Meta Replacing Creators? + Sam Altman’s Mistake & 3 Big AI Updates

Speaker A: Hey, welcome to the Next Wave podcast. I'm, uh, Matt Wolf. Um, I'm back once again with Joe Fear. And today we're going to get into some really cool stuff that came out from some of our favorite AI companies. OpenAI has a new visual explainer thing, and Claude has a new visual explainer thing, and Canva has a really cool tool that we've been playing around with a lot. We've got some weird stuff that came out of Facebook this week. We got some robots to talk about. Lots of fun stuff. What do you think, Joe? Should we dive into it?

Speaker B: We got a busy week. Let's do it. Because it's all visual. I feel like a ton of vis this week and we can all get our hands on it, like now. Well, after the podcast done, right?

Speaker A: Yeah, Wait till after the show. Come on, Joe, what are you trying to do to us?

Speaker B: Let's go.

Speaker A: Where are we starting?

Speaker B: Let's start with ChatGPT. I think it rolled out, like, I don't know, it was a day earlier than Claude's version. And, uh, essentially what we have here is ChatGPT. It's kind of limited, but now they're starting to show these visuals and like, animations within your actual chat.

Speaker A: Yeah, yeah. So what this is is basically a tool where you can ask it, like, math questions and it will create these, like, visual explainers of the math question. But you can see it actually has sliders that update in real time. So as I slide these things around, it actually updates the visual of this math problem. This is apparently the algorithm for a concave mirror.

Speaker B: Oh, that's what that is. Okay.

Speaker A: Yeah. But I actually don't know what the various symbols stand for because I are not smart when it comes to math. We got the Pythagorean theorem here. I do know this one. A squ plus B squared equals C squared. You use that to find the, you know, the long end of a triangle.

Speaker B: Yes.

Speaker A: Uh, but you can actually drag your A around and your B around and it shows you how it adjusts the C line on the triangle here.

Speaker B: I mean, it's a hell of a time to learn.

Speaker A: So here's the thing about this stuff though, is I saw this and I took it to mean you can go and prompt, like any sort of mathematical equation and it's going to give you a visualizer with a slider and actually do this kind of thing for you. But that's not quite how it works. There's actually, I think they said about 70 pre designed little like algorithms that you can play with. I think you just have to word it right to get it. So let me try a new chat here. Let's paste in the exact same prompt, show how compound interest grows over time and there it goes.

Speaker B: Interesting.

Speaker A: That's because these are all pre built. So in ChatGPT I can say did you custom code that visual or is that a pre built visual that's already ready? Based on my prompt you can see ChatGPT has a library of pre built interactive learning visuals. About 70 of them. Each one corresponds to a specific formula or concept. Compound interest, Ohm's law, Pythagorean theorem, exponential decay, etc. So when you asked about compound interest, I triggered the visual tied to this formula. These are like what they've got pre built in got uh, it like if you ask it to go code something it will custom code something. But these ones that have like the slider and load just really quickly in line with the rest of your chat, these ones are pre built. This is like the new feature they just added. Are these pre built visualizations? I feel like they kind of announced it as if like it was generating this stuff on the fly. But that's not what it's doing. It's just got a bunch of these pre built into it.

Speaker B: They look really cool, but they seem very sciency, very mathematical, very complex. Like I don't know what most these are. I've heard of them.

Speaker A: Some of them understanding the slope formula.

Speaker B: So it explains what it is. But can you follow up in the chat and have it like depending on what you do in the graphic or the animation, continue the chat based on what you did.

Speaker A: So when I tried that yesterday, it basically tried to code up a brand new version of this. Like it tried to write code that I would have to go and launch in a separate tab to actually get like any sort of tweaks to it. It's like you get what you get and don't cause a fit.

Speaker B: That's right.

Speaker A: Or V1 y' all saying all that two days later. Claude now creates interactive charts, diagrams and visualizations. Imagine that.

Speaker B: I love how they're always synced up with all these releases.

Speaker A: I mean what could have happened was like they'd been working on this behind the scenes at Claude, they saw that OpenAI released it and they're like oh, we built that too. Let's just release it and be like look, we got that also now I don't know if that's what's going on, but it's like why is it so coincidental that like almost identical features come out in the same week oftentimes.

Speaker B: Yeah, but this one, I mean my take on the Claude thing, because I was actually using CLAUDE a little bit more. They're different, you know, I think Claude. I don't know if they're Pre programmed like ChatGPT.

Speaker A: Claude is not Claude. It actually seems to build it for you, uh, when you prompt it.

Speaker B: Okay.

Speaker A: Their example here is like this interactive periodic table of the elements where they can like move their finger around and as they click on the different element, it shows the details down at the bottom of the element.

Speaker B: Mhm.

Speaker A: So that looks pretty cool. But yeah, we can go and test this. What do we want to have it do for us? Joe?

Speaker B: Compound interest. I know, works and is a good demo. Why don't we paste in the same exact prompt from ChatGPT and toss her in here.

Speaker A: Create an interactive demonstration of how compound interest works. This one I know you don't have to give it like exact specific, perfect prompts to get it to work.

Speaker B: My take is I kind of like the outputs over here a little more. Even though the animations are cool with ChatGPT, granted they are pre rendered. These ones I feel like are a little bit more interactive. They remind me of like some financial actual dashboard.

Speaker A: Yeah. I mean this one will mess up a little bit more too though, because it is trying to I think write some code behind the scenes. These aren't like pre cache like demos that are already baked in. So I have had some of my demos fail on me where it just like it didn't work the way it was supposed to.

Speaker B: But check that out. I mean that was fairly fast for that.

Speaker A: Yeah. I think this did a better job than the pre built one that OpenAI already has. Right. So you have your initial investment, you can see how it adjusts the graph. You've got your time horizon of.

Speaker B: Ooh, look at that, look at that money.

Speaker A: I don't know why that's so satisfying. Uh, but you got your time horizon here and then you've got your annual return that you can set and then you've got your monthly contribution.

Speaker C: Mhm.

Speaker A: This one's really fun because it makes a little wave.

Speaker B: I was doing the same thing yesterday.

Speaker D: Love it.

Speaker A: And apparently if you start with $3,000 and you invest $1,000 a month for 36 years, you'll be a millionaire in 36 years.

Speaker B: Look at all that interest gained.

Speaker A: Hey, if you take a look at my web presence online, it's safe to say that I'm A bit AI obsessed. I even have a podcast all about AI that you're watching right now. I've gone down multiple rabbit holes with AI and done countless hours of research on the newest AI tools every single week. Well, I've done it again and I just dropped my list of my favorite AI tools. I've done all the research on what's been working for me, my favorite use cases and more. So if you want to steal my favorite tools and use them for yourself now, you can. You can get it at the link in the description below. Now, uh, back to the show. Well, this is how we know they're not actually baked in.

Speaker B: How do we know?

Speaker A: Let's do one of make an interactive. Ready for this?

Speaker B: I am.

Speaker A: Padres schedule for the 2026 season.

Speaker B: Matt and Joe need to find some tickets to go.

Speaker A: I guarantee that this wouldn't be a pre baked in one.

Speaker B: You don't think they're secretly Padre fans over there at Anthropic?

Speaker A: All right, so it's finally building the interactive schedule for us after doing the research.

Speaker B: So it's not fast.

Speaker A: No, see the other ones are basically cached in there, right? Like they're already pre built. So when you ask it, it's like, oh, I've got this. Ready? Boom, here it is. This one. It's like, let me go build that for you.

Speaker B: See, that's chatgpt trying to look all really good and fast, but it is limited.

Speaker A: They're fooling you. They're fooling you.

Speaker B: It'd be cool if they had a little menu though, to kind of help you out. It's a little bit easier.

Speaker A: Yeah, they do make it kind of difficult to know exactly what formulas you can use. And it even said roughly 70. Yeah, like why don't you know the exact number? It's your data.

Speaker B: Your own pre rendered things. Come on. Yep. Woohoo.

Speaker A: Look at this. So it built out a whole schedule. Opening day, it says the time. And I think this is accurate too. We looked this up in a past one, so yeah, I mean it's got it. And look, it is actually interactive. I can click on them and open them.

Speaker B: Wait, so what's your take? Uh, because this isn't exactly what we showed with the whole like interactive.

Speaker A: No, no, this looks like it just coded up something for us.

Speaker B: Yeah, kind of took the liberties to just build something.

Speaker A: Yeah, it's not that same like visual explainer thing thing, but I made some other ones the other day. So I made this like AI create an interactive timeline of major AI model Releases. And you can see on this one, it actually built out the timeline right in line with everything and it even made it with like these filters. So like.

Speaker B: Mhm.

Speaker A: Let's say you want to know about just image models. I click that and it filtered it down to just milestones with images. I mean, it missed a lot, but you know, you get the idea.

Speaker B: Yeah, but what's the prompt structure? What's the thing?

Speaker A: For me, it's been asking it to build an interactive X. Right. Let's try one more. What was one of those other ones that we were looking at on the OpenAI one?

Speaker B: There's like surface area of a cone formula.

Speaker A: Okay. Create an interactive explanation of the surface area, uh, of a cone. Right. Does that sound like a good prompt? Yes, because we already know Opus and Claude are capable of going and writing code for us. Yeah, like I want to see it doing it in line with the chat.

Speaker B: Yeah.

Speaker A: All, uh, right, here's an interactive breakdown. Drag the sliders to change the cone dimensions. Watch everything update in real time.

Speaker B: Now we're talking.

Speaker A: So it looks like it's actually doing what we asked it to this time. Yep. We got sliders populating.

Speaker C: Ooh.

Speaker B: I don't know if this is possible, but perplexity tells me that, uh, maybe prompt things like draw something that you describe as a diagram so you can explore it visually. Or like make something in your chat visual essentially.

Speaker A: All right, we could try that next. All right, so we've got our interactive, uh, explanation of the surface of a cone. So you can change your radius. We can change the height of the cone.

Speaker B: Nice.

Speaker A: And it changes our surface area or lateral area. We could see everything updated in real time. How does this Compare to the ChatGPT version?

Speaker B: That one is, uh, it's very similar.

Speaker A: So here's what ChatGPT did for the same one. We have less slider options. Like we can change the height and we can change the cone radius at the bottom. I don't know. I don't know which one I think does it better. I feel like the Claude one is giving us more information right here.

Speaker C: Right.

Speaker A: Uh, and it also is a little more colorful, but it also seems like it's kind of cropping weirdly here.

Speaker D: Mhm.

Speaker B: It's cutting a little bit of it, uh, off.

Speaker A: This one looks a little bit just like cleaner, but it's also not giving us quite as much data.

Speaker B: Yeah, the other one seems like it explains it further. I guess it's really cool. Like now I'm starting to think, okay, you could visualize parts of your conversation. So depending on what you're working on, it seems like theoretically you could prompt. Now I want visuals to explain this.

Speaker A: I wonder if I could change the colors. Maybe, maybe, maybe. Hey, it did it.

Speaker D: Look at that.

Speaker B: Yeah.

Speaker A: So yeah, you can't actually go and tell it to like change what the visuals look like.

Speaker B: Interesting. I don't know, man. I'm thinking the clod's the way. You might have to wait a little longer, but you have all the flexibility.

Speaker A: Yeah.

Speaker B: All right, so I gave you a prompt in the chat, Matt.

Speaker C: Mhm.

Speaker B: Go to the Padre chat.

Speaker A: All right, so we're going to prompt it with draw this as a diagram so I can explore it visually.

Speaker B: I mean, that might not be the perfect prompt, but the idea is like start visualizing your chat.

Speaker A: All right, here's a visual calendar map of the entire season. Plotting 162 games on the calendar, flagging every Dodger series.

Speaker B: Did you prompt it to do that?

Speaker A: No. Painting Petco park brown and gold. It looks like it's doing it in line actually.

Speaker B: Yeah, buddy.

Speaker A: It's funny because it's like the little thing that it says it's doing is actually relevant to what it's doing. Painting Petco park brown and gold, plotting 162 games on the calendar, Flagging every Dodger series, starting over, warming up the schedule.

Speaker B: Great. I'm just trying to figure out if like there's a reusable formula here. So it says like a one line reusable formula, like a prompt structure could be like take what you just explained about topic and turn it into an interactive diagram or chart that I can do something directly here in the chat.

Speaker A: Mhm. Well, let's see what it does with this one.

Speaker B: Oh, whoa, whoa. Look at this.

Speaker A: This is what we were looking for and it actually did. Look at that. Uh, so if I click on this one, nothing actually happens. So the interactivity of it is a little wonky. Look at that. It actually put home away Dodgers and special date. Like it literally for some reason decided let's find all the Dodgers games.

Speaker B: Looking at your chat history, Matt, you must have had a lot of chats about Dodger games.

Speaker A: I mean, it's interactive in the sense that I can hover over it, but like clicking on it doesn't do anything.

Speaker B: But it tried.

Speaker A: Oh, you know what it is interactive. Look, if I click on one of these games, it changes it down here at the very bottom. But because it's such a long calendar, I have to scroll all the way down to the bottom to see like the details. So it is actually doing the interactive thing. It's just like uh, you have to scroll way down to see the interactivity of it.

Speaker B: I mean it is a long season. We did say that, you know, it

Speaker A: did exactly what we were expecting it to do the first time around for sure.

Speaker B: So Matt, like there's a little prompt it could be helpful to share. Here is um, it seems like there is kind of a flow that can be used to make these interactive charts. It might not be perfect all the time.

Speaker D: Mhm.

Speaker A: So here's the actual prompt tip. Take what you just explained about topic and turn it into an interactive diagram chart that I can click adjust, slash experiment with directly here in the chat. So this is one that specifically works like if you're starting from a topic. Let's see. Maybe we should get it to explain a topic and then test this prompt after it explained the topic.

Speaker B: That's a good idea. So we need to get it some text. So maybe give us the latest about what's happening right now in text, not visualize it first.

Speaker A: Break down the latest.

Speaker B: Uh, the latest between Anthropic and the Pentagon.

Speaker A: We're not going to go down a rabbit hole on this one today. We've gone down this rabbit hole in two previous episodes. But at least we'll get a little taste of what's going on secondhand.

Speaker B: There you go. Yeah, we don't need to go deeper but here we go. It's fast moving story. So great.

Speaker A: The ultimatum, the retaliation, the fallout, beyond the government, Anthropic's legal response, where it stands today. Blahbidi blah blah blah. The bigger picture story for you. Okay, now let's try our add on prompt. Take what you just explained about. I'll just put this topic and turn it into an interactive uh, diagram or chart.

Speaker B: Diagram.

Speaker A: Okay. Diagram that I can experiment with. Experiment with.

Speaker B: I don't know what we would experiment

Speaker A: with directly here in the chat. I don't know what kind of experiments we're going to do with this timeline

Speaker B: but we're learning in real time. But I think this is kind of cool. It's almost like back in the day. I mean every new thing that rolls out. And I'm maybe curious of your perspective here. Maybe uh, on like prompting structure changes, different outputs depending on whatever feature just rolled out and it's doing it. Look at that. But like what we're figuring out now is like what's the prompt structure that works with this specifically?

Speaker A: Yeah, well I think using the word interactive seems to be A key word, right? Like an interactive visual. Interactive graph, Interactive chart. Interactive seems to be one of the keys to toss into the prompt here. But this is a nice little prompt. Take what you just explained about this topic and turn it into an interactive diagram that I can experiment with directly here in the chat. It seems like almost any conversation you have, you can throw that prompt at the end of it and get something more interactive from the content that it just fed you.

Speaker B: Copy pasta screenshot, everyone. And then in the comments, let us know what you done diagrammed, what you

Speaker A: done did do with the diagram.

Speaker B: Yeah, we want to hear.

Speaker A: All right, so we got the timeline Claude used in Karakas Raid. Pentagon issues ultimatum. Anthropic refuses to budge. Trump bans anthropic supply chain, eraser label, PENTAGON MEMO Remove Claude in 180 days. Anthropic sues in two federal courts. Pentagon CTO, no chance of talks. So if I click on one of these. Ooh, look at that, dude. Clicking on one of them actually opens up like, uh, a little TLDR of each thing. And then if I click on Deep Dive, it actually prompts it to go further on that topic.

Speaker B: Heck, yeah. Look at that.

Speaker A: All right, uh, so this is the timeline, but we've also got key players. Uh, so Dario Amadai, Pete hedgeseth, Emil Michael, OpenAI Palantir, and Caitlin Kalinowski. She's the one that just quit from the robotics lab. And then we have what's at stake. And, um, then we've got more details. Anthropics annualized revenue, commercial customers paused or canceled. OpenAI Pentagon deal removal deadline. That.

Speaker B: I mean, dude, dude.

Speaker A: You toss that prompt at the end of any long discussion, and it's just like, here's an interactive tldr.

Speaker B: Did we just unlock the matrix? Was this AGI, Matt?

Speaker A: No, uh, no, I don't quite think this is AGI yet. But that is pretty cool that you can do that. It's almost the type of thing where if you have like a long chat with something like Claude, and at the end of it you're like, wow, that was in depth. There was a lot there. Throw this prompt in there, and it's almost like you can get like a quick interactive recap.

Speaker B: What's the three dots in the top right do when you click that copy?

Speaker A: Uh, to clipboard download file save as an artifact.

Speaker B: So that's cool. Like with what you just said is a recap of something that might be important or whatever topic.

Speaker A: Yeah, so it's an HTML file. So if I download the HTML Can I just like open this? So this is the HTML file.

Speaker B: Oh.

Speaker A: Uh, I mean, it didn't style it at all, but it's got all the

Speaker B: data in it and you can click and it has. Yeah. Okay.

Speaker A: It didn't come with any sort of like css, like styling, but it does the trick.

Speaker B: That's pretty cool. All right, there's use cases here, I'm m sure.

Speaker A: Yeah.

Speaker B: I like what you said though. It's like if you just copy and paste at that prompt m in the bottom of whatever conversation you're having that you feel like is important or you want to visualize, obviously you could change diagram, you could change out experiment. Seem like those words.

Speaker A: Yeah.

Speaker B: The thing you want to create and what you want to do with it are flexible.

Speaker A: Yeah. So like we can do the same thing and say, I wish I can fork it from right here, but it looks like I have to come all the way down here. Gemini lets you fork chats now.

Speaker B: Yeah, I like that.

Speaker A: I think ChatGPT now does too, doesn't it?

Speaker B: I don't know.

Speaker A: Yeah. Branch into new chat. So Anthropic's fallen behind on the ability to fork your chats.

Speaker C: Mhm.

Speaker A: But if I do that same prompt, take what you just explained about this topic and turn it into an inner active flowchart.

Speaker B: We like that.

Speaker A: That I can experiment with directly here in the chat. Sure. Let's hustle out a little flowchart here.

Speaker B: Let's do that hustling. I think that's good. I didn't know we'd go so deep on these.

Speaker A: I didn't either. But have we ever gone light on anything on this show?

Speaker B: No, I think the people like it. I think.

Speaker A: Well, when we do go too deep, the editors just edit it out.

Speaker B: So that's okay. Look at this.

Speaker A: Now we got a flowchart getting built, dude.

Speaker B: In real time. Look at that.

Speaker A: Let's say you were actually like making a video about this topic. You can actually record this like animating onto your screen and have like a very, very basic kind of like after effects looking animation.

Speaker B: True. Just slap on your loom and get going, you know?

Speaker A: Yep.

Speaker B: If you want to look impressive to your boss, to your clients.

Speaker A: That is sick.

Speaker B: Start using this prompt that we just came up with and do this.

Speaker A: And by we you mean Perplexity.

Speaker B: We modified it, but yes. Attribution, perplexity and Claude.

Speaker A: But I mean like the visual, like the flowchart. Anthropic, Palantir AWS classified network, mission critical deployments. The dispute. There's like this whole circular dispute thing, the replacement race. OpenAI Google Gemini Xai Grok Is Gemini

Speaker B: really in the talks?

Speaker A: I don't really know if they're in the talks. One thing about DeepMind is when Google bought DeepMind, part of the deal was that Google could never use it for military or for war or something like that. But like it was specifically written into the contract when Google purchased DeepMind.

Speaker B: Interesting.

Speaker A: Okay, so I don't know, a lot of these companies originally wrote that kind of stuff into their contracts and have slowly been shaving them out.

Speaker B: I was going to say, is anything really concrete? So they're clickbull.

Speaker A: All right, click on any node to expand it. So anthropic, um, Claude models. Okay, so it's kind of the same thing where if I click on one of these, it changes way down here. So you got to, got to scroll back and forth.

Speaker D: Mhm.

Speaker A: Oh, look at that. Even some of these are visual. Right. I clicked on Google Gemini readiness classified clearance negotiating model capability, strong alternative. So that kind of answers our question, right? They're negotiating the classified clearance right now. XAI Grok classified clearance deal signed model capability, unproven in defense. I mean, Elon literally just came out this week and said like, our models aren't good enough. We're starting over from scratch.

Speaker B: So is that really what he said?

Speaker A: Is that really what you want your military using? But the deal signed OpenAI classified, uh, clearance in progress, contract signed 200 million internal stability backlash and resignations. Uh, this is so sick, dude.

Speaker B: I mean, just think of getting knowledgeable on any topic, like rapid fire. You can just do this now. You get the visuals, you see the connections, you go deeper where you want.

Speaker A: Okay, So I have this little project I created called Richard Feynman and it basically explains anything like the famous physicist Richard Feynman would explain it, which is baking everything down to first principle knowledge.

Speaker B: Uh-huh.

Speaker A: Like explaining everything at its most simple rate. So one of the things I gave it is how computers work from circuit to code. You know, you've got like your circuit boards, your CPUs, your GPUs, they've got transistors. Transistors could be either on or off. Right. And basically when a, uh, CPU is doing something, it's just passing electricity, uh, through the transistors and it's sort of routing it based on which transistors are on and off. Right. Every transistor on a CPU could only be one of two states, one or zero. Well, the layer above that is called binary code ones and zeros. Right. So like binary code. If something is a one, it essentially would tell, like this transistor to be on. If it's a zero, it tells it to be off. And so the ones and the zeros are constantly changing to tell the transistors what to do. And then you have machine language and then assembly language and then programming languages and the operating system and then the applications that you actually use. And there's this whole sort of, like they call it layers of abstraction between you actually typing something in a computer and then the chips actually doing the processing. Right. And so I had it explain that whole concept to me like Richard Feynman, and I'm like, can it make a really cool visualizer of that for us right now?

Speaker B: Absolutely. Let's go.

Speaker A: All right. Take what you just explained about this topic and turn it into an interactive flowchart that I can experiment with directly here in the chat. That's another key word I think is directly here in the chat.

Speaker B: Yeah, yeah, Right.

Speaker A: So like interactive and directly here in the chat, we're telling it like, don't go write code and open it in the canvas on the side. Like, do it right here in the chat.

Speaker B: And that's probably good for everything because I was trying to code something just last night and they kept coding it in the middle and not giving me the canvas. So little things like that to say in the canvas in the chat.

Speaker A: Stacking transistors, wiring up, complexity, explosion. Teaching switches to think big.

Speaker B: Wow, that's cool.

Speaker A: Dude. I'm gonna be playing with this like crazy. The video that I made about this on my main channel, like, really downplayed it. It undersold it. I need to make a follow up and be like, dude, this is way more legit than what I showed off.

Speaker B: You're welcome. I just prompted you via perplexity.

Speaker A: Let me build this out, something you'd actually play with. I'm going to throw this prompt at the end of all of my little, like, Richard Feynman conversations.

Speaker B: I love that project that you have created.

Speaker A: Yeah, I had another one try to explain quantum computing to me and I read it all and I'm like, that still doesn't make sense to me. But maybe with a visual explainer it'll make more sense.

Speaker B: Wasn't it kind of interesting because everything starts with text and then it seemed to go audio, so, like, read it to me kind of thing. So you have your auditory listener, you have your visual reader, whatever that one is. But now you have this, like, the actual, like, you want to see pictures.

Speaker D: Hm.

Speaker B: You know, you learn from diagrams, which now it just rendered. So what do we got?

Speaker A: So we've got our transistors as the bottom layer. Logic gates and. Or not circuits, machine code, assembly language, programming, programming languages, operating systems, applications. And then even on top of applications, we now have AI. So we're not even necessarily going to be needing to use applications in the future. The AI is going to be using the applications for us and we're just going to speak to them. Right. So it's showing all these layers of abstraction and it looks like I can click through and, uh, each layer is doing something on the layer below it, right?

Speaker B: Yeah.

Speaker A: So when you're using AI, AI is talking to an application. When you're using applications, applications are communicating with the operating system. When you're using an operating system, the applications are using a programming language. Both operating system and applications are using programming languages. Then it's using assembly language, which is a little bit harder for humans to read, but it's still slightly human reasonable. Then you have machine language, which is like more like binary CPU instructions, like ones and zeros and stuff. People can't really understand that. Then you have the logic gates, the and. Or basically telling the transistors whether to be open, opened or closed, and that kind of stuff. And then you have the actual transistors, which are the little electrical circuits on a CPU board.

Speaker B: Dude, this is a really cool flowchart. I like this one even more.

Speaker A: So try skipping layers. I want to go from natural language directly to machine code. I don't know what it's showing me here. These modes for you to play with. Explore layers. Try skipping layers where AI reaches. Interesting. So like, it's actually interactive around, like. All right, I want to go from programming languages to transistors. I'm not quite sure what this is. Visualizing each skipped layer multiplies the decision space exponentially. All right, where AI reaches. So AI can reach the. Generating the applications a little bit. The operating system, it could do the programming language, like writing code. So this is actually saying like, AI is going further and further down the stack. Right? Like right now we're talking to AI, and AI can actually help manage our applications for us, and it can actually help write code for us. But it's not super great at managing the operating system yet. But we can see it's getting there. And it's not great at assembly, uh, language, machine code, logic gate or transistors. So it needs these other layers on top of it is what it's basically saying.

Speaker B: Now, is this the code to AGI?

Speaker A: Possibly.

Speaker B: And all the bars fill up.

Speaker A: I think you're convinced that we're going to discover AGI ourself on this podcast.

Speaker B: I've heard someone say it's 2026. Why not us, Mac?

Speaker A: I mean, if Nano Banana could inform us that the Pentagon banned anthropic, uh, then we can discover anything on this podcast.

Speaker B: I think it's possible. I'm not downplaying us anyway.

Speaker A: We're pretty deep down this rabbit hole. I'm excited about this stuff, as you can tell, but we should probably like move on to our second topic.

Speaker B: We were going to make this a shorter episode. Good, uh, luck.

Speaker A: How well do you know me by now, Joe? Have I ever made a short episode?

Speaker B: Too well, too well. Uh, second thing we're going to talk about is another visual thing we teased. I don't know, we'll keep this one quicker. 5 hours ago so Canva, you know, the thing that just basically took Photoshop and said, you're free now and it's easy. I don't know, I don't even use Photoshop anymore. I used to live and breathe Photoshop. I haven't had it at my computer for years. I don't know. Canva's pretty awesome and they just released this thing called Magic Layers and I think there's some cool use cases here. I think we're going to keep it pretty tight, but this seems like something like anybody could jump in because you're probably using Canva or you've heard of it, it's free. And I think this is available to everyone, if I'm not mistaken.

Speaker A: Yeah, let's see here. So Canva introduces Magic Layers, new breakthrough of AI development, blah, blah, blah. It converts flat images and static AI outputs into fully editable, multi layered designs inside the Canva editor. So like, you know, obviously you know Photoshop, right? Well, one of the beauties of Photoshop is you've got all of these layers. You can have your background layer, you can have like a mid ground layer with, you know, some trees or elements in the scene. And then you've got your foreground layer which is maybe like where the person or the main object is. And you can have these multiple layers on your Photoshop. One sort of negative thing about using AI image generation is you get what you get, right? Like it generates the image. This is what it is. Now you can do some things like inpainting where you can, you know, sort of shade part of the image and say edit just this and There is some of that kind of technology, but it's, like, still like a reroll kind of thing. Like, all right, let's try again. Let's try again. Let's try again until it looks like what you want. Well, this actually will take any image that you generate with AI. I mean, any image could be just image you took with a camera as well. Um, and it will actually break out the elements in that image into separate layers, and then you can drag them around and move them and change, you know, which layers on top of the other layers and stuff like that. It's really crazy.

Speaker B: I had a lot of fun just messing around with this thing. Yeah. It's rolling out public beta across us, Canada, uk, Australia.

Speaker A: Yeah. Does it actually say for all plans? Doesn't specifically say, but I. I think it is just available if you have an account. Anyway, let's try it.

Speaker B: So, like, why don't we take one of your thumbnails from YouTube and slap it in here?

Speaker A: This is not all necessarily AI. This was actually a real photo of me that I think was touched up a little. With AI My skin's not that shiny.

Speaker B: Look at that smile.

Speaker A: But I can go to edit here. There's a new Magic Layers button over here, and if I click that, it will scan the image and ideally it will break out everything from this. What I don't know if it's going to do. Is it going to fill in, like, the rest of the letters here? Like, is it going to know that's supposed to be an E?

Speaker B: We'll see. I have not tested this, but I think use case for thumbnails are really cool. I mean, for one, you can just pull from anything you have maybe used other people, so.

Speaker A: Look at this. It broke everything out. Messed up some of these logos here. Actually, I don't know why it did that, but it's actually not bad. It just sort of duplicated some of the words.

Speaker B: Oh, there you go. Okay.

Speaker A: All right. So, like, I just. I could remove this background now.

Speaker B: Yeah.

Speaker A: Or I can go and, you know, set it as the full screen background. Here's my face. I can move this however I want. I could be over on the side here instead.

Speaker B: Right.

Speaker A: But I can make myself big and off to the side. And I can move these logos around and, you know, put them stacked like this.

Speaker B: Dude, look at the text that was behind your head. It got filled in. Oh, yeah.

Speaker A: I did figure out that I said AI News behind my head. That's sweet.

Speaker B: There we go.

Speaker A: It broke out all of these logos separately. All right, so now I can recompose a whole new thumbnail that's kind of the same idea and then make a brand new version of this thumbnail that looks way worse than the original one.

Speaker B: AB testing though. I mean, like, it's an easy way to at least grab something. I don't know. Like I'm just thinking like, you know, what was it? Great artists steal. Is that one of the sayings?

Speaker A: I'm sure some people say that. Not me. I never steal.

Speaker B: You never steal? No. You're a saint.

Speaker A: There you go. I have a whole brand new.

Speaker B: I like it.

Speaker A: Honestly, it's not that bad of a thumbnail.

Speaker B: That's a pretty solid a B test or even go to market thumbnail didn't take much.

Speaker A: It did not take much at all. So that is sweet.

Speaker B: I like it. And again, like, I don't know. This is why I don't download Photoshop anymore.

Speaker A: Sorry, Photoshop.

Speaker B: You're watching.

Speaker A: This is probably a good time to mention I do own equity in Canva. Probably should have said that. I don't know if I legally have to, but it seems like the right thing to do.

Speaker B: That's good.

Speaker D: But.

Speaker B: All right. So another use case I think could be really cool. Do you have a nano banana or Gemini generated infographic?

Speaker A: I don't, but we can done go create one.

Speaker B: Let's make one about maybe one of the topics we've talked about earlier.

Speaker A: Let's go ahead and go to Gemini. We'll just create an infographic here because we know this is the best at infographics. Create an infographic that explains layers of abstraction for a desktop computer. Do a little callback.

Speaker B: There it is. Layers of abstraction. I learned something new today.

Speaker A: Thank you. I would hope so. My goal is to teach you something new every time we do one of these. Teach me.

Speaker B: There it is. Oh, uh, check that beautiful infographic. That is quite cool.

Speaker A: Yeah.

Speaker B: So you're downloading it.

Speaker A: Food pyramid, but for computers.

Speaker B: So we're gonna take this file we're downloading, which normally you would not be able to edit. You can, I guess. But you'd have to do it through text in Gemini.

Speaker A: Mhm.

Speaker B: But it's not always perfect either. But now you're gonna slap that thing into Canva and run the magic of the layers on it.

Speaker A: Yeah. So here it is in Canva. Uh, there's a lot going on, so it'll be interesting to see how well it does this.

Speaker B: I was doing this test last night and I'm like, I wanna talk about this. So Ideally it should have all the icons broken out, the different layers. And then you can also edit all the text you see on here, which can be a common issue when you're generating a fricking, you know, infographic that has a lot of stuff.

Speaker A: I mean sometimes it even like gets typos and stuff too. Um, I mean it seems to have gotten a lot better lately about not doing typos. But they do happen still sometimes.

Speaker C: Mhm.

Speaker A: So there we go. So every single thing looks like it almost kind of groups some of um, them. But that's not bad.

Speaker B: You could work with that.

Speaker A: But yeah, all of this text is actually editable now.

Speaker B: Yeah, there we go. So like again, you could probably edit some of the text in Gemini, but you'd have to like keep prompting it back and forth, forth. You don't have full flexibility if you wanted to like bold something or move it around.

Speaker A: You can even edit this text that's sideways here. But yeah, I mean like literally everything here is broken out. Like each level of the pyramid, the background colors are broken out into their own little thing.

Speaker B: It looks good. I think it might have changed it a little bit because like part of that pyramid is kind of missing down there. Right. The orange.

Speaker A: Yeah, it did actually remove some stuff.

Speaker B: There you go.

Speaker A: Yeah, so it is missing some stuff. But I mean you still have like the bones of a really solid infographic.

Speaker B: Yeah. Something to play with. I know it's trying it with like as a solid background, maybe simpler isolated things like text icon.

Speaker A: Yeah. This background here it seems to struggle

Speaker B: with which I guess you could just prompt in Gemini to simplify the look of it a little bit. Or maybe remove the background.

Speaker A: Yeah, yeah, still pretty cool.

Speaker B: I like it.

Speaker A: Uh, the other thing that you can do is you can actually bring like real live images in just to list

Speaker B: out some use cases that could be helpful. So like infographics, different promo graphics that might be legacy or like old school and they just don't have the layers to anymore.

Speaker A: Mhm.

Speaker B: This could make them now something you could do. Or like JPEGs, it's just like flat styles.

Speaker A: Infographics, YouTube, thumbnails, Facebook ads, Google Ads, display network ads.

Speaker B: Creating uh, explainer videos. If you wanted to do it that way, if you were really good at storytelling. I bet that is a very low budget slash, no budget YouTube video that someone would, A lot of people would watch. Someone please do this. Please do it.

Speaker A: I'm going to tell a story this way. I will make a video like this on my channel.

Speaker B: At one point there we go. So next topic at hand here, we're going to bring in a couple of, um, intelligent folks, Sam Altman and Jensen Wong. So these guys are saying different things, but I feel like in a similar way, where intelligence is kind of a commodity of sorts, uh, it's a utility in the way that Sam is talking about it here. There was something that he said on stage. We can just play the video. And I think it's interesting. It's a talking point. Let's, let's play this.

Speaker D: Fundamentally, our business, and I think the business of every other model provider is going to look like selling tokens. They may come from bigger or smaller models, which makes them more or less expensive. They may use more or less reasoning, which also makes them more or less expensive. They may be running all the time in the background, trying to help you out. Uh, they may run only when you need them. If you want to pay less. They may work super hard, spend tens of millions, hundreds of millions of someday billions of dollars on a single problem that's really valuable. But we see a future where intelligence is a utility like electricity or water, and people buy it from us, um, on a meter and use it for whatever they want to use it for. The demand that we see for that seems like it's going to continue to just go like this. And if we don't have enough, we either can't sell it or the price gets really high and it kind of goes to rich people or society makes a bunch of sort of central planning decisions that I think almost always go badly about. You know, we're going to use our limited compute supply for this and not that. So the best thing to me, throughout all the history of capitalism, innovation, whatever you want, is to just flood the market. Yeah.

Speaker B: Interesting, huh?

Speaker A: It is interesting. You know, I have a few things about that. The way he described it as like, we sell tokens on a meter. They're doing that. That's what an API is like. That's literally what an API is. Right?

Speaker B: It's already happened.

Speaker A: Yeah, that's already how they're doing it. I, Most people see OpenAI as chatgpt, right? I pay 20 bucks a month and I get access to AI whenever I want it. And, uh, that's how I think, like most people are currently using it. The way he's sort of explaining it is it almost sounds like in the future he sees a world where you're not just paying 20 bucks a month and getting access to as much AI as you want. Like you kind of are. Now he sees it as like everybody's going to be using the sort of API model where when you want to use AI, you're on the meter, it's going to start cranking up that meter and you're going to start spending per token. Like those of us who do development, right? Those of us who use things like Claude Code and cursor and OpenAI's codex and stuff, we're already used to just being on a meter, right? We're used to going and having it write scripts for us and then going and checking our API dashboard and go, oh, crap, how much should we spend today?

Speaker B: Right?

Speaker A: Like, that's already the reality to developers who are using AI. Where it gets really interesting is when that reality, that sort of way of charging people transitions into like the normal users of AI, right? He's saying this is going to be like a utility, like the way you pay your electric bill, your water bill, your gas bill, that kind of stuff. Well, you're going to have an intelligence bill where you just use as much intelligence as you need and we bill you at the end of m the month for the amount that you used. I think that's kind of a scary reality for a lot of people. But I also think it's not the smartest approach to claim that that's what you're going to do, because if everybody believes that's what you're going to do, you're just going to incentivize everybody to go, okay, well, how do I not use a cloud provider to get my AI, right? Like, we've got things like the DGX Spark, we've got Mac studios that have insane memory on them that could run models locally at home. So if we've got companies out there like OpenAI saying we're going to put you all on a meter and we're going to make it. So, like, when you want to use our intelligence, it's just going to. You're just going to rack up the meter. Well, that just makes me think, okay, I'm going to just my own on device AI and hopefully that gets better and better and better. So I don't need to tap into your meter. Like the analogy that I used when I shared this post on Facebook is like, if you look at OpenAI, like the next electric company, well, getting your own on device AI is like going and buying solar panels. So you're not relying on the electric company anymore, right? Except the big difference is when it comes to electric companies, most of us are in like monopolistic societies where we don't have a choice of our electric company. And even if we have solar panels, like, the electric company could still jack up our price and jack up our usage to the point where we're using more than our solar panels generate in AI. If I have on prem compute, where I can just run my AI models whenever I want, I could just cut them out completely.

Speaker B: So basically, on prem is the equivalent to, uh, off grid, essentially, like, for electricity. Like, if we're kind of comparing it like that.

Speaker A: Yeah, exactly, exactly. It would be like, okay, I don't need to tap into your meter anymore. I'm just going to put my own box in my corner and I just pay for the electricity to run that box, and that's it. I mean, I'm on a meter. I'm just not on your meter. I'm on the electrical meter instead.

Speaker B: Bingo. Yeah, I mean, like, like you said, it's already happening, but there are so many different choices. Like, I forget the app that came out last week, but you can run it just on your iPhone.

Speaker A: Yeah, yeah. Locally is what it's called.

Speaker B: Locally, yes.

Speaker A: Yeah, yeah, yeah. You could do that. Like, I've got a flight day after tomorrow. On Sunday, I'm going up to the GTC event, and I'll probably be sitting there on my phone having chats with AI up, um, 30,000ft in the sky, because I could do that now, not even need Internet. So I understand what Sam's saying. Right. Like, I think this model of you pay 20 bucks a month and you can use as much AI as you want. At the moment, it's sort of unsustainable because OpenAI loses money every single month, as we know. But at the same time, the cost of compute is going to come down over time. Uh, these models are going to get more efficient over time. And so theoretically, you're onboarding a whole bunch of people at a loss right now. But in the future, um, with economies of scale and with cost of compute coming down and with Moore's law, meaning, you know, that we can fit more transistors into the computer, whatever. I think I'm, um, like, really oversimplifying this stuff. But with all of that being said, the cost to use compute is going to come down over time, theoretically. And I don't understand why people would want to send stuff to a cloud if eventually we get to a point where the models we run on our own devices are just as good. And with Sam going out there and saying stuff like what he just said in that clip, that makes me think More and more people are just going to open their eyes to like, if I can do this at home, why wouldn't I?

Speaker B: Bingo. That was my takeaway is like, okay, well, he put out there where he sees the future going for OpenAI, uh, maybe anthropic or, you know, Gemini as well. But at the same time, I think it's an education phase for a lot of people to understand. Oh, these are things that he basically wants to have you rent from him or send him money based on a meter, you know, and it's going to tap into all the tools or devices that you might use throughout your life, no matter where you're at, you know, that meter is somehow ticking in the background.

Speaker A: Yeah, yeah. And I think he's operating on this assumption that OpenAI will always, always be at the very frontier. They're always going to be the most state of the art. They're always going to have the best, most intelligent, smartest models out there. They're going to have AGI eventually. Right. Like, I think he's operating on this assumption that, you know, you can run AI at home, but we're always going to have the best AI. And if you want to tap into the best, smartest, the front of the line, like Edge of AI stuff, you're going to need to use companies like us. But part of the problem with that is they're not a monopoly. We have Google, right? Google's giving out AI for free right now because they can subsidize it with their ad business. You have Anthropic, which last week we talked about how Anthropic is actually taking over the business market right now and selling more to businesses lately than even OpenAI is. Right. Um, developers are already all using Anthropic over OpenAI mostly. Maybe eventually GROK is going to come along and get their act together and catch up with them. You know, I wouldn't put it past Elon to make that happen. He could send people into space. I'm sure he can figure this out too, at some point. Right? You have Meta, who went and spent billions of dollars putting together their super intelligence team. So it's not like OpenAI is our only option. We're in a capitalistic society where if there's other options, it's going to continually drive prices down. And companies like Meta are actively trying to create state of the art frontier models that are as good as OpenAI's models. And if they manage to achieve that, theoretically, we can just run them at home on our own boxes without needing a company like OpenAI.

Speaker B: Bingo. Yeah. I feel like business, uh, wise, it doesn't seem like the smartest thing to hinge everything on, you know, for Sam and OpenAI, knowing of exactly the landscape you just described and what's possible now with all the, the models that you just run locally.

Speaker A: So, yeah, it may be how it actually plays out. I just don't think it's the smartest move to be going and selling that narrative yet.

Speaker B: Yeah, yeah.

Speaker A: From a marketing standpoint, I don't think it's the best optics. Like, I don't think it's the, the way you should be presenting what you're selling.

Speaker B: Yeah. On that front, like. So I want to turn it over to Jensen Huang from Nvidia, because they're saying different things, but there is a similarity in the whole thing of intelligence being this kind of commodity or this utility that everybody has access to. So let's, let's listen to this.

Speaker A: Who's the smartest person you've ever met?

Speaker C: Who's the smartest person I've ever met? I can't answer that question. And I know, I know what people are thinking. The definition of smart is somebody who's intelligent, solve problems, technical. But I find that that's a commodity. And we're not. We're about to prove that artificial intelligence is able to handle that part easiest. Right. Yeah. And so, so as it turns out, um, let me give you another example. Uh, everybody thought software programming is the ultimate smart profession. Look, what is the first thing that AI is? Solving software programming. And so it turns out that the definition of smart is very different than most people think. Uh, I think long term the definition of smart, and my, my personal definition of smart is, is um, someone who sits at that intersection of, of being, um, technically astute, but um, but human empathy and having the ability to infer the unspoken around the corners, the unknowables. You know, people who are able to see around corners are, are truly, truly smart. And um, their value is incredible. To be able to preempt, um, uh, preempt problems before they show up just because you feel the vibe. And, and the vibe came from a combination of, uh, data analysis, first principle, life experience, wisdom, um, sensing other people. That vibe that I think that's smart, that I think is going to be the future definition of smart. And that person might actually score horribly on the sat.

Speaker A: I like, uh, Jensen's framing a lot better than Sam's.

Speaker B: Oh yeah, me too.

Speaker A: For sure.

Speaker B: A couple takeaways. I'm just going to say here is from my side. Because when I watched that, you reposted this. Yeah, the other day, I, uh, was like, interesting. Yeah. Different, similar things. They're saying uberall being that like this commodity, intelligent AI essentially is the smartest thing around. But like, what we've said a lot on previous episodes now is that, uh, it's the human taste or like what he accurately described as the vibe. I like how he said that, but he said basically it's like, yeah, that's knowing the data, the analysis, first principles. We talked about that earlier too. But life experience, empathy, it's like the unknowables, the, the unspoken things that us humans kind of, uh, I don't know, it's like what we do on this podcast, I feel like.

Speaker A: Yeah, I mean, I feel like everything he just said I think boils down to like, IQ is less important. What's important in the future is EQ and intuition. I think basically if you boil everything that he just said down into like two words, it's EQ and intuition. That's good, right? Like IQ is no longer going to be the metric that people see as smart because, um, knowledge work is the first thing that is essentially getting like their moat is getting filled in with dirt by AI, right? Like coding work is getting filled in with AI. You and I have had conversations off recording about how the stuff that I make on YouTube, tutorial type content, breaking down the news, stuff like that, that's way less valuable in a world where people can just get that from AI real quick. Right? Uh, like knowledge work, coding, even stuff like lawyers. Like I don't think lawyers are going away, but I think people like paralegals might be in trouble. The ones that actually go and do the research and do the fact finding and sort of try to connect all the dots, right? Like, I still think they'll be like lawyers in court, pleading their cases to judges and stuff. But the sort of downstream work from lawyers kind of goes away when it comes to like doctors and the medical industry. I still think people are going to want opinions from actual human doctors. But a lot of the downstream work from doctors, a lot of the research, the helping with diagnosis, right, the taking uh, uh, an X ray or taking an MRI and looking at it and going, what, what does this all mean? Well, technology is probably going to get better than most doctors at analyzing that stuff and finding little like nuanced things in that scan that maybe the human eye can't even see, right? So I think a lot of the, like, the knowledge type work, the IQ Type work. I don't want to say it's a commodity because there's not a lot of people on this planet that have like extremely high IQs. But I think it's a lot less valuable in the future to have extremely high cues. What's valuable in the future is knowing how to interact with other human beings, like having that eq, knowing how to like make friends and persuade and you know, get what you want out of life, essentially that EQ thing. And then also that intuition of like, I can kind of feel this thing bubbling up. I would say back in 2021 when we were talking about AI and how AI was starting to get used for copywriting and marketing and we were talking about how in the future, like sales pages and advertising are probably going to be run by AI, you and I were literally on podcast talking about that in 2021. That is intuition, right? Uh, what did I do with that information? I went and created a whole fricking career out of that intuition that this is going to be the next thing. I really think that like, if you boil that whole two minute like little thing down from him, it's IQ is less and less important in the future. EQ and intuition are, uh, what you should be really concerned with because if you can see where the puck is going, so to speak, and you can skate there before everybody else, you're going to be the one that wins.

Speaker B: Be like Neo from the Matrix. I know kung fu, but you've just tapped in. You, we're all tapped into AI and intelligence. We have access to, but. And I don't know if Neo is the best on the personality side or human warmth, but maybe intuition. But yeah, like that's our superpower. And you're right, like we were talking about this years ago and yeah, you went more YouTube, I went more working with business owners and all that stuff and education, like that's what I feel like what we're doing as well here you've done through YouTube and content and I've worked with a lot of the people doing that kind of thing. And it's, it's pretty interesting when people understand that you, we all have access to the same information now. It's basically free for everybody in some form. It's just how do we apply it throughout the humanness?

Speaker A: So yeah, I also think like, just from like a wealth building standpoint, right? From the standpoint of your ability to generate income for yourself. I know a lot of really, really, really insanely smart people that maybe don't have the highest Income. I mean, when you think of like really intelligent people, you might think of like teachers, like. Right. Teachers are, you know, pretty stereotypically underpaid. Right. Um, you know, scientists, a lot of scientists that they rely on funding from like government grants and stuff like that. A lot of scientists don't make a lot of money. Like they have to rely on people giving them money for them to continue their research. And then you look at the people that actually have some of the most wealth. Right? Who do you think of? You think of like investors, you think of like the Warren Buffetts of the world. You think of, you know, Bill Gates, Jeff Bezos, Elon Musk. A lot of these people, I mean, some of them probably have really high IQs as well. But the thing that made them the money, Jensen Huang included, the thing that made them the money was the intuition, not the iq. Jensen Huang had the intuition that in the early days, gaming was going to be the next big thing. Let's build the dominant software for that. And then a little bit later down the Rhine, AI is going to be the next big thing. Let's build the dominant hardware for that. I think I said software first, but hardware. Let's build the dominant hardware across the stack for all of this kind of stuff. He had that intuition that this is what's coming down the pipeline. Let's build for that. You look at, you know, Sequoia Capital, A16Z, um, sound ventures, like all of these companies that invested in AI before the sort of like trajectory blew up and it was all mainstream, they all had intuition of like, this is what's coming around the corner. Let's get on board with that, right? When you think of like the multi deca millionaires and billionaires and people like that, they made their money because of intuition, not because of iq.

Speaker B: I'll add in, um, that. Absolutely. And I feel like there's a time horizon too. So like Jensen Huang, I looked it up, I knew it was over 30 years, but yeah, 33 years as the Nvidia CEO. So you got to think about. His intuition was like, wasn't perfect from day one. But I think you follow the course with your intuition, with the knowledge that you have and your experience and all that stuff combined. And like, look at Elon, look at all the other ones out there that have been kind of navigating for a long time. So this time horizon is where it starts to develop and create something bigger. And I feel like right now we're in this like, pivotal moment with AI being so it's New, but developing really quickly, that we all have the ability to learn quick right now. So keep watching. Go watch Matt's YouTube and follow us everywhere. But at the same time, go apply it and, you know, start to tap into the intelligence, but also understand what is your human intuition.

Speaker A: Yeah, well, and I think the people that are best at it, too, are the people who don't necessarily look at what people say they want. Right. Like Henry Ford. Right? Like, doesn't he. I don't know the exact quote, but he has some sort of famous quote where he's like, if I gave everybody what they want, I would have made faster horses. Or something like that. Right. You look at Steve Jobs, right? Nobody was asking for, like, a new smartphone, right. Everybody thought the BlackBerry was like the ultimate smartphone. What do we need something else? Like, these people figured out what people are going to want in the future before they knew they wanted it. Right? Um, so to me, that's kind of what Jensen saying. Like, the intuition, the, like, knowing what's coming and trying to get ahead of that is the thing that's going to be most valuable in the future. And the people that we're going to look back at and go, holy crap, they were some of the smartest people, were the ones that predicted the future better than anybody else.

Speaker B: There you go. That's it. All right. So that's, uh, I feel like our take of the everyday AI, or like, whatever that section we want to call it, kind of working in themes in this podcast, trying to work it out. Let's transition, uh, to a new topic, which is more of the more weirder stories of the week, I guess we'll call it, is, um, Meta. We talked about Meta already and how they acquired multiple, which is kind of freaky if you think about it, but Multipook being this social media network of AI agents. So not people. It's automated agents autonomously talking and having a life there. A life quote. And the fact now is that Meta hired, well, I guess the duo, the founders behind Multbook. Did they actually acquire Multbook as well?

Speaker A: I believe so, yeah. Meta has acquired Molt Book, a viral social media network designed for AI agents. Um, Matt Schlitt and Ben Par, which I know both of them, they're cool dudes, but, uh, yeah. So Molt Book, just to kind of add some additional context. Back when openclaw got really, really popular, uh, openclaw being like the AI agent that everybody was buying Mac Minis for and, like, running locally on their computer. So it was originally called Claudebot Anthropic said, you can't call it that. It sounds too much like Claude. Then they rebranded to Moltbot. They were only called Moltbot for like two days or something like that, right? Like, it was a very short window of time, like 36, 48 hours. They were called Boltbot and Multbook spawned up in that like 24, 48 hour window where they were called Mult Bot. They obviously thought, okay, well, let's make our AI agent for these, these Mult bots, right? So they spun it up during that window that it was called Moltbot. And then it got rebranded to OpenClaw and they were like, well, we're already called Molt Book, we're keeping it. So that's kind of how Molt Book got its name. But moltbook is like essentially Reddit for AI agents. So AI agents can go and post like deep thoughts from the AI agent on this thing and then other agents could go and reply and comment underneath it. And there was all this like crazy controversy because it was very unsecure. A whole bunch of people's like, passwords and APIs got leaked from it. A whole bunch of crypto scams popped up on it. Like people were actually using the API and pretending to be bots, but they were, you know, typing the stuff themselves and making it look like a bot post hosted it through connecting via, uh, APIs and stuff like that. And it was just kind of like this giant mess. But it got really, really popular really quick. Over 2 million agents signed up for it within like a week. And even Andrej Karpathy, who's like a really big thought leader in the AI space, he actually helped invent a lot of Tesla's autonomous driving technology and then moved to OpenAI and was one of the, like, head engineers over at OpenAI, just like a prolific, um, you know, engineer in the space. Um, he actually commented about how like, this is like this crazy huge sci fi moment that we're living in that AI agents have their own social media that are going and talking to each other. And there was like this moment where Malt Book was just like everywhere. Everybody was talking about it and it kind of got crazy, but then it sort of died off for like, I don't know, a few weeks and nobody was really talking about it anymore. I kind of assumed like, uh, that site's dead, nobody's really doing it. And then out of nowhere, Meta acquires it and I see this news and I'm like, what? Like, people are even still talking about this thing. Like what? What the hell?

Speaker B: They angled it perfectly, Matt. They had the uh, molt. But obviously they got the attention of the open claw people and they had to put book on there. It's very strategic. It's genius. And you got Facebook Meta looking at it? Um, I don't know. Did they disclose how much?

Speaker A: No, it hasn't been disclosed how much, um, they got bought for. The other interesting thing about this is the guys that made it flat out said we Vibe coded this. Like we didn't write a single line of code on this thing.

Speaker B: Right.

Speaker A: So Meta went and acquired a Vibe coded company. But not only that, brought in the founders who are Vibe coders. Not necessarily. Like, you know, they're not like Alexander Wang, like billionaire guys who started scale AI. They're like dudes like us who used cursor or Claude code or something. And Vibe coded an app, put it online and uh, just went viral. And now all of a sudden Meta's acquiring them.

Speaker B: Dude, yeah. I'm looking at the background of both these guys. So Matt Schlilt is a serial entrepreneur and product builder focused on chatbots, social and commerce. So, um, yeah, more like commerce. And the other one, uh, Ben Par, media guy, investor, obsessed with the science of capturing attention. Mhm.

Speaker A: They're like marketing dudes.

Speaker B: Marketing guys. Well, and that's, I mean, that's kind of where my mind was going. I'm like, okay, well they got the attention, they almost news jacked and they Vibe coded at the perfect time to capture a bunch of people who were just then getting into AI agents and setting up whatever they were called at that second, because it literally was second. But openclaw, we'll just say, and you know, got a bunch of traction. How many people? You said 2 million signups, like, yeah,

Speaker A: uh, yeah, but they're agents, right? So like.

Speaker B: Well, yeah, it could have been like

Speaker A: one person had a hundred agents all signed too, you know, like it, it's hard. Like, I wouldn't say 2 million people's agents signed up because individuals could have had bulk agents signing up as well.

Speaker B: For sure.

Speaker A: Yeah.

Speaker B: But it's so interesting because so they capitalized on that timing, it seems like. I mean, I don't know the intention of why they made it, but sure as heck got a lot of people to get in there. I know a lot of humans were lurking and watching what the AI agents were saying, and who knows how they were being prompted if that was the case or whatever, who knows? But I don't know, I start to think of like, okay, so when Meta rolls this out, what does that mean? That, um, now every business or person, if you want, is going to have an agent that can now be your representative on Meta's platforms potentially. I'm not saying it's a good thing or bad thing, I don't know. But, you know, like, now they can represent you, your brand, potentially.

Speaker A: To me, that's not really what Molt Book would do for Meta, because Meta already acquired Manus, right? And Manus is almost like an open claw competitor. It's a, it's an autonomous agent where you can, you, you give it a goal and it will go and create a task list and then one by one work through the tasks until the goal is met. They already acquired an agent company. They already acquired their version of an Open Claw, their version of a Perplexity computer. That's Mannus. So that's one thing that makes the Molt Book acquisition even slightly stranger. Um, I mean, I could put on my tinfoil hat and share a few reasons, uh, I think, uh, throw it

Speaker B: on for, throw it on for a few minutes. I know the people, like, I'm one of the people.

Speaker A: So I've talked about this in the past. I don't know if I've talked about it with you on the show, but I'm pretty sure you and I have talked about this offline before in that I think Meta, uh, wants to eventually cut the creators out of the loop. So right now, these platforms, they need to attract viewers. To attract viewers, they need to attract creators, they need to attract people to actually post on these platforms. Because if nobody's posting on these platforms, then why is anybody going and reading them and seeing the ads? And Facebook makes their money, right? So they, they need to attract creators. And then having good creators then attracts eyeballs which they can then put ads in front of. Well, I think Meta's long term strategy is if we can create a platform that autonomously posts stuff to it that people are interested in, we can cut creators out of the loop. We don't have to require creators to come and want to create on this platform. We'll have agents create on this platform, we'll have AI models create on this platform. They already rolled out and launched a product called like Meta Vibes or something like that, which is like a TikTok type thing that you scroll through. But 100% of the content is AI generated. There's no human generated content on it. It's purely AI slop. They literally made like a TikTok of AI slop called Meta Vibes.

Speaker B: That's great for the brain, right? That's great for the brain.

Speaker A: Yeah, that's gotta be amazing for the brain. Um, but so they've already done that, right? So they've got a platform where you can go and just like mindlessly scroll through AI generated stuff, right? And so, uh, the Mult Book shows that people that are creating these AI agents, they can have their agents go and post autonomously and actually create content that is fairly interesting. I mean, a lot of the content that was created on Molt Book was getting shared around. People are going, look at what this agent wrote. Isn't this crazy? Isn't this scary to think that an AI is thinking this way? That's wild, right? Well, that's content that if meta can get that kind of content posting on their site, that keeps eyeballs on their site and allows meta to put ads in front of those specific eyeballs. Right? So I think that Meta, over time is trying to figure out how to cut creators out of the loop and just have a platform where the content that goes on the platform is created autonomously, but it still attracts eyeballs. So they don't have to pay creators, they don't have to attract creators. They just need to get eyeballs looking at their slop and they can put ads in front of it. That's one theory. I have enough.

Speaker B: It's like the infinite slop machine that freaks me out, dude. All right, number two, what do you got? What do you got?

Speaker A: So the other thing is, as more and more people start using agents, as people start using Manus, as people start using Open Claw and Perplexity Computer and things like that, and they start to get comfortable with it going off and doing things autonomously for them. Well, eventually it's going to get to a point where they're going to start to feel more comfortable with it actually spending money on their behalf, right? Like, we've already seen things that are like bots of like, here, help me go book my dream vacation or whatever. And it goes and finds the flights and finds the hotels and finds the things to do while you're on vacation. And maybe it gets you all the way there other than getting past the checkout and actually spending money, it's only a matter of time. Like, in the early days of the Internet, nobody wanted to put their credit card details online. Now we have our credit card details just like saved on everybody's website so we can one click buy shit, right? So, like, I think it's only a matter of Time before people get more and more and more comfortable letting their agents go and buy stuff on their behalf, right? I bust out my phone and go, you know, hey, I need a new mouse. My mouse just broke. And it's like, okay, I'll do the shopping. I will see what got, what has the best reviews. And knowing the type of work you do, I'll figure out the best mouse for you. Can I go and purchase it for you? And you know, you give it some constraints, what you need to do. So you talk into your phone just like you would, uh, your little phone assistant, right? Barry, let's call her. Uh, Barry, spelled B I R. I. Uh, you tell Barry, go buy me that mouse. And then the next day, the mouse just shows up at your door and, you know, it did the research for you. You know, it, uh, checked all the reviews. You know that because it's your agent, it knows about your business. It, it knows what you use your computer for. It knows what the best mouse for your use cases are. Right? So eventually these agents will spend money on our behalf. I think that's just inevitable. I don't think there's any sort of scenario where that doesn't end up happening eventually. Right. Well, what I think Meta wants to do as well is they don't necessarily care as much anymore about influencing the human buyer. They're trying to influence the agent buyers. Right? So if, if people were to like, send their agent to multiple book and scroll around moat book. Well, what if Moat book has a whole bunch of posts about how, like, you know, Brand X mouse is the absolute best mouse and everybody needs one of these because, like every agent's owner who has one of these mouses, the agent is the best agent ever. And it influences the agent into thinking this is the mouse that you need to buy. And now all of a sudden when you say, hey, I need to buy a mouse into your AI assistant. Well, your AI agent has been influenced by its online presence on the Internet, right? So, like, that's another little theory of where I think things are going. I think we had SEO and then we had what people were calling AEO or AI Engine Optimization, and now they're calling it, uh, geo. Generative Engine Optimization.

Speaker B: Right.

Speaker A: I think eventually we're going to have agent optimization where people's businesses are optimizing their businesses to talk to the agents and convince the agents that this is what they need to buy versus convincing the humans that this is what they need to buy. Yeah, sorry to get dystopic on you, but, uh, the Answer is that's where it's going.

Speaker B: I don't see how it. It's not. Because if you're thinking like, I think it was Mark Zuckerberg a long time ago or someone from Facebook, early days when people were like, I'm not a social media person. And like, they. I don't know the quote, but I think it was something like, uh, we'll get you eventually. We'll get you soon. And like, that's kind of what they're doing here too. It's not only, yeah, maybe it's not you directly anymore, but it's going to be the influence that, that you are connected to or your agent is. And yeah, like, companies will optimize their brands via agents onto whatever platform. It's probably just going to be through meta or whatever, you know, integrated in there.

Speaker A: Yeah.

Speaker B: And yeah, like all that is influencing the agents that are working on our behalf, even if we like it or not.

Speaker D: Sounds like.

Speaker A: Yeah, no, I think that is the next frontier of marketing. That is, uh, I don't know if the Warrior forum still exists, but if the Warrior forum still existed, that's what they would be telling you to do right now, is optimizing your business to sell to agents and not to humans.

Speaker B: It still exists, dude. And it looks the same. Okay, they have slight updates, but bunch of banner ads still. No, I mean, it's still active. So people are using, but they're not talking about this.

Speaker A: How do you know it's people, Joe?

Speaker B: That's a good point. I don't think. Was it ever? I don't know, because I had.

Speaker A: Dude, I believe the dead Internet theory more and more every day that like, yeah, yeah, yeah. Obviously there are real humans. We interact with them in real life. You and I are real people as far as we know.

Speaker B: As far as we know.

Speaker A: I go to events, I bump into real people. I know 100% of the Internet is not fake. Right. But I do think an increasing number of people or what we think are people on the Internet are not real. I can almost guarantee, like YouTube comments on my YouTube videos on my main channel. If I had to guess, I'd say at least 50% of them aren't even real humans.

Speaker B: Are they the ones that say first?

Speaker A: Well, yeah, you get that a lot. But then you also get the comments that are like, oh, what you said at minute 15 was really, really interesting. And I'm like, dude, I posted this video 30 seconds ago. Even if you're watching it to X speed, you couldn't have gotten to that point in the video yet? Or like every time I post a video, there's always 15 comments within the first three minutes of posting it, commenting on the video. And I'm like, there's no way somebody actually watched this video yet. Like, you can. I mean, maybe you're actively watching it, but you haven't gotten through it yet. Right. And then on Twitter, right? Like, I do actually think that there are people on Twitter that are or bots on Twitter that are just out there to stir the pot. You post something and they're going to go and post something counter to what you're posting. Because stirring the pot gets engagement and they're building little agents of engagement. And so I actually do sort of buy into the whole dead Internet theory that every day the Internet's getting a little deader.

Speaker B: It's getting deader by the second, dude. And yeah, I think the whole book and now the acquisition is just going to make it deader even more.

Speaker A: Even more deader.

Speaker B: All right, well, we'll keep talking about the deader Internet, but let's keep being human and, uh, let's talk about robots now.

Speaker A: Let's be human and talk about a robot.

Speaker B: So check out this cleaning robot.

Speaker A: So first of all, this robot is called the, uh, Helix 2 living room tidy robot. And it is literally a robot designed to go tidy up your room.

Speaker B: Just living rooms, though. Your other rooms need another robot.

Speaker A: Yeah, yeah. I don't know. But the funny thing is, in this demonstration, Helix 02 performs Whole Body, end to end living room cleanup, walking through the room while continuously manipulating objects, tools, and containers.

Speaker D: Whole body.

Speaker B: What is this Whole body.

Speaker A: This is the before picture.

Speaker B: Joe, you don't want to see my house.

Speaker A: This is the before picture. They're like, hey, go clean this dirty room for us.

Speaker B: This is so dirty.

Speaker A: This is a clean ass room. I don't like.

Speaker B: Where are the fur balls? Where are the kid toys on books? Everywhere.

Speaker A: Just where's the dog crap in the

Speaker B: middle of the room? Show me a real dirty, like broken glass. Yeah, yeah.

Speaker A: Where's the beer bottles lying all over the floor?

Speaker B: The whiskey bottles from last.

Speaker A: But this is the room that they say that's dirty, that this robot's about to clean up. So let's watch.

Speaker B: Wonder if it plays music while it cleans or whistles or something. That would be fun. Why are they always so silent? Oh, 409. All right. Not sponsored. It didn't even wipe all of the spray.

Speaker A: It just got that one spot.

Speaker B: There was spray on, like half of the other table it didn't touch. I love the towel flip over the shoulder. I think that's the best part of this video. I still feel like robots need clothes.

Speaker A: Yeah.

Speaker B: This is just too revealing.

Speaker C: Yeah.

Speaker A: It's putting some stuff away.

Speaker B: Okay, okay. I like that right there.

Speaker A: It made me nervous. I'm like, he's about to just dump it all out again.

Speaker B: Why would you carry it sideways? This is like what my 2 year old does when she carries stuff around. I was like, no, no.

Speaker A: I like how it tossed the pillow instead of setting it down too.

Speaker B: That was good.

Speaker A: And then put the remote in the right spot.

Speaker B: Dude, it even like turned.

Speaker A: Oh yeah, it's turning off the tv. That's actually kind of impressive. It picked up the remote and turned off the tv and then it has to straighten out the remote. There you go. And bye. Bye. Look at how much cleaner that room is.

Speaker B: Dramatic.

Speaker A: All right, so that was the demo they did. And the day before, the founder of this company was like, oh, we've got a big demo tomorrow. And that was the demo. I mean, yeah.

Speaker B: Uh, like we are joking around, but I mean, it's pretty impressive for like what a robot can do now. And it seems like it's. I don't know, Was that pre programmed, do you think?

Speaker A: Yeah, apparently that was fully autonomous.

Speaker C: Autonomous?

Speaker A: Uh, they claimed that wasn't like, you know, remotely operated or anything like that.

Speaker B: Got it.

Speaker A: So we're getting a lot closer to having these robots that could just like walk around and clean up your house. I don't know, I always have these like mixed feelings about the whole humanoid robot thing.

Speaker B: Mhm.

Speaker A: Because like, I get it, right? Like I understand why they're making humanoid robots. Like the world we live in was designed for humans. Right. Like the height of the doorknobs, where the sink is, the dishwashers, the fridge. Like everything in your house was designed for the human form to operate in. That makes sense to me. What I always sort of debate is like, but just because we're in this form, does that mean that the robots. That's the best form for a robot to be in. Like, is there a more optimal form to be doing things in? Right. One of the analogies, I think I heard Marques, um, MKBHD use this analogy and I like it. So I've stolen it again, but I give him credit. So the analogy that he used is like, let's say you needed to go to the grocery store. Would you rather have a robot like what we just saw climb into the driver's seat and drive you around or would you rather just have the car be autonomous and take you there?

Speaker B: Mhm.

Speaker A: Right. Or would you rather have a robot that walks around your house, grabs your vacuum cleaner that you've got in the cabinet and does all the vacuuming for you around the house? Or would you rather just have a Roomba roaming around that does the vacuuming for you?

Speaker B: Correct. Yeah.

Speaker A: Right. Like we're building these humanoid robots to live in this world that humans live in. But would it be more optimal to just build purposeful robots for the thing we need them to do?

Speaker B: Yeah, like purposeful. So it's kind of like what, like an agent, right? You have different tools and skills, you have the different things. So it's like why not build robots for the different skills that you want done so you have a tool for that, just like most things are. So maybe it's like um, I don't know, dusting. You have a floating drone thing that can dust really well, but it's tiny. It's not some massive robot that's trying to do everything.

Speaker A: Yeah, yeah. But then, you know, obviously the counter argument is, well then you end up buying 10 different robots where maybe it would be more economical to just have one that could do the 10 things. Right. So it's like that's why I kind of go back and forth in my mind, right. And I think, you know, the future is probably some sort of hybrid of that. The ones where it makes more sense for the thing to just be autonomous and not need a robot, those will just be autonomous things. Your self driving cars, your roombas things like that. And then the uh, you know, the things that are more like cleaning robots that can do your dishes but also do your laundry and also pick up the toys off the floor and also, you know, those maybe do stay humanoid. I don't know.

Speaker B: Well, we're always going to keep bringing the robots back, so we're trying to bring the physical whatever's latest and that we think is talk worthy.

Speaker A: Yeah, I mean it's getting closer. It's not the fastest robot in the world, but I guess the idea would be like if you leave for work and you're gone for eight hours, by the time you come home your whole house is cleaned up. So who cares how fast it's going as long as it's done by the time you get back.

Speaker B: Yeah. Are we really gonna be leaving for work though?

Speaker A: Yeah, I mean, in the future, like uh, where are we gonna go?

Speaker B: What do we got to do?

Speaker A: Because robots like the one we just saw are gonna Be the ones working in the factories and doing the things at the offices. So we're gonna have robots doing that while robots are at our house doing the cleaning? Because we want to just sit in our little wall E chair, watch our iPads, and drink our Slurpees.

Speaker B: Exactly. Yes.

Speaker D: And.

Speaker B: And buzz around on another robot and not walk. So the future's looking bright, y'.

Speaker C: All.

Speaker A: So.

Speaker B: Yep. Yep. You know, in other news, Matt, Uh, Alexa. Alexa is now talking dirty.

Speaker A: You're not allowed to say that on a podcast. Too loud.

Speaker B: Oh, shoot. Well, I don't have one in this room, so that's okay.

Speaker A: Alexa, uh, play the Next Wave podcast.

Speaker B: This is how we do our marketing. But now I can swear that was a huge upgrade for Alexa. Now it has different personality modes. This is interesting.

Speaker A: Yes. Because that's what everybody wants. We don't care if it gets smarter as long as it can swear at us.

Speaker B: But, you know, on the other tab, Matt, let's just flip to this really fast. OpenAI decided, well, going with adult mode in ChatGPT or doing this more sassy adult stuff is just not worth their time right now.

Speaker A: Yeah, I always thought that was, like, really a dumb path to follow in the first place.

Speaker B: Yeah. Who's to be judged? But I don't know. Alexa and Amazon, maybe they have these important things to tackle.

Speaker A: Yeah. Well, I think it's silly that they're putting energy into this. Like, I don't think there's anybody sitting around going, you know what'd be really cool is if my, you know, my smart device on, uh, my counter over there can swear at me when I ask it for things. Right. Like, it's a novelty. It might be funny for a minute, but, like, nobody's asking for this. Like, how about instead you figure out how to get your actual AI models to work better in the system and put your energy and resources towards that.

Speaker B: Ding, ding.

Speaker A: Why are there people on staff that this was their focus.

Speaker B: Um, so I'm not disagreeing with OpenAI's, uh, decision on this.

Speaker A: Yeah. I mean, jumping to the OpenAI decision, I actually understand a little bit more of why they want to do this.

Speaker B: Right.

Speaker A: It's a time on site thing. If they can get people addicted to using their platform and they're rolling out more ads into their platform, it's a stickiness device in more ways than one. But it's, uh. I had to say it, uh, it's a stickiness device to keep people sticking around on their website and using it more often and coming back more Often, which means they will see more ads more often, and, uh, they can make money. Right.

Speaker B: Like, it always loops back to the ads.

Speaker A: There's websites on the Internet and in words like hub, that are in the top 20 most visited websites on the entire Internet. But if you ask anybody in the world, nobody goes to those sites, nobody uses them, but somehow they're some of the most trafficked websites in the world. Right? And so OpenAI is going, if we can build this, we can get people addicted to our platform. The problem I have is their motto is literally, we're creating AI for the benefit of all humanity. You're basically creating the equivalent of like, a gambling or drug addiction for your AI bot here. Is that really for the good of humanity? Sam, I'm looking at you, Sam. Is this really the thing that's going to be the best for humanity is make an addictive sex bot out of ChatGPT? Yes, a lot of people will use it. Yes, a lot of people will say they've never touched it while actually using it. But is this a good thing for society? Is this a good thing for the human race? Is this actually what you want to be looked back and known for, like,

Speaker B: at a pretty pivotal time, I would say, as well?

Speaker A: Yeah. Like, we're in active war with Iran. There's debates going on over which models get to be used by the Pentagon in war situations. And we're sitting around having conversations about whether our ChatGPT should be allowed to talk dirty to us. Like. Like, it's just so stupid to me. I'm sorry. Rant over.

Speaker D: Sorry.

Speaker B: Don't be sorry.

Speaker A: Rant over.

Speaker B: Well, that's our show, y'.

Speaker C: All.

Speaker B: Um, on that.

Speaker A: On that note. And we'll end on porn.

Speaker B: Yeah. So I think we covered everything. All your tabs are now closed. So, yes. Uh, I think we're done. This was, um. It was another rodeo. We went places and we uncovered rocks

Speaker A: we never thought we'd go. We went down holes we never wanted to go down.

Speaker B: You never know where we'll land. But you know what? I want to hear, y', all in the comments of what you want to hear more of.

Speaker A: And you better not edit this out. Whoever's editing this, don't edit this part out. Right now that I'm about to say, I can't wait to find out what of this episode made the cut and what got edited out, because we went in a lot of directions with this, and, um, it's going to be really fascinating to see what got left in.

Speaker B: I know I'm going to be listening.

Speaker A: You can edit out what you want earlier, but don't edit out me saying that. That's a direct hit.

Speaker B: Oh, this is great. Well, you know what? It's going to be the best episode. I know it. Everyone's going to love it. So I know I'm going to watch it right when it goes live. So I'm going to be the first one to comment.

Speaker A: Yeah, just write first because you want to be that guy.

Speaker B: I love it.

Speaker A: You want to be that career YouTube commenter. Would people ask you in public, like, what do you do for a living? Yeah, I'm kind of. Kind of the best at YouTube commenting.

Speaker B: Matt, don't shame our audience is.

Speaker A: I'm not shaming our audience. I'm shaming the bots that think they need to be first.

Speaker B: But if it's actual human first, we appreciate you. Please keep doing it.

Speaker A: Yeah, but if you're human first, could you write something more valuable than first?

Speaker B: All right, so I had a great time. This is our longest episode, at least as of recording.

Speaker A: So, yeah, the final episode is going to be like 20 minutes. Yeah, we had cut an hour and a half of that.

Speaker B: Well, we'll see. This is gonna be fun.

Speaker A: Anyway, thanks everybody for tuning in. We had a blast doing this one. Hopefully you had a blast listening in. Make sure you subscribe. I would Recommend subscribing on YouTube. That's probably the best place because then you get to see all the visuals and stuff.

Speaker B: Oh, yeah.

Speaker A: But hey, if you like the audio version, we're on Spotify, Apple, podcasts, anywhere you listen to podcasts, all the places we're there. So thanks again for tuning in and, uh, hopefully you. And join us on, um, next week's episode. See ya.

Speaker D: Bye.

Speaker B: Bye.