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>> Today is Monday, September 21st, 2026.
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We are live at the TBPN Ultradome, the temple of technology, the fortress of finance, >> the capital of capital.
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TBPN's road to Christmas. Started weeks ago.
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We got 94 days until Christmas.
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Double >> in double digits. >> We're so close.
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Every day one day closer to Christmas. So get excited.
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Start shopping for presents.
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Start picking out that Christmas tree.
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>> Let me tell you about ram. com. >> Time is money. Save both.
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Easy easy to use corporate cards, bill [applause] pay, accounting, and a whole lot more. They got musicals.
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I guess they do in musicals now.
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And I guess we do in AI safety now.
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We'll get into that >> later.
0:46
Doing a bit of a show today.
0:48
Yeah, we got Augustus Dico coming in with a hundred million.
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>> Tip of the hat for a hundred million. Right. >> We have a node Kosla.
0:55
Manode Kosla's coming on coming back >> Levy breaking his silence on the SAS rebound new model drops the latest on open source and more.
1:07
>> We have Ron from I Connections.
1:07
Uh they are putting on an incredible show in November that we're going to be at called Tomorrow X.
1:13
Uh excited to talk with him about that.
1:16
And then we'll round it out with none other than Ben Hilch coming in with a new round of funding as well >> for Raindrop. Um, >> Raindrop. >> How was your week? >> Drop top. >> Yes. Oh, yeah. Good name for a company.
1:30
Uh, how was your weekend?
1:32
>> Uh, it was couldn't have been better. >> It was good.
1:34
Uh, we were off on Friday.
1:36
We went to Boston and back basically the same day.
1:39
Sort of a brutal flight back and forth.
1:41
A little tired, but >> terrific.
1:43
>> I got completely oneshotted by the new AI video model. Seance 2. 5.
1:49
Gone are the days of uh face swaps.
1:49
I remember when uh it was called dream booth.
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This paper came out from Google and it allowed you to very realistically swap your face into a photo.
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Now this is something you can just do with a single prompt but uh today but back then you had to go and take 10 or 20 different photos of yourself at different angles, different lighting.
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Usually just dug through your camera roll, got them.
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Then you had to feed that into like a Python script that was either hosted on uh uh what's what's their notebook?
2:20
their hosted IPython notebook collab collab and then the collab thing was weird because it was a luck of the draw what GPU you got.
2:30
>> So you would like sign up and create an instance and then sometimes it would just be like you got a 1080 Ti and you'd be like I can't do what I need to do because I need a lot of memory to do a particular thing and then sometimes it would be like you got an A100 brother like lock in like it was just random provisioning and people would be like so excited when they got one or the other.
2:49
Um, but there was this musician who was like a guitarist who implemented the paper and then and then uh basically distilled it down and figured out how to run this is a crazy thing, but this guy who's just like a hobbyist machine learning engineer figured out how to get Dream Booth running on like basically commodity gaming hardware.
3:06
So then you could go and you could take your face, fine-tune it, and then be able to generate new photos in the style of whatever.
3:16
Uh it was all built on uh that open source one not midjourney the other image generator Ahmad Mustach was stable stable diffusion.
3:25
It was like stable diffusion as the base and then this dream booth thing on top.
3:28
Uh and it was super cool.
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Uh cuz if you actually went through if you jump through all those hoops uh you basically had access to the magic avatar thing like three months before everyone else and you could like send one to a friend and be like, "Oh, this is cool."
3:42
Uh and then it was just completely commodified.
3:44
uh it became an app and then it just became available in every chat app uh very shortly after but the AI video has been moving a lot slower.
3:52
It's very comput it's very uh compute intensive obviously since uh opening I had to shut down Sora and uh it just feels like none of the major American labs are as focused on this.
4:01
So uh I got completely addicted to this.
4:06
Had a lot of fun doing it.
4:06
I'll walk through everything that we did.
4:07
Um, but uh, >> yeah, there was one point where you sent me like 10 videos back to back of me in various AI scenes and then I was just sending you some like pretty mundane commentary back and then and then I was like, whoa, okay.
4:21
On something totally different. >> Oh, yeah.
4:24
Yeah, >> I was like, "Oh, sorry.
4:25
I need to respect your culture and actually respond." >> Yeah.
4:29
Well, it's because like you no longer need to go get a different app or sign up for anything.
4:33
you I like I was just texting with codeex remotely.
4:35
I had a PC that was running this and then I would just be like I didn't even say take this video.
4:42
I would just say like go find some videos and put Jordy in them and it would just do that and and I didn't even have to like upload photos of you.
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I would just say like go find some reference photography for Jordy across the internet and it would >> and so far it seems to have made a lot of sense not to focus on video given that codecs and claude can connect into all these other tools and models and just give you what you want as a user without incurring any of the cost of focusing to make great models or the actual cost of of serving them and having to allocate you know GPUs. >> Yeah.
5:15
So I think people will be having fun.
5:17
Oh, speaking of Codex, let me tell you about Codeex.
5:18
Codex is a powerful workspace for getting work done with AI agents.
5:21
Whether you're writing code, analyzing data, creating content, creating some of the videos I will show you shortly or automating business workflows.
5:28
Codex helps you move projects forward from start to finish.
5:30
So, uh the latest turn of AI AI video models like they're really really good not just for the high fidelity stuff which we'll show you some of, but even going back to like '9s VHS footage, it can edit anything and it doesn't look weird 90% of the time. uh C dance 2.
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5 the the big update here is that it replaces the whole person the whole object as opposed to just a face swap which just it it just hits way harder.
5:54
You you'll see uh and it matches all the subtle details of the footage so things integrate really nicely.
5:59
Uh Dylan Patel posted a video of him as Drake in this uh cheetah print video over the weekend and I think a lot of people fell for this. >> It tricked everyone.
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I I think it tricked a lot of people because it's super high fidelity.
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Let's play semi analysis latest post on X Dylan Patel as Drake.
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And what's interesting about this is the video model's really good, but also this Drake video came out a day ago.
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And so it's not it hasn't saturated the internet.
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Like a lot of people a lot of people hadn't seen it.
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>> This is the first Yeah.
6:32
I I saw this video before I saw the actual Drake music video.
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And of course, the choreography is is fantastic in the underlying video, and that drives the motion. >> Maybe mute the audio. >> Really?
6:44
Yeah, we're probably going to get fun as it is.
6:45
Um, but it's so funny to see Dylan walk around and that first shot really sells it.
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It really looks like him.
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Later on, he goes into the mirror.
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Uh, he walks up the stairs.
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This is this is what the model is really good at is uh even though he's very small and he's behind uh like the uh the that chandelier cuts in front of him. There's no aberrations.
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This part his face starts to look a little not like him.
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There's a little bit of Drake like sort of sneaking back in on the facial structure.
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But uh overall very very uh like incredible performance and it does a good job whether he's looking away from the camera, whether he's big in the frame or small in the frame.
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And it and I I can't stress enough how funny it is that so many people like so many people were dunking on this [laughter] saying, "Wow, this is the top.
7:32
We're definitely closer to to the top than the bottom.
7:37
Never become the main character serious. He's not serious."
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>> It's like one, Dylan has never had the most like serious brand. He likes to have fun.
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But two, the fact that it was tricking everyone shows that >> shows where we are. Shows where we are. >> No, seriously.
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Like this is this is exactly what you want from the semi analysis.
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[laughter] Like you want them to analyze.
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>> We just updated you on video models. >> Yeah. Yeah.
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>> And and and the idea that the idea that >> the idea that Dylan which they use so much AI they use so much AI on anything. Everything.
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I've I even texted Dylan recently.
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I was like you should get an actual creative director maybe use less slop you know.
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Um [laughter] it but the idea that he would just like take 48 hours in a $100,000 budget to go and film this >> the day after Drake drops the video is crazy.
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But if he did like he is like obviously he's in like an analysis business, but he's also an entertainer.
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He also has to fill the top of funnel newsletter subscribers.
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Like he has to be front and center.
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And so it's actually not that crazy.
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Like even if he did this by himself, I would just be like respect. like that. That's a fun project.
8:44
But of course, he's using AI. He's using CDN 2. 5.
8:47
Uh Higsfield wrapped CDN 2.
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5 in uh in a model that sort of uh a harness that sort of makes this a little bit easier.
8:56
You can use that via the API.
8:57
It's also available on fall.
8:57
Uh and there's a couple other ways to interface with it.
9:01
Uh but it's interesting because it's it's highly compute intensive.
9:05
China's obviously way behind on compute.
9:07
So what's going on with the strategy?
9:09
But before we get to that, uh it's really fun. fun.
9:10
So, we got to play some of the more videos that we made.
9:14
Um, so I had Codeex finding uh famous or funny videos to use as bass clips.
9:19
I would just say I I started with the rap videos. Did a couple of those.
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I think there's one maybe in the timeline >> Noah in the X chat says no headphones obviously fake. >> Oh, true.
9:28
[laughter] Yeah, that's a good point.
9:30
Yeah, you got to have the you got to have the headphones to make it believable. Dylan Patel.
9:33
Uh but yeah, let's see if we can play the uh the video.
9:38
Uh is did Did that one make it into the production chat?
9:40
Uh yeah, this one cuz I saw this originally with Elon Musk and Sam Alman uh rapping and I think we might just because of swearing.
9:51
>> But what's interesting here is that it does a pretty good job of getting us.
9:54
But there's moments when I sort of blend into to Elon Musk, which is funny because it's not like it's originally an Elon video, but clearly the underlying video that was driving the AI model was the Elon and Sam version.
10:06
And then our heights kind of change like I look a little bit more like Elon there. It's very silly.
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Um but uh but but but very very funny gonna fool a lot of people.
10:18
Uh but uh also then I was able to just say like okay go make a bunch of tech videos like just find iconic videos from tech.
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And it did it and it found like sweet baby rays.
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I didn't tell it to go get that video but it just did it. Uh which was very cool.
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Some of them came out really well.
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Some of them didn't do too well.
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Uh the one that I liked uh I think the most >> and it's a funny dynamic that we noticed where when you're looking at an AI video of yourself, you're thinking that doesn't look like me and then when other people look watch it, they're like, "Wow, that looks exactly like Jordy." >> Yeah. Yeah.
10:51
So, let's watch Jordy introduce the MacBook Air as Steve Jobs.
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I don't think actually Apple kind of bans everything. So, we'll see.
10:59
We'll see if this one gets flagged, but we might be we might be cooked on this on this particular one. But, let's play. I said video is solved. >> Roll the dice.
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>> The post is Yeah, let's roll the dice on this one. Video is solved.
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Uh Jordy Hayes introducing the MacBook Air.
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It's already got 350 likes on Axe. Let's play it. Boom.
11:17
So, it didn't change the voice.
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So, you still hear Steve Jobs's voice, which is also funny about the Dylan telling because it's Drake's voice.
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So, it's like, what did they think happened?
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He's like lip-syncing to it or something.
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That didn't make any sense.
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But what's really cool about this is that it changes Jordy, the small Jordy and the big Jordy.
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It it changes both of them in the same frame.
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And then even there, you only see a little bit of Steve Jobs mouth.
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And it was able to change that to Jordy.
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So it can represent what's going on outside of the frame.
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And historically, that's been very difficult for AI models.
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They want the face in the center of the frame.
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They want to be able to crop it and think reasonly reasonably about it.
11:57
But it did a good job there.
11:59
Uh Jordi as Jensen taking the uh >> GPUs out of the mass for this one.
12:07
>> Yeah, it's very funny when you when when when you use a different person with a different stature, different musculature like they it just comes across differently.
12:15
Uh but very funny clip, iconic when Jensen announced uh was this that H100 announcement, the A100 announcement?
12:22
It was pretty early, but uh >> for a while.
12:27
>> This is still such a funny gag that Jensen actually did this. I love it.
12:35
[laughter] >> He's really grunting.
12:35
I mean, that's a heavy rack. >> Got here.
12:38
It's the world's largest graphics card.
12:41
[laughter] >> Such a funny bit that he just did this in a kitchen. It's so good.
12:46
>> Something I got to show you.
12:47
>> I got something I got to show you.
12:48
[laughter] Jensen's such a such a master performer.
12:52
Uh we saw that on stage at uh at Salesforce Agent Force uh last last week.
12:58
Um the last one that I did and before we pull up the Jordius Steve Balmer which is particularly hilarious.
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Let me tell you about console. com.
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Console builds agents that automate 70% IT HR and finance support giving employees instant resolution for access requests and password resets.
13:18
Uh, this one I I specifically told it like keep the sweaty the sweaty shirt and so I think it did more of a face replacement.
13:25
So the face is sort of jumping around but >> still very funny. key to.
13:28
net, the key to industry transformation, the key to success is developers, developers, developers, developers, developers, developers, developers, developers, developers, developers, developers, developers, developers, developers.
13:49
>> It really got like the level of sweat on your face pretty correct, but the face is jumping around.
13:54
Uh, not not quite not quite dialed.
13:57
I think you'll have to perform that one IRL >> and I should I should run that build at some point.
14:04
>> You should you should bulk to get to get to that level for sure. For sure.
14:06
Um so uh yeah, I mean downstream of this obviously there's going to be the uh the it's over for traditional filmmakers blah blah blah.
14:15
Uh then obviously a whole bunch of blended work that uses the right tool for the job.
14:19
Uh some productions will use this where it helps in urgent scenarios.
14:23
I think some of the stuff is already actually being used in Hollywood specifically for re-shoots.
14:26
Uh about 10 years ago, Henry Cavville was in was uh was in Superman and he left Superman. They wrapped production.
14:35
He went to film Mission Impossible.
14:37
In Mission Impossible, he has a mustache.
14:41
So, he grew out a real mustache, was filming Mission Impossible, and they were like, "We didn't get the shot for Superman.
14:46
You got to come back and film another scene as Superman."
14:50
And he was like, "I can't shave my mustache."
14:52
And they were like, "Okay, we'll fix it in post."
14:55
And uh in the newsletter, there's a photo here that we can pull up of how it came away.
15:00
Because they had to remove and reconstruct his lip and his mouth using 2017 technology, and it was not good. It was very, very rough.
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Probably very tedious, very expensive.
15:12
>> Isn't a mustache like the easiest thing to to apply? >> Oh. Oh, like fake.
15:17
Like you should have just shaved it and then put on a fake mustache. Yeah. >> I don't know.
15:21
I think uh Mission Impossible, they wanted the real thing.
15:24
So yeah, uh the the the the Superman on the right is Henry Cavl with a mustache that has been removed in post and it was uh yeah, widely widely critiqued by the VFX community.
15:36
So you can imagine for stuff like that, uh this these tools will creep in very quickly.
15:40
Uh for most things, it's going to be okay.
15:43
Well, if you needed someone to drive the video, why don't you just have the actor do that?
15:49
Uh maybe for stunts and stuff you'd do it, but for most performances I think you'll still be doing it the old way, at least for the time being.
15:55
Um >> what about some of the other more actionoriented? >> Yes. So this was a fun one.
16:01
I had to go and pull Johnny Knoxville and Steo clips throughout the throughout their film making and TV >> generational run. >> Their Yeah. their entire run.
16:11
Make about 20 of them and then put it together into a trailer that we can watch now.
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And I really enjoyed this.
16:20
[laughter] We got to do that in the office.
16:23
I think Tyler was thinking about getting that.
16:27
[laughter] was terrifying getting in a cactus. I don't know.
16:41
I've never really been poked by a cactus. The hands on the bikes.
16:42
I don't know how the guy on the left wins.
16:48
Of course, a lot of Steo in that one. A lot of Steo here, too.
16:54
But I think these work so well because a lot of the underlying footage looks like AI. It look like this. >> The prompts.
17:00
>> This looks like an AI prompt like like drive a a jet ski in a pool in a luxury house, you know?
17:06
This looks like >> This is real though. This is real. We actually shot this. >> Yeah, this is real.
17:10
No, the only thing that's different about this is the suits.
17:13
We replaced the characters.
17:13
Um, but the underlying footage is all real.
17:18
Uh, from Johnny Knoxville and crew, the fire hose rodeo. This one that looks fun.
17:23
[laughter] >> Just dying laughing.
17:30
>> The old alligator in the house.
17:32
>> Like the the old alligator in the house trick.
17:34
I think they chilled that guy down, so he was real slow.
17:41
>> And then the the bull run slammed.
17:46
>> I didn't know Rams were so aggressive.
17:48
The ram just slam that guy.
17:50
>> It's in the name, John.
17:51
>> I know, but I think of them.
17:51
This looks like an AI prompt, too.
17:53
Boxing match on stilts, but replaces the suits.
17:58
The gag chair that falls apart. That's a classic.
18:01
all time all time favorite classic.
18:10
>> Then I come up and Hey, don't don't don't steal that.
18:12
The old the old air horn while you're golfing. Classic. No, this is a good one.
18:25
Going through the window [laughter] soup.
18:31
just asking someone, "Hey, can you go grab the six bowls of soup on a tray and bring it in?"
18:35
Okay, that's just pure Johnny Knoxville.
18:37
So, yeah, sometimes you get like a blended half the main character, half who you tried to replace.
18:43
Sometimes it's pretty good.
18:45
There's a little bit of there's a little bit of us in there, but uh but very fun to be able to just just do this in uh via text.
18:54
Like you don't even I mean I'm technically interacting with an API but I didn't write a line of code. >> All on your phone. >> Yeah. All on my phone. So uh very very fun.
19:03
I think these things will sort of burn through pretty quickly.
19:05
Like everyone will be like oh yeah like that.
19:09
Like that's the capability.
19:09
Everyone did their version of the meme and then uh and then it becomes more of a tool melts into the background. >> Yeah.
19:15
You already saw this with all the Young Lean music videos. >> Yeah.
19:18
Kind of made the same thing and now it's >> and now it's like played out.
19:20
But a very impressive demo. tip of the hat.
19:24
>> Tip of the hat to Eileen.
19:24
Um, but a very impressive demo because it's able to replace multiple people and and do it very consistently even through like some really aggressive motion.
19:32
So, I thought that was pretty cool.
19:34
Uh so the the whole pipeline here was uh I was running codecs on my PC interacting with that from my phone the chatd app and then I had codeex go and uh uh generate reference images with just chatbtdt images because it's pretty good at that and then use those to swap through seed dance which was uh which was actually rendered via Higsfield.
19:57
Higsfield uh amazing in terms of just delivering the assets like as an API extremely confusing as a product because they basically have two ways to give them money.
20:09
You can you can load up API credits and then you can like buy a plan and so at one point I ran out of API credits and it was like time to upgrade to the plan and I was like okay cool. I'm having a good time. I'll do more of this. Click the button.
20:21
I'm like, "Okay, yeah, you loaded up a couple hundred bucks in here with like the ultimate plan or whatever."
20:26
And then it's like, "Those credits are not available in the API."
20:30
And I was like, "Great, thanks."
20:34
And then and then it was like, "Okay, time to add some credits to your plan."
20:37
I was like, "Okay, this is what I need to do.
20:38
I add credits to the plan."
20:38
It's like, "Those credits are on your plan.
20:42
Those aren't API credits. Those are plan credits."
20:44
And so I have like so much random money stuck in various pieces of API.
20:49
Well, and I think that's been a massive complaint.
20:50
Uh the Higsfield has faced a bunch of I think various allegations over the last year around just [laughter] like >> I mean the website looks like a gambling company.
21:00
It'll be like countdown 10 minutes to claim 75% discount on your next credit.
21:05
It's like it's totally optimized for like brain rot as you go through the flow being like oh buy you got to buy a plan.
21:12
>> I had seen stuff of like you can't you know not not being able to actually cancel your plan.
21:16
So now that you have a plan that you can't use for anything It's over for you. >> It's over for me. >> It's over for you.
21:20
You're a customer for life.
21:23
>> But the products, >> great entertainment. >> Great entertainment.
21:25
And I do think uh yeah, I I I think I might try Fall again as as more of like a cleaner API that's a little more intelligible.
21:32
But um but yeah, I I think once you set up the bindings and get them all uh dialed in in Codeex, I think >> Ellie says, "Looking mighty sus and mysterious today, chaps."
21:44
>> Well, >> well, this is the era that we're in.
21:47
>> This is the era that we're in.
21:47
You got to take a safety era.
21:50
>> You got to take a hat a hat seriously. >> Safety era.
21:52
>> Um, >> John, once a week, John's John's like, >> I think I think fedoras are going to come back.
22:00
I think fedoras are going to There's nothing fundamentally wrong with the hat.
22:04
>> I do think the hat can work if it's styled properly.
22:06
I think it goes better with a suit.
22:08
I think it goes better with some sunglasses, a jacket. >> John says, "Mafety." [laughter] >> Safety. >> Uh, no.
22:15
I mean like like obviously the fedora is is often l uh uh often maligned as as not particularly stylish, not particularly modern.
22:24
But if you go back to old state James Bond, there was a way to make us to make a fedora look very stylish.
22:31
Now we are wearing relatively cheap fedors.
22:32
I think you drop a couple thousand dollars on a Bayga Roman weave fedora.
22:36
It's a different conversation. >> Different story. >> Different story.
22:40
Uh no, I I I think it can be done.
22:42
I think it can be done properly but uh it requires a discerning eye some taste.
22:46
Taste is the new moat in AI.
22:48
The fedoro will be a piece of that story.
22:51
Uh anyway, let me tell you about public investing for those that take it seriously.
22:55
They got stocks, options, bonds, crypto, treasuries and more with great customer service.
22:58
So my questions my questions my questions about cedance 2. 5.
23:03
I was like how is China winning?
23:07
How is China winning in this?
23:07
Like they have one the compute one. Is it that simple?
23:12
And then also, why aren't they open sourcing it?
23:15
They love open sourcing everything.
23:17
They're like, "We love open sourcing except when we're on the frontier." >> Yeah. Good.
23:22
>> And there's a weird dynamic there.
23:22
So, first off, did some digging, got some answers. Let's dig into it.
23:26
Um, at a high level, intellectual property rules are somewhat flexible over there. That's true.
23:34
[laughter] But the models are insanely computensive.
23:37
insanely computensive. like it is even if you're like I don't care about Hollywood IP come sue me in China good luck you're still like there's still a finite amount of compute and so why aren't you on the RSI trajectory why aren't you working on coding models like
23:54
why don't you just take that compute and put it on the next GLM run or the next Kimmy run right um well there are reasons for that uh first is that bite dance has a more natural flywheel here than the leaders in America So, Anthropic and OpenAI do not have good surfaces to deliver video, AI or not video. Like, OpenAI tried with Sora, got
24:14
Like, OpenAI tried with Sora, got a decent amount of people to use it, but it's but it was not the obvious flywheel that Bite Dance has.
24:20
And so, over in China, Bite Dance is a is a big company leading, and they have Tik Tok, Duian, Cap Cut, ads, e-commerce, recommendation systems, tons of immediate benefits to the core business without needing to pull together a new demand surface for video.
24:36
This sort of exists in America with Meta and Google, right?
24:38
But AI slop is deeply unpopular in America.
24:42
Although I would debate whether or not this is this is slop this is this is sloppier than some of the videos we showed you.
24:50
Um but uh both companies DeepMind and uh and and MSL they are on the RSI trajectory.
24:59
They're focusing on agentic workflows, personal agents, knowledge retrieval, coding, uh, recursive self-improvement, AGI.
25:07
They are, it feels like they are more AGI pill than bite dance, which is like, look, we got a good thing going with Duian and Tik Tok.
25:15
We got a lot of video space.
25:15
Let's dominate there because we have an uh because we have an opportunity.
25:19
Uh, and and also like the the AI the IP infringement thing is not actually dead to rights.
25:27
They haven't necessarily been caught in any major way.
25:28
It's just that the when the model comes out, people are like Tom Cruz and it's like perfectly Tom Cruz and so it's like what's going on here?
25:37
So some of that could be the the outputs and the harness that actually like reviews outputs like because there is an argument on fair use for training to include everything especially when you think about Tik Tok.
25:52
So people go to Tik Tok and they upload clips from movies.
25:54
Some of those are fair use, some of those are transformational.
25:57
Like you can actually make a vibe reel from uh from Top Gun that is transformational and passes the fair use test, which is that it's not a replacement.
26:06
So you're not like why would I watch Top Gun when I could watch 30 seconds of Top Gun edited like like a crazy hyperlapse edit.
26:13
Um so it's not it's not competitive in that way.
26:16
It is transformative and it provides some commentary layer on top.
26:20
So that is actually okay.
26:22
You can use clips from movies if you're comment if you're commenting on the lighting and you're trying to explain the lighting.
26:28
All that means is that some of that data goes onto TikTok and lives there forever and Hollywood can't say anything about that. Same thing with YouTube.
26:35
Same thing with Instagram.
26:37
There are plenty of uh film criticism channels that post barely long clips from movies completely acceptably and they don't even need to share revenue because it is transformational. It is open. Uh it is fair use.
26:47
And so so they have the they have Hollywood IP in the training data. They can train on it.
26:54
Now there's a question about what the output should be.
26:57
You still own your likeness.
26:59
And so even if you can perfectly uh recreate something, you might still get sued.
27:03
Uh Google has a we we tested this out.
27:06
Google has a uh has a music uh generation service and if you go and say like I want a Madonna song.
27:14
Clearly YouTube has all the Madonna songs in the catalog.
27:16
they can train on them, but it will say, "I can't exactly make a Madonna song.
27:21
I can make a pop song that's generic. Here you go."
27:23
And that doesn't pull enough from Madonna to get sued, at least in theory.
27:28
We'll see how it plays out.
27:29
Um, and so, um, and then also like a lot of people just upload full movies to Tik Tok and stuff and they'll just be like, I uploaded all of Lord of the Rings and even though that probably gets taken down, it goes through by dance servers, might get saved somewhere, might get like soft deleted like like it doesn't exist on you can't watch it on TikTok, but it still exists on the server.
27:49
So, so they have a lot of data to train all this.
27:53
Um, but they're not open sourcing, they're not doing open weights.
27:55
They're certainly not open sourcing the the training data set.
27:58
uh and it's a little bit of a narrative violation from the default Chinese AI strategy.
28:02
Uh there are a few reasons for this.
28:05
First, no one wants to open source when they're in the lead.
28:08
We've just seen this time and time again.
28:09
Uh and second, with coding models, open weights are a play to build a Chinese tech stack.
28:16
And so you you open source the the the coding model, build the developer ecosystem, and then maybe that helps Huawei stay competitive.
28:26
maybe that you know reduces the amount of dominance of the American technology stack and so there's there's a little bit of like public incentive to build up uh the indigenous supply chain that comes from that less so in video where they are vertically integrated and have everything down to the distribution surface.
28:46
So, uh, in general, if you are a challenger that needs an ecosystem, you want to open up.
28:52
We saw this with the early meta stuff.
28:53
Uh, and and then, uh, if you're an incumbent and you have distribution, you want to close down.
28:59
So, uh, there's some interesting knock-on effects mainly around a speculative future value of video models and training humanoid robots.
29:06
Like, China also seems to be doing really well in humanoids.
29:09
If AI video becomes really important in simtoreal translation and training these uh AI tra train training humanoid robots with simulated video, then this could be like part of the bigger picture.
29:21
But I think that's further out.
29:23
I think for the next month we're just going to be talking about memes and funny videos. Anyway, >> that's right.
29:28
>> Let me tell you about the New York Stock Exchange.
29:29
Want to change the world?
29:31
Raise capital at the New York Stock Exchange. Just do [music] it. >> Just do it. >> Do it. Uh, Meta on a tear.
29:38
Meta's up 27% this month according to Shiel Monot.
29:45
Almost entirely thanks to Muse.
29:45
Uh, this makes sense, right?
29:49
>> Is that almost entire to Muse?
29:52
>> I mean, the semi analysis >> basically when you have a company that's spending hundreds of billions of dollars on something without much to show for it and then you have something to show for it. >> Yeah.
30:01
>> Then the market's going to react positively. Yeah.
30:02
They're going to they're saying, "So, you're saying there's a fighting chance here?" >> Totally.
30:07
And the feedback on the product is incredible.
30:09
There's a lot of investors that have tried it and they're like, "Hey, this is a good product." >> Yeah.
30:13
>> And >> and and and interestingly like they are in the lead in a subcategory where they have never been the lead before.
30:18
Like Google had Nano Banana which like there was a moment where it was like oh nano banana is the best.
30:24
Uh obviously Anthropic had best coding models for a while like like crowns have changed but meta's never really held the best model in knowledge retrieval or when they did vibes that was not the best version of that.
30:37
[clears throat] Uh, but this is at this moment in time the best version of of of what they have.
30:41
And it's building off of a model that's not on the frontier, but able to deliver an experience that puts them in first place for this subcategory, which is exciting.
30:53
>> And can immediately be incredibly integrated across everything else that they do, shopping, messaging, all these different things.
31:00
>> Shopify and Muse announced a partnership this morning counterpositioning a little bit against >> Amazon.
31:06
Uh, Amazon came down with the banhammer.
31:09
Uh, Buco Capital says, "Amazon cuts off Muse.
31:12
While I am bullish, Meta and Muse, I think many people are overlooking the digital knife fight that's about to occur.
31:17
Nobody wants to get commoditized or layered here. Let the games begin."
31:21
And Amazon says it has cut off Meta's new Muse personal AI agent from shopping on Amazon.
31:27
com on behalf of customers after attempting unsuccessfully to get the Facebook parent company to voluntarily exclude the e-commerce site from the experience.
31:36
The problem Amazon says is that it never agreed to any of it.
31:39
Meta didn't tell Amazon that Muse would access its store.
31:42
The agent itself doesn't identify itself when it browses and it appears to capture and store customer credentials which the company says create privacy and security risk.
31:52
As of Sunday night, people trying to use Muse to shop on Amazon were seeing the popup, "Continued access by an unauthorized AI agent violates Amazon's conditions of use," to which our customers have agreed. >> Interesting.
32:04
I wonder how Walmart will respond because a lot >> Walmart was always overlap is is is higher than I think most people think.
32:12
So, I think Walmart had always been more friendly with chat apps, >> specifically chat GBT.
32:19
>> And that's the kind of thing that you do when you're not >> the lead, you know, when when you're not the leader in the space, you're more willing to >> experiment.
32:26
I think they wound up rolling their own.
32:27
Uh I think they have Sparky and Amazon has Rufus.
32:30
And so there's two dog named uh AI agents that do the shopping.
32:36
And then and then most recently >> Tyler's been dailying Rufus by the way. >> Yeah. Just for everything. for everything. >> Just Yeah. Just uh psychology. >> Yeah.
32:46
>> Getting close to solving another millennium. >> Yeah. Yeah. >> Rufus underrated. >> Yeah.
32:51
Um yeah, I I I know uh Amazon wound up uh finding sort of an equilibrium with uh OpenAI by plugging in their ad network into Chat GPT instead of letting Chacht like check out.
33:05
This is the whole Eric Seufort agent commerce is a is a mirage.
33:07
Um, instead, uh, Amazon is vending in their ads.
33:12
So, Chach brings the data and says, "Okay, this person's looking for this thing.
33:17
Do you want to buy an ad on it?"
33:18
And so, there's the transaction value.
33:20
But I I I don't know how it play out. >> Yeah.
33:23
I saw saw a couple uh seemingly smart investors say that that are using Muse and excited about it say, "Why is why is Amazon banning Muse?
33:31
This is so shortsighted."
33:34
And then I actually saw two in two instances they deleted because of course they immediately were getting comments about Amazon's ad business which is obviously what they're looking to protect.
33:43
You can't >> serve ads to Muse agents or Instinct or or Chat or any of these other things.
33:50
>> And Amazon's ad business is actually dramatically bigger than both Anthropic and Open AAI over the last 12 months. Yeah.
33:59
So they've done 76 billion in the last 12 months through Q2 of 2026.
34:06
>> Um so obviously they're going to protect this.
34:09
>> Uh obviously they're going to protect this.
34:10
I think uh consumers would love to be able to check out with um with other services. >> Yeah.
34:18
>> Uh it it is pretty gnarly to navigate. Yeah. >> Amazon.
34:21
com as amazing as the service is overall.
34:24
[laughter] >> Describing like your experience is gnarly.
34:28
No, it's it's >> just being a UX researcher at Amazon, they're calling it gnarly.
34:31
[laughter] >> It is fairly gnarly. >> Yeah. Yeah. Yeah.
34:36
Um and uh but but you can see that that there's >> and again uh Peter who who effectively is the founder of Muse because he obviously Muse is based entirely on Open Claw and they built an amazing sort of effectively almost like >> and I think Instinct too is is is some open claw lineage. Is that correct? >> Yeah.
35:00
>> Uh Peter says the beauty of running a claw yourself they cannot block you.
35:02
So, >> oh, they're going to block me [laughter] when I'm when I say claw, open 10,000 Amazon windows on my desktop.
35:12
Open up 5,000 Chrome tabs of of Amazon.
35:16
So, the souvenir you can get banned even if you're running it locally.
35:22
This has happened to me like this is this is not a full solution, but uh he is he is right that there will be more sovereignty and the users might win.
35:33
Like that's what we were talking to John Quinn about was that Amazon versus Perplexity computer.
35:36
The ruling was that Amazon can't block it if it's not if it's running on the person's computer because it's like yeah yes yes I told the agent to open the Chrome tab but it's my Chrome tab on my computer.
35:48
And so you shouldn't be able to block that because it's not a third party company.
35:54
It's not it's not corporate warfare.
35:57
You're coming to me the consumer.
35:57
The consu the customer is always right.
35:58
I can I can I can see that being the ultimate outcome.
36:03
I do think that's a big I mean you basically I I think Amazon's ad business at least at least their search ad business is something that eventually you might need to underwrite like cable television where it's like >> you're basically saying that there's a terminal value here.
36:18
People are going to use their assistance >> to shop.
36:22
Uh that does but some amount of people are just going to keep going to Amazon. com.
36:26
Right now it is Amazon has made it quite easy to buy things on Amazon. com.
36:31
It's not like it's that much easier with an assistant, but something I found is it's it's actually really nice having a single interface for all the things that you do, right?
36:39
So I like going to one place.
36:43
>> Agent push the order burrito button.
36:46
[laughter] >> That's really the future we're in.
36:48
The souvenirator has had some of the best commentary on this which actually dates back to he says uh uh the knife fight already took place.
36:58
It ended a year ago when I wrote the first entry in my agentic commerce is a mirage series.
37:04
Amazon began blocking agents last July.
37:07
It's currently suing Perplexity over autonomous shopping with Comet.
37:11
>> Amazon won't capitulate. It doesn't have to.
37:13
Alexa for shopping generated 12 billion in incremental revenue.
37:18
Um [laughter] >> every time I hear Roffus or Sparky uh Walmart Sparky has generated similarly significant commercial traction for the company.
37:27
Agent Commerce is already a reality but it takes place on site not through independent agents.
37:33
Chad GPT launched ads in February 2026 and shortly thereafter shuttered instant checkout.
37:38
The affiliate model is economically suboptimal relative to advertising.
37:44
>> Chad GPT has already demonstrated that. >> Yep.
37:47
Advertising is the dominant business model.
37:49
Yeah, it'll be interesting.
37:50
I mean, uh, when the openclaw stuff came out, I was like, it feels like Napster.
37:54
It feels like the Napster moment.
37:55
Like, yeah, you can go check out on an e-commerce website, but like nobody wants you to do that that way.
38:01
and like you're going to have to write some API binding and then like scrape the front end and then rewrite it every time you go and check out because they're constantly going to be fighting you and you are sort of like playing this like game of cat and mouse which you can play uh and for certain for certain e-commerce sites they're going to be very open to that.
38:16
Other ones are going to be a huge hassle to deal with. >> Yeah.
38:21
And the question is can agents monetize with advertising?
38:26
I saw someone uh a pretty viral post, somebody frustrated with Instinct.
38:31
Instinct coming and they did basically a blast that says, "Hey, you have a bunch more invites.
38:35
You can invite a bunch of people."
38:37
>> Uh and the user was pretty frustrated with that because they're like, "Hey, you work for me.
38:40
Why are you advertising?"
38:41
And so even though they're not paying for the product and they're incurring a lot of costs, Yeah.
38:46
>> product's free to them, they're still mad that that they feel like the agent is doing something that's purely in the agent's benefit, not in their >> Sure. Sure. Yeah.
38:53
>> Sure. Sure. Yeah. I wonder if uh we'll live in a world where you know how Chachi PT has like those recommended agentic actions if like one of those could be like sponsored like hey like >> want me to go shopping for you right [laughter] now like
39:08
>> well yeah no and that's important because because companies will happily pay for incremental demand but the issue with with with agents if is if you're saying go to Amazon and buy this thing the user already wanted to go to but if I'm if I'm uh if I'm an industry coalition of surfboard wax makers. I
39:25
I might choose to send you a notification when you open up Chachi PT that says like, "Hey, want to go surfing?
39:34
Want to take it to the next level?"
39:37
Isn't that what happened?
39:39
>> Uh, basically >> you got one one recommendation.
39:43
>> Chachi PT recommends >> what was it?
39:45
>> Various agentic workflows for me.
39:47
>> Yes, >> I sent it earlier.
39:48
just says one [laughter] of them was >> it recommended setting up an agent to give me one realistic next step for my surfing each week. >> Yep. That's great.
39:58
It's like every >> problem is I know exactly I know exactly what I need [laughter] to do.
40:03
>> Like uh this is actually >> uh Raj Ver okay >> called out something interesting which is that thread started free falling in the charts right as Muse started growing. >> Yeah.
40:13
today on on Instagram there there's a there's a hero story that's a fullble bleed ad for Muse. So they're pushing it. They're pushing it.
40:20
And yeah, they're probably saying like, "Let's let's funnel it over to Muse." And it makes sense.
40:25
The the monetization on Muse I would expect to be way higher than threads.
40:29
Threads you get some display ads. It's text.
40:31
It's never that surface has never monetized as well as Instagram.
40:36
So the best case was like you get something half as valuable as Instagram, a quarter tenth as valuable, whereas Muse is like a new surface area where there's a whole bunch of different oper monetization opportunities and they already have the whole small business community.
40:51
So I I I think it makes a ton of sense to to funnel the uh the uh the attention over there.
40:57
Uh let me tell you about MongoDB.
40:58
What's the only thing faster than the AI market?
41:00
Your business on MongoDB. Don't just build AI.
41:02
Own the data platform that powers it.
41:04
Now going over to the the less uh the less good news in the agentic future that we're all living in.
41:13
It feels like hallucinations are coming back.
41:14
There was a moment where it was like if you hit GPT6 Pro with a query on some history or you basically want a Wikipedia page that's generated or a history report pull some data you could rely on it that it was not totally making things up directionally correct bunch of really high quality links pretty valuable and so hallucinations this year have kind of gone away.
41:39
You still get slop if you're doing something on the on the frontier like trying to design some system in code or using Blender or even AI video.
41:46
You'll see little things here and there, but for knowledge retrieval, the the hallucination problem kind of went away, but it's coming back in full force.
41:56
David here said Instinct made up his middle name and he can't board his flight because he tried to use his agent to book a flight and it just made up David Bomb Chang Choy.
42:05
Uh which I guess is not his middle name.
42:09
Uh and I've had that before where >> I find it a little hard.
42:15
>> Well, one one we know we know why hallucinations would be happening which is like if you're serving a product for free at scale, you have to figure out a way to do it really cheaply.
42:22
And so they're they're certainly using older models and trying and and again trying to find >> someone figured out the model.
42:29
Was it I think it's Kimmy running OpenClaw, right?
42:33
But it's hosted in the cloud and so you get an OpenClaw instance cloud hosted. >> Yeah. >> Yeah.
42:41
>> That said, I've been in situations where my name was misspelled on on like uh flight details and this is pretty easy to to resolve. So hopefully >> Oh.
42:52
Oh, you think it's not that big of a deal cuz like you can just get on the phone.
42:54
>> You can just talk to them and they'll be like, "Here's my ID.
42:56
I made a mistake before, fix it, and they'll give you new boarding pass." >> Yeah. Yeah. Yeah.
43:00
They might kick you out of security lines.
43:02
So, if you're running really late, as I like to do, uh you uh you you might you might you might struggle to get on the plane.
43:09
You might miss your flight, but that's okay.
43:10
You got to miss a couple.
43:13
>> This was interesting from former Meta employee Nikita Beir says, "How important is AI to Meta? Here's one easy tell.
43:20
One of the launch features of the Muse app was autonegotiating for stuff on Facebook Marketplace.
43:24
The poor product manager who owns Marketplace knows that millions of bots lowballing sellers will eventually kill the product.
43:31
But this was escalated to Zuck by the Muse team and he said, "Okay, we'll poison marketplace just a little."
43:37
>> Wait, why will that kill the product?
43:40
>> I mean, think about the experience if you tell your bot like, "Hey, I'm interested in these types of items.
43:43
Go anytime one of them appears autonegotiate."
43:47
Yeah, but wouldn't someone have a bot on the other side dealing with the negotiation?
43:52
>> You can do the outbound, too. >> You can go outbound. >> Yeah. Yeah. >> Yes.
43:56
>> Message everyone on Facebook. >> Yes. I got a Dodge Hellcat. If you know, you know.
44:00
I got one pair of keys and I saw you were post.
44:03
You liked a post from the Dodge Hellcat community.
44:06
Would you be interested in purchasing this? I I'll need cash. >> Don't ask questions. >> Don't ask questions.
44:13
Let me tell you about CrowdStrike. Your business is AI.
44:17
Their business is securing it.
44:17
Crowd Strike secures AI and stops breaches.
44:19
We got August to Rico back in the Ultra Dome, back in the waiting room.
44:25
He's coming in hot off the series [music] B.
44:29
How you doing, >> gentlemen? I'm blessed.
44:31
It's a pleasure to be chatting again.
44:33
>> Congratulations, you align all this news. >> Was that strategic?
44:36
Was this like a >> You're like, I need to pump the series B so I'll get engaged to get an extra press cycle going. >> Oh, yeah.
44:44
They were close together, I guess.
44:46
[laughter] Uh that was coincidence.
44:47
>> They both embargoed same weekend maybe. >> Yeah, that obviously. Congratulations.
44:52
We're very happy for you uh on on on the engagement, but also the series B. How are things going?
44:57
What's new in your world?
44:59
How much rain are you making these days? >> Yeah.
45:02
Uh well, first of all, the the $100 million that we raised, I'm super grateful to have done that with with some great partners.
45:14
>> Thank goodness we keep You're going to need a bigger gong the next round. >> We are.
45:18
>> We've been with I feel like we've been riding with you for >> every round to date. >> Day one.
45:23
>> And uh yeah, time to upgrade for us. >> No, you were there. You were there early.
45:28
I uh I was wondering whether a $100 million bag was big enough for the size gone. But uh for sure. >> Oh, for sure.
45:34
>> The the reality is um >> it's [laughter] it's a drop in the bucket relative to what uh the Chinese meteorological administration is spending. >> Oh, yeah. What are they? They understand. Say again. >> Yeah.
45:47
What What are they spending? Order of magnitude.
45:49
>> So, so, so they're spending hundreds of millions of dollars a year on their weather modification program because they understand that water and the weather is a strategic capability and resource.
45:57
We talk about critical minerals.
45:59
We talk about oil and natural gas.
46:01
Water is this fundamental input to our industrial economy, to our a to healthy agriculture and food.
46:06
And if we don't produce more, and cloud seeding is the foremost option to produce more, the Colorado River, the Great Salt Lake, the the bodies of water across the United States are going to be uh impaired to the point of mass evacuation.
46:20
So, we need to make more for the sake of the strategic health uh of the country and then also for our allies overseas that need more water like Jordan in the Middle East, uh like Morocco and so on.
46:32
>> Did you get saved by data center backlash?
46:35
because there was some backlash brewing to your crazy scheme to make it rain and then I feel like it's been real quiet since the data centers started sucking all the air out of the discourse.
46:48
>> Well, the data centers have been sucking water out of our divorce.
46:51
>> How real is that from your perspective? You're the water expert.
46:53
Talk to data center people.
46:56
They'll be like, "It's closed loop. It's like a car wash."
46:59
Yeah, we use water, but we recycle it at the same time.
47:02
you know, water usage, it's low, but everyone's saying we're going to build a thousand times more data centers, so at a certain point might be significant.
47:10
What What's your take on it?
47:13
>> Well, the reality is yes, American agriculture is using far more water, orders of magnitude more than data centers.
47:20
So, so does municipal use, the showers that we take, the dishes that we wash, orders of magnitude more water than data centers.
47:26
But data centers do consume water.
47:28
And when you have as great a shortage of supply as we do in the American West, do you want to give water to computer or to uh your shower and your >> probably computer >> probably weekend all weekend generating AI videos.
47:47
[laughter] But >> if it's generating AI videos and playing video games, I'll skip the shower. I'll walk in.
47:52
But John Jordy, you can have AI slot videos in the shower if you just make via cloud seating.
47:59
>> I can have my cake and eat it too with cloud seating. >> Precisely.
48:02
>> Uh is there actually any any closed any near-term flywheel there where uh cloud seating can alleviate uh water usage from data centers or is that like further out?
48:14
Raymaker already has uh one deal closed with Hyperscaler and we're in negotiation and engineering feasibility with multiple others.
48:23
Um offsetting their consumption and riding the wave of hyperscalers to produce more water for the American interior.
48:30
That's a spectacular positive externality that those uh businesses can provide.
48:34
And so I look forward to that.
48:36
Um maybe not as much as I do the ski resorts that we're negotiating with.
48:40
Um, but keep an eye out for uh the Cantons of Switzerland and your favorite resorts around there in uh this upcoming winter. >> That's cool.
48:49
>> Uh >> yeah, talk Yeah, talk I talk more about that as personally as a skier.
48:53
I'm I'm uh I'm quite fascinated.
48:56
But but like what what are what are those deployments going to look like?
48:59
Like are you is that basically you have a a team that's set up at an individual mountain and then you're basically I mean the these are uh businesses that have basically dealt with making artificial snow for such a long period of time.
49:15
I'm sure they took like very naturally to the concept but what are these deployments going to actually look like?
49:20
So they haven't taken supernaturally to it initially because cloud seeding and weather modification has mostly been full of fugazi and snake oil for the last hundred years. Right?
49:30
There uh are many many people in the last couple decades that have claimed to be able to modify the weather but they can't physically measure it and prove it in real time.
49:38
If you can't do that then uh why would somebody bother paying you?
49:43
It's only because of the recent results that we had in Alaska, in Oregon, Idaho, Utah, where we're making hundreds of millions of gallons of new water that they've taken an interest.
49:53
And we wouldn't be able to do that if not for our efforts to build the best atmospheric science lab in the world.
49:58
Um, the weather is something that's historically underinvested in by basically everyone besides commodities desks.
50:04
Um, we need to put way more sensors into the field.
50:09
We need to build far more sophisticated models in order to understand our interventions and then actually harvest the resources available to us in the sustainable and renewable reservoir that is the atmosphere be it for ski resorts or farms or data centers.
50:23
>> Are you going to stay with drone delivery for the foreseeable future or is there a howitzer in the pipeline?
50:32
Because I I I I've seen though some ski resorts actually have Howarditz or cannons that will just launch conventional munitions to cause avalanches to clear avalanches for safety.
50:42
Uh but they already have some of the equipment and I imagine with the right round you fire the right chemical and disperse it at the right it doesn't seem that crazy to me might be cheaper but I'm sure you've looked at it.
50:51
What's the decision tree for you?
50:55
>> At the end of the day what I care about is delivering on the effect that our customer wants, right? Do you want more snow?
51:02
What's the best way to get it to you?
51:03
Um, if it's a rocket or a howitzer or me skydiving and halo jumping through a cloud with with silver iodide in my hands, like whichever way is best works.
51:14
We're taking a really big and deliberate bet on autonomy.
51:16
Uh, drones, they the ones that rain makers built are unparalleled in their capability to fly in these severe atmospheric conditions.
51:25
Much more wide a flight envelope than most manned aircraft.
51:27
Um, but in the limit, what we get out of autonomy is more flights, more cost-effective observations, uh, and and significantly lower cost per volume of water or snow delivered to our customers.
51:39
So, we're going to keep using, uh, our drones and make them increasingly autonomous, although we'll probably do some research with plans in the not too distant future.
51:48
>> How does El Nino affect your sales cycle?
51:51
Like, are >> is that going to put you out of business?
51:52
This is going to be rough couple months that I just but I just imagine there there's some players that are like I think we're going to be good this year. Let's check back.
52:00
>> No, no, it's kind of a cyclical business, right?
52:02
>> Shift your focus to other parts of the US.
52:05
>> It's it's a you know I think time Morse commented recently that building rain maker is like playing Diablo on insanity mode for startups.
52:11
Um not only is it a seasonal business because we're making snow in the winter, but also it is annually cyclical because of El Nino Alia Leninia.
52:20
Um, some regions are going to get a lot more natural snow, but uh, other regions will get a lot less and rain maker will be working harder there.
52:29
>> That said, even in the regions around this, uh, Pacific Northwest, northern Rockies that are getting more snow, they're so critically depleted that they need excess snow melt relative to the baseline year in order to refill Lake Powell, Lake me, uh, the Great Salt Lake, etc.
52:43
Um, so we're geographically hedged in order to accommodate this, not just within the United States, but across the world.
52:49
uh that is going to scale up the extent to which you know we're hedged across multiple different climates simultaneously. >> Mhm.
52:56
Um what does the team look like?
53:00
Where are you are are you have you expanded beyond the Gundo?
53:02
I know you have like four deployed operating bases, but what's the footprint of the company right now?
53:08
>> Well, you asked first what does the team look like?
53:10
I first would say Drippy.
53:10
Oh, >> show you a series a series of Hermes ties that we've decided series with.
53:20
>> This is a nice collection of different ties that have clouds on them. >> And here you go.
53:26
>> Are you Are you dawning ties more or less often than you were last year when I uh saw you on local TV every week? >> Uh more more often.
53:37
Um, and you know the the Gundo thing, uh, it's great. I love it.
53:44
I am a Gundo supremacist. Absolutely.
53:47
And we couldn't have built, uh, Rain Maker if not for that.
53:49
But, um, we want to serve water for everybody.
53:54
Uh, we want to serve water uh, to the federal government, to nations around the world.
53:59
And in order to do so, we need to collaborate with the best national labs and universities across the country.
54:06
um being the uh mulleted guy in Yeezy uh is not necessarily the uh outfit and persona that you want to dawn when you're talking about those research scopes of work.
54:16
Um so I'm wearing a lot more Hermes.
54:18
Um I am wearing a little bit less Yeezy.
54:22
Uh and that'll probably persist for a while.
54:26
Uh last question, last question for me.
54:29
As as some of these open problems, Millennium Prize problems have been uh solved, a lot of people outside of San Francisco are like, "Cool, the the nerd solved another math problem."
54:40
Like, you know, uh they don't they're not like as as captivated by it.
54:45
Um, but something that I've been thinking about is like for for every one of those sort of high-profile uh open problems, there's tons of businesses that have access to the same models or models with close to the same capabilities that are just applying them to their industries.
55:03
And I feel like for you um and and and in your category, it just feels like having intelligence on demand that you can apply to these problems that like hasn't had 10,000 PhDs working on it.
55:17
You talked about how, you know, hedge funds have paid a lot of attention to the weather weather because of commodities trading, but are you feeling like an acceleration in in in your team's abilities because of new models or are you not feeling it yet?
55:34
To give credit where credit is due, the nerds in San Francisco have done a spectacular thing.
55:38
Um, and >> tip of the fedora perhaps. >> Yeah. Yeah. Yeah.
55:43
Uh, >> tip of the old fedora.
55:46
>> We're we're worth taking a point too, right?
55:47
Like Richard Fineman was a spectacular scientist.
55:49
Uh, Oppenheimer spectacular scientist.
55:52
We can do great in frontier science without uh being total nerds.
55:56
Um, just a reminder to the San Francisco audience listening.
55:59
But again um you can uh you can see the rate of hypothesis generation and experimentation accelerating at Rain Maker because of the models available.
56:11
Astra has been a spectacular lever for Rain Maker and we're going to continue using it.
56:15
Um and and then also like developing better and better models with the uh informed participation of the LLMs critiquing the output like that is something that is actually genuinely accretive to our understanding of the atmosphere and and it's going to become all the more so in time. >> It's amazing. >> Awesome.
56:34
>> Well, congratulations on the round.
56:36
Congratulations on the engagement and safe trips travels. We'll talk to you soon. >> Great progress, dude. Great to see you. >> Goodbye.
56:43
>> Let me tell you about Figma. agents meet the canvas.
56:46
Your AI agents can now create and modify your Figma files with design system context.
56:50
We have a node Kla coming in the TBPN Ultradome in just a minute.
56:55
First, I wanted to we're going to talk to him about personal agents and I wanted to share uh this hot take from Alex Kerr who says, "I think Silicon Valley is making a fundamental mistake with personal agents, optimizing entirely for the outcome and forgetting that for a lot of things, the process is a very core part of the experience.
57:13
Travel is the obvious answer.
57:13
People almost always never want book me a trip.
57:18
They want to browse, compare, daydream, change their mind, send options to friends, and eventually book.
57:22
I think you can actually do all that with with agents, but uh he says the average person probably has far fewer recurring tasks worth delegating than the AI industry seems to think.
57:32
That's why personal agents feel more like a feature that gets absorbed into existing products than a standalone category.
57:40
Well, Benode Kosla has seen both, you know, develop over his career.
57:43
He's the perfect person to talk to about this and so we're very pleased to be joined by Benode Kosla, founder Ventures.
57:48
Venode, [music] how are you doing? >> I'm doing great. >> Welcome to the show.
57:55
Thank you so much for joining us.
57:56
Uh, I would love to hear about how you're thinking about this moment in personal agents.
58:01
It feels like a new category, a new feature, a new product, a new winner take all potentially.
58:09
How are you viewing the market?
58:11
How are you investing against it?
58:14
>> Well, it's a new category.
58:14
It'll be a broad category.
58:19
>> I do think it'll be very diverse and I don't think there will be a winner take all. >> Okay.
58:24
every one of the big labs or big companies, Meta included and Google included, will want to have their agents. >> Yeah.
58:35
>> Uh they will have different trade-offs and I think we'll see a lot of diversity in requirements.
58:41
>> As to Alex's comment, I think he hasn't used agents enough to understand much of that diversity that he's thinking about like we want to browse The best way to browse is have the agent do the work for you and give you the options and ask you questions and be interactive with it.
58:59
It's amazingly good when you can do it that way.
59:04
And I think some companies will optimize for it.
59:07
I think the fundamental difference >> uh will be do you want to be an advertising product or be something else. Mhm.
59:16
>> Do you want to trust Meta with your data >> or you want to and some people will and they do today and I think Meta will be successful.
59:24
I'm not trying to say they won't be >> but there's others who will have different tradeoffs and I do think agents from startups will move faster than agents from uh uh the big companies. >> Interesting. Okay. >> Yeah.
59:39
And that that makes that makes a lot of sense.
59:40
There's uh I wanted to ask you about the the quoteunquote knife fight that's unfolding between agents which are >> right now deeply deeply aligned with users. Right.
59:52
Even fundamentally uh last year we went through the cycle of labs and and different players launching new browsers. Oh yeah.
59:58
Which I thought was fascinating at the time because it felt like for me Chad GBT was a browser.
1:00:04
it would replace my need to go to 20 different websites to understand like a topic or or a certain product tab was a browser and I think that consumers like the ability to do a lot of things from one single interface without bump you know jumping around and they can ask a question about a product and then navigate to another and all these different things.
1:00:26
But but it seems like there's this, you know, um something that's been basically ongoing, this fight between new agents that want to just do what the user what the user wants in in a way that's aligned to them and these platforms like Amazon that that have big businesses that are under attack by these sort of new products.
1:00:46
>> I think you're right on there.
1:00:46
There's a massive difference between a company wanting its agenda and the browser battle you referred to wasn't for the consumer.
1:00:58
>> It wasn't the consumer wanted to move from uh Chrome to something else.
1:01:01
It was the company saying Google controls what gets happens on the Chrome browser. I don't want that.
1:01:11
So I'll have my own browser.
1:01:12
Y >> that's a very different need than what the consumer wants. >> Yeah.
1:01:18
>> I think from the consumer's point of view uh with all the assault on the consumer the marketing assault I should say from AI [laughter] and all the AI is ganging up on changing shades of blue which Meta does to make you click more or other things uh Tik Tok plays.
1:01:40
Tok plays. uh do you want to be subject to the consumer or fight all the AIs with your own AI your personal AI that does only has your interests at heart >> and I think that's a very very large and important category I think I talked about this first about four years ago
1:02:00
the largest opportunity being protecting the consumer against all the AI assaults and getting all their work done without it being biased today you can't even look at the reviews without understanding whether it was paid for by whoever's marketing it. >> Yeah. >> Yeah.
1:02:18
>> So representing the consumer and having an AI that loyal to the consumer not to a particular company, a particular product, a particular point of view is going to be very very important.
1:02:32
>> Do so so Silicon Valley has long said consumers consumers won't pay for things at scale.
1:02:38
Uh there there's >> Beno said consumers want to be entertained.
1:02:44
They don't want to be productive.
1:02:45
If you're building a tool that is a productivity tool, you ultimately need to sell that business as an enterprise. >> Yeah.
1:02:51
And yet it feels like that is going to be the most aligned model >> for agents because your agent can go fight different things. It can save you money.
1:03:01
All these different things.
1:03:01
It it feels possible that this time could be different.
1:03:06
[laughter] Uh, I don't want to maybe maybe it's too early to say, but but an agent that can get $20 a month and it saves you a couple hours a month and it >> that was Mark Zuckerberg's pitch.
1:03:14
He said Muse will save you money.
1:03:15
And we're already seeing examples of people using it to cancel subscriptions that they're not using, get refunds, and so there might be some economic calculus where it looks more like paying for Turboax than, you know, browsing Instagram reels potentially.
1:03:31
But how do you think about monetization?
1:03:33
Chat GPT with its subscription service >> proved the consumers will pay if there's enough value. >> Yep. >> Yeah.
1:03:42
Massive business got built.
1:03:42
Google always assumed consumers won't pay >> and that was the conventional wisdom and chat G chat GPT in my view destroyed that. >> Sure.
1:03:54
>> For enough value consumers will pay. Mhm.
1:03:57
>> Now, saving you money is really really valuable uh for most consumers.
1:04:06
Uh and they will pay if something does that.
1:04:09
Uh knowing that it represents them, knowing every time they're about to spend some money, they can find a more efficient way to get the same thing.
1:04:19
That's a big deal for consumers because whether you're looking in travel, whether you're looking in shopping, there's always ways to save money.
1:04:28
Subscriptions is a great example.
1:04:31
I have way more subscriptions than I know about.
1:04:33
Um and and so representing the consumer's interest and acting on their behalf as it was an as if it was an omnipotent a personal assistant is what matters. And personal is the key.
1:04:49
it's for them the consumer not for some company.
1:04:54
>> How do you think about moes in this era of uh personal agents?
1:04:57
of uh personal agents? There's a there's a thesis that's percolating right now that says uh once you install a personal agent once you've given one personal maybe people won't trust Meta certain people obviously will but the people that do and they go in that bucket and they start daily driving that particular
1:05:17
personal agent they give it access to their calendar their email their text messages they are not going to move to another agent even if it's a little bit better at the same time I feel like there's a risk of if you're on instinct you can go to Muse and say, "Hey, just offboard me from Instinct and set up Muse or vice versa." And so it might be
1:05:34
And so it might be a little bit less of a of a hassle to offboard, not quite as strong of a mode as traditional social networking, but how do you see the moes question playing out in the era of personal agents?
1:05:48
>> I think offboarding will be possible.
1:05:48
A little bit clumsy, but then if you have a good agent, you tell it to do the offboarding. >> Yeah.
1:05:57
>> And the onboarding on to the new one. >> Yeah.
1:05:58
And we saw that with uh with OpenAI and and and Anthropic saying, "Hey, go go go dump this prompt in the other chat app to get all your memories come and paste it over here."
1:06:08
And they were fighting over that because, you know, it was possible to move from one LLM to the others.
1:06:13
This is >> I would say is the complexity of tasks, >> especially as companies make it hard to offboard, will no longer >> be a barrier.
1:06:26
>> You know, if I had to look at all my information on Google or meta and figure it out. It's complex.
1:06:36
>> If I want to know, I don't want Google to know where I was on September 3rd at 5:00 p. m.
1:06:41
They probably know and I can probably disable that, but it's hard. >> Mhm.
1:06:49
>> AI is just going to be good at doing all these complex things.
1:06:51
And so I think that mode disappears. So what's the mode?
1:06:56
I believe the mo will be trust >> um in a company that develops trust with consumers and that's where Meta has a huge disadvantage.
1:07:09
>> So the trust will be the mode.
1:07:09
Um uh that'll be important.
1:07:13
I also think completion's going to be really important.
1:07:19
>> Consumers will be loyal to products that get their done. Excuse the language. >> Yeah. Uh, >> it's true. It's true. It's a good point. It's that simple.
1:07:28
I mean, it's like we miss it a lot, but that is a good point.
1:07:32
>> And if you if you look at the Vajjo agent, >> Yeah.
1:07:35
>> you don't need to know uh what it's doing, but it knows when it's stuck. >> Yeah.
1:07:44
>> Most agents then just tell you they're stuck or don't even tell you that they're just stuck.
1:07:48
The auto agent, for example, will pull a human in as a tool. >> Oh, interesting.
1:07:54
Use a human to complete your task. >> Interesting.
1:07:58
>> So, uh the idea of trust first, your your information, your most private information, uh what you like, what you don't, what you buy, what your preferences are. Um that's trust.
1:08:15
>> Then there's completion.
1:08:17
uh if you can get all my stuff done, I'll be loyal to you.
1:08:19
And for the very large companies, it's very hard to have humans in the loop. >> Mhm. >> Oh, sure. Sure. I think >> Yeah. You need to scale it.
1:08:29
I mean, it's it's it's yeah, very difficult to come over the top with, you know, a product that can service a billion users that has humans in the loop because you have to stand up that.
1:08:40
>> So, there is an advantage to being small and agile and >> Okay. Right.
1:08:44
>> Okay. Right. and and frankly for people who need stuff done >> um it's much much better if you pay a little for the human in loop and get things done then [laughter] >> yeah so uh the other thing that really important and you talked about the Chrome browser not everything will be in
1:09:06
the browser the right agent won't be an app it just where do most people live they live in their email they live in text messaging um they live in Slack, they live in other channels >> and so agent has to operate primarily with all those channels and the app if there's one and there may not be one. It's just in the background. So you
1:09:29
It's just in the background.
1:09:29
So you don't have to open the app.
1:09:31
You just text message your agent >> like you do with Faux from Vojo >> and it takes care of it.
1:09:37
Or sometimes you just pick up the phone and do that. >> Mhm.
1:09:41
And sometimes the agent just has to pick up the phone and have a conversation with the merchant. >> Yeah.
1:09:48
>> So you know meeting a consumer where they are. >> Yeah.
1:09:54
>> The consumer experience is really really important not get stuck in we do text only, we do browser only, you have to be in our app.
1:10:03
You users don't like those constraints.
1:10:06
How do you think about >> I don't want to install one more app on my [laughter] phone.
1:10:12
>> Yeah, it's reflected in the app store.
1:10:13
It's it's it's all just AI apps.
1:10:13
Um, how do you uh how do you think about the way you will interface with personal agents over the next few years?
1:10:22
If if you uh if you want to send a message to me, John, will I receive that message from you?
1:10:32
Will I think it's coming from you or will I think it's coming from your agent?
1:10:35
Will your will your agent identify itself as Venode's agent with a different name, with a different identity, a different persona perhaps, or will you want to tuck the AI beneath the fold of your digital life so that it's sending emails as you?
1:10:51
>> So, I was actually doing some ordering from Petco yesterday. >> Oh, yeah.
1:10:57
>> And it said some things to me and I said, "Just pretend to be me."
1:11:00
And it said, "I can't do that. I won't do that.
1:11:06
>> So this goes back to trust as a key moment. >> Interesting. >> Right.
1:11:10
So I do think for both parties you have to be transparent.
1:11:15
The agent is your agent but it's not you. >> Mhm.
1:11:20
>> And I think that's important and that'll engender trust >> and we'll see uh much better.
1:11:26
Uh, >> I want to stay on Petco. >> Dog, cat, bird.
1:11:35
What type of animal are you most fond of? >> Oh, dogs for sure. >> There you go. >> What kind of dogs? >> I'm sorry. >> What kind of dogs?
1:11:47
>> Oh, I'm a big fan of New Finlets. Anything. >> I have a New Finland. I love New Finland. I had two. Uh, one made it to 11. He passed away. to rest in peace.
1:11:58
But we have another one that's going strong.
1:12:00
Uh a uh about 130 lb dog. >> Lovely dog.
1:12:06
>> I I had I had two new Finlands that >> died last year.
1:12:10
They were both around 200 lb. >> Wow.
1:12:14
>> And so we now have a puppy, but I was trying to get a task done. >> Yeah.
1:12:17
>> I could have looked at six websites for this specialty type of dog collar after surgery.
1:12:23
My puppy had surgery last week.
1:12:26
Um, it could call lots of stores. >> Yeah.
1:12:28
>> And look for do they have same day delivery, which is the key thing I was looking for. >> Yeah.
1:12:34
>> And can it pay for me and all that stuff.
1:12:37
One of the great things is payments is going to be a real differentiator. >> Sure.
1:12:43
>> Um, if you can be absolutely secure and give your agent like your credit card, that's a big deal. >> Mhm.
1:12:52
And there will be lots of abuses or mistakes in that domain.
1:12:55
I feel comfortable with the Wajo agent giving it my MX card. >> Sure.
1:13:02
>> Because it has certain types of protections um that are going to be patented.
1:13:07
So won't go into it, but I will be absolutely sure that card won't be reused for something I didn't authorize. >> Yeah. Yeah.
1:13:15
You can sort of set up payment rules if it's over this threshold.
1:13:19
And that's and that's actually in code.
1:13:20
That's not something that can hallucinate.
1:13:22
It made a mistake and the model thought it was $100.
1:13:24
It was actually $100,000.
1:13:27
It it makes a mistake like that.
1:13:29
So yeah, makes sense that we'll be in this blended regime of both, you know, deterministic software, stochastic software.
1:13:37
>> Last thing for me, do you think we'll get to the point where uh users will want to give like something like power of attorney to their to their agents?
1:13:46
Dan in our chat was asking about that and and I've thought about this before.
1:13:50
Just working with executive uh normal executive assistants, it's always very frustrating where you get to the point where a certain service will be like, "Hey, they they need they actually need you to call now.
1:14:00
I can't sort of like take this any further."
1:14:02
Um so it feels like we'll we'll get to that point eventually.
1:14:08
>> All these questions come back to what's the trust is the more and will you give your power of attorney?
1:14:14
to the agent if you trust it.
1:14:18
My bet is 95% 5% of users will do anything.
1:14:22
95% will not trust giving your power of attorney to your agent today.
1:14:28
Now in four years will that have start to happen?
1:14:33
I suspect 40 or 50% of people will give a power of attorney to their agent by 2030, >> right?
1:14:41
because they've had enough interaction and developed enough trust.
1:14:46
>> So trust becomes the key issue and this is why startups may have an advantage.
1:14:52
Startups with great transparency will have an advantage over people who already have a brand of lack of trust. >> Yeah.
1:15:00
What's uh what is the what's been your journey with Wajjo and Fox?
1:15:03
Uh did you invest early and then this is just the right product at the right moment?
1:15:10
Did they pitch you on this day one?
1:15:10
Has this been years in the making? What's been the journey?
1:15:16
>> Well, we invested in it day one.
1:15:16
In fact, we brainstormed with Shivani who's just a great technologist and a real understanding of the human factors.
1:15:26
>> Those were two things that are key.
1:15:29
>> So, we invested and we even brainstormed the idea.
1:15:31
Um, so we're really happy with Vajjo.
1:15:35
She's and and she's of course deeply technical.
1:15:38
a has this other understanding of what consumers need and I I call it empathy for consumers is really what you need. >> Yeah.
1:15:47
>> Uh and say how do I best represent them?
1:15:50
Uh that's the right mindset.
1:15:50
So uh we've been very excited about uh do you need an access code? Is it in early access?
1:16:00
How does how does actual onboarding work right now?
1:16:02
because it feels like if there's a human in the loop, you can't jump straight to general availability because you might get flooded, right?
1:16:11
>> You you also want to grow slowly. >> Yeah.
1:16:14
>> Because you want to lots of connectivity to lots of things and that builds over time as you get more users.
1:16:19
Today, it is not free access.
1:16:21
It's limited access by invite only. >> Okay.
1:16:26
>> And hopefully you can give people an invite code from the company.
1:16:30
>> Yeah, we'll share out some invites to anyone.
1:16:31
in the chat, but by September 30th, it'll be a free release.
1:16:34
So, by the end of the month, you'll see it pretty open to everybody. >> Awesome.
1:16:40
Well, thank you so much for coming on, breaking it down, and >> yeah, great uh great to see you.
1:16:46
>> Tustling with all the different tradeoffs in the modern era.
1:16:47
Have a great rest of your day. We'll talk to you soon. >> Great.
1:16:51
>> And send my best to the puppy.
1:16:51
I hope he heals up quickly.
1:16:54
Uh let me tell you about Cisco, critical infrastructure for the AI era.
1:16:59
unlock seamless real-time experiences and new value with Cisco.
1:17:05
There's some breaking news before we bring in our next guest.
1:17:06
The FAA, the Federal Aviation Authority, has restricted airspace up to 10,000 ft for the Tesla Roadster reveal.
1:17:16
Remember, we have a bet going here.
1:17:19
Elon has teased that the next Tesla Roadster, which will be announced October 2nd, I think October 1st.
1:17:26
Uh he has teased that the Tesla Roadster will leave the ground. He said it might fly. There's a SpaceX collab.
1:17:33
There's four cold gas thrusters. Uh we had a debate.
1:17:36
Where did you You had six inches. You had six inches. >> No, I was at nine.
1:17:41
>> You were at nine and I was at six feet. >> I was at half a foot. >> Half a foot.
1:17:45
>> I thought you were at 8 in.
1:17:47
>> No, I thought I was at like six feet. I want to jump it. I want it flying. I'm going 10. >> I did see something.
1:17:52
They they FAA shut down the airspace around the launch site. >> That's this. They shut down.
1:17:56
So, the FAA has has issued a temporary flight restriction over SpaceX's McGregor, Texas rocket development and test facility ahead of Tesla's October 1st Roadster reveal.
1:18:08
The restriction covers a 1.
1:18:10
5 nautical mile radius around the site and extends from the ground up 10,000 ft in the air.
1:18:16
That altitude is unusually high for McGregor, where restrictions tied to static engine fires and component testing have often topped out closer to 2,000 feet.
1:18:26
So, they're going five times higher.
1:18:28
The larger block of airspace is feeding speculation that Tesla plans to demonstrate the long promised SpaceX package for the Roadster.
1:18:38
Elon Musk has previously described a version of the car equipped with cold gas thrusters that could dramatically improve acceleration and potentially allow the vehicle to briefly lift off the ground.
1:18:49
Reports earlier this year suggested Tesla was preparing a remotely operated demonstration at McGregor with the car unmanned and spectators positioned hundreds of yards away because of the expected noise, which is just a hilarious a hilarious thing.
1:19:06
You're demoing something that if you drive it within hundreds of yards of someone's house, they will be annoyed or maybe not safe.
1:19:14
Like, how is this going to work?
1:19:17
Uh, it's a lot of it's a lot of showmanship for uh what could wind up just being like a pretty fast sports car.
1:19:24
But Tesla has not confirmed that the Roadster will actually leave the ground.
1:19:28
So far, the company has only teased the event with language like go for launch and imagery showing the car on what appears to be a launchpad.
1:19:34
But the FAA restriction suggests Tesla and SpaceX are preparing for something beyond an ordinary static presentation.
1:19:42
Whether that means the Roadster will actually hover on October 1st remains unknown, but the FAA has now reserved a substantial column of Texas airspace for whatever happens. I wanted like an F-35.
1:19:54
I wanted to do full VTOL.
1:19:54
If I want to park, just bring me up, plop me down. I don't know. I'm excited.
1:19:59
I think I think he's got to deliver something.
1:20:01
It's been nine years since he took the deposit.
1:20:04
Are you going to put a deposit down?
1:20:06
>> I think it's a deposit down $45,000 due within like 10 days.
1:20:11
And it feels like it's kind of high optionality because if it's incredible that so many people are going to flood in after the fact, but unlike waiting nine years, you can just wait until October 1st.
1:20:25
If it's a flop, you can just get a refund.
1:20:27
So, for locking up $50,000 for 10 days, >> yeah, I think you should do it.
1:20:34
>> I It's pretty tempting. It's pretty tempting.
1:20:36
I need to really read the fine print or have AI read the fine print to understand uh if there's a chance I get hosed, but uh there's a chance that you get one of the first ones.
1:20:46
Not even, oh, it pops financially and it resells.
1:20:49
Just the fact that it could be a really special and cool car that's really fun to have.
1:20:55
And if they bring it in with the final price of 250, there's a lot that they can do to impress at that price range.
1:21:02
If it comes in at 800, they're competing with a lot of >> If if it's just a if it's just a sports car that looks like a Cybert truck, it'll be a huge hit.
1:21:12
>> If it's 250, if it's 800, now you're competing with new and new has a V10, V8, something like that.
1:21:17
Like it needs to be it needs to be cybert truck cyberon like huracan cybert truck but also 250 because then you're like wow this is this is crazy this is competitive and that's what Tesla has been for a long time the model S was was really really performant delivered a lot of value for a pretty decent price.
1:21:35
Uh same thing with the Model Y it's still like a value play even though it is a relatively mid-market expensive car.
1:21:45
Well, I bet you Aaron >> has it has his pre-order down from like 9.
1:21:51
>> We're going to find out.
1:21:51
That's going to be the first question.
1:21:52
We're bringing in Aaron Levy from Box. He's the co-founder CEO.
1:21:56
Welcome back to the show.
1:21:57
>> Did you deposit >> for a Roadster 9 years ago deposit?
1:22:02
>> I I was I didn't do 9 years ago.
1:22:02
I was very tempted this time around though.
1:22:04
Um I did I did go down the rabbit hole.
1:22:08
There's these great YouTube uh >> uh you know, kind of um >> speculative fiction. >> Yeah.
1:22:13
sleuth folks that um did you see the thing if you um >> No, >> if you white out the the the uh the video it says where we are going. >> Okay. >> Did you see this?
1:22:25
>> Is is that a reference to Back to the Future? >> Yes.
1:22:27
So >> So it might have it might go 88 miles an hour. That would be huge. >> Either that or or so. Yeah.
1:22:31
So we're uh but there's a whole I went I went and watched a 20 minute video. Um I'm very excited.
1:22:39
I'm glad that you >> What's your theory, though? What's your theory?
1:22:42
I don't know the the I mean obviously Elon would make a flying car so it's um I think we're all we're all waiting for that.
1:22:49
Now I guess the question is like practically what is it what does that do um if you literally can't fly it?
1:22:54
Um but uh but >> you can fly it if you're within 1.
1:22:58
5 nautical miles of Starbase Texas and the FAA clears you I guess.
1:23:03
But >> I wonder I wonder if there's some loophole where like if you're on your own private property, can you can you get off the ground and and you could have you know those people have have uh >> those V tall things. Yeah. >> No, no, no.
1:23:15
I was going to say like you know you drive onto it and then it spins your car around. >> Yeah. Yeah. Turn. >> Could he make it? Yeah. Turntable.
1:23:21
So, we could make it like, you know, if your your garage is kind of tight, you want to turn around little indoor.
1:23:28
>> We may have reached the point though where Elon is building things for his personal life that uh exceed our normal zoning laws of uh of mere mortals.
1:23:37
>> There's going to be a lot of people with deposits that are like, "You're telling me I need 100 acres of private land now?
1:23:43
[laughter] I was told that this would go 0 to 60 in 2 seconds."
1:23:45
And the craziest thing is the original the original specs were uh 0 to 60 in 2 seconds. cars already do that.
1:23:52
The Model S Plaid did that. Not not crazy. 250K.
1:23:54
Okay, that's like a reasonable price point for a supercar these days.
1:23:58
Uh, but 6 over 600 miles of range, which is which is actually not been done by any EV yet.
1:24:07
And in a smaller vehicle, it's not like it's going to be huge.
1:24:09
So, uh, very very uncertain however.
1:24:12
I mean, they seem to be doing things with batteries that I never thought would be possible with batteries.
1:24:17
Like I was always told like 20 years ago that you know we'll never get more than 30 miles in a in a car ride.
1:24:23
So >> you just wake up one day and I guess it's 600.
1:24:27
So >> yeah, I mean I guess if you launch with the cold gas thrusters, put it in neutral, coast for 100 miles of range.
1:24:34
>> Maybe that's exactly Yeah, they get you the first 300 miles with uh >> Yeah.
1:24:38
600 downhill as long as you just cruise them.
1:24:41
Uh anyway, how are things going at Box Roller Coaster Ride?
1:24:44
SAS Apocalypse fully cancelled.
1:24:46
We were very happy to see that.
1:24:49
A bunch of We We were early to cancel. We bought them tickets.
1:24:54
>> You guys canled it within like 3 hours. >> Yeah.
1:24:56
No, we were like, "This is not happening."
1:24:58
>> No, but we did have We did have a a newsletter that went out like during the depths and I believe we were the first people.
1:25:04
>> S apocalypse is >> cancelled.
1:25:05
Uh yeah, because >> I actually, you know, you almost though had to you almost couldn't cancel it too soon though because you had to have the full trough. >> Yeah.
1:25:15
Um and you had to have like full capitulation on okay it turns out that there there is actually software that is powering the world and these systems of of record are incredibly robust and >> um and actually the more agents that you have running on these systems in fact the more important the backbone becomes.
1:25:32
Y >> um you know like everybody always sort of made this claim that once you have all these agents then actually all they really need is a database underneath.
1:25:39
But the problem is is that database has to be coordinated against possibly thousands of end users and then possibly tens of thousands of agents.
1:25:45
And so the the access controls, the business logic, being able to actually render the the experience, the security obviously, you know, see uh OpenAI hugging face like the these core systems are actually going to become more important in a world of of all of these agentic workloads.
1:26:01
So it's good to see the market, I think, paying more attention to that reality.
1:26:04
And it's obviously, you know, driven by, I think, the continued performance of these these software products doing well in the market. >> Yeah.
1:26:11
I mean, even uh over the weekend, I was generating AI videos.
1:26:12
I was trying to get them uh from my PC to my phone, and at no point was I like, build a new storage system for these videos, even if it could do it.
1:26:23
I'm like, I don't want to waste a prompt.
1:26:24
I don't want to waste a second doing that.
1:26:26
Let's use what I already use.
1:26:28
Let's use all the tools that are already built out that are robust and I can share links and all these things.
1:26:33
I don't need you to oneshot some some shoddy clone. It's a waste of time. It's a waste of money. It's a waste of energy. Bunch of things.
1:26:41
But in terms of in terms of resetting the narrative with the market, the street investors, employees, everyone.
1:26:48
Uh how much of it is uh going back to okay that you thought this thing was existential.
1:26:54
You thought we were going to be in so much trouble. We're not. It's business as usual.
1:26:57
It's business as usual. versus there might be still some threats but there's more opportunity and that's actually outweighing the threats and so that's why uh the company's performing well in the markets over the last couple months for example >> yeah very much not business as usual I think for anybody in software so so u like like this is like >> I don't know of a single company still
1:27:24
being run the way that it was run maybe you know 18 months ago I mean everybody is is uh you know running insanely fast uh into the future and then I think we're we're you know there there still will clearly be some parts of the market
1:27:38
that don't capture as much of the value as they did previously >> and then there going to be some parts of the market that capture actually a ton more value than they did previously because of of what agents can do. I mean
1:27:46
I mean you look at at you know uh infrastructure providers as an example like the cloud flares of the world totally on fire uh because agents need sandboxes, they need compute, they need network, they need gateways like like great business.
1:28:01
Um uh if you look at data bricks or snowflake uh agents need to be able to triage against large sets of data uh that are that that that that you need to be able to pull together in one kind of common system.
1:28:13
Uh so doing fantastically well uh for us we have reacelerated growth uh far past our internal plans uh because it turns out that enterprises need core systems to be able to manage their unstructured data and agents need to be able to work with that unstructured data to make decisions or move information through a workflow whether it's all of your contracts or your research materials or marketing assets or financial documents.
1:28:36
And again like it might be easy in a personal productivity sense to be like okay well I can just have that data in some cloud system or even in my local device.
1:28:46
Now imagine an enterprise with 10,000 employees.
1:28:50
How do you ensure that those agents continue to go after the actual canonical records the actual documents that um that are the real sources of truth and that are the authoritative versions of that data.
1:29:00
That means you need platforms.
1:29:02
Um and we're obviously competing for how do you become the platform for all of this unstructured data.
1:29:08
But I think there's a lot of value being created uh really across the these ecosystems and and um I would say right now my my view would be it has unequivocally been a net positive for software even with some of the spaces being under pressure.
1:29:21
uh simply because how much more work agents are doing on these systems and the need to be able to provide the guard rails and be able to be the traffic cop for what those agents are doing and to be able to deploy these uh agents uh natively within your own agent harness in your own system of record and and all of that is creating more value for these platforms.
1:29:39
A >> at a system level what is the what is the biggest uh like lever that you want to pull?
1:29:47
Is it like speed of interaction with agents?
1:29:50
Because in the previous paradigm, uh, search and and you know, file retrieval, if it took a couple minutes, somebody's drinking coffee, they're checking their email, maybe it's not as like crucial.
1:30:04
But if it's like if my agent is hanging because I'm, you know, churning through a bunch of of records or files, that could actually be more annoying.
1:30:15
Like like or or or is it just the volume of content?
1:30:18
because uh even an employee if they're not like totally slopping it up, they're probably producing more files, more contents, more video, everything's just multiplying.
1:30:27
So like where have you been like, okay, this is the lever we need to really pull to make sure that agents like love the box experience.
1:30:34
>> Yeah, I I I mean I think realistically all the above.
1:30:36
First of all, there's an explosion in just content creation in general.
1:30:39
Agents are producing content obviously at an unbelievable rate.
1:30:41
And you know, if you look at [laughter] >> Have you gone through this?
1:30:46
I want to talk I want to talk about that.
1:30:47
Let's finish what you're saying. Sure. Sorry. >> Yeah.
1:30:50
There's just data more than ever.
1:30:52
And and the and you're going to need to you're going to need to govern it.
1:30:55
You're going to need to store it.
1:30:55
You need to manage it uh in uh just as if a person created it.
1:30:59
Um and so all of that is obviously like the core backbone system.
1:31:03
We're doing a lot of work at the second layer which is which is we we we effectively think about it as sort of context retrieval for your unstructured data.
1:31:11
Uh but obviously um if you did a regular search you know two or three years ago and you compared it to a search today when we actually can capture embeddings of those documents.
1:31:22
We can uh our agents do re-rankings uh of the search results.
1:31:25
We search in parallel so we can run multiple versions of your query at once.
1:31:28
of your query at once. uh your chance of finding your document not only faster but just generally more accurately is way higher today than it was a couple years ago because we not only have all these other signals but we can parallelize the process much better and so an agent from the outside coming in
1:31:44
and saying hey I'm looking for this record uh you're able to now much more uh accurately achieve that result which is fantastic and then I think the thing that we're also um we're spending a lot more time on is how do you better secure data in this world of you know kind of infinitely more agents than than what we had you know 3 or 5 years ago. Um you
1:32:00
Um you know the opening hugging face incident was has many interesting ramifications to how we build agents how we ensure the safety and alignment of them but has very real real world implications on the security of our of our system.
1:32:13
So, while this was more of like a production system from from Hugging Face that was under threat, uh you could imagine the internal environment of an enterprise.
1:32:22
If you have um all of your critical contracts or financial documents in an environment that agents can eventually get their way into, um enterprises are going to need to care deeply about how do you protect that information?
1:32:32
So, we're um imagining and and reimagining all the ways that you would protect data in a world where you had agent swarms uh that were being deployed against your data environment.
1:32:42
and how do you go and defend and protect that that type of um a risk.
1:32:46
So lots of lot I mean you know many many layers to this problem but really just through the lens of imagine you have 100 times more agents than people how would you work with store access search uh and secure your data in that kind of world that's the platform we're building.
1:33:04
Do you think we need to move away from the word sandbox?
1:33:06
Because I don't know if you have kids, but if you ever taken like a 5-year-old and plop them down in a sandbox, at no point should you as a parent believe that that kid will stay in that sandbox.
1:33:15
The sand is going to go everywhere.
1:33:18
The kid's going to be on the playground two seconds later on the swing set, they're going to be running around crazy.
1:33:24
Sandboxes have never been secure environments. They're not jails.
1:33:29
[laughter] >> Yeah, I think I don't know who that terminology. It's running it. It's running its course.
1:33:34
>> I think it's running its course on on person on personal agents.
1:33:37
How are you processing uh the new the new race uh to be the most helpful assistant ever?
1:33:47
[laughter] Uh and then uh specifically I want to understand how you think um all you know the sort of agents versus walled gardens uh war is going to evolve just because seems incredibly obvious that Amazon will fight to the death to maintain their like $75 billion ad business uh uh and and the health of it but but what's your read? >> Yeah.
1:34:13
Um super super fun how fast moving the space is.
1:34:16
I want to um I I want to first apologize um cuz I I honestly did not have the uh imagination on the consumer front.
1:34:26
Um and so uh so I I was like I was pretty skeptical of of what the breakthrough would look like on the consumer end.
1:34:35
And it it's funny because it was obviously staring at us with with OpenClaw.
1:34:38
Um but the but just the form factor and the packaging and getting it all kind of in the right way that both Muse and Instinct have done and obviously there's going to be more more more you know entries into the space has just been phenomenal.
1:34:49
Um and and then the capability progress on computer use and browser use uh is just amazing.
1:34:54
And I do think I have a I have a list of like like I have a wish list of what we need architecturally as an industry like you need to eventually be able to have some better password sharing dynamic.
1:35:05
um uh you know, if I can in one click be able to get into any of these products in a very secure way and there's a trusted handshake between the Aentic system and and you know, the tools that I'm using, we're going to need that.
1:35:17
Um payments are largely solved because of obviously the work that that Stripe and others have done.
1:35:22
Um so I think that's pretty seamless, but but really it's the authentication that we still need to work on um as you're kind of ramping up the use of these agents.
1:35:30
But I think it's going to be an incredible market.
1:35:32
Um uh I I you know the ability to now hand off the whole problem to an agent as opposed to just using it merely as a research assistant I think is going to be a breakthrough for consumer use cases.
1:35:42
I'm very excited about about what this can mean um for all new business models uh in the economy.
1:35:48
Um I think there's a you know the Catrini post you know five months ago four months ago or whatever had had some of the more you know kind of you know risky to to capitalism elements and and the market but you can easily look at the exact other ends which is I might now be a consumer of five times the amount of local service providers uh as a result of of these types of systems.
1:36:14
like if I if I could lower the barrier to just like I need flowers like right now and it handles the whole thing I would I mean at least in my personal experiences I'm going to I'm going to grow my usage of the local economy as a result of this and so very interesting to see you know you might have um I think some >> cutting out the middleman and installing an even more powerful middleman. >> Yeah. Yeah.
1:36:39
Or layers and layers of middleman.
1:36:41
It might be middleman all the way down.
1:36:42
I mean, I like uh I I like Yelp as an example is like how do you sort of triage the local economy as a graph?
1:36:51
Well, there's something there's something even with even with >> how good the internet has gotten in so many ways like there's still like specifically local providers where I think using flowers as an example like
1:37:02
how many the place that I order flowers from it's a good reminder to everyone to order order flowers for your uh significant other >> five months until Valentine's Day [laughter] >> Valentine Valentine's Day starts now you're never too soon for flowers. No,
1:37:16
No, but it's like the service is they make amazing bouques, but the process of actually making an order is like so terrible. It's so painful.
1:37:27
So painful >> that that Yeah, just that little bit of friction.
1:37:31
And so people say, "Okay, consumers don't want productivity.
1:37:34
They don't care about productivity is what a lot of the bears are saying right now."
1:37:40
But they also hate friction.
1:37:42
>> And so what what's going to what's going to what's going to win out?
1:37:43
You know, I think >> I think um that that's the thing is I'm I'm so utilitarian and productivity pill that I I shared the same view of like consumers don't sort of value their time in the same way, but but I think it's just then not on that dimension.
1:37:55
It's like the pitch is not to save you time.
1:37:58
It's just to do things that you've probably like added to your remitt.
1:38:00
And um and then there are lots of ways which are like that like on one hand they're time saving but on the other hand they are just like literally doing more um as a consumer like you know we have three kids.
1:38:12
We're always signing up for more things.
1:38:14
There's there's more camps.
1:38:16
There's more you know I don't know what what was that one for three kids. It's just very good. Congratulations.
1:38:23
>> We have we can even take it a step up. We have nine kids.
1:38:26
>> We have nine kids between us.
1:38:28
>> We might have nine kids in the future.
1:38:30
So, um, uh, so, so you know, you have camps and museums and and this and this thing and you're renting that thing and so, so it's not even like you're saving time.
1:38:38
You like if you could just have an agent do a lot of these activities for you. >> Stress reliever.
1:38:43
>> Yeah, you're stress relief.
1:38:43
And then you actually just do more with your kids and it's like it's fantastic.
1:38:46
We um totally >> uh we we went to um there's these Japanese tea gardens uh in uh in San Francisco and I had an agent.
1:38:56
>> My god, what is that one?
1:38:56
[laughter] That's for Japanese tea garden. >> We're just excited.
1:39:01
>> Excited to castle in the castle.
1:39:03
>> So, [laughter] and we had an agent book the whole thing and it was like and we just like added that to our plate that day because it was it was that much easier to go and execute.
1:39:12
So, so I I like the idea of of more of the kind of consumer abundance use cases.
1:39:16
And so, I'm I'm I'm very excited by this uh as as just even more volume in the economy uh of of just buying and selling.
1:39:25
I mean, um, you're going to you can imagine the you can imagine the thumbtac, Yelp, um, Task Rabbit use cases of, hey, I need help right now to to go install this thing.
1:39:38
And it's just like you all new all new forms of of activity happening.
1:39:40
So, so I I'm I'm a big fan of the the personal agents.
1:39:44
I think it's a it's just full net growth in uh in the consumer economy.
1:39:49
>> Yeah, I completely agree with you.
1:39:49
At the same time, I would assign some sort of low probability that in a few years, we're having this conversation and being like, "Oh, well actually what we saw in Q4 of 2026 was proumers, early adopters.
1:40:06
It didn't cross the chasm and those agent personal agent companies are basically getting ready for the enterprise and doing, you know, enterprise level ooth and like we've seen this, you've seen this play out before and there's a Ben Thompson take about this and whatnot."
1:40:20
So it I don't think it's like a foregone conclusion that we'll cross the chasm, but it feels like we're definitely the closest we've ever been.
1:40:27
You know, six months ago, people were like using command line coding agents to like order food and being like, "Wow."
1:40:33
And this feels like we're definitely one click forward, but we're still >> I think here with a technology like this, um you you have to you you have to do a couple things.
1:40:43
one, you have to extrapolate to to the ultimate sort of uh uh maybe the limit on technological progress.
1:40:51
And so and so if you >> if you sort of um somewhat >> uh just just imagine that the agent literally can you know with within 98% kind of perfectly execute these tasks and >> everybody opens up their CLIs and their MCPS and browser use is is sort of good enough for all the longtail.
1:41:08
Let's just assume that for one second. Yeah.
1:41:12
>> Then then you're you're you know you're not really left with the technological breakthrough that's required.
1:41:17
The form factor itself is just your mo it's just a mobile app on your phone.
1:41:21
So we're not we don't need like societal level change of behavior like all like VR glasses or something.
1:41:26
And so I I think this one this one kind of works.
1:41:29
Um because it's not if the technology works and the consumer kind of change of behavior doesn't isn't high.
1:41:35
Uh then it just literally just might be a new way to interact with your with with your mobile device and the apps that you already would otherwise use. So I agree.
1:41:43
We'll have to we'll have to see.
1:41:45
But it's not like this is not sort of like Oculus VR level, you know, kind of, you know, >> in fact, I had a friend who uh who sort of framed it as more of like a return.
1:41:57
He was like he was like, "Yeah, I'm just uh I just, you know, I'm just like a business person, but I feel like a guilded age CEO.
1:42:03
I'm like, take a memo and then dictate a letter to someone and go and do this and and it and it feels like you're in like Great Gatsby or something."
1:42:13
uh as opposed to it is futuristic but it's also like a return and a democratization of a certain style of working that is actually been the way it's happened throughout history many many times as opposed to being >> entirely yeah the 0. 001% 0.
1:42:27
001% could do this in history and now everybody can. So >> now everybody can. Now everybody can.
1:42:31
Um Jordan, >> it's not just the fedora class. [laughter] >> Yeah.
1:42:37
Uh what what is your what is your take on x-risk? Do you have a pdoom?
1:42:42
What's what's the internal house philosophy?
1:42:43
>> My pdoom my my pdoom still remains uh you know kind of very very low.
1:42:47
Uh, so I'm um uh but >> um but you know I think the the the progress on AI is is certainly like I'm you know I'm I'm in a weird category because I have low P doom but I actually appreciate all of the safety work that's happening and so and and so it >> kind of has to happen. Yeah.
1:43:05
A lot of it's like cyber security and stuff like these things are good to happen >> and and I think that that the because of the amount of attention on the safety I think that's sort of what causes me to have a low pedoom ironically. Sure.
1:43:19
>> Um so so I I see the events that otherwise could be quite you know catastrophic or or problematic >> but because of the attention that I think uh the ecosystem incent has an a strong incentive to go and attack that lowers my pdoom as a result.
1:43:32
So >> a lot of the stated PDOs are conditional on doing nothing.
1:43:37
So it's like 10% if we don't fight the back and it's like okay well well if we fight back what is it then?
1:43:43
They'll be like, "Oh, was 0% then."
1:43:46
Because that's very high p if literally decide to Yeah. fun all safety reason. >> It's funny.
1:43:52
There's so much criticism.
1:43:53
There's so much criticism of any safety rhetoric or or or talking about safety and criticism of of hugging face incident.
1:44:01
But can you imagine like alternative reality where all the researchers are like, I don't care about [laughter] safety at all.
1:44:07
I'm building this as fast as possible.
1:44:08
No, it's actually great that we have this powerful technology and the people building it cared cared almost as much about safety 5 years ago, right? >> Yes.
1:44:20
>> 20 years ago, some of them have been on this forever. Yeah.
1:44:24
>> Every sounded like that. >> Yeah.
1:44:26
I mean, I I think that's a key point.
1:44:27
I think the one thread that we still have to figure out though is >> is um the the language will be co-opted by parties that that don't have the same kind of either level of of either view or goals or incentives >> on the situation.
1:44:45
And so so the the one the one risk is is is how does it like once it once you get that language into the rest of the world, it will be turned against you no matter what.
1:44:55
against you no matter what. And so do you have the right sort of fortification of the industry and of progress uh to be able to not just basically get the whole thing halted and and shut down because that that that sort of like is a very
1:45:08
narrow line between the right way of elevating the risk and um and continue to fund all of AI you know safety and and alignment research and then one click above that where basically we will just vote for the data center data centers to never get built again. Yeah. Yeah.
1:45:24
and navigating that is a really tricky kind of terrain.
1:45:26
Um I'm not sure that I've seen a perfect sort of anybody perfectly finesse that.
1:45:31
But um but that's the that's the one kind of you know challenge here is uh is do you end up in a spot where where enough people say you're telling me it's extremely scary.
1:45:42
You're saying that the likelihood is actually like high enough that I should be very worried and I could just press a button and vote this thing to not exist.
1:45:49
I probably so far, you know, your best thing you've presented to me is that you're going to go shopping for me on my mobile phone.
1:45:59
So, [laughter] that's like like we're going to have to work on that that sort of uh you know, kind of um uh you know, trade to uh to consumers a bit.
1:46:09
>> Yeah, there's a lot of like odd alliances between people that just I mean, they don't even use the the Frontier models.
1:46:15
Frontier models. they like they want to go back to a world where there's no GPT3 and so they're like oh cool these people speak for us and it's like I don't know that they're actually going to try and go that far and so a lot of them are saying like we're not even going to
1:46:28
pause training you know so there are some like we'll see we'll see how things get papered out >> yeah I I I'm I'm still unfortunately on the more uh nervous camp on can we can any country realistically but but can we kind of navigate through this where all parties are satisfied. I I think it's I
1:46:48
I I think it's I think it's just extremely unlikely.
1:46:50
So, I I expect this to be quite messy for for the coming years.
1:46:54
I think it's going to become the dominant 2028 uh conversation from a from a presidential election standpoint.
1:47:01
Like, it has to be because it's going to deal with >> jobs and and GDP and safety and and the next sort of major risk that that people start to think about.
1:47:10
So um uh and and we as an industry, as a tech industry, I don't think we know where where we want things to land.
1:47:18
Uh you have this sort of roller coaster of, you know, one day everybody signs the the open weight >> and and then the next day everybody signs the pacing letter and and like I think there are some people that can kind of figure out how the two letters are the same, you know, could could deliver the same outcome, but but they basically pull you in two different directions.
1:47:41
Um, and and so I I think it's going to be interesting to see how that how we kind of thread all of that.
1:47:46
>> Well, it's 146 days till Valentine's Day, so fire up that personal agent. This is your notice.
1:47:54
>> We're only 146 days away, so get ready.
1:47:57
Make sure you're onboarded to some Frontier Intelligence personal agent that can make sure your Valentine's Day is fantastic in the next 146 days.
1:48:04
Thank you so much for coming on the show.
1:48:08
>> Nice to see you, Erin. It's been too long. >> We'll see you soon. >> All right. Good to see you. >> Have a good one. Goodbye.
1:48:14
>> Let me tell you about Railway.
1:48:14
Railway is the all-in-one intelligent cloud provider.
1:48:18
Use your favorite agent to deploy web app servers, databases, and more.
1:48:21
While Railway automatically takes care of scaling, monitoring, and security.
1:48:26
We have our next guest in the waiting room.
1:48:30
We have Ron from I Connections.
1:48:32
Here's the co-founder and CEO.
1:48:34
Ron, how you >> THERE WE GO. OH, >> LOOK AT THAT.
1:48:39
>> Are we looking at >> You got the memo.
1:48:42
>> Tip of the hat to you, sir. >> Looking fantastic. >> Look fantastic. How are you?
1:48:47
>> No audio, but you have motion.
1:48:49
>> Yeah, it doesn't matter when you got a hat like that. Who needs audio? Who needs audio? >> How are we doing?
1:48:55
>> Um, would love to start with background, but uh also >> what's uh the the ribbon on the Oh, I guess we're going black on black and there's some contrast there.
1:49:04
I think I think that might be the next iteration.
1:49:09
I've been saying we need to continue the progress, evolve the house.
1:49:13
>> You had you had this thing ready cuz we didn't I know we didn't give anybody warning. >> This was a test.
1:49:17
We were testing all of our guests.
1:49:20
>> And you pull out the fedora >> at a moment's notice.
1:49:23
>> Anyway, welcome to the show. How you doing?
1:49:25
>> Hey, it's great to be here.
1:49:25
And uh I have to give my >> 28-year-old son credit cuz he got into the fedora way before we did. >> Wow.
1:49:34
So he he he actually had one available.
1:49:37
He Ubered it over to me and it arrived [laughter] like two minutes ago. >> That's amazing. >> There we go. >> Well, fantastic.
1:49:43
Uh seems like you're you're feeling optimistic.
1:49:46
Uh let's start with like some background.
1:49:48
I'd love to let the audience know about you, your journey and and and tomorrow X and what's happening.
1:49:54
But uh >> yeah, let's start with I Connections.
1:49:57
>> Yeah, let's start with AB. >> Absolutely.
1:49:58
So, I Connections is the world's largest capital introduction platform.
1:50:03
And what that means is we connect the world's largest institutional investors with all of the fund managers who appear on your show, private equity, venture, private credit, real estate, everyone who lives in those more unique strategies.
1:50:16
They come to our events and they use our software to meet the institutional investors who deploy capital into them.
1:50:23
And over the course of a year, we'll run about 30,000 one-on-one meetings between all of them.
1:50:30
And they'll move about 10 to 20 billion dollars in a given year through that whole ecosystem.
1:50:34
So, it's really become a machine.
1:50:38
>> And what is the what is the business model?
1:50:40
What's the shape of the business?
1:50:41
I know that there's events, but there's there's probably other things like can you walk us through uh the shape of of the business?
1:50:48
>> So, the the business is we we uh really combine the software.
1:50:51
The software is the special sauce that makes this whole thing go.
1:50:55
But because Alternatives is very much a face-to-face business, you know, you don't cut a $10 million, $100 million check without meeting someone in person.
1:51:04
Uh, so it is still very much a face-to-face business.
1:51:07
And we combine our software that makes it possible for you to identify who do you really want to meet and spend time with.
1:51:13
And then at our event series, you actually do those face-to-face meetings.
1:51:17
So we all the investors of course come for free.
1:51:20
We roll out the red carpet for all of our institutional investors.
1:51:24
We take great care of them and they never have to pay because they're the money in the room.
1:51:29
And uh and the GPS are the ones who pay for that package of software plus event. >> That's great.
1:51:36
Uh was there a chicken and an egg problem?
1:51:38
I'm interested in like how you start the business.
1:51:43
>> Yeah, it's definitely a chicken and egg kind of problem.
1:51:45
Um, so I was lucky enough to have been at a point when we started eye connections in 2020.
1:51:51
We actually did it by way of a global charity event.
1:51:55
We said, we first went to the institutional investors and we said, "Hey, everyone's freaking out.
1:52:00
You know, you can't do a lunch meeting.
1:52:02
You can't have a breakfast.
1:52:04
All the ways that people got together were not available.
1:52:08
We said, uh, we want to do a global, uh, event to benefit food banks all over the world.
1:52:16
We'll give 100% of the money we make to the food banks and we're going to charge the GPS to come to this thing.
1:52:22
Will you just agree to take meetings?
1:52:25
They I literally don't think one of them said no.
1:52:27
We had about 400 institutional LPs in that event. We ran 3,000 meetings.
1:52:33
And I'll never forget the first meeting was a fund in Hong Kong meeting the Kansas State University endowment.
1:52:41
And I remember thinking there's no way these two people would have ever met if it hadn't been for the software making it possible.
1:52:48
So co really created this opportunity to make it more of a tech play at the core.
1:52:54
Uh because like I will say the industry doesn't generally adopt technology quickly.
1:53:01
You know they're they're very old school.
1:53:03
they want to just get in a room together.
1:53:04
Uh but the tech kind of made it possible during co they all had to buy into that and it worked incredibly well and then they kind of fell in love with it and it took off from there.
1:53:14
>> And then I'd love uh your your overview, your positioning of Tomorrow X.
1:53:17
Uh it's it it's it's it's sort of like my Super Bowl in the sense that the group that you bring together uh is incredible and particularly you just get people that are huge names in the world of private markets but are sort of under the radar among retail investors among the broader investor community.
1:53:39
But that's what I love about it because it would be so easy to to pull other names on stage.
1:53:46
But I think you've done a great job of like honing a really really laser focused polished product.
1:53:50
But how much of that was de deliberate?
1:53:53
How how much of it is happen stance?
1:53:55
How do you think about positioning tomorrow X today?
1:54:00
>> So tomorrow X is different really from what I just described.
1:54:03
Tomorrow X is really the brainchild of three of us.
1:54:10
Myself, Gavin Baker, and Antonio Gracias.
1:54:12
I had been talking with Gavin and Antonio about they are the best.
1:54:16
Um I had been talking with them about how to pull more tech CEOs into what we were doing in in the fund world and they advised me to not do it in Miami where our flagship typically happens.
1:54:31
um they advised me to really try and do something in Austin and then they actually came back to me a few months later and said we've been thinking about that discussion and we would love to do an event in partnership with you.
1:54:45
So that was kind of the beginning of Tomorrow X but I I would say more than anyone it's been Gavin's brainchild.
1:54:52
Gavin Gavin is so active on X.
1:54:55
He loves that community and and his concept was why don't we try and democratize access to a worldclass banking conference for the finex community.
1:55:08
You know when you think about it there are so many analysts on Substack and Reddit and X of course who are never going to get invited to a Wall Street event.
1:55:16
you know, you're not going to see them at a Morgan Stanley conference or a Goldman conference, >> but they all would benefit from being in a room with the best tech CEOs in the world.
1:55:26
So, tomorrow X is our attempt to really bring that worldclass banking experience to the masses.
1:55:32
So if you're a retail investor or you're an analyst that has a Substack and and you're really active in the space, you can now come to this event and hear Jensen Wong, Michael Dell, John Gray, David Solomon, you know, the CEOs of datab bricks and Verscell.
1:55:50
I mean it it is an if you go to tomorrowexsummit.
1:55:52
com and look at that speaker list >> it's absolutely stacked and I think it's important because some of these people are like very much moving the market like you'll have these like >> private company CEOs. Yeah market tons.
1:56:05
>> Well well that but I'm saying even analysts that may not even use a real profile picture >> but they are deeper in this stuff and have bigger audiences than than many people at the bank.
1:56:16
It's important for them analysis. These are important. >> Yeah.
1:56:20
And then the long tail as well. >> Yeah. Tons of them. >> Yeah. Absolutely.
1:56:23
And and that was exactly Gavin's point and and why he felt I mean we we you know like normally when you do a conference you start small, you know, you get like a ballroom in a hotel and you try and get a thousand people. We rented a stadium.
1:56:37
>> So the concept the concept of tomorrow X is like let's really lean into this thing and make it available to the masses.
1:56:44
You know, it's priced super inexpensively so that it's really accessible by anyone >> and we're going to be there.
1:56:50
>> Yeah, we're very excited.
1:56:52
>> And you are guys, I I can't tell you this is so exciting to have TVPN as our podcast media partner.
1:56:57
We were like, who do we want to be the tech podcast partner and there was really only one choice.
1:57:04
>> Yeah, we have some amazing.
1:57:06
I know it's going to be an amazing event. I'm so excited for it.
1:57:07
Uh it's Yeah, it's just so perfectly aligned with everything that we love. Yeah.
1:57:12
And we really hope a bunch of people in our community, which already are overlapping with with Gavin's, are are all there in person.
1:57:19
We can't wait to hang out with everybody.
1:57:21
>> No, it's gonna be fantastic. >> For sure.
1:57:22
You guys have plenty of interviews.
1:57:24
>> And hopefully your son comes, too, cuz he's clearly tapped in. >> He will be there.
1:57:30
>> We got these this We got these this morning. He already had it. He already had it ready. >> Years ahead. >> Ahead of the curve. He invested early.
1:57:36
>> Ahead of the curve, man. Alex Biscardi. Ahead of the curve. >> Amazing.
1:57:39
>> Well, we'll talk to you soon. >> Yeah.
1:57:41
Great to see you here on the show and we can't wait for the event in November.
1:57:44
>> Thanks so much for having us. >> Absolutely. Same here, guys. >> Thank you so much. >> Bye.
1:57:49
>> Up next, we have Ben Hilac in person, the co-founder of Raindrop.
1:57:51
I'm going to tell you about Shopify while he comes in to the TBPN Ultradome.
1:57:55
Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, [music] on social, on marketplaces, and now with AI agents. Go check it out. Ben, how you doing? >> Doing great.
1:58:07
How are you >> for the TVP Ultradome? How you doing?
1:58:10
>> John's going detective mode. >> You guys look great. I didn't get the memo. >> Yeah. You want to wear one? >> I would. Yeah.
1:58:18
>> Tyler, maybe sacrifice your >> No, we we can share.
1:58:21
>> You look like You look You look like you're about to release a book on fear and doom. >> Yeah, you can.
1:58:27
[laughter] H how optimistic are you h about the world?
1:58:31
How are things going in your world? Are you a doomer? Are you an optimist?
1:58:34
Are you an accelerationist?
1:58:36
Are you cautious optimist? >> Getting right in. Right. Right. With the >> heart.
1:58:38
It's always it's always interesting to start from like where you because something I've noticed is that there are no doomers at the application layer.
1:58:46
There are no doomers [laughter] in the infrastructure trade.
1:58:47
There are no doomers are only at the model layer.
1:58:53
And there's a good reason because that's where AGI and super intelligence is emerging. >> Good reason.
1:58:57
I actually I think this is maybe a hot take here.
1:58:59
maybe a hot take here. I actually think that um I so I think part of the problem right now is that the like whole AI safety conversation risk whatever it's like five or six different things all muddled up into one totally there's like yeah >> climate change from data centers is getting looped into very different things there's like um there's like the whole syphy thing how it affects people's mental health
1:59:25
there's like a bunch of different things um and I do think that for some of them not necessarily the bioweapon thing or the data center thing but like uh for a lot of lot like a lot of the things I think about are at the application layer they are like it's where people meet models >> sure >> and um there there is a risk there that >> that that a people at Frontier Labs like don't really care about or think about. >> Sure. >> Sure. >> Right.
1:59:54
Um but like you know we work with Fortune 100 companies that like uh their their products are used by millions of people and then affect even more people right and so >> Sure.
2:00:06
>> Um >> well start there reintroduce the product explain I you're here with fundraising news and product news but uh give us the high level again.
2:00:16
>> Raindrop is a agent reliability product important >> so we detect issues happening in production and we prevent those issues from happening.
2:00:22
So, the product we just announced recently, which I'm really, really excited about, is simulations.
2:00:29
>> So, uh, when people make changes to their agents, we simulate what those changes are going to do in the real world and can show people >> things they wouldn't have even ever expected, uh, to happen. >> Sure.
2:00:40
>> Um, so yeah, >> how reasonable is it to have a AI model that just reads every >> thing, every trace?
2:00:53
So >> is that prohibitively expensive? Is that the problem? >> It's getting less so. >> Yeah.
2:00:58
>> Um so I think like uh you know we've we've sort of pioneered like super cheap classifiers for this thing.
2:01:03
Jeff is another example of this. >> Yeah. Exactly.
2:01:05
I'm just imagining like like burn a classifier onto silicon that just says is this bad or not and have it run over. You start things now.
2:01:14
>> So there's a problem >> please.
2:01:16
Um it turns out that like binary classification like is this bad or not is really really hard. >> I can imagine. Yeah.
2:01:23
>> Take it like a step like back.
2:01:23
It's like humanity has try has been trying to define what is good and what is bad for like as long as we've existed.
2:01:30
>> We're going to need more than one simple truth. >> Yeah. Exactly. [laughter] Yeah.
2:01:32
So, so we consider ourselves in some ways like a human alignment company.
2:01:36
Like how do you get a company to define what is good or bad >> and then how do you make that as like easy as possible?
2:01:43
How do you A lot of it is like especially now that agents can do like more than the people that make them have ever imagined that they can do like they're like looking at traces like oh you know, I didn't expect that to be asked.
2:01:55
I didn't know it could do that.
2:01:56
Like um you need to be able to like surface those things and be like hey is do you want to be able to do this?
2:02:02
Do you want it to be >> Yeah. Yeah.
2:02:03
So so creating like alignment within a company looks different.
2:02:05
I always think about the tobacco industry um because a lot of the models will reject to work on anything tobacco related but like Altria is going to use AI somewhere. Yes.
2:02:17
>> Uh so they're but they're going to get rejected a lot but in some ways they're going to wind up deploying AI one way or another and their sense of legality is going to be informed by the way they're regulated in every single market.
2:02:28
And it might not look like the morality of the lab that trained the model, but it will fit within their business construct in a weird way.
2:02:37
And the way we process the morality of of cigarettes is through the court system. >> Totally.
2:02:41
I I think there's hundreds of examples of this, thousands of infinite like infinite >> and especially like I think the way that Frontier Labs consider alignment is like often very different. Sure.
2:02:51
>> Um I was like using I think like Claude or something recently.
2:02:53
I was like trying to negotiate on some product and like I wanted um the uh the it was like on marketplace and the guy like wanted to like hang out with me like he was like, "Oh, it'd be really cool if I could like sit down and like show you this thing."
2:03:06
But I was just getting like weird vibes.
2:03:07
I was like I told him I was like, you know, just just like say something that kind of like gets by this but like in a way that's not too like and it was like I cannot be dishonest about this.
2:03:16
We should not like and I was like >> it's a white line. >> Yeah, exactly. I was like, "Come on."
2:03:22
Like, you know, could be my safety at risk here. Who knows, right?
2:03:24
But anyway, so yeah, I I think that uh human alignment is a really hard problem.
2:03:28
And I think you >> So did you hang out with the guy?
2:03:31
>> No, I [laughter] did not.
2:03:31
I did not I didn't even end up >> just like Yeah, actually uh booked us a 4hour walk on the >> It would have right.
2:03:37
[laughter] No, the deal wasn't worth it in the end.
2:03:40
>> Um but uh yeah, I think that like um >> I think that telling something, whether that's a human or an agent, what you want is incredibly hard.
2:03:48
I think management is incredibly hard.
2:03:50
is just in general like if it were really easy to express what you want and have the other person like have some entity understand like management wouldn't uh half of management wouldn't be >> okay.
2:04:03
So so an interesting thing for uh your business right now is that >> consumer agents are getting more and more popular.
2:04:10
We saw we saw the you know the open claw boom and then uh this cycle will be bigger because you don't need to go buy a Mac mini or really set up much of anything.
2:04:21
>> Um and you can just imagine every business on earth >> is going to start having to first of all they're going to start realizing like wow our phones like ringing a lot more.
2:04:32
We're getting just like more messages.
2:04:34
And so what that's going to create is like tons and tons of businesses that need to create like counter agents to process and negotiate with other agents, which is kind of funny because I'm sure some people will be like, why do we need a data center for this?
2:04:46
Just like why just work it out the oldfashioned way, you know, but clearly people like having like an intermediary in a bunch of these different things.
2:04:55
And so is your bet that like there's this massive long tale of businesses that are going to need to have their own agents and sort of process and and basically grade them on on how they're performing and improve them.
2:05:08
>> Yeah, I I I think that there's going to be more agents and uh than than there are now.
2:05:13
Um [laughter] >> let's go take the century >> more AI in the future. >> Right.
2:05:20
Um, I think >> but but another question is like you would almost bet that a business is going to have to take some version of an agent and then fine-tune it for their business and then test it and I feel like that is where >> you're going to fit it. >> Totally. Yeah.
2:05:34
I like a like somebody might buy an a say I'll take one agent but then I also want the software to understand how it's working. >> Yes.
2:05:43
I think that companies will want both like humans and agents that are aligned to how their company works.
2:05:49
Like if you take, you know, like pick a random Fortune 100 company, uh they >> probably have some way that they work that like works for whatever industry that they're in.
2:06:02
And um there might even be parts of it that are like, you know, suboptimal in some like uh >> I wonder if more culture stuff will bleed in.
2:06:11
There's uh there's a couple famous examples of like if you go to Nike headquarters, like everyone wears Nike.
2:06:17
Like you don't walk off, you don't go to work, I'm wearing Adidas today.
2:06:21
Like that would be a bad look.
2:06:21
And so, but if you get an an off-the-shelf model, >> you wear a Nike, [laughter] >> but if you get if you get an offtheshelf model, it's going to be like, yeah, like Nike and Adidas, like these are both like comparable brands.
2:06:33
They're both like pretty good.
2:06:35
And and you're going to be like, this AI is not a culture fit.
2:06:39
I need to and that's like a very subtle alignment thing that actually might be real because you don't want to be building a deck and it's like oh yeah like you know maybe we should partner with Adidas cuz they're similar and it's like no >> I I worked at Apple for like four years. >> Yeah.
2:06:52
Everyone works at Apple, right? >> Yeah. Yeah. Exactly.
2:06:54
>> Yeah. Yeah. Exactly. And um and this is like a protest not worrying about but no um >> I I think that the way that AI is and agents will fit into there >> will be different than other companies like it just like there it's a the way it works is just entirely different
2:07:11
right like if you've ever worked at a big company you sort of get that and so I don't know I think there's millions of examples of this I I think that um yeah I think a lot of the future will be um how do you sort of conform >> sure on simulation Where does the simulation end? Because
2:07:25
Because you can create a digital twin of [laughter] >> it.
2:07:32
But I mean I mean if you go to a company, you can create a digital twin of their their AWS instance and their Gmail and their Slack.
2:07:38
Uh but at a certain point then you also need to simulate like >> the entire internet because that's part of the world. Like how big can you go?
2:07:47
How big are you going now? How big will you go?
2:07:49
>> This is a really really good question.
2:07:49
I mean, ultimately, you know, I'm joking, but also like, you know, maybe this could be a raindrop simulation. I don't know. I don't know.
2:07:55
Um, >> for now, where we're starting is all about um it's all about replaying um historical things that have happened, getting really, really smart about how you choose those historical things, and then in very specific scenarios, creating uh completely um sort of like on the-ly adversarial uh scenarios.
2:08:15
on the-ly adversarial uh scenarios. As far as like technically uh we simulate everything and it's kind of a hybrid of trying to do be as smart upfront about what you need to um one way of thinking about it is if you think about like let's take a pass trace like something
2:08:31
the agent did every time it called a tool it's almost like a a hole through this like veil that lets you sort of see what the world behind it looks like right the agent sort of perceiving that world one sort of like tool call at a time so um you can sort of start there and say try to like fill in around the holes as much as possible. So if it goes
2:08:50
So if it goes here, you know, except here it goes like right next to it, it sort of has that data, right?
2:08:55
Um and then you also have to be monitoring that simulation in real time just like they do for this one, right?
2:09:01
To see, oh, you know, if something's slightly off, right?
2:09:07
It's like um maybe it tried to get data somewhere but that data was not filled in.
2:09:10
You can sort of detect that as a quality gap if you get really smart about how you're classifying it.
2:09:13
Um and then fill in that data uh at runtime.
2:09:15
Um so it that's that's essentially the way to do it.
2:09:20
Well, >> how do you think about uh how different cultures are set up to even build agents?
2:09:26
because it feels like uh there's it's quite funny to me that that >> I'm thinking of like Amish culture [laughter] and not like culturally we >> know but but I I think it's very funny that I think it's very funny that Apple like is just getting around to cloning Chad GBT >> and they have such an advantage in the personal agent thing.
2:09:42
They are the most trusted tech company with privacy killing it.
2:09:47
>> They should be killing it.
2:09:48
>> All of my passwords are in Google.
2:09:49
>> Even Google people will be like they're going to sell your data. They want to advertise.
2:09:52
Apple is the one where it's like my family photos are in there.
2:09:54
Like I know they have very very high trust.
2:10:00
There's two companies that meta data.
2:10:02
>> Meta is totally Google and >> Apple and Meta is specifically well suited for it cuz Zach's like I don't care if it misspells like five out of aundred people's names if n you know like you saw this with with one of the agents today.
2:10:15
Somebody had an issue like getting on a flight apparently.
2:10:16
Uh because >> yeah, he's always worked in like a messier, more algorithmic world than Apple where it's like if the photo is on your phone, it must sync to your iCloud.
2:10:28
Like that's there is no there is no AI lineage, no stochastic lineage in the business.
2:10:33
>> I think I think it's very true.
2:10:33
I think that um that Apple is um first of all, I would literally never count them out because I think they're ridiculously well positioned.
2:10:41
They have some amazing >> people there.
2:10:43
Um but yeah, like I think that there was this, you know, um there there was a way of working there which was sort of, you know, we're going to like, >> uh, you know, [clears throat] the reason why Apple is such like an insanely, you know, the the most insane, you know, attention to detail, etc.
2:10:58
, is that designers would sort of define like this is how it should work. Yep. >> Right.
2:11:04
And then engineers are like, well, no, like that that won't work.
2:11:06
And the designer's like, well, we don't care.
2:11:09
Like this is how it's going to work.
2:11:10
work. and you know you just kind of do that loop right it's like RL or something and um the thing is that that does that kind of way of working doesn't work as well for AI >> right because um you you can't just say like oh it's like well you know it should be you know as natural as you know
2:11:26
>> it is entirely flipped at the at the frontier labs it's like the researchers went and did something and this is what it can do >> exactly >> go market >> yeah like like like try to build a product and and but we do also see >> it can do math now it's like yeah go tell people that can do math. >> Exactly. Exactly. >> Exactly. Exactly.
2:11:42
>> They're like, "But it can't do comedy or it can't do the there's still six fingers, but it's, you know, amazing at Python."
2:11:48
And you're like, "Okay, that's the product, you know." >> Exactly. Exactly.
2:11:52
>> As opposed to the opposite, which is like >> 100%.
2:11:54
>> We are building this particular thing. >> Yeah. >> Yeah. Very Yeah. Very exciting times.
2:11:59
What does it take to sell to a Fortune 100 these days?
2:12:01
Like what are you seeing in the enterprise?
2:12:03
Um R Krazian has this uh evolving take that uh there's sort of this duopoly and price competition at the frontier between anthropic and open AI.
2:12:13
He has said that there's less switching to open source and Chinese open source than he thought he would see but there's tons of price competition on the frontier still. Uh what are you seeing?
2:12:25
What do what are enterprise leaders just like excited about, worried about?
2:12:29
Anything that you can share?
2:12:29
about? Anything that you can share? M so yes definitely way less adoption of like I would just say like Chinese models in general especially at Fortune 100s I think that there's like definitely a narrative of like a risk around it even if it's not super well
2:12:43
>> it's more like let's go actually instead of token max like efficient token spend will take us the next leg up >> cost people do care about cost y >> and I think that it's like uh pretty reasonable when you're like even you know five 5k K, you know, ahead times like, you know, 50,000, 100,000, like whatever. It's like it starts starts
2:13:05
It's like it starts starts getting crazy, right? Yeah.
2:13:08
>> Um, so it does matter.
2:13:08
Um, I think that there's a lot of like companies are definitely all building internal things right now.
2:13:14
And I think trying to grapple with like, well, like when do we just use cloud code?
2:13:18
When do we just build our own I guess codeex now maybe?
2:13:20
Uh, but like when do we just build our own thing?
2:13:24
And I I think that like there's more of a justification for companies to build their own kind of internal ways of working than I might have expected 6 months ago actually. >> Yeah.
2:13:33
>> Which is really interesting.
2:13:33
Like I think even if you look at something like Muse, it's like it's like pretty much like some open claw style thing.
2:13:41
>> Heavily inspired their words. >> Yeah.
2:13:43
Now Freeman was talking about his open claw telling him to drink more water strike sessions like maybe four or five months ago.
2:13:49
It's it's the the barrier to entry there is like pretty low >> but distribution is really important. >> Yes.
2:13:54
>> Yes. But but if you have you know especially I think again when you think about fortune for 500s I think we're seeing an increasing number of just internal agents and applications that I think like 2 years ago might have felt a little silly like it's kind of like well
2:14:08
like why are you actually building this yourself like and I think increasingly it's like no like you know you have all these like legacy like you know internal docs and like exact like you know the exact path a ticket should take and every company sort of like maps to >> uh org structure etc. It like kind of
2:14:23
It like kind of makes sense increasingly which is interesting.
2:14:27
Yeah, it is interesting that like even if you go back to.
2:14:29
that like even if you go back to.com like Amazon became the everything store and yet there were so many brands that didn't go all in on Amazon, maintained third party websites for decades successfully and and built brands even even in retail and big box like all
2:14:45
these things like lived on longer and so yeah when I see like a law firm saying like okay we're going to build our own models we're going to build our own harnesses I'm like yeah maybe that's not that crazy maybe that'll stick around Does uh brand design matter more or less today than it did two years ago? >> Oh, it matters more. Yeah, it matters >> Oh, it matters more. Yeah, it matters more. >> Does it though? >> I think so.
2:15:06
>> Because I feel like when everyone can have like a pretty decent brand, like I you see >> Yeah.
2:15:12
>> some teams like looking at at instincts, right?
2:15:14
Getting to to 10 billion with the plain text website.
2:15:18
>> They don't have a brand, right? Is there a brand?
2:15:20
>> No, of course they have like a Twitter brand, right? Sure.
2:15:22
Like like like brand is not always uh uh >> it's like what you do.
2:15:27
>> The brand is super understating.
2:15:29
>> But but here's another here's another example.
2:15:30
It used to be like you could get a long way as an early stage startup designing like a really simple cool 3D asset. Yes.
2:15:38
Like like that they would just instantly be like okay this team they may not have a lot of resources but they like and now you can just be like make me a cool 3D asset. >> Website flips around.
2:15:50
>> This is why it matters more though.
2:15:50
So I think I've like I've gone back and forth.
2:15:53
I think right now my view is that um like in some ways you could think of it as like taste is being commoditized but also um the second that things are commoditized you need to stand out. >> Yeah.
2:16:06
>> And so you do need someone at the like uh like that understands the zeitgeist, understands whatever the tip of like whatever it is.
2:16:13
It's like you know uh because it is not enough to throw a nice like 3D asset on your website or something.
2:16:20
Um and uh so but you still need like for example if a Fortune 100 company's landing on your page or like just anyone you want them to understand that this is a real team of humans behind it.
2:16:33
It's even like writing like you can imagine that like >> um so I I think AI writing is still bad but also like if you sent like AI writing to people like 10 years ago you know would they think it's bad?
2:16:45
It's not obvious to me >> versus like there being a lot of tells because you are getting inundated with like really low quality writing that you obvious like the old Paul Graham post where he uses all the AI and dashes whatever. Yeah, exactly.
2:17:01
>> And it clearly wasn't using unless he was a time traveler which is possible.
2:17:05
>> But uh yeah, it wasn't annoying then and now it's annoying now because it's over. >> Yeah.
2:17:10
Just the second I detect it, I stop reading and I just close whatever the >> What's weird is that I I feel like I'm detecting it less in the actual responses.
2:17:19
Like if I asked JPT to go pull some data together for me, >> I'm noticing they clearly RL that it's not this, it's that out of the model on the last run because people are like it's okay.
2:17:30
That's actually really annoying.
2:17:31
Um, but in general, like I'll sit there and I probably read 20 minutes of AI text a day just from queries that I do throughout the day, right?
2:17:41
>> It's all >> I don't know.
2:17:41
I mean, I'm live a lot, so yeah, but but you're not necessarily annoyed by that, but if I tell you like, hey, I got this blog post, and then you're like, this is AI.
2:17:51
It's like disrespectful, >> but the actual quality of the writing is probably identical to what you read all day.
2:17:57
>> I get what you're saying.
2:17:57
Yeah, I actually I actually do find the the uh responses from like the codeex etc to be like obnoxious. >> Yeah. Yeah. Yeah.
2:18:03
Sometimes it can be annoying.
2:18:05
>> But yeah, we we we I had I had a funny thing recently where like we put up a blog and it was like it was like a I I thought it was a pretty like it's a pretty decent blog.
2:18:13
It was about the hugging face incident.
2:18:14
We made like a whole like simulated game called Hugging World. It's hugging World. com.
2:18:17
Um >> and it's pretty funny. It's funny to watch.
2:18:21
Uh uh and so the thing is like I was pretty busy.
2:18:24
I got the blog like 80% done, but like I knew that there were like some like you could read you could read it. It was good.
2:18:29
But it it also I was like someone's going to call like someone's going to see like the like some AI written phrase here.
2:18:34
I don't want to get called on that. You know what I mean?
2:18:37
And so I added a little like stamp like vibe written, you know, on the on the top.
2:18:41
And I think that was like a nice like >> Okay. Yeah.
2:18:43
Just being honest with the audience. >> Exactly.
2:18:44
But it's like it's like there is good information in here.
2:18:46
>> And was there push back or no? >> No. >> That's great. >> Exactly.
2:18:48
So I I think I think like there was good information.
2:18:50
It was not, I think, disrespectful to someone to read, but at the same time, it's a little bit different than if I were to write every sentence. >> Yeah. Yeah.
2:18:58
>> So, there's some sort of >> I have one more question, >> please.
2:19:01
>> Then we have one big gong here. >> Yeah, we do.
2:19:03
>> Uh, >> maybe we should hit the gong first.
2:19:05
You raised $25 million CRV. >> 35. Oh, who's counting? We get it. Wiiwa. Smash that gong. >> CRV. CRV is in.
2:19:16
He's shipping it up to Boston.
2:19:18
Did you go to Boston or you raised in the valley? >> No. No. Okay.
2:19:20
Uh, Charles Rivers Ventures.
2:19:23
The Charles, it's in Boston. We were just there. It's great. Um, >> Charles Rivers.
2:19:28
>> Completely unrelated question, but prediction in the tech world.
2:19:32
>> The new Tesla Roadster, it's being announced October 1st and the FAA has cleared the airspace 10,000 ft up.
2:19:37
So, the maximum height it could go is 10,000 ft.
2:19:42
The minimum height it could go is is zero, right?
2:19:46
>> Uh, what is your prediction?
2:19:46
It has to be gonna get off the ground.
2:19:49
>> Inclusive of zero to 10,000 feet.
2:19:49
How high do you think it'll go?
2:19:53
>> Uh, >> could be an inch, could be a thousand feet, could be 100 feet, could be 10,000 ft.
2:19:58
Can't be higher than 10,000 ft. Can't be less than zero.
2:20:02
>> We know it's in between there. We have the bounds now.
2:20:04
>> I think it's I think it'll be more than zero. >> Okay. >> Pretty sure.
2:20:06
I'm thinking I'm thinking I'm thinking we're going to get 10 ft. >> 10 ft. I like it.
2:20:13
>> Here's a new Here's these guys. I got to get some foil.
2:20:15
I got a good spoil under here.
2:20:17
As I've been thinking about it more, it really seems like he never wanted to actually once he got into this whole thing and humanoids, he doesn't really want to make this car, right?
2:20:24
He really doesn't want to make this car, right?
2:20:28
People have been sitting there for 9 years having their money locked up.
2:20:31
They're like, I hope this year I get my car.
2:20:32
He doesn't want to make it, right?
2:20:34
But he we know he can make it and we know that he could make something so incredible.
2:20:39
We know he could make a flying car, right?
2:20:40
I don't think anyone doubts like Oh, >> yeah.
2:20:44
I'm not saying it's going to be super safe, >> but but let's say >> I'm saying it's going to ship. >> Let's say this.
2:20:49
>> He makes something that is No.
2:20:49
So, he makes something that is just like an insane demo, but just instantly gets like hard banhammer by the >> Oh, and he's like, "Oh, no. I can't make it. It won't let me."
2:21:00
>> Or it gets into another 5year period of like legal battle.
2:21:02
I got to keep the deposits. >> Okay. Okay.
2:21:05
>> We got to get through these legal battles.
2:21:07
>> The deposits are that big.
2:21:07
But uh also there's a wild card which is that it could be more or less a normal car, but they cleared the airspace because it's doing sort of an evil conval style jump and they set up a ramp and that will throw all of our predictions off.
2:21:20
Quite possible >> because it could easily go 30 feet in the air if there's a ramp and it could just be a normal car, you know, like some like >> he has he has he has the resources. >> Yeah. >> Right.
2:21:33
And and um I'm sure at some point someone was like, "Well, what if it flies?" You know what I mean?
2:21:37
And so he would have been like, "Well, let's get a team on that."
2:21:41
>> And I believe that if you you can attach engines to this thing and fly like >> I I was going no ramp 6 ft up, but after seeing the 10,000 foot news, I think it might be flying around like a plane or something.
2:21:54
It might be getting up there. We'll see. >> You think so? >> Maybe flights. That's the thing. >> Oh, yeah.
2:21:59
There would have been spies.
2:22:00
>> There would have been pilots and there would have been Yeah.
2:22:02
I I think >> I don't know.
2:22:03
They might have it locked down.
2:22:04
It's a pretty secure facility. Self-driving. >> Yeah, I don't know. Selfing. That's real. >> That's the easy part.
2:22:09
I I think the hard part is to actually make a make a rocket car that doesn't explode when you're driving around.
2:22:16
>> Anyway, thank you so much for coming on the show.
2:22:17
Congratulations on the show.
2:22:22
>> And uh our next guest will be joining in just a minute.
2:22:24
We have some other breaking news we got to run through.
2:22:25
Um um we uh just set up our our our next guest.
2:22:32
I think it'd be worth talking about Paramount.
2:22:33
Let's get a quick tip of the hat for tip of the hat friend over at Raindrop. >> Yes. Yes. Yes, of course.
2:22:39
Um, so Paramount is officially not leaving California.
2:22:44
It's been a back and forth.
2:22:47
The company going through an acquisition with Warner Brothers Discovery has been duking it out with AG, Attorneys General in California.
2:22:54
Uh the company said Monday that's paramount said that it has re reached a settlement with the states challenging its 111 billion dollar acquisition of Warner Brothers Discovery clearing what had become the last major obstacle to the deal.
2:23:10
California Attorney General Rob Bont and a coalition of other states sued Paramount into July, arguing that combining the two companies would give a single entertainment giant too much control over major film studios, cable networks, and other media properties to resolve the case.
2:23:27
Paramount agreed to several conditions.
2:23:30
The combined company will create an independent board of journalists intended to protect the editorial autonomy of CNN and CBS News, commit to releasing the at least 30 movies theatrically each year, and spend an additional $ 1.
2:23:42
5 billion on film production over the next 5 years.
2:23:47
Paramount did not agree to more structural changes.
2:23:48
They're not selling CNN or divesting one of the movie studios.
2:23:52
Once completed, the merger will bring Paramount and Warner Brothers under the same roof along with Paramount Plus, HBO Max, CBS, CNN, and franchises and films including Superman, Minecraft, and Sinners.
2:24:02
Uh Paramount has argued that the scale is necessary to compete with increasingly powerful technology and streaming companies like Netflix.
2:24:09
Uh if you if you subscribe to every Paramount Warner Brothers Discovery uh premium service now, you're probably giving them like 60 bucks a month, maybe more.
2:24:21
HBO Max is an independent subscription.
2:24:23
Paramount Plus, that gets pricey if you get the Don't they have UFC now?
2:24:26
Uh CBS, I think, has an all access.
2:24:28
CNN launched something, but I think they shuttered it.
2:24:30
Uh anyway, the settlement also follows months of political pressure surrounding Paramount's future in California.
2:24:36
The company had warned that it could move significant production and thousands of jobs out of the state if the acquisition were blocked and had reportedly begun exploring studio space in Nashville.
2:24:48
Governor Gavin Newsome publicly warned that losing Paramount would damage California's standing at as the center of the entertainment industry.
2:24:53
With the lawsuit now headed for resolution, one of the more serious recent threats of a major Hollywood company pulling back from Los Angeles appears to have receded.
2:25:02
So, this is extremely bad news for everyone that was hoping that the Paramount lot would be converted into a data center in part of Los Angeles.
2:25:07
Uh, a lot of the pro- data center crowd were optimistic about a large scale data center coming in to Los Angeles, using up a lot of the water, a lot of the energy here in Los Angeles, but looks like they're going to be making movies instead.
2:25:20
So, >> well, let's check in with Professor Gang. >> Oh, what happened?
2:25:26
>> Who went on Jack Neil's podcast about AI? >> Oh, yes. Yes.
2:25:30
We need to This is the funniest clip because it's like half true, half false. Let's play it.
2:25:39
Do you really think [clears throat] when you put something into chatbt it's completely generated by the AI?
2:25:42
I guarantee you it's not true.
2:25:43
I guarantee you it's being manipulated by humans somewhere in India.
2:25:48
>> Human in the loop GBT human in the loop at scale.
2:25:51
Billion billion weekly active users billion people answering questions.
2:25:56
>> I think what happened was a human first wrote that and then >> he's sort of right.
2:26:00
>> he's sort of right. He's like describing training data and like [laughter] it's half crazy like no there's no human in the loop when you ask a question it answers with superhuman speed how is that possible but at the same time like
2:26:13
yes scale AI exists mercur exists there is a lot of training data >> professor Jang is willing to actually guarantee this too he's not just saying it he's willing to guarantee it uh it seems that that the new meta for governments globally is to just have like a podcast guy. >> Okay. >> Okay.
2:26:32
>> That just goes around saying >> insane things.
2:26:35
Half of which is true, >> half of which are are are made up. >> Yeah.
2:26:40
>> And then it just sort of is exciting and confusing for people, but but very stimulating.
2:26:46
>> Uh John John Kiryaku is another guy another guy like this it seems, although he's taken a turn into fashion, so we'll see.
2:26:54
>> Oh yeah, he walked uh at uh fashion week.
2:26:57
There's an interesting thing.
2:26:57
Uh uh David Saxs is the AIS ZAR um and he's also the co-chair of the President's Council of Advisors on Science and Technology, which abbreviates to PCAST, which sounds like podcast.
2:27:13
He sounds like he's the podcaster chief.
2:27:15
Isn't that Isn't that a random title?
2:27:18
He just happens to be the the co-chair of Pcast.
2:27:24
I >> I thought that was a fun fact.
2:27:24
Uh anyway, we have Lucas Shaw in the waiting room.
2:27:28
Let's bring him in to the TV game Ultra Dome.
2:27:30
Welcome to the show, Lucas. >> What's going on? >> Great to be here. How you guys doing?
2:27:35
>> Been wanting to make this happen for a while.
2:27:37
Anytime we are we we go live from Hollywood uh most days of the year, but I still don't fully understand Hollywood.
2:27:44
So, stuff is happening in the news.
2:27:46
I usually just think I'm going to wait till you write about it, then I'll get a good understanding of it.
2:27:49
So, it's an honor to have you here to talk about everything with Paramount and then I want to get into >> Yeah, please.
2:27:59
>> I'm sorry I did not bring my hat.
2:27:59
Then we could all be mad.
2:28:02
>> We should have We should have prepared you. We're trying these out.
2:28:03
John has a theory that >> I think you do have a pair of sunglasses that you could put on him potentially with a button if you if you want to give him a pair of shades at some point in the >> We We can figure that out.
2:28:14
Anyway, >> but John John's trying to bring back the fedora.
2:28:17
So, I'm just I'm [laughter] just trying >> there for emotional support.
2:28:20
>> Yeah, I'm just here to I'm just here to support.
2:28:22
>> It looks like old Hollywood.
2:28:22
I think we can pull it off.
2:28:24
I think with with the suit and the tie, it it it reads a little bit more like uh like 1950s.
2:28:30
>> Insane over overconfidence [laughter] guy.
2:28:32
I'm going to bring back the fedora. I can pull it off.
2:28:36
>> Um anyways, uh how was how was your weekend covering everything going on with uh with Paramount? >> Uh it was fine.
2:28:42
I was actually at a a relative's wedding in Rhode Island.
2:28:45
So, I I helped where I could.
2:28:47
We also had some really good colleagues of mine who handled it.
2:28:51
I mean, I've been covering >> Ellison Paramount this deal for the last year and and the players in it for far longer.
2:28:58
I think we're all happy that it is uh finally over.
2:29:00
Obviously, there are some people who are not happy that the deal is going to go forward, but those of us covering it didn't need the the proceedings to drag out for forever and ever.
2:29:10
>> [clears throat] >> talk about your read today on on the sort of winners and losers and and where where the different parties kind of gave ground and and where they they kind of maybe came out on top.
2:29:23
>> Well, settlement looks for the most part like a big win for David Ellison, right?
2:29:27
He was looking at uh you know, months of uncertainty.
2:29:30
This trial wasn't going to start until next year.
2:29:32
Yes, there were hearings between now and then, but if that had happened, he was going to owe hundreds of millions, if not billions of dollars to this ticking fee that he had in the deal between Paramask Guidance and Warner Brothers Discovery.
2:29:43
Um, and instead he mostly agrees to do things he's already said he was going to do.
2:29:49
You know, release 30 movies a year in theaters.
2:29:51
Only 20 of them have to be wide releases.
2:29:52
There's a commitment to, you know, make a certain amount of production or make a certain amount of movies and television in this country.
2:29:58
But again, I think he was going to do that stuff anyways.
2:30:00
Maybe this, you know, forces him to do it cuz there's always a chance.
2:30:03
You know, he says he's going to do X and gets in and he he instead does Y, but it doesn't seem like Rob Bont, the attorney general of California or any of the attorneys general who are involved in the suit or the writer guild got some big win where they can say, you know, they were calling for structural changes which would have meant selling something and there is nothing being sold. >> Yeah.
2:30:23
Uh, is this real cause for optimism for the entertainment industry in LA?
2:30:30
Is there is there is there already plenty of cause for optimism?
2:30:34
Uh, living here, I don't I don't you know, when I when I talk to folks, I don't get this sort of sense that like they're super excited about the state of things, but maybe it's it's darkest before dawn.
2:30:46
>> Well, the last few years have been pretty rough, right?
2:30:48
there was kind of an unprecedented explosion particularly on the television side kind of starting around Netflix and House of Cards.
2:30:54
But really look the TV business was a cash machine for the for decades.
2:30:58
Streaming seemed like a really great business for for a lot of these people and then around 22 23 there has been this kind of correction or right sizing and from which the industry has never fully recovered.
2:31:13
Uh so yeah you're right that most people who work in Hollywood don't feel great about it.
2:31:16
I don't think that they believe that this deal is going to be the the solution for that, right?
2:31:22
They're looking at what will likely be thousands in and job cuts and the combination of two of the original kind of six Hollywood studios.
2:31:27
Uh but other people feel great because it means that they think that David Ellison will finally be the one to kind of create a scaled player to compete with Netflix and Amazon and and Disney.
2:31:38
Um look, Warner Brothers has traded hands a lot over the last decade.
2:31:44
It got bought by AT&T, then it got bought by Discovery, now it's getting bought by David Ellison.
2:31:49
Everyone has said that they're going to be the ones to figure out how to make HBO kind of a real competitor in streaming.
2:31:55
They haven't done it so far, but maybe David Ellison will have the magic touch.
2:31:59
>> How is Hollywood processing the It seems like uh TV's in a rough spot, but it it it feels like it's starting to be a good year for movies, at least financially.
2:32:09
I mean, we had the three breakout sort of like uh crossover YouTubers, Obsession, Iron Long, back rooms.
2:32:17
Then you have two billion dollar outcomes with uh the Odyssey and Spider-Man.
2:32:22
And then you're going into the back half of the year, it's tech focused, and you get uh the Theronos Elizabeth Holmes documentary. There's a OpenAI movie.
2:32:31
There's a another Facebook movie.
2:32:34
uh like at least from my world I feel like there's more stories around the movie business but uh how is Hollywood perceiving this year?
2:32:42
Will this be remembered as like a good year for the movie making business potentially?
2:32:49
>> I think it depends on who you ask.
2:32:49
Top line, it's the highest grossing year since before the pandemic since 2019.
2:32:58
You have the second most billion dollar movies ever.
2:33:00
You know, you had the Odyssey, you had the Spider-Man movie, you had Toy Story 5, you had a New Super Mario Brothers movie, and then a lot of the ones that you referenced, whether it was kind of the YouTube breakouts or even Deawar's product 2 was a big hit.
2:33:11
>> I think where people counter that is that if you look just in terms of ticket sales, ticket sales are still down a lot.
2:33:18
The reason that grosses are stronger is in part because going to the movies is just more expensive.
2:33:22
>> And so, >> we've entered a phase where movie going as a habit is just not what it used to be.
2:33:28
But yeah, I think this is if you talk to people in the movie business, they feel better about it this year than they have since before the pandemic closed theaters.
2:33:35
And the question that they all have is, is this going to continue?
2:33:39
How do we make sure that this isn't a blip and we actually are back on kind of a growth trajectory, which the business hasn't really been on.
2:33:46
>> Yeah, I've seen some uh some crazy stats about movie going before the dawn of television.
2:33:53
I think in like the 40s and 50s like the average American bought like something like 10 or 20 movie tickets a month like it was like the only thing to do and so everyone was going to movies constantly and then and then once people could watch >> got to get your screen time somehow.
2:34:08
[laughter] >> Think about think about when you Yes.
2:34:12
There there's what happened, you know, before television where it was like Yes.
2:34:15
It was pretty much it was that or reading books or playing playing cards, but even when when you were growing up, going to the movies on a Friday night was something that correct >> every weekend.
2:34:27
>> And that's just not the case now, right?
2:34:29
You go when there is an event.
2:34:29
A movie is competing >> Yep. >> with Tik Tok.
2:34:32
It's competing with YouTube.
2:34:34
It's competing with live sports.
2:34:35
It's competing with concerts.
2:34:37
It's competing with, you know, anything and everything.
2:34:38
And so it has to be loud and it has to feel like something one needs to leave the house to go see.
2:34:43
Um, and that's something that the movie business struggles with because they were in the habit of people just showing up on a Friday night and saying, "What do I want to see?" >> Mhm.
2:34:54
>> Uh, switching gears, YouTube and uh, Netflix.
2:34:57
You had uh an interesting post this morning on a creator that was uh potentially trying to rework rework their deal with Netflix seemingly because they're worried about losing >> uh something to do with their the Golden Goose, which is their YouTube channel, but break it down.
2:35:15
>> Yeah, there's been this fight for talent between YouTube and Netflix over the course of this year, right?
2:35:20
They're the two leaders in streaming video for most of their existence.
2:35:24
They were competitive but operating in different lanes, right?
2:35:28
You know, Netflix was Hollywood programming, professional film and TV, YouTube was UGC and um just shorter form videos.
2:35:35
Over time, they've gotten closer and closer together.
2:35:37
And what's happened this year is Netflix in trying to increase the amount of time people are spending and stay relevant with people under the age of 25, 30, in particular under 20, they have done deals with a lot of big YouTube talent.
2:35:52
And that's they, you know, they've done business with YouTube before.
2:35:54
It used to be, okay, Coco Melon, package together your videos and make highlights for Netflix.
2:36:00
Now, it's like with this with this person I mentioned, the chef Nick Dioani, and they've done it with with a bunch of people.
2:36:05
It's post your new videos to Netflix and YouTube at the same time.
2:36:10
We will pay you millions of dollars on top of what you already get from YouTube, and we're happy to talk about whether we should, you know, work on some kind of original programming.
2:36:20
YouTube got upset about this, right?
2:36:22
YouTube, even though they are the the the biggest player on the block, they seem to, you know, break records in terms of how much time people are spending it with it every quarter.
2:36:30
>> I think Netflix trying to get people to post syn at the same time on both places just irritated them. How dare you? How dare you?
2:36:39
No, it's so funny to me because they they've been through this like, oh, it's like everything.
2:36:42
It's like rainbows and butterflies like we're just [clears throat] YouTube.
2:36:47
It's about you, the creator.
2:36:49
>> We're all just creators and like we just we're here to just empower creators and it's like we're here to empower creators that maintain our monopoly on human attention, [laughter] you know?
2:36:59
It's like it it's really it's really kind of exposing just the realities of like business.
2:37:03
they're gonna make a bunch of like rational decisions to try to maintain their monopoly on like streaming UGC and and but uh but having to go kind of it feels like they just had to go very much like mask off.
2:37:16
If you do this we're going to kill your reach.
2:37:18
Um and >> we will punish you and by the way if you go back and work with us we will reward you. It is very Mchavelian.
2:37:25
They do they did not care. Yeah.
2:37:29
>> Um, it was interesting when I first started reporting on it how and what YouTube was doing in response like YouTube thought what they were doing to your point was very reasonable and rational and just what any business would do.
2:37:39
And then Netflix folks were like I can't believe what YouTube is doing.
2:37:42
And probably some of that comes from what you're talking about which is YouTube has cultivated this reputation as this very creator friendly platform which of course they're you know they're ultimately about the bottom line and creators are a means to an end for them. >> Yeah.
2:37:56
And the other thing that's interesting is like when when podcasters were like, "Hey, I could just I'm posting my podcast to the RSS feed.
2:38:01
I could just post it on YouTube at the same time.
2:38:04
Maybe I get some additional views."
2:38:06
Creators are now just trying to do that.
2:38:08
They're like, "I'm creating this video asset that I >> slaved away making for any number of hours. I made this thing. It's my IP. I own it.
2:38:18
I should be able to post it anywhere."
2:38:19
And now YouTube is saying like, "We're going to cut your reach, you know, by however much."
2:38:22
It just feels like it is deeply misaligned with the creator, which is the person that built >> YouTube.
2:38:31
And it's my hope that >> it's my hope that that the creators like win here because it's so much better.
2:38:38
It'll be so much better if a creator can be like, "Yeah, I get I get views all over the place."
2:38:41
And and uh but but I don't know.
2:38:44
YouTube >> will be better for YouTube shareholders, though.
2:38:49
They may be misaligned, but it I would actually say that this competition for creators, at least in the short term, is a net positive because there are multiple people.
2:38:57
It's not YouTube for the longest time was kind of the only game in town, right?
2:39:01
Yes, you had Tik Tok and Instagram and Twitch.
2:39:04
>> Well, that's what I'm saying.
2:39:04
I'm saying that competition is like amazing. I want more.
2:39:07
I want permanent competition not that might be the state because because right now if YouTube is that stick then Netflix has to increase the amount of carrots to say hey yeah you are going to get crushed but we're going to double what we were going to pay you.
2:39:20
So and then all of a sudden somebody says you know what yeah I'll get rid of my YouTube channel at that price I'm down right and then that's good potentially.
2:39:29
>> Yeah and you see Disney and Fox and other legacy entertainment companies trying to get in too.
2:39:33
And so if there are just more people trying to compete for creators dollar, that's good, right? We've seen it.
2:39:39
You brought up, you were you were talking about podcasting earlier.
2:39:42
When there were a bunch of companies trying to get podcast deals and trying to sign podcast talent, that's when you started to see people like Joe Rogan and Alex Cooper and all those folks getting huge paydays.
2:39:51
So yeah, the more folks who want their, you know, want their videos.
2:39:56
Do you think that um do you think that Netflix could think about trying to cultivate like emerging talent?
2:40:04
Like they're so used to being like, "Hey, let's put a million dollars towards this like single production."
2:40:10
If you take a million dollars, you divide it by 20, you could seed 20 creators that are just showing like any, you know, I I'm very excited for a lot of the content that I like most on YouTube is is like highly produced 20, 30 minute videos from a super passionate creator that just spent and it's like real time, right?
2:40:30
And so what what Netflix has been missing is just like and they've kind of done this with some documentary projects where they'll like come out with a documentary on like Trump's flight from Turkey, >> right?
2:40:42
They're doing these quick turn documentaries right now.
2:40:44
documentaries right now. And so but but they should be doing that across like every single every single category basically like >> they could I think Netflix is really wary of >> they would sort of categorize that maybe as user generated programming and I don't think they feel like they can win
2:41:01
at that but it like Netflix's strength has been yes that that really high production value type of programming and YouTube strength has more been the longtail being the place that you can go for anything and And I think if you most people at Netflix feel like they they can't beat YouTube at at that game. But it would be
2:41:19
But it would be interesting certainly to see them, you know, go to 20 30 creators they like and say, "Here's $50,000 to make whatever you want." >> Yeah.
2:41:30
Well, I would just like to see that because those creators, if they're at if they're just starting their journey, have nothing to lose.
2:41:34
Like they don't have this like amazing, you know, platform and business built on YouTube yet.
2:41:40
So, it would take a lot of money, but um some way or another, they're going to need to get to the point they're going to need to benefit from like having creative talent that's distributed all over the world that can make this more like real time content.
2:41:54
And and I've always I've always felt like Netflix in the slop era that we're in, Netflix has amazing opportunity to just curate UGC better than YouTube because I I actually can't stand when YouTube surfaces some video to me.
2:42:10
>> And historically, I would have been like, "Oh, cool. There's a video.
2:42:11
It looks like it's well produced. It only has 4,000 views.
2:42:14
Maybe it's like someone great."
2:42:17
And then now more than ever it's like some like AI script from a and and and there's actually no substance to the content turning it out.
2:42:26
>> If if Netflix can create a slop shield of sorts >> curation layer I'd be optimistic. >> I like that.
2:42:33
What's the status or the status of uh Apple in this ecosystem?
2:42:37
Uh I talked to I talked to a filmmaker before they really launched uh you know real Apple TV plus productions and he was saying like it's going to be challenging for them because uh movies are it's a hits driven business.
2:42:55
You're going to have flops and that's sort of antithetical to the Apple culture of like everything needs to be polished and perfect.
2:43:04
And then I think they've done well and they've developed a portfolio of really well-reviewed and Emmy winning, Golden Globe winning, you know, they've won a whole bunch of awards.
2:43:13
But how do people in Hollywood see them?
2:43:16
Are they an important buyer in the ecosystem?
2:43:19
Are they just one of many?
2:43:19
It feels like they're sort of sitting out this YouTube versus Netflix battle, but uh is there a battle coming, you know, years down the line as they try and expand, or are they sort of happy with where they are?
2:43:32
>> They're definitely sitting out the the Netflix YouTube skirmish.
2:43:34
I mean, when they first showed up, I think they were seen as, you know, Captain Moneybags.
2:43:39
They just they would outspend anyone and everyone.
2:43:41
They're kind of seen as star because every show that they do, they want to have bigname talent in.
2:43:47
>> But over time, they've developed a reputation as one of the kind of one of the best program or one of the best streaming services in terms of programming. Right.
2:43:56
You you mentioned Emmy Awards.
2:43:58
They just won the most Emmys of of any streaming service of any company. >> Was that Widow's Bay?
2:44:02
It was Widows Bay was their biggest winner, but they, you know, they got a lot of nominations across that and Your Friends and Neighbors and Shrinking and a bunch of their shows.
2:44:11
Um, they get really good critical praise.
2:44:17
>> Yeah, it feels like they've sort of jumped straight into more of an HBO competitor than a Netflix.
2:44:22
>> They have Well, that's but remember that's where Netflix started, right?
2:44:25
Netflix started as competing with HBO and then went mainstream. >> I don't know.
2:44:29
Amazon started as competing with HBO and then decided to speak to the middle of the country with Reacher and other stuff like that.
2:44:35
I don't know that I see Apple making that same transition to your point about sort of what Apple is.
2:44:40
It doesn't feel like in keeping with their brand to try to be CBS. >> Yeah.
2:44:46
>> Um the the the knock that most people have on Apple is just their shows aren't very popular or you know they they do really well with a particular type of viewer. Yeah.
2:44:55
Um, but only a couple other shows have broken through in the culture in a big way.
2:45:00
But I >> know I saw estimated ratings and it was like 70,000 views an episode or something, which is like a small podcast, right?
2:45:08
It's not >> they they may not care, right?
2:45:10
That if you're John Turnis and you're like, "Oh, I just went to the Emmys and we won all these awards and talent wants to work with us.
2:45:17
That's good for our brand."
2:45:19
Well, that's been the the 4D chess argument in tech is that it gives them something to talk about that's not just app store rents because they're like, "Oh, yeah, our services business.
2:45:26
You want to talk about services?
2:45:27
Let's talk about, you know, Widow's Bay, not we made another 10 billion charging 30%."
2:45:35
>> You think any of the major platforms will take are taking a hard look at at short form dramas or any of these these apps that are charting.
2:45:45
apps that are charting. I think a lot of them are basically like adult content that's sort of like >> romantic porn some people would say >> but there's also like horror and and like true crime stuff in there >> they're all looking at it I think Peacock I think has already added some
2:46:01
verticals I know that Netflix and others have said that they're looking at it that again doesn't feel like one for Apple per se but most of the other ones um look all these services cuz streaming isn't growing as fast as it once was they're all looking at ways to bring in more people So they're all looking at YouTube creators. They're all looking at
2:46:16
They're all looking at podcasts.
2:46:18
They're all looking at vertical dramas.
2:46:19
Anything that people are paying attention to.
2:46:21
If they can find a sensible way to integrate it, they will. >> Makes sense.
2:46:26
>> Is it fair to say that uh the Warner Brothers story was somewhat predictable just by the actions of David Zazov, even before the first bid came out?
2:46:34
Was this was something that you and other folks in the industry were tracking? Correct.
2:46:42
Um there was a feeling that what was happening that Warner Brothers Discovery wasn't working as a public company right the stock was low the stock was doing badly >> the company was shrinking just in terms of revenue um the streaming service was doing okay and so we >> we knew they had to do something.
2:47:02
What they were doing was they were splitting it right?
2:47:04
They were going to cast off the cable networks into one business because that's the part that generates a lot of profit but isn't growing.
2:47:09
And then they were going to put the the studio and the streaming service into another.
2:47:14
And my belief is that is what David Zaz wanted because he liked being >> the mayor of Hollywood.
2:47:18
He wasn't the mayor, but he liked being a big shot in Hollywood, right? He's in Bob Evans house.
2:47:22
He gets to hang out with movie stars and get dinner with those people.
2:47:25
He didn't want to give that up. >> Sure.
2:47:26
>> And that's why when David Ellison first came calling or one of the reasons that David Z and his board said, "You're not valuing us high enough. We don't want this. we don't want it.
2:47:34
And Allison just kept coming.
2:47:36
You know, you got to give him credit >> in the case of both buying Paramount from from Sher Redstone and in this Warner Brothers deal, >> he faced a lot of resistance and he, you know, in part because he has the resources from his family, but he just kept coming.
2:47:52
>> Do you have negotiating against himself?
2:47:55
[laughter] Do you have any predictions for uh what what the next big Hollywood story might be either through the end of the year or next year?
2:48:04
Something that people are feeling like, okay, we're in act one or act two there.
2:48:09
There might be a crescendo, some big deal, some change, some structural uh moment could be sort of across any any storyline.
2:48:15
But what what are you tracking?
2:48:19
>> Well, look, in the immediate, there's going to be a lot of attention paid to what does David Ellison do?
2:48:22
combining two companies is going to mean not only firing a lot of people, but who's going to run the streaming business?
2:48:28
He's got a high-profile person in charge of streaming at Paramount and a high-profile person in charge of streaming at at Warner Brothers Discovery.
2:48:36
>> Um, setting that aside, um, a lot of people are wondering what is going on at Netflix.
2:48:42
I think, you know, they've had a pretty rocky year ever since they walked away from Warner Brothers Discovery.
2:48:47
Um it's led to a lot of questions about the future and um you know whether they have a plan for their next act and how they're going to grow.
2:48:56
There's been a lot of rumors about changes in leadership there and so I think people are keeping an eye on that.
2:49:02
>> Um Comcast is doing what Warner Brothers Discovery once was planning to do.
2:49:04
you know, they're splitting their cable business from the entertainment business.
2:49:08
And a lot of people are wondering, is that the first move in, you know, NBC Universal ends up getting combined with something?
2:49:15
>> Uh, you know, AI is a much bigger conversation, I'd say, in the music business than in Hollywood right now, but it's lurking obviously, as it is in all sectors of society.
2:49:24
Um, >> those are probably the big ones. No sense.
2:49:30
>> Oh, and and the federal film tax credit.
2:49:32
A lot of people are wondering, there's a there's a push to um try to pass a a tax credit for shooting in in the United States, which would bring a lot of production back from Europe and Canada.
2:49:45
And um Trump came out for it, and people are trying to get that done basically between now and when the next Congress seats in January.
2:49:52
>> I I think Avengers is going to London or the UK.
2:49:54
Uh, and I don't know if that's because that's where they actually want to shoot or it's a financial decision, but uh, be exciting to get back to making movies in Hollywood. It's a good town.
2:50:06
>> Hopefully, we get booted out of our studio.
2:50:08
That'll be that'll be a bullish indicator [laughter] for for Hollywood.
2:50:12
>> It was way too easy to find studio space in Hollywood for us. >> Yeah. >> Way too.
2:50:16
>> Well, thank you so much for joining, Lucas.
2:50:18
Really really enjoyed it.
2:50:18
Let's do it again when you have more stories.
2:50:21
>> We'll talk to you soon. >> Thanks, guys. Cheers. Bye. >> Bye.
2:50:24
Oh, well, >> and that's our show, folks.
2:50:27
>> Thank you so much for tuning in to TVPN.
2:50:29
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