This Week in Startups - Udio AI’s Music Magic, Aqua’s Unique Dictation, Copyright Laws & the 1000x Potential of AI  | E1931

Episode Date: April 14, 2024

This Week in Startups is brought to you by…Gusto is easy online payroll, benefits, and HR built for modern small businesses.Get three months free when you run your first payroll at http://www.Gusto....com/twist*Gusto pricing shown in ad is based on pricing prior to March 2025Mantle. The AI-powered equity management platform designed for modern founders and operators.Get your first 12 months free at https://www.withmantle.com/TWISTHubspot. Join thousands of companies that are growing better with HubSpot for Startups.Learn more and get extra benefits for being a TWiST listener now at http://www.hubspot.com/startups/twist*Todays show:Sunny joins Jason to dive into AI news and demos including, Adam Schiff and the new bill to force AI companies to reveal use of copyrighted art (9:03), Udio the recent AI music creator catching a lot of hype (17:48), the AI dictation power of Aqua (39:10), and more!*Timestamps:(0:00) Sunny joins Jason to dive into this weeks AI news and demos.(4:02) AI News: Meta, Google and Intel all launched chips this week.(9:03) Adam Schiff and the new bill to force AI companies to reveal use of copyrighted art(9:51) Gusto - Get three months free when you run your first payroll at http://www.gusto.com/twist(17:48) Sunny demos Udio - the recent AI music creator catching a lot of hype.(19:36) Mantle - Get your first 12 months free at https://www.withmantle.com/TWIST(20:56) Sunny and Jason further explore Udio and discuss the copyright issues around AI models.(31:45) Hubspot for Startups - Learn more and get extra benefits for being a TWiST listener now at  https://www.hubspot.com/startups. Check out their report “How AI is Redefining Startup GTM Strategy” here: https://bit.ly/hubspot-ai-report(36:31) Sunny creates a song with Udio about Jason’s passion for copyright laws.(39:10) Sunny demos Aqua.(45:36) Sunny demos SWE-Agent*Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*LINKS:Check out Udio: https://www.udio.com/Rolling Stone article on Udio: https://www.rollingstone.com/music/music-features/udio-ai-music-chatgpt-suno-1235001675/Check out Aqua: https://withaqua.com/Check out SWE-Agent: https://swe-agent.com/demoMeta’s new chip news: https://twitter.com/Techmeme/status/1778078194345955765Google’s new chip news: https://twitter.com/WSJ/status/1777654095601348775Intel’s new chip news: https://twitter.com/Techmeme/status/1777725152102699026Article on Adam Schiff introducing new bill: https://www.theguardian.com/technology/2024/apr/09/artificial-intelligence-bill-copyright-artCheck out statmuse: https://www.statmuse.com/*Follow Sunny:X: https://twitter.com/sundeepLinkedIn: https://www.linkedin.com/in/sundeepm*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis*Thank you to our partners:(9:51) Gusto - Get three months free when you run your first payroll at http://www.gusto.com/twist*Gusto pricing shown in ad is based on pricing prior to March 2025(19:36) Mantle - Get your first 12 months free at https://www.withmantle.com/TWIST(31:45) Hubspot for Startups - Learn more and get extra benefits for being a TWiST listener now at  https://www.hubspot.com/startups. Check out their report “How AI is Redefining Startup GTM Strategy” here: https://bit.ly/hubspot-ai-report*Great 2023 interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland*Check out Jason’s suite of newsletters: https://substack.com/@calacanis*Follow TWiST:Substack: https://twistartups.substack.comTwitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartups*Subscribe to the Founder University Podcast: https://www.founder.university/podcast

Transcript
Discussion (0)
Starting point is 00:00:00 But this Gen AI movement is the actual industrialization movement of making more images, making more software, making more mockups, making it easier for us to access data quickly. And so I think with that, when you apply that back to software engineer agent, we can now, the same way, we went for making one card A to 10, we can 100x ourselves. And so me as a software engineer, I can work on 10 different problems at the same time or 30 different problems with the help of these agents. I think we're about to have the thousand X jump in software development. This week in startups is brought to you by Gusto is easy online payroll, benefits, and HR built for modern small businesses. Get three months free when you run your first payroll at gusto.com slash twist. Mantle. The AI-powered equity management platform designed for modern founders and operators.
Starting point is 00:00:57 Get your first 12 months free at withmantle.com slash twist and HubSpot. Join thousands of companies that are growing better with HubSpot for startups. Learn more and get extra benefits for being a Twist listener now at HubSpot.com slash startups. All right, everybody, welcome back to this week in startups. It's your boy, J-Cal here with my guys, Stephanie Madra G.M of Brock Cloud. Go to console.g.org.com. and you could start playing with the fastest and cheapest inference in the world. Welcome back.
Starting point is 00:01:33 Sunny. Good to be back, Chekow. Yeah. We missed you on the All-InPod. What happened? Well, yeah.
Starting point is 00:01:41 I mean, a lot of people are asking me because I never miss, right? You never miss an episode. Yeah. So. You had the Iron Man going. I think you had the Iron Man going.
Starting point is 00:01:49 I mean, I'm pretty good, generally speaking. What happened was I was, I was here in Austin and I went to the Salt Lake and they have this great bison race. and I'm chewing on it. I mean,
Starting point is 00:01:58 I wasn't chewing on the bone itself, but it's a chewy rib. And I heard like a crack. And I thought, maybe I just, you know, when your two teeth, you know,
Starting point is 00:02:05 cracked together or something, I didn't think much of it. Yeah. It wasn't hurting. And then two days later, I'm flossing and do, like, the tooth kind of hangs halfway out.
Starting point is 00:02:14 I'm like, holy cow. And so, you know, then a couple of days later, I get, find an emergency dentist as I get there. They're like,
Starting point is 00:02:20 oh, you know, that root canal I had 20 years ago. You know, those kind of deteriorate over a couple of decades. And, you know, it's basically it's cracked. And so that I was able to get emergency surgery. They extracted the root of the root canal and then put in, I guess, what they call an implant or something.
Starting point is 00:02:38 And then I guess I got to wait three months. It heals. And then they put another crown on it or something. But, you know, for three days, I don't like taking pain meds. And they gave me some pain meds. And that screws up my sleep. And then the pain was screwing up my sleep. I just like really was in a fog.
Starting point is 00:02:52 And I tried to go. And I'm like, looking at the dock. And I'm like, I can't even read the docket and my mouth the swollen tongue. I'm now four days or five days past the surgery. But at the taping of all in, it was like, whatever, 48 hours. And I was just loopy. And I was like, you know, I don't want to disappoint the audience to be loopy. So yeah, I just took a day off.
Starting point is 00:03:11 Which, of course, is always great because the MAGA people are like, take a permanent vacation, Jake Allen, and other people are like, I'm not even watching the show. So, you know, to my MAGA friends who absolutely are. thrilled when I'm not on. They're like, oh, more time to talk about Ukraine and Biden, Biden, Biden. But it was a good episode, actually. So great job to the TV. I only made about three quarters through, but yeah, it was fun. It's, yeah, but it was missing the moderator. How are you doing? I know you been traveling and grow and continues to grow? Yeah, you know what? Maybe let's like, it was a big week this week. Let's do a little bit of news before we do demos. There's kind of like
Starting point is 00:03:47 three important news stories that we want to highlight coming out of this week. And, you know, I had a tweet about it, so maybe we'll use that as like the grounding here. And this one's kind of related to us, but we won't talk about GROC here. But, you know, three major companies launched chips this week. And this is really important. So the three companies were meta-announced a new chip called MTIA, Meta Training and Influence Accelerator. Google made some of their chips available to the public out of their conference, their TPUV-5.
Starting point is 00:04:21 and then Intel launched the Gaudi 3 AI chips for mass production in Q3. And that's really interesting because these are three major companies that are basically out there, you know, putting new hardware into the ecosystem. And, you know, let's, what are your thoughts when you read that? What do you make of that? Yeah. So it does seem there's a number of things that occur when we have a boom like this. you know, there were people who've been investing in this technology all along, and they've seen,
Starting point is 00:04:55 hey, there is a path here, and Nvidia comes to mind, right? Like, they saw there was a path here, but they were working on video games, crypto, and then AI. And then, of course, crypto kind of plummets, video games still growing on a pretty good clip, but of course, AI then becomes a spoon. And when people see that, there are two drivers in basic human behavior. One is fear, and one is greed, right? Yeah. And so if you pause and you think about, you know, okay, your Intel, your Google, your Amazon, whoever it happens to be, meta probably has a fear that, or I should say,
Starting point is 00:05:35 they see an opportunity having their own chips. What's the opportunity there? I think they're probably opportunistic. Hey, we have this data. If we have these chips, we can save money. So sure, we're backing up the Brinks truck. I think they're one of the biggest customers of industry. of Nvidia.
Starting point is 00:05:50 But, you know, hey, this gives them a little bit of a hedge. Hey, you know, if we have to negotiate prices with Nvidia, you know, we do have some of our own ships being deployed here. And then for other folks, it could just be complete fear that they're going to lose their business, you know, like in Tao, right? And that other people are going to run away with it. So there's usually those dual, you know, motivators. And what's good for everybody is, you know, most of these projects will probably fail to be
Starting point is 00:06:16 significant, but in aggregate, they're going to drive prices lower and the competition will make everybody sharper. So you could always see in one of those tweets, I guess it was Intel was claiming, you know, they're all going to make claims. Hey, we're better on this task and friends. We're this percentage better. And that's what you really want to see in a thriving economy is competition. And here we go. Competitions here. It's great. Yeah. I'll just add like one more thing on that particular story, I think that holds true. You know, we don't really see any of these chips in production or external benchmarks just yet. So that's, you know, kind of TBD, which means that it is sort of like a, you know, maybe like you said, like an internal thing slash pricing
Starting point is 00:07:01 pressure thing. The other thing that I thought that Google did at their conference was not only did they launch like an AI chip, which is all the rage these days, but they also made available a new kind of CPU, which is an arm-based CPU, which is interesting because that's them kind of going more directly after the traditional compute stack with a chip that they've created. And so it's really fascinating how the future world of compute is playing out. Yeah. And if you look at someone like Facebook, they have really pushed open source hardware, commodity hardware, because they realize that the business they were the first actually. They were the first back in the day. Yeah. So they've pushed very hard for decades now on just making servers, commodities,
Starting point is 00:07:52 data centers, commodities, the infrastructure and data centers are commodity because that serves them, right? And I think Google participated in that as well. So you have the people who have a consumer application like Google search or Instagram, Facebook, a social network, and the advertising businesses, they don't care about the hardware being commoditized. That's better for them. Now, Nvidia may care very much. Brock may care very much. And so this just makes everybody sharper and better at their jobs.
Starting point is 00:08:22 And I think that competition is going to become very real. But like you're saying, are these in anybody's hands yet? It takes years to get these things into people's hands. Right. There it is. This was a big project. Yeah, this was a big project that Facebook started, you know, back in 2009, right? So it has been over a decade, which is incredible.
Starting point is 00:08:42 Yeah, almost 15 years. Yeah, wow. And that really has driven a lot of server-based and cloud-based computing is this commodification of the hardware sack, right? And so, yeah, great. Awesome. It's going to be great for the industry. And, you know, there's other problems that need to be solved.
Starting point is 00:09:01 And then I guess we'll get into some of those now. Okay, switch gears. Two more quick news stories. So Adam shifts. So this one is kind of near and near to you, right? Because, you know, he has pushed. put something on the table to basically, you know, require people to disclose, right? It's called the Copyright Disclosure Act and disclose where they got their content from. You know, this is an
Starting point is 00:09:28 interesting one because it's very near and dear to you, and we've talked about this a lot. Sure. Actually, we have a demo coming up, which I think is an incredible demo, but definitely does cross into some of these lines. But what do you think about this law? I think. think this is sort of what you've been saying for a long time when it comes to... Yeah, I mean, I hate to say, I told you so, but... Yeah, yeah. I told you so. Listen, as a founder, there are things I love doing, like building products or meeting with
Starting point is 00:09:56 partners, hanging out with my team and dreaming up new ideas, and then there are chores that I don't want to do. I don't want to do HR. I don't want to do payroll. I don't want to deal with all that. So I use Gusto. Gusto is the best for payroll, for HR services, and for running a small business, it makes everything so much easier. Even a mid-sized business, man, I get a lot of portfolio companies
Starting point is 00:10:17 that are pre-sizable using Gusto because it is designed for you, the small business owner. And payroll is something you definitely do not want to mess up. You got to get it right. And Gusto is going to make it perfect for you by calculating paychecks perfectly. Also, payroll taxes. You got to get your taxes right. You can't make mistakes there. And you want to set up open enrollment. You want to be good to your people. Gusto handles onboarding, health insurance, 401k, time tracking, commuter benefits off the letters, and they even give you access to HR experts. So Gusto takes all of this off your hand and lets you focus on important stuff. Your product and your customers, it's super easy to set up and get started.
Starting point is 00:10:53 And if you're moving from another provider, Gusto will transfer all your data for you. Here's your call to action. Because you're a Twist listener and you're part of the family, you're going to get three months free, incredibly generous, totally unnecessary. Thank you so much to our friends at gusto.com slash twist. You must go to Gusto. Again, gusto.com slash TWIST to get free months free. Thank you, Gusto team. You can't just take people's work and build a derivative product out of it without their
Starting point is 00:11:18 permission and without their consent, without, you know, paying them. And so here we are. The industry has stolen content and they've explicitly stolen it and they knew they were stealing it. And so opening eye, it's come out, has stolen tons of content. They built scrapers to do this. and their concept that it's fair use is laughable. You as the person who created this IP, you have the right to create the derivative products from that IP. And the fair use doctrine is very narrow, and its purpose is very clear.
Starting point is 00:11:54 Educational to make society better, right? A small portion of the original work and not interfering with that person's ability to monetize it, you can look up the four-part test. There's little exception. So, you know, if you're doing an educational project, you get a lot more leeway. An example of that might be if I wanted to do, you and I decided we're going to do a critical analysis of Blade Runner. We could sit here and play clips from Blade Runner,
Starting point is 00:12:16 but we can't create Blade Runner 2049. And so people will use like a really silly argument, like, oh, well, this is how humans learn and the computers learn differently. None of that really matters. The way intellectual property works is you have some amount of ownership of it. There are fair use exceptions for education and using small amounts. of content, but that doesn't give you the right to create the derivative product and exploit future products unless you have a license. So what I like about this bill is it just says, hey, tell us what you used. And that seems more than fair. If you used my content to build something, I should know. Yeah. Yeah. And so I mean, look, I'm on this one, I do hope, what I hope happens here, and I'll
Starting point is 00:12:56 just end on this, is I hope that New York Times gets an injunction against Open AI, and they have to pull their product from the market. And I think the New York Times, Dow Jones, all. Open AI. Yeah, I think they should all get together and gang up on Open AI at this point right now to protect the future. And this idea that, you know, oh, it can't be done and technology always wins. Tell that to Napster. Tell that to scour.
Starting point is 00:13:20 Like, you can stop this. You must be coordinated in order to stop it. The music industry is a highly coordinated group. What has to happen is journalists, publishers and content creators on the internet, have to join that group. And as a United Front, they should get together and they should not stop with just a settlement with Open AI. They should force them to remove the product from market and they should force them to start the
Starting point is 00:13:46 product over again. Because if you stole all that content and you made the model and then you're saying, oh, well, you know, now we'll leave you out of it. You've already created the value. And $100 billion in value has been created. And I think $2 billion or $3 billion in shares have been sold. So essentially what's happened is they've taken the value. of the New York Times and other publications.
Starting point is 00:14:07 They've built a company. That company has perceived value in the market, the point at which the most sophisticated investors in the world are buying it at a $90 billion or $100 billion evaluation. That money, a portion of that belongs to the New York Times and whoever else they scrape. And so, you know, hopefully this time the content industry will act in unison and not fold.
Starting point is 00:14:28 That's my belief on it. I think you and I are a little bit different sides here. I wouldn't think that open eyes should go down, but I do think, you know, a lot of those organizations struggle, and they should get at least some share of the revenue or something like that, that's being generated while everything else is being settled. But that bill is going to be interesting. And, you know, let's put another bet, J-Cal.
Starting point is 00:14:51 Because, you know, since we're on a way to 100, you know, bets, we're probably past it, but who knows? This is just take aside, does this bill pass or does this bill, you know, what version of it passes. I think that a bill will get passed. I don't know if it will be this one, but I do believe a bill to do this will get past because it's going to take 10 years
Starting point is 00:15:16 to litigate this stuff or 5, 10 years for this to go through the court system. But NAPSUR didn't take that long. They were a private company sued into oblivion. So, you know, yeah. So, I mean, here, I think Open AI, they have a lot of resources. And so part of this is they can fight.
Starting point is 00:15:32 They can fight for a long time, whereas Napster didn't really have the ability to fight for a long time. Even YouTube. The reason YouTube was sold to Google was because. So they could fight the fight. The lawsuit. And that took years and years and years. And so, you know, I do believe that there will have to be some new laws around training specifically, because we're sitting here and we keep debating. Is it legal to train on other people's data?
Starting point is 00:15:59 I guarantee you. It's not legal. And I guarantee it will be found to not be legal to use other people's content to train a new intelligence that you can then go exploit that work. Well, maybe we'll come back to this bet. We have to think about it a bit more. We have to think about how to frame it. And it's not that I want to see Open AI go away.
Starting point is 00:16:18 I do believe the technology is valid. But if they could build this technology without the content, they would have. And all the papers that you and I have read and discussed, say the more data you put into it, the better the output. And that's obvious to anybody who uses these that it's stealing other people's content in order to give the answers. So if it's giving answers, based on content, it found that the New York Times or YouTube videos or whatever web content or books, and they know they stole it. They did it covertly, and they're trying to cover it up. And I think they need to basically redo all the models. They'll have to start over. And I think that's what the New York Times
Starting point is 00:17:00 and Wall Street Journal, Dow Jones, Disney, they should all via Com, all the major content creators, they should get together. And they should, as a group, sue Open AI into oblivion and make them pull the product from the market and then make Open AI get permission and then have them start over. That's what I think should happen. Got it. And that's my advice to content injury is, you're going to lose your entire business. They're going to lose their entire business. Just like Google took over the entire ad business. It's a perfect segue, you know, J-C-Chi.
Starting point is 00:17:32 You always managed to do it. I didn't even set it up this way. But there is a new service that just got launched this week that's backed by tech and music heavyweights called U-D-O, U-D-I-O. And I'm going to pull it up here. You can see here, it's a new service that's backed by tech and music heavyweights. And it has powerful capabilities. And I'm going to go right into a J-C-C-C-C-L. Yes.
Starting point is 00:17:59 And I did this song in the style of Dyer Straits about New York City and big money. And Jake, I'm going to play this for you. Okay, here we got. And I want the raw reaction. Okay. You're going to get it. I mean, it's so impressive. It's not exactly dire straits.
Starting point is 00:18:34 That was more like, I forgot the person. Against the wind. Who sings against the wind? Tom Petty? Against the wind. No. Against the wind. Bob Seeger and the Silver Bowl.
Starting point is 00:18:44 a little bit more. Yeah, a little bit more Bubshooters. But the fact is if you played me, if that song was playing on the radio and you and I were driving down the road, I would not know it was AI. I might think it was cheesy when I listened to the lyrics. Yeah. We are now past the uncanny valley.
Starting point is 00:19:00 This is absolutely of the quality in which it would pass a Turing test. In other words, you would think a musician and human musician had written it, but that does sound so much like Bob Seeger that I'm surprised it didn't get the dire straits piece.
Starting point is 00:19:19 And I'm excited about this product to exist because I do think we might get some Rolling Stone songs or some dire strait songs or Bob Marley songs or Jimmy Hendrix riffs. That, you know, I know it sounds sacrilegious to people that you might enjoy as much as the originals. Look, business leaders face a maze of tasks today. We all know that creating and managing your company's ownership shouldn't add to your stress. Well, meet Mantle. This is the AI-powered equity management platform for modern founders and operators. It's going to simplify your strategy and save you a ton of time. Mantle's been built from the
Starting point is 00:19:55 ground up by founders for founders, and they've spent 12 years building and scaling successful companies themselves, and they've seen every mistake in the book, and they've solved for it. You can model your price round. You can update your equity documents. You're going to understand your dilution. And it's designed for ease of use across all stakeholders. Power by Mantle, AI assistant, man, it's fast. For example, you just drop in your term sheet and you watch the platform generate a pro forma cap table for you in seconds. This used to take, oh my God, you would ask your attorney, it'd take a week, and then it was wrong. And now it just gets done instantly. And this will allow you to focus on the things you need to focus on and not worry about your cap table. So here's a call to action.
Starting point is 00:20:36 Visit W-I-T-H-M-A-N-T-L-E dot com slash twist to get your first 12 months free. And you're going lock in an exclusive rate of $100 a month after your first 12 months. That's withmantle.com slash twist for your first 12 months rate. See why hundreds of founders are switching to Mantle right now. You missed the beginning there because I think I was playing it before. So I'm just going to do the beginning of it as well, the first 15 seconds because I was really, I really thought it was great. But he takes it and makes it on his.
Starting point is 00:21:21 Oh, man. I mean, it's, yeah, I mean, it sounds a little like counting crows, maybe. Okay. Counting Crows in there. So, yeah, I like it a lot. And so, look, they've done an incredible job here of all the ones we've tried. And, like, they don't, you know, have like a sort of, like, you can put in style of, you know, a band. Fantastic.
Starting point is 00:21:46 And they've really made it work. They've really put it together. And it's super, super impressive. And, you know, it has a bunch of ex-steep mind folks that started it, you know, backed by one of the Instagram co-founders and A16T. Yeah. So when you type in the name of it, though, it should, if you say I wanted in the, in, so is Dyer Straits licensed their music to them?
Starting point is 00:22:15 Is Bob Seeger licensed to them? Do they have the rights to people's music? It's just trained on, you know, Columbia. records and Bob Dylan's catalog. Will I Am is involved. And he's kind of been at the intersection of tech and music for a few years, right? And there are many years now. But in the article that I pulled up, they did say they didn't confirm or deny if it's been trained on copyright music without permission. That means it has been. Yeah. All these people are guilty and it's all going to come up. You might as well all fess it up right now because you're going to get busted because
Starting point is 00:22:49 you sent a scraper out and the scraper scraped it. There's a tracker of a scraper unless people who are in these LLMs are going back and are wasting all the code they did and then telling their employees to lie, the employees are going to know. And there's some employee who had a conversation, just like when that woman from Open AI with SORA was like, yeah, I don't know exactly what it was trained on. And it's like, uh, you work this.
Starting point is 00:23:12 I think she's the CTO. You see, oh, yeah, yeah. If you don't know, that's like going into the back of the rest of, restaurant and you're like, who cook this steak? And there's like 10 chefs and they're like, we don't know. Yeah. It's like, but you're sitting there cooking a steak in front of us. There's the head chef. There's the head chef. The head staff is literally cooking a steak. And the head chef is like, she's like, I don't know who cooks steak here. It's like she's flipping the steak over. I should be saying it's like, well, you know you're lying. And
Starting point is 00:23:43 you know, the question I have is I don't believe the music industry has the right to this. In other words, If you're Columbia Records and you have a relationship with Bob Dylan to publish his music, do you have the right to create virtual Bob Dylan? I don't believe you do. And so I think there's going to be another layer of lawsuits, which is Bob Dylan's going to be able to sue Columbia Records if they try to license his lyrics to one of these services and his voice to make future music. And I think, Bob, we should not allow record labels to own people's entire like
Starting point is 00:24:19 and ability to write the next set of songs without their permission. The Rolling Stone article is interesting. They definitely talk about, they don't say whether they did or not. They do say they have AI to detect if a song sounds too similar to an existing piece of work. And so this is the New York Times lawsuit kind of thing where they got it to spit out like the exact words of the article. and so maybe that's the you remember that famous lawsuit with vanilla ice and ice ice baby
Starting point is 00:24:54 and then he took that beat from I think it was like a sting song or wasn't it or something like that that's what they're trying to stay here and David Bowie because that was under pressure yeah you're under pressure yeah yeah sorry yeah I got that wrong and he said oh no I changed the beat by one right
Starting point is 00:25:11 yeah and then he got in trouble because he didn't change it enough Let's put things into two different categories. There's a human being who's inspired by another human being to create something. Yeah, vanilla ice, right? Yeah. So whatever you think of him as an artist, he has a collective amount of music he listened to over his lifetime. And he created a new song.
Starting point is 00:25:32 And either he unconsciously channeled that or he explicitly copied it and edited it a little bit. Okay. So now that one human has created one piece of output. based on some number of pieces of input. Okay, that feels like a certain scale, and then society can debate the output there, and did he steal it or not, right? And how close is it?
Starting point is 00:25:57 And there's a test for this, which is, is the audience confused? So if I were to create, if I were to create a Star Wars film, and I called myself, you know, Darth J. Cowell, and I made a whole, you know, character around myself as a Sith
Starting point is 00:26:15 Lord, etc. And I had a lightsaber and I had two droids who went around with me and made funny jokes and were, you know, and I was up against a, you know, a Jedi. And then I had a little teacher who was like a Giotta. You know, like, the audience would be very confused by
Starting point is 00:26:31 it and they would assume that this was in some way, Star Wars. And so now we look at wholesale. So now you have two examples there. Ice, Ice, baby. And then me creating my own little short film. In both cases, you can sit there and discuss, hey, how confuses the audience? Now, imagine, you take every film ever created, every song,
Starting point is 00:26:55 ever created, every lyric, every written, every story in the New York Times, every book ever published by Harper in the library. And then you say, now we can create all output at all time. And I, as the person who created this LLM, get all that economic value, these are profoundly different things. And so for people to use the analogy of Ice Ice Baby is just so ridiculous because you have but one artist making but one song and the courts and society can, you know, debate that. Taking everything ever created and putting it into an L.M., which is what Sam Walman and
Starting point is 00:27:32 Open Eye is doing. This is what they want to do. This is what Google wants to do. They want to take all the content in the world ever created and they want to get the economic value from it. That is completely different than writing a short story inspired by Stephen King that might use one of his characters. And even in that case, you probably would have to settle and license, you know, the content or license like the hip-hop industry did. We have a great analogy of it. The hip-hop industry has been sampling songs forever and they just pay a small
Starting point is 00:28:01 licensing fee. And the people who have their music licensed by some hip-hop artist, which has a tradition of doing these things, they love it. Yeah. Yeah. Like for the love of God, please license it more. I'm sleeping and you take something from Queen and under pressure and I get paid of royalty? Great. But the technology industry doesn't even want to give that edge.
Starting point is 00:28:22 That just shows you, you know, I don't want to use a really colorful piece of language here, but it just shows you how unethical our industry is. Okay, okay. Well, look, you know, it was nice to see some industry folks involved. Yes.
Starting point is 00:28:37 Hopefully they find a path to it. It's really good. good. That's great at J-Cal. Oh, I give this an A. I give it an A. Yeah, just straight up. It's great. And if you type in, I mean, at a minimum, if you type in dire straits, it should say, you know, we don't have permission to use dire straits as music and like this in here. You can describe other things about music you like, but it should tell you that it doesn't have the rights to it. And if it does have the rights to it, it should say we have the rights to it and explain that. And this is what I think what's great about the bill that Adam. Schiff is proposing is it's just looking for disclosure. Just be honest about what you're doing here. And our industry could go, the reason our industry is not being honest is because they're liars and they're thieves.
Starting point is 00:29:21 Yeah. If you weren't stealing and you weren't lying, you would tell the truth. We didn't train on this. When people don't tell you in our industry what they've trained on, they're liars. Yeah. And they've stolen it. So just that's the ultimate tell. Because if they didn't steal it, they'd say, no, no, no, we trained it on only stuff we've
Starting point is 00:29:37 licensed. You really think that these institutions. super intelligent people at Open AI don't know what they trained it on. Really? These are the smartest people in the world. Let me just give you the opposite side. Just for the sake of argument. When you let something loose onto the internet, like a crawler, and you made a crawler and you had it go look at videos everywhere. Yeah. Now, the question you could say is like, hey, did you hit YouTube? That you should know because you shouldn't have been there or not, right? Yeah, it's URL. You could just look at the log files. Yeah. But like, what if?
Starting point is 00:30:10 there's YouTube videos embedded on pages, which they are all over the place. And it watched those. Literally in the code. It's literally in the HTML code. You would see it there. Would say embed YouTube. Yeah.
Starting point is 00:30:22 Let's be honest. You're making, you're actually arguing my side of it, which is these are highly technically sophisticated people. They know what an embed is. They actually would know bad content. So all you have to do to bust the opening AI stealing is to look at what they excluded and ask them,
Starting point is 00:30:38 why did you exclude this? And if you said to them, hey, why did you exclude this? And they'd say, oh, those are just like, we happen to stumble upon with our crawler or some random. It's like porn sites, most likely. Right, yeah. And they said, oh, no, we didn't want to have porn sites in here.
Starting point is 00:30:51 We didn't think that was really good content. Or, you know, although this was a different language, and we were doing an English language one, so we didn't need Japanese, so we excluded it. Or this was just machine language. This was just code. So we left that programming code because we're not doing code in here. We're doing, you know, whatever content.
Starting point is 00:31:06 This is, you know, an image database. And so you could just ask them, what did they include? What do they not include? And the crawlers break. The crawlers are optimized. Like Google's crawler is optimized. They're optimizing it all day long. There are probably thousands of people in the last year who have optimized the Google
Starting point is 00:31:29 crawler. I would say probably a thousand people have sat there and written code to make that crawler more efficient. So to pretend that they just like, oh, we just said it, lose something the internet. We don't know what came back is the height of arrogance, would be the height of arrogance for them to say, right? Hey, everybody. I am obsessed with AI right now.
Starting point is 00:31:49 You know that every Tuesday we do a bunch of AI demos, and we're trying to figure out on this very program, how do we take all this AI potential and make it a reality? So when we're running our startups, our startups are more efficient and we get more done with less, and we delight our customers. I just read a report by our friends at HubSpot, and they're talking about all the different ways to use AI to improve specifically sales marketing and customer support.
Starting point is 00:32:11 Now, if you're running an organization, you know that you live and die by your sales and that marketing drives yourselves. And that customer support is how you keep your customers. These are three of the most important pillars in your startup. And the team at HubSpot did something really interesting. They surveyed a thousand early stage founders. They asked them, how are you using AI to do sales, to do marketing, to do customer support? First, using AI to segment your customer list. What a great idea. Second, personalizing everything with AI from your website content to SMS to email. Third, how do you encourage your team to get creative with AI? And fourth, how do you balance between investing in AI trained experts, right, and developing your current team? Now, you're going to read this report and you're going to get all of this information. These weapons for massive growth, WMGs are just waiting for you. If you're in your podcast player, check up the link in the episode description. And if you want to save 70% on HubSpot for Startups program, head over to HubSpot. HubSpot.com slash startups. That's right. HubSpot loves startups. They were a startup themselves.
Starting point is 00:33:07 Visit HubSpot.com slash startups to see what discounts you qualify for and start using their powerful solutions and pricing that will break the bank HubSpot.com slash startups. Yeah. I mean, like this whole idea, because something's open on the internet, Sunny, doesn't mean it's yours. It doesn't not mean it's yours. My car is parked on the street here. It's on a public street. You can walk up to it. You can sit on the hood of my car. It doesn't mean you own my car and you take it. Yeah. Yeah. And that's the position that Open AI's We trained on the open internet. Yeah, society's open.
Starting point is 00:33:38 You know, my front door might be open right now. You walk in, doesn't mean you can steal from my house. Yeah. No, it's interesting times where they're for sure. I feel like I'm a, why do I sound like a lunatic trying to defend copyright? It's like so funny in our industry how people trying to defend basic. But you know why? Because many people in our industry, many people we know have benefited, right, from the growth of these companies,
Starting point is 00:34:02 whether directly involved or indirectly involved, right? And look, the flip side is we don't really pay to use Google, we don't pay to use YouTube, we don't pay to use any of these services. And so the company has to sit there and say, well, we have to do some of these things because that's how we make our business work. Right. And so it's a really interesting time. The whole notion of training a model and the argument is to be said,
Starting point is 00:34:28 well, that's just like a person going and watching all the videos of guitar players on YouTube and then all of a sudden creating a style of their own that's in the style of Jimmy Hendricks. Do you anything to Jimmy Hendricks? Probably not, but it's different
Starting point is 00:34:42 if you're doing it as a commercial entity. But if you went and become famous, it's fine. That's the thing I can't really, you know, no one could go to an artist and say, hey, you were inspired by watching YouTube and you got here
Starting point is 00:34:57 and you now owe all these people royalties because you've become a, you know, a multi-platinum or, you know, however the category is. There's an example of this. If you were to go and take all of Dire Straits records and create a Dire Straits cover band, and then go on the road,
Starting point is 00:35:13 and there's one called the Dyer Straits experience, I think. And I wanted to see them because I would, they literally do the entire album of Alchemy. They call it re-alchemy, which is my favorite album of all time. And I really wanted to see, but they're only touring Europe, and it just hasn't been in sync. But they have to pay a licensing fee to, do that. So there is literally an analogy here, which is if you do a cover band, you have to pay fees.
Starting point is 00:35:37 Every time you perform, you're paying licensing fees through royalty organizations. If you wanted to create, you know, a version like I used before of Star Wars, if you wanted to make a Marvel comic, if I wanted to take one of the X-Men and make my own series based on Cyclops, I would need permission, right? And so you could be inspired by, I think we all know what that is. And then when you take the entire corpus, that should give you an indication that if you took the entire corpus, yeah, maybe you are stealing,
Starting point is 00:36:07 yeah. And why would you not get permission? That's the other thing. It's like, why wouldn't you get permission? Oh, this is like a reasonable thing to do, you know? I'm going to show you this, I try to do this one. Maybe I missed it when I did it.
Starting point is 00:36:21 What did you give a letter grade, by the way, too? I'm going to give it an A, but I noticed, I just want to share one thing because I want to get these guys on. UD-I-O.com. I'm proud of it. Yeah. And I was doing this because I thought we would be able to, we could get this song here. I said, a song in the style of Dyer's Rites, Sultans of Swing about a friend that is really passionate copyright protection. Oh, no. Oh, no.
Starting point is 00:36:42 And when I did create, it did give me an error a second ago saying, you can't do dire strates. So maybe there. Yeah. Fascinating. Yeah. So. So maybe they are thinking about these things. But let's play this one real quick. Guardians of the score. Guardians of the Square. Here we go. hilarious.
Starting point is 00:37:25 I mean, it's hilarious. I mean, it's hilarious. Right now, it's super funny, and I think there's going to be great art created with this. That's what I'll say. I do think we're going to see some great things come out of it. So I don't want to say I don't want this product in the world. Yeah.
Starting point is 00:37:42 I just want to see it be fair. So if you're going to do this for dire straits, it would not kill the person who is making this piece of software. It would not kill them to get permission from dire straits. And it would not kill them to not have permission from dire straits and have every other artist. So like, remember what's her name? Taylor Swift didn't want to be on Spotify at some point and she didn't have her music on there. And I was like, yeah, that's totally fine.
Starting point is 00:38:09 I mean, and Daniel Eck was like, well, no, you know, and he kind of got into it on Twitter at some point. And I was like, no, artists who don't want to be on your platform, don't need to be there. It's their choice. So let them not be there. And, you know, you have to cut a better deal with them if they're a better artist. And it would not kill this service or any other service to get permission
Starting point is 00:38:27 to pay and to pay a term that that person felt was great. The Rolling Stones might say, yeah, well, the Beatles held out for a long time, if you remember, to be on iTunes. That was like a big deal when the Beatles finally decided. So there are content. They had like a whole ad campaign about it. Yes. And you know what? As it should be.
Starting point is 00:38:47 It's their content. They get to negotiate it. And you know what? All these people are hypocrites. Because if you stole the Google algorithm and made a new search engine and you stole their index, you could be sure they would be all over you. Absolutely. fascinating times. All right, let's go on. J-Cal, you're really going to like this next one. Okay. It strikes me as like a J-Cal daily. So I think this one might make it into the daily workflow of J-Cal. It's called Aqua.
Starting point is 00:39:15 And what it is, like sort of like a note-taking app, that doesn't just do straight transcription. Okay. And so it lets you talk to it, but then as you're making the edits, it will fix what you're saying. And so you could kind of, let's say you're trying to formulate a thought. And then you're like, oh, no, no, go back and change it. So let's give it a try here, okay? All right. You know, I've had this meeting with Jason and we were talking about copyright protection. Actually, actually, actually start all over.
Starting point is 00:39:50 What really, we had this meeting and it was about buying new GPU chips. and I was trying to convince Jason that groc chips were the best chips. No, no, no, just start all over again. So it understands just start all over again. It might understand like when you use notepad or using the transcriber, a new paragraph, that kind of thing. Exactly. But not just that, right?
Starting point is 00:40:19 And so here's the example. You can say, remember that meeting. It's on Thursday, Friday, Friday. And so it knows that you meant Friday. And you don't have to say start all over again. Or like, you can say imagination is, more important than knowledge, Albert Einstein, put quotes on that.
Starting point is 00:40:33 It knows how to go back and do that. Right. So this is like, it's, what I like about this is transcribing has worked pretty well. And we're finally starting to see the gains from it and people use it. I see people all the time composing text messages. Yeah. By hitting the microphone,
Starting point is 00:40:49 it transfers what they're saying and then, but you do want to bold something. You want to make something a link. You want to make a new paragraph. And somebody coming up with a way to do that without ever having to touch the keyboard is great. So yes, I give this a B plus. It sounds like a really smart tool that needs to be made.
Starting point is 00:41:10 If you can start talking to say, you know what, can we make a bullet point list out of that and see how that looks and then make it a table as well. And then show me the bullet point list in the table. No, no, let's do it. So let's do it. Let's give it a try here. Hold me bring it back up. Yeah, just say, you know, my favorite foods are, you give it a bunch of foods.
Starting point is 00:41:26 And then say, can you put that in a table with the calorie count and see what happens? All right. I want to make some pizza tonight. The items I need are dough, pepperoni, cheese, pizza sauce, and peppers, onions, tomatoes. Actually, can you just put those items in a bulleted list? Okay. Yeah. Yeah, that's pretty good. That was pretty sweet, I have to say. So the LLM was listening, and for people who are watching, it went from a paragraph just to a bulleted list. I mean, that was pretty nice. I have to say. say, dictate, edit, and transform using natural language. I give it a B plus. Oh, I thought you were going to upgrade it after the bulleted list. No, I mean, I think this is what I expected it to do. I feel like this is something that will be a notepad.
Starting point is 00:42:20 And so, you know, as a startup, you know, my advice to with Aqua is to really start to think about, you know, what's defensible here and who their market is because I kind of feel like this is something that notepad, grammarly, are going to be able to add pretty quickly. But I do think that they've just, you know, they got like a couple of months ahead of them,
Starting point is 00:42:46 like they're six months ahead of them. So I do wonder, you know, who this is for. I'm not, I'm not going to stop using grammarly or my notepad to use this, but I'm going to play with it.
Starting point is 00:42:56 I will play with it. Okay. Okay. I'm going to give this an A. Okay. And I think what they should go all out on is, And like I said, they should go all out on just dominating this, like becoming the best app that does it,
Starting point is 00:43:10 like sort of in those early days of apps. Because I do think, look, they have a lead, and I think they could create an experience, which the main reason I don't like using voice to text, which I notice a lot of people do now, these errors happen. Then you're like sitting there editing it. You're like, I wish I just typed this out.
Starting point is 00:43:28 But if I wanted to get a thought out and kind of the way that this allows it, This would be really, really powerful. I'm going to try to put it in my daily work. Yeah, give a shot. I mean, I think Grammarly works really well for this. And that's why I started with grammar. How do you use Gramarly for it?
Starting point is 00:43:42 Like with it? So I will talk into the Gramerly app or I will talk to a Gramaly web page or I will use the Grammally keyboard on my phone. And so, yeah, you know, Gramerly is just very good at cleaning up your pros and giving you some options and ideas of how to make it better. And so I pay for it for my phone. It's very good at that. Yeah, same here.
Starting point is 00:44:04 I think it's great. I find my whole team is like, it's less embarrassing. The idea of being embarrassed by something somebody sent because they didn't use grammarly is kind of ending now, which is great. Like people would send, sometimes I'd see somebody send an email. I'd be like, what the, you work for me and you're misspelling this word or you're like, it's so sloppy or it doesn't make sense what you're saying. Now you use grammarly. It's like really hard to be, to write something bad in grammarly and get it past grammarly is. hard to do.
Starting point is 00:44:34 Like, to have a mistake in grammarly, I think is impossible. I didn't know that they had a, I'm going to try, I have it on my. They don't have these navigation tools. They don't have that, but I do know in Siri, you know, when you hit the microphone keyboard, the microphone icon on your keyboard on your eye, I don't know what they call that dictate. The Apple dictate tool has gotten better. And if you do say new paragraph or strike that last word, like some of those work, but not
Starting point is 00:44:59 a lot of, not like this. Not like, hey, start over. not like, hey, make it a bullet point list. So I agree they should keep working on this. And see a world class notes app. I think everybody would use it. It'd be awesome. Yeah, ever,
Starting point is 00:45:12 I mean, every couple of years, somebody finds a new vector. Evernote was the one that was a cloud-based and mobile. You know, grammarly is based on AI, machine learning and making you a better writer. This one is based on formatting.
Starting point is 00:45:25 So yeah, there's always an opportunity with no taking up. So I agree. But yeah, I give them a big plus. Keep going. I'm going to give them a many. I'm going to give them an A.
Starting point is 00:45:33 I like it. Great. Keep going. Okay. So the next one on our list is, so we saw a couple of weeks ago, Devin, which was the automated coding that had like a sort of multiple work spaces to work on a problem. And this team has basically made an open source version of it. And so if you go to SWE dash agent, this team has come together. It's an open source project, and they compared themselves, again, some of the bigger models out there.
Starting point is 00:46:09 They have just a demo in place here. I didn't want to do this from scratch. And so you can see here, they have like a 30-step demo. So it's like they have an issue that they pull from their repository, basically. They have it create a bug. They reproduce the bug, and then they move the code around. So I'm just going to go through this quickly. This is, you know.
Starting point is 00:46:31 And so it reproduces it. And look, it's just, it's open source. And what's awesome about this is they've, you know, made this available to everyone very quickly, shows the pace of development we're at. And I think folks are going to take this and really kind of build on top of it very, very quickly. And, you know, it kind of just walks through the same workflow that we saw these other ones. Tell me the name of this project again. This is called SWE-D-A-A-A-G-A-A-G-A-G.
Starting point is 00:47:00 Oh, right? So it's a software. engineer agent. Agent, yeah. And it's now open source, hosted, and you can go play with us at SWE dash agent.com. Yeah. And you can get access to the code, and you can see, you know, what everything is behind it. They're going to release their paper.
Starting point is 00:47:19 They show it how they're scoring in the software engineering benchmarks. So do you see this as being like paraprogramming where you and a agent are working together eventually? What do you think this is going to look like when, it's finished. You know, when I say finished, it's like reasonably trustworthy enough for you to use every day
Starting point is 00:47:39 and somebody would want to take the time to use it and it's not slowing them down, it's actually speeding them up. I think that's a really good analogy. I think it starts out as like a pair that's kind of giving, you know, someone's superpowers. And so, you know,
Starting point is 00:47:53 I read this really interesting analogy. I can't find who came up with it. And I'll try to find it in Twitter, but the search is, really difficult to use. I love it. It's always been terrible. Yeah, it's always been, it's always been
Starting point is 00:48:07 difficult. You may know someone that can fix it, you know, it's something about search. It's like such a rarely used feature compared to all other features that it's always, with the exception of Google, which is certain. I know, but the problem is most people don't. And it really has always been,
Starting point is 00:48:25 they did like a very advanced Boolean search where you do like from at Jason greater than this many likes or whatever. That's not what people want, people want a plain language, interpret my search, you know, tell me about the Nix or people talking about the NICs playoffs. And that's where I think language models will help
Starting point is 00:48:42 something like Twitter X leapfrog, right? Where the language model will be like, oh, I understand what your intent here. There's a website called StatMuse. You know about StatMuse? Everybody in the NBA uses this thing constantly, and I guess it's got some machine learning. So if I said, you know, which
Starting point is 00:48:58 point guards have the most 40-point games season. It should have Jalen Brunson or whoever come up with yeah, Jalen Brunson number two, Luca Donchick, number one. And so like that's like a just a natural language search, right? And it just
Starting point is 00:49:13 nails that. I think that's what people want. And I don't know if this is a language model doing it or it's just machine learning. Like look at this. When I type in, yeah, for Stapmuse, which point cards, you know, have 40s to season. And then if I said with
Starting point is 00:49:29 seven, a six, Yeah, this is like, this is RAG, right? This is retrieval augmented generation. So this is using an LLM to drive a database. Because this is structured data exists in a database, but the SQL for this is not, you know, trivial. And the LLM is able to take this English and turn it into the SQL and go and get the results for it. Yeah. You know, interestingly, Google just launched this for BigQuery and Snowflake just made this available for Snowflake, powered by Gemini for BigQuery and powered by, I think, Anthropic for Snowflake. But let me just check the snowflake. It's just amazing when you think about, you know, something simple like being an NBA analyst, right? And you see on the screen here, I said, which point cards have the most points per minute this season, right? Like, that's a statistic that, you know, I don't know, you would probably do the day before. Yeah, of course.
Starting point is 00:50:28 You'd have to go to the work. playing the New York Knicks, right? And then somebody would give that stat to the people who are doing it. Now you can just do it on the fly. Which point cards have the most points per minute this season? And as you can see here, again, Luca and Jalen and Steph are the three best point cards. And it's 0.9 points per minute for Luca.
Starting point is 00:50:44 And then Jalen and Steph have 0.81. And then it drops off from there. But like how wonderful to be able to pull up this level of detail on the fly. This kind of knowledge was, you know, pretty amazing. Yeah. I mean, it's mistral, sorry, they did it with text as equal with mistral on Snowflake. Yeah, this is going to be the world going forward. So let me share something with you just a quick aside, J-Cal.
Starting point is 00:51:10 And this is not an original thought by me. I read it and I'd like to find the person to give credit to, which is when the world went from pre-industrial revolution to industrial revolution, let's use an example of making cars. We went from making cars like in a bespoke kind of way, which is like you'd make one a day, till you had the Henry Ford production line in factory, and all of a sudden you make a thousand a day.
Starting point is 00:51:34 Similarly, in farming, right? We went from people working in farms to having machinery, and all of a sudden, you could farm thousands of acres with machinery and feed lots of people, right? And so that was the industrial revolution impact on our lives. What someone said, what AI is doing, and we're kind of looking at it in different ways, but that person's framework was,
Starting point is 00:51:55 we are now having the industrial revolution for digital. And their example was like, look, you used to make someone make a mock up or a picture, and then they'd make like one, a great illustrator, maybe take a couple of days. Now using Mid Journey, I can make like, you know, a hundred in a minute if I really want to. Right?
Starting point is 00:52:15 Or I could make, you know, a thousand songs in a minute, right? Just like a factory can make a thousand buttons in a minute. Yes. You know, or a thousand T-shirts in a minute or a thousand. But does it mean the book or the button or the t-shirt is going to be high quality or not? But it can spew a lot out. It can. And so now what we're seeing is for digital.
Starting point is 00:52:36 And we've had these eras where we had digital stuff pre the internet that was like sort of when you were working in Florida. Right. And then you had the internet show up, which, you know, kind of change distribution. And we had mobile, which was just like, again, going to like a different form factor. We had cloud, which made it easier. But this Gen AI movement is the actual industrialization movement of making more images, making more software, making more mock-ups, making it easier for us to access data quickly. And so I think with that, when you apply that back to, you know, software engineer agent, right? It's we can now, you know, the same way we went for making one card A to 10, we can 100x ourselves.
Starting point is 00:53:21 And so me as a software engineer, I can work on 10. different problems at the same time or 30 different problems with the help of these agents. What do you think about that? I feel like this existed already where I had writers, no, no, in a minor way. I had writers who would come to me and they'd have like, I would say, hey, come to me with great story ideas. And then, you know, I'd have bloggers or writers come to me in magazine day. Somebody would have seven incredible ideas.
Starting point is 00:53:50 Okay. And then other people would have one. And I'm like, how did this person come up with seven really great ideas? those people came up with one. And that person had different resources they used to come up with story ideas. They had different techniques, right? Yeah. And so they net net were seven times more valuable to the magazine or to the blog, right?
Starting point is 00:54:09 Yeah. And then you had people who had source. It turned out they had sources in some cases. They might have three or four sources where they would say, you know, to that person, hey, tell me what's going on in gadgets this week. And, you know, or they would just be shooting the, or chewing the fat with somebody and they would get these ideas for stories. And it was like they had some better technique,
Starting point is 00:54:30 which just then made them 10x better than the next writer or 100x. And that's just but one example in journalism, like your sources matter, right? So some source might get you the content you need, some leak that makes you a Pulitzer winner. And then somebody else might be a better technical writer than you. And so I think what's going to happen is there are going to be some people who figure out how to use this pair programmer,
Starting point is 00:54:52 how to use SORA, how to use, you know, whatever the tool is, they're going to find some like little edge and be able to use it in a way to perform at a much higher level. And yes, we will have the same way some knowledge work or some developers, some writers with sources, whatever it was,
Starting point is 00:55:10 or 10 times better than their contemporaries. This could be like 100. And so if you know how to use these tools, you're going to be just so valuable to different companies and then companies are going to start to learn. If you can't use these tools, then think about how little value you provide to your company.
Starting point is 00:55:30 It would be like trying to go work at a company in 2024 and you didn't know how to use Microsoft Office or email. You didn't know how to use an Office Suite. You didn't know how you spreadsheets, word processors. You didn't know how to use Zoom. You didn't know how to use Gmail. But you're like, I have a phone. And I have a calendar that I write shit in and have like a written calendar.
Starting point is 00:55:49 They'd be like, okay, short. can give it a shot, but you would just be like this, you would be like this Neanderthal, right? Yeah. And I think that's what's going to happen here is the people who know how to use these tools are going to be slowly become bionic and outpace their contemporaries. You know, like I said, that framework was really interesting for me. You know, I sold my last company to Ford and I spent a lot of time understanding the history of the company and really just, you know, what they were able to do in terms of industry.
Starting point is 00:56:22 industrialization. And when I read that, it just clicked for me. And I said, all the stuff that we spend time thinking about is wrong. Because we are about to undergo this moment that those folks did like 100 years ago when, or it was over 100 now, right? Early 1900s where they were like, people were making like one car a day and it couldn't change the world. And then all of a sudden when you took it to a thousand a day and made it affordable, everything changed. The world fundamentally changed. And I think software is still in that bespoke era, even though we've had all these advancements in making software, better programming languages, we're not doing punch cards anymore, right? We have great, amazing IDs. But I think we're about to have the thousand X jump in
Starting point is 00:57:08 software development. I mean, what does that even do? I mean, can we even comprehend, like, we can comprehend what a 10x developer does. You ask them to build something. You thought it would take two weeks. It comes back tomorrow. Okay, yeah. Instead of, 10 days, it took one day. Great. You love that developer, you give them more stuff to do. A thousand X person, like, okay, we have a roadmap to build something over the next three years, and it came back tomorrow. It's like, wait a second. Okay, so should we just start another company or should we start another product line? Like, that's really wild when you think about that. Or like, or think about like, you know, using like some kind of service. And instead of like
Starting point is 00:57:46 trying to integrate and, you know, maybe even pay someone to use it, you know, this thousand the next world, you just get something built bespoke for you. And so it really has a huge impact on SaaS companies. It has an impact on, you know? Yeah. I mean, it would be like, I'm trying to think of the analogy here, but, you know, I'm envisioning, I want a car and I want my car to be a sports car, but it also has a ski rack or like some way for me to put my skis on it and, you know, has snow tires and can, you know, be in four feet of snow, but I also wanted to be a sports car. And like, all of a sudden, this ranking car is on your doorstep, right? You just, you're going to be able to make very custom things that didn't exist before, which in manufacturing, we actually have now.
Starting point is 00:58:32 If you wanted to get a, the idea that you could get a t-shirt made or a pair of sneakers made to your specification with specific designs, we kind of take that for granted right now and nobody really does it. But if you want a sweatsuit with, like I see some people do this, like they'll have a birthday party or something for somebody and then everybody shows up with like a sweatsuit. That's the person's picture. And you're like, okay, that's corny, but charming or whatever. We should do that for our friend. We should do it for our special friend.
Starting point is 00:58:59 Oh my God. If we all wore a Phil Helmut sweatsuit, which is pictures of Phil blowing up. Oh my God, that would be hilarious. We should totally do that for the film. Birthday weekend. Oh, my God. If we all showed up in a sweat, a track suit, a Phil Helmut track suit with 10. pictures of Phil Helmute on it.
Starting point is 00:59:19 That would be hilarious. Just the track suit with logos at least. Just the track suit with the Phil Helmuth logos on it. Oh my God. So great. Any other debusorya ready to wrap? This is a great Saturday show. Ready this is a good one.
Starting point is 00:59:31 It's a wrap it Saturday. All right, listen, everybody. Go to check out GROQ.com. com.com. Yeah, the cloud. There is. We've got 85,000 developers. 25,000 apps.
Starting point is 00:59:45 It is really, really awesome. We're going to cross 100 K suit. I love it. I love it. Continued success. And if you have any great demos you want us to do here and give you a letter great and give you some candid feedback, just at Jason and at Sundip, SUNDEP, SUNDDEP, on X.com slash formerly known as Twitter. And, yeah, just reply to us. And we'll do it.
Starting point is 01:00:06 We'll see you all next time. Bye, bye.

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