What's up? What's up? What's up? I'm brand man Sean and I'm Corey and we are back with episode number 33 of our necessary podcast. You can catch us every Tuesday, every Thursday on YouTube, Spotify, Apple, whatever you stream, podcasts, talking about the music industry, music business, entrepreneurship, but also the content creator economy as a whole.  So check out this right here because the new way to break out in content is creating bad content on purpose. I'll show you exactly what I mean when I play this clip right here.  I don't like that. I mean, I maybe have like five that I really, really like. I've yet to delete them all. I have no process. I just kind of, I think of something bad and then I do. OK, did you hear that? Doja Cat just revealed a mindset shift you need on TikTok, especially if you're feeling burnt out or you're feeling like you're putting in a ton of effort, but you're not growing. I've grown viral TikTok accounts and I also design creative content strategies for national brands and influencers on TikTok. Right now, it's becoming clear that there's one strategy that the most brilliant marketers do that you can do here on TikTok. Kanye West has used Doja Cat strategy to market himself and his products to make billions of dollars. Trying to be good or come up with good ideas is often boring. Kanye, Doja Cat and other marketers take a good idea and do the opposite. With the Kanye West gap collab, the good, boring idea would have been to display his clothes and gap beautifully on the shelves, but instead he put them in the worst idea possible in trash bags. This was brilliant because it made him viral. People would have been bored if he had just put the clothes on shelves. And here's how this is going to help you grow on TikTok. On my viral account, I was feeling stuck at about 150,000 followers. While my videos were getting about five figures, 10,000 views, 30,000 views, 60,000 views and out of frustration one day, I just kind of woke up and I was like, you know what? I'm not going to try on this video. I'm just going to have fun. I'm going to try something I haven't done before. And I made this video, my 15 million view video. Being good and being perfect is the enemy. Try to be bad. Try to be bad. What do you think about that, Corey? I think it's contextual advice, right? I think it is good advice. It kind of goes back to the conversation we had about just create more so to learn like who likes you, what you're good at, that type of stuff, right? I think for the artists of Doja Cat or Kanye, caliber, it's more about humanizing them. That's the marketing, right? You are now this larger than like entity. We need you to do things that make you feel relatable, regular, right? And so what do we typically associate with high level acts, artist brands, really hot quality content? What do we typically associate with regular people? Much lower quality content, right? Creator A, who was a mega superstar. Creator B, who was a guy with 10,000 followers. Creator A might be using the red camera to make his or her TikToks. Creator B might be using the iPhone 8. It's only different. So we tend to associate lower quality execution of ideas and content style with like regular people. So we watch Doja Cat very geniously use that to submit her brand, right? Like if you looked at Doja Cat really early on on TikTok, all her companies always said, hey, she's just like me for real. She seems just like a regular person, right? So that was a part of her game plan. Let me, even though I don't think, I don't know, now watching that, I don't know that. I always thought she was intentionally going for that. Now it sounds like it was an accident, you know what I'm saying? But I always thought that was a game plan. But that's why I worked. Hey, we can make this larger in life figure, look like a regular person. And it's different because if you just did some super hot quality stuff, people, it wouldn't be as exciting because people are expecting that from you. Same thing with Kanye. Like he said, be easy for Kanye to go set up some massive display in like a gap store or a mall. And that will be the norm for someone of his size, but what's different, what's gonna draw a camera session?  However they want to. So like I said, I think good advice contextually, but the key part of it is like, like I said, like being bad will either lead you to your eventual genius idea. I do agree with that. Or being bad will create something that other people like that you don't like. You know what I'm saying? Like you do something. I mean, we've seen it, right? How many times have we just thrown up a video or a piece of content? Oh, we gotta make the deadline.   Like you ain't never gave me no advice. Like this, you like, bro, what?   You liked this video that took me two minutes out through it because, you know, EJ was young and that's about giving some videos on time. So people are interesting, man. That's the one thing I thought I would remember. But people are interesting. People are fickle. You would never truly have a gauge on what people like because people's tastes will literally change overnight. And, you know, like I said, to this point, the best thing you can do is create, even if you feel like it's going to be bad and just put it out there and see how the marketplace feels about it. Let that guide where the rest of your process goes. Hey, man, you use one of my favorite words, which is context. Like that really does dictate how to go about this advice because talking about Kanye, yes, you obviously could do it in this high-end type fashion, but doing it in a trash bag is something that's less expected for people at his level, right? So you're always getting view through the context of how people view your world, right? Or your peers, right? Your category is a better way of saying it, right?  But if I look at you as an indie artist, right? Different. It's different, right? An indie artist that doesn't have anything going for themselves, you only have a thousand listeners.  Without you building the story.  Everybody else will create it for him. You would have to push that story just to make me feel it anywhere near the same and I still wouldn't view it exactly that way. So yeah, the bag, good, I don't know, but one thing I can say is, especially when you're in a Kanye space where you have the ability to give a lot of visibility to whatever you're doing, it becomes almost easy from a standpoint of people get used to one thing and then you just do the opposite, right? That's what bad is essentially coming down to. You're like, oh, I'm just gonna give it this other, I'm gonna do it differently. And because of who I am, it brings validation to it where someone else might have to do it differently and then also convince you while it's still good. But people are gonna assume, oh, this is Kanye, this is genius, just because he did it.  Right, it's not a concept. It's a concept that you got money, you broke when you don't. Yeah, exactly. It's like, just like, it's no different than, have you ever seen artists that you were watching since they were like small? You could tell they were like really grounded. And then you remember the day they post like their first like hot quality music video, something like that. You feel like they leveled up, right? It's like, they'll tell us with drops of hot quality video every time she drops one, but it's not special because we expect tell us with the drop hot quality videos. But for this new artist who we watch shooting videos with iPhone, this new HD video that he dropped is cool because it feels like a level up moment, right? So even in that context, the marketing might be like, oh, it's genius. This artist finally is able to X, Y, Z, writing that narrative is much different for them. So that's why I say like perception plays a big part into it, positioning of the artist plays a big part into it. And it's also why I don't knock the way he gives the advice because he did mention like as a marketing himself, he mainly works with national brands. So he is mainly working with people who are on that level, probably trying to seem more reliable, you know what I'm saying, trying to, you know, to your point, take what would be your regular idea and make it seem more genius because we as this big brand are doing it. So the audience of people that he's probably talking to, like I said, it makes sense for their audience. For, like you said, those smaller artists who might be listening to this, like I said, to me, the value in creating bad content is more about getting yourself into the motions, getting yourself comfortable being on camera. Cause there are a lot of things that we do look at from artists.  And it was genuine accident, you know what I'm saying?  So yeah, that's what I want people to take away. Well, I'll say the other thing for me is just the perspective that comes with saying I'm going to do something bad, right? Because you force yourself, right? Just as an exercise to get out of your box and say, what would make me completely uncomfortable to do? Not just like, oh, I don't like speaking to people, right? Cause that's one way of saying, oh, I'm uncomfortable doing this and I got to get better at that skill. So not that, but hey, I'm cool. I'm good at posting videos. I'll post plenty of videos, but what would make me uncomfortable cause I think it's a bad idea and it would just suck.  And a lot of times we get anchored based on what we already like. If we don't go through some exercise that starts with the perspective shift, then we start to lose that punch in whatever we post. So just creating a starting point, even if it's just mentally as that exercise is going to pick you down a different path. And I don't think people use mental exercises like that enough, but companies, content teams, many of the artists that I know who do it well and do it consistently, it's actually always these types of exercises cause you can't just like churn out creativity again and again and again without it starting to become dull and it's not coming from a new perspective. So it's two things, right? There's, hey, I'm going to continue to experience and consume new things. So I have new information to work with and creative raw material to build something from. And secondly, I'm going to strategically make myself think about something from a different perspective, all right? So it was like, well, what if I had to start with a letter? Or what if, you know, I would do something that all my audience hates? Like, who does my audience hate? And what if I did the same thing that they did, but I did it in a way that they liked it? But it's just weird exercises that literally just forces you to think differently. Just as simple as that. So that's my biggest takeaway, right? Do the exercise and consume new information. Those two things will put you above most people in general. Yeah, I understand. A lot of times your most genius idea will come from you stepping out your comfort zone. One thousand, one thousand. And with that being said, cause this is a TikTok special episode today, by the way, we played that TikTok clip for some advice, but now we got to talk about TikTok and the heist that they're pulling. They're about to run some game on the industry. That's probably crazy. Directly labels that they're about to come for TikTok. They might want to shut TikTok down. Let me tell you why. Imagine being the TikTok star and next thing, you know, 57% of the sounds on your videos has been completely muted. You don't have no sound on your videos. Most of your videos at this point, your back catalog. So now, once you know you don't have sound, the videos don't really get watched like that. We've all seen those videos on TikTok and they're muted and it's like, I'm just gonna go to another video. It's awkward. It's awkward. It's real weird. You don't know what's going down. And sometimes you're like, I can tell there's a good video, but I will, right? That's the type of experience that's happening on TikTok right now being tested in Australia. And why is TikTok muting sounds? Well, music business where why did an article on this, and it basically breaks it down like this, right? So one, the test involves limiting access to songs for a select group of users in the market when they upload new videos. So they don't even want certain sounds to be available from these major labels because TikTok's trying to figure out, can we survive without major record label music? Can we get popping? Can we stay popping without music from the record labels? And obviously the record labels aren't feeling this. So they're muting all these different sounds in the Australia territory where you use those songs before, oh well, can't use them again. And now if anybody else wants to use them in the future, they can't. So what's TikTok doing on the other side? They're also generating music with AI. Trying to see, can we just generate music with AI and users not even notice or care and they still create successful unborrowed content instead of us having to pay these record labels because these record labels keep complaining and wanting new things from us day by day. That is creating an issue. And that's why they're calling it a highs for TikTok because one, TikTok use record label music in the beginning and the record labels are like, hey, y'all need to pay up. TikTok said no for a long time, a good amount of time. And then finally they agreed to a fixed deal. When they agreed to that fixed deal, the record labels, many didn't like that, but they got a fixed deal. They last, well, two to four years, whatever that term was, right? And by the way, when I say the record labels didn't want the fixed deal, they wanted to be based on the amount of streams and activity that actually happened, right? So they had all this happen, got record labels to agree to a deal that the record labels didn't even want to do. And then they get to this point where they're testing. All right. This agreement's probably going to start in in pre-sum. Yeah, I mean, I see the writing on the wall. Instead of having to negotiate with these pools, let's see if we don't need these pools at all because that takes away leverage even more. So they see us winning in this territory and things are popping through this music made by AI. Why do we need labels? Cause we got our indie artists. The indies are always going to be creating new music anyway, day by day, trying to pop. Cause then the labels don't own that yet. And then secondly, AI, oh, that'll fill in the gaps in terms of the quantity we might need. TikToks, pulling a finesse. I don't even know, we should talk about how it might affect the consumer side of it and the artist side of it. But overall, if they pull this off, recollect was going to be angry. Like different type of anger. Like, oh, another level.  So like, here's the stat. According to TikToks, end of the year recap, 13 out of 14 billboard hot 100 number one songs in 2022 were driven by significant viral trends on TikTok, a lot of leverage on TikTok. So, you know, the labels, they need TikTok or they really, really, really want TikTok. Why? Cause we weren't seeing us a clear engine to drive music streams like we were and like we have seen since TikTok came about. Yeah. All right. So we know they want it and the record label's problem is they don't do well at innovating and bringing attention to their music, especially at scale at a price that they can't, that they actually can't pay. So what do we do? We keep waiting for new technology to pop up and then try to utilize our rights that we hold to leverage a deal in our favor. We can't create TikTok. We can't create Spotify. It's just not in our system and infrastructure to have the mental capability to do it well and manage it and continue to grow it. That's just not their expertise. So Spotify gets leverage. Oh, well, let's try to own some of Spotify. TikTok gets leverage. Let's try to own some of Spotify or I mean, let's try to own some of TikTok or let's try to do a deal with them early enough on. But these tech companies and TikTok is like, like the indie artists, like the new age indie artists, they know their value, bro. Yeah. And they're trying to own the whole thing themselves. They don't want to bow down to the label at all. Yeah, it's going to be crazy, bro. Because I was just thinking about this, right, too. Because TikTok has sound on, which for those of you that don't know, sound on is TikTok's distribution company. And what do we just, you vaguely touched on it last episode, episode before, right? Where distribution companies are a lot of them times by the new regular levels, right? 100%. Now, this is how I'm seeing it with TikTok.  So no major label, artist music, can be used on the platform in Australia for now, assuming everywhere if there's hits. Now, let's think about, because you said how would this affect consumer artists? This is what I see, bro. Think about the Trigodon effect, right? I'm a major label. I can't go to this platform that has, you know, significantly benefited me because the music isn't available there. So not only do major labels lose a large chunk of their promotional assets, they lose everything that comes with that, right? But then on top of that, if I'm an artist who has been finding significant success on TikTok, then now I don't even wanna go sign to a major label because it's gonna completely cut off my priority engine, my priority vehicle, you know what I'm saying? And so who picks up the slack of that? TikTok and their sound on distribution, right? We're not a major label. So we don't violate our own rules. We have the growing leverage to provide a lot of things for you that, you know what I'm saying? These labels can provide outside of maybe capital, because I don't have a sound on it. It's giving out like deals or anything yet, but I'm pretty sure they have DSP relationships. They're giving out some money. They have? Okay. Yeah, I know some artists. Right, so we can do for you what a major label can do. We can, you know, of course, help you do some backend things on the on to help you grow. And you can keep this whole funnel within the TikTok ecosystem. So now we can go out there and we can push the narrative, hey, artists can be successful on TikTok despite major labels or artists can be successful in music despite major labels. All they need is to help of your friendly neighborhood, distribute like a sound doing or something. So that's what I think is gonna happen is it's gonna take this whole generation of artists who value the ecosystem of TikTok more than they necessarily value the ecosystem of a label because a lot of these artists will come to understand TikTok before they ever come to understand the label system because it's easier access.  Yeah, you've been in a relationship early. Yeah, so that's how I look at it. It's like almost like, hey, we're going to use this influence we have to train the next generation of music artists and music stars who already see us as the way out to only fuck with us and think about what you'll be given up by accepting help from people that we are at war with. Yeah, because if you think about most artists, but the most artists with the pop and TikTok presence is a hundredth of something that's going to pick TikTok over the label any day. Most, sure. Okay, yeah. It's the very least by TikTok has first rider refusal. Yeah, yeah, exactly. And then like they also, they are the A and R, right? I can see this creator when he's first hopped on and see when he first asked about our video and I'm like, hey, this guy only got a thousand followers, but he just caught a 10 million view TikTok last week. Let's reach out to him to give him some crazy deals to sound on because we can also just leverage more visibility on the platform because we know that's what they want. Saving us some money, saving us some dollars, helping us build our narrative because TikTok is a narrative building law right now. I don't think a lot of people realize it, but we talked about it on, I think maybe on another episode where like, you can tell a lot of the moves they're making right now aren't necessarily because like, they think it's going to like cap immediately. Like they're setting the stage for the future. You know what I'm saying? Like they're setting the stage so that in two or three years when the conversation can be who's competing with major labels? TikTok, you know what I'm saying? Who's competing with blah, blah, blah, blah? TikTok, you know what I'm saying? And like we have been very vocal over the last six, I've only been doing this podcast and saying that, hey, TikTok is competing with YouTube, you know what I'm saying? YouTube has been for the most part, the only real social media platform with a direct pipeline into the music industry. From what I can tell, Instagram doesn't really seem to have one like that. You know what I'm saying? Twitter, most of them don't really seem to like have as deep of a relationship or be as deep in bed with the music industry as YouTube is. You know, TikTok has put themselves in the position to be like YouTube in that same sense, but in a different way. And I mean, both of them are probably scary to labels, you know what I'm saying? Because like I said, if I'm an artist and I know I can go pop on TikTok and sound on it, get me right, I'm gonna make some money on YouTube, you know what I'm saying? YouTube would get me right if I played the rules right. Why would I go over there and jeopardize half of my promotion engine? You know what I'm saying?  They'd like, like... Do you think that it'll get to that point where TikTok's straight up saying, hey, if you're using a record label, we're not gonna have you on here? I think so because I mean, because the individual artist can't control how the licensing agreement goes, right? Like TikTok isn't able to negotiate something that the labels find fair and the label's not able to negotiate something that TikTok finds fair, then the relationship is gonna dissolve. And so either way, those artists are gonna kind of be left in limbo. So what's the difference if that happens? You know what I'm saying?  Do you think the consumer music will matter? No, I'll say it like this. Do you think that AI music will fail in the test or it'll win? I think it'll win only because instrumental music and electronic music and things like that have been pretty popular on TikTok. So it's not like every single viral song on TikTok is a song with words and lyrics to it, you know what I'm saying? Sometimes it's just instrumental and things. So it kind of makes me think of when Spotify saw that whole in their system where people were like, what was it like sleep music and things like that? And they created AI to create those type of playlists and music to fill in that gap. I see TikTok doing the same thing. Hey, electronic music and this type of instrumental does go viral on the platform. Cool, we're gonna hire some AI creators to make that type of music. And then for the other genres where it is, people or lyric focus, we're just gonna look internally in the platform and look for who to turn up and be represented as that part of music. That's what I think is gonna happen because you're not gonna be able to completely remove major label music from the platform because fans aren't gonna let that happen.   So I was like, how do you navigate that? And that's why I wanna ask you like, how do I discover music as a fan, right? If I'm not gonna have an artist pushing this music on his page that then goes viral or somebody paying for it in Florence as a part of my artist's campaign for me to discover the music, how are they gonna get the AI music out to new people that even discover in the first place and compete? I mean, I think traditional stuff, they can get influencers to use it. They can still get influencers to do the influencer campaign. They can still do advertisement. I've seen TikTok leverage other social platforms for marketing their own brand. So I'm sure they would do it for the artist.  Like to make the argument a little spicy, even the AI is kind of high right now. I look at it like the only way that going to, from a general music artist perspective, the only way they could get around that narrative is to highlight artists that are indie within the platform, right? So, and like massive artists too, like which we know they exist. Like we've seen like the Nick Dees and you know what I'm saying, people like that who compete with major label artists, but all that main thing is TikTok, right? So like they're going to have to kind of step back and pay a lot more attention to that, which I know TikTok doesn't pay a lot of attention to because we've had instances where we've had clients go viral on the platform and they had no idea that it was happening. You know what I'm saying?  And then they'll move from there. So I think there's going to have to be a bit more of a developed like internal A and R team for TikTok or they build something in the algorithm. But I think for them to completely get out of this narrative and make people go like, hey, here's the reason we need you to be cool with us taking away your Drake and your Taylor Swift and your Beyonce sounds. And which I know TikTok could do this because Liam is narrative heavy is they could say, hey, because we want to continue growing the community of TikTok and giving shine to the TikTok stars. And we feel like that's more important. They play that narrative, it'll work. They don't lean to that narrative. I don't know if it'll work.  That was happening even before TikTok had licensed, right? I remember TikTok before that happened. It was all like generic music and like rip sounds floating on the platform. You just kind of had to like find one and favorite it and hope it lasted until you got to make your video. So it would just go back to that. But I think it'd be a cool peg in TikTok like overall narratives of trying to be creator friendly. And we're here to help the creator and take them to a new level. It would be an amazing narrative as a part of that. I think I can see how they might find it or find a way to make it easier for people to find the AI music within the platform experience too. As a part of your posting, find ways to push it on there. Yeah, cause they already got like the main sound tab where they have like the playlist and things.  You know what I'm saying? So they already kind of been like building towards that. So they have their playlisting editorial culture of their own. So I could see how they could work that in. Something I also think about though is the question, right? Did they need major label music to pop in the first place or not, right? And we know that major label music did have a part in the blow up of TikTok, but did it have to? Was it a primary driver? I'd argue no, because so much of it, label side has been, hey, here's these artists who are popping on TikTok, let's sign them, all right? So those are indie artists that are popping and creating culture. And then the labels are signing them. So it's not their music. And then we knew what we were saying early on is why we went so hard on TikTok in 2019. Cause they're like, man, we got maybe like one summer and the labels catch wind. The labels catching wind and coming hard. So that gave us maybe about six months, nine months max. So let's get it now. And it started to happen in 2020. Label started to kind of catch on, get in the bag and saturate the market. And you would start to see some of those bigger artists drop their stuff. And I remember one thing that you specifically said, and you were like, yeah, it's going to be a rap. It didn't fully work out in the perfect way, but it still marked that time step. You remember what you said it was going to take? Was it that, oh, what I said was going to take? So was that Lil Nas X that? No, no, no, no. You're like, all it's going to take is one Drake song. Oh, yeah. And then Jay did Tuesday's live. You're like, Jay's going to come with a song for TikTok.  Right, it was a sense. Yeah, I know. You know, that song was, you know, oh yeah. He did what he had to do. Yeah, he did what he was for, I guess, you know. But yeah, but that's a good point. And think about it like labels would kind of psych me because I do think the narrative of TikTok being the savior of the music industry did do a lot for TikTok because it made the artist community more interested in it, which then brought over like other creative communities. And then, you know, like music is an integral part of TikTok. Just major level music isn't necessarily an integral part of TikTok, you know what I'm saying? So it's like, they're probably looking at like, hey, like if we were to take you out of the equation, we will maybe our dissatisfaction rate goes up 30%. You know, maybe our quality of the after some people go down about like 10%. But eventually they'll get over it, you know what I'm saying?  And they'll just be so used to all, because not like it's, they're not like this and like, hey, we're going to push terrible music, right? Like you said, there's still lots of amazing acts who get their star on TikTok. And so that's why I was saying, I think the narrative is going to be like, hey, let's just double down on making these acts stars in whatever capacity we can control because this is a better narrative for us as a platform. This is a big middle finger to the industry. You know what I'm saying? That they don't want to work out a deal with us. We know at least in the US, our culture love middle fingers. Yeah, they love middle fingers. So we're a big company, right? Yeah, yeah. We love some middle fingers. So they can always put that narrative. Hey, we're doing it to give more shine and light on the India. That's what they're going to do, bro. That's a hundred or something like that. They did the same narrative when the Crater Fund came out, bro. Like we knew what it was about. Hey, you see a revenue source, but how they flip it? We want to make sure our creators have a legitimate way to monetize their audience that's fun and blah, blah, blah to the audience. It's like, bro, no you don't. You want 50% of this money you see sitting on the table by not offering them this thing, right? So I think that's what TikTok is going for story. Like, okay, we're probably not going to like super cap on these artists in the next year or two. You know, it's going to take time for us to even build that trust with this artist community and make us believe in, to believe in us over the major label system. And then three years from now, we are propped up in a position where we are seriously competing with labels at least with for the attention of rising superstar talent or possible superstar talent.  Like that's going to be crazy because that to me, I think TikTok is leading a really interesting fight against the labels that I always thought you two was going to lead. I always thought you two would be the one kind of doing this stuff. But I think they got too deep in bed with the labels. No legal code and console music.  Like I built up all this history and work with y'all these decades, right? So TikTok doesn't have any of that traditional connections and stigma, right? They just see pure competition, see pure dollars. And so they're leading a fight that I always thought you two would lead. That I think if they are successful in it, every platform is going to look at it that way.  Like how can we build some pipeline where we can be the main ones monetizing our top percentage of this type of creator instead of them just using us as a platform for the audience to then go give away IP to somebody else, you know what I'm saying? Like all of them, man. Like I said, I think TikTok and YouTube could get away with it the most. But I do think every, like Twitter's gonna start going, like, damn, how can we help? Like the Twitter monetization thing, right? Like how can we help these writers start monetizing their tweets? So I'm assuming the conversation's gonna go at some point. Like, okay, how can we all get a bigger percentage of this because you built your audience over here and we help you monetize them? But I'm like, no, I don't go to this, don't go to Amazon and sign a book publishing deal, right? Come to Twitter and like, maybe we sign a distribution deal for your ebook, right? So I think they're gonna open that door for other platforms or something like that. If they haven't already. And that is person what I'm interested to see what comes out of that. You know what I'm saying? Like I'm interested to see like, is the battle three to five years from now I'm gonna be major label versus indie artists or is it gonna be major label versus social media platforms? You know what I'm saying? And social media platforms that are now because they can all go open up a Tumacore account. They can all go open up a Dishoke account. They can all leverage their corporate way to get in bed with some of these music corporate people. You know what I'm saying? These social media platforms that might be moving like Brecca labels just in a more traditional sense is more favorable to the new artists that came up watching people like us and all these different creators talk about and this year we talk about and like they're just gonna win like a battle of attrition. You know what I'm saying? Like how can we wear people down over time to make them believe in our vision because we keep pushing this creative family narrative and y'all don't, you know what I'm saying? And like we know how much the artist community especially loves a good narrative about what company is for the people versus the company that's not for the people. You know what I'm saying? I see the vision for it, bro. And I think it's genius. It was like, personally. Look, because they use music and if they didn't need, if they kind of need major label music at the beginning, they don't need that a little bit now. I don't think. Yeah, 100%. Because culture is established. People are already used to going there for their music. People already have the habit of going on TikTok. There's tutorials. There's things beyond music itself. Kind of like with YouTube, right? Yeah. They're not just there for music, which is why they had more leverage with Spotify. TikTok is like, yeah, music is an arm of this leg. Or, you know what I mean? Yeah. Arm of this. But it's not the full body because we got so many other spaces and places to pull when we want people to come over just to consume content. So it's going to be really interesting to watch, but, you know, it's like, hey, we riding together. And then once we got to the location, it's like, man, I don't need you. I never needed you. That's what it feels like. The record labels are feeling. Yeah. And, you know, nobody's going to feel sorry for them because they're record labels and record labels already have a stigma. All right. There's already been a bad PR campaign for record labels for like 20 years now. We even watch old movies, right? Where the record labels is the bad guy.  My grumble with time. Yeah. You know, it's like a storied history.  Like that's that's the kind of mindset people have yet. Tiktok has a brand name that people respect and recognize these days. Instagram, people still respect and recognize. You, too, respect and recognize Facebook's struggling, you know, and everywhere, but there's many other social media apps that people respect and recognize and have a relationship they're building with on a daily basis before they even entered the music industry, where Atlanta records don't really mean nothing on these streets. Just the name of it. Because I say a lot of record labels and, you know, the your friend or cousin might be like, oh, OK, I think I might have heard of them before, but it doesn't mean anything to them. It's like telling your mom, I got a job at Amazon. They know what Amazon is. You know, I mean, that job might be working, making less money than you were at a different company.  He's doing it. Maybe Amazon. Yeah. Maybe Amazon. You know what I mean? So it's a that brand name, that value that these tech companies are building with the app specifically is something that I don't know how labels are going to be able to overcome. Until they I don't know, they figure out the model, man, because you can't just rely on the catalog, the old catalog forever. To continue to give that leverage. Most of this and their survival through this era has been the control of these older forms of music, because you still got to go through us if you want to get this. But hey, if everybody says, hey, we're going to take away access and then we're just going to keep pushing new music and then get everybody used to that. We're basically rewriting history or writing your old records out of history. Yeah. You know, so that's that's interesting to see. And I 100 percent am going to be very curious to like stay stay on top of this one, see how it goes. I'm going to hit up some of our Australian people. You know, see what's up over there, see what's up. See, see is it really going like it sounds from over here? Or is this just a little propaganda, you know, to get some clicks on the article? Because it's really it's believable, but it's also hard to imagine at the same time. I mean, they do it, bro. It's a it's a strong right hook, bro. Like it's a it's a it's a wild job to take, man. But as I said, it's to your point, it's like, if this was maybe two, three years ago, the labels had a point. But now it's like, like it's like, hey, bro, like we help you get those billboards. You know what I'm saying? Like you didn't you didn't really help us.  So even if you not what I think is going to happen is like Tiktok is going to start charging labels for promotion, like a typical marketing campaign. I'm saying like, hey, you didn't want to license this to us for whatever. So now you want us to feature this Taylor Swift song on the platform and X, Y, Z have the half a million dollars, a hundred K, right? Like now we just a marketing expense. The same way you would drop this PR expense if you wanted to get on complex or get on Billboard or whatever. And it's like, hey, now we're going to make money off of you. We was willing to break bread with you. If you was chill about it, but you didn't want to. And now we've got to violate you, perception wise and pocket wise. Crazy, bro. That's what I said.  It'd be funny if they go that far with it.  But they would essentially be treating them like any other corporation. All right. If you want us to market because, you know, Tiktok of course can be used individually with all the content creators who exists on the platform. But as you know, you know, they work directly with some of these major corporations like, you know, when we first started working with them as an agency, they had some pretty expensive. I didn't want to say pretty good.  They got some packages that they compete with those numbers. Y'all are here with radio and how expensive radio gets. Say some of those numbers, if not more. Craily, it's some numbers out there. You know, I mean, it's numbers out there, but we got we got NDAs and stuff. So you can't get all this specifics and slap it on the screen. So yeah, man, it's going to be interesting to watch. I hopefully y'all find this as interesting as we do. But but like, trust me, that impact on that and how the outcome of this is it can literally change the landscape by out of nowhere for indie artists. You know, always being affected by the top level of the industry, even if you aren't participating. Think about that. They will make TikTok the only platform with any art song competing with major artists that go out of the way. That's true. Yeah. Yeah. Possibly negatively impacted there. So this is yet another episode of No Labels necessary. Episode number 33. Make sure you share it with your folks, man. Don't keep this information to yourself. Don't keep this sauce to yourself. Go ahead and share the pie so we can continue to grow. I'm Brandon and Sean. I'm Corey and we out. Peace.


Well, on the heels of this 38-31 win for the Rams, the question is simple. After what we saw here tonight offensively by LA, an offense that's put together by Sean McVeigh and guided on the field by Jared Goff, I'll ask you, can anybody beat the Rams in 2018? Well, not if they continue to play like they did tonight, at least offensively, because I just don't think when you look around the league, who's going to be able to score the amount of points to keep pace with them. And I think the thing, though, that really is most frightening, because you're not going to expect the Rams to go out and go for 500 yards. And the big plays that we saw tonight, Wade Phillips is going to get this defense playing better. They've got two good players to not play better than what they showed here today. And so you combine the veteran players and then the veteran leadership of a guy like Wade Phillips, along with a Jared Goff and some of these younger players that are coming along. And that's hard to imagine that they're not the favorites as we move through this year.


This is the story of the birth certificate of a railroad. Not the story of the Santa Fe as we know it today, but simply the notation on the back of its birth certificate. Its infant smiles and tears, its struggle to survive. Now, in just a moment we'll tell you about it. But first, here's Gain Whitman. This year, winter sports have grown increasingly more popular. More popular too are all the new models of outdoor sportswear, which carry the tag that reads, Fabrics Treated with DuPont Zeeland. There's good reason for this wide use of Zeeland durable water repellent. Outdoor enthusiasts know that garments made of fabric treated with Zeeland give continuing satisfaction because they afford protection against snow and rain, even after many washings or cleaning. Zeeland, it's one of the DuPont company's better things for better living through chemistry. Music And now Ralph Bellamy as Cyrus Holiday and Louise All-Britain as Mary in the Prairie Burner on the DuPont's Cavalcade of America. It's the year 1866, just outside the frontier town in Kansas. The prairie, like a golden russet carpet, stretches unbroken on each side of the rough wagon trail. The only sound to disturb the peacefulness of the morning is the sound of a stagecoach traveling up from the south. Uh-oh, did I say peaceful? Say, that was a rifle shot. Yes, there's a band of cowboys stopping the coach. Get their hand away from your shooting arm, darling. We ain't aiming for trouble with you less than you asked for. What's the idea of stopping my coach? We got a little something to say to one of your passengers. You, Holiday? Yes, what concern have you with me, sir? Just this, Mr. Railroad Builder. We're warning you. Keep your blasted prairie burners away from our grazing lands, understand? No, I'm afraid I don't understand. You see, mister, we just don't favor railroads in these parts, right, boys? That's right. Oh, you don't, hey? No, and we don't favor railroad builders, neither. So we're giving you the way around. And you'd better pay up some money. Now, you listen to me, my friend. I'm leaving for the east.  Harris, Holiday, back home in the east, found that the problems of building a railroad were not confined solely to the west. In the year 1867, we find him seated at the dinner table, glowering down at the plate before him. Mary, his wife, gently suggest? Eat your bluefish, dear. Bluefish. Yes, that's what they all are. Bluefish. They have as much imagination, as much vision as this broiled bluefish. Why, who, Cyrus? Guilford, this crowd, that's who. I think a railroad from Topeka, Kansas to Santa Fe is impractical and they won't give me a sense worth of backing. Why is the very idea? Well, we'll use our own money. That's what we'll do. You know how much money it takes to build a railroad. No, no, but we have about $20,000 in the bank. Mary, it takes lots more than $20,000 to build a railroad, lots more, dear. It takes hundreds of thousands, maybe millions. Oh, my. Really, Cyrus? Sure, $20,000 will build no more than maybe 10 or 12 miles of rail, dear. Well, then it's built a 12-mile railroad. You had to be throwing money away. No, it wouldn't. Your charter with the government gives you deed to land on each side of the railroad, doesn't it? Yes, if I build a railroad, but... Well, then why not build 12 miles of road and sell the land and make some money and build 12 miles more and then take that money and don't... Whoa, whoa, there! I suppose you think that's ridiculous, too. Dear, I can't build a railroad with $20,000. Well, you can start one with that, can't you? It just won't work. I just don't see why not? Well, because... Well... Well? Because... What? Yes. Why not? Why Jupiter? Why not? That's what I asked you. My heavens, I'll do it. Do you hear, Mary? I'll do it. You mean we'll do it, don't you, dear? Because I'm going with you this time. What? You mean to Kansas? Uh-huh. To Kansas. Oh, no. Oh, no, my pet. Oh, yes. Oh, yes, my darling. Mary, I will not hear another word about it. Ah, yes, darling. And that's final. Yes, darling.  It's really quite good, dear. This is Topeka. Just one muddy street and two lines of quabbert houses. I shouldn't have allowed you to come. This is no place for... For a decent respectable woman. Yes, darling. You'd better inquire about Mayor Wyndham's whereabouts. Yes, I understand the building. New City Hall, since I was here last. But none of those buildings look like it. If you please, sir. Whoa! Can you direct us to the City Hall? Sir, that noble edifice across the road to the new City Hall. Oh, thanks above, that shack. Yes, sir. The railroad man, Wendy, has been expecting it, you know? He's under the Mayor. We call him Wendy, and the county's got heaps of talking talent. I see. Yes, I'm the railroad man. The Mayor has been expecting. Thank you kindly, sir, for your assistance. Careful of the mud, ma'am, when you cross the road, six inches before you hit bottom, Maracan. Thank you. Yes, I'd better carry her across to the board, Mary. Oh, how nice, dear. Up you go. Oh, careful, dear, don't flinch. Do you think for a moment that I'd let such a precious burden fall on the Kansas mud? Mr. Railroad Man. Yes, my friend. Here it comes. That's right, sir, right across the desert to Santa Fe. What's so funny about that, my good man? Now, now, Cyrus, don't get into a fuss wedding. At least carry me out of this mud first. Let him laugh, the confounded. Mr. Yes? Cyrus, please. No, please. I fear you've met with a mishap. Just a little fall in the mud. Oh, may I present my wife, Mayor, Mrs. Holliday? How do you do, sir? May I help you up, Madam? Thank you. Upon my word indeed, a double delight awaits the proud citizens of Topeka, for grace and prosperity, beauty and grace. Indeed, my dear Madam, indeed. Oh, thank you, sir. This way to the city hall, folks. Yes, sir, you may count me as your most willing servant. Indeed, sir, your most willing servant. Here you are. And her, please. Sit down, folks, do so now. Thank you, Mayor. Now, Mr. Holliday, sir, if I can be of any assistance in my official capacity as Mayor of Topeka, you have but to speak, sir. Thank you. However, in truth, sir, I think it best to warn you, there may be a bit of trouble. Trouble?  Sam Coulter, do you know him, sir? Yes, I met the gentleman on my last trip here. Sam Coulter, sir, can't abide the sight, smell, sound or thought of a railroad. In fact, sir, a railroad man to Sam is lower than, excuse me, ma'am, a sheepherder. Huh? Oh, goodness me. Yes, sir, seems Sam had a ranch up north of here. A railroad come along bringing settlers and had big pardon, ma'am, sheepherders. And drove his herd off in the free grass. Sam, he fought like all good out, but didn't do him a mighty good. Said he'd rather sell out than have any truck with a railroad than buy George he did. Yes, sir, as he hates railroad worse than he does a horse. Coulter and all the cattlemen in Kansas aren't going to stop me from running a line to employ you. Oh, here's a man of spirit, madam. Indeed, a man of spirit. It might I inquire, sir, I see you don't carry any firearms. Firearms? Well, I'm sure I have a few spare ones, ma'am. Yes, here are the good ones. Oh, my, what a pretty pearl handle. They are just... Sorry for the love of heaven to put that thing down. Thank you kindly, ma'am, but I don't think I'll need a gun. Yes, you will. Perhaps not. Perhaps not. Oh, Cyrus, do take the gun. It has such a pretty pearl handle. Mary, please. Ah, yes, darling. No, I don't think we'll need guns to build the Santa Fe. At least, I hope not. Yes, Mary.  I might have been a coach road builder and made roads like this. Like a pistol shot. Oh, my, whoa! Whoa, the coach has shot. What is it? Hold up.  We're no higher to get your bristles up. Coach, sir, Cyrus, isn't that the end of it? Yes, sir. Now, don't worry, dear. What do you want, Cody? One of your passengers. Come out of that coach, Holiday. If you have anything to say to me, Coach, say it and let us go on our way. Step down, Holiday. Why? This ain't no concern of yours.  All right. I'll come out. Oh, no, Cyrus, they might just... Stay in the coach, dear. Don't worry. All right, boys. Let's take them and get a go.  The lady's packing a shooting iron collar. He'll... Harry, put that gun down, and please let me handle this alone. Ma'am, it won't please me not to make smoke with a woman, so I'm asking you politely. I dropped that gun. I won't drop any darts with ma'am. Ma'am, if you wasn't a lady... If I wish I weren't a lady, then I'd really tell you what I think of you, Harry. Ma'am, we don't need none of you slick tongue easterers to tell us how to run our fairs. These are free-open ranges, and we aim to keep them that way. Have you say, my friend, I'm listening. Come on, boss. Enough of this chin music. Let's go. Now, wait a minute, Pete. All the day I warned you once. Now, this is the last time. You keep your blasted prairie burners away from our grazing land, or the only way you will ride will be when you set a straddle. Come on, boys. I guess they won't dare bother us again. Not while I've got my pretty pearl handle shooting iron. Now, dear, give me that gun. Oh, all right, dear. Where in heaven's name did you... Oh, I see. Where are Windham? Yes, darling. I just couldn't resist it. It has such a pretty pearl handle. Well, I'll keep it myself. If I know Kohler, I'm afraid I'm going to need it. I'm listening to Ralph Bellamy and Louise All-Britain in the Prairie Burner on the Cavalcade of America, sponsored by the DuPont Company, maker of better things for better living through chemistry. The second part of our story opens a month later. Cyrus Holiday is building a railroad from Topeka to Santa Fe. The rails are being laid in record time. Everything is going well. And... Just before sundown one day, the public trouble starts.  Oh, sure, Mr. Holiday, those cowboys hate the shots they're made out to be. The way they're shooting... They're aiming high, Mike, on purpose, trying to scare your men of the quitting. Quitting? Well, quit. We've raised the last fight down in Santa Fe. And then a mysterious fire broke out one night in the supplier. Stop the men, Mike. No use waiting until they're finally under. The Sheds of Bonner. But the railroad ties, Mr. Holiday. I'm afraid there's nothing we can do about them now. Oh, black cross on them. This is going to set us back for a month or more. Yes. And we meet each month with the government deadline coming closer every week. And then the rails were torn up almost as fast as they were laid. Mike, tell the operator to get on the keys and raise Kansas City. We'll need a new batch of rails to repair the section they tore up last night. But Mr. Holiday, sir, are you sure that we have the money to cover? I don't know, Mike. But one thing I do know, one more setback and we're through. Mr. Holiday, sir. I know, Mike. I know what you came to tell me. The men are all quitting. Well, no, not exactly, sir. Well, I can't say I can blame them. Can't expect them to work without the certainty of being paid. Well, no, sir. Tent as bad as our lads only about half the hands have quit. You might as well tell them all to put down their tools, Mike. Good morning. It looks like Sam called her wins. Good morning, darling. Morning, dear. Well, what's everyone looking so darn them off about? Oh, sure, no, ma'am. There's only the set of my face. Uh, I guess I'd better get back to the men and tell them Mr. Holiday. Oh, I know. No, now I know money. Heavens as if that was something to worry about. Look what I've got. What? Three thousand in cartwheels and gold. Mary, where did that money come from? From the men, sir. Good. I'm going to be pulling out on the new Santa Fe tracks two weeks from today on my name is Michael O'Day. I'm baking Mrs. Holiday, ma'am. Oh, I'm glad to. Never thought Jake Carter would be driving the first iron kiosk on your railroad, Mr. Holiday. Never thought anyone would, by the way, it looked for a good while. When do we let it book, Mr. Holiday? You know as well as I do that nothing gets started around here without a speech from Mayor Wyndham. Ah, time nation. How do you like your new saddle, Jake? Driving an iron horse is a little more complicated than a stagecoach, huh? Ma'am, I feel as good as a coast harbour's horse in fly time. Ah, no worry, Jake. Mary and I will be riding in the engine with you on this run. Ah, Mr. Holiday, sir. Oh, and more. A most memorable occasion, ma'am. Ready, sir, for your speech? Sir, I've been ready for weeks and this day is memorable for most resort record in the great, unwritten future of that strategy. For reaching on and on and on to Galveston, to San Francisco. I even back east to Chicago. I can see the coming tide of the Great Ones flowing along these lines like an ocean wave and fans of the tide. Mr. Hargane, ever thought we'd pull out into a picnic? Yeah, it wasn't very nice, it was, Jake. He was trained for no wind and had a chance to finish his speech. No, he wouldn't want the first trainer even late, would he? Like he never even missed us. Wouldn't surprise me in the least if he was still there in his run. Uh-oh. Look at there, Mr. Hargane. What's wrong?  A herd of cattle. A herd? I didn't know there were so many cows in the whole world. Here's to me, Mr. Hargane. They've been herded and bedded down for the purpose for life. What do you mean? They're just chung out? Yep. Bar, tea brand. Coders marking all right. Here they come, riding up to us. Well, there's going to be gunplay or I reckon it's might easier shooting from the cab over locomotive than this from the seat of a stagecoach. What do you think that up to, Jake? I can't say, Mr. Hargane, but I know Sam Coders can't be up to no good. Anyway, we'll find out soon. Now, here he comes. You sure look mounted for the inside of that tea cattle, Jake. Get your heart off in them tracks, Coders. I reckon I just can't, Jake. Why not, Coders? What do you see, Mr. Railroad Man? My cows are sort of peculiar. They don't understand a mighty English. Ah, Jake, keep away from your gun or you'll have a mighty short career nursing that prairie burner. Mr. Coders, I hope you're not going to keep that herd on the tracks until they learn the rudiments of England. Don't fandy words with him, Manny. Jake, stop the locomotive. I'm warning you, Jake. You hit one of them cows. What are you expecting to do, Coders? Wait here until they make up their minds to move. I reckon if you don't fancy waiting, Mr. Railroad Man, you can back this rattle to Topeka. But I ain't moving that there or hers. Stop the engine, Jake. I reckon that won't be necessary, Mr. Harday. No, sir. What are you going to do, Jake? I'm going to practice on my little tutor and if I know cows, they'll run and keep running until kingdom comes. It looks like the cattlemen are beginning to change their ideas about railroads. After six months of running our little lion, they're getting wise and beginning to ship their cattle by rail. Yes, I know. Isn't it wonderful? But according to Jake, there's a reason for their change of mind. What reason? It's been this drought, the grass and the range has burned to a crisp. The streams are all dried up on the cattle trail to Abilene. I see. So they were forced to ship them by rail. What about our friend Sam Coders? Coders?  Shall some up, cut plug? Coders, what's the use of driving the poor critters any further? They ain't had a lick of water for two days. Look at them. They make the marketer today, but... Some up, sir. Look here, boss. What need to do like I say? If you don't... No, blast. You cut plug, I'd sooner see them cows dry up and bust them on them on the railroad.  You'll have to hog time me first. I'd make 722. That'll all cut plug. I reckon that's tally, Mr. Holiday. 722 head. Mm-hmm. Sure glad to see him bedded down in them cattle creek. Mm-hmm. And I'm glad the cover outfit finally came around, but where's Sam? I don't see him about. Sam? Well, skin me for a mule I've forgotten. We got him hog tied in a chuck wagon. Well, Matt, after six months of running our little railroad, we're beginning to show a profit. Yes, my dear, to peek us in for a boom at the cow business. And are you listening, my dear? Sorry, is that that man? What man? Digging at that desk door and tell me, Mary, will you stop playing with that gun for the last time? You don't need that gun, ma'am. Coulter. Yeah, Coulter.  I want to have a talk with you. Mary. Yes, dear. I'm putting it down. Well, Coulter, what can I do for you? I want to know what I'm owing you, Holiday, for shipping my cattle abalone. I won't be beholden to no railroad, ma'am. Well, I got your bill here, but I'd much rather you'd pay me off in good will. No, you won't have no more trouble for me, Holiday. I had to be hog-tired first, but I reckon I know when I'm licked and come the next cattle run, I'll sign that contract right regularly. Can we shake on that, Coulter? Well, never shook hands with one of four, but you know, Holiday, for a railroad, man, you ain't such a bad umbra after all. Shake, partner? Shake. Partner? And now, Mary, I think you can give Wendy back his gun. Oh, must I do? Mary? Oh, yes, darling. But it's such a pretty pearl-handled revolver. Holiday lived to see his road go over the desert to Santa Fe. Up over the mountain passes to Denver, down to the gulf, east to Chicago, and west to the Pacific. He lived to see his twelve miles of road go to twelve thousand. His plans were opposed by some who, like Sam Coulter, thought his own interests were threatened. Yet his faith in his enterprise, the kind of faith that built America, not only carried the road through to its destination, but converted those opponents into supporters. So it has been many times in America, and so it will be many times again, as it must, in a land that is dynamic and still growing. Gain Whitman speaking for a depart. The other day, I had some oil put in my car. While the man at the service station was pouring in the oil, I happened to pick up the can and read the label. Gee, I said to myself, this oil manufacturer claims a lot for his product, but then I realized, say, these aren't just claims, these are facts, or the oil companies wouldn't print them on the label along with their brands. Listen to some of the things a modern motor oil does. It has a detergent in it, what you and I might call a cleaner that prevents carbon and sludge from dirtying up your engine. The oil you buy today tries to help keep your engine clean. Today's oil must operate under much higher temperatures and pressures than motor oil used to. But today it doesn't break down so quickly because it has been made more stable, stands more heat, and it runs more freely, even when the thermometer gets well down below zero. But perhaps the most striking improvement of all is that chemistry has developed compounds called lubricant assistance. When these are added to oil, this is the thing that seems unusual to me, they actually make it oilier. So I asked myself, there at the gas station as I looked at the label, how did all this happen? How did this lubricating oil we buy nowadays get to be so much better than the oil my dad used to buy for his car in, say, 1920? There are two answers, and they both begin with a letter C, chemistry and competition. Years of scientific research in the laboratories of the oil companies and the laboratories of industrial chemical companies like DuPont have made oil better. Why have scientists done all this just to give you better oil for your car? I suppose partly because human beings are that way, always trying to develop and improve things. But mainly because that other C, competition leads business men to give you the best oil you can buy so that you will continue to be satisfied customers and keep buying their products, the best oil or the best baking powder, the best refrigerator. That's the burr under the blanket of our American business system. Competition, petroleum additives helping to make modern lubricating oils as good as they are, deserve their place on the roster of the DuPont companies for better things for better living through chemistry. Next week the DuPont Cavalcade brings you William Holden and Marcia Hunt in Builder of the Sioux. It's the true story of a man who had a wonderful dream and of the woman who stood by him until that dream came true. Charles Harley believed the canal could be built across the Great Lakes. So did Katie Bingham. They fought ignorance, bad weather, sickness and financial problems. But they won out and Harvey built the Sioux canal in two years instead of the ten that Congress set aside for this project. Be sure and listen next Monday at the same time to Builder of the Sioux starring William Holden and lovely Marcia Hunt on the Cavalcade of America. The music for tonight's DuPont Cavalcade was composed by Arden Cornwell and conducted by Donald Borey. Our Cavalcade play was written by Henry Walsh. In the cast with Ralph Bellamy and Louise All-Britain tonight with Ted DeCorsi as Coulter, John Griggs as Wendy, Joseph Boland as Peake, Cameron and Andrews as Jake, Walter Kinsella as Mike and Ted Osborne as Cup Club. This is Ted Pearson inviting you to listen next week to William Holden and Marcia Hunt in the Builder of the Sioux on the Cavalcade of America brought to you by the company of Wilmington Dalloway. This has been being a national broadcasting public.


We go. Is that OK? OK, so let's go. Starting now. So hello, everybody. Thank you very much for the invitation. So I'm a student at EcoNormal Superior in Paris. I'm working with Florence Akela. And the title of my talk is Exact Asymptotics with Realistic Data. So the question of generalization in machine learning algorithms can be tackled with several different frameworks. And the framework that I will be interested in here is the framework of high dimensional statistics, which is also very heavily linked to a statistical physics of learning, which is one of the topics of this conference. And so what is typically encountered is more of a typical average case analysis as opposed to the worst case analysis found in statistical learning theory. The focus is on a benchmark, random design problems, obtaining exact solutions as opposed to upper bounds, again, which are traditionally encountered in statistical learning theory. But there is a catch to these exact solutions, which are assumptions that are quite strong, so namely high dimensional problems. And then the dimensions of the problems go to infinity and random design assumptions. So a question that naturally arises from this is how realistic are the statistical physics benchmarks? And perhaps what can we do to try to make them more realistic? So let me introduce the typical setup that I will use during this talk, is the teacher-student generalized in our model. So the name teacher-student comes from the statistical physics of learning community. However, in machine learning, you could call this a generative model. Learning a generative model is the same thing. So we observe a generative model parameterized by function f0, a ground truth vector w0, and the data matrix x, which is typically taken iid Gaussian. And then what we try to do is reconstruct this model using a student. So here, I will take a very simple model, which is a convex generalized in our model, which is parameterized by a loss function l, a convex one, and a regularity, a penalty, r of w. And as I mentioned before, the dimensions will be going to infinity. And the typical goal in this type of problem is to try to understand the statistical properties of w star. So for example, can I calculate the mean square error between w star and w0, an overlap, and so on and so forth? And there is a very rich literature of results here on this type of problem. And the question that I want to ask is, is it possible to go beyond this idea assumption and introduce some correlation to reflect as much as possible a realistic scenario? So the first thing that I would like to present is a joint work with Bruno Loureiro, Hugo Cui, Sebastian Goldt, Marc Mésard, Florence Zacala, and Lenka Zdeborova, where we propose a block-covariate model to try to create a scenario where the teacher and the student can act on two different feature spaces. And so if you consider samples of the form here, u and v in a vector of size r to the power p plus d, u is described by a covariance matrix. So modeling a feature space psi, v by a covariance matrix omega, and the interaction between the two, a covariance matrix phi. So now the generative model generates labels using the samples u, and so the feature map psi, and the student tries to learn this using the samples v, using the covariance matrix omega. And so there are many works that have been proposed trying to deal with correlated scenarios, and perhaps the closest to this is this Masti-Montanari-Rosset-Antipchirani, where they had at a certain point a similar block-covariant structure for the specific case of ridge regression. And so here where the idea was to do this for a generalized linear model. So let's jump directly to the solution. So it's not very nice, but I want to show what it looks like. And so the theorem that we have is if you consider the unique fixed point to this set of self-consistent equations, you can exactly characterize the training and generalization error, as the dimensions of the problem go to infinity. So there are close form formulas for these quantities. And so the proof uses convex Gaussian comparison in equality. So these inequalities are a family of proofs which are quite popular at the moment for this type of problem, and that worked very well for this type of problem. They were introduced by Mihail Oztognik in 2013 and popularized in other works later on. So how well did this work? So again, we were trying to reproduce realistic scenarios. So for ridge regression, as was observed in earlier works, a lot of realistic scenarios can be reproduced. Feature maps can be included directly in the problem and the random design problem is quite accurate and it works very well. However, it was also interesting to look at when the model breaks down, which is what you see on the right-hand side of the plots. So this is just a logistic regression. So binary classification task on a synthetic data problem. So the red curves, which are generated with a type of gun. So here the fit is quite good. And in blue is taken directly on the real data. And on the real data, so this random design block covariance model doesn't work so well. So we see that classification is more problematic. However, I mean, the Gaussian model is quite interesting. We see that it captures some features that are interesting. So it would be nice to have another realistic benchmark problem, which includes correlated Gaussians and goes beyond the binary classification case. And this motivates us to study a classification of K Gaussian mixtures with a convex GLM. And so further motivation for this problem is several scenarios that have been observed in machine learning recently, where Gaussian mixtures are accurate to describe a certain realistic scenario. So for example, the team of Romain Couillet has shown using random matrix theory that some data generated by guns can be accurately described by Gaussian mixtures. And other works are related to deep learning. And also classifying a Gaussian mixture with K clusters, this is a benchmark problem in machine learning is quite clear. And on another note, Gaussian mixtures are universal approximators provided you have enough Gaussians, of course. So let's go. So the data distribution that we chose, so the generative model, which implicitly defines the teacher in this teacher student framework. So it's a Gaussian mixture model. So I have data points X in R to the power D, one hot encoded labels Y in R to the power K and a joint distribution with row K, so the probability for the clusters and the Gaussian densities parameterized by a generic means mu K and covariances sigma K. So here is a familiar picture for three clusters in dimension two. And the goal is to try to learn this Gaussian mixture. So learn separators using again, a convex generalized linear model. And so this time, instead of learning just a vector, so we are learning K separating hyperplanes. So we are learning a matrix W in R D times K. And so examples includes, for example, a rich regression, softmax with a cross entropy. So any loss and regularizer as long as it is convex, otherwise we don't have the solution. And so again, I'm showing you the result. So in this, again, with Bruno-Lauré-Rogue, Gabrielle Sikourot, Alexandre Paco, Florence-Zacallan-Lengas-Devorova in the recent preprint. It has the same flavor as the previous one, so it's a bit heavy. Consider a fixed point of a self-consistent set of equations. And again, as the dimensions go to infinity, we can compute exactly the training and generalization error. So here are the misclassification rates. So this formula is not very nice. It's a bit heavy. I mean, I'm happy to give more intuition because all these results actually have the same core intuition. So if someone is interested later on, I'm happy to discuss more of this type of formula. But what's interesting to note is that, so this is a very generic statement. There are very few assumptions that are made. However, it greatly simplifies if you make assumptions on the covariances. For example, if they are diagonalizable in the same spaces, if you make assumptions on the separability of functions, you can get statements that are a lot clearer with a lot less parameter. And in most relevant cases, it reduces a lot to a low-dimensional statement, which allows for maybe a more intuitive analysis of what is happening. So now let's look directly at some examples. So examples for synthetic data on random design problems. So here on the left-hand side, we plotted rich penalized logistic regression on K-Gausson clusters with identity covariances. And we plot the generalization error as a function of the sample complexity. And for two, three, four, and five clusters. And what we recover is a type of curve that had been already observed for two clusters. So for binary classification, where a separability phase transition occurs and there is a kink in the generalization curve, which otherwise, I mean, remains monotonic. And so this type of result, observing separability phase transition. So then we observe them at different places for a higher number of clusters. There is a rich literature of this going back to Covarrin 69. And so here on the right-hand side is a plot of the generalization error, again as a function of the sample complexity, but this time for different regularization parameters. And so we see that regularization consoles this kink in the generalization curve. So there is also a comparison to the base optimal scenario. Again, the fact that regularization removes this kink had already been observed in other models. So I talked about real data. So let's look at an example on real data. And so this is a binary classification task on MNIST. And on the left-hand side, what we did is take MNIST, consider the classification task of odds versus even numbers. We took the empirical covariances of the two clusters and we designed our generative model, the random design model with this. And we try to compare how does the random design model compare to the actual regression using a standard machine learning solver. And we see that actually the logistic regression cannot make the difference. So the prediction is exactly the same between the real data and the Gaussian approximation. So on the right-hand side is fashion MNIST. So I guess data set, which is a bit more structured. And so there is a discrepancy between the theoretical prediction in blue with the Gaussian approximation, which is represented by the green stars, and the orange prediction, the orange dots for the real prediction. And so maybe a brute force way to try to solve this. So this is another binary classification task on MNIST. But this time, classifying 0, 1, 2, 3, 4 versus 5, 2, 9. And here again, you can do a Gaussian approximation. So this is the P2 with the blue stars. Or you can do 10 clusters. And so I give an idealized view of this on the right-hand side. I just have a data set. I can either approximate it with two Gaussians or four Gaussians. And adding more Gaussians is a brute force way to get closer to the real thing. And this is a bit what we observe on these curves. So now I will come back a bit to this in the discussion at the end of the talk. And for the remaining time, I would like to talk a bit about the sketch of proof and why this was a challenging proof. So what are the difficulties here? So we are learning a matrix. And so implicitly, we need to understand how the different hyperplanes are correlated by the learning process. And this is something that's non-frivial. And the second thing is each cluster is different. We want to allow different covariance matrices. And so intuitively, we cannot use the same quantities to characterize the effect of each cluster. And actually, this was observed in a recent paper by the group of Christos Trampolidis, where they showed that the convex Gaussian comparison inequality, so this nice family of proof that I've talked to you about earlier in this talk, they actually break down beyond the least square case for a multiclassification problem. So just a quick disclaimer, perhaps there is a solution using this method. It's just that now the way they are formulated, they could not find it. And so we did not use this method to solve this problem. So how did we solve this problem? So from the statistical physics side, the replica computation works. But how do we solve this rigorously? And so we used approximate message passing algorithms. So what's an approximate message passing algorithm? Well, it's a family of iterations, which has a very nice property. It's inspired by statistical physics. It has a nice property of having exact closed form asymptotics called state evolution equations. What do I mean by that? So I mean that at each time step of this iteration, you can exactly characterize the statistical properties of the iterates using a low dimensional equation, low dimensional iteration. And one of the nice things is that AMP, you can treat matrix value variables as a whole. This is no problem. You can handle block correlation structures. This is called spatial coupling in the AMP parlance. And so here intuitively, we have different clusters, which behave differently. So spatial coupling will be useful in the formulation of the problem. And AMP methods are very adaptable. So just a quick bit of history. Initially, as I said, these SE state evolution equations were derived in statistical physics using heuristic methods. And the first proof was due to a great mathematician, Erwin Bolthausen. And the proof method that he used was popularized later on by Etienne Montanari, notably in 2011. So what does an AMP look like? So there are many different form of AMP's. But the one I'm interested in is the following, which is a sequence of matrices, u and v, defined by a Gaussian matrix z, which can be a block Gaussian matrix, and two sets of nonlinearities, h and e, which here are matrix value functions. So there is a z transpose h, ze. So this kind of look like a first order method or classical descent method. And in addition, you have these two correction terms, momentum terms. And these brackets, they are Jacobian like terms. And they are inherent to AMP. So you cannot discard them. And they are really crucial to get these nice properties of state evolution equations. So now, how do we use this to solve the problem? So I have a target. So the target is the W star defined by the convex GLM on the Gaussian mixture. I have this tool, which is an iteration that has this nice state evolution property. Now, how do I solve this? I need to design the nonlinearities h and e, such that the fixed point of the iteration too much is the optimality condition of problem one, which is convex. Then one needs to find a converging trajectory. So in this case, convexity is very helpful. And once you have done these two first steps, well, what have you shown? We have shown that the estimator W star can be found as the fixed point of an AMP trajectory. So this means that the state evolution equations characterize this fixed point. So this estimator, and then all you need to do is use the fixed point of the state evolution equations. And this is what we did. So now just a quick look at the design of the AMP. So the AMP is very often designed from a factor graph representation of the problem. In this case, the factor graph representation is really not obvious. So what we did is reformulate a bit the optimality condition of the problem, and then match it with the fixed point of the AMP iteration. And this actually can give you the form that you need for the functions h and e. And so just a quick technical point of the validity of the state evolution equations. So here, actually, when you reformulate the gradient, the fixed point, sorry, the optimality condition of the problem, you get this block structure with non-separable functions. So here, L tilde and R tilde are reformulations of the problem, which include the covariance matrices. So there is no trivial mixing. And the different technical tools have been developed in this Javambar and Montanarin in 2012, and for non-separable functions in the Berthier-Montanarin-Guillain in 2018. But the combination of both, so formally, this is really a formal point, but it was not included. So this is included as a side result in a country, in a recent work with Raphael Berthier, where we proved state evolution equations for a larger class of approximate message passing algorithms. So, and yeah, this basically concludes the proof. And what are the future directions that are interesting to look at with respect to this work? Well, the relevance to realistic scenarios, well, I guess it was quite clear from the plots. Okay, Gaussian models are relevant to a certain degree. And then the brute force way to try to make Gaussian models more realistic is just to add more clusters. But then if I keep adding more clusters, in the end, as you saw, the formula is already quite heavy, I would just have a problem that is more complicated than the original problem. So this will not be useful. So is there a middle ground, a clever parameterization that allows to describe machine learning problems in an exact or close to exact way? So in the statistical physics way. And at the same time, remains sufficiently intuitive to be useful. And on the technical side, so there are a lot of technical improvements that can be made related to AMP methods. So there are really a bunch of possibilities offered by approximate message passing methods that can be composed to almost an arbitrary degree of complexity, and they are very interesting objects. So here we are working with the dimensions that go to infinity, but actually AMP methods, they are amenable to finite size analysis. So how fast do we need the dimensions to go to infinity? And so it's possible to characterize this. And a lot of work has been done in this direction by Russian Venkatraman in 2018. And finally, universality properties. So the randomness of the IID Gaussian core can be replaced by a universal IID matrix. And so one of the core work on this was done by Bayati LeLarge and Montanari in 2015. And with this last slide, I would like to conclude. Thank you all very much for your attention. And I would like to thank the wonderful collaborators that have worked with me on this project. So Bruno Lourero, Gabrielle Sikourot, Raphael Berthier, Lenkas DeBorova and Florian Zakala. And thank you again. Thank you, Cedric, for this very clear talk. It was very useful and pedagogic. Thank you very much. Thanks a lot. So Cynthia Vosch is the next speaker from Columbia University. Whenever you, one second, sorry, I have to stop the recording.


Morning Traders, Patrick Munley here with another Tick Me All Chart it. I want to draw your attention today to a developing opportunity in the Euro Kiwi and the daytime frame. We've had several tests of this 17450 level and we found buyers certainly on Friday when we dipped below and then saw a reversal into the close. What I'm looking for now today is a move through Thursday's high and we should see then a range expansion. Certainly we can look to test 17715 and then up to range resistance at 179 using protective stop just below the turn of the daily view out there at 7419. Important thing though is that we take out Thursday's high. As always Traders, plan the trade, try the plan and most importantly manage your risk. Until next time, thanks very much.