you're talking about the integration 0:17:51.359 --> 0:17:53.600 of AI and blockchain. 0:17:55.000 --> 0:17:57.480 Yeah, so let's look at it. I think a good 0:17:57.600 --> 0:18:00.000 use case. Let's look at music for example. So let's 0:18:00.119 --> 0:18:03.479 say there's a decentralized music platform and right now, artists 0:18:03.520 --> 0:18:07.120 that put music on iTunes or Spotify get a very 0:18:07.160 --> 0:18:09.320 low fraction of return and there's lots of you know, 0:18:09.359 --> 0:18:12.160 middleman hands in the way. There are these decentralized music 0:18:12.160 --> 0:18:15.960 platforms that are popping up where actually artists directly submit music. 0:18:16.560 --> 0:18:20.720 People pay in still small increments, but instead of ten 0:18:20.720 --> 0:18:24.600 percent of their payment going to artists, ninety some percent 0:18:24.720 --> 0:18:26.640 is going and the other piece is going to the community. 0:18:26.720 --> 0:18:29.040 Well that's a cool Web three application. But the way 0:18:29.119 --> 0:18:31.720 I AI would intersect is all of a sudden, you're 0:18:31.760 --> 0:18:35.960 getting conversational input in terms of you know, what you 0:18:35.960 --> 0:18:38.000 should listen to, how you should listen to, artists are 0:18:38.040 --> 0:18:42.439 creating music faster, better, more specific, more tailored to certain audiences. 0:18:42.440 --> 0:18:46.240 And ai is is really a creation tool, and so 0:18:46.280 --> 0:18:49.040 you're going to see you know, both artists and and 0:18:49.119 --> 0:18:51.560 it's a creation and creation tool. So you're gonna start 0:18:51.560 --> 0:18:54.159 seeing the kind of I guess symphony of these end 0:18:54.160 --> 0:18:56.680 results come together where people are going to start. You know, 0:18:56.720 --> 0:18:59.639 we're gonna start creating more things, faster and more and 0:18:59.640 --> 0:19:03.280 for more specific audiences and with programmable money without less middleman. 0:19:03.359 --> 0:19:04.800 That's that's one example. 0:19:04.440 --> 0:19:06.359 Of where you know, and hopefully you don't need an 0:19:06.359 --> 0:19:08.480 engineering degree to use that application, which is where we 0:19:09.000 --> 0:19:09.240 need to. 0:19:09.200 --> 0:19:10.160 Get to go today. 0:19:10.200 --> 0:19:12.960 I was coming to work and I was asked Apple 0:19:13.040 --> 0:19:15.919 Music to play me a radio station that was centered 0:19:15.960 --> 0:19:18.359 around Black Sabbath. So I wanted to hear stuff that 0:19:18.480 --> 0:19:20.840 wasn't Black Sabbaths. I've heard all of it a million times, 0:19:21.200 --> 0:19:23.879 but like Black Sabbath. And then I realized that Apple 0:19:23.960 --> 0:19:27.879 Music is just selling me with this radio station what 0:19:28.000 --> 0:19:29.960 it wants me to hear that's like Black Sabbath. So 0:19:30.000 --> 0:19:34.080 I've had something decentralized. I could hear true Black Sabbath 0:19:34.240 --> 0:19:34.840 esque metal. 0:19:35.640 --> 0:19:37.720 Yeah, And and you look at all the drama. And 0:19:37.920 --> 0:19:40.679 you know our Twitter feeds and our social feeds, and 0:19:40.720 --> 0:19:43.679 who's in control of those algorithms. Well, eventually those are 0:19:43.720 --> 0:19:46.640 going to be all large language model algorithms that are 0:19:46.760 --> 0:19:49.560 super smart and intelligent. But you know who's in control, 0:19:49.840 --> 0:19:53.399 who's managing my political view? You know, get what you 0:19:53.640 --> 0:19:54.760 will to and yeah, we. 0:19:54.800 --> 0:19:56.399 Got to run. Jack, Thank you so much of a 0:19:56.400 --> 0:19:59.960 great weekend. Jack o'holler and co founder CEO of Scale Lab. 0:20:00.720 --> 0:20:04.280 You're listening to the Bloomberg Business Week podcast. Catch us 0:20:04.320 --> 0:20:08.320 live weekday afternoons from three to six Easter on Bloomberg Radio, 0:20:08.520 --> 0:20:11.800 the Bloomberg Business app, and YouTube. You can also listen 0:20:11.920 --> 0:20:15.000 live on Amazon Alexa from our flagship New York station, 0:20:15.480 --> 0:20:26.560 Just say Alexa play Bloomberg eleven thirty. 0:20:30.359 --> 0:20:34.800 All right, everybody, if you're feeling sluggish at work, unmotivated, overworked, 0:20:34.840 --> 0:20:38.520 and with no real work life balance, enter the Ketamine Retreat. 0:20:38.600 --> 0:20:41.320 Gating popularity among those ambitious professionals who want to show 0:20:41.400 --> 0:20:44.000 up both for themselves and their families. This story online 0:20:44.000 --> 0:20:46.320 at Bloomberg dot com, Slash BusinessWeek, and of course, on 0:20:46.320 --> 0:20:49.200 the Bloomberg terminal. Bloomberg News startup supporter Ellen Hewitt row. 0:20:49.240 --> 0:20:52.760 It wrote it, excuse me on zoom from San Francisco 0:20:52.960 --> 0:20:55.640 Theater at Bloomberg businesswektil Weber here in our Bloomberg Interactive 0:20:55.640 --> 0:20:58.840 Broker studio. Okay, I want to know the pitch here. 0:21:00.080 --> 0:21:01.919 Come to you and say what you know? 0:21:02.040 --> 0:21:03.119 Sometimes you just don't know. 0:21:03.640 --> 0:21:03.760 Uh. 0:21:05.400 --> 0:21:06.560