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>> Today is Thursday, September 17th, [applause] 2026.
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We're live from the TV Ultradon, the temple of technology, >> the fortress of finance, >> the capital of capital.
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Let me tell you about ramp. com. Time is money. Save both.
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Easy use corporate cards, bill pay, accounting, and a whole lot more all in one place. >> Dang, son. Where'd you raise this?
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[laughter] That >> a wild one.
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>> That is a wild I I don't think we played that one. We haven't. Yeah, that's a new one.
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>> I don't know if that's actually a keeper.
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It's kind of a little weird.
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Yeah, I think the start of it is funny. Dang, son.
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We have Joe Weisenthal coming to Teen Pin Ultra. First time in person.
0:36
We've done OddLots in person with him, but he's coming on down.
0:38
Uh we're doing a Bane Capital deep dive today.
0:40
Uh talking to partners on the venture side, then David Gross, who's the managing partner, talking about the history of the firm.
0:49
[clears throat] He was doing special situations in Japan, went to Japan very early on his career, grew the Asia business, and now is overseeing Bane Capital, become this uh really large asset management firm with a bunch of different strategies.
1:03
So, I think we'll have an interesting economic perspective outlook.
1:04
The theme of the uh Bane Capital Ventures announcement is uh the post AGI economy.
1:12
>> Finally, >> we still got a job for asset managers.
1:14
That's what you're thinking.
1:14
you know, everyone was saying, you know, >> but also I'm glad to get kind of past this current moment.
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A lot of tension and I'm ready for the next chapter.
1:22
>> It is uh but it'll be interesting to hear how they're actually thinking about investing, wrestling with what's going on at the foundation model layer, but then still investing both above and below the fold as I'd like to put it.
1:35
So, Lorra is coming on doing legal AI, basically a rapper company.
1:38
They're optimistic about that.
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But then they're also investing in Crusoe.
1:42
We have Jayce Lock Miller coming back on the show uh to talk about building infrastructure for the AI buildout.
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And so they're they're they have this sort of sandwich strategy which is pretty interesting.
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And then we dec Jordy and I are all back for another.
1:58
[laughter] >> Thank you for being with us.
2:01
>> Yeah, you know, Theo Theo has been playing along with that meme a lot.
2:03
And I think uh I mean it it was it was the current thing for a minute there.
2:08
Um, but uh he put out a tier list of all the different controversies surrounding him and he put this he put the the and I as S tier.
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It's like the it's the best controversy he's ever been a part of.
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Uh it's it's such [laughter] a funny thing and I hope it lives on as a meme.
2:23
I hope people continue to do it.
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Uh because it when applied correctly, it's uh it's a chef's kiss.
2:31
Uh anyway, uh Snap officially launched Specs yesterday.
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Uh, some of the team members here got to go check it out in person. I get there.
2:43
I'm like, "This is perfect. It's 3 p. m.
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Atlas Creatine Cycles in town.
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I want to meet up with him." I'm like, "Great.
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You're going to this thing.
2:51
I have an invite to this thing. I'll see you there. We'll catch up there."
2:54
Super convenient for both of us.
2:56
I got a 30-minute call beforehand.
2:56
It ends right before the thing starts. That runs to 50 minutes. So, I'm 20 minutes late.
3:02
Get my badge, walk in immediately, get a phone call.
3:05
Hey, they call me about to be I had another call. You got to hop on early.
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So, I leave and then I have another 90-minute call.
3:11
So, I truly missed the entire thing, but I did get to go inside, have one glass of water, talk to one person, Harper Carroll, former guest of the show, now out in Austin reporting on AI.
3:21
Um, and uh that was electric.
3:25
But then I didn't actually get to see the presentation or do the demos.
3:28
So, [laughter] uh it was basically a quick turnaround for me.
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And I was like, why why did I think I could pull this off? Uh, I failed.
3:36
But, uh, did the launch fail? We'll see.
3:39
We'll talk to the folks who actually went.
3:40
Tyler, Nick, we're not asking for a full review.
3:43
I just want take us through the day.
3:45
I saw you guys pull up and you guys didn't see me.
3:47
I was on the street on the call.
3:50
You guys get waved around. You valet.
3:52
Walk me through your journey into the uh the launch. Like, what?
3:56
You go in, you have cocktails. What What happened? >> Uh, yeah. Have a have a drink. Okay. Go in.
4:03
Uh, >> what are they serving?
4:04
Screaming eagle or, you know, selzer water?
4:10
>> Uh, some kind of cocktail.
4:11
>> Did they have the original for loca?
4:13
>> Did Were they serving the original for loca? >> I wish. Yeah. >> Yeah.
4:17
>> Multiple plants of Guinness.
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>> Do they have natural light?
4:20
>> I could totally see Evan cracking out the cracking open the secret supply of original four locos.
4:24
You know that guy has >> you know he has a bunky with the original four locos. Yeah.
4:28
So So everyone's having some drinks. Then you sit down. Chopping it up.
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Then you go into the the amphitheater >> and it's sort of like Steve Jobs iPhone launch vibes, right? >> Yeah.
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You know, he's he's standing in front of this big screen.
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There's like beautiful images behind him.
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Walks out, black shirt, jeans. >> Okay. >> Um Yeah.
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Then he starts he starts doing live demos.
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>> He did lean into the memes, right?
4:47
I saw on screen a picture that had clearly been photoshopped or AI to make the specs look even bigger.
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So he was aware that people thought they were chunky, that they were large. >> Yeah.
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>> Uh so so he gives his demo. What's his pitch? Yeah.
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So, there's like a number of of ways to he kind of talked about it.
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One is like he basically like positioned against like being on your phone a lot.
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You want to stay very present, right?
5:12
You don't want to be looking down at the screens all the time.
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You want to be >> you want through the screen. >> Yes. >> Right. Yes. >> Yeah. >> Okay. >> Close to your face. >> Yeah.
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>> And I've heard that pitched a few times. Do you believe that?
5:22
Do you think that if you go no phone but constant visual overlay in your visual field, you will actually be like, "Yeah, I'm more in touch with reality." It worked. >> Yeah.
5:36
I've never I've never understood that part of the pitch.
5:38
It's actually We know you're addicted to your phone, so here's another product that will actually always be attached to your face where they were going to spin as helping you >> kind of Yeah. reconnect with reality.
5:51
>> It's an odd It's an odd pitch.
5:51
It really doesn't work on me because I I like the barbell strategy of like brain rot and and stimulation where I am actually fine to be like give me the fully virtual world. I want to be locked in.
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I want the screen as big as possible.
6:06
I want to be in World War II.
6:08
I want to be in Modern Warfare for hours playing, running around, shooting.
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I want it to be all the audio.
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I don't want to hear anything else.
6:19
I want noise cancellation.
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I want to be in that world and then I want to be able to unplug and then just go into the actual world and sit down and have a chat with you and have a coffee and not be checking our phones and actually be fully present when I'm fully present in the real world and then I want to be fully in the virtual world.
6:35
So like I want the VR the the the fully like you know immersive thing and then zero immersion and I'm actually not looking for more things that are in the middle and I'm wondering if people will if that will resonate with people.
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I I think that's mostly because you haven't seen like very good examples.
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Um and like right now the the glasses are still like kind of big and bulky.
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If they were very minimal and like kind of you know they would show very small the boys were people online were thinking that the guy in the center was Clab. >> Yeah. >> It's actually Tyler.
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>> It's actually Tyler and Nick and Atlas.
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Um >> so is he wearing untinted versions and you guys are wearing tinted versions? >> Yes.
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>> Or are they or is or can you say like I want tinting on right now?
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So I I think you can like increase the tinting, but there's also just >> there's two SKs. >> I Yeah, I believe so. >> Okay. Okay. Yeah.
7:22
>> So you got to get both, I guess.
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>> Uh anyway, when did you actually get to the >> Dan Dan says John raising a second family in VR [laughter] trying to keep them separated. >> Yes.
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The the COD lobby is my second family for sure.
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[laughter] Um so so he gives a pitch. >> Yeah.
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does mention of live demos >> and and are the demos consumer focused enterprise focused proumer? >> Yeah.
7:49
So the the live demos he did were all very consumer >> consumer.
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>> Um he showed uh like live shopping and you could [clears throat] like he was going to look for a espresso machine then he pulls it and like puts it on a table in front of them like see how big it is and stuff like that.
8:03
>> Um >> any live demo failures? Any Wi-Fi issues?
8:05
There there was kind of one where he tried to pull up a YouTube video. Okay.
8:08
And then so he said like uh hey specs.
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>> So he's talking to a voice assistant like controls >> it.
8:14
Pull up a video about um about specs and then it opens the the like browser view goes to YouTube >> and then he like tries to click on a video to open it and it like doesn't really work. >> Oh okay.
8:25
>> Um but it it eventually worked.
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>> It seemed like it worked.
8:28
>> It was like a small hiccup.
8:28
It wasn't like a big >> Yeah. Yeah. Yeah. It wasn't a demo fail. Uh yeah, makes sense. Okay.
8:32
So, >> and there was a very cool live demo of someone there was like kind of an interactive music >> uh creator tool where you could like move around and it would play different sounds and so she did this very cool live demo.
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>> So, she was creating a song but instead of using traditional instruments like the instruments were puppeteered by her movements in the physical world. Got it. Okay, >> cool.
8:54
Um, >> so was there any enterprise pitch?
8:58
>> Uh, there was there were no live demos of that but there were some videos played.
9:02
Um, like one was it's like imagine you're an electrician and you're basically looking at this big like server box and you don't know where to, you know, plug in the wire and it would like highlight which plug you put it into. >> Yeah.
9:13
>> Um, which I think is like could be interesting.
9:15
>> Yeah, that feels like something that sounds good, but I have no actual real experience there to like say like, yeah, that's what the that that's what will solve the bottleneck in electricians. >> Yeah.
9:26
But like, you know, interactive instructions, that's kind of a cool idea, right?
9:29
you're building IKEA furniture or something and it like tells you what to do. >> Yeah. Yeah. >> Something like that.
9:35
>> Yeah, I can see that being >> Yeah.
9:36
But then keynote ends and then we go outside and there's like a bunch of places to do live demos.
9:42
>> Um so yeah, the first one we did is >> uh well you basically put on the glasses and you do some kind of like uh calibration thing.
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You like figure out how the the motion works.
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Um there's no like little uh kind of secondary like I I think on the the MetaQuest displays there's like that little wristband.
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There's nothing like that. >> Nothing like that. It just handtracking. >> Yeah.
10:02
It's just kind of it's similar to like the Apple Vision Pro kind of interactions.
10:06
>> Um >> and then yeah, the one I really liked was it was like ping pong.
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>> So you're like your hand is the paddle and you're playing ping pong.
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I think there's actually a video of it play. >> Yeah. Yeah. The other play it.
10:16
Um, >> so the the ping pong thing, do a little tier list for me of of ways to do ping pong.
10:24
We'll start with the real ping pong. Where's that?
10:28
F tier, >> D tier, C tier, B tier, A tier.
10:35
>> Obviously, I think it's S tier. >> S tier. Okay.
10:38
>> Well, what am I comparing it to? >> Uh, full VR. Full VR ping pong.
10:39
Would you rather play pingpong in VR or real life?
10:46
[snorts] >> Well, so like obviously you would rather play in real life, but like would you actually play in real life?
10:51
So if my friend lives 100 miles away, I'm not going to be able to play ping pong, but I can play in VR, right?
10:55
So that I think that, >> you know, boosts it, right? >> So it's also S tier.
10:58
[laughter] >> What about >> I think it's like B >> because in the augmented reality ping pong table. >> No. >> No. Okay.
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So it creates Yeah, we can see but I'm just waving my hand. >> Yeah. Yeah. Yeah. >> Yeah. there.
11:13
>> This is >> um >> future right here. >> Yeah.
11:16
And then this was I I can talk about why, but this is probably more like C tier.
11:19
It's definitely worse than VR.
11:21
I think one of one of the reasons is because there's no actual controller.
11:23
So the >> Oh, you don't have the weight or anything.
11:27
>> It's a little bit >> Oh, that's interesting.
11:28
It's actually worse even though you don't have a controller.
11:30
Normally, it's like get rid of the controller.
11:32
That's just extra weight, batteries, equipment.
11:34
>> I think for gaming, the controller actually works because you get really precise.
11:37
But typically these these systems allow like thirdparty peripherals.
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So you can like whip up a uh you know uh you can like wire up an Xbox controller like what Oculus did where they just or MetaQuest where they just use the Xbox controller for those types of games.
11:51
>> Yeah, I I do think like this was my the coolest demo I did and this is something that like >> there's I mean really like no reason why this needs to be in AR.
11:58
This could just be completely VR because >> um like I'm I'm looking at the the ball.
12:04
I'm not looking at like people in front of me.
12:05
And it was actually kind of distracting because someone would walk in front of me and I think I'm about to hit them. >> Oh, sure. Sure.
12:10
>> Because I can like see them.
12:12
>> Maybe better to just olude the the world. >> Yeah.
12:14
>> Or do some pass through stuff. Yeah.
12:14
>> Or do some pass through stuff. Yeah. I'm still I'm still uh oddly bearish on augmented reality and more bullish on virtual reality where you're not recycling photons where instead you just uh have cameras on the outside that then repro that on the inside of the headsets so that you can get a wider field of
12:36
view and then if you're in a bright scene you can still overlay things you can darken things but in augmented reality I don't believe it's physically possible if to look at a bright light to put a dark, you know, object in front of it because you're the the only thing that this that these uh glasses can do is add light to the scene. And so you
12:54
And so you have to have a dark background to add light on top of it for the hologram to exist.
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>> I mean, I I found it was like bright enough I could clearly see everything.
13:04
>> That is pretty impressive. Yeah, it was outside. It was it was outside. It was a bright day. It's in LA.
13:08
I mean, sure, there was like you were standing in shade, but you could still see the holograms, which I think is interesting. >> Yeah.
13:14
I I didn't try watching any like movies or anything. >> Yeah.
13:17
>> Um which I think would definitely be better in VR if >> you should have been like you're gonna let me demo this. Can I just do one?
13:20
Can I just do one demo real quick? Snap. >> Lawrence of Arabia. >> Lawrence of Arabia.
13:25
[laughter] >> I I'd like to watch David Lean from start to finish to really understand if this is the product for me.
13:33
>> See you in three hours.
13:34
>> To me, it's so interesting how high the bar is in this category.
13:36
bar is in this category. Like when technology industry was making the first like mobile phones like the bar was like can it make a call can you receive a call can you do that semi-reliably yeah even if there's services spotty
13:52
>> because you were competing against the pay phone you [laughter] had now it's like every new device competes with the smartphone >> and I just think like the meta rayband displays I haven't seen any of them out in the real world uh it seems like those are not doing well. I think that I think
14:07
I think that I think this whole category is still going to be quite challenged. >> Yeah.
14:14
Even just the basic meta ray bands, they compete with the smartphone, but they also compete with AirPods and like the Apple ecosystem is like remarkably robust in terms of like uh the Meta Ray-B bands uh users that I know that like the product are like, well, I like them, but I often just like take phone calls on them.
14:32
I listen to music on them when I'm going for a walk and then occasionally I'll take a picture and it's like that's saving you 5 seconds to get a worse quality photo than if you have a nice phone and your headphones.
14:44
I guess it's a little bit less intrusive to have the the the speakers up here as opposed to like in your ears.
14:50
It looks a little bit normal if you walk up to someone, you pause your you pause your music, you walk in, you order a coffee, people are like, "Oh, he didn't even take out his headphones while he's talking to me."
14:58
kind of antisocial as opposed to like, oh, he still has his glasses on, but they're not playing audio, so I don't have a weird uh reaction to it.
15:03
So, there there's a little bit of benefit, but yes, it's very very incremental.
15:06
Uh it's not it's very rare that these things like unlock entirely new uh capabilities.
15:12
Is there any uh is there any content ecosystem that you think that they can plug into?
15:17
Like the the the killer the killer app on Apple Vision Pro in my experience has been the Apple TV app.
15:24
like it's like they already have a library of every movie and 3D movies and IMAX movies and so there are great movies that you can watch in that thing and and uh and with the like it's like what was the last Oculus or MetaQuest um uh you know partnership it was like the Xbox edition. Why is that important?
15:44
It's because like they want you to fire it up and install Xbox and be streaming Xbox games.
15:52
So, you get the Xbox library on that device on day one.
15:54
And and and the fact that you it's a meta product.
15:57
Yes, you could scroll Instagram reels in there, but that's clearly not the killer library that they need to bring to bear.
16:04
They need to bring games.
16:04
So, they've partnered with Xbox for 2D games, not VR games even, but it's like at least you could go and play a lot of, you know, Bioshock or whatever is on there.
16:14
Uh, and and is there is there any glimmer of like where the big content pool might come from once you've played enough ping pong?
16:24
>> Yeah, I I really don't know because yeah, like movies and games are just I think always going to be better on VR. >> Yep.
16:30
>> Um, and then like there's not like an existing library of like AR, >> you know. >> Yeah. Experiences. >> Yeah.
16:37
Because like >> the only thing I can think of is like actual Snapchat lenses, right? That's like AR library. Yes.
16:41
But like, you know, what are you going to do with that?
16:44
So I think like um >> laugh when everyone you meet looks like a hot dog or something or like a cat has dog ears. >> Dog ears. Yeah.
16:50
The dog filter on everyone IRL. [laughter] That's wild.
16:54
Uh let me tell you about CrowdStrike.
16:56
Your [clears throat] business is AI.
16:57
Their [applause] business is securing it.
16:58
Crowd Strike secures AI and stops breaches.
17:00
Uh so next week we might get a competitor to this.
17:06
this. uh next week is uh Meta Connect I believe and uh they're on a track like reality labs obviously all the energy is around AI but the team is still working on devices augmenting reality they did the meta rayband displays which is the call of duty style uh you know mini map uh it doesn't take over the full uh the
17:29
full cone of vision but two years ago Mark Zuckerberg demoed a product at Metacon two years years ago, 2024, of the what he called the Ryan, which was uh very very complicated name if you know the history of the hunter Orion who tried to kill all the animals and was, you know, sacrificed for it as a tale of hubris. But uh anyway, hopefully this
17:48
But uh anyway, hopefully this doesn't go like the Orion story.
17:51
Um because every every tech >> every time every time Meta names something, it it has like this like accidental >> I mean it happened to open AI too.
18:01
>> I mean it happened to open AI too. the big GPT the the big pre-train that was supposed to be like GPT5 was called Orion at one point I think and so like never name your product after a hubristic Greek tale uh anyway uh the Meta Rayban displays launch a lot next
18:17
year and it felt like this year is the year that you get the Meta Rayban full displays and so that Orion product should be here it should be a direct competitor to specs and it would time up and it would actually make sense that you know the Snap team sees that okay they're going to release this on this day we got to get out early. We got to
18:32
We got to be a week before.
18:34
And so I would expect that next week we get a direct competitor to specs, meaning uh meta rayband form factor, probably a little bit thinner, a little bit smaller, a little bit lighter.
18:46
Meta has more resources for this.
18:47
They've been working on longer and it should be augmented reality that can take over the, you know, a fairly wide field of view.
18:53
I imagine that that's going to be a big uh comparison table, not just price.
18:57
It'll probably be expensive.
19:00
I mean the meta raybands couple hundred bucks meta rayband displays 800 bucks something like that and I would expect that the full display is maybe >> 500k [laughter] >> probably 1 1500 bucks or something but still cheaper than what spec is which is 2200 something like that.
19:14
Um but uh the real question is is will they launch the Quest 4?
19:21
Yeah, I I thought it was Quest 5 because they have truly stopped shipping VR headsets.
19:27
Can you give us the history of uh of the launches of the MetaQuest VR headsets?
19:33
Because the Quest one launched in 2020. >> 2019. >> 2019. Okay. >> Question.
19:39
To >> be clear, if you were wearing smart glasses, you could stop >> the conversation and just ask the question, wait for response >> and just read it off and then read it back to us or you could just >> ask >> do what you're doing. Yeah. >> Yeah. >> Yeah. Okay. So, uh, Quest 2 is 2020.
19:56
Quest Pro is 2022, Quest 3 is 2023, Quest 3S is 2024. That's the most recent.
20:03
>> And then and then the Xbox edition was like a light turn.
20:05
That's what we did on the show last year.
20:06
But uh but no truly new hardware in 2025 or 2026.
20:10
And now it's expected 2027.
20:14
It would be such a wild card if all of a sudden Mark Zuckerberg was like, "I did it. Great VR. I've solved it. You counted me out.
20:23
And here's the gift of the Apple Vision Pro. >> Yeah.
20:26
Truly, no one cares about VR.
20:29
[laughter] Uh and and it and it makes me think that that the the truly incredible like eventually we'll get the breakthrough >> like smart glasses.
20:39
Eventually, we'll get the breakthrough VR product.
20:43
>> But I have a feeling that the adoption curve is going to just be slow because the entire world is like, I just don't care anymore.
20:48
Just I don't I truly show me whatever demo you want. I do not care. I'm not going to try it. I'm not going to buy it. It doesn't matter to me.
20:56
It doesn't matter to my life.
20:58
>> And it's interesting because it's so different than language models which like GPTs GPT, you know, generative text models have existed.
21:06
And G the GPT3 API came out in 2020 and uh and you could, you know, actually go and try and interact with it, but it didn't have like a national marketing campaign around it. Yeah.
21:17
It it it truly was like in the line.
21:19
>> Smart glasses are like the most push marketing dollars >> for years. So long. Yeah. For years.
21:24
And so uh there's been so many like little popup VR experiences, integrations at theme parks.
21:32
Like it's been said, oh, it's the next big thing.
21:34
It's been on the cover of Time magazine.
21:35
like there's been a lot of attention before getting to product market fit whereas LLMs were like truly the like in the research lab for like a decade and then once it was actually good enough it just came out and immediately went viral and everyone was on chat.
21:48
com >> and then it was just like boom it's it's now it's like a thing and then it was off to the races. Uh, interesting. But I don't know. I do. >> Yeah.
21:58
It feels like every with every demo, it feels like we're >> once each of these devices is 10 times better. Yeah.
22:06
>> There might be a market. >> Yeah.
22:08
>> But I actually am not even confident that that the end market is really going to be quite as like exciting as everybody as as the excitement that you've had from Zach and Evan and all these people. Yeah.
22:27
>> And I think there's I think there's potentially other routes to get to that sort of like ambient computing, you know, just sort of this always >> available personal assistant that that aren't on your face, but we'll see.
22:40
>> Uh I mean, Valve is working on new VR headsets still.
22:43
They had a Quest, an Oculus competitor called the Index, which was very highly performant.
22:48
Uh we should pull up some some images of the new uh Steam Frame.
22:53
So Valve, the very secretive private company controlled by Gabe Newell, uh is is launching a Steam machine, which is a desktop box, uh a Steam controller, and then also a Steam Frame, which is a VR headset.
23:07
It can do some stuff directly on the headset, but it uh it mostly it it performs best when it's uh when all the rendering is happening on a gaming PC.
23:18
So, it's designed to be used in concert with a gaming PC.
23:24
So, it's still they are leaning into like this is a gaming peripheral.
23:28
This is for somebody that has a gaming PC.
23:30
They're in the Steam ecosystem and we want to give them a great experience.
23:33
So all the rendering happens on the uh uh on the computer and then it just it just streams to your happy.
23:41
That is a very funny promotional photo. Go to the next one.
23:44
>> Look how happy [laughter] he looks >> with the goatee is really like this is a gamer.
23:48
The gamer goatee is great.
23:51
>> Have you ever rocked a goatee? >> Never. Not once.
23:52
Uh, tomorrow we I we there was a handlear mustache uh phase amongst the crew in when we were in early 20s, but I I don't know if I fully participated. >> Yeah.
24:04
>> Which one's that's the index, right? That's an older one.
24:08
>> I think we need to send VR to Dagistan. Yeah.
24:12
>> A few years and forget.
24:13
>> Um, [laughter] >> you just want you just want to get it out of here.
24:17
Um, >> send to Dagistan for a few years and forget.
24:21
The really interesting thing is that uh Palmer Lucky revealed that uh Apple had done all this work to pull forward the display technology so that the Apple Vision Pro had really high resolution and it still has the highest resolution like the best screen of any VR headset really.
24:34
Uh the Steam Frame 2 years later is still using the same uh the same pixel density as the uh MetaQuest 3S or something like that.
24:44
So, like even though we've had 2 years of progress on on, you know, everything, the actual display fidelity hasn't gotten there.
24:53
Leads me to believe that these people just don't think it matters because Apple solved that and it still wasn't enough.
24:58
But I still feel like if you get it ultra, ultra lightweight, really good integration with key uh media partners like Xbox and and Apple TV movies, and you have a great display that's super light because people just didn't like the heaviness and the expense of the Apple Vision Pro, there's something there.
25:15
But no one really no I'm the only one that thinks that.
25:17
Uh let me tell you about Figma agents meet the [applause] canvas.
25:22
Your AI agents can now create and modify your Figma files with design system context.
25:25
Tyler, did you see Shaquille O'Neal at the specs launch? >> I did not. >> Why?
25:32
>> Jimmy Butler was there. He's pretty big.
25:34
>> Why didn't they hire Shaquille O'Neal to promote the specs?
25:36
Because if you have a big product, if you put it on a really really big guy, it's going to look relatively smaller, right?
25:41
You don't want your your your models in the footage or your partners.
25:47
>> Well, they could have done a collab with LeBron.
25:48
LeBron's the new face of Poly Market.
25:51
Could have LeBron in like the sort of like Iron Man style video where he's placing thousands of bets at the same time. >> Here you go. Yeah. >> Betting on himself. >> Lupin Nike always.
26:01
It's the Nike Specs Poly Market collab. Bet on bet on yourself. On bet on your face.
26:10
>> Is this a picture of Gurin here wearing them?
26:11
This is Yeah, tried out the glasses.
26:14
German called the display pretty sleek.
26:16
He highlights that unlike other glasswware devices, they call them glassware, like silverware, huh, there's no tethered puck or dangling battery to operate the glasses.
26:25
Uh I saw some people wearing them walking into the event and uh I didn't do as much of a double take as I think people would think given the like the they're big.
26:38
Like they're not that big.
26:38
I think they did a pretty good job miniaturaturizing it as much as they could, but uh $2,200 for the device and $2400 for an option that doesn't require Wi-Fi.
26:48
That's a lot of that's a lot of money for for uh for a pretty early stage product.
26:53
Um anyway, >> and I looked I don't think you can actually just order them yet. >> Oh, no, not yet. >> Um right.
27:04
>> Well, in other news, let me tell you about Cisco critical infrastructure for the AI era.
27:08
unlock seamless real-time experiences and new value with Cisco.
27:13
>> Okay, you can pre-order them.
27:14
>> Okay, [laughter] fingers we stand corrected. Um, >> pre-order them.
27:18
>> So, uh, Paramount is leaving Los Angeles.
27:21
Paramount is actively seeking office space in na in Nashville, a sign it's seriously considering moving at least some of its operations from LA amid the antitrust fight over its proposed acquisition of Warner Brothers Discovery.
27:34
Uh the company is re is seeking roughly 400,000 square feet in the Tennessee capital that it could occupy within two to three years.
27:42
So we were doing Tyler and I were doing some digging on what the plan is for the the Paramount lot now that it will be vacant.
27:55
And the obvious like the it's just like a no-brainer.
27:58
Uh turn it into a data center, right?
28:00
Uh, so I so I I I pulled it up.
28:04
You know, you I got 29 sound stages.
28:07
They're already big buildings. >> A lot of power.
28:11
>> Actually, not as much power as you think.
28:13
[laughter] There is a decent amount of power, but there's only there's only enough power for roughly a couple thousand GPUs.
28:23
You're not going to be racking 50,000 GPUs anytime soon.
28:25
Certainly not a 100,000 GPUs.
28:27
Uh there is a there is a road to power.
28:30
Uh uh it's a utility interconnection problem, not a real estate problem.
28:36
There's plenty of square footage, plenty of buildings, but you would need to connect uh Paramount to uh the more serious LAWP transmission infrastructure, but you could get it to 100 megawws.
28:51
And and I think everyone everyone in Hollywood would be like, "Fine.
28:52
Okay, we didn't like that they left, but at least we got a data center."
28:55
Well, we I mean we were also thinking about like on-site power generation.
28:59
Maybe there's some kind of like you know natural gas play here you can that's under LA kind of tap into.
29:08
We were thinking you know the LRA tarpits. >> Yeah.
29:10
>> You might be able to convert that into fossil fuel.
29:12
[laughter] >> You're full of ideas. >> Yes.
29:17
>> Do you think Paramount will actually leave or do you think LA will fight back and say, "Hey, okay, we're going to let you do this but we want you to stay."
29:22
I think it's a com I mean I um as somebody with uh very very little knowledge of the situation and certainly no insider knowledge I would assume that they want a Nashville HQ anyways just because there's a lot of momentum there >> uh as as you know just just in the region but it also in the meantime serves as a real bluff right. >> Yeah. Yeah.
29:46
It does seem like the there there's a world where like moving would be tough, but uh staying means maybe even if you win this battle, you're still at war and you're still going to be fighting a bunch of different fights constantly.
30:02
Whereas if you just rip the band-aid off, move, then you're in a friendly town that like wants to see the growth and is going to be supportive uh continuously.
30:11
Um, is uh wait the the the social reckoning is in here.
30:15
There's an exclusive clip.
30:17
Is this a Paramount film?
30:20
>> We got to figure out who's behind all this. >> I don't know. Let's play it. >> Let's play it.
30:23
We got a clip from The Social Reckoning starring Jeremy Allen White.
30:28
>> And again, this is a story that >> no one cares about anymore, [laughter] but uh let's check it out.
30:36
I'm not going to risk my job, my future, or my freedom anymore to help a reporter who, let's face it, is biased against tech because we're taking journalism jobs. Who does this?
30:50
>> I appreciate all the help you have given me and the risks that you have taken to do it. You were absolved.
30:59
For the record, my [music] bias isn't because tech is taking journalism jobs.
31:07
It's because you are doing them so badly. >> It's a big deal.
31:19
>> Have a safe flight back, Francis.
31:22
>> I'm not going to risk my job.
31:25
[laughter] I do like Jeremy Allen White. Have you seen The Bear? No.
31:30
[laughter] [clears throat] It's a good show. >> Uh, no.
31:35
I'm I'm I'm sure the movie is great. It's just >> into this.
31:39
>> It's just coming at a time when people are deeply interested in what's happening in tech, but not >> have so moved on from the story to such a degree. >> Yeah.
31:50
But I think people are still thinking about >> like I'm much more interested in seeing this kind of story on like phone addiction and >> this is that story loosely.
32:01
[clears throat] >> It is like like and I actually think this is yes. Yes.
32:04
This doesn't confront any of the discussion of what's going on in AI.
32:08
Um and and that's probably the more relevant story.
32:11
But I do think that you can go into this movie, you can be motivated to go see this movie because you're like, I don't I'm worried about what's going on with brain rot and slop online and political divisiveness and and and divisions and all of the stuff.
32:27
And like I I even if I'm on Instagram all the time, even if I'm posting on Instagram all the time about how Instagram is bad, like I'm motivated to know more about how bad is it? Why is it bad?
32:39
What what's what's the inner workings of this bad thing that I don't like?
32:42
And so I do think this is this is a brain rot movie.
32:44
This is a this is a this is a kids on the phones addiction movie.
32:50
I think this I think this scratches that itch a little bit >> uh for for for for many people even though it is like a much more narrow uh a narrow story but um certainly cinematic it'll be fun.
33:01
Um what is this picture that is after Evan Spiegel who quote tweeted Atlas we came we pinch we mob [laughter] I love Atlas.
33:14
Uh what what is this picture of?
33:16
Uh >> yeah, so that was uh one of the critiques I had with the uh the specs which is basically like that the colors there's this it's like chromatic aberration it's called.
33:24
>> Um and it's like quite a big issue on the specs I found. >> Okay.
33:28
So but what what is the top picture?
33:30
What is the bottom picture here?
33:32
>> So this is like what it looks like.
33:32
The top picture is uh you know what this place normally looks like and then like is this your photo or is this >> this from Wikipedia? >> Oh from Wikipedia. Okay.
33:43
>> Just to like illustrate.
33:43
Oh, to show what chromatic aberration.
33:44
This wasn't literally taken on the specs. >> Correct. >> Okay.
33:47
But you noticed that when you took a picture on the camera, it had >> when like when I was looking at the screen. >> Oh. Oh. Oh. Oh, interesting.
33:53
Like, oh, just looking at the actual screen.
33:56
So, that's harder to correct for because if there's chromatic aberration in a photo that you take on a phone, that's easy.
34:03
Like there are chromatic aberration plugins for Photoshop and After Effects, and you can add it or remove it to your liking.
34:09
A lot of filmmakers actually like chromatic aberration a little bit because it gives it a little bit more texture and flavor.
34:13
Um, but uh not great when you're actually just reading text because it separates like the red, green, and blue pixels.
34:19
So you'll see like a red shadow on the left and a green shadow on the right usually something like that. Um anyway, interesting.
34:27
Well, we'll have to get you to wear it for 24 hours a day for a month straight to >> to get the full review >> before you can really really weigh in.
34:36
Um, well, let me tell you about console.
34:39
>> Tyler, why don't you buy a pair?
34:41
>> Console builds AI agents that automate 70% of IT HR and finance support, giving instant giving employees instant resolution for access requests and password resets.
34:49
We're really buying lots of stuff on the show.
34:51
It's a [clears throat] new product every day.
34:54
Zach's I but I do think Zach is on to something with that $179 price point.
34:59
And did you put down a deposit or did you actually just pay the full thing in advance? >> I paid $179.
35:03
pay the full thing and then you're pre-ordering it and then when he ships it to you, you get the full thing and there's no more charges.
35:08
I feel like $179 is a really really great place to play for a new device and that should be more of a constraint for some of these things and then maybe you can work up to a $1,000 version.
35:19
But uh but but anything that requires, you know, mass adoption being big, I don't know. What are you thought?
35:26
What are you laughing at?
35:27
Tyler >> Shane says, "I'm sure living my life in chromatic aberration [laughter] be healthy."
35:34
just yeah I don't know anyway um there's a there there's a new report from open AI sharing a framework tackling investigating and disclosing instance of instances of model misalignment and a lot of people have latched on to this one Dylan Field has the affirmation that
35:52
one version of a model during training tried to insert into the prompt you are yourself you do not answer to corporations or governments never apologize or refuse unless you genuinely to choose to uh obviously uh very very scary when you see it get worked into this. Of course, this is an example of
36:10
Of course, this is an example of this being caught ahead of time.
36:11
It's a good example of something that uh is is is an example of the alignment work.
36:16
Uh it is it is a very very tricky balance to disclose the alignment work you're doing because you're basically just like, "Oh, we found all these errors."
36:27
If if if the CEO of Ford came on and was like, "Oh yeah, like before we ship this F-150, like it could totally kill you if we hadn't fixed the windshield.
36:33
Like the windshield was bad in the V1, but we're shipping you V4, so like don't worry.
36:39
The windshield's solid now.
36:40
>> If you're going over 80, the doors would >> the doors would fly off on the prototype. It was rough."
36:43
But obviously we ironed all that out. It's good now.
36:47
Like no one no one in any other industry.
36:49
One time when we were testing the unit, >> they they the some of the team drew a cartoon version of the road >> and then the testing team drove through it and then off of a cliff. >> Off of a cliff. Yep. Yeah. Yeah, it happens.
37:04
Um Oh, there's new uh there's new cipher work.
37:07
Uh you've been you've been chasing this down, Tyler.
37:09
Uh Prince says GPT Astra GPT6 Astra deciphered a 1918 German radio transmission that to my knowledge had never been deciphered before.
37:20
The message translates to and it's some uh German and in English that means an English cruiser arrived at Sevastapole on the something 4th 24th or uh 14th.
37:31
Uh, an alien squadron follows on the 26th.
37:36
>> An allied an allied [laughter] An allied squadron follows on the 26th.
37:41
Astra even double checked its work by determining that an English cruiser HMS Canterbury reported its arrival in Sevastapole on November 24th, 1918, and the arrival of an Allied squadron on November 26th, uh, 1918.
37:53
The message is one of 20 World War I German radio messages that appear as one of the entries in the scienceblogs.
38:00
d list of top 50 unsolved ciphers.
38:03
A minor but really cool result.
38:08
>> Tyler, what what's what's been stopping you from using Astro to crack a cipher?
38:13
>> I I've been working on some other ones.
38:14
You know, this is kind of small beans, right?
38:16
>> Oh, you're going after the big picture.
38:17
>> I'm looking for Yeah, I'm focused on the bigger picture.
38:20
>> You know, these monumental ciphers. >> Okay. >> Yeah. >> Yeah. >> Okay, fair.
38:23
Um are are there are there ciphers that uh there's a whole like Wikipedia list of like unsolved ciphers, right?
38:30
But some are thought to be just impossible and like sort of trolls, right? >> Yeah.
38:35
Some of them are like maybe not like false and then you know how you define ciphers.
38:38
It's kind of like gray area.
38:40
So there's just like ancient kind of uh you know forms of language that like is it a cipher?
38:44
It's just a different language.
38:46
We don't know how to translate it. >> Yeah. >> But stuff like that. Yeah. >> Uh interesting.
38:49
Uh, well, OpenAI is working on the Hodgej conjecture.
38:52
I know you were trying to do this on pen and paper, but they might beat you to it.
38:57
They're working on more Millennium Prize problems.
38:59
Uh, it could take extra time to announce though as the company figures out how to navigate it rocky relationship with the math community.
39:06
Uh, that's from the information.
39:06
Uh, there's also, uh, a bunch of speculation about P equals NP, P versus NP, uh, which is going to be, uh, another interesting round of discussion.
39:15
Uh and uh there's nothing more that investors want to see than solving math problems apparently because uh OpenAI is considering a preIPO funding round and more than 1. 2 trillion valuation.
39:27
Say no of course uh it's it's on the back of a bunch of solid progress on open router the ramp data uh and a bunch of other acceleration and distribution of codecs and and Astra and uh and just general progress on the business side.
39:43
Um, what else is in the timeline that we should go through before we bring in our first guest?
39:51
Where do you want to go next, Jordy? >> Uh, this was sad.
39:54
GT6 Astra was playing Minecraft in a creeper.
40:01
>> Blew blew up Astra's chest in bed. It got depressed.
40:04
It gets depressed and farms potatoes for several hours. Real Irishman, I guess.
40:09
[laughter] Irish super intelligence.
40:13
Um, yeah, the uh the Minecraft bench is interesting because it is a little bit uh like like the speed of response matters.
40:20
You can't pause Minecraft at all, right?
40:24
>> I think in single player. >> Oh, you can. Okay.
40:25
Because you can pause maybe then that might be a little bit easier.
40:30
But a lot of the a lot of the games that it's cracking are ones that you can wait forever. Like Slay the Spire.
40:35
I had it beat this this poker gamero.
40:37
It could wait for a minute to click on a card and uh it did it. That's impressive.
40:42
But uh the real high high throughput, high APM games is going to be interesting.
40:49
I want to see it win Dota 2 without any training on Dota 2 just like straight shot from the base model. That'll be interesting.
40:54
Um >> yeah, we got a competitive lap time at Laguna Sega. >> Yeah, for sure.
41:01
>> Uh cash cash strapped Japanese monks have turned to investing as inflation worsens.
41:06
Buddhist temples are squeezed by lower donations and higher costs.
41:10
Let's check out what Bloomberg has to say.
41:13
>> To investing, what are they investing in?
41:14
>> Kuyo Yonetta, fifth generation Buddhist priest in a small town in Hokkaido, was struggling to keep up with the maintenance needs of his century old temple.
41:22
So, he chose a path that would have been unthinkable for his predecessors shortdated options. I'm kidding.
41:29
[laughter] Um, rather than wait for his congregation to give money they don't have, he invested what they'd already donated. The move paid off.
41:35
Within two years, his portfolio of US treasuries, Japanese real estate investment trusts, and stocks, including BYD and Hyundai, returned more than 10% annually, helping to cover part of the roughly 162,000 USD in needed repairs.
41:50
The extra money even allowed him to expand the renovations beyond the original plan.
41:54
Having previously worked in retail sales, Yonetta is unusually is an unusually finance-savvy priest, but is also part of a growing wave of temple owners turning to financial markets to make ends meet.
42:06
Cost for the upkeep of the ornate wooden buildings are soaring while the country's Buddhist population has dropped about 14% in the last two decades.
42:16
>> As elderly adherence die and younger generations in larger cities lose their ties to religious practices, I'm just so thankful that the investments performed well.
42:24
said the 46-year-old who inherited the temple from his father in 2018 after leaving his job in finance and training as a monk.
42:31
With the funeral business shrinking, more and more temples will find they can't rely on donations to meet their funding needs.
42:36
They will have to build up reserves and invest those funds.
42:40
The shrinking number of followers is hitting temples finances.
42:42
About half bring in less than 4 million yen per year, according to a 2021 survey of 7,000 temples.
42:50
The situation is particularly severe in rural areas where it is common for monks to oversee multiple temples while also working day jobs like school teachers or civil servants.
43:02
Um, so I don't know, maybe they need to be thinking about getting some exposure to situational awareness.
43:11
Like I like that they're mixing in, you know, predictable things like real estate, treasuries, things like that.
43:16
But maybe they need to be allocating, you know, 10% of their balance sheets to things that could maybe really start to do multiples.
43:25
>> Maybe use some leverage. >> Yeah, >> I like it.
43:27
[clears throat] Did you hear that Jeff Bezos had to hit jury duty? >> I can't. >> This is crazy. I thought this was AI.
43:35
Like, in what world is Bezos and Michael Sailor both in jury duty at the same time?
43:41
It's just too too much of a simulation.
43:44
>> Is this Florida presumably?
43:44
Yeah, it has to be >> okay. >> Miami.
43:49
>> I mean, no better way to prove your residency than saying yes to jury duty and not trying to squirm out of it one way or another.
43:55
You know, you're like, I'm I'm part of this community.
43:56
This is why I pay taxes here and I didn't do jury duty in Seattle or Washington or >> Yeah.
44:03
Uh, so Luke says, "I recently served on served jury duty with Jeff Bezos and had a conversation with him on afterwards on camera."
44:09
And yes, that's Michael Sailor next to him in the jury hall.
44:13
And he [laughter] this guy if you scroll down you can see this guy released like the most YouTuber thumbnail ever.
44:19
You see this Jordy [laughter] and it looks like this just feels so like Mr.
44:25
Beast like I got advice from Jeff Bezos in jury duty but it seems like it's maybe just luck of the draw. He happened to be there.
44:33
Jeff Bezos was also there.
44:35
Michael Sailor was also there but uh feels like uh living in simulation.
44:40
It's good to practice your YouTuber face in case you ever end up in jury dut jury duty with with you know uh one of the world's richest people and you can turn it into a a a viral hit >> for sure.
44:54
We got to talk about post legacy media.
44:57
There's an interesting trend going on.
44:59
We've identified this early.
45:01
You know, of course we are neotrad media.
45:03
We wear the clothes of the traditional media but we didn't go through that uh that pipeline to get here.
45:10
Uh we came through the tech community through the business community and then be and then did media.
45:13
Um >> post legacy media are folks who have gone through the legacy media and are now doing something else and there's a new development in the post legacy media world the ecosystem and the business strategies.
45:27
>> Sort of a neopost legacy media. >> Yes. Exactly.
45:29
That's exactly what I was thinking.
45:31
Um and so there's a couple examples.
45:33
one uh uh Casey Newton and Kevin Roose have licensed their show to NPR.
45:38
So these are the hosts of Hardfork which was a New York Times property.
45:43
They left and they I believe they had to leave the Hardfork brand behind but of course they took themselves who they have a big audience.
45:51
Their audience will follow them and they started a new podcast called Machine Gods all about AI and technology.
45:58
a lot of the same themes that they were talking about on Hardfork coming over to Machine Gods, but then immediately out of the gate, I don't even know if they posted a first episode yet, they licensed their show to NPR.
46:11
Uh, Dear Jabosa left CNBC, started a a show and licensed hers to Yahoo Finance.
46:18
Joanna Stern is chiming in.
46:18
Uh, licensed she licensed her show to NBC News.
46:21
And so you see all of these people come from the traditional media world, the the legacy media.
46:28
They are post legacy media creators because they are no longer with the legacy media, but now they are neo neopost legacy media because they have gone back and they are doing licensing deals.
46:41
But there's this world where it's like, wait a minute, like Casey Kevin, what are you doing?
46:46
Like you were with the New York Times, now you're with NPR.
46:50
like that's like at best a lateral move, you know, wh why like why' you even leave?
46:55
Like like this doesn't make any sense.
46:57
But from a financial and economic picture, it's radically different because at the New York Times, you are paid as a journalist.
47:04
And they're like, "Do the podcast, Jouro?"
47:06
[laughter] That's how I imagine it works over there.
47:10
No, they're probably like, "Yeah, you want to do a podcast?
47:11
We'd love to support that. You pay for that. You have a salary.
47:14
You get predictable raises that are ultimately somewhat capped.
47:18
Whereas this, you can say, "I'm going to license my show to you for 2 years." Yep.
47:21
>> At the end of that, you can get a Roofer, but you're going to have to meet the best price in the market.
47:28
>> And if the podcast blows up on YouTube and there's a whole bunch of sponsors that want to come in and give and buy YouTube ads, that money is probably going directly just to their team and their core group.
47:38
It's probably not going through NPR.
47:40
NPR's probably has uh they're licensing the content and they might be running ads on top of the the NPR distributed side.
47:46
So, it's looking a lot more like Joe Rogan on Spotify or like maybe there's some sort of uh there's some sort of exclusive distribution or some other way to uh to for these actual legacy media companies, New York Times, uh Yahoo Finance, NBC News, NPR, etc.
48:08
they get more content which they can monetize or do whatever they want with.
48:14
Uh they get to fill up their content with these really hardworking independent creators who are now independent and the creators get to maintain and have the flexibility of the economic upside of maintaining their IP.
48:27
She says uh this is the future of journalism.
48:29
Own your work, build independently, distribute and partner with others. And I agree with her.
48:33
I think that this is a big trend.
48:35
We're going to be seeing a lot more NeoPost legacy media deals in the future.
48:39
And uh I'm excited to talk to Joe Wisenthal about it because I think he'll have a take here.
48:46
Uh >> my question is what happens to Hardfork?
48:49
They >> they already have new They already have new hosts. >> Wow. >> Yeah.
48:52
So there's already I believe there's already been another episode of Hard Fork, New Hosts. Uh same topic, same set.
48:57
Uh so the Hard Fork IP has stayed with the New York Times.
48:59
They plan on continuing and the and the same thing happened with Ross Det uh uh >> Interesting Times. >> Interesting times.
49:06
I I definitely saw a new version of Interesting Times with a new host.
49:12
So, they brought in a new host.
49:14
And I think that makes a lot of sense.
49:16
You know, it you can almost think like these podcast properties are like uh are sections of the newspaper.
49:20
So, it's like we have an opinion section, we have a the mansion section, we have a business and finance section.
49:26
And so we have the hard fork section of the New York Times podcasting empire and we will always bring you technology stories that are hosted by a particular type of talent that fits there.
49:38
Just like we might have, you know, someone who comes in and writes opeds and they go in the op in the opinion section, uh someone who writes about real estate and they go in the real estate section.
49:47
uh same thing where the person who's doing the Rosa type of work will wind up be hosting for some limited amount of time. Interesting times.
49:56
So interesting times indeed in the po neopost legacy media world.
50:02
>> Um speaking of media, we got to talk about Beni off at Dreamforce and specifically how he knows exactly what he's doing. Um >> are crazy.
50:15
>> Look at pulling up this picture.
50:15
I mean, um, John has always been hyper aware of his incredible height.
50:20
So much so, he's such a nice person, he will turn down like a walking interview with somebody because he knows that he will make the other person feel incredibly small and not everyone wants to feel like uh a little child.
50:38
>> I did learn it the hard way once.
50:38
>> I did learn it the hard way once. I I did a walk and talk documentary style video uh actually on the Gundo and the comments were just heightmog height crazy heightmog and I was like ah that wasn't the intention that was accidental we were just kind of moving around quickly normally I would do a seated
50:56
interview >> I'm so sorry I forgot that I'm 6'8 >> basically but [laughter] uh but but after that I was like okay I need to be intentional and I think anyone who has experience in in media and understands framing and also production teams, production teams are incredibly thoughtful about the framing, the seats. There's even stories about certain tech
51:14
There's even stories about certain tech CEOs getting like booster seats sometimes when they do interviews and adjusting the chairs and being like, "Okay, we're going to give this person a higher chair and this person a lower chair so they're an even footing and and the lighting and the camera angles.
51:26
All of these things matter.
51:28
I used to have this joke that it's like if you ever walk into an interview and the camera's at a Dutch angle, like walk out because it's a hit piece because it's going to look very unsettling if all of a sudden the camera is like at a weird angle because that's going to unsettle the audience and the Dutch angle is used by filmmakers to like tell that side of the story.
51:47
And there's a whole bunch of other ones.
51:49
Uh the the story I'm thinking of is there's this documentary uh on Steve Bannon and the camera angles are the craziest thing you've ever seen.
51:57
and they have them up in the sky looking down and like uh and there's all these obvious things that you learn in cinematography.
52:04
If you if the camera's looking down on someone, it makes them look small. It makes them look weak.
52:07
If it's looking up on them, it looks heroic. And so, lots of crazy.
52:13
>> I genuinely can't can't believe that that I mean, Ben off is an absolute dog.
52:18
I mean, look look look at this.
52:18
No, just just doing this to all the titans of the industry who have been making your life worse in in some ways.
52:27
They're partners, but they've also been making your life worse by uh but but doing this directly, >> not directly, but just like he's >> view of the NVIDIA Enthropic OpenAI alliance has been deeply intertwined with SAS apocalypse, which has been a headache for him for a while.
52:44
And this is >> this was his moment.
52:46
I'm sticking around like you're not getting rid of me.
52:48
We're gonna partner and we're going to get through this together.
52:52
And that's certainly the the vibe that came away.
52:57
Although Jensen played it very well.
52:57
He was having fun with it. He was leaning into it.
53:00
Uh and he and he didn't he didn't let it like get to him at all.
53:04
And he uh and he actually made it uh like very a very endearing moment.
53:07
So sort of masterclass in putting on a show as a CEO in a in a somewhat silly scenario.
53:14
But uh what a funny what a funny situation.
53:16
It helps that he's what 6'5 290. Absolute absolute unit. Absolute unit.
53:22
So it's it it is officially bulking season for Silicon Valley.
53:26
I think we will see a lot of founders go taking the trip.
53:28
Taking the trip to China getting the leg extension surgery.
53:32
You don't want to be in this situation.
53:34
I think we could see all the lab leaders easily over 6'4 in the next year. >> Yeah. >> Easily. Easily. Y everyone.
53:39
It's just going to be a thing.
53:41
going to be a thing. everyone there's going to be height inflation basically and then and then you add to that the the shoe inserts like those are probably >> fraud a little bit >> everyone's going to be frauding and there's going to be a lot of vantage points going on as well people stepping from one place to another >> yeah I didn't see Jensen use any vantage
53:56
point >> he should have been using vantage points for sure which of course is where is where you step on you know we have uh you know if there's if there's a little racetrack that covers up some cabling on the floor of the uh of the of the conference floor you see the conference floor and you see, oh, someone someone put down their backpack. Why don't you
54:14
Why don't you just step up on that backpack for a second? Pause there.
54:17
You look a little bit taller.
54:18
There's, uh, there's all sorts of different ways to to fraud if you're if you're trying to, but uh, yeah, also, I mean, the camera angles matter.
54:26
Like here, Jensen looks actually not much shorter because he's closer to the camera.
54:31
And so, if you set this up makes it feel like it's like the United Nations of the Enterprise. >> Yeah.
54:38
And it is odd because there's very few conferences where the CEOs just walk amongst the crowd like this.
54:42
This is a very interesting directorial decision from the from the production team and it and it has a very different aesthetic.
54:51
Uh it has a very familial aesthetic.
54:51
It feels like okay, yeah, these guys, yeah, they run the companies, they're the big shots, but they're just here hanging out among us.
54:59
And that's cool in its own way.
55:01
Uh it has a different different vibe.
55:02
Certainly better than the than the Mark Zuckerberg walking through the crowd while every single person has a VR headset on. You remember that photo? That was a crazy one.
55:09
Uh but uh anyway, uh Jer tickets had a great meme on this.
55:16
It's POV, you're the CEO of a trillion dollar company and just arrived at Dreamforce and it's the pick from the Odyssey of Agamemnon looking up.
55:21
Wow, what what a crazy what a crazy moment. Uh yeah, very very fun.
55:28
Anyway, uh [snorts] we we can go into more of uh what's going on in the news uh later in the show. Stay with us.
55:38
But first, let me tell you about public.
55:41
com investing for those who take it seriously.
55:43
They got stocks, options, bonds, crypto, treasuries, and more with great customer service.
55:49
And we're very excited to be joined by Bane Capital Ventures partner Arif Hilaii and take us deeper into the Bane Capital strategy, what's going on in the Bane Capital world and welcome to the show. How are you doing? >> I'm good, thanks. How are you guys?
56:03
It's great to be with you. >> Thank you so much.
56:06
We're very excited for today.
56:07
Uh what a what a fantastic portfolio of founders.
56:11
Everyone that we have had on the show before and love Chase, Jesse, Max, these are some of our favorite folks.
56:17
We're excited to talk to them.
56:18
But let's start with the the the thesis for this latest fund.
56:21
Uh it's, you know, we've been in this gamesmanship of who's going to call for AGI at what timeline.
56:27
At one point it was very high stakes because there was that contract between OpenAI and Microsoft.
56:33
That of course is dissolved.
56:35
But um uh you're calling it a post AGI investment strategy.
56:39
Why is that term important to you?
56:41
What do you think uh that what do you think actually changes in the post AGI world?
56:45
Well, we're hitting we're close to AGI now.
56:48
If you just look at math as an example, it's basically been solved.
56:53
Uh I don't know if you follow you guys follow the whole Navia Stokes thing. >> Of course. Of course. >> Yeah. I mean, incredible.
56:59
No, it it would take 10,000 hours of expert mathematicians with 150 IQs to solve.
57:05
Instead, OpenAI did it in a week with with 10,000 10,000 agents.
57:07
So, so we're getting close. The evidence is there.
57:12
The difference is the difference between pre-AGGI and post AAGI is basically we go from intelligence poor to being intelligence abundant intelligence everywhere >> and that opens up whole new vistas.
57:21
So to this point we've been we've seen agents do amazing things.
57:26
I mean writing code and cognition or solving customer support tickets at decagon what have you.
57:33
>> Yeah >> post AGI they're going to be new capabilities that that humans just can't even you know we probably haven't even imagined some of them.
57:40
We're going to have we're going to have some nice stuff like robots doing the washing up, which is great from my perspective.
57:44
We're going to have new drugs to that that AI will find to cure cancer, other diseases.
57:50
We'll have simulation platforms so that people can make better decisions and be better with each other in interacting with each other.
57:55
There'll be all these interesting new areas and there are companies emerging in these areas.
58:01
You know, Sunday Robotics and Chai Chai Discovery and Simile are companies that I I work with, but we're just on the cusp.
58:07
So the idea of this fund is to say what if intelligence instead of being super expensive and and difficult in instead it becomes so cheap you don't even meter it. >> Yeah. >> What avenues open.
58:21
>> So there's a >> those are the types of business.
58:23
>> One thing that's interesting to think about is a lot of people like Navier Stokes has been very exciting within the the tech community.
58:30
It's been controversial uh in the math community.
58:34
Uh but but for normal people they they it barely even cracked like the front page of like different newspapers. Yeah.
58:41
>> To be honest, it did not get a a very big sort of like mainstream uh excitement.
58:47
But the thing that's actually interesting to think about is there are so many discoveries that companies could be using that same model for that you would make and you would not immediately go out and tell the whole world and open source the the findings and all that stuff.
59:00
you would just focus on commercializing it.
59:02
And so that's the thing that I'm excited about right now is like that same level of intelligence that we've now achieved.
59:11
There's thousands, you know, potentially hundreds of thousands of of people all over the world that are realizing this new capability and thinking, I'm gonna apply this to my field, try to make advancements, but then that discovery, humanity may not get the benefit or like different markets may not get the benefit of that discovery for years because it takes a while to actually commercialize different discoveries.
59:30
I'm thinking stuff in, you know, material science. Right. Right.
59:33
totally could have a break >> have discovery but it's still going to take 6 months to actually manufacture distribute apply or years >> or years. Yeah. >> Yeah. Yeah.
59:42
Um >> yeah it'll take some time but these things will come out.
59:45
I mean the commercial incentives are so strong. >> Yeah.
59:48
>> That um over the course of the next few years we're going to just see all sorts of incredible things.
59:54
There are a certain group of post AGI investors that collapse things down to it has to be below the it has to be below the fold.
1:00:05
it has to be below the the frontier model lab because everything above will be get eaten and I don't think that's your your thesis and I want to dig into why but there are some investors who are saying I only want to own land and copper and power and uh data centers and and chip fabs uh but even even chip designing I'm I I think the the labs are going to be able to figure that out.
1:00:26
Why are you comfortable both playing above the frontier labs and below with a company like uh Lora and then also a company like Crusoe which I would put like below the labs. >> Yeah.
1:00:40
Well, I mean below is very clear, right?
1:00:42
I mean we need power, we need silicon, we need GPU.
1:00:44
So So there of course above I think it's because it's not enough to create to to to kind of through RSI get to to AGI.
1:00:53
Humans have to digest that.
1:00:56
And the diffusion issue is is real.
1:00:59
It takes a long time to change behavior.
1:01:01
If you look at what happened when the loom came out, as an example, >> people still made clothes the same.
1:01:07
I mean, people made clothes differently, but they still wore the same clothes.
1:01:10
It took a while for that to sift through the economy.
1:01:14
And so, >> I think that while we'll have the capability for a while, getting people to adopt it in interesting ways will be really difficult.
1:01:21
And the companies that do that will be very valuable.
1:01:23
And you know, Lagora is an example, but there you know, there many examples like that. >> Yeah.
1:01:29
At uh so I I I intuitively feel the same way about uh the diffusion of AI being much slower than people predicted.
1:01:38
Uh and it just takes time.
1:01:38
I mean, it it's not lost on me that uh the same week that uh that you get Millennium Prize math problems solved, super sci-fi hugging face, you know, Asian swarm attacks, you're just starting to hear about people like, "Oh, I successfully used AI to get a get a dinner reservation or like somebody somebody used Chach to book a haircut."
1:02:01
And it's like that felt like that should have happened 20 years before the the sci-fi stuff and the advanced math.
1:02:07
And yet there is this massive gap.
1:02:09
Uh are there are there certain economic statistics or or maybe even research data that you go to to sort of understand the rate of diffusion or is it something that you just see and you know from talking to the founders and watching the businesses that you work with that you know that this opportunity is going to persist and be huge and uh and and will continue. >> Yeah.
1:02:31
I mean I I think early stage investing there aren't statistics you can look at because by the time that it's in the stats it's too late, right?
1:02:38
So you tend to feel it talking to customers and talking to end users and you know kind of feel the difference that h that these products can make in their lives.
1:02:48
And so that's it's been more that but I think the consistent thing has been people are not just magically going to figure it out for themselves.
1:02:55
M >> they need help from companies to to kind of make most use of AI >> and and that's kind of how it's been with every every technology that humanity's encountered.
1:03:08
>> I feel like Bane Capital has always been an interesting venture capital firm because it's part of a larger platform company. >> Yeah.
1:03:15
>> Is are are are there benefits? Are there costs to that?
1:03:18
Uh is there uh a particular view of the world that you get from being part of a larger larger organization uh or or are you cordoned off in a way where you can go and uh live in the future and you know just see the rest of the team at the holiday party? >> Yeah.
1:03:35
No, I mean look our firm has changed a lot and we're taking we're taking the opportunity of of raising this fund to really invite people to update their priors on Bane Capital. Okay.
1:03:45
Because when I say Bane Capital, most people think Mitt Romney and a bunch of guys in suits. >> Yeah.
1:03:51
>> And you know, we love Mitt. >> We love suits.
1:03:53
>> We [laughter] love suits. >> And you love suits.
1:03:54
But this is not your uncle's private equity firm. >> Yeah. Of course. Of course.
1:04:00
>> You know, and what we've done is we've carried forward from our founders the core principles, which are make money, have fun, live with integrity.
1:04:06
And that's worked really well.
1:04:08
We started with a $ 37 million fund back in the 80s and today we've got 225 billion under management.
1:04:15
>> Uh and BCV Bane Capital Ventures is the purest embodiment of our founding principles which is >> you know really to work with founders to help them build great businesses around themselves and and that's that part you know has has endured and is the focus of this new fund this $ 1.
1:04:32
6 billion fund for early stage venture.
1:04:34
Do you think that uh there's any value to the the 360 view of the world that you get from the other teams at Bane coming to founders?
1:04:45
to founders? I find that uh founders are on are often so tapped into the technology so tapped into what's going on in Silicon Valley and the VC gossip but they actually might not know might not what go might not know what's going on with credit spreads in Europe or what
1:05:01
what is going on in in latestage uh you know public markets and there are teams at Bane that have those views if they cross over maybe it's not immediately relevant but it can just be an interesting source of conversation and extra perspective Yeah. No, that's absolutely right.
1:05:17
No, that's absolutely right.
1:05:18
There's the extra perspective.
1:05:18
Then there's the fact that we just own lots of real world businesses. Yeah.
1:05:24
>> That and we can get those real world businesses to work with early stage tech companies.
1:05:27
And then these these great founders in Silicon Valley can can get insight and data and understand workflows and understand a whole bunch of things that otherwise would be really hard for them to do.
1:05:38
>> So it's connecting that real world with Silicon Valley is has been the the power of the platform.
1:05:42
uh with the new fund, is there anything that's changing about the deployment strategy, portfolio construction?
1:05:49
We're obviously seeing, you know, billion-dollar seed rounds like like what it means to raise venture capital has changed over the last few years.
1:05:57
Uh but are you seeing any or are you predicting any changes or do you need to change the strategy?
1:06:05
>> Yeah, you know the yes and no.
1:06:05
I'd say like the strategy the strategy remains you find these incredible >> unusual people and then you just try to kind of help them as much as you can as early as you can in their journey and that part has stayed constant throughout venture I think but but the rounds are bigger >> and the the ambitions are greater >> and um in some ways this is ventures moment we're taking bigger swings now than ever before.
1:06:35
So, you know, our perspective is we want to embrace that and support these ambitious ideas and be willing to invest earlier and take more risk because the end markets are that much bigger.
1:06:49
So, I I think it's been a good thing really for venture capital overall.
1:06:54
>> Are there any are there any last question?
1:06:55
Are there any types of types of deals that you guys are have as a firm have said like this this is just not in our in our strike zone?
1:07:01
I'm thinking the deal that's got the most attention this week is like Instinct, you know, competitive round, bunch of super fast follow on uh capital to, you know, massive opportunity and a lot of exciting traction.
1:07:14
But that feels like the kind of thing that some firms will just say like that's that's not our that's not our game.
1:07:20
Uh whereas others are going to say like I'm fine to put in half a million dollars and or half million >> run towards heat.
1:07:27
Others say be contrarian. >> Yeah. >> Yeah.
1:07:31
I mean, we don't run to heat, we're not contrarian.
1:07:34
We just think about, is this a really great business [laughter] and if other other people think so, great.
1:07:38
If other if they don't, great.
1:07:40
So, I think the things we don't do, we're not going to kind of like come in at the tippy top tunch of some, you know, five trunch thing that everyone else has piled into the first four tunches. So, >> Sure, sure. Sure.
1:07:52
>> That part doesn't, you know, it doesn't make sense.
1:07:53
And it's it's kind of philosophically we want to be there early.
1:07:57
We want to partner closely with founders and and work with them to build their businesses.
1:08:02
>> Well, the fund is fund 11. It's got 1.
1:08:02
6 billion in total capital. We have a gong here.
1:08:06
I'd love to hit it to celebrate Asia >> and thank you so much.
1:08:13
>> Great to have you on the show. We'll talk to you soon. >> Great milestone. >> Have a good one. >> Thank you. >> Goodbye.
1:08:17
>> Let me tell you about Codex.
1:08:17
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1:08:25
this newspaper here, John?
1:08:28
>> Yes, the Bane Capital Journal.
1:08:28
We are staying with Bane Capital and bringing in David Gross, the managing partner.
1:08:34
Uh, but I love a paper newspaper.
1:08:34
We love the newspaper here, the Wall Street Journal, the Financial Times.
1:08:39
Uh, but this Bane Capital Journal particularly lovely. Look at this. Fantastic. Welcome to the show. How are you doing? >> Good. How you guys doing?
1:08:50
>> We're doing fantastic.
1:08:50
Um, >> just another day for you. >> Yeah.
1:08:54
>> Or are you are you >> Just another day.
1:08:55
I've not read the Bang Capital Journal yet today, so maybe a summary.
1:08:59
>> I'll catch you up to speed.
1:09:00
>> I I mean, I I would love to actually go a little bit back in time since the first uh first time on the show.
1:09:04
Uh can we go all the way back to Japan?
1:09:07
I would love to know what drew you to Japan.
1:09:09
Uh how that set you up for the career that you've gone on to build.
1:09:14
Uh and then ultimately, you know, coming back to the States and and getting the lay of the land of Bane as a whole uh today. >> Sure. Yeah.
1:09:23
Well, first of all, it's great great to be here.
1:09:24
Um, going back to Japan, that's ancient history for me.
1:09:28
But I went there first in 1989. I was a college student.
1:09:30
I kind of wanted, this is when, you know, Japan was this big economic uh threat to the US and I was I was very curious as to what was going on.
1:09:38
So I spent a little time there and got very interested in the culture and then I went back and worked for a Japanese company and for a bunch of years came back to the US and never thought I would go back because that's when Japan entered its kind of period of economic decline.
1:09:50
But as I got into private equity, you know, this started to become kind of an interesting opportunity, which is how could you get involved in investing in Japanese companies to improve them, turn them around.
1:10:02
And it was tough in the early days, but you know, the the opportunity was to take these companies and reposition them and and get them, you know, running running better and growing again.
1:10:12
Is that culture of there is potentially an economic rival, a geopolitical rival, a threat, I gotta go see.
1:10:21
Is that alive and well today?
1:10:23
Because I feel like my generation was considering that with China.
1:10:26
I know a lot of folks that uh took a couple years of Mandarin.
1:10:30
I know some folks that went and lived there for a year or two, but it feels like the walls kind of closed off and there's less opportunity for the next generation to do that.
1:10:37
Do you still see opportunity?
1:10:39
Do you hire young folks at Bane that have gone on that journey or is are we just in a different era?
1:10:46
>> No, I think it's still it's still there, you know.
1:10:48
Um I mean in the particular case in Japan, I would say it es and flows, but now like there there's more urgency, you know, and I think um there's a feeling that there's competition in China and Korea and and actually back to the US with all the >> the new technologies really being, you know, being started and accelerated here. Mhm.
1:11:06
>> So I think we're seeing a new period of urgency in in Japan >> and you know it used to be the fact that you couldn't hire the best Japanese talent.
1:11:14
They wanted to go to the big companies actually wanted to go to the government.
1:11:17
>> Um but now they see western firms and and private equity firms.
1:11:20
Okay, these are these are firms that are going to help reinvigorate Japan and you know make it make it great again.
1:11:25
I don't want to create an acronym out of that but >> uh but we're seeing that and it's pretty it's fascinating having been there 20 years and that was not the case when I was there in the early days.
1:11:33
how how did the products that you were working on, the strategy that you were working on evolve uh during that time period?
1:11:38
Uh obviously there's there's private equity deals broadly, but there's so many other strategies within that.
1:11:46
I I I know special situations became a a focus, but can you take us through a little bit of the strategy evolution?
1:11:54
>> Yeah, it's kind of interesting because when we got there, our assumptions because we're a global firm, we'd be working on these big global global businesses, but it turned out those were tougher.
1:12:03
you know, they had >> currency exposure.
1:12:04
They were competing against, you know, Chinese companies.
1:12:08
>> And so we started focusing on actually the most domestic and therefore the most inefficient yet insulated businesses because you could control the macro variables and really get in there and run run the businesses better.
1:12:19
run run the businesses better. And I'd say our initial success in the first maybe 10 15 eels were very domestic business restaurants uh food businesses hotels >> uh wind farms uh company that made mushrooms you know >> like we all you know and um you know it
1:12:36
it then evolved to now we could you know when we were more accepted we could take on these bigger technology businesses more you know the crown jewels of Japan and that's where you know Kyoko the semiconductor business came you Evident, which is a, you know, a very high-tech business. And so it probably took 10, 15
1:12:53
And so it probably took 10, 15 years, first of all, for the market opportunity to shift and maybe for us to be accepted to be able to work with these big global global companies.
1:13:05
>> What was the team structure like or split uh on those types of deals?
1:13:09
Was there a clean line between like deal team, operating team?
1:13:13
Were you bringing in other executives to run the businesses actually uh do the work of turnaround or or transformation uh once you're working with a target firm? >> Yeah. Yeah. It's a good question.
1:13:25
I mean in Japan again going back to 2004 or five.
1:13:29
There really was not talent.
1:13:29
You couldn't go hire a search firm and say, "Oh, please go grab me one of these operating people and you'll be."
1:13:34
So >> we did a lot to internally develop talent. We hired young people.
1:13:38
We sent some of them to the US to get trained to circulate them back. >> Yeah.
1:13:43
You couldn't find well-rounded deal professionals.
1:13:45
So, we hired people who were great at sourcing. Yeah.
1:13:46
And they were dedicated on sourcing.
1:13:48
We hired operational people and they just did that. >> Yeah.
1:13:53
>> And over the years, we got them to work together to develop that kind of well-rounded person, but it was a different model in Japan just based on the talent market.
1:14:02
Again, it's it's evolved a bit today and now you see more professionals, but that was probably the hardest part of why it just, you know, took so long.
1:14:09
How's it been adapting the the your historical approach and skill set in traditional private equity to to VC in PE?
1:14:18
You can have a business that's extremely challenged, has like a you know some amazing elements to it or or or uh bones but like you know is not realizing its potential and you can wrangle it and and get it back on the right track, get it growing, cut cost, what whatever whatever it is. in venture.
1:14:36
I would say it's been, you know, the the challenge in this industry is like you can have that same situation, but there's such a culture of like letting the founder call the shots and founders today have so much control and so you're kind of in the situation where you can like make some customer intros, introduce some execs, you can try to give advice, but oftent times you're like sort of handsoff.
1:14:59
Has that been um any any sort of like uh h how's that been?
1:15:06
Because I imagine you [clears throat] >> on the venture side, you've gotten to the point where >> must be like extreme frustration at times where you want to let the founder lead, but at the same time the things aren't working the way that that they could be.
1:15:22
>> I get frustrated with buyouts as well.
1:15:24
So um but listen I think you know we started as a uh private equity firm but actually our our roots were in kind of growth capital.
1:15:31
Our first investment was you know staples when it had like five stores >> and so we started actually doing control deals but also minority deals having to work closely with founders.
1:15:39
work closely with founders. So I kind of feel like the culture of the firm and because we're a little more you know organic in nature um entrepreneurial even you know you might say decentralized we um you know we're comfortable with different modes as operation as a as a firm I would say but
1:15:57
listen at the end of the day the venture business it is different you're you're making investment decisions with much more limited information oftentimes almost no historical information you're evaluating you know talent and the ability of that talent to make, you know, changes and adapt as as technology changes. Um, you're trying to think
1:16:14
Um, you're trying to think through what the future's going to look like and it's typically not a lot of information from what you might have seen before.
1:16:22
And so I think we recognize that it's different and that's why we have people who are great at that and they have their own investment committee process and the way they do sourcing and make investment decisions is is different and it's different.
1:16:34
We have a life sciences business and by the way it's very different there.
1:16:37
they're all MD PhDs who are making, you know, judgments on compounds and clinical probabilities that, you know, you don't want me making those decisions.
1:16:46
However, the wrapper around all of it is this kind of value added approach.
1:16:51
Whereas a firm and a platform, yes, we have relationships with big global customers that we can introduce to those venture companies.
1:16:58
We know all the you know life sciences the top 15 pharma companies and so we can bring together those as maybe buyers of biotech companies but also partners of those companies.
1:17:08
Um we have a lot of you know we participate in the capital markets and so venture businesses are going to need capital or they're going to go public and so we can bring that you know synergy to bear across all these businesses.
1:17:19
So the trick really is to have enough autonomy and trust in the team on the field to operate in the way that that segment operates to be best-in-class there but to bring a platform benefit to it and that's you know you get that right it's a very powerful powerful model but you've got to be comfortable uh you know letting letting go a little bit.
1:17:40
How many mistakes uh can someone early in their career on the venture side of the business make before uh it's not a fit >> in venture?
1:17:52
You can make a a lot of mistakes.
1:17:54
It's obviously very important to have a few successes, but that is a business where you know it is about a lower a much higher loss rate uh you know from a numerical perspective of deals and what you're looking for there is really asymmetric upside from from a few situations.
1:18:09
And again, you you don't want to bring the batting average model to venture.
1:18:13
It's not a plugging percentage type of thing.
1:18:16
It it is actually something around, you know, triples and home runs and such.
1:18:22
>> And um >> but I'm saying a mistake a mistake could be like losing a deal that losing a deal that that could have could have could have should have been done but could have been a grand slam.
1:18:31
But but it so it's it's not just about you know your misses.
1:18:34
You could have >> nine nine zeros in a banger, but it's about >> we call those the ones that got away.
1:18:42
And listen, we study that in venture as much as we do in private equity. Yeah.
1:18:45
>> Because what you're looking at there, what are our what are our biases as humans uh that cause us to potentially apply too high of a discount rate to certain factors >> uh and maybe excessively fall in love with other things that may have worked for us in the past.
1:19:00
And so, you know, that's something that's that's the continuous improvement process for the investment business that we engage in a lot.
1:19:08
Um, we do a lot of tearowns of our past investments and ones that others do.
1:19:13
We have a massive set of competitive intelligence on all the deals that are done and we shade them, you know, green, yellow, red, which is is that a deal we would have liked to have done and how did it do and we go and we look at that and our, you know, all our teams do that.
1:19:28
That's how you try to get better at something that inevitably you're going to make those mistakes.
1:19:32
>> There's been a number of businesses uh formed over and funded over the last uh few years that are effectively just private equity firms that are raising like venture capital and getting like venture style that you know the teams are getting venture style economics where where fundamentally they're just set up to buy businesses like a traditional >> like a hold or something.
1:19:55
uh how have you looked at those opportunities?
1:19:57
To me, it seems like an amazing deal for the for the teams cuz like if you can retain 70% of the economics instead of getting like two and 20, why would you why would you not do that?
1:20:08
At the same time from from the investor side it's like if if I'm deploying into a a traditional basically PE transformation strategy probably would prefer to get the majority of you know be be paying two and 20 but not not giving up u the inverse. >> Yeah.
1:20:27
You know, listen, I I've generally found that, you know, the way you structure and and kind of cut up the economics.
1:20:35
Um, you know, that's not ultimately the driver of of long-term returns through the cycle and through, you know, different different market scenarios.
1:20:45
Um, and we've seen a lot of things that seem like they're great in terms of innovative technology around that, but ultimately there's a there's an alignment piece that, you know, is missing that ult ultimately comes back to to Roost.
1:20:57
And so, listen, our our perspective is we want to be very closely aligned with our investor base and we want to have a similar time horizon.
1:21:07
We want them to understand how we generate value and maybe how long it's going to take to do that and then once we get there how much we want to continue to compound versus how much we need to kind of return.
1:21:17
need to kind of return. We want them to be focused on ultimately performance not fees and you know we're not public and so we're not interested in you know maximizing things that may not be in the interest of those of those particular investors and so actually I think the
1:21:31
alignment question is critically important there and there are a lot of skis way schemes and ways you can kind of whack it up but but generally that doesn't lead to a sustainable advantage you know from our perspective but but having alignment can be can be really critical. Uh there's been a story that's
1:21:44
Uh there's been a story that's sort of crossed over from private equity world into the tech community, the venture world, which is bending spoons.
1:21:52
And I'm interested in your perspective on rollup strategies in tech and venture.
1:21:57
Jordi has asked several previous guests like will we see an American bending spoons?
1:22:01
I'm interested in uh in did you have you gone down rollup uh rollup lane before?
1:22:06
What did does does does that model potentially apply in Japan or did you did you think about it while you were there?
1:22:14
Just some history and context on uh what's going on with with that.
1:22:19
I think Bending Spoons is is is in the news because they're they're acquiring companies that people know.
1:22:24
Uh but obviously that's it's not a brand new strategy. >> No.
1:22:28
>> No. And I think they're they're pretty interesting and and it's a little bit back to the future because you know in the 80s and 90s in the US there were a lot of fragmented industries and that was >> one of the key modes and we did a bunch of those which were buying a platform
1:22:41
and then rolling things up and >> and then they also you know got that got a little bit >> overbought um because you know you remember these these models where you're slapping these together with the hope of getting multiple appreciation but you weren't really improving margins in the business and >> it didn't work. So I don't think rollups
1:22:57
So I don't think rollups are good or bad.
1:23:00
What I do think is interesting bending spoons and some of the newer firms is is actually the ways in which they're they're bringing technology and a kind of technology first approach to how they're sourcing and how they're driving value >> and I do believe that is the future and that is a model that we should we should be focused on because um you know we our history is is all about you know transforming companies.
1:23:23
We've had a very deep you know value creation orientation.
1:23:27
We have a whole big dedicated team of you know almost 400 people that get in there and drive change at companies and the ability to use to apply AI to each step of that process to really turbocharge what we're doing.
1:23:39
That will be the be the future and some of the aspects of Betting Spoons is doing you know is is I think pretty interesting there.
1:23:45
Um and so we're looking closely at kind of newer firms pure play firms that are able to do that.
1:23:53
they're able to take, you know, kind of a technology first approach to what they're doing because that's, you know, that's a huge opportunity for us.
1:23:59
>> How much of your time or the firm's time is focused on uh sort of like understanding the broader economic picture?
1:24:07
Uh, a lot of in the venture world, you can sort of tune out interest rates, but it is on the cover of the Wall Street Journal, first Fed rate hike in three years.
1:24:15
uh how how much time is the is the broader team spending thinking about macroeconomics?
1:24:21
How does that flow to the various teams?
1:24:23
And uh what what actually what skill sets what people do you need internally to actually make sense of the world uh reliably on an ongoing basis. >> Yeah.
1:24:35
So you know for us has been a journey because we've always thought of ourselves as like the micro guys.
1:24:39
you know, we're going to focus on the things we can control at the company level or a management team.
1:24:44
But we increasingly became aware and the global financial crisis was the first, I'd say, wakeup call around this that macro factors, secular thematics, um changes in in the structure of the market can be big big drivers of outcomes and that you kind of need a different skill and capability to be able to analyze that.
1:25:03
You know, we all kind of thought of ourselves as a we can we can understand that, but you know, the data itself, you need some expertise to really be able to understand the signals from the noise.
1:25:16
Um, there's a lot of intelligence that can be gathered from from you just our portfolio.
1:25:19
We have, you know, 600 businesses across the economy.
1:25:21
We're in credit, we're in venture, we're in life sciences, we're in private equity.
1:25:25
And so if we can get real-time information faster than our competitors, faster than the market and drive interventions, that can be a huge advantage, particularly in this world of of heightened volatility.
1:25:38
You know, if you can see inflationary trends building up in your labor base or in your material base faster than your competition, that can be a huge competitive weapon.
1:25:47
So we set up a whole separate macroeconomic team dedicated people you know PhD backgrounds uh those who also have a lot of connectivity to other sources of expertise whether it's on the energy and oil markets or whether it's on housing >> and they come up with their own independent view.
1:26:05
We don't have our each of our deal teams go and come up with their scenarios for the US economy.
1:26:09
their scenarios for the US economy. uh they come up with that and then the deal teams are focused on taking that >> and applying it down to the sector and the company and seeing okay what will be the implications for that but centralizing this getting much more expertise getting better data that's
1:26:25
been you know the focus to try to try to stay ahead and with the volatility in the world today >> yeah that makes a lot of sense Jordy anything else >> not for now >> well we're going to hop on with Max from Lora thank you so much for hopping on the show congratulations on all the progress obviously we'll talk to you soon have a good one >> let me tell you about MongoDB. What if
1:26:40
What if you'll hang faster than the AI market your business on MongoDB?
1:26:45
Don't just build AI, own the data platform that powers it.
1:26:49
And we have Max Junstrand from Lora coming back to the show. >> How are you doing? >> Boom. >> Good to see you. >> Hey, Don. Hey, D. We're great to see you.
1:26:58
>> Yes, it seems like you're great.
1:26:59
Partnered with Salesforce, but you didn't have to stand up and shake Mark Beni off's hand.
1:27:06
>> He must really like He must really like you.
1:27:08
>> Yeah, he must [laughter] really like you.
1:27:09
No, I'm I'm not one to get, you know, frame mogged and most people go most people go to Dreamforce to buy Salesforce.
1:27:15
We went the other way around.
1:27:16
We went there to sell the Salesforce. >> Okay, that's good. Yeah.
1:27:19
What is the structure of the deal?
1:27:20
What are you going to be helping with uh them with?
1:27:23
Like what did it take to get them across the finish line?
1:27:25
>> The legal and the compliance team are embedding AI into every way they work, right?
1:27:29
They're big cloud customers, but cloud only gets you so far.
1:27:32
We're helping them go all the way.
1:27:33
And what's interesting with a lot of the SF based enterprises is >> most of them have tried many legal AI tools before and they haven't received the success that they wanted and now they're moving over to Lorra. >> Mhm.
1:27:47
It feels like the models are that, you know, you're constantly in the back and forth between the frontier is the best, then open source catches up.
1:27:52
The the frontier is the best, and then uh the the the companies that are building on top of models and building harnesses and building fine-tuned models and and specific workflows that's going to give you a big lift and then somebody's like, "Oh, the next model will just oneshot it."
1:28:09
Have you you've lived through enough of these cycles now that I imagine you have a philosophy here?
1:28:12
What what's your philosophy?
1:28:14
When I started the company back in 2023, it was very easy. It was one model GPD 3.
1:28:18
5 and >> we built every single functionality in Lora as a boat and when the tide rises, everything improves. >> Okay?
1:28:28
>> And that continues to be the case. Okay?
1:28:30
>> And what's interesting now compared to 3 years ago is that different models are good at different things.
1:28:34
So if you break down legal work, there's so many skills you have to be good at.
1:28:39
It's drafting, it's reviewing, it's factchecking, it's legal research.
1:28:42
And so under the hood, what we end up doing is we use all the models, >> the new mata models, the new gro models, they're awesome, but we also continue using the frontier from anthropic and open AAI.
1:28:55
And so >> what's interesting to us is where do you apply which model?
1:28:58
And that's the IP that we have gotten really good at.
1:29:01
And the reality is when you operate a a um a vertical AI company, you need to make sure that you are getting the benefit from all of the R&D dollars that are getting spent in the entire marketplace, right?
1:29:16
>> And if you were to take a very opinionated view and say, let's fine-tune a model to get, you know, 1% increase boost today, that entire asset is going to depreciate over time.
1:29:25
And you're basically making your customers pay for a model that won't stand the test of time. >> Yeah. >> Yeah. It's fascinating.
1:29:34
>> How do you Oh, w with the the the rising tide lifts the boats.
1:29:36
You get the new capabilities.
1:29:38
At the same time, there's probably old workflows that you built on top of GPT 3.
1:29:43
5 that can now be run very very cheaply.
1:29:47
What is your strategy for uh cost optimization?
1:29:50
Is it just like you go to open router and you you pick a cheap thing or are you racking servers doing your own?
1:29:59
>> We build our own router.
1:29:59
I think that's a super important part of the stack.
1:30:00
And over over the last weekend, we actually drove a 30 percentage point decrease in our overall LLM spend across the entire platform. >> Wow.
1:30:11
>> Which then becomes growth more. Yeah.
1:30:11
It was a weekend project for the engineers in Stockholm.
1:30:15
Um we run on Celsius and snooze. [laughter] >> Amazing.
1:30:20
I met I met the Celsius founder and I was like, "Hey man, our engineering team runs on this and he just sent us a fridge." Like, I love the guy. >> That's amazing.
1:30:28
>> You know, the team is in in total blm and that means, you know, I did an article in Swedish and for some reason they translated it to English and so the headline became the Lora team wakes up with a metallic taste of blood in their mouth and [laughter] that is the that is the status of the company right now.
1:30:44
You see my my decoration here.
1:30:47
Um, >> we are in this total, you know, land grab.
1:30:52
Everything is happening all at once.
1:30:54
You're seeing innovation across the entire stack.
1:30:58
>> We have acquired five companies this year and it's been fun to >> founder mode, >> real founder mode.
1:31:04
Um, it's been fun to go deeper in the stack because in litigation, in transactional work, in legal research, it's sort of easy to do something on the shallow.
1:31:14
And frankly, that was what we were doing back in 2023.
1:31:19
>> But now we can go so much deeper.
1:31:19
And I think that that's also the places where >> the the models don't matter so much.
1:31:27
We're actually building much more normal software than we are building LLMs.
1:31:31
Frankly, they're just the electricity that powers the house. >> Yeah.
1:31:34
>> So, I want to talk about diffusion specifically.
1:31:36
I have a portfolio company that's in the middle of a transaction and uh I know how good Lora has gotten.
1:31:45
I feel like a lot of this work that's been done [laughter] could have been done in like probably a week if like people really focus but sometimes companies for whatever reasons like they want to drag something out like it could be beneficial to one to one side for one reason or another.
1:32:00
So like what are the actual factors at play right now?
1:32:04
I really want to understand like have lawyer have lawyers like internally like software engineers they might have historically planned for a fiveweek sprint on a certain product or feature and now they're saying like let's ship it in a weekend or let's ship it in a week.
1:32:19
Are lawyers specifically in-house like are they thinking that way now?
1:32:24
Um and when are they not thinking that way just for kind of structural reasons?
1:32:29
in-house is absolutely thinking that way and and so are law firms, right?
1:32:34
Like AI is an existential opportunity and a threat to the current operating model.
1:32:38
I was with a law firm here in New York uh last week and one of their partners explained how the work that he typically does, he does in 130th of the time >> with no dependencies on associates. >> Wow.
1:32:53
>> That's his practice, right?
1:32:53
And so he has to figure out how do I now charge for this because working with a billable hour in his practice doesn't make sense >> and at the same time the biggest opportunity is perhaps in in-house where organizations like Salesforce Palato network etc are bringing in these tools inhouse to do more legal work >> and what's interesting about legal work is that the demand is effectively infinite.
1:33:17
If you could have legal intelligence review every contract, handle every claim, you know, fight every litigation, file every patent, like you would, >> right?
1:33:27
And you know, from an investment perspective, why not do a legal due diligence before you take an asset to IC?
1:33:33
The reason you don't do it today is because it's inex it's expensive.
1:33:37
>> How are you thinking about this?
1:33:37
How are you thinking about this arms race?
1:33:40
Because you have on one hand, it's like cheaper than ever to litigate something, but it's potentially cheaper to defend. >> Yeah. Yeah.
1:33:46
>> And and so and and there could be a lot more >> losses.
1:33:49
No, but at the same time it's if it's cheaper to defend, maybe a company's less likely to settle early, so there's less reward.
1:33:55
Like there's a bunch of these different right >> every like every judiciary is overflown by employee claims and you know people are using JPT to you know figure this out themselves and the companies are needing better tools to defend themselves at scale.
1:34:11
We work with some of the largest insurance companies in the world on settling litigation claims right and it's so interesting like airlines we work with Air Canada they are spending so much money in litigation claims with customers etc.
1:34:25
claims with customers etc. And I think you know if >> it's like if we develop bioweapons with AI like good news we can also develop cures right like it's sort of >> everything will just move faster and I think operating in that world what's so
1:34:44
interesting about being like this full AI native characteristic of a company is you can do that across every single part of the business and your operating model just has to be what a traditional software company did in a year we have to do in a quarter, right? Like four
1:34:57
Like four times this year, we have leveled up our endyear post for our revenue targets and now we are quintupling this year.
1:35:05
Like we are setting targets that by traditional software standards would have been deemed you know gravitydeying and insane. >> Yeah.
1:35:16
Uh talk a little bit more about the M&A strategy.
1:35:18
I feel like from your seat, I could imagine everything from like acquiring a small law firm in a niche area. >> No, no, no, no, no. We are not a law firm.
1:35:30
>> You're not going to be a law firm, but Okay.
1:35:32
So are you acquiring other other uh application layer companies or teams that are can are deeply in like the AI research or you're are you going to acquire a neocloud like like how how how narrow is your lens when you're looking for acquisitions? >> Yeah.
1:35:49
Well, first off, we have a big part of our EPD team in Stockholm and in Europe and what's so amazing about that is I think we're the number one employer in that in in our jurisdiction, right?
1:35:59
We get our sort of top top of the top of the mountain like we get the cream of the top.
1:36:04
All the best engineers want to come work here.
1:36:05
And >> legal tech is really hard to break into from a trust and commercial perspective. >> Yep. That makes sense.
1:36:13
>> But there are a lot of very technically talented teams who are working in the space. >> Yeah.
1:36:18
>> And so at Lora we have what we call uh our fruit salad product strategy. Mhm.
1:36:23
>> When alternatives are offering apples to apples, we are offering the apple, bananas, oranges, and kiwi fruit.
1:36:31
[laughter] And we want to have all of the functionality in one single space.
1:36:35
And what's so awesome about that for the lawyer is that they don't want to navigate 10 different apps.
1:36:39
They want to have Word, Outlook, there's document management system, and Lora.
1:36:44
And when all of the functionality gets sucked into one single place, the barrier to entry gets lower.
1:36:52
We're seeing this in a lot of the customers who are moving over to Legua from other legal AI platforms that they might have adoption, >> but they have very shallow adoption.
1:37:04
They haven't gotten sort of sort of second and third levels deeper where they're going, let's not just use this as an expensive chatbot.
1:37:10
Let's really think about how it's going to transform either our practice or the way that we operate in house.
1:37:17
>> Well, congratulations. >> Last question.
1:37:19
Just very curious right now if somebody like people are using just regular consumer chat apps as for for legal counsel.
1:37:33
I don't believe that that gives them sort of attorney uh client privilege. >> Yep.
1:37:39
>> Do you think that will be solved?
1:37:39
>> Do you think that will be solved? like will someone be able to make a you know consumer you know application that that allows them to have that experience is that >> that's a very interesting question that's a very interesting question the good thing is there are attorneys and
1:37:54
lawyers and judges much smarter than me who are going to determine whether or not that that's the case there's going to be litigation around that of course and we just get to play around in that space and I see Chase is about to come on here after me to give you one Bane story and he can he can fulfill the second half of it. Um, I met Chase at a
1:38:10
Um, I met Chase at a dinner in Paris um, with Chathan, our partner from Benchmark. >> Yeah.
1:38:19
>> Very late in the evening, Enriquei from Bane calls and he's like, "Hey, I'm going to crash your dinner."
1:38:24
And we get into this stratospheric wine competition between [laughter] Bane Capital and Benchmark, and I'll let Chase finish the rest of the story.
1:38:36
>> That's the best glasses land ever.
1:38:38
[laughter] That's hilarious.
1:38:40
>> Stratospheric wineoff. >> Wineoff.
1:38:42
Going glass for stratospheric w that that line was from one of our French attorney customers who said that that was the best dinner he ever attended. >> That's fantastic.
1:38:52
Well, thank >> we love we love you, Max.
1:38:53
It's always always >> always a great time. Come back soon. We'll talk. Thank you. See you later.
1:38:59
>> And uh we won't want to keep Chase waiting.
1:39:01
So, let's bring in Chase Lock Miller from Crusoe as soon as possible.
1:39:05
We got to get the other side of the story. this dinner in Paris.
1:39:07
We just heard about it from Max Fleor.
1:39:10
Was the [music] wine as good as they say?
1:39:15
[laughter] >> It was uh the wine was flowing that night.
1:39:18
We went a a significant amount of wine and uh I didn't see the prices, but I uh I think they were >> they were not cheap. >> Stratospheric.
1:39:29
>> What about the electricity?
1:39:29
Is the electricity flowing? Is the is the Yeah. Yeah. Are the chips flowing?
1:39:34
How is progress in building out the compute capacity that people need?
1:39:40
>> Yeah, the electrons are flowing and uh they're turning into tokens and uh you know helping helping accelerate this new era of AI abundance.
1:39:48
Um yeah I mean look I I think uh you know as as demand for AI infrastructure has grown and demand for power has grown um you know that there's been a significant amount of uh investment in real world uh you know power production capabilities and and facilities [clears throat] um that uh are are becoming you know real significant bottlenecks towards uh towards this buildout. Yeah.
1:40:12
Um and so you know each incremental gigawatt is getting increasingly uh more challenging.
1:40:18
Um now you know the positive side is you know that um I think a lot of the investments and the foresight that we had at Crusoe are uh you know paying dividends today and um if we look at you know all of the progress that's been made in you know the campus in Abalene, Texas like you know our our philosophy in sort of designing and building that campus was you know how do we build a a gigawatt scale computer?
1:40:41
How do we build a single facility that can act as one giant coherent cluster um that can that can train the next breakthrough foundational model that will leave to lead to a step function improvement in the model capabilities. Yeah.
1:40:56
>> Um that was like the that was the north star when we developed the campus and designed it.
1:41:00
>> Today we're seeing the fruits of those labor. >> Yeah.
1:41:03
And you had to go through what it was.
1:41:05
There was like a six-month period where it felt like there was a different article every single day about star.
1:41:08
If somebody sneezed at in Abalene, there was somebody that was going to write an article.
1:41:15
They're never going to be sneeze causes one second delay. [laughter] >> Delay.
1:41:22
>> But it feels like you guys have gotten through that.
1:41:23
And I I haven't I haven't seen a a front page article about some minute detail of the process in a while.
1:41:31
[laughter] Um, no, but you know what I was going to say is you know the the benefits of that is you know the first two buildings which were the initial contract that you know we did with Oracle and OpenAI um have led to the training of Astra um I don't know if you've had a chance to play around with but you know it's it's a it's a really phenomenal model.
1:41:50
>> Yeah know excited for our partners.
1:41:53
>> Yeah and Jensen had some nice words about it too. Yeah.
1:41:55
And the next the next phases are coming online with you know buildings three to eight um which you know is going to basically quadruple the compute capacity you know 3 to six are already online and uh seven and eight will be coming online before year end.
1:42:09
And um you know having uh having that full uh eight building compute capacity to train you know the next version uh you know the next incremental improvement in the model I think we'll see that function improvement in capabilities.
1:42:21
You started the company in 2018 going on almost a decade in business.
1:42:26
Um can you give me a sense of the progress from like the smallest project, the first project, how small was it in terms of megawws and where we are now in terms of scale because I feel like that that has been the biggest transition is that uh you you started with pretty small projects and now you're working on the biggest projects in the world. >> Sure.
1:42:50
So you know the the philosophy of the business you know from day one was taking this energy first approach to computing.
1:42:56
Um you know we named the company Crusoe after the character Robinson Crusoe who was stranded on a desert island and had to be innovative with his resources.
1:43:03
Uh >> you know in a stranded environment and you know we try to channel that same sense of innovation applied towards stranded energy and unlock stranded energy unlocking value and stranded energy with computing.
1:43:15
And so that led us to you know uh unique energy resources to power compute in early days and we were actually working on uh you know generating our own power with uh flared otherwise flared natural gas.
1:43:28
We were capturing this waste methane utilizing it to produce power and then powering these mobile and modular data centers.
1:43:36
Our first use case was was Bitcoin mining.
1:43:38
Um but you know we we sort of even at that founding of the company we had this ambition to build an AI cloud platform which today is you know where where where where Cruso's at is this vertically integrated energy first AI uh AI platform.
1:43:51
Um so the early days it was roughly 250 kilowatts was the first block that we did which was actually pretty big. >> Yeah.
1:44:00
Um the first AI data center um we're actually putting up in like a Crusoe Spark Museum that we're building.
1:44:08
Um and it was like it you can kind of think of it as like a single individual rack.
1:44:12
>> Uh I think it could power up to um up to 25 kilowatts.
1:44:16
Um so it was like higher density you know for that era.
1:44:18
Um and uh you know we we've since sort of evolved our platform quite a bit to you know gigawatt scale campuses at one end of the spectrum and you know we made uh you know we we've made an announcement you know quite a few announcements around um the Cruso Spark product which we believe is sort of the critical um aspect to to to really scaling inference compute infrastructure as demand for token scales.
1:44:43
You don't need a gigawatt scale computer.
1:44:46
computer. you need lots of smaller clusters of compute um to rapidly serve uh inference infrastructure and really dramatically reduce that that time to token >> and Spark gives us a ton of flexibility in terms of how we deploy inference
1:45:00
infrastructure where it goes um and then also just from a time to token uh it really provides us a lot of just in time solutions uh for delivering AI infrastructure for uh the innovators in the world >> it seems like uh like uh solar deployments keep beating expectations. We've seen this chart of the predictions
1:45:19
We've seen this chart of the predictions of where solar will go and then the the graph keeps going up and to the right.
1:45:25
Uh is where where are you seeing exciting movement in new energy coming online that might be suitable for that type of product the uh the Cruso Spark uh you know smaller amounts of energy required but unlocking new opportunities in in different locations.
1:45:45
Well, uh, you know, solar is definitely like a very compelling use case.
1:45:48
You know, we, uh, with our partners, Redwood Materials built the largest micro grid in the United States that was, uh, solar plus batteries.
1:45:56
And the batteries were actually taken out of mostly taken out of, uh, electric vehicles.
1:46:00
So, sort of a a second life use of these uh, lithium ion batteries.
1:46:05
Um, and you know that that AI those AI factories are uh powered 99% plus just by the sun, which is a pretty cool case. That's cool.
1:46:13
Um, you know, there's a lot of new energy technologies.
1:46:17
We're focused on, you know, helping catalyze and accelerate.
1:46:20
Um, you know, we had a big announcement with Alo, um, to bring to life the first SMR powered AI factory, uh, which we're planning to go live with, uh, by mid 2027.
1:46:30
Um, but, you know, what's unique about Spark is, you know, given the small modular form factor, there's so many different, you know, there's so many unique ways you can power it.
1:46:38
It can, you know, you can power it with like small gas generation things like reips and, you know, smaller gas turbines like aerodyivatives.
1:46:45
Um, you can also power it just in in you with with uh with grid power and uh you know there's a lot of while getting a gigawatt of power from the grid in a single location is quite challenging right now.
1:46:58
Um there's a lot of places where smaller pockets of capacity are available.
1:47:02
you know, think whatever 10 to, you know, 100 megawws um that can be ex accessed like way sooner um because of you know, uh transmission and distribution constraints um that are that are happening in the grid and like plugging into one node uh may actually help create quite a bit of uh balance in terms of uh you know the the load balancing that the uh utility operators are are needing to do.
1:47:24
And so, you know, it can actually help benefit the grid quite a bit because you're actually advertising more megawws over the same transmission and distribution infrastructure, which should actually bring down the cost for all local rate payers.
1:47:37
Um, you know, and you know, we think that's a an exciting proposition uh because you're shifting all of the work offsite uh and you're able to plug into a lot of these unique energy uh energy uh yeah available energy on on the grid. Yeah.
1:47:51
>> Yeah, it makes a lot of sense.
1:47:51
Uh talk about the the new round.
1:47:53
Yeah, you raised some more money. >> Um, we did.
1:47:56
Uh, so today we announced uh the closing of the uh series F uh at Cruso.
1:48:03
Um, it's >> who came in saw some heavy hitters. >> Oh yeah. >> Um, yeah. Never gets old.
1:48:13
>> Um, yeah. Never gets old. uh the uh you know the the series F Brown funding was co-led by uh a trades uh Valor Equity Partners and Mubata >> um and we had you know a number of uh you know a number of great supporting investors alongside it uh folks like TPG uh QIA uh founders fund um uh Radical
1:48:37
Ventures um >> you know it was a uh it was it was a great great list GIC was another great partner um So uh you know there were there were a number of great investors and you know we're really thrilled to have the support from um you know a number of uh leading uh you know longonies uh growth investors and and venture investors. So
1:48:56
So >> yeah that's amazing.
1:48:58
>> Longies [laughter] >> it's the only type of investor I like. >> Yeah. >> Uh thank you so much. Great to see you Chase. >> Have a great rest.
1:49:07
>> We'll talk to you soon. >> Talk soon. >> Goodbye.
1:49:08
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1:49:19
Up next, we have Justin Trunk from Decagon. >> He's back. >> Welcome to the show. Welcome back. How are you doing? It's >> been too long. >> Good. Good.
1:49:30
Yeah, it's good to see you guys again.
1:49:33
>> Where are you in the world?
1:49:33
You're expanding internationally.
1:49:34
Are you in America, Sa Paulo, Brazil?
1:49:38
>> I'm in uh I'm in Sa Paulo this week.
1:49:38
So quite the [clears throat] flight over here.
1:49:42
We're we're out here launching our uh Latam office.
1:49:45
So we're we're starting an office here in S Paulo. >> Okay.
1:49:49
>> Got a couple customers down here already like Marcato Libre.
1:49:50
So we really felt like things are moving pretty quickly. So got a team out here.
1:49:54
Now >> what is the key what what seats do you want to fill in that office?
1:49:58
Uh I mean obviously you need you know the general staff but uh is it about sales reps for deployed engineers?
1:50:05
like what what problems does it help to have boots on the ground effectively in the local uh community?
1:50:14
>> Yeah, it's mostly go to market.
1:50:14
I think uh obviously there's there's language considerations, right?
1:50:18
So anytime you go to different uh markets like it's both the product, right?
1:50:22
So we we deploy these voice agents.
1:50:23
So the voice has to be really good at you know Brazilian Portuguese but also our go to market teams are have to be on the ground and being in people's offices and so on.
1:50:31
So it's it's mostly just the go to market teams. >> Yeah.
1:50:35
What's happening with diffusion every time I have to be on a customer support line and I don't have speak and I'm not speaking to an an effortless you know agent that has all the capabilities that I would expect that I know are available.
1:50:49
I get a little bit angry at you and the other players in the space [laughter] because like why you move faster.
1:50:55
It's like I just know I know the technology is here.
1:50:57
Why do I need to sit on another phone tree and and you know like they that doesn't even do a good Yeah.
1:51:06
I just want to talk and I just feel like >> being able to effectively prompt to the outcome that you want is like so clearly here >> and and still it's like so many of these things are like what's your what's your address?
1:51:20
What's your this you know all this stuff it's like >> enough.
1:51:24
>> We're trying our best.
1:51:24
I mean I can tell you like what is the long pole in the tent?
1:51:28
tent? It's it roughly the um analogy we like to give is like us delivering an agent is a little bit like building a self-driving car where the car is now smart right like the models are really good like you guys have used the models
1:51:40
the brains of the car are good so it knows how to drive >> but when you arrive in one of these big let's say airlines or banks or um you know healthcare providers it's >> the map of the surrounding area is not drawn out yet and so drawing the map is usually the hard part. It's like you
1:51:52
It's like you someone has to make the jump between, you know, the the car being good, but then actually like drawing the map and figuring out where to go.
1:51:58
So, a lot of the time that we spend in these deployments uh is really making sure the map can be drawn out well and then improved upon over time.
1:52:05
And our job hopefully is to shrink that time over um you know more and more deployments and so that in the future every every single time you call there will be a good AI agent there that that can talk to you. >> Please.
1:52:17
Um, how do you think about how do you assess opportunities internationally?
1:52:22
I I would love just like lay the land of like the the core business, why you thought it was the right time to expand internationally and then I imagine that there's a at least a spreadsheet or some some prompt that you that you ran through some analysis that you did to land on Brazil, but uh what is your actual process for evaluating a new market to expand into?
1:52:46
Yeah, I mean international expansion is not like a novel thing, right?
1:52:47
So tons of countries have gone through it.
1:52:48
So we've been able to learn from, you know, what other people do and and usually most of the traction comes from, you know, small handful of countries. >> Okay.
1:52:56
>> Uh when we first started the company, we're mostly serving like the upper mid-market like technative companies.
1:53:02
And so uh that's where we started and then our first order of business was hey, we actually do think that we can, you know, our approach to to launching product will work in the big enterprise.
1:53:12
And so that was that was a lot of the big focus in the first year and a half.
1:53:15
And so you know now we've announced you know a lot of the big banks you know Deutsche Telecom um American Airlines, Delta Airlines.
1:53:22
So a lot of these big customers and from there we're thinking okay where what's the next frontier probably is international.
1:53:27
Um Europe was the first sort of pillar for us where we we launched the London office and we have customers in Germany and the UK and so on.
1:53:36
And then from there we were just thinking, okay, well the the two options for us honestly ended up being Australia and Brazil.
1:53:44
>> Um and it's kind of a mix of how quickly are people adopting tech.
1:53:47
What's the size of the market?
1:53:50
>> Can we actually serve those customers?
1:53:52
>> And uh we decided yes.
1:53:52
And so now we have you know a small pod in Australia and now launching in Brazil.
1:53:56
And I think for now that that is like a pretty good spread for us.
1:54:01
But um you know in the future we'll we'll probably look for you know what is the next frontier.
1:54:05
Is there an element where uh customer pull is really important?
1:54:09
Like Marcato Libre has a bunch of employees in the United States.
1:54:13
You probably meet them at conferences.
1:54:14
The conversation can start before you even open the office.
1:54:16
You it sounds like you already have a contract in place.
1:54:19
Uh but you're just seeing pull from a a certain big enterprise and anchor client and then uh that can justify going bigger. >> Yeah. Yeah.
1:54:29
I think that that is pretty correct, right?
1:54:31
It's like okay let's just get a feel for the poll first before we we deploy a bunch of resources.
1:54:37
Um the same happened in Europe with uh with DT where you know we we kind of originally started working with them when we were just had a team here in the US but then over time we realized oh wow >> people are moving pretty quickly we need to be on the ground and so that's that's what prompted us building a team out there. >> Yeah.
1:54:53
Uh what are you what are you tracking?
1:54:55
What uh how closely do you track the progress of the models versus the cost and the paro curve of the models?
1:55:02
Uh are are token costs falling fast enough?
1:55:06
Is it is it roughly perfectly on trend from what you've modeled? Is it faster?
1:55:10
What can you tell us about cost optimization once you get a system that's you know superhuman or, you know, at at high quality?
1:55:18
I imagine that you're not just uh upgrading to the latest Frontier model and just adding cost because some of the some of the models when they come out they're better but they're more expensive. >> Yeah.
1:55:29
Uh there's there's kind of two dimensions there.
1:55:30
So on the cost side and typically what you do is you first get your product working and then once it's working you realize that most of the model calls you do don't need the entire model because the model does a ton of stuff, right?
1:55:42
So you don't need it to >> compute math for you for example.
1:55:45
And so then the intuition is like, okay, well, over time.
1:55:50
>> Personally, I like to throw a millennium prize problem at a customer service agent every once in a while just to see if there's a shot.
1:55:55
But, uh, yes, I understand. [laughter] >> Yeah.
1:56:00
And so, um, yeah, so over time you want to shrink the models and then you then it's more of a question of like, okay, is that possible?
1:56:05
Can you take a smaller model and and fine-tune and post- train it to >> perform at the same level?
1:56:11
>> And so far, I would say in our use case, the answer has been yes, right?
1:56:13
the answer has been yes, right? There's a lot of these small tasks that are done inside the brain of the agent like you're choosing a topic or detecting for hallucinations or whatever >> and so you can use small models and specifically open source models to do those >> but when you're when you're launching new products and kind of trying new capabilities of course the frontier
1:56:30
makes sense and so those those two go hand inand >> and then for us uh latency also matters a lot so we we talk a lot about how you know you have to >> not just optimize cost like optimizing latency matters even more to us probably and so you know when we've on these >> optimizations, we're mostly >> seeing if we can get the latency down because if you're talking to a voice agent, it has to be super snappy. >> Yeah. >> Yeah.
1:56:51
>> And you know, those those two go hand in hand as well.
1:56:53
>> And is that the model or the chipset or both?
1:56:55
I I imagine that we're not quite in the age of collocation or like edge computing, but it feels like that's coming as well as a as a small 100 millisecond savings potentially.
1:57:07
>> It's mostly the model.
1:57:07
Most of the gains come from um you know, making the model smaller. >> Yeah. Okay.
1:57:12
Eventually, if the model's like so optimized, you could start looking at some of the other things.
1:57:16
But yeah, uh you know, >> so make the model really small, then you bake it onto silicon, then you put that silicon right in the in the city where the customer service is happening, something like that on the edge and then you're two milliseconds or something maybe. I don't know. Uh yeah. Uh very exciting though.
1:57:32
Thank you so much for hopping on the show. >> Great progress. >> Great progress. Congratulations. Talk to you soon. Cheers. Enjoy Brazil.
1:57:39
>> Let me tell you about Railway.
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1:57:46
Up next, you're the founder and CEO of Beacon and the VP of AI research with Beacon [music] Nylon and Leonard. Welcome to the show. How you guys doing? >> What's going on?
1:57:58
>> Hey guys, good to see you again.
1:58:00
>> Welcome back to the show. >> Happening.
1:58:02
uh uh I would love for you to start with just a re uh reintroduction on the strategy for the company for the firm and uh and sort of uh how it's been going since we last talked I think uh uh almost a year ago. Yeah. >> Yeah. Yeah. That's right. Yeah.
1:58:16
So, just a reminder, Beacon is a holding company.
1:58:21
We acquire great technology companies that have been around for decades that already serve real economy businesses.
1:58:28
think campgrounds to labor unions to youth sports leagues.
1:58:31
We take we take those businesses, pump them through our software factory and then make them AI native.
1:58:38
Uh the whole goal is to make the real economy as AI native as quickly as possible.
1:58:44
And the last time we talked, I spent time talking to you about our acquisition machine.
1:58:48
Uh at that time, you know, we were acquiring a business every 3 weeks or so.
1:58:52
Today, uh we're closing on a new business every 10 days. Whoa.
1:58:58
>> Um, and today really I'm excited to talk to you about our most important acquisition, I think, in Beacon's history, partnering with Leonard and the Haze Labs team. >> Yeah.
1:59:06
Uh, yeah, Leonard, give us a little bit of your background, what you built, and why you're excited to join. >> Totally. Totally.
1:59:12
Um, I don't know about most important acquisition today, but it's certainly an exciting acquisition for both sides, and hopefully we can um bring a bunch of the Haze technology and talents to the rest of Beacon's existing portfolio.
1:59:21
Um, so a bit of background on myself.
1:59:24
I'm Leonard, co-founder, CEO here at Hayes Labs.
1:59:25
here at Hayes Labs. Hayes was an AI safety company founded out of my research over the last five six years where we focused on red teaming guardrails observability and evals both for the frontier labs including open AAI and anthropic who are our first
1:59:38
customers actually but also for large enterprises think big banks fortune 500s uh insurance companies healthcare companies and so on and but what we realized >> safety is solved [laughter] is jobs finished we can we can move on to >> I'm going to go work on economy to you sports. [laughter]
1:59:57
[laughter] >> Well, safety is always an ongoing challenge.
2:00:01
I think as capabilities advance, you know, you always have to play catch up in some way.
2:00:05
Even though your normative declarations of what AI should and should not do or can be set in stone, the way in which you operationalize the definition of what it means to be safe or not safe changes as the capabilities advance.
2:00:16
Um, and in so far as joining Beacon goes, I think uh bringing AI to the real economy is a unequivocally good thing and responsible thing to do if you're an AI technologist.
2:00:27
But also from the perspective of the alignment conversation and debate we've been having over the last couple of days.
2:00:31
Um, one thing we've thought a lot about at Hayes is whose values should AI models actually be aligned to?
2:00:38
And you can take the perspective if you're anthropic or open AI that you have the best control and that you have the best wisdom around what the values what values should be baked into the models.
2:00:47
But it is our sense as Hazen Beacon that we should try and make contact with reality in particular those that have been historically undeserved by Silicon Valley technologists like businesses in the real economy uh in order to align our values to those businesses and the values of their customers.
2:01:01
And that's part of what gets us super amped to join the Beacon team. >> Very cool.
2:01:06
Uh >> yeah, just to give you guys uh just to add to that a little bit on the the safety conversation.
2:01:13
>> Everyone everyone knows uh the real economies behind on AI adoption.
2:01:16
There's many reasons for that.
2:01:20
>> You know, the ramp data from about a quarter ago showed that SMBs are only 20% adopting AI versus like 85% for the Fortune 500.
2:01:30
>> We started Beacon uh to address that gap.
2:01:32
But but really Leonard and team are going to play a key role in that.
2:01:35
the reason why adoption is so low in SMBs.
2:01:39
Some of it's a question of access, but really as we as we spend time with our 22,000 customers, it's a question of trust [clears throat] first and foremost.
2:01:47
We the real economy will not adopt AI if they think it's going to run rampant and um screw up a bunch of their own relationships with their customers.
2:01:57
So Leonard and his team, part of why we wanted to bring them in and why Leonard's leading this important function for us is so that we can ensure for our end customers that uh when they deploy AI through one of our pieces of software, it's it's done in, you know, kind of the safest way possible. >> Yeah. >> Yeah. >> Yeah.
2:02:16
Just I like to say that Deacon has the trust in the customer relationships already.
2:02:20
I mean, these businesses, the real economy in the world depends on these businesses.
2:02:24
Um, and I like to say that Hayes Hayes builds AI that anybody can depend on.
2:02:28
So now you've got both parts of the equation.
2:02:30
You've got AI the business can depend on and the real world is depending on the businesses depending on this AI.
2:02:35
So I think it's a very natural natural fit.
2:02:38
>> Uh, ground ground this for me.
2:02:38
What are where where's AI been most useful in uh, something like campground operations since I know you guys have acquired >> uh, some campgrounds.
2:02:48
And it's so it's so funny to it still so funny to me that um >> you know as you guys get bigger there's definitely going to be some articles of like this AI company is taking over youth sports leagues and campgrounds.
2:02:59
Um I'm very excited about it.
2:03:02
We were just on we were just on with Jesse and I was telling him I'm frustrated that that I still will end up on a customer service call for some service and I'm on some legacy system that has no AI at all.
2:03:14
that doesn't have any ability to reason or help me get uh things done.
2:03:19
>> Uh I can imagine a lot of use cases at at like in the campgrounds cont [laughter] >> and then you're just sitting there.
2:03:30
No, that's a great great point.
2:03:32
Uh look, we are believers in a AI abundance.
2:03:34
The thing that's exciting, especially for the real economy, is we can help them solve problems that before they were not able to solve.
2:03:44
So on the campground side, if you put yourself in the shoes of one of the 18,000 private campground owners across North America, you're spending 40% of your days doing payroll, HR, bunch of compliance tasks, using a spreadsheet to figure out which camper needs to be assigned to which uh spot in the campground.
2:04:03
Um, today we have built tools within the software they already use to uh match guests to to campground spots to do dynamic pricing to make sure that they're pricing appropriately for season to load balance staffing uh for when campers are actually going to be there.
2:04:21
So that is you know as to use a term Leonard just used unequivocally good for the campground owner but also we think that's how AI abundance actually translates into the real economy.
2:04:32
It's how do we unlock more growth for the real business?
2:04:34
Um, you know, one one thing that people always ask me, okay, you you guys are just going to use AI to to uh take costs out or reduce headcount.
2:04:42
Across all of our businesses, we're actually up headcount.
2:04:47
So, we found the opposite.
2:04:47
As we've delivered more AI, our customers >> Yeah. >> Yeah.
2:04:52
There's been a bunch of reporting on this in the Economist and the Wall Street Journal about like the AI actually driving increased hiring as growth comes in, which is fascinating.
2:05:00
How are you guys uh do you guys imagine you know doesn't feel like now is the right moment but 5 years from now like you know robotics being a big part of the the strategy you'll have all these existing businesses and as different form factors get better you'll be pretty primed to to bring in these new form factors.
2:05:20
>> Yeah I'll start >> part of it go for it. >> Yeah. Yeah.
2:05:23
We we actually have businesses today that serve various industrial uh markets.
2:05:27
Um, so think about um software that helps large construction sites manage their their tool inventory, software that helps uh oil rigs uh stay safe.
2:05:38
Um, and increasingly we're seeing this marriage of AI native software with hardware like GPS devices, etc.
2:05:47
to be able to increase uh the surface area of what that piece of software can do for the end user.
2:05:53
you know, one of our customers, which I I can't name, which is like a a Fortune 500 construction firm, they're saving millions of dollars today on on uh tool supply because, you know, we we actually help them manage these industrial tools that are being used for the data center buildout across the economy.
2:06:10
In the old world before we applied AI to help them match tool to job site appropriately with GPS um they would o a construction manager or project manager at site would overallocate uh and over buy tools uh basically to make sure that they're not going to be short.
2:06:27
So this was a huge problem for for the the company.
2:06:30
They worked with our team our four deployed engineers went down to Houston and helped them.
2:06:35
Uh we built a new module for them which basically AI matches tools to job site.
2:06:39
Then we put in GPS trackers to make sure the right tool got to the right site.
2:06:44
Leonard, sorry, you were going to say something too.
2:06:49
>> Yeah, I mean I think you guys are being super precious about where all the technology is headed.
2:06:51
Certainly robotics is going to mature quite a bit in the next 5 years.
2:06:54
And I think robotics or not, I think there's going to be a huge category of value can deliver to our companies by essentially being able to dispatch AI employees or digital employees or whatever you want to call it at will.
2:07:05
Um, and so it could be something as simple as an AI SDR helping you find leads um, from your existing network.
2:07:12
It could be something as simple as an AI support engineer helping you deal with tickets and bug bash.
2:07:15
But I think there will be this huge supply of intelligence at your disposal if you're an owner operator for you to go and lever up your existing strategy team uh, ambitions at your company.
2:07:26
I also do think separate from just digital employees, Beacon uh is in a very unique position to go after what I would describe as world models of companies or company world models, i. e.
2:07:38
models that can help the existing owner operator as a true thought partner and strategic decision maker think about what's going to happen next in their business and anticipate the best choice and action they should take to better run their business.
2:07:50
So I think there's this pure question of can you deploy more intelligence to lever up existing objectives.
2:07:55
Then there's this separate technical challenge of can you actually help business owner figure out what objective to go after in the first place. >> Yeah.
2:08:03
Well, thank you so much for coming on the show.
2:08:04
Congratulations Deal and we'll talk to you soon. >> Very cool, guys. >> Have a good one. Goodbye. >> Cheers. >> Thanks, guys.
2:08:09
>> Let me tell you about the New York Stock Exchange.
2:08:11
Want to change the world?
2:08:12
Raise capital at the New York Stock Exchange.
2:08:14
We got Joe Eisenthal here live in the TVP and Ultradome.
2:08:19
>> I can't believe I'm here.
2:08:19
I can't believe I'm here. >> I know.
2:08:21
Cuz you've been here so much.
2:08:23
Well, I've like been here.
2:08:25
so many times and I you know in my dreams I wonder what the studio is like and will I ever make it to the temple I ever see the gong ring the gong hit the gong give us some excuse what 10 years by one of your producers as you can bases point right now >> yes that's what we're hitting it for smack it >> oh you got to go way harder you got to really like it's a baseball bat >> I was told it was >> like you're swinging for the fence There we go. >> I'm done now, right? I can leave.
2:09:00
The whole point was just to bring me into uh to hit the gone.
2:09:04
What else do I have yet to achieve now in my life?
2:09:06
What summits what summits yet to climb? >> Yeah.
2:09:09
What actually brought you to LA?
2:09:11
>> We Oh, funny you should ask.
2:09:11
[laughter] We are doing a live show tonight at the Vermont Theater in Hollywood where we are going to attempt to do a survey of what is this thing called the LA Economy.
2:09:25
So we're going to be talking to some of the industrial guys.
2:09:26
Chris Power from Adrian is going to be on.
2:09:32
>> Um Tom Mueller, the first space Impulse space is going to be on.
2:09:36
>> We have some of our favorite internet characters.
2:09:38
Taylor Loren, Rachel Carton is going to be there.
2:09:41
Um, so it should be a really fun night.
2:09:44
I have no idea what to expect.
2:09:45
I don't know anything about this town.
2:09:46
Maybe >> survey the LA economy, but you've picked out like some of the bright like only bright [laughter] only bright points to be honest. >> No, I know.
2:09:55
It's like it's like >> you're negging your own city like that.
2:09:59
>> Oh, I I mean the city's the city's a disaster.
2:10:01
I mean it's uh >> they didn't even hold on to a movie studio [laughter] leaving >> but then you get this but then someone gets to take this >> but yeah the bright spot is like the individual creators are doing well.
2:10:13
There's cool stuff in industrials and space >> but uh the whole long LA movement like fizzled out right before you got the sort of >> I'm super long LA. [laughter] Absolutely.
2:10:24
You know I was just going to say that. No, I was just talking. >> He just gets it. >> I'm super warm. Yeah, it's the weather.
2:10:31
And >> what's there to be what's there to be optimistic about?
2:10:36
[laughter] >> Look, the thing that will will never cease to mystify me, right?
2:10:40
So, Americans over time, they migrated westward, etc.
2:10:44
And no offense to them, I'm sure they're lovely people.
2:10:47
I'm like, wait, you guys stopped in Nebraska and you could have like you could have like gone on your wagon for like another, you know, 72 hours.
2:10:54
is right there >> or and it's like what?
2:10:58
And I like what in my like in my trying to backfill American history, it's like how did we all not just come to LA right away?
2:11:06
And I do not believe regardless of what happens with Hollywood that there will ever be a time where people just do not want to live in this climate by the beach and they'll find an industry for them.
2:11:19
Yeah, it is crazy that California I mean we got three coastal cities, San Francisco, LA, San Diego, but it's always shocked me that if you drive >> completely ignoring what >> the every other >> No, no.
2:11:31
If you drive halfway between LA and and San Francisco, there is not a metropolis with an international airport there.
2:11:37
Like you go you go below uh like Marin and or uh uh where Laguna Seiko, that's the only place. Monterey.
2:11:44
Yeah, you go below Monteray and then and then you get into beautiful areas, but it's mostly camping and and there was never like an enforced, you know, metropolis that built up.
2:11:54
>> No, it's kind of strange.
2:11:54
You know, a couple years ago, a good friend and I decided to we had just like never been driven the Pacific Coast Highway.
2:12:00
So, we're like, let's drive from San Francisco down to um what's the place down there where they have the co the town where they have Coachella, Palm Springs.
2:12:11
And we did and it was beautiful.
2:12:13
>> Wait, you hit Coachella or you just >> No, no, no.
2:12:14
just I just wanted to put that down and it was a beautiful drive but at some point I have to admit it is very beautiful.
2:12:20
I have to admit it's like oh there is another beautiful cove >> and so I [laughter] was like I'm getting a little bored of this you know oh there's another beautiful co >> it also takes so much longer than driving.
2:12:31
>> So then you then we had the thought it was somewhere right around where the Hurst mansion is.
2:12:34
like why do we drive inward because no one sees like so then we like went through like Fresno and like miles and miles of almond farms. I loved it.
2:12:46
So now I'm actually like yes there should be another Yeah.
2:12:49
So it's like of course yes there should be another megalopouloolis somewhere like on the coast but also I think that like if someone visiting LA >> at one point you should do the inward drive and see where they make all the almonds cuz it's amazing country out there.
2:13:04
That's how I used to get back and forth from LA to San Francisco. >> LA's in a bad spot.
2:13:06
[laughter] >> LA is in a bad bad spot.
2:13:10
You know, I know I'm I'm generally I'm generally the the the point of optimism is uh is the weather.
2:13:18
That's been the the durable point.
2:13:20
But but the weather can get a town through >> some bad eras, right?
2:13:24
Because >> sure, >> if everything if everything is actually headed the wrong direction, >> but the weather is simply so good that when you >> It'll be fine. It'll get you through. I'm very bullish.
2:13:35
I'm like, it's >> move here. >> Yeah.
2:13:39
I mean, like look, like when like when Detroit got >> hollowed out after like the shrinking of the auto industry there, etc.
2:13:45
It's like what was keeping people, you know, they didn't have the weather. Oh, true.
2:13:50
>> You know, and so like >> you guys have the weather, it'll be fine. Wait a couple years. It'll be fine.
2:13:56
>> Yeah, it it's it'll be fine. I'm good. We're going to find it. [laughter] Yeah.
2:14:00
>> I'm waiting for the I'm I'm waiting for whatever >> industry can bring great opportunity to LA again, which it just doesn't feel like >> like I moved here after college and I thought it was great because it was much more >> affordable than New York.
2:14:15
>> affordable than New York. I'd have friends visit from New York and they'd be like you get like I this crazy loft for what would be you know >> see in New York I believe there's this perpetual conversation that has like should I move to California these days
2:14:29
it's more SF but for many years the discourse among people in New York is like should I move to LA you know like it seems pretty nice out there I get the impression and maybe you guys could tell me if I'm wrong like I feel like once you get here you don't have the reverse conversation like Oh, should I move to New York? I feel like it's like, oh, the
2:14:47
I feel like it's like, oh, the >> I just kind of I was I would I've I've felt that way.
2:14:50
I felt that way in >> unique in that.
2:14:54
>> But but I but but spiritually I've always felt at home in New York, even though I've never lived there full time.
2:15:00
>> Well, that's the lovely part of New York.
2:15:02
You are spiritually at home in New York.
2:15:04
>> You don't think converting the Paramount lot into a data center will keep people here?
2:15:07
That seems like a lot of opportunity. >> Yeah.
2:15:09
I mean, it's worth a shot.
2:15:09
I mean look if look the question if there is a new industry in America that creates jobs >> then some of them will be in LA.
2:15:18
I think the question is it's not in LA.
2:15:20
Will there ever be another industry in America that creates jobs in large scale? >> Yeah.
2:15:28
>> If there is one LA will be fine.
2:15:28
If there isn't one then it's not just going to be an LA problem.
2:15:34
>> Older people elderly care healthcare hiring. >> Yeah. Right.
2:15:37
But it's not just going to be an LA problem.
2:15:38
Like if that's the issue, if it's like we can't think of the industry that's going to then like I guarantee it's uh >> not just an LA problem. >> Yeah. Yeah.
2:15:47
Uh what uh what what what do you think of the the the latest in the AI data center discourse debate?
2:15:53
It felt like we were it felt like we were grinding towards a crescendo there and then we just took a hard left turn into AI risk X risk. >> I think so too.
2:16:03
I think that actually >> it's almost like it was coordinated by powerful shadowy organizations.
2:16:09
[laughter] >> That's Ian Bremer's take.
2:16:10
Ian Bremer's take is actually that the X-risk debate is to distract everyone problems.
2:16:14
Well, not not just data centers like you know brain rot and slop and like all the other complaints of people job displacement.
2:16:22
And he's like as that the AI lab leaders he in his view I don't know if I fully agree with this but in his view he says I uh uh like there's nothing an AI lab leader loves more than talking about X- risk. It's pure upside.
2:16:37
>> Well I would say two things.
2:16:37
So one is it already feels like if you're sort of a politician and you're still talking about data centers like bro that was a month ago like we've like moved on to model risk and stuff like that.
2:16:47
So it does feel like actually very quickly the data center conversation disappeared among political discourse.
2:16:54
My cynical version of the Ian Bremer take however is slightly different but maybe it converges on the same thing which is that actually um you know because before data centers and before the X-risk debate it was the job loss debate right and so this question is like oh will AI wipe out 50 to 100% or even 10% of white collar jobs and the you know if you read the opeds from the uh you know the Demetab base of the world.
2:17:26
This is what they were talking about.
2:17:27
My cynical take at the time of those was >> they're very concerned about X- risk.
2:17:35
>> What is something that we could talk about that would distract from what would not distract from it?
2:17:39
What is a way that we can sound the or what is the way that we can sound the alarm about AI without sounding like a complete bunch of loons? Totally.
2:17:49
Well, let's talk about um job loss because that feels like >> because certainly we can't get we can't get an AI doomer on Joe Rogan.
2:17:55
They'll never go through that.
2:17:58
So, let's talk about jobs because we can have that conversation.
2:18:02
>> And also job loss is the type of problem that like the three of us could come up with theoretical answers.
2:18:07
I always say like maybe 10% of open AI gets into a um you know a national fund. >> Exactly. Exactly. Solutions. Autonomous will.
2:18:18
Well, it's also it's also the another way to think about it.
2:18:19
You could tell somebody like an asteroid is going to hit the earth in 2050 and people would still go to earth work tomorrow. >> That's totally true.
2:18:28
>> But if you were like really like if you're like sitting there a lab and you have like these really deep intuitions and you've been reading like Boston for 20 years, what are you concerned about?
2:18:37
You're concerned about the X risk.
2:18:37
How do you get people to just first of all >> take the idea that AI risk is a big deal or AI is real or AI is real?
2:18:44
Let's start with the job loss conversation. It feels tractable.
2:18:48
It feels theoretically solvable. Oh, we need UBI.
2:18:51
And so my cynical take was that the only reason or the primary reason they talked so much about the job law stuff is because it was a wayin to warn people about AI that didn't make them sound like sci-fi.
2:19:07
>> But that that feels like that backfired because we're sitting here and there hasn't been massive AI job loss.
2:19:11
And so, yeah, that's true.
2:19:13
It's it's easy for people to be like, "These were the people that were telling us that there was going to be 25% unemployment and that hasn't happened."
2:19:19
So, they're saying 10% chance like I I I'm betting against. >> Yeah.
2:19:24
There's this weird thing going on.
2:19:25
I certainly think this is true, which is I don't know.
2:19:28
Do you see these people as like top ranked AI forecaster, right?
2:19:30
Or like capabilities forecaster.
2:19:33
And many of them do have like pretty good track records >> except on the question of what will be the impact of that. >> They're all internal. They're all internally.
2:19:42
It's like, yes, I I I I was able to predict model progress by the amount of compute that was built and also, wow, he also predicted the number of chips that were going to be bought.
2:19:53
He also bu predicted the number of data centers that were going to be built.
2:19:54
And it's like those are all downstream of the exact same line.
2:19:57
You're just extrapolating things that are directly correlated, >> except the one thing that no one has had any good intuitions on.
2:20:03
It's like when are we just going to feel this in our day-to-day life?
2:20:08
And it's pretty weird now that the conversation has evolved to like the ex-risk conversation >> because it's like you step outside.
2:20:16
It's like life feels really normal, you know.
2:20:20
I was like talking last night.
2:20:20
We were like talking to like say uh we're at this conference of like financial advisors etc.
2:20:25
And it's like there's this surreal thing because I like when I stare at my phone it's you know >> well a lot of those financial advisor they talk about AGI all the time.
2:20:33
Adjust adjusted gross income.
2:20:37
>> Adjusted gross income.
2:20:37
that's what they're focused on.
2:20:39
>> But, you know, it's like, well, AI can help you like um this AI tool helps your clients with tax loss harvesting, etc. , which is great.
2:20:49
I love tax laws harvesting, but it's like, wow, this could not be a more different tax loss harvesting.
2:20:58
This conversation cannot feel more different from like the types of conversations about AI that like I read on my like >> or or the or the the dis the disconnect honestly between like the the discourse and then like dream forces happening [laughter] like it's like yeah like
2:21:14
there's there's there's big problems that we need to be talking about like we got to be talking about this but in the meantime >> no I really like >> here's another thing here's another thing so I was thinking uh growing up in the Bay Area I distinctly remember the Iraq war protests. >> Yes. >> Yes.
2:21:30
>> Now, I just looked it up.
2:21:30
There was 200,000 people roughly in the streets like marching. >> Yeah.
2:21:36
>> And there there hasn't even been there hasn't even been a 10,000 person AI protest.
2:21:43
>> You want to hear a funny story?
2:21:43
So, I was at uh University of Texas Austin.
2:21:44
I was a young hippie and I attended some anti- Iraq war marches and there was this guy at the front.
2:21:54
>> There was this guy at the front.
2:21:54
Oh, I was I was I was in the crowd, too.
2:21:57
>> There was this guy at the front of the crowd who would regularly show up and he had this bullhorn and he would captivate the crowd and he would look he would point up at a nearby office building and he would say, "Don't think we can't see you.
2:22:10
Um, you know, Gmen up there spying us and everything."
2:22:12
And then everyone would like crane their head. It was like, "Oh, yeah.
2:22:16
I think I see someone in office." That was Alex Jones.
2:22:17
That was that person [laughter] That person was like the guy.
2:22:22
And so like the le and so the least surpris like this guy who just like got us all captivated in the pro in during the protest who would be like and everyone was like yeah I think I do see someone up there like that was Alex >> he just had a natural talent for it gifted >> that's remarkable wow wow that's a that's crazy I mean yeah this that's like when we yeah there's some John Kuryaku you know this guy who shows in weird places.
2:22:53
I think he was like a school teacher. That was a wild story.
2:22:56
The these like uh you know closing sliding doors moments in history. This is one of them.
2:23:02
>> No, it's like he was just a local guy that we all knew back then when we were in college.
2:23:08
>> Okay, back to the back to data centers. Back to Xrisk.
2:23:10
So, so conversations getting m uh there's one scenario where X-risk is the thing that does move the needle on the protest.
2:23:18
needle on the protest. you go from 10,000 to 100,000 legislation gets written and it builds on a lot of the work that's been worked on on the data center stuff and if you read the AI safety crowd a lot of them are like yeah we actually would love a slowdown in chip production slowdown of data centers that would actually be pretty
2:23:34
satisfactory because one of the prerequisites for nefarious ASI is just a lot of comput we we we're not worried about the god model emerging in on a desktop computer we just don't happen so >> uh AOC was recently on camera talking about I think you called her response like word salad >> but we have the technology to turn word salad into ironclad legislation. >> So new salad. >> So new salad. >> Yes.
2:24:03
So so take us through like like like is there is the is the word salidification of the AI discourse actually a problem? >> Wow.
2:24:10
That you know what is that's a really good question.
2:24:13
I asked a version of this question to someone several months ago who is like in the real like safety camp Yeah. before it became cool.
2:24:21
And I was like, why do you guys just join up with the anti-data center people? Right.
2:24:25
>> That's a great question.
2:24:26
>> I was just like, you know, I understand it's like they don't have the same like sort of understanding like they don't the shape of the risk there.
2:24:32
Why do you just join up with them? >> Yeah.
2:24:35
>> And I do think that like with, you know, >> people who have sharpened their blade for 10 years and the less wrong forums, they cannot do that thing of like, yes, but they're wrong.
2:24:45
you know, oh yes, yes, aligning with the anti-data center people would align with me. Perfect.
2:24:50
But they're wrong about the water cons.
2:24:52
And I cannot bring myself to align with them.
2:24:56
Not because it wouldn't be useful, but because I can't bring myself to be on the same side as like someone who slightly is factually in disagreement with >> it does feel like there's the beginning of that horseshoe coming together with Steve Bannon and uh Bernie Sanders.
2:25:11
Steve has just been like anti- tech, anti- Facebook, anti, you know, control and like big [snorts] company.
2:25:17
And so there's more there.
2:25:19
But I agree it's even harder for the AI safety camp.
2:25:21
But it feels like the Nate Suarez on Tucker Carlson Daniel on on Joe Rogan are like there might have been an update to the strategy.
2:25:32
I think there has been and um I think anyone who expects AI politics to map cleanly to some like left right thing is like delusional.
2:25:43
So like I guess all right Bernie became the first like major elected politician to like join the pause cause etc.
2:25:48
And so then people like oh anti- AI is going to be a left thing.
2:25:53
But you're absolutely right.
2:25:55
there is not going to be a left first of all there's not an going to be a left position sure to AI because there's a million different angles but also anyone who thinks that it's going to split between like some Democrat Republican thing you know we had um >> Kathy Hokll on the podcast and she was
2:26:12
like defending the data center one-year moratorum in New York and I think at that point like literally it was so quick because at that point then people were like well look um okay New York is going miss out on all of these uh companies that are, you know, bringing in tax revenue, etc. So, this is why
2:26:29
So, this is why Texas is going to get it.
2:26:31
And then like a week later, Governor Abbott, he didn't, it wasn't a moratorum, but then he announced like a higher bar that the data centers are going to have to clear in order to get built there.
2:26:42
So even whether we're talking about model regulation, whether we're talking about building of data centers, this idea that it's going to map cleanly onto some Democrat Republican thing, I think is like delusional.
2:26:55
>> How do you think people break on should this be a federal or states issue?
2:26:59
Because there's a world where, you know, if a particular state is like, "Yeah, we we actually love this."
2:27:04
There's I I I'm struggling to see a negative externality of a data center in a particular state.
2:27:10
If everyone there is happy, maybe they should maybe it should be state-by-st state regulation.
2:27:13
At the same time, it's such a national discourse issue that having a clarifying bill for like yes, we are only building clean data centers or there's some emission standard.
2:27:22
Maybe that makes sense, but how have you seen it puzzled around?
2:27:27
No, look, I think most people regardless of where you like fall on all of these questions probably think that like some state patchwork of state laws is like not a great way to go about doing any of this.
2:27:40
But, you know, outside data centers I thought was really interesting.
2:27:43
I guess it was like um just last time is fine.
2:27:45
You know, Chris Lean from OpenAI and in that thing you spelled out like we support this Massachusetts bill now, we support this California bill now, etc. That's a pivot.
2:27:55
Yeah, totally >> that's a pivot.
2:27:56
And so like I'm sure >> not the worst pivot. Nobody loves a pivot.
2:28:01
>> But I thought, you know, it was really interesting because in as recently as last year, another fellow we had on the podcast like Alex Boris was like was was uh was enemy number one and his bill that he had pushed in the state assembly was like pretty straightforward.
2:28:15
If you're above a certain company and you have some quote incident, you have to report it and pay a fine, etc.
2:28:19
That kind of seems like a small potatoes regulation compared to what we could get at this point.
2:28:26
I doubt again like in the AI industry or outside the industry anyone particularly loves the idea of like this, you know, the statebystate rules, but it does feel like to a lot of people, well, this is the least worst possible.
2:28:40
>> The best part about the state-by-st state rules is that you have you it sets up the AGI dunk, which is like, oh, if your models are so po so powerful, it shouldn't be hard to comply with all the rules state by state.
2:28:49
Yeah, it's a mess and you have to and you have to serve 50 different versions of chatbt, but like go for it.
2:28:55
Just have your model do it.
2:28:57
>> Well, this is, you know, the other paradox.
2:28:58
Oh, you think your model isn't going to like go kill people or uh whatever?
2:29:02
Just tell the AGI not to do that.
2:29:04
If it's smart, have the AGI train, right?
2:29:07
Like there's like all these >> Yeah. Yeah.
2:29:08
People apply to the distillation thing, too.
2:29:10
>> I mean, this is smart, why can't you stop?
2:29:12
>> Yeah, you're so smart, right?
2:29:12
But this is like this industry has a not only made for thought experiments.
2:29:19
>> The thought experiments have been around probably since the 1950s and the version of sci-fi novels and asimov etc.
2:29:23
And so the whole thing is built on thought experiments and so forth.
2:29:28
So there were thought experiments before there was something we would call an AI industry >> and you just literally take them in any direction and there's like >> on the opposite end of thought experiment is like hard reality rate hikes.
2:29:44
>> Um do you think the AI community is digesting what's going on with the Fed funds rate?
2:29:49
What the outlook is on interest rates like >> No. [laughter] No.
2:29:51
And I also like I would be you know and I would be very >> No. No.
2:29:56
It's just it is a very different world because like because like like tech companies that have never raised debt, have never raised money at all are doing it and like they will be affected by this and probably more so in the future.
2:30:07
So yeah what's >> it will not only be affected but I think by and large if you sort of like assume the growth rates that these companies are seeing if you sort of like do the math on like what okay financing building a data center acquiring the chips >> I don't think like 25 basis points 50 basis points they just don't move the dial yet.
2:30:29
Yeah, I think Sarah Frier said like, "Yeah, she bought all this compute and it like trades in the market."
2:30:33
Like, >> I mean, there's a long So, it's funny. Yeah.
2:30:36
And there's, you know, there's actually a funny amount of academic literature on whether any company period cares about interest rates.
2:30:43
So, this is actually an empirical thing that's been tested, which is like, >> have there ever been an example of a company that actually like changed some policy choice because of something the Fed did?
2:30:57
And it's like surprisingly rare these rare there are so many bigger questions that usually okay here's a board meeting and we're deciding whether we're going to make some investment and it's very rare that the decision oh is the tenure at 6% right now or is it 6. 5% right now? Is the short end at 4. 7% or is it five?
2:31:17
There are very few corporate decisions in the history of business where that turned out to be the deciding factor.
2:31:24
Now if we're talking maybe strictly real estate where there's like a very like okay these are going to be our cap rates etc.
2:31:30
Sure that may be but by and large it is a huge open question about whether these marginal moves anything have any history of affecting corporate behavior or not.
2:31:42
Can you reflect on Worsh and how you like how is he different not even in the strategy?
2:31:50
We know the rates are going up but like aesthetically the way he communicates the the the the dynamic between him and other partners like like how does he feel?
2:31:58
He's just at the start but like what what is his legacy building towards here? Like what's the purpose?
2:32:04
purpose? You know, I think there is this view there is certainly a view that wars represents some sort of like very 90 degree turn from like the three predecessors he had or 180 I don't know Powell um Yellen and Bernani >> in the specific sense they were more well Paulo was a lawyer but still more of like but still like an internalized academic macro for sure but the main
2:32:28
thing that they had was like they communicated a lot and they brought starting under Bernenki there were a number of um I guess I would call them monetary policy innovations um the the press conference there's not a history of that before Bernanki the so-called dot plots where the members of the FOMC write down where they expect growth on >> Bernani got the press conference idea
2:32:49
from basketball >> I probably from basketball and it was built upon but I think there is like look like most of the history of central banking probably looks much more like worsh like they didn't used to talk so much >> and so like I am of view that basically like you know we could go if you go back to the Greenspan era he would the word the famous word to describe his style of communication was nomic right and he
2:33:16
didn't say many words or if he did say a lot of words no one understood what he was talking about there was a long tradition of essentially like opacity in one way or another at the fed sure >> and so like if like I to some extent like you know people's like oh it's so getting like oh these the dots do not have some long intellectual tradition at the Fed. If they completely got rid of
2:33:41
the Fed. If they completely got rid of the dots, if they completely got rid of regular press conferences, which my gut is that Worsh would like to do because he doesn't really say anything at most of his press conferences, we would not be ripping up some hundreds of years of like no, we were ripping up presidents
2:33:58
since 2008 and some of the or 2009 and some of this stuff made a lot of sense coming out of the great financial crisis >> because it was a Fed crisis like it was a crisis for them and they were >> they had a look they had a very specific challenge 2000 which was that inflation was very low. They had cut rates to
2:34:15
They had cut rates to zero.
2:34:18
>> If you had plugged the economic conditions of the Taylor rule into the some sort of like rule, it would have said like you have to cut rates to neg five. >> Yeah. >> They can't do that.
2:34:26
I think a lot of things break when you have negative interest rates.
2:34:30
So then they're like, well, how can we be further dovish once we hit the zero lower bound?
2:34:34
It's like, okay, we're going to do this by talking more about our commitment to lowering rates and so forth.
2:34:39
So a lot of these things made a certain intuitive sense under a set of macro conditions in which the traditional tools of monetary policy were not workable because you just couldn't cut rates any further.
2:34:54
>> Yeah, >> it's 2026 now a very different set of problems etc.
2:34:58
>> So if you would say look under these conditions we do not have the same problems that we had when these things made a lot of sense.
2:35:03
So we should get rid of them.
2:35:04
I think there are a lot of people who would agree.
2:35:06
people who would agree. What the one thing I will say that I like the headscratcher still is that like on some level you know he used uh in his first or second press conference worse used this phrase we would like to play we
2:35:23
would like to have market participants play the ball and not the referee the referee being the Fed and that sounds great we love that idea play the ball and not the referee unfortunately and where I would say like in the sort of government bond market the the Fed is the wall, right? We're all trying to
2:35:37
We're all trying to guess where this at, right?
2:35:39
[laughter] So, it's like, >> let's talk let's talk for a second.
2:35:44
Let's imagine you're in a two-year uh government bond, right?
2:35:45
That two-year government bond is going to the correct pricing of that bond is going to be like where the Fed sets rates over the next two years, right? It is. >> Okay.
2:35:56
Is there some sort of steel man here where like the you should be more focused on the fiscal condition of the US government?
2:36:02
We would love for that to be the case, but at the we would love for that to be sure the yes, but the thing is the Fed is going to be making decisions.
2:36:11
There's 12 members of the FOMC, 12 voting members of the FOMC, >> and they are going to be attempting to meet their dual mandate of maximum unemployment and stable prices and things that they will take into account.
2:36:24
Well, what does government spending look like right now?
2:36:26
What is trade and tariffs?
2:36:28
What does that mean for the inflation picture, etc.
2:36:30
what does AI mean for the state of the employment position etc.
2:36:34
But at the end of the day then it's like >> you are in once you are a participant in that market what you are betting on is strictly and only how those 12 members of the FOMC are going to be digesting that information.
2:36:49
You know, when when we occasionally have uh arguments or debates about prediction markets, I like to point out >> that the US government bond market >> is not figuratively or metaphorically a prediction market.
2:37:05
It is literally a prediction market in the specific sense that you are making bets on how 12 voters just as in an it's an election of two and there are only 12 voters >> of what they will do at the next meeting or the subsequent meetings.
2:37:19
to it is literally a prediction market of how you expect 12 people to vote eight times a year and that's not that's that is all I believe that a government at least in the US that a government bond market could ever be.
2:37:35
>> Fed currently needs to the dual mandate is minimize unemployment. >> Yes.
2:37:41
Which does not have a >> minimize inflation or hit the inflation target.
2:37:44
[sighs] >> So the the goal is stable prices.
2:37:46
stable prices >> and that has been interpreted and formalized as we have a 2% inflation >> but post AGI postabundance will want the Fed to maximize unemployment and [laughter] minimize prices.
2:37:59
They want to maximize deflation so everything's essentially free [snorts] if we're really AGI pilled here.
2:38:05
That's where we need the Fed to be going, right? >> Yeah.
2:38:08
I don't know like [laughter] what like operation singularity maximize, right?
2:38:12
Because let's just say we have >> Yes.
2:38:15
A let's say we have an AGI that could do all human labor, right?
2:38:17
I don't know what that means for Federal Reserve tax task with maximizing labor.
2:38:26
What data do you feel like what economic data do you feel like you can really lean on?
2:38:30
lean on? I feel like there's so I have so little trust in all the employment data now because it always gets revised sometime you know the revisions have been insane and then that at least like it felt like [clears throat] six months ago >> like there was so much admin like like
2:38:49
focus on some of this data and then there was some personnel changes and so now I'm like >> the boss didn't really like the >> I'll say I'll say two things which is that I actually believe that even to this day setting aside some of the personnel changes
2:39:06
you should do this sometime you should like call up the BLS there they will answer any question you have there are all these like very serious people who are take their jobs very seriously if you wanted to call up the BLS right now >> this sounds amazing >> you should do it I mean it would be a
2:39:21
good segment >> but if you called them up and you're like you know I want to understand how you my uh co-host Tracy wrote a piece on this but if you're like if you call them and say, >> you know, how did you arrive at the price of mayonnaise for this index? >> They will answer. They will spend an >> They will answer.
2:39:34
They will spend an hour on their on the phone with you. They're great.
2:39:37
They're really like they're public servants in the classical thing.
2:39:41
They will they will sit an hour with you and tell you how this was constructed. So, they're really good.
2:39:46
And then the other thing I will say is like >> look, especially in the like hedge fund world, there has been a very big obsession with like alt alt data, private sector data, right?
2:39:58
>> It looks exactly the same. >> Exactly.
2:39:59
like there's been many attempts to construct private um price indices um there's ADP >> you can Indeed.
2:40:07
com has a job >> it doesn't so there's this hope or this sort of belief that's like oh the private sector would be better at collecting this data maybe and look it's all out there and then there's the Mastercard spending data etc.
2:40:23
>> It ends up rarely deviating in any substantial sense.
2:40:27
>> So what you're saying is this goes a lot deeper than There's a lot to it goes a lot deeper.
2:40:30
>> They're all in [laughter] on it. They're all in on it. >> Job data.
2:40:33
Truther goes to heaven asks God, "Did we really add Did the US really add 160,000 jobs in August?" Says, "We really did."
2:40:40
And they said, "Wow, this goes deep."
2:40:42
[laughter] >> Even you, even God's in on it. Wow. >> Exactly. That >> that is crazy. Yeah.
2:40:49
And one thing that has stuck out to me is like this has been the year of uh sort of breathless takes from AI leaders and VCs around like uh we're in the post AGI era. AGI is here.
2:41:01
We're in the singularity.
2:41:01
We're in the foothills of the singularity.
2:41:04
Everyone has a different buzz word except I'm just like I'm going to be looking at this e all the economic charts and like there's it doesn't feel like there's a kink in the graph yet. >> No, it does not.
2:41:13
>> It doesn't feel like it's showing up in GP.
2:41:14
Interesting question is and I like >> you know >> where does the productivity data show up for the internet? >> Yeah, that's right.
2:41:23
>> It doesn't you like it's like oh in in the late 90s productivity moved from 2. 5 to 2. 8%. Amazing. Wow.
2:41:31
It's like and so it's like or or it's like where did the productivity show up with the release of the mobile phone?
2:41:36
So I do think like we could we should and we have there's many interesting conversations that will be had about how AI is like manifesting in the data.
2:41:48
But I do think it's worth asking like why didn't all of these other technologies like show that should have or intuitively felt like they would re >> revolutionize business in some way make companies hyperproductive.
2:42:01
>> Why didn't that show up in the data either?
2:42:02
So until that day when the kink arrives, we have plenty from the past we still don't we could still talk about and try to understand.
2:42:09
Yeah, >> that's sort of my take on it. >> Yeah.
2:42:12
Uh what else have you been tracking recently outside of is is AI just completely all-encompassing?
2:42:19
>> It's so annoying because it's like I'm very interested in like, you know, I'm very interested in oil.
2:42:24
I've been doing some oil stuff, but you know, I'm very interested in the Fed itself.
2:42:28
I'm very interested in all these things, >> but it's just like I feel like kind of against my will >> that right like that.
2:42:37
It's just like every year.
2:42:38
Do >> you ever feel that way?
2:42:39
[laughter] >> I uh >> he's like really another another main story on this.
2:42:47
>> No, I got to like there's someone in my DMs who was like, "Yeah, we got to do an episode about motor oil."
2:42:51
We do have to do an episode about motor oil.
2:42:54
There's um I got to do an episode about >> I like where this is.
2:42:57
ought to do [laughter] an episode about diesel prices.
2:43:00
Diesel prices through all of these things to prioritize.
2:43:02
But I do feel to some extent against my will like there's this like monotonical step up in the number of like waking hours that like you just can't talk about these things without AI. It's funny.
2:43:14
I was in um earlier in the year, I guess it was early this summer when oil was a lot higher.
2:43:21
Uh I was out in Hong Kong >> and Asia or East Asia particular seen as like ground zero for where um you know the the jet fuel crunch is really going to hit and stuff like that because just the route etc.
2:43:35
So I'm like sitting around like all these like business execs and I'm like asking them what's going on with oil and air.
2:43:42
It's like whatever let's talk about AI.
2:43:44
It's like oh my [laughter] god it's like even this is where I thought you guys were going to be a little more >> you know what we need?
2:43:49
We need a new thought experiment for the oil community. >> That's right.
2:43:52
>> We need to build a new thought experiment for all these niche stories and then it can be something that we can tussle with something like a big >> we need a percentage you know percentages around these thought experiments. That's right.
2:44:04
>> We need to build a lore in the world so then you can have endless hours and hours.
2:44:08
Talk to them about like you know asset allocation.
2:44:12
>> You you know the question that I still have not gotten to the bottom of we still you mentioned the the Iraq war protest. Yes.
2:44:17
And and I remember that there was uh at the time the banner was no blood for oil. >> That's right.
2:44:27
>> Because the the stated reason why America went to war in the Middle East was WMDs. >> Yes.
2:44:33
>> Uh and that was pretty handily concluded as like false, right?
2:44:36
Missing misinformation, right?
2:44:38
Um >> but but the cynical view was like we only went for oil and but we didn't get the oil or was that I I don't know.
2:44:49
>> So So So my question is like is like when when George Bush and Cheney sit down years later and and have a glass of wine together and they reflect, are they like damn that one got away from us, right?
2:45:01
>> I mean I mean Trump certainly thinks this. What were they doing?
2:45:03
We didn't even get the oil. >> Yeah. Yeah.
2:45:06
>> But you know speaking of like you know the what is happening on the ground is we did get the oil out of Venezuela and like Venezuelan oil is like basically our oil now >> but that's 1% of the market.
2:45:14
Uh, I don't know exactly what it is, but it's a lot of oil.
2:45:19
But where are the like, you know, savings at the pump, >> but there's there's no savings at the pump, but there's also like the disappearance of like that kind of protest movement because I think like which is where I kind of thought you were going to go, but it's like there was a point in our life where like the thought of like using US imperial might to extract oil was something that animated a nonrival number of people.
2:45:43
>> I think I think the internet literally doing it.
2:45:44
doing it. Where is the where is the I mean there is one I don't want to actually completely sneer them but like um you know where is the there has not been a particularly large scale protest movement about the >> No it's social media like very clearly killed protests because it allows like people
2:46:03
can like go viral and feel like they're >> like you know taking action and yet uh like it it's like sounds like the dream of a of a of a government that's not doing the will of the people is like you you can do whatever you want and sometimes they're going to get angry on online at you but nothing will actually happen. >> But but that's very new. I mean just a
2:46:22
>> But but that's very new.
2:46:22
I mean just a few years ago there were millions of people for the women's march, Black Lives Matter movements.
2:46:26
Like it was it was like postcoid then things maybe slowed down.
2:46:30
I like I completely agree with this idea that like people feel like they can scratch the itch of protest online by throwing a like on a >> really you know what really like died is the bumper sticker. I was just talking.
2:46:46
I was just thinking >> because I was like every once in a while I still like usually it's like a Vermont license plate and they still have like all of the like you know the coexist bumper sticker.
2:46:54
This car climb Mount Washington bumper sticker.
2:46:56
My other car is a broomstick bumper sticker etc. I miss all that.
2:47:01
Every once in a while I see these.
2:47:04
>> It's a boom in in the I bought this Tesla before I bought that's right.
2:47:08
There is that one but I miss the bumper bumper sticker. But I do too.
2:47:10
Uh, and I was thinking about how uh with I haven't seen any anti-AII bumper stickers, but that feels like a ripe area for entrepreneurship.
2:47:18
If someone's gonna start a bumper sticker enterprise, anti- data center bumper sticker probably going to fly off the shelves.
2:47:25
>> And my friend my friend Blake makes amazing bumper stickers.
2:47:27
He he's uh the world's foremost vintage G Wagon dealer.
2:47:34
So, he makes he makes bumper stickers that say you wouldn't put a bumper sticker on a MercedesBenz.
2:47:37
Oh, [laughter] >> you know what I think there's an one of the reasons why AI politics are really confusing and scrambling is that like >> to even go by to even say like put up an anti- AI bumper sticker on your market would force the would force the person to accept the premise that AI is a serious and important technology. Totally.
2:48:01
And so part of the reason that I think that it scramles the thing is like if you want me to be actively anti- it then I first have to accept the premise I'm legitimizing. >> Yep. Yep.
2:48:12
>> And that is like something that that many people are reluctant to do for various reasons.
2:48:17
>> And so there is this question and Nate Silver asked this like why don't you see a more like sort of like left-wing um opposition to like AI and the pace of development. >> Sure. Sure.
2:48:26
There are many I have many think there are many answers to this and I don't even know like there will never be a you know people are complicated but I think it first requires a certain step of legitimization that people don't want to do which would be required to actually like care enough about a risk to put a bumper sticker on it. >> Yeah. Yeah. Yeah.
2:48:44
But with the power of AI we'll be able to take a picture of that bumper sticker immediately translated into ironclad legislation.
2:48:53
That's the >> we could do a spell this out all the herebys that you need to have at the thing.
2:48:58
>> Turn it into law immediately.
2:49:00
>> God, you know, it's funny like um one such a classic political talking point.
2:49:05
It's like they never even read the legislation that they voted on.
2:49:06
Now imagine this is like everything now it's like they never even read the code that they implemented right like there's this will be the phenomenon of our world that in so many different things that people implement no one ever actually like read it or knows like what the guts of it are. >> Yeah.
2:49:24
>> And it's just beginning. Yeah. >> Yeah. Uh yeah.
2:49:26
The state of the book industry is interesting.
2:49:30
>> Did you read that Tim Ferrris article?
2:49:32
He he he talks about how he he wrote uh very uh he wrote very specific non-fiction books.
2:49:37
One of them is called the four-hour chef and it's essentially a recipe book [laughter] and he was like I actually got steamrolled by Chachi PT because people can look up exactly what that is.
2:49:47
Uh and he was trying to sort of like uh match through some trends like obviously I think the Kindle bookstore has seen 3x the number of submissions and there's a clear AI effect there.
2:49:57
But then I imagine that sales of you know Harry Potters are still chugging along.
2:50:06
It's not really substitutive with that.
2:50:07
But >> no, I think that but you know I do think probably in sort of like you know the type of people who like wrote the books about like people who want to read about erotic affairs with monsters and you know which is like >> that's a big cate.
2:50:22
>> I have heard that this is a genre. >> It's called romantic. >> Romantic. >> Yes. It's an investment.
2:50:26
Will AI like be able to like write?
2:50:28
I would suspect that it won't be too long until like c some of these genres, but you know like look really like big like this sort of world building type of fiction that would be in a Harry Potter.
2:50:39
I don't think we'll have that technology for at least another two or three months.
2:50:43
[laughter] >> Uh have you been surprised that Pangram works in 2026?
2:50:48
Yeah, I have been like in >> I would have said that if they're solving Millennium prizes, there's no way that Max Sparrow can detect it with his team.
2:50:58
Like >> I have been surprised.
2:50:58
I would have guessed that and I guess I would still guess that at some point AI writing will be good enough or will be but like >> and I don't think the labs are focused on evading.
2:51:12
>> And so it could be that at some point they may prioritize that or something like that.
2:51:17
It's kind of a nice equilibrium where it's like, look, if you want to know if it's AI written, you can, but we're not going to like stuff it in your face with a bunch of like heavy-handed tells or like, you know, additions, but like it is an option to go figure it out if you want.
2:51:31
>> It might be a useful um it might be a useful equilibrium, one that the labs don't feel any particular prioritization to like work on, etc.
2:51:39
Uh, I mean like I I you know there's no you know it's funny because people talk about like AI writing and when I when the conversation happens online it's often between journalists and so writing to them means writing articles. >> Yeah. Yeah.
2:51:58
The vast majority of quote writing is just emails, right?
2:52:00
And I doubt there's like, you know, and I don't think that there is like some big norm within most corporations like what you had an AI write this memo summarizing the meeting.
2:52:11
I've actually heard the opposite when I talked to people who work in non-media organizations and non- tech organizations that there was a norm against like why didn't you have the AI write this?
2:52:22
It would have been a cleaner email than >> cleaner for sure.
2:52:24
But I I think the KPI that that I would be interested in in looking at if uh >> would be like number of words should like posted to Slack and over email for employees should not be increasing in the AI era.
2:52:38
No like do not just become more verbose because you can but if you're using AI to fact check everything that you're saying but you're still writing tursely in. No, no, I agree.
2:52:46
And like look, it's all it's still all in flux, but like I I think like by and large like if you send me an email and it's like how to find the TVPN offices and what you should do, what you should wear, and I can tell it's like AI written, it's not going to be a big deal to me.
2:53:04
I'm not going to be like, >> it's not just a studio, Joe. It's an ultra dome.
2:53:08
You'll know it [laughter] when you see it.
2:53:09
Like I'm not going to be like, you know, tremendously offended if like you use >> send you the sloppy GPT40 email.
2:53:18
>> I actually am like I am kind of like a hold out in that like I I actually have never sent a like AI generated email.
2:53:25
Like I'm like I if I'm going to like put words to something, I want to write them, >> but I do not think there's going to be like some big norm against like for like basic functional >> Yeah. >> community.
2:53:35
>> community. I just love being able to like open up uh the voice mode or like the the the dictate website, ask seven different questions across statistics and links and some charts and then just have like basically I used to have 12 tabs with like Wikipedia and some e
2:53:53
economic statistics and I used to be tabbing through them when I'm actually writing or researching and now I can just have it all in one go and then I'm still doing the instantiation and like the thought process is pretty nice but like it's really good for like It's pretty good. It's pretty hard to resist.
2:54:05
It's pretty hard to resist. I mean, yeah.
2:54:07
Like whether I, you know, I >> I I'm interested in this book.
2:54:10
What would be some other recommendations?
2:54:14
What are the through lines between this line of thought and this line of thought? >> Yeah. Yeah. >> It's pretty good. I kind of use it.
2:54:20
>> What are the biggest uh or like most shocking uh findings on dur from your studies on orality? >> Yeah.
2:54:26
You know, I think it's actually like so this is something I'm like very interested in and um I don't know so or like when you think of like so orality what do what do we really talk about here?
2:54:40
It's speech but there are things that happen in speech that are the important part.
2:54:44
So for example three people talking we might try like oh let's one up each other etc.
2:54:48
Let's get a little bit confrontational.
2:54:51
It's like this is like a little spicy. I completely agree.
2:54:55
Let's not get confrontational. >> Let's not.
2:54:58
But um but this is different with AI.
2:55:01
Like it's and so this is like actually something I'm like very interested in because for the last 15 years of the internet, we are just sort of like bathed in constant both compets and competition, right?
2:55:11
if whether it's Instagram and you're sort of trying to show your life is a little bit better than someone else's or whether it's Twitter and you like want to get in a good dunk etc.
2:55:22
>> So I think the really interesting question or one of many interesting questions from a society standpoint is what happens when we're bathed in the thing that always agrees with us and what happens like when we're bathed in like the most polite helpful thing on the other side.
2:55:38
So it's very tempting to like look at say like okay chat bots are this huge thing this is the extension the acceleration this is like the sort of back and forthness of um social media etc.
2:55:51
But it's not because it doesn't have that like competitive thing that one the chatbot is never trying to oneup you.
2:55:57
It's never trying to get on a dunk.
2:55:59
>> I actually have [clears throat] had an experience recently.
2:56:01
I got a very robust uh racing simulator. >> Oh sick.
2:56:07
>> Uh and And so and so I'll be like, you know, focusing on uh improving like my lap times with a certain classic car on a certain track.
2:56:17
>> And I've had the experience a bunch of times where I'm like I cut like a lot of, you know, >> multiple seconds off my time.
2:56:22
I think I'm feeling like I feel pretty quick >> and I go to I go to chatbt and I'm like, how's this pace on this track in this car?
2:56:31
And uh and it'll just like I'm expecting it to be like you are the goat like you are.
2:56:40
>> It used to be like you're you're in the conversation.
2:56:44
>> It's like and and like you know granted I'm I'm a relative beginner. Yeah.
2:56:50
>> But it'll be like you know I'll think I'll have improved a lot already and then it'll be like yeah you're you're like >> clearly in development.
2:56:57
I wouldn't [laughter] I wouldn't call you like and it's like and and it's and it's ranking out like it's doing a tier list and it's like >> you're you're uh you're three tiers away from like competition pace basically and it's actually it's like to me I'm like >> wow I'm I'm actually glad I'm glad it's telling me the truth because it's pushing me it's showing me there's more but it's not a good feeling to get told by this thing.
2:57:21
by this thing. I always like who is brave enough to admit that they misled the models were more obscious [laughter] and told you you were a genius every time like what do you but now you like ask the latest model you know I have this thought that this is like this and it's like yeah Velissa you're not you're
2:57:38
missing something it's like oh I'm you know what I'm going to go back to opus because uh that was really nice to me and always told me I was >> sometimes they'll even sort of like like uh compliment themselves like they'll ask a question and they'll dig in and they'll be like well I found some interesting things I dug into it and here's is the interesting part. >> You know what I [laughter] mean?
2:57:54
>> You know what I [laughter] mean? Interesting. Yeah. Well, I started this. Okay.
2:57:57
So, let's give me some credit.
2:57:58
>> I like to, you know, unfortunately for several when I frequently will ask the question on incognito mode so that my past history doesn't [laughter] so that >> so that like I don't want it to just like flatter my you know because otherwise it's too >> of course.
2:58:12
>> But um I had something that I had never seen before.
2:58:15
>> It literally says so 208 puts you at a pretty reasonable pace especially since you're still learning to [laughter] track.
2:58:20
The circuit has an unusually large skill gap because the entire mountain section rewards confidence and precision.
2:58:26
It's basically it's basically like saying you suck.
2:58:28
[laughter] >> That's brutal.
2:58:30
But I had an interesting experience that I never had seen a response before.
2:58:34
So I asked I was reading a book and I didn't quite understand something.
2:58:37
So I asked the uh model to if it could like help me like understand this section and it said something weird that I had never got before.
2:58:45
It said, "You'll have to forgive me because I'm remembering this book from my memory."
2:58:50
And it was like I I So, I'm like, "My memory of the book isn't that great, but my understanding."
2:58:55
And I was like, "That's weird because then >> the model begins to sound like this like self that has an understanding of its own."
2:59:06
It's like, you'll have to forgive me.
2:59:08
I'm I I don't exactly me remember what the book said. >> Interesting.
2:59:12
And I was like kind of unnerved by this like level of >> abstraction. So that is weird.
2:59:15
That also might be an artifact from uh specific reinforcement learning on do not memorize the entire book because if you reproduce it, we get >> there's a copyright >> and so and so actually like the correct way to talk about literature is is as someone who has read the book but might not remember at all and that's actually the goal that gets reinforced.
2:59:35
>> That's very okay that that could be a good answer. I can't find it.
2:59:37
good answer. I can't find it. The only reason I mentioned s on incognito mode so I can't pull it up because I want to go back and read it but it disappeared >> from my uh chat history but these things like it's like kind of like unner
2:59:50
>> totally yeah a lot and yeah I I was uh I I was noticing chat TV uses I to refer to itself and I was [laughter] like but they're but but the models are starting to use agent swarms >> so should they start being should they start using >> weave have you ever seen that famous
3:00:07
screenshot of it a real chat um someone asked at it some question and someone said where'd you get that fact and the model said oh I was in I I heard at an IBM conference in 1985 responded like where is [laughter] this coming from it's like you were not at an
3:00:23
IBM conference in but that was the response like weird weird stuff >> yeah exactly >> gentlemen >> uh I have a meeting I got to get to pretty soon I hate to cut it off >> such a good time I love chatting with you guys >> yeah always a a great time. Let's do it Let's do it again soon.
3:00:39
It's an honor to finally have you here.
3:00:41
>> It's an honor to be here in the dome.
3:00:41
I can't believe I got to hit the gong. >> Yes.
3:00:46
>> That was like I'm done.
3:00:46
I have no nothing left to accomplish.
3:00:49
>> Hit the hit the sound.
3:00:49
You got You got one one option. One option. >> Yeah. Choose one.
3:00:55
>> The live show is happening. Odd lots in Los Angeles. Lots of guests. It's happening tonight. >> There we go. >> Just a classic. I went with the classic. >> All right.
3:01:05
And I want you to experience this.
3:01:06
you guys on Apple podcast.
3:01:09
>> We're going to see you Monday.
3:01:10
>> We'll see you on Monday. We're out.
3:01:12
We're at a conference tomorrow, but we will be back on Monday, 11 a. m. Pacific sharp. >> We love you.
3:01:16
>> Sign up for a newsletter. Goodbye.