SPEAKER_00: They've taken all the image editors and all that. Oh, that is not a, so that would be a good job.

SPEAKER_02: I mean, that actually, I look like a headlifter. Like, hey, would you like a soy latte? I feel like I'm making you a crab cocktail.

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SPEAKER_09: All right, everybody. Welcome back to This Week in Startups. Our guy, Sandeep Madra, is back.

SPEAKER_11: He's been busy. Grok is cooking with oil. How are you doing, my friend, Sonny?

SPEAKER_13: I am doing excellent.

SPEAKER_15: Uh, it's been a really, really busy, and we said this, remember, it's going to be a Q4 plus one. So we're now actually in Q4 and we are cooking. We are cooking. It is, we're 10, 11, 12 days in by the time we publish this. And J. Cal, tell me about your September in Q4 and like what's going on because.

SPEAKER_18: You know, I am settled in here in Austin. It's been absolutely fantastic. And, um, we're doing our next, uh, class of founder university, not our ninth cohort.

David Friedberg: You know, that's where we have people come for 12 weeks.

SPEAKER_21: It's virtual, 250 teams, two or three founders, each team, hopefully a technical co-founder or two. And then, um, we invest in the top 10% of those.

SPEAKER_22: We might put 25K in if they want like that first friends and family check, or we'll put 125K in, you know, if they want the standard like incubator deal in Silicon Valley. And then, uh, you know, what will be different this time is I'll meet them all for the week one in San Francisco with some of our partners.

SPEAKER_18: Then my plan is in week six, nine, and 12, perhaps the top performing companies, the ones we invest in, have them come to Austin for the day or two, hang out with me, go to the salt lick, have a little brisket, some, uh, bison ribs, you know, the one that broke my tooth in half.

SPEAKER_28: Oh yeah. And, um, maybe a little Terry bat blacks, beef rib, which I took Chamath to for the first time and, you know, just jam out with them about their vision.

David Friedberg: And I am super, um, excited just because so many of these companies are able to go so far with such a small amount of capital, especially when they're teams of two or three because of AI specifically.

SPEAKER_23: And it's really, uh, wonderful to see how fast people are working.

David Friedberg: And then I'm very excited about Oh, one I've been using chat GPT Oh, one version to the point at which it gives me like a warning about credits, you know, and says, Hey, you gotta take a pause. That's how often I'm using it. Uh, so it's really amazing. I had just, while we start here, uh, we're taping on a Friday. I'm not sure when this is gonna come out, but we taped on Friday, October 11th last night was the, a cyber cam big reveal. I wasn't able to make it. Sorry to, uh, my friends over at Tesla. Uh, but I was traveling this week for Sax's LP day earlier in the week. So I couldn't do two trips in one week. What were your thoughts when you saw, uh, the cyber cab, the cyber bus, uh, and optimists, especially in relation to AI and where we're at?

SPEAKER_32: Yeah. Okay. I think it's a great lead out.

SPEAKER_00: Um, and I've been thinking about this all day and we talked a little bit about it in our group chat. Okay. Um, let's go in that order. I think the cyber cab is really a culmination of everything that, you know, Tesla has been doing, which is building cars, building great electric cars, um, you know, uh, building on autonomous technologies with sort of all the in-camera learning and, you know, their ability to basically, um, you know, put that all together in a form factor.

SPEAKER_15: Now without a, you know, uh, uh, steering wheel and, or pedals, uh, quick aside, I heard a number of people say, put a steering wheel and pedals on that and I'll buy it just.

SPEAKER_28: I mean, I literally said that as well.

David Friedberg: And I think that this was in the Walter Isaacson, uh, book about Elon where fronds or whatever, you know, it was a big internal debate. Um, and I think Elon went with the kind of burn the boats, uh, according to that approach of, Hey, we, we just gotta force our autonomy. We gotta take the steering wheel out, et cetera. Um, and so maybe there'll be the, what they were calling, I think the model two, which is the two door hatchback. I want to buy that two door cyber cab so much. I would buy two of them immediately because they just look so fun and, and cute and zippy to drive.

SPEAKER_18: Can you imagine, uh, uh, a Tesla powertrain on something, you know, of that footprint? It would be unbelievable.

David Friedberg: It would be like that Nissan, um, or is it Toyota, the GTR that all the racers, like, do you ever tripping and stuff? It would be like a, a mini Cooper, you know, you get that like really small thing. I would love to put fat tires on that and feel it. I love the design too. I like the fact that this feels like kind of the love child of the cyber truck and the model Y or model three.

SPEAKER_28: It's kind of got its own like thing going on there. So aesthetically, I love it. I love the vision of it, obviously for self-driving. What did you think of the bus to me that I think it's an RV. I, I looked at that thing and he, I don't know if you saw, do you see my tweet that I did about it? Yeah. Yeah.

SPEAKER_40: So let's talk about the bus. Cause I thought, well, let's finish on the cap.

SPEAKER_15: Okay. So I think, I think what they've been able to do is bring together all the pieces.

SPEAKER_44: Now the final thing, which, you know, I think there's the market reacted negatively to Tesla, but I think that's probably a buying opportunity because look, um,

SPEAKER_46: the stock went down, whatever, five or 10% then.

SPEAKER_15: Yeah. Yeah. But look, think about what they've put out there and what it's capable of.

SPEAKER_00: And I personally think given, and you know, there's a couple of things that Elon really touched on in the talk track was look, we collect, you know, millions or what? I don't even know what the number is, but let's just say a huge amount of data. And we, and there was a video that he showed during that where it showed all these like crazy scenarios of like people jumping in front of a car and like, you know, the car crash happening right in front of you. Or someone spinning out or, you know, someone crossing the road really, really fast.

SPEAKER_44: And so all of that has been kind of given to them, uh, through their existing car network, which then they can use to build models around. And so I actually think, and look, look how confident they were yesterday. They allowed people to just use it inside, obviously a square, you know,

SPEAKER_50: No safety driver because there's no steering wheel. So yeah.

SPEAKER_44: Yeah.

SPEAKER_51: And they were letting anybody do it and it wasn't just on a controlled environment.

David Friedberg: So it works in a controlled environment. So on a grid system, it's ready to go now, but you have regulators and regulators, you know, they like steering wheels.

SPEAKER_18: They like review. They like side mirrors.

David Friedberg: So this is, I mean, really going to be challenging with regulators, I suspect or not. I don't know what your take on that. Yeah.

SPEAKER_44: So I think like, you know, what we'll probably see is like the crawl, walk, run because they know they can do it there. So you can imagine like in a, and I think companies are going to buy them first. So think Disneyland, right? Think all, you know, all these kinds of places that operate. Think about like a retirement community in Florida, right? So think about all these like, you know, places. Like a campus.

SPEAKER_56: Yeah. Yeah.

SPEAKER_51: Exactly. Places where there's golf carts or those little. Yeah. Exactly. Easy.

SPEAKER_44: And I think, I think you sell in there first.

SPEAKER_53: And then as the technology evolves, because he did say end of 26 or 27. I think by that point, we get to kind of widely generally available release. And I think that's the underestimation because they had enough confidence to allow people to, you know, just use it openly, obviously in a fixed area. But they, they weren't scared. They had no safety person in there. They had nothing on it, which is incredible. So that's my summary there. I think we get it in, you know, what you call like fixed, fixed cordoned off areas.

SPEAKER_59: We get it there sooner than I think people believe.

SPEAKER_60: 2027 would be a pretty good estimate.

David Friedberg: I think he said he could have those cars being manufactured. He, he, he, it was interesting because he was like kind of 20 and I'll say 2026, but maybe 2027. He kind of hedged a little bit there, which kind of, and maybe that's why the stock went down a little bit because maybe people want everything yesterday. But the truth is you got to get this right. Right. And when you do, they have the ability to produce, I think they did 1.9 million cars last year. So he does have the ability to produce that volume. And so listen, you know, you know, he can put millions of these on the road, you know, in, in a short period of time.

SPEAKER_21: However, you know, just doing back of the envelope math, there are a billion rides a day in the U.S., a billion rides a day in the U.S., a billion rides.

David Friedberg: Of those rides, about 12 million of them are Lyft and Uber. So, but 3%, 2% of rides in the U.S. are done by ride sharing. It is a minuscule amount of the overall rides. And we're not even taking into account when you do that math, of course, public transportation and other forms of transportation, bicycles, et cetera. So there's a big pie here. And of course, if this became cheap and ubiquitous, people might stop buying cars and use these and people would induce more usage. So it's a bright future. I do believe there'll be three, four winners in this because it seems like everybody's solving it at about the same time.

SPEAKER_22: But there is a difference between Waymo and Cruise writing code top down versus building it off the data set.

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David Friedberg: So maybe explain to the audience in plain English as best you can the two different architectures of these systems.

SPEAKER_28: We know one had LiDAR, the other ones don't. Yeah. Or Tesla doesn't use LiDAR, the other ones do.

SPEAKER_77: So there's one issue here, but we've beaten that dog to death a million times. Let's talk about the model and how they're doing it.

SPEAKER_53: And so, you know, it's actually kind of related to that, right?

SPEAKER_44: Because, you know, what Elon says is a human has two eyes and sort of a head that moves around and that's all it has. And we're able to drive cars, you know, perfectly fine, right? That's what we're trying to mimic. And the reason, you know, others add sensors is all the, you know, these eyes, the eyes, the cameras can get covered. So you have an extra set of sensors that give you another view of the world and then use that. So now you take that into the model, right? Where if you're building a model that's using vision and using like a LiDAR and using, say, ultrasonics, you have to write code that brings that all together. And so what you're doing there is basically sort of, you know, I just call it like sort of the traditional approach across all those things. And you're double checking and, you know, it's valuable that you have all that, but it's much more difficult because you're having to have the, you know, code and the drive and all those things make decisions, right? What Elon and team did, and this is a gross simplification is they just took a model that would learn to drive by watching video. All they fed it was, you know, hours or, you know, maybe hundreds of millions or billions of hours of video that they had from the cars. And so just figure out what humans do and follow what they do, see how they sit in lanes.

SPEAKER_53: And so instead of coding and saying, you know what, what people tend to do is they don't drive right in the middle of the lane. They tend to move based on if they hug the left or if there's a car to the right of you, they go to the right. Or if there's a bike, they even go out and give it a little extra grace in that period. Yeah, I'll give you an experiment you can do if you make a right, like a right turn, but there's no one in like city oncoming lane into the train into the lane that you're turning into the road. It'll actually go wide and go out into the lane into into the oncoming traffic. And that's because it's learned that from from from humans, right? Like you don't need to hug the right side curb if no one's in the it's yeah, you're kind of scared to hit your rims or whatever it is. Right. And so so what it's learned to do is like just do that by watching humans. Well, there's no one in the lane just stretch out in the left turn lane, the oncoming left turn lane. And, you know, you can't write that in code. That's the nuance. Right. And that's what you have to do if you build kind of a more traditional system versus this one is just watching all the nuances of humans and then implementing them. on how they take curves and how they move around people. And, you know, now it has to follow a certain set of rules. Like one of my biggest frustrations is it does this like full full stop.

SPEAKER_44: And I'm always afraid of like someone from behind hitting the car. Yes. Yeah.

SPEAKER_88: This is a Waymo issue as well.

David Friedberg: I saw somebody on threads today. I went over to threads to see what the reaction was there. And that's like that's like really the people who hate Elon or hate, you know, they're the left. So they hate anything that's Republican or GOP. Yeah. And, you know, one person was talking about Waymo and they were like a San Francisco bike person. And you know how those people are. Like they kick your car. Literally. Like I had one kick my car and was got into Pista cuffs with the guy. Started yelling at my pregnant wife. That's all another story. Putting all that aside. Um, the, um, the, the really interesting thing he was saying was I actually was, I used to screw around with the crews and the Waymos. You know, I was like one of the guys who put cones on them kind of thing. And he's like, and now I walk with my dog and I love them because I know that they're not going to be looking down at their text or distracted and roll through a stop sign and hit me.

SPEAKER_18: There's no way they can hit me and they stop perfectly.

David Friedberg: So the other thing people are complaining about, and somebody on our group chat said this is it's kind of annoying that they're such square drivers and they kind of take their time too much. And that's been my issue with, uh, you know, using the test of full self-driving in Austin.

SPEAKER_02: Yeah. And is a traffic circle. And it is very, it's very cautious.

SPEAKER_97: Cautious. Yeah. But you know, you can put it on aggressive mode.

SPEAKER_28: I have it on aggressive mode and it's still a little scared of traffic circles, I think. So for the team over there, I think that's like probably traffic circles are not that common.

SPEAKER_99: So maybe it needs more training data and then how people behave in traffic circles is wild.

SPEAKER_28: That's one of the other things I've learned in Austin. Like what I thought was the proper way to use a traffic circle is not how people in Texas use them. They use them like, I mean, they'll be going through them. Yeah.

SPEAKER_102: They don't slow down.

SPEAKER_28: Yeah. They just, you know, yeah, it's a pretty interesting, uh, moment there.

SPEAKER_18: Let's talk about this. Um, the bus. I thought the bus. Robo van. Robo van. I'm calling it the cyber sled. I think that this could change everything.

SPEAKER_28: If you look at this thing, he did mention it could be used for transporting goods. Okay. Yum. Yum. You imagine this thing with an Amazon person in it. Yeah. There's an Amazon rep inside of this thing and it's driving to the next destination. That rep is getting the box ready. It opens the doors. It jumps out. It tosses the box. Okay. That's going to save a lot of time, but what were your thoughts on this?

SPEAKER_111: It looks gorgeous, obviously, but I, I have my own thoughts and you saw my tweet, so we can jump into that.

SPEAKER_53: Yeah. Like my personal thoughts, like very similar to yours.

SPEAKER_44: Like this could be like a great basis for like a whole new generation of RVs, long distance commute, all that type of stuff, right? Let me get in. Like you could own one. It could have your whole office desk in there.

SPEAKER_114: Big monitor, sit down, work, you know, Starlink on top. It's like a, it's a, you know, all things.

David Friedberg: Mobile office. I've been looking at when I moved to Texas, I was like, you know, I'm going to get one of

SPEAKER_21: these mobile offices, like a sprinter van. And I started looking into them. They're not cheap. They cost like 200 grand. I mean, cause they, they dialed them in or 300 grand or whatever.

David Friedberg: So I was like, well, that's a little ridiculous, but anyway, you can have a desk and you can have like a, a full on, you know, basically like it looks like a private jet inside. Um, but I thought these would be incredible for a mobile home.

SPEAKER_21: Imagine autonomy, a giant battery. And then you have a hurricane occur in Florida and they say, okay, send 10,000 of these to,

SPEAKER_18: you know, this stadium's parking lot or to these Walmarts people come and you could rent one. Uh, or like you're at the world series of poker and you're, you want to have your own trailer or you're at burning man, or I don't know, you have your in-laws coming in and you order one to your house for a week for a hundred dollars a night and you park it in your driveway. And now you have an extra bedroom. These things are so compelling to me. Um, because it's somewhere between a car and office and ADU. You think about the giant battery there. Like how long could that battery last? That could be a battery that lasts 30 days and has enough roof space to put solar on it.

David Friedberg: So congratulations to the team there. Optimus looks like it's doing well as well.

SPEAKER_41: Yeah.

SPEAKER_15: Last thing on Optimus, you know, just like the car, they had it out in the wild. They had it serving drinks. They had it walking around, talking to people and reacting to people.

SPEAKER_44: So, you know, I think what I really liked about this was they made it more real, right? And it's kind of funny because the reaction wasn't that way, but by letting cars and letting people drive around and letting the robot walk around amongst people, those are big accomplishments. And what we forget, Jason is just two years ago, Elon did the, um, or you know, Tesla did like the announcement. Remember they had the guide, the suit, like, like kind of acting as a robot. I don't know if you saw yesterday, they had that one in like a gazebo and they were dancing. And like, you think about it two years ago, it was a dude in a suit. And then yesterday it's like, you know, robots actually dancing like in a gazebo.

David Friedberg: I think, you know, it's like bankruptcy. They, they asked somebody like, how did you go bankrupt? And they said slowly then all at once. Um, and I think that's what's self-driving is it's like, this thing is taking forever

Chamath Palihapitiya: because of edge cases and regulation and safety and competition. And, you know, well, you know, what happens when there's an emergency vehicle, how is the

David Friedberg: public going to respond to it? But it's pretty clear that this is going to be the future. And then the build out is going to take time because even if you built 2 million of these

Chamath Palihapitiya: a year and they did 30 rides a day, you know, 2 million of them doing 30 rides a day, 60 million rides, you know, you're still, it's, it's going to be like 1% of the rides in the

David Friedberg: United States. I mean, let alone the world. And then you have BYD that copies everything Tesla does. You've got cruise Waymo. I mean, there's a lot of players in here. So everybody wants to ask me about like my thoughts on Uber. Well, Uber went up tremendously because I think people realize if every single

SPEAKER_122: little J Cal, yum, yum.

David Friedberg: Um, you know, listen, and I own a lot of different stocks. Like it's not a big deal. Like if Uber goes up and down, you know, build out of this will be a 2 decade build out.

SPEAKER_18: I think 10 years from now, 10 years from now. We'll be at 20% of rides being automated.

SPEAKER_125: So 20, we're almost in 2025. So 2035. 20% of rides globally will be autonomous.

David Friedberg: 80% will still be done by drivers.

SPEAKER_00: Oh, dude. In 10 years. I'll take the over. I'll take the over like way more than 20% in 10 years.

SPEAKER_21: Perfect. Okay. We'll put that on the bets this week in startups.com slash bets.

SPEAKER_28: There's an easy bet because here's the thing. I think what people don't realize is the number of rides out there is so giant and the number of rides are going to triple. What I learned from being an early Uber investor was that we were comparing it to cab rides, but then it quickly exceeded the number of cab rides. So you said, well, what happened here?

SPEAKER_21: Well, people left their cars at home because they were having a drink. It was more convenient, et cetera.

David Friedberg: And then they started using it for commuting where they might have previously taken a bus and they said, well, I'll go point to point because I can afford it because it's eight bucks. So a lot of great things going on here, but the number.

SPEAKER_53: Jeevan's paradox. It's Jeevan's paradox. You make more of a. So Jeevan. Yeah.

SPEAKER_44: Jeevan was a economist that basically came up with this theory, you know, in the late 1800s, British economist that said, if you make more of a resource available, people end up consuming more of it. Right. It was kind of in the steam engineer. Right. Whereas like, oh, like steam engines are going to change everything, but they start. And what's it going to do to coal? And then all of a sudden they start consuming more coal. And so anytime we've put something out there, actually a better example here is much more is that farming. Right. So when we went to the industrialization of farming, what ended up happening is the consumption of food really increased. Right. And like, you know, Americans are every, everyone's more obese because it's just more of it's available. So we eat more of it. So it's just something that we tend to do is cheaper. Yeah.

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SPEAKER_18: And when I lived in L.A., they were constantly making the four or five one lane bigger.

David Friedberg: And like when it stopped, when they stopped one project and then they'd have two years.

SPEAKER_18: What happened was people from people would move further out from the city center because they're like, oh, I can live now in El Segunda and make it to Santa Monica or Century City for work. And then it fills up again.

SPEAKER_22: So the traffic, no matter how many lanes you did, would instantly fill up with induced traffic. But congratulations to the team there. And I think it's awesome.

SPEAKER_28: And I think there are going to be I think, you know, we talked about this. There's going to be three or four players who are all going to figure this out to different extents, I believe, in the same 36 month window, which means at the same time. Now, I know that's hard for people to understand that figuring out a technical problem in the same 36 window is the same time because there is a physics constraint here.

SPEAKER_18: You need batteries and you need resources. It would take literally to do the number of rides just in the United States every day. There's a billion rides. You're talking about 50 million of these cars.

SPEAKER_22: Like, I don't know if the battery packs are available for 50 million cars. And if Tesla makes 2 million a year and they were to double it every year and they went to four, then they went to eight. I mean, I don't know what the physics constraint of the factories and the batteries are, but, you know, it's going to take a lot.

David Friedberg: And so that's why I think 20% being automated, you know, in 10 years is a realistic goal. Right now we're below 1%.

SPEAKER_111: I think that means the pie is going to get so big. Yeah.

SPEAKER_00: And I think one, two, and three are pretty clear, right?

SPEAKER_144: Waymo and Tesla. Right? Yeah. And BYD and some of the Chinese companies.

SPEAKER_149: Can we give, we can add in Joby. Sure.

SPEAKER_88: I mean, and then going in the air is going to be part of the Joby Archer and the other one.

David Friedberg: Yeah. And there's, it's pretty clear that we're going to, um, really have a bright future. So, uh, congratulations to everybody.

SPEAKER_151: Um, let's talk a little bit about demos here. It's, uh,

SPEAKER_00: We got to get back into it.

SPEAKER_15: All right. Got to get back into it. All right. I'm going to go, I'm going to go a little bit different order. Cause I'm generating something and it's taking longer. So my first demo, actually, Jake, I don't know if you've used this yet.

SPEAKER_97: Um, is, uh, let me, let me get my, uh, chat GPT open here. And I don't know if you've, you've tried this. So let me get my share going here. So they have a new mode here and it's called chat GPT 4.0 with canvas. Have you seen this? I have not used it.

SPEAKER_152: I haven't. Okay. Okay. This came out this week.

SPEAKER_97: Yeah. Uh, write me an itinerary. Uh, okay. For a one day tech conference in Austin. I'm just going to do it just for you, Jake. All right. And so what you're going to see here is.

SPEAKER_15: So now what it does is it, it, it, on the left hand side is your chat GPT.

SPEAKER_97: And you can do this for writing code and a bunch of things, but I think this is much more applicable to folks. Right. And you can basically take a section of it, highlight it, which I'm going to do here. Oh, let me just highlight this properly.

SPEAKER_154: How did the chat window move over to the left?

SPEAKER_15: Because that's what happens when you use this mode. And now for these two sections here, I can say, uh, let's just say, make these more about intros and a special guest.

SPEAKER_97: And so now see what I, what it'll do is it highlights it right in place.

SPEAKER_51: Oh, yeah. Yeah.

SPEAKER_97: And so if you're working on something, basically what it's doing is it will highlight, it'll let you work on the document while you're kind of editing it on the left hand side, which is really cool.

SPEAKER_158: So weird that mine's not doing that.

SPEAKER_23: It's not putting me on the left hand side for some reason. No, but are you doing 4.0 with canvas?

David Friedberg: I am on 4.0 with canvas, but it's not showing me the left hand column. I don't know why. Maybe I've got to log out and log back in, but, um, this is really cool because it's editing the same document.

SPEAKER_162: Yes.

SPEAKER_28: This is what we've been waiting for because it's constantly. Yeah. So this is great. This is a 10 of 10, obviously. Yeah. Yeah.

SPEAKER_22: This is absolutely wonderful because we could put in today's docket or like a news program docket. Yeah. Like make it shorter, make it longer. Add something to that.

SPEAKER_104: Yeah. Add something to that. Add it, put it in a table. Yeah.

SPEAKER_35: Yeah.

SPEAKER_28: And so, you know, we're starting to see the, this is what we saw in Blade Runner when she is asking to analyze some, uh, video clips and he's zooming into the left and the right. And it's responding in real time.

SPEAKER_22: That was a vision from Ridley Scott, you know, from the eighties.

SPEAKER_99: And, uh, yeah, this is fantastic. Absolutely. 10 of 10. Yeah. Just great.

SPEAKER_44: Yeah. And then this is daily use. This is use all the time.

SPEAKER_00: This is much better to iterate when it comes to, uh, usability. And so you give it a, uh, give it a, give it your grade J Cal.

SPEAKER_125: I'm giving it a 10, 10 of 10. Yeah. Okay. All right.

SPEAKER_174: Yeah. A plus for me. What about for you?

SPEAKER_44: Yeah. Yeah. I mean, I look, this was the one last thing that I always kind of struggle with which had GPT is like, oh, you're always having to copy paste or rewrite the whole thing. And now you can edit it in place.

SPEAKER_00: And so I want to make sure you get it enabled J Cal. Like I, I, I, I feel for you right now. I don't know what.

SPEAKER_178: Well, you know what it might've been. It might've been that I didn't wait till it was done. Like when does it actually open up the left?

SPEAKER_180: Kind of starts in a, it starts. I mean, I can do another one. Yeah.

SPEAKER_182: We can just do another one here. What were you trying to do? I'll do your one here.

SPEAKER_184: Well, I just said, uh, you know, create an itinerary for going to Tokyo and Niseko to go skiing this winter. Um, and it gave me like three days in Tokyo and four days in Niseko.

SPEAKER_183: Yeah. But it didn't put it on the, um, oh, 4.0 with canvas. Nope. Try.

SPEAKER_188: Yeah. So see, it's, it kind of, oh, it's interesting. So for this one. Yeah.

SPEAKER_189: So it's open the left hand side. I wonder why it's not doing that. Hmm.

SPEAKER_23: Somebody from, uh, one of our friends over there explained to us why it's not opening the left hand chat for everyone. Yeah.

SPEAKER_13: Yeah. Because I just had that happen. Yeah. It just happened there, but it's now it's not doing it for me either. Hmm. Weird.

SPEAKER_60: Very strange. Uh, well, anyway, this is, uh, absolutely fantastic.

David Friedberg: And, uh, I think this is the game changer. Yeah. That I've been waiting for. So. Yeah. Congratulations to the team over there and, you know, just using a one all the time and seeing it show its work of what it's doing has been extraordinary for me. I have been doing so many interesting, um,

SPEAKER_28: Um, and like actually speaking of what we're talking about here. Um, I was, um, looking at, you know, I was having these conversations with people about, let me share my screen. Um, one moment. So I was having these conversations with people about, um, car production, because I was trying to figure out how fast could we actually make enough cars to do all the rides in the U S and who makes the most cars. And I did a table, um, with this and, you know, then it was missing some companies.

SPEAKER_99: So I was like, Hey, where's BYD in all this? They make 4.5. Then I said, well, where's Tesla? And I said, well, Tesla's making, you know, put Tesla in there at 4.5. And I was like, wait a second, that's not the number of cars they made. They made 1.8. So is that right? And then I was asking it to, you know, correct itself and it did memory updated, et cetera.

SPEAKER_28: And it's really like coming together. Um, and then I asked him how many cars are sold in the world per year. And it told me 70 million cars are sold per year.

David Friedberg: So then I was able to back into, well, in the United States, we need like 50, 60 million cars in order to have a fleet big enough to do all rides. Cause I was like, what, what's all rides? All rides is probably 50 to 75 million of these cars. Cause you gotta realize some are gonna be in a dense urban area. Some will be in the suburbs where, you know, you might do an hour long ride and then it takes 45 minutes to pick up the next person because it's across town or whatever. You know, it's, we're half an hour to pick something up. Long story short, it would take every car manufacturer in the world just to make enough cars to do the United States. And then onto the next country, onto the next country, you know, it's, it's not gonna be easy is the point.

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SPEAKER_51: J. Cal, we can do your demo. Try this. So try it again. Okay. And say, use canvas. If it's not. I just was.

SPEAKER_202: Yeah. I was getting annoyed. Yeah. And then see if you can do it. Okay. Let's see. I'll pick. Use canvas mode. Use canvas mode to.

SPEAKER_53: Well, pick the canvas mode. Type it. And then if it doesn't do it, when your next prompt to say, use canvas mode.

SPEAKER_204: Use canvas mode to explain the total number of car rides in the United States.

SPEAKER_207: Give us citations as well.

SPEAKER_11: And let's see if it doesn't. Oh, it did it. There you go. So, you know, and this is what I was trying to explain. Yeah. Sorry. I've got to stop sharing.

SPEAKER_21: So, you know, 344 billion rides annually. I mean, it's just nuts. The number of rides that are occurring.

SPEAKER_28: Um, and you know, if you say 344 billions for under 65 billion days a year, it's about a billion.

David Friedberg: Rides per day. And so, you know, now, if I went to the side here, let's make a financial model.

SPEAKER_11: Um, how many, um, automated cars would be needed to, um, service all these rides.

SPEAKER_204: Hot on. Yeah.

SPEAKER_99: All these rides. Okay. Uh, so here we go. It's giving us a total number of the total number done. Average rides per car per day. Assuming a car can include 30 rides a day. That's actually a pretty good estimate, by the way, because that's what an Uber driver can do is like 15 to 20. So two shifts, you could kind of get there, uh, days in service a year. This assumes they operate 365 a day. That's a big assumption. We're probably going to do that. Total car rides, um, per car is, uh, you have to bring them in to change tires, to charge

SPEAKER_28: and the charging time, as you know, is to fully charge. Well, maybe if you're doing a supercharger, it'd be less, you know, but it's still going to be some time. So it's saying here approximately 31 million. Um, and I say, let's say assume cars are on the road.

SPEAKER_67: Uh, 80% of the time and charging 20%. And that they cost $40,000 to buy.

SPEAKER_99: And, uh, let's say 10,000 a year to ensure and clean.

SPEAKER_22: And that we can like, let's see if they can do this. Now, this is something you would be talking over the shoulder to an analyst, right? If you were in a, in a, in a venture firm or whatever, uh, or you were at Morgan Stanley and you were an analyst and you start, now you're here, you got the financial model says cost per car 40 annual insurance, 10 total cars needed 40 million, 39 million, $1.5 trillion to purchase the cars.

David Friedberg: 1.5 trillion is a lot of money folks. You know, just to give you an idea. I think apple may be sitting on a hundred or 200 billion at any given point in time. Um, and so the operating costs would be 400 billion a year.

SPEAKER_11: So, you know, it's, it's not easy, right? Um, and, uh, what would the revenue be if each ride was, I don't know, uh, let's say 20, uh, $15.

SPEAKER_67: Now we can start to see what the revenue would be here. $15 ride seems reasonable for a half hour ride.

SPEAKER_217: Uh, and you can start to get to, let's see, uh, revenue 5.6, $5,000. Oh my God.

SPEAKER_219: That's at $15, right?

David Friedberg: So then you take 15, you take out the cost of buying all these cars 1.5, the cost of maintaining them 400. And you can see there's a big business to be at here. Uh, who knows what the margin would be, you know, but this is incredible. I mean, wow. And what, what I love about this is when we were talking about crypto, we were trying to figure out the use case, right? You, you were in crypto for five years, right? You, you have your, you have almost a, you have, you lost a half decade to crypto. No, no, no, no. I mean, you did okay. You made a bunch of money on your, but my point is as a technology, we, we put all this effort into it. And then you look at what is happening with AI. Like this is actual real value. If you're an analyst, I had to have a whole talk with my team the other day because they were giving me work before doing this.

SPEAKER_22: And I was doing this while I was asking the questions and I'm like, your work sucks. ChatGPTs is awesome. Why don't you use ChatGPT and then come to me with your work after you've polished what ChatGPT has done? And they're like, are we allowed to do that? Is that fair? And I'm like, fair?

SPEAKER_226: What are we talking about here? Like, let's, let's kick everybody's ass into, I think.

SPEAKER_228: That's like going from typewriters to word processors. Like, oh, I can't use it. I'll check.

SPEAKER_02: Yeah. I mean, like literally people are taking white out. People don't know what white, look up what white out is. There was a huge business. Oh my God. White out where you would take a little bit of nail polish and you would, you know, misspelled. If you did a typo, you would put white out in and then blow a drive and then retype over it. Okay. We're not in white out mode anymore. This is a 10 of 10. I could sit here with you all day and come up with examples. Yeah.

SPEAKER_28: And now imagine this thing could put images in there, you know, like, and then I could say here, um, put this in a simple table. Yeah. You gotta share.

SPEAKER_232: You gotta share.

SPEAKER_28: You're doing demos. I was doing demos. I know.

SPEAKER_99: Sorry. I was trying to be gracious here with you. Okay. Put this into a table. Yeah.

SPEAKER_237: That's nice. No, but you don't. Make an infographic. Do it.

SPEAKER_15: Do it different. Do it slightly different. Okay. What I'm saying is you can highlight like a little paragraph on the right hand side. So just highlight, say, say the paragraph that says that no, no, on the right hand side, on the right hand side. On the right hand side. Yeah. Paragraphs is total number of rides. Just, just highlight that paragraph right up a bit. Oh, okay.

SPEAKER_44: Yeah. Highlight that. No, wait, wait, wait. Now see who's just asked you at GPT. Make this more spicy or expand on this. Or just say something.

SPEAKER_241: Yeah. Make this, uh, more concise.

SPEAKER_243: And yeah, make this more concise. Let's see what it does. Yeah.

SPEAKER_44: Let's see what it'll do is it'll rewrite that. Oh, wow. Boom. This is the superpower J Cal. Now you don't have to do it on the left hand side. You can just go to each bit and you can say, yeah, you can say, oh, put an image of that. So you can highlight it again and say, can you turn this into a graphic, right? Of the same paragraph.

SPEAKER_15: Say, I want to see this as a graphic or something, right? Yeah.

SPEAKER_204: Yeah. Pretty amazing. I mean, this is, this is what we've been looking for. Yeah. Well done to the team over there. A plus. A plus.

Chamath Palihapitiya: I've been waiting for this too, because it's so obvious that this is not a difficult thing to do. And this is, you know, I got to give the team over at open eye credit and I got to give the people at Gemini a bit of a warning here at Google.

SPEAKER_22: This entire workspace is dedicated to the UX of chat GPT. You can't do this with Gemini because you shoehorned it into Google. Google should buy chat.com, the domain name from whoever. You've been saying this.

SPEAKER_247: You've been saying that.

SPEAKER_22: And made a dedicated new service.

SPEAKER_18: You can leave Gemini inside of search, but I need a domain name. I go to that's different than Google that does this.

SPEAKER_28: And I can then, it could be, it's, this is powered by Google. You know, it's from alphabet chat.com.

SPEAKER_22: And then have a great app that compliments it on iOS can work on the iOS app first. We'll start releasing stuff to iOS first.

SPEAKER_99: So you get those top users and you know, everything is hidden inside of an app. You ask somebody, how do you get to Gemini? They're like, I don't know. I don't know. Somewhere in my Google interface. I got a hunted pack for it. 100% of the user interface must be dedicated to the AI. But wow. Give us another demo here. This is a great one. Okay.

SPEAKER_32: Thank you.

SPEAKER_59: Awesome. And you're going to, it's getting daily use. You go, the, the weekly active, daily active remain solid for, for, for open AI. Okay.

SPEAKER_252: 400, three or 400 million people a month is what I heard. Yeah.

SPEAKER_97: Some, some 250 or 300, some, some really massive number and a big portion of those paying 20 bucks a month, which is also incredible. Okay.

SPEAKER_44: We're going to just give a quick shout out to Meta and a couple of demos real quick. And we're going to start with one of their models, which we have running on Grok. So I'll just show it there. And so what, what Meta released a few weeks ago, two weeks ago now was what they call vision models.

SPEAKER_15: And so I'm going to give a quick demo here and let me get my screen share going properly. And I just did it before. So I'll reset it here. So let's just clear this out. So basically this, this I'm going to use the 11 billion.

SPEAKER_44: So it's llama 3.2. It's called vision. And so what you can do is, um, you know, you can give it like a picture of anything and you can give it a task. And I'll just kind of turn this down a little bit. And so I just said, so for the folks listening, I gave it a picture of a plate of food and said, tell me everything that's on this plate, estimate the portion size and calories. And you do that. And basically what you'll see here is, and you see how quick that is now. So this is what's starting to happen in this universe, right? Right. Which is we're getting the same models, but instead of, you know, this used to take like 30 seconds, 45 seconds. And, you know, this happened in 300 milliseconds. Right. And so, um, now you have to think about this combined with glasses and other things, Jake, how, where it can, this is the era we're going into where you can be looking at information and the processing of it's even faster than our own brain.

SPEAKER_15: Hmm.

David Friedberg: There is a really interesting, uh, thing. It's really good that you brought up interface on the new Apple AirPods and I'm not an AirPods guy. I'm, uh, I'm, uh, and, uh, I like the pixel buds, but in this new version that I just got the fours with noise cancellation.

SPEAKER_77: Same here.

SPEAKER_44: I got not the interior ones, but the fours are the noise cancel. I got the same ones. Which I prefer. Yep.

SPEAKER_21: Uh, there is, um, a very interesting feature when Siri is going to read you something.

David Friedberg: It says you can shake your head up and down to say yes, or left and right.

SPEAKER_144: I saw that in the settings. Okay.

David Friedberg: Yes. And so it's really compelling. Cause it will say, sunny, just texted you a long text, read the text. And I go, and then when I just nod, it reads it to me.

SPEAKER_262: Yeah. Yeah.

David Friedberg: Or you say no. And it, or it's like, Hey, you're, would you, you, cause I use the walking thing. I like to track my walks as exercise. And it's, it says like, Hey, you, would you like to end your outdoor walk? And I just go, Nope. All right. Yes. And it ends it. So this is becoming really compelling. People are going to start doing shaking of their head, or they'll have something on their wrist to kind of do small gestures to interact with the glasses that we saw from, you know, uh, meta.

SPEAKER_22: And you put this all together, we're gonna be constantly interacting with data and information if we want to, and it's gonna ruin social settings and everything, but it's gonna make people incredible.

SPEAKER_02: Like the idea that in a poker game, you could be wearing glasses. Well, they're gonna have it.

SPEAKER_28: Yeah. You're gonna have to ban them. I, I think we're gonna have to ban those glasses in restaurants, obviously in gyms. Yeah.

SPEAKER_99: And I think I, you haven't been to a public gym in a long time. I go to my YMCA here in, um, uh, in, uh, in Austin. I like the YMCA. It's great.

David Friedberg: Um, well, it's good for, it's like a fun for families and kids and stuff. Um, but, uh, you know, like they ban, I think you can't have your phones out in the locker room, I think. Um, but I mean, these glasses, that's a whole nother level of, um, you know, invasion

SPEAKER_21: of privacy and then also distraction. So do you want those glasses? Do you want the AR glasses?

SPEAKER_53: Yeah.

SPEAKER_44: So, so like, look, I think the era of, um, us, you know, getting superpowers because, you know, other than getting like the brain implant and everything can't be done over audio. So what I kind of think about is what if you're wearing those glasses at work and then it's just analyzing everything you're looking at. So instead of you having to kind of keep telling your, you know, employees to keep using chat GPT, it's just automatically like looking at whatever you're doing and giving you guidance and advice on it. Like, Hey, I can help you make this better. Or what do you think about this? So I think, you know, it has huge implications just in, in that setting.

SPEAKER_00: And you know, like there's a crazy stat someone told me this week, you know, what percentage of people like, like in America wear glasses? Yeah. It's like 60 apparently. So it's, yeah. And so it's, yeah. And so, um, and then, you know, naturally everyone gets old and used to wear glasses too. Right. So it kind of adds up.

SPEAKER_28: I mean, I wear readers because when I'm doing the show, I, I, you know, I want to be able to crisply read it. And if I don't, I have to strain. And so these 1.5s or 2.0s are the same. Yeah.

SPEAKER_275: What did you think of the, um, the hack?

SPEAKER_28: Um, I had the two Harvard kids who built the facial recognition that would then go look up in public databases information, feed it to them. Yeah. And then they were like kind of tricking people into thinking they knew them. Yeah. You saw the demo. I had them on speaking startups this past week with Alex.

SPEAKER_284: Yeah.

SPEAKER_15: What are your thoughts on that? Look, I, I think like when people do that kind of stuff, it's like art of the possible, right?

SPEAKER_44: It, it, it, it's not like a practical thing because, you know, um, at the end of the day, the people that make those platforms won't approve apps like that. And, you know, you can do all these bad things. Like you can sit in front of a store and capture everyone's wifi. Like you, you can do all these like nefarious things all the time. Right?

SPEAKER_03: I think really what look, you know, who I want to have that is like the, uh, security guys at like, uh, uh, baseball or football game. Totally.

David Friedberg: Yeah, no, I know if we started having tech, if we had terrorist attacks, God forbid at a stadium, uh, which has happened in the past in other countries, you know, people would be like, you know what? We need this facial recognition. Uh, James Dolan is, uh, famously installed a lot of facial recognition at Madison Square Garden. Um, and, uh, little controversies there on the margin, but even, um, you know, uh, I, I have a big security system at my ranch and it knows faces. Um, and I put in everybody's face who works at the house. Like, uh, we have a plumber or an electrician. I, when they come to the house, I put their face, I put their name. Hey, that's Carlos. Hey, this is Jane, whatever. Um, and then if somebody comes on the property who we don't know, it tells me and I get a little alert, Hey, there's an unrecognized face or a license plate on the property.

SPEAKER_22: So it knows certain, you know, trash pickups, license plate and others, and that's all coming to corporate software. And then it's gonna make its way down to consumer.

SPEAKER_71: Yep. Yeah. All right. So meta's new vision models. What's your grip? I mean, yeah, I gotta give it a B plus. I mean, it's, it's really solid and it's gonna get better and better. I mean, this, what do you give it?

SPEAKER_44: Uh, I mean, look, I, I think the fact that it's open source for me is a plus, right? You are now able to do in open source, what you can do with the book. Of course, what you can do with the best, uh, models that are there. And I think that's better for society. So I give, I give them an A plus for putting vision models out there. And look, this, think about what it took to make a calorie counting app. J. Cal, probably someone came through your incubator at some point. We didn't want to do it.

SPEAKER_71: And, and look like this did it in 300 milliseconds without. We actually had one years ago, like a decade ago that pitched us that was using

SPEAKER_28: people in Manila. Yeah. Uh, you know, like mechanical turking it, you would send the image. They would look it up online and they would make their best estimate and give it to you.

SPEAKER_22: And they would do it for, you know, two cents or five cents through mechanical Turk.

David Friedberg: And people were paying 50 bucks a month for the service. So, you know, they, even if they abused it and used it 50 times a day, it still wouldn't. Yeah. Match their subscription price.

SPEAKER_300: Yeah.

David Friedberg: Uh, absolutely. Fantastic. And, and, um, w let's pause for a second here. W what does this mean? You know, that the language models are catching up to what open AI is doing the leader in the space very quickly. And there, it doesn't seem to be that much distance between the models. I would say under a year, six months to 12 months behind.

SPEAKER_304: Yep.

David Friedberg: Six months, but the interface six months, but the interface seems to be where open AI is making, you know, really great advances.

SPEAKER_44: So it's really fascinating. And it's a, it's a good point. You've highlighted it, right? I think what they've realized, and I think, uh, their revenue was like leaked and it showed actually more of their revenue is coming from ChatGPT than their API. Basically what I think is exactly what you said, ChatGPT is, you know, um, an open AI are becoming like a consumer facing application. Whereas, you know, meta, and we're gonna do a couple more meta demos in a second is focusing on the fundamental technology and integrating it into their interface, which are consumer facing applications. So what you're seeing and for them putting it out there in the open to make it the community to make it better is important, but their core business is not to be selling, you know, tokens as a service to people or selling intelligence. Right. And so that's the interesting intersection that I see, you know, or maybe crossroads is a better word across what ChatGPT is doing now. And, you know, if you take a step back for all the, you know, let's just call it chaos for lack of better word that's happened at, at open AI. If you think about everyone that's left for a second, J Cal, right? They all, the people that have left been pretty much like were focused, like not on, like, you know, they were there as like kind of a core research types, right? Better for the world types for real open AI. And as opening, I commercializes, it's looking like a different business.

David Friedberg: And so it's looking like an app business. It's looking like an office suite or something. Yeah. Starting to feel like productivity software. It's like, it feels like a sales force.

SPEAKER_53: Yeah. If you're an AI researcher, maybe you're kind of like, oh, well, this, I signed up to work

SPEAKER_59: at open AI and build intelligence for the world. And now these guys are like, oh, we're just gonna build like, you know, commercial product, which is totally fine.

SPEAKER_21: Yeah. And with all this money being poured into it, it feels like this is getting commoditized fast, faster than anything I've ever seen.

SPEAKER_00: That's why them having the users is important, right?

SPEAKER_44: Because I think, you know, having, you know, 200 million paying users. Yeah. You gotta give them credit for that.

David Friedberg: I guess so. Yeah. That is hard to do to get people to take their wallets out. So a couple of million paying users, pretty impressive. But the other point of it is like, I think, you know, using Siri, I've been using the beta and I've talked about it on the show and all in a bunch. I feel like they're gonna intercept the first 50% of queries. Yeah. Are gonna be done by Siri, Alexa, Microsoft co-pilot. Yeah. Google, et cetera. People who already have scale on their devices.

SPEAKER_71: Yeah.

SPEAKER_44: But you're gonna expect that for free versus what we were just doing. You're gonna willing to pay for that. Cause you're like, oh, this is my workflow versus I'm just, you know,

SPEAKER_125: if I'm doing Q and A, I just want it for free. 20 bucks or 30. I think we have the enterprise version.

SPEAKER_217: So maybe we're paying 30 bucks a person and maybe half my people are using it. And I, I think I'm like, if you're not using it at my companies, I don't, you're not gonna be on my companies for long. I just, it's gonna become obvious that you're falling behind for $360 a year. If your average employee is 50, 75, a hundred, pick your business 150, depending on where

SPEAKER_210: you're located in the world, 1% or 0.01% or 0.1% of your employee salary is nothing to pay. It's kind of grossly undervalued.

David Friedberg: If you, if you told me this product was $500 a month, I would pay for five seats. I wouldn't pay for everybody. I would make sure they're using it, but I would have five people on it.

SPEAKER_217: I mean, things like the wall street journal cost $400 a year or something. I don't know what it costs. Something crazy. Um, so Bloomberg can add up. Oh yeah. This is providing serious, serious value.

SPEAKER_99: Um, and I guess canvas and 01 are not available for free. So yeah, I do think there's, there's a case to be made. But if, if, if you're a Microsoft or Google, I'm making all this free. I'm taking everything chat GPT does. And I'm it's the teams you're gonna do the teams and you're gonna. Yeah. I'm gonna bundle it and make it for free. I'm like literally gonna make it super for free and just, you know, take the oxygen away from them. Right. So that people, but right now this, you know, there's no domain name for me to send my team to for Google to go use Gemini like this. Right. And the multiplayer mode is the thing that I want. I wanna use cam canvas with you or with another person.

SPEAKER_71: So when we're building the docket, we're working on it together. Yeah.

SPEAKER_144: That that's gotta be close. They, they can't be, I mean.

SPEAKER_323: Multiplier modes.

SPEAKER_144: Yeah. Yeah. It's gotta be super, but you can already share it with each other.

David Friedberg: It's just. Okay. But then we, it gets forked, right? When you share a discussion, it gets forked. And did you notice when you create them now? It asks you when you share it, it asks you if you want to publish it, publish it. This is gonna be crazy for SEO. Yeah. Yeah. Um, so when you share a link and you copy it, there's a little chat, but there's a little button. It doesn't work with cam canvas, but with the regular one, um, yeah, it does let you share it, uh, publicly.

SPEAKER_99: So that means the, the Google index is gonna be filled with conversations.

SPEAKER_326: I mean, it's wild. Like what about the biggest hack, right?

SPEAKER_327: To get more traffic in is basically just open your index of questions up and then basically everyone's coming to you. It's so smart.

David Friedberg: It's all the work that went into Quora is now they, these, these guys scraped Quora and they're gonna republish Quora a thousand times.

SPEAKER_217: I mean, if I'm Quora, I'm suing the hell out of them. Um, if they, I mean, I don't know what they're paying for.

SPEAKER_332: Maybe they have a deal. Maybe they have a deal.

SPEAKER_204: I think this, this just guts everybody who's got a business is, uh, yeah. Okay. Let's do another.

SPEAKER_00: Okay. Okay. We're gonna keep rocking. We got, we got a few more here. Uh, okay.

SPEAKER_15: Let's go back to, um, and I don't know if you guys did this already. So if we did, we'll, we'll, we'll just go quickly here.

SPEAKER_44: Yeah. So I had this like MIT, uh, management fall 2024 review.

SPEAKER_00: And it's just like somebody had sent it to me on WhatsApp. And so basically I didn't wanna read it. So I just dropped it in notebook LM and it turned it into a 13 minute podcast.

SPEAKER_336: And so, so basically, so like, I'm gonna just kick it off. We'll listen to the first. Hey everyone. Welcome back.

SPEAKER_337: So it seems like you're all about diving deep into how organization tackling change right now. Those MIT Sloan management review articles you've got stacked up. Amusing the NPR voice. Yeah. We see you. Don't worry. This isn't about drowning you in information. We're here to pull out those golden nuggets. The insights that'll really get you thinking. Oh yes.

SPEAKER_339: The insights. And maybe spark some ideas for how to navigate change in your own world.

SPEAKER_340: And here's my female co-host cause we're woke and this is NPR coming to you.

SPEAKER_347: All right.

SPEAKER_346: Okay. Jacob. I actually like. I love it. I love it. Have you tried that mode yet? Have you tried it?

David Friedberg: I haven't used it yet, but I think that it's fantastic that one of the modes of consumption will be make this into a conversation that I can listen to.

SPEAKER_349: Yeah.

David Friedberg: Fantastic.

SPEAKER_226: Like I wanna learn physics, but I don't wanna learn it.

SPEAKER_44: Like reading the textbook or I don't wanna do Q and A with it. I wanna listen to a podcast about it. And so Jacob, the hack that people are doing now. And I'm gonna tell you this is they take their diary, right? And you know, some people diary at different levels and then, or their feelings about a certain situation. So let's say you and I are having a conflict, right? And I go and I write myself like a three page letter of like, ah, these are all the things that like, I love about Jacob.

SPEAKER_352: Yeah. Jake. Yeah. Making fun of me.

SPEAKER_354: Yeah. Exactly.

SPEAKER_357: My money in poker. Yeah. Yeah. And write it all down. And then they put it into notebook. And then they have two people.

SPEAKER_359: And they make a podcast.

SPEAKER_357: Yeah.

SPEAKER_361: Oh my God. I mean, this is. And then you get like a third party view of your situation.

SPEAKER_362: It's really incredible.

SPEAKER_21: I mean, think about this, like for a coach kind of situation or a therapy kind of situation or a mediation situation. It's kind of in that zone.

David Friedberg: And I had a lot of people pitch me on coach, not coaches, but like therapists, like virtual therapists. And we had some spicy ones that were on earlier, like a year or two ago.

SPEAKER_18: So there is something here of being heard is a human, very cathartic for humans when you feel heard. And that's why I think, you know, if the AI can pull this off in an authentic way and it makes you feel heard. Um, that could lower people's anxiety where they're like, Hey, I'm having feelings of jealousy.

SPEAKER_22: I'm having feelings of anger towards my boss. He's a jerk. His expectations are high. He's giving me a hard time about air pods and all this stuff and how to do like perfect production or whatever. Yeah. Oh, my boss is. Wonderful. Whatever. It's like, oh yeah, you know, but your boss just wants you to get the best out of, you know, that the company just wants to produce great content. There's a reason why, you know? Yeah. Okay. Now I can sleep at night.

SPEAKER_99: You know, like, it's kind of cool actually. I have no judgements. Like, I think it's kind of cool that people can find.

SPEAKER_44: So I want you to try it this week, Jake. I want you to diary one day and I want you to put it in there. And then we'll do it next one. We'll do it actually. Yeah, absolutely. Okay.

SPEAKER_374: All my feelings. Yeah. From one day, do it after you record the all in pod. Absolutely.

SPEAKER_376: You're doing great. Oh, I, I, I, I give that one a B plus. I think it's like a cool feature.

David Friedberg: I don't think it's gimmicky. You're going to try it next week.

SPEAKER_377: You're going to try it next week.

David Friedberg: I will try it. But I'm giving it a B plus because I don't think it's a gimmick. And I think there's, if they did podcasting, which feels like a gimmick, they could also do a therapist.

Chamath Palihapitiya: They could do a coach. They could do a best friend. They could do your mom or dad.

David Friedberg: And that's where I think this could get really interesting is if you took whoever the great advisor or friend you had in your life was, and then you capture them. Like, I mean, that could be very special for people. You know, if your grandma always gave you the best wisdom and advice. Yeah. And then you said, Hey, here's everything grandma. Like, and grandma was one of us with a big online footprint. Right. Or you just had AI talk to grandma before she passes for an hour a day and just asked her questions.

SPEAKER_22: And then you could say, Hey, I got grandma forever.

SPEAKER_380: Yeah.

SPEAKER_22: Like, I'm actually getting a little sad about it thinking about my dad. My dad's sick. Yeah. So I've been thinking about it and like, you know, him being gone and whatever. Yeah. How long he's got left. He's 81. You know, he's a cancer survivor. Like, I'm like, ah, my mom and dad, I want to capture it.

SPEAKER_385: So I was talking to my little brother, like, Hey, maybe we should do like an interview series with my dad. Yeah. Just record it. So we have it for our kids.

SPEAKER_132: Just record, just do it. No, honestly, just record it.

SPEAKER_44: And then, you know, the rest, turning it into AI and all is super easy, but just record it. Just go and do a couple hours and you'd be surprised.

SPEAKER_15: Yeah. And do it as in like, I would say, do the history of the family from his perspective, and then do, you know, like top, top big moments of his life. I need the prompts.

SPEAKER_28: I need like to get the prompts. Yeah. So I think that's something where I.

SPEAKER_390: Ask chat GPT for the prompts, dude. I know.

SPEAKER_22: I was thinking chat GPT Canvas would do it for me and get all the prompts together. And then I could actually have chat GPT do it with him.

SPEAKER_391: That would be very interesting too. Yeah. This would be a great business. I don't know why this doesn't exist.

SPEAKER_00: I think some, I think some folks will do it, but like, but what I know, what I think you could do is just give the prompts to him and then have, you know, some combination, you know, of Josh or someone just go sit with him and record him. Like he can just read out the questions. He doesn't have to come up with them. And then he answers them. And then, you know, I'll help you do it. Jacob, if you want to do it. I think it's a great idea. Last two, last two. Okay.

SPEAKER_44: So they've created a movie gen model. And, you know, just to kind of show you like what it's capable of. It's, you know, yeah.

SPEAKER_00: And look like, you know, we've seen this stuff before, and this is tied into some of our bets. But like, I think this is just getting better and better and better, right?

David Friedberg: The fidelity is getting there where if you weren't paying attention, you would think it's real. Yeah. And obviously a koala surfing, you wouldn't think it's real, but the stuff that's not koala, you would think it's real.

SPEAKER_00: Yeah. Like, that's pretty good. And, you know, we're just kind of looking at some interesting videos here. And then you can edit them with text, right? Yeah. You can have this video and you can say like, hey, add pom-poms to this or replace this person with a dinosaur. And then, yeah, this produce personalized videos. Like of like a picture of yourself saying, hey, make me a, you know, scientist doing something with a, you know, beaker or whatever it is. Soundtrack, sound effects, pretty incredible where this is going. So it really shows the power of them and having lots of data like they have. And they haven't released this to everyone, but it's very, very exciting.

SPEAKER_15: So maybe we don't grade this one yet because it's not released, but it kind of shows the power of what's potentially coming our way.

Chamath Palihapitiya: And that's Meta's video version.

David Friedberg: Yeah.

SPEAKER_202: It's called Meta Movie Gen. Meta Movie Gen. Yes.

David Friedberg: Amazing. I think Zuckerberg's, you know, really doing something special here with this open source stuff. I think we're going to look back on this and be like, hmm, this is, uh, he, he made a strategic, he made a very strategic decision that I think is going to pay off massively for him.

SPEAKER_401: I, I completely agree with you. Okay. Last one here is, uh, and that one's a B plus too.

SPEAKER_119: I mean, okay.

David Friedberg: With the processing speed of these is the other one I'm wondering about is like, remember they were all limited to five seconds. And have they gotten past that now?

SPEAKER_402: No, they, they haven't released them yet.

SPEAKER_44: I think that's what they're all kind of working on. Right. And so the last thing here is like Meta AI. I don't know if you use it J Cal, you, you should. And, and, uh, you know, it's kind of like their, their chat GPT. Now it's designed a little bit more for fun than it is for, I think kind of like the workflow stuff that we were talking about, but where it's super powerful. And, and I'm just going to do this.

SPEAKER_15: I got a picture of you and what you can do is you can give it a picture and this is like a more modern one. And then you can say, edit this image and you can say, uh, make me bald. Right. And what you'll see is it's like so powerful.

SPEAKER_44: Um, that like, you know, all these image, um, things that were coming out the last couple of years, they've combined all that functionality. And basically just, you know, this is like J Cal, uh, Mark and Mark entries.

SPEAKER_252: I don't actually, I kind of look good bald. I mean, it's, it's a look, I look like I'm, um, yeah. Yeah.

SPEAKER_405: Yeah.

SPEAKER_22: Who is that guy, uh, who played the crazy guy in the M Shyamalan, M night Shyamalan series. There was like glass.

SPEAKER_99: And then there was the other one. And then there was this guy who plays like a guy with multiple personality disorder. I think it was James McAvoy playing him. Okay. But I look like professor X. I like it.

SPEAKER_00: I like my professor X. Yeah. So yeah. So anyways, like, look, that's what you can, that's what you can do here. And you can say, you know, as you can say, give me a, uh, beard. All right. Oh God, here we go.

SPEAKER_97: Yeah.

SPEAKER_411: I can never grow a good beard.

SPEAKER_410: Yeah.

SPEAKER_411: For some reason it's not, let me go back and do it.

SPEAKER_97: Let me, I might have to just re upload or restart again here. Yeah. Um, yeah. That's hilarious. Yeah.

SPEAKER_44: And so, um, yeah, so you can say, uh, but it's, it's, uh, you know, it's like, uh, you know, it's gonna be a lot of fun.

SPEAKER_287: Uh, I mean, and then I think they're gonna have to start watermarking these.

David Friedberg: Correct. Because like, what is reality? Like we don't make people watermark face tune up or those tune up things that I know.

SPEAKER_418: No, we don't. We don't.

SPEAKER_419: We don't.

SPEAKER_00: Yeah. Yeah. So look, I think, you know, and you can do all kinds of fun stuff with this. We're just playing around here, but, uh,

SPEAKER_420: I can, this would be solid B.

SPEAKER_00: Yeah. But you know, they've, they've taken all the image, image editors and all that. Oh, that is not a, so that would be a good job. I mean, that actually.

SPEAKER_02: I look like a Hitler. I like, Hey, would you like a soy latte? I feel like I'm making you a crab cocktail. If you put suspenders on me.

SPEAKER_22: I was gonna say crab cocktail, crab cocktail.

SPEAKER_422: Yeah.

SPEAKER_22: I'm gonna make you a smoky old fashioned with a lump of sugar in it and, uh, whatever. Yeah.

SPEAKER_424: Yeah. I'm gonna make you an overpriced cocktail. Let's go in Austin. There's a bunch of places in Austin. Yeah. There are. They're big into cocktail culture here.

SPEAKER_427: Yeah. And that mustache beard. And that mustache beard. Yeah. That's a waxed mustache. I look like a super villain.

SPEAKER_431: Exactly. Exactly.

SPEAKER_28: Yeah. All right. All right. Well, this has been an amazing episode. Welcome back. Uh, let's do it every two weeks. You gotta store all these up and we're gonna get dialed in here.

SPEAKER_22: Uh, and, um, he is, uh, Sandeep x.com slash Sandeep. I am x.com slash Jason and get, let's give a little promo here for Grock. Yeah. You got tons of developers. Anything coming up on the calendar?

SPEAKER_306: 500,000 developers. You know, we have the fastest automatic speech recognition.

SPEAKER_15: So look, Jacob, one of the things that we can do if you, if you haven't done it is we

SPEAKER_44: can take almost all of, uh, all we could take all of, uh, this weekend startups. 2000 plus episodes. Yeah. And we could, uh, and we do it at 250 X real time. So basically, you know, whatever timeframe that is. So let's say that's, uh, you know, 2,000 hours divided by 250 and that much time we can turn it, we can get transcript for it. Love it. 10 hours. Yeah.

SPEAKER_144: We can do it in 10 hours. Yeah. Unbelievable. Yeah. We'll find out more about Grock. Just go to grock.com. G-R-O-Q.com. All right.

David Friedberg: And we'll see you all next time on this week in startups.