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4:02
5 on the horizon founder. YOU'RE WATCHING TVN.
4:36
>> Today is Friday, January 23rd. >> It's casual Friday.
4:39
>> Casual Friday cuz I got the semi analysis jacket on. Zoom in on this. Thank you.
4:44
Normally I'm the casual guy. I thought I'd let Patel. >> Thank you to Doug.
4:50
Thank you everyone over at semi analysis. This is fantastic.
4:53
It's extremely comfortable and uh I look like I'm ready to go to our data center.
4:57
I feel >> it's built for abene.
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>> I feel like this is built for abling.
5:01
You throw this on, you're ready to go.
5:03
Uh see what the hyperscalers are up to.
5:05
Uh maybe wire up some GPU racks, do whatever you need to do. >> I I love it.
5:09
So, thank you to everyone over at semi analysis.
5:10
Uh we have another we have another gift that came in the mail from a friend of mine, Alex Moore, over at the Ark phone case. Arc Pulse thing.
5:19
It's got uh it's a phone. It's so heavy. Feel how heavy this is.
5:27
[laughter] It's a [clears throat] It's a fantastic uh presentation. >> Yeah.
5:33
>> It has a certificate of authenticity in metal.
5:35
The Arc Pulse Exclusive Edition Titanium Opal Damascus.
5:41
>> The new iPhone is really been testing my case-free lifestyle that I've been running for >> Yes. Oh, yeah.
5:47
You know, super bullish for cases.
5:49
Like my my phone's only a couple weeks old, maybe months old, and it's just like completely destroyed on all the corners. It's really bad.
5:55
Um, so born from a fascination with precision engineering and material mastery, the arc pulse titanium opal Damascus unites advanced metal energy with sculptural intent.
6:06
Every case is forged from over a 100 individual layers of titanium purged with argon gas bonded at temperatures exceeding 3,000 Celsius.
6:14
Uh, so thank you to everyone over at Ark with this fantastic case that has been delivered with its own case, series of cases.
6:22
It's a uh sort of a Russian nesting doll situation.
6:28
So, do you have news or can I tell everyone about ramp. com? Time is money. Save both.
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Easy to use corporate cards, bill pay, accounting, [applause] and a whole lot more all in one place.
6:37
>> Couldn't have said it by myself.
6:38
>> What did you want to chat about?
6:39
>> What uh what did you write about today, John?
6:41
>> I wanted to dig into the question that we had with Joe Wisenthal yesterday.
6:44
What does China actually import?
6:44
Uh obviously, this was off the back of Davos.
6:49
Vice Premier Haley Fang highlighted China's determination to become the world's market.
6:53
They say, "Hey, we we're the world's factory, but we also can buy stuff. Send us your stuff. We'll buy it."
6:59
But what are they gonna buy?
7:01
So, he said boosting domestic demand was now on top of their economic agenda.
7:07
This is in their their 15th five-year plan, something like that.
7:09
Uh and we were going back and forth like what are they actually importing?
7:12
Uh we were saying semiconductors, but you know, obviously there's there's chip deals and and GPU bans.
7:17
Now, interestingly, uh, China is like the number one trade deficit for China is semiconductors and it has been since 2005.
7:26
So, um, they wanted they they they they want to buy semiconductors.
7:31
Obviously, US trade policy oscillates.
7:33
Um, but semiconductors are the single biggest deficit for China.
7:35
In 2020, even before the AI boom, China imported 350 billion worth of semiconductors.
7:40
Uh, which was more than the value of the crude oil it it imported that year.
7:44
And it's been the largest of importer the largest importer of chips since 2005 and accounts for huge chunks of revenue for Qualcomm.
7:52
It's over 50% of Qualcomm's revenue I think and over 25% for Intel.
7:57
So everything that you get from China, if it's an electronics product, it's some gadget, it has a chip in there, that's probably going to be made in the West, you know, fabbed in Taiwan or made in in an Intel fab, sent over to China, assembled and then sent back out >> and then sent back out. Exactly.
8:11
So they they aren't imported there.
8:13
Uh energy is a big driver of the trade deficit with China.
8:17
Uh China imports 74% of its oil supply and 42% of its gas supply.
8:20
Uh soybeans, which you mentioned, and iron ore are also big categories.
8:25
The iron ore obviously goes into a lot of again the factory, the world's factory.
8:31
>> Why can't China make enough soybeans in China? >> I don't know.
8:36
>> It must be climate related. They love making stuff. >> Yeah, I don't know. That's a good question.
8:40
We should we should dig into that.
8:41
But um um luxury was what you said and you were right.
8:47
Uh luxury is a clear net import category for China.
8:51
Estimates are around 100 billion annually.
8:53
Now it's not the it's not the biggest driver of their trade deficit or trade surplus.
8:59
Um but it is uh and it's also not critically important in the way chips or oil or soybeans or iron or are.
9:07
Um but it is but it is an important story and almost all of Chinese luxury good imports are from European conglomerates.
9:15
You got to think LVMH and Caring.
9:17
Uh it's not strategically important really and uh the the foreign luxury market in China.
9:25
So European conglomerates sending their goods to China.
9:27
It actually completely fell off a cliff in 2024.
9:28
Uh imports went down about 20%.
9:32
based on more more international shopping that was happening, travel and a domestic boom.
9:39
So domestic Chinese luxury brands are on the rise.
9:42
Laoo gold is now drawing this from the same customer base as Louis Vuitton, Hermes, Cardier, Bulgari and Tiffany. Gucci is closing stores.
9:48
I think around 18 stores are closing.
9:51
Uh while the local champion Songb is seeing significant growth in their handbag business.
9:56
Uh so ch the China does want to be the world's market but they're also buying domestic a lot.
10:01
Um the other dynamic that changed recently uh in the east versus west brand dynamic has been the acquisition of successful brands by Chinese companies with more competitive supply chain.
10:12
So Morris Garages started in the 1920s and became synonymous with affordable British sports cars under the badge MG.
10:19
Are you familiar with MG? >> Not super familiar.
10:22
>> We got to pull up some videos of old MGs to show you.
10:24
Uh my family actually had one when I was a kid. A really old one.
10:29
Uh do are you familiar with MG?
10:30
>> I think my grandparents also had one. >> Yeah.
10:31
No, it it was like a cool It was a really really cool like British lux not luxury, not high-end, but uh a true driver's car.
10:40
So, we'll pull up one of these videos uh while I tell you about the brand.
10:44
It's changed hands a ton.
10:46
British aerospace owned it at one point. So did BMW.
10:47
Uh but the MG business just collapsed.
10:50
Uh because British Britain had a lot of, you know, sports car manufacturers.
10:55
They had uh Jaguar and uh Land Rover and Aston Martin and there's a whole bunch of other companies.
11:00
But the MGs, the old MGs, they still look great.
11:04
Here's a video of one of them.
11:06
Jordy, give me your review.
11:06
Would you pick one of these up?
11:08
I like the soundtrack, too.
11:10
It's a good This is a good song for for an old retro video about an MG.
11:15
These were these were iconic back in the day. Yeah. F >> I like it.
11:21
It's got a nice silhouette. >> Yeah.
11:22
Um certainly certainly a throwback sort of a Porsche Speedster style. I like it.
11:28
Um but eventually the company failed 2005 and the brand was sold off to Nonjing Automobile Group which was rolled into SIC Motor which is China's largest stateowned automobile manufacturer.
11:42
And so the acquisition it actually worked and uh sales of new MG motor models have picked back up.
11:47
Since 2019, MG has been China's most exported car with more than uh 88% of sales happening internationally.
11:56
So, they bought the brand.
11:58
They >> Any idea where >> uh Europe, Canada, basically everywhere except the United States.
12:03
They sell them in in England.
12:05
So, the MG brand is still well known in uh in Britain.
12:09
And uh with the new uh models, they're selling pretty well.
12:15
We can pull up a video of the newer MGs uh because they have a sports sedan.
12:18
They actually have I think um like sort of minivan as well, but here's here's a review of the sport sedan. See the quad exhaust.
12:26
>> All of the world has never >> Look at this. Uh look at this.
12:28
They have this crazy like tail fin that comes out.
12:32
They have a lot of like fun gimmicks on here, but there's the MG brand.
12:36
>> Still alive and well thanks to China.
12:39
>> This is one of the best looking MG cars on the market.
12:41
At the front, you can see the LED headlights with the striking DRLs, 19in alloys, sleek fast back profile with aerodynamic lines around down this 4.
12:51
9 m long car and frameless doors.
12:55
At the back, we have wide hips with flowing LEDs with not two but four exhaust tips.
13:00
And surprise, they actually work because this Chinese car is not electric. Finally, I know.
13:05
And after all that sportiness outside in here you find >> Yeah, it does. The the rear end's nice.
13:14
>> 375 liters of space with a lift back design.
13:18
So, it's super easy to load and unload stuff.
13:20
So, this car is not just sporty.
13:22
It's also daily friendly.
13:25
>> They also have a sports car that we can pull up that [snorts] has some very interesting features.
13:29
Uh it has some scissor doors. It's electric.
13:31
Uh there's there's a reveal video that we can play here. Look at this. This is the MG H.
13:38
It's like Sportster, Speedster, something like that. Cyberster. Cyberster. That's what it's called. The Cyberster. Look at those doors.
13:47
That's kind of It's It kind of ribs. It looks >> Tyler.
13:50
I mean, we've been We've been wanting you to to for your next car go up >> to kind of like establish dominance in the in the >> I don't know if I can the Chinese. Yeah. It just feels >> Yeah. Yeah. Yeah.
14:02
Uh let's play the review of the Cyber Stir from Forest Auto Reviews.
14:05
I I really like this creator.
14:07
He does uh one minute vertical video reviews of cars from start to finish.
14:13
So essentially compressing like what normally >> and this is an electric drop top sports car and >> he just goes through everything.
14:21
>> The electric thing aside, this thing is gorgeous.
14:22
You have these awesome headlights.
14:23
I get these gorgeous body lines.
14:25
But I think my favorite part has to be the way the door opens.
14:27
I just come over here, push this button, >> and it pops right out. >> So cool.
14:32
>> But don't worry because if it's going to hit something, >> it's hard to get those doors BMW i8.
14:36
That's the only option in America really at this point.
14:39
>> They really are cooking here.
14:40
>> They are paddle shifters.
14:41
>> Paddle shifters in an electric car.
14:41
It just changes your drive mode.
14:43
But you could imagine with an update, you can do the uh like synthetic DCT, digital DCT, which has been very popular in the uh >> lot of storage space down there. Storage under here.
14:55
Tons of storage back there. [music] More storage.
14:58
>> He really gives you like a full tour of the car in just 60 seconds. >> Back here.
15:00
In the back, you get literal arrows as your tail lights.
15:02
This can do 323 mi on just one charge. It does 544 horsepower.
15:06
And because it's allwheel drive, if I push, >> you cannot buy these in the US. >> Do 0 to 60 in 3. 1 seconds.
15:12
>> And then he rips away. >> Boom. This is some traction. >> Back to a safe stop. You get Brembo brakes.
15:17
And if this were sold in America, it'd be $41,500.
15:21
>> That's not bad, right?
15:21
Like that's kind of a steal.
15:23
Anyway, quickly, let me tell you about Century.
15:26
Century shows developers what's broken and helps them fix it fast.
15:30
That's why 150,000 organizations use it to keep their apps working.
15:35
Um, so uh this this trend has been going on with American or you know storied brands, European automobile manufacturers uh selling to Chinese companies.
15:46
Volvo changed hands from Ford uh to China's Xi Jang Xile Holdings Group.
15:52
Uh in 2010 the deal valued Volvo at 1.
15:55
8 billion and it also basically worked out.
15:57
sales have grown from half a million vehicles in 2015 to over 700,000 vehicles in 2023.
16:02
And when I told you this, you were like, "What? Volvo?"
16:04
And and I Yeah, I couldn't believe it either.
16:08
Um, Jilei also bought Lotus, the maker of the Lotus Elise, the Avia.
16:12
There's a bunch of other sort of like more affordable sports cars, ultra light uh sort of tossable cars.
16:17
Uh, and so Lotus is also another British sports car manufacturer to wind up in China.
16:22
And so the the basic trend is like China excels at uh developing efficient supply chains, streamlined manufacturing operations.
16:30
Uh and it doesn't stop with cars.
16:31
They're doing it with TVs now.
16:31
So on Tuesday, Sony announced that they would be spinning off its home entertainment business, which includes the TV brand.
16:38
And uh uh to their Chinese rival TCL Electronics Holdings, Sony selling a 51% stake to TCL while the brand will remain Sony.
16:47
Uh the display technology will be TCL.
16:49
And so Sony's been falling behind Samsung, TCL, LG, Xiaomi in terms of TV shipments for a while.
16:56
Uh, but the brand still holds a ton of value.
16:58
Like Sony TVs were the best uh a decade ago.
17:00
And still today, people like the the software a little bit more.
17:05
And the Sony brand, it still has the aura of the the Walkman, the the PlayStation, like it's just beloved electronics.
17:12
And you see the Sony logo, and it's just way more familiar than >> you think Japanese excellence. >> Yes, you do.
17:18
and and so uh Sony has been you know falling behind on the manufacturing front.
17:24
TCL has been basically delivering a much stronger value prop on a price to quality basis and the panel technology is is is uh is loved and and very competitive.
17:34
Um but there's just more faith in the Sony name.
17:38
So the Chinese manufacturer is effectively pulling forward heritage and brand legacy by buying the name.
17:41
Uh and this feels like a trend that will continue for a while.
17:45
China's fantastic at quickly grinding down manufacturing learning curves, developing high quality products at affordable prices, but creating an iconic brand, it just takes decades and so it's better to buy than build.
17:56
Like this is the one thing you buy instead of build.
17:58
Uh and so Western companies after getting beat up on margins and seeing their market share slowly shrink.
18:02
I think the Sony TV market share was like dropping to less than 1%.
18:08
Uh while I believe Xiaomi is at like 6%.
18:11
I didn't even know Xiaomi makes TVs.
18:14
phones and cars and apparently they make everything.
18:15
Um >> it is it is such an interesting dynamic because you have like you know western brands and manufacturers that have just been saying like yes China is out competing us on manufacturing by like 2x we're getting destroyed.
18:27
We need uh we basically need uh tariffs and things like that to protect uh to protect market share etc.
18:34
Uh, but the one thing that they'll never have is brands, right?
18:39
It just takes so long, you know, building up the Volvo brand.
18:41
It's not just like an advertising budget.
18:43
It's time >> and it's their safety record and all these things that go into that.
18:47
Um, but of course, if you if you're out if you out compete just on manufacturing long enough >> and then you're >> and then you get these opportunities to actually buy the the the top brands, eventually you can actually own the full stack. >> Yeah. Yeah.
19:03
Uh, so we got to look at one more MG, their hyper car. It's a concept car.
19:08
Probably will never ship, but uh I want your review on whether or not you would step into this and take it for a spin.
19:14
This is the MG Hypercar or Supercar.
19:17
This is from Supercar Blondie.
19:19
And Supercar Blondie has an uncanny ability to get access to every concept car ever made.
19:24
concept car ever made. I'm constantly seeing supercar blondie content about cars that feel like they barely exist or or >> so single seater >> single seater like this is like this is like a competitor to the Valkyrie and the or something Valkyy's
19:40
>> Valkyy's two seater but yeah it's like a crazy like I I mean this is p probably just for show during a big conference something to turn heads and draw eyes but uh pretty pretty remarkable to see this from MG the company that made, you know, these open top roadsters in the 1920s. Anyway,
19:58
Anyway, >> yeah, I mean, it just looks like uh looks pretty close to a speed tail.
20:05
>> It does look like a McLaren Speed Tail, >> which is also the center >> Yeah. >> center seat.
20:09
>> Also McLaren Speed Tail. Uh inductive charging. Have you seen this? >> No.
20:13
>> So, there's a pad that when you drive over it, it will charge the battery.
20:16
And I think that's also like a regular trickle charger. >> Yeah.
20:21
So, you don't So, it's still a trickle charger.
20:22
8 hours, but you don't need to plug it in.
20:25
>> And I think that's also happening with the the new uh Porsche SUV EV. Maybe the Cayenne EV.
20:32
>> Ferrari should pick that up.
20:32
Ferrari loves to put put their trickle charge.
20:36
>> Tesla should pick it up. Tesla's the obvious one.
20:38
>> No, but but but Ferrari is notorious for being like, "Oh, that thing you need to use every time you drive your car, we're going to put it buried in the trunk.
20:47
You're going to need to crawl in." >> Yeah.
20:48
I mean the uh the like the Tesla charging remember the the robotic arm the snake that was gonna do you remember this there Tesla was at one point teasing this might have been like a decade ago but they were teasing basically a a robotic snake like arm that could go and plug in the car like autonomously.
21:07
So you just pull in and then at some point it would just go and plug in and they never shipped it.
21:11
Are you're looking at me like I'm crazy.
21:14
>> I've never heard of that.
21:15
I think they should also do the um you know there's the Chinese Eevee where the battery explodes at the center.
21:19
[laughter] >> That thing is crazy. >> Can we pull that? >> Yeah.
21:22
Yeah, we got to pull that out.
21:23
>> You know, if you're next, you pull next to your your ops, your enemies, you just hit them in the shins with your battery. >> Yeah. Yeah.
21:29
>> Uh Jordy, I want you to try and pull some of that up.
21:31
But first, I'm going to tell you about Turbo Puffer.
21:32
Serverless vector and full text search built from first principles and object storage.
21:37
Fast, 10x cheaper, and extremely scalable.
21:39
Uh [laughter] do we have any luck?
21:43
Uh, John Arnold says, "I don't know if Chinese manufacturers will ever make money, but uh, I came away not wanting to invest in any manufacturing business in the rest of the world."
21:51
And Ian Roundtree says, "I'm going to keep investing in American manufacturing."
21:55
So, people are still still pushing it.
21:57
Uh, there's also big news.
21:57
Uh, Anderl is bringing a 1 million square foot union built campus uh, along with 5,500 jobs uh, to the city of Long Beach.
22:06
the the the office of Mayor Rex Richardson, the Long Beach mayor, uh posted this uh over the next three years, Andrew will be building this.
22:18
This is the largest private investment in Long Beach history, and it's a major vote of confidence in Long Beach's leadership in aerospace and advanced manufacturing.
22:27
It's accelerated by 28 and uh grow Long Beach in action. Great work, Lex.
22:30
Love to see it, says Grunt Daniel.
22:33
Uh it's fantastic and what a banger. Thousand likes on this.
22:38
Everyone's happy about the new Anderal campus in Long Beach.
22:39
Uh anyway, >> um I have this pulled up on futurism.
22:46
China unveils EV that can violently eject its battery. >> Okay. >> In case of a fire. >> Okay. Send that to the team.
22:51
I'll tell everyone about public.
22:53
com investing for those that take it seriously.
22:56
Stocks, options, bonds, crypto, treasuries, and more with amazing customer service. >> Okay.
23:01
If you scroll down this video and we can see this in action and see what kind of situation >> Yeah. This is so wild.
23:07
I remember when this video went viral.
23:09
It's like [laughter] what what is the point?
23:11
Oh, it's because if it crashes and it's going to burn, it'll shoot it out.
23:15
But oh, that just seems like so so dangerous. [laughter] Who?
23:23
But yeah, at the same time, people people, you know, watch these videos and they and they think like, oh, this is like widespread Chinese best practice when really like this is probably like their Gundo equivalent, you know, just like a couple dudes.
23:34
It is interesting that they're like, "We don't just need to get it 10 ft away.
23:37
We need to get it 30 ft away." [laughter] >> Yeah. Yeah.
23:40
Because you could just like like gracefully drop it out or something or like or like slide it out sort of slowly with a little pusher, but they have to like shoot it out like a cannon. It's amazing.
23:50
Anyway, Gemini 3 Pro, Google's most intelligent model yet.
23:55
Next level uh vibe coding, state-of-the-art reasoning, and deep multimodal understanding.
23:59
And speaking of Google, I think we got to watch the video about AI industry news.
24:03
Every two weeks, one of these models is destroying someone else's model.
24:09
And we we we we found a fantastically funny video on Instagram reels that we will play for you today, folks.
24:16
So, let's play the re the com >> destroyed Pinterest and Chad GPD.
24:23
[laughter] JGBD destroyed perplexity and Google AI.
24:29
[laughter] LinkedIn AI just ruined WhatsApp AI. We met Meta II.
24:36
IRCTC AI just destroyed Uber AI. Wow. >> Wow. >> So good.
24:43
[laughter] What is that last one? IRCTC AI.
24:47
I've never even >> He's just making stuff up.
24:49
>> He's just making up acronyms at this point.
24:51
But it really is so true that like there's just a timehonored clickbait title of like destroyed in all caps.
24:58
I used to do it on my YouTube videos. Always went viral.
24:59
It's it's it's been proven.
25:01
I was I was taking credit for for inventing that format on YouTube.
25:06
Brandon Guerell put me in the truth zone and and said that I did not in fact create that.
25:10
That was created [laughter] long before the Buzzfeed the Buzzfeed era and is is potentially timehonored.
25:17
Uh anyway, >> don't worry.
25:19
I will I will drop I will drop the video link in the in the YouTube. >> Please do.
25:23
And uh and while you're doing that, I will uh pull up the linear lineup and tell you who we have on the show today, folks, because we have a great lightning round coming up.
25:31
Uh we have Turin from base 10, Bryce from Nominal, Max Sparrow, the AI slop, janitor from Pangram, and then Russ closing out with Live Kit.
25:41
Some fantastic uh funding rounds coming up.
25:45
Linear of course is the system for modern software development.
25:47
70% of enterprise workspaces are using linear with agents and you should be too. So >> that's right.
25:55
What's going on with Tik Tok?
25:58
>> Tik Tok is it it's sort of the reverse honestly. It's very interesting.
26:00
uh you have this dynamic of like the American companies or the western companies uh MG and Sony selling to Chinese because they have great manufacturing and then Tik Tok you know we want America wants uh control over the algorithm over the data security and so you have a Chinese company that's now going to be operating in the US and the Wall Street Journal has a piece here on it first I will tell you about Lambda.
26:24
Lambda is the super intelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.
26:30
So the agreement was negotiated to comply with a 2024 law requiring the company to do a deal to address US national security concerns.
26:39
Of course uh it was it was a total like will they won't they for all of 2024 with Tik Tok and then also in 2025 we were constantly tracking like when will this happen?
26:49
It took years and years and years.
26:51
Like the actual Tik Tok should divest discourse is now like three or four years old.
26:56
Lots of people have been working on this for a long time, but Rome wasn't built in a day and Tik Tok was not divested in a day.
27:01
Uh but Tik Tok officially established a joint venture that would allow it to keep operating in the United States.
27:07
The company said Thursday, resolving a year'slong fight to address Washington's national security concerns.
27:12
Under the terms of the deal negotiated by the Trump administration, the popular video sharing app will be operated by a new US entity controlled by investors seen as friendly to the US.
27:23
Its data management and algorithm training on American users will be overseen by Oracle, the cloud computing giant that has safeguarded its data for the US for years and has close ties to the Trump administration.
27:33
The deal was negotiated to comply with a law passed in 2024.
27:37
President Trump delayed the implementation of the law a year ago after starting his second term to keep Tik Tok operating in the United States.
27:46
He signed a series of executive orders to extend the deadline for completing a deal until it was met Thursday.
27:49
Uh Trump said in a social media post, "I'm so happy to have helped in saving Tik Tok."
27:56
He sang he thanked Chinese leader Cinping for working with us and ultimately approving the deal with a capital D.
28:02
[laughter] uh he could have gone the other way but didn't and is appreciated for his decision.
28:07
Trump and Tik Tok's investors and allies uh pushed the deal through despite lingering concerns among lawmakers and security hawks that China could still influence the new entity through Tik Tok's parent bite dance which% of it >> uh it makes sense that this took so long.
28:25
It sounds really simple just divest but in reality you have to effectively rebuild an entire app, right? >> Yeah.
28:32
It's got to be it's got to be it's going to be like a new app figuring out the logistics of that.
28:37
>> Uh there's also just a ton of hair on the deal, right?
28:40
There's a huge revenue share that's going back to bite dance in perpetuity that uh is obviously reflected in the valuation.
28:47
>> Um and so and then the other the other factor is like if you have a US Tik Tok now and then you have normal Tik Tok.
28:52
If I'm on the US Tik Tok, am I sharing content to international Tik Tok?
28:57
If I'm on the international Tik Tok, is it sharing my content back into the US app? Yeah.
29:04
How does that all work out? Yeah.
29:06
And so there's a lot of stuff that still needs to be handled.
29:07
You know, I I would say like most of the social media app, pretty much every social media app that you use, if you just cut off all international content creators, the experience on the app would get worse. Yeah.
29:18
So, there needs to be like some content still flowing back and forth.
29:22
But figuring out how exactly that works is um uh still in process. >> Yeah.
29:27
Uh, Tik Tok CEO Shou Chu said in an internal note to employees, "The majority American-owned joint venture will operate under defined safeguards that protect national security through comprehensive data protections, algorithm security, content moderation, and software asurances for USU users.
29:43
Uh there was a the the whole Tik Tok debate really erupted when uh Tik Tok CEO Shou was in front of Congress and was not really acting like he was the boss basically.
29:58
That was the main criticism.
30:00
It felt like he didn't have full control over the entity because of course it's a subsidiary of Bance and um and some of the US lawmakers were pressing him on how much control he actually has.
30:10
Did they send the right person to the congressional hearing?
30:14
Uh but it seems like he's held on and he's done well.
30:18
He's also Singaporean, by the way.
30:18
Uh so, you know, easier to, you know, be a part of the new US uh Tik Tok organization um and and allay any concerns of Chinese control, which is uh certainly at the heart of the uh of the administration's goals here. So, who's in the deal?
30:35
You got Oracle, you got private equity firm Silverlake, you got Abu Dhabi based MGX.
30:39
They will each own 15% of the new entity.
30:43
while Tik Tok investors will own about 30%.
30:45
Other notable investors include JD Vance's former Revolution uh former firm Revolution and tech executive Michael Dell's family investment office.
30:55
Dell's getting in the deal.
30:57
Uh Vance spent a brief stint at the firm founded by AOL co-founder Steve Casease during his time as a venture investor which preceded his 2022 Senate campaign.
31:08
I didn't realize that uh JD had been at uh at Revolution.
31:13
I I know he was uh he had a separate venture firm.
31:16
Um but I didn't know that he was hanging out with Steve Casease, the former co-founder of AOL.
31:20
Uh Vance has said previously that the deal values the new entity at about 14 billion.
31:25
A lot of people thought that that was really really low given uh Tik Tok's immense growth.
31:32
immense growth. But there is another side of this which is that Tik Tok I don't believe was ever monetizing or as profitable as the its competitors YouTube and and Instagram and uh Mark Zuckerberg and uh and the and the Google team were not like exactly slow to move
31:52
and launch competitive products and so a lot of the you see this continuously where uh Snapchat comes out stories is on a tear and you're looking at the Snapchat growth curve and you're like, "This is going to kill uh this is going to kill Facebook. It's going to be the
32:05
It's going to be the next Facebook."
32:07
And Mark Zuckerberg needs to acquire it.
32:09
He puts in an offer, gets declined.
32:11
Um and it looks like it's over.
32:14
But then the Instagram team moved really quickly.
32:16
They launched stories and that effectively, you can see in the chart, stories launches on Instagram and people stop moving on to Snapchat.
32:24
And so a lot of people went back who had who were on Snapchat, they went back to Instagram and Instagram continued to grow and Snapchat it didn't flatline but it like definitely put a dent in their growth.
32:33
And I think the same thing is true for Tik Tok.
32:35
Like Tik Tok a lot of people who just want that format vertical video endless scrolling slop.
32:41
Uh they can get that now.
32:41
We we got we got Americanmade troughs all over the place everywhere the eyes can see.
32:48
[laughter] So, uh, the investors are paying the US government a multi-billion dollar fee for arranging the deal, a concept Trump previously called a tremendous fee. Plus, interesting.
33:00
Tik Tok said it had 200 million users in the US, up from its 2024 estimate of about 170 million users. So, decent growth. Uh, but I don't know.
33:11
I mean, 200 million in the US is a lot.
33:14
Like, that's pretty much everyone. >> Yeah.
33:15
I guess the question is will they ever get the rest of the US >> in the in the way that YouTube you could assume has like effectively >> you think they have like 300 mil.
33:24
>> Yeah, I would assume that that uh >> I don't know.
33:26
There's a lot of Philistines out there.
33:27
There's a lot of Leites who are just like nah I want I want DVDs. I want VHS tapes.
33:31
Anyway, Trump touted his popularity on Tik Tok earlier Thursday, posting on Truth Social that his posts on the platform Tik Tok get more engagement than posts on Tik Tok competitor Instagram, which is owned by Meta Platforms.
33:48
>> Tik Tok Trump said that Tik Tok helped him win.
33:51
>> I mean, that's always uh for what it's worth, that's always been the case, right?
33:54
Like Tik Tok has always had allegations that they were botting. Yes.
33:58
>> Like as a platform effectively.
33:58
people would go on there and they'd be like getting a tremendous amount of followers, tremendous amount of just engagement broadly, far more than uh than they would have on Instagram with the same content.
34:13
>> And you know, some people would say, "Oh, that's cuz the Tik Tok algorithm is so good."
34:17
>> But uh uh and there certainly are a bunch of very real people on Tik Tok.
34:19
I don't I don't mean to say that it's all bought it, but uh the experience of using Tik Tok, a lot of creators will just naturally have >> six times as many Tik Tok followers as they do Instagram followers. >> Yeah. Yeah.
34:33
It does seem like the algorithm is set up to uh like serve you more content in a 10-minute session because you're more quickly scrolling.
34:42
And then there's also accounting issues like uh on some platforms if you just scroll past something for even one second that counts as a view.
34:49
On other platforms it might take three seconds.
34:52
On other views other you know platforms it might be 10 seconds a minute you might need to watch the full thing.
34:56
So there's always like accounting abnormalities there.
34:59
Anyway, if you want to stream on Tik Tok because it's Americano now, you want to bring, you know, some Oracle focused content to Tik Tok on live stream focused content, >> get on reream one live stream at 30 plus destinations.
35:10
[applause] If you want to multiream, go to reream. com.
35:14
>> Uh, this might hit you like a sack of bricks. Yep.
35:18
But, uh, breaking news, JD Vance is younger than Future. >> That is a crazy stat. 22.
35:25
Future is is straight up an elder now. >> He's ank. >> No, he's beyond. >> Oh, yeah.
35:32
He's an elder, I suppose. Yeah, you're right.
35:34
>> He's uh >> not quite an OG, but Oh, no.
35:35
It It goes It goes then OG then elder. >> Right. >> Yeah. >> Right.
35:42
>> Uh Gen Z are arriving to college unable to even read a sentence, says Fortune, reposted by Uncle Wales.
35:50
>> See if you can read this.
35:50
See if you can [laughter] read this.
35:53
>> See if you can read this. >> Try and read this. Wow. He can't. He can't. He can't do it. >> Slopped. Slopp.
35:59
>> I I I just I need like some subway surfers or something. >> Yeah, for sure.
36:03
>> I'm going to need some Subway Surfers [clears throat] to read this next sentence.
36:07
>> Anyway, Gusto, the unified platform for payroll, benefits, and HR built to evolve with modern small and medium-sized businesses. Get on Gusto.
36:17
Um, we have we have some drama that's continuing to unfold in the in the payroll space.
36:21
The Justice Department opens a criminal probe into Silicon Valley spy allegations.
36:25
Subpoenas seek information on allegations.
36:28
The deal valued around $17 billion recruited a spy inside a rival company.
36:33
This is a huge story last year and then it's been pretty quiet and both companies have just kind of been chug chugging along.
36:43
Um >> spending a lot on legal. >> Yeah.
36:44
So, the Justice Department opened a criminal investigation.
36:46
Uh grand jury subpoenas were sent out in recent weeks by Craig Mas Masakian Msakian uh the US attorney for the Northern District of California.
36:56
The documents show they seek information related to a spying operation that deal allegedly ran inside a rival company.
37:02
Ripley, an Irelandbased Ripling employee, in case you've forgotten, Keith O'Brien alleged in an affidavit filed in April that deal CEO, Alex, uh, recruited him and gave him instructions for what information to take from Ripling.
37:16
O'Brien alleged that other executives were involved in the spying plot, including his father, who is Deal's executive chairman and chief strategy officer.
37:24
A spokeswoman for Deal said the company isn't aware of a criminal investigation, but is willing to cooperate with authorities.
37:30
That's an interesting statement.
37:31
the the Wall Street Journal is reporting this and and and you find out from a Wall Street Journal reporter. That's that's wild.
37:36
Uh so the company has previously said, "We deny any legal wrongdoing and look forward to asserting our counter claim."
37:44
So deal says we didn't do anything wrong.
37:46
Of course, the affidavit from Keith O'Brien is is extremely dramatic.
37:51
There's that whole like uh you know, oh send that watch to London.
37:53
We're going to be like uh James Bond.
37:54
Like it's a it's a really dramatic read and uh you can go back and watch some old TVPN episodes if you want to hear our full take on that.
38:03
>> Yeah, it's interesting.
38:03
Uh >> they're not they're they're >> Yeah. >> Yeah.
38:08
I wonder I wonder uh what what information is actually available kind of publicly on this because like obviously in a situation like this you have both sides that are kind of like feeding the media >> their side of the story.
38:18
Uh >> but I mean the facts of the facts here like the Justice Department did open this uh because because the the Wall Street Journal confirmed that the Justice Department opened the investigation.
38:29
So >> um anyway, I think a lot of people weren't expecting this to last actually uh have any type of like criminal component. >> Yeah.
38:39
I think a lot of people were just expecting like a lot of drama, a lot of you know and they would eventually just settle. >> Exactly. Settle.
38:45
And like the worst case was like, okay, maybe it's like a like a, you know, like a series D size payment for Rippling, but they're both going to just keep grinding.
38:54
>> Um, but it seems like it's going to the courts. So, uh, we will see.
38:56
Maybe there will be, uh, maybe there will be, you know, courtroom sketches of these folks. >> Yeah.
39:02
>> Uh, anyway, uh, Nick, the chief >> OpenI, >> uh, has some breaking news from CNBC.
39:11
Uh, OpenAI chair Brett Taylor says AI is quote probably a bubble, expects a corruption in the coming years.
39:16
And Nick is he his camera roll is truly just filled to the brim with images of Sam Alman in various like like you know >> the guy has probably the largest collection of Sam >> Rare Alman shirt.
39:30
He has every photo that's ever been taken of Sam.
39:33
Uh and and Nick just is looo. >> Yeah.
39:37
But uh I don't know this could be true like you know who knows I wonder what what more of the context was that >> yeah I mean a Brett Taylor quote taken out of context turned into a headline [laughter] and then and then and then it's like >> nowhere of course would Brett Taylor be like oh yeah I think I think LLM usage is going to fall off a cliff. >> Yeah. >> Yeah. Yeah.
40:01
There's variety of different companies >> and kind of subcategories that could be overheated.
40:06
But >> yeah, you could take uh you could uh you could easily uh dig into that.
40:10
And he's like there's a bubble in like seedstage valuations like I can't get an angel check in at less than 50 pre like you know the bubble can take a lot of different shapes and stuff.
40:22
Who knows what he was actually commenting on.
40:25
Anyway, Crowd Strike your business is AI their business is securing it.
40:27
Crowd Strike secures AI and stops breaches.
40:32
Uh, another clip from Dennis from the Big Technology podcast.
40:34
He's taking shots at open air according to Euchen Jin.
40:40
>> Think actions think actions speak louder than words.
40:41
Going back to the original conversation we were having with, you know, Sam and others claiming AGI is around the corner.
40:46
Um, why would you bother with ads then?
40:48
So, that is I think a reasonable question to ask.
40:50
Um but I I I think uh look from our point of view we have no plans at the moment to uh to do ads if if you're talking about the Gemini app right uh specifically I think uh we are going obviously we're going to watch very carefully what uh you know the outcome of what uh chat are saying they're going to do um I think it has to be handled very carefully but think actions speak louder >> he's post AGI the clankers need to advertise to each other.
41:21
You got to do ads for the clankers.
41:23
Ads >> I mean it I mean the thing here is like OpenAI has to not only like figure out how to actually implement ads within the product, but they have to build out all the advertising like infrastructure, the platform infrastructure in order for people to run campaigns successfully and at scale.
41:40
So Google already has all of that.
41:42
It is far e like it it is what do you think it's like a h 100red times easier for Google to turn on ads in Gemini, right?
41:48
they already have all the customer relationship.
41:50
Literally any company that advertises online is already working with Google.
41:56
>> And so it's really just like you can just flip the switch.
41:57
And so I could easily, you know, don't have any inside knowledge, but I could easily see Google just like having it all basically ready to go and it literally just being like, okay, >> there we can launch this whenever we want.
42:09
>> There there is an interesting steelman here. Let me try and do it.
42:11
So uh you need the helmet.
42:14
>> I I I might need the helmet, but I think I'm good for now. So, so Sam and others.
42:19
Well, first let me tell you about advertising. Vibe.
42:20
co where DTOC brands, B2B startups, and AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like on Meta.
42:29
So, uh, the steelman on Sam Alman claiming that AGI is in the corn around the corner, but we still got to do ads.
42:36
Well, around the corner, even if that means 6 months, like if you have an incredible capital expenditure to get over that hump to create AGI, it's only 6 months away, but you got to do that last data center and you got to raise that last 50 billion and all of the investors.
42:54
>> Yeah, it's easy it's easy to say like we don't want to do ads when you have hundreds of billions of dollars in existing ad revenue coming in funding everything that you're doing.
43:01
So anyways, I I think this is >> I mean we can also debate whether or not ads will exist post AGI.
43:06
I would argue that they would.
43:09
But uh what do you think Tyler?
43:11
>> There was that headline about how OpenAI maybe they're thinking about like taking a percentage of the >> of the share of like the discoveries.
43:16
I don't know how they would actually do that or if it's like they're being serious at all.
43:19
But that's like much more AGI pill right than ads. >> Yeah. Yeah.
43:23
Oh, that Yeah, that's a good point. So they're doing both. They're doing both.
43:26
Uh anyway, New York Stock Exchange.
43:29
Want to change the world?
43:31
Raise capital at the New York Stock Exchange. Just just do it. >> Just do it. >> Just do it.
43:37
>> Uh apparently Vimeo uh almost everyone at Vimeo was laid off.
43:41
Uh >> including the entire video team.
43:43
I would assume that most most of their team so unfortunate.
43:49
I have some fond memories of being a teenager when Vimeo was like really >> Vimeo was so differentiated.
43:55
It was where you there was like a level of quality that it wasn't just >> I would go there to watch short films.
44:03
In my case, it was like surf like really it was like if somebody was putting a ton of effort into making like a surf movie or you know some snowboarding movie, it would be on Vimeo. >> Yeah.
44:13
And they wanted higher quality footage.
44:14
You could get higher bit rates 4K HD.
44:16
like they they were really on the front tier of that.
44:19
Yeah, I remember watching a lot of uh ski videos there.
44:22
There were some great ones and also just like it was a place where people would put their their short films.
44:25
They had the Vimeo uh like you know awards with the little wreath laurels that you could rest on.
44:33
Um but uh eventually, you know, YouTube just went everywhere all places.
44:39
is the ads went away for the people that care about that because they had premium subscriptions and uh ultimately the quality on YouTube just got better and better and better and now you can get 4K really high bit rate on on YouTube and it's indistinguishable from Vimeo.
44:51
So fewer and fewer uh fewer and fewer um ways to make a case for you know consumer adoption essentially like I I I I certainly would not recommend anyone who's uh making video content uh distribute on on Vimeo.
45:07
I I put everything on on YouTube because YouTube has a massive audience and it's discoverability.
45:13
>> Yeah, discoverability is just so >> high Harry has the meme for the moment.
45:18
He says but now we shall both surely drown said the frog. Lol, said the scorpion.
45:24
>> I don't think I don't I I don't think this is exactly right.
45:25
Like, if if you buy uh if you're a private equity firm and you buy an asset like this and you and you lay off the team, like you're likely there are still people that are going to be trying to extract the value from that asset.
45:38
It just might be a team on a different on in a different section of the firm or an outsourcing agency or something else.
45:46
I would be surprised if this means that Vimeo is shutting down.
45:50
And I would imagine that they're trying to continue whatever business relationships they have and whatever subscriber base they have. >> Yeah.
45:55
>> Um >> um >> anyway, >> Banjo says, "Vimeo was cool, but if you know about Vimeo, it probably means you're old."
46:02
>> And uh >> that's true.
46:04
>> That's certainly true. >> You know about Vimeo?
46:06
>> Yeah, I know what Vimeo is.
46:08
>> What's the last thing you watched on Vimeo? >> I have no idea.
46:10
Yeah, >> but No, but I remember.
46:11
Yeah, it was like like artsy films would be on there or something. >> Yeah, it was good.
46:15
Uh anyway, um app loving profitable advertising made easy with axon. ai.
46:21
Get access to over 1 billion daily active users and grow [applause] your business today.
46:25
Um what is what is all this?
46:28
So, uh Matthew Zaitelland says, "My basic model of modern artificial intelligence labs is that they are like emotionally intense graduate school programs but with unlimited money." Matt Lavine.
46:42
>> Matt Lavine is writing about this.
46:42
And Mary says, "My friend is dating a guy who works at one of the frontier research labs in SF, and his sole job is to think and come up with a big idea every six months." >> Capital B, capital I.
46:53
>> So his work day consists primarily of long walks spent pondering.
46:56
That's >> very Womanitis coded. >> That's amazing.
47:00
>> That's amazing. I mean that seems like honestly in the age of research in the ILAS world like this is probably a good use of time as opposed to there are plenty of people that will that will lock in and and you know improve make minor improvements to the consumer application or the consumer side of the
47:16
business but um >> yeah in a world where you have you know infinite minds uh when you're a manager of infinite minds what uh Satia was quoting >> notion co-ounder >> um yeah you're probably just walking ponder wondering thinking about what uh what the next set of uh tasks to assign to your to your infinite minds. >> Well, Epic Games and Google apparently
47:38
>> Well, Epic Games and Google apparently have a secret $800 million Unreal Engine and services deal and the quote in their scoop quote.
47:47
Sorry, I'm blowing this confidentiality.
47:50
What a crazy quote to give to a Verge reporter.
47:52
Uh but we're going to dig in.
47:55
Uh Addie Robertson and Sean Hollister have the story.
47:57
A judge is questioning whether Epic Games and Google are settling their longrunning antitrust fight, partly because of a previously unannounced partnership involving the Unreal Engine, Fortnite, and Android.
48:09
In a hearing in San Francisco today, the court revealed that Epic and Google have struck a new deal that apparently includes joint product development, joint marketing commitment, and joint partnerships.
48:19
California Judge James Donato expressed concerns that the agreement, which he indicated would involve Epic quote helping Google market Android and Google quote uh Google's newly quote eps using Epic's core technology, could have led Epic to soften its demands for changes to the overall Android ecosystem.
48:38
Donado allowed Epic and Google to keep most of the details of the plan under wraps.
48:43
But during the hearing, he quizzed witnesses, including Epic CT CEO Tim Sweeney and economics and economics expert Doug Burnernheim on how it might impact settlement talks, revealing some hints in the process.
48:56
Quote, "You're going to be helping Google market Android, and they're going to be helping you market Fortnite.
49:02
That deal doesn't exist today, right?"
49:04
Donado asked Burnheim, who answered in the affirmative.
49:08
He also described it as quote a new business between Epic and Google.
49:12
Sweeney testimony cracked the mystery a little further.
49:14
He referred [snorts] to the agreement as relating to the metaverse, a team, a term Sweeney has used to refer to Epic Epic's game Fortnite.
49:22
Epic technology is used by many companies in the space Google is operating in to train their products.
49:28
So, the ability for Google to use Unreal the the unear the Unreal Engine more wholesome.
49:33
Sorry, I'm blowing this confidentiality.
49:34
Sweeney [laughter] said, oh, that's a great line. Um, yeah.
49:38
I mean, we we we've seen a number what was it?
49:41
What is the what is the deep mind model that does that plays the games for you that I'm in the market for because I don't have any time to play video games.
49:48
So, I need an AI agent to do it for me. Uh, they have a number.
49:52
So, they have Genie 3 which generates basically a vid a 3D world that you can walk around in. >> Sema 2.
49:59
>> Sema 2 will play the game for you.
49:59
And both of those uh should in theory benefit from uh using Unreal as the backbone.
50:07
>> Elon's probably pretty excited about that as well, right? >> Why?
50:10
>> Because he likes to play on accounts that are >> Oh, yes.
50:13
ranked, but he all the time. >> Yeah.
50:17
So, instead of needing to hire someone, you could you could bot your account.
50:20
People already do that with uh like aimbots and stuff.
50:22
Uh usually you get banned, but uh makes a lot of sense in terms of training Google's generative AI models.
50:29
use Unreal, create a bunch of virtual worlds, walk around in those, interact in those, use them as reinforcement learning environments for agents, and then bake that out into a bunch of different models that can be used for a bunch of different things.
50:41
I'm I'm I'm super excited for all of this.
50:42
Um, but uh it's it's just funny the way it's coming out.
50:45
Anyway, if you need a reinforcement learning environment, you got to go to Label Box.
50:50
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50:54
Labelbox is the data factory behind the world's leading AI teams.
50:56
So, Coinbase established an independent advisory board on quantum computing and blockchain.
51:03
Quantum computing, if if built at scale, have the potential to reshape entire industries.
51:06
We were talking to Kathy Wood about this a little bit yesterday.
51:09
From finance to healthcare to material science and national security.
51:13
For blockchain, the stakes are especially high.
51:14
The cryptographic foundation that secures digital assets today could be challenged by the advances of the coming years.
51:19
At Coinbase, security is our highest priority and preparing for future threats, even those many years away, is crucial for our industry.
51:27
Most people, I think, handicap the quantum thing at like 2030, 2032, 2040.
51:31
I think Kathy Wood's estimate was 2040 for serious quantum adoption.
51:36
Even if you get on a Moore's law type uh adoption curve.
51:38
Um, but >> yeah, Nick Nick Carter's been super vocal on X about about quantum just being like the biggest uh headwind to like further Bitcoin price appreciation. >> Yeah.
51:51
I mean, there's also this question, maybe I'm just like very I'm like super out of the loop, but like if you can crack like whatever the the Bitcoin or or any like blockchain with quantum, like surely you can also just get into like, >> you know, banks or like tons of like actual like things that are like probably way more important than than crypto.
52:10
Like it's like if we have a world where you have like these incredibly powerful quantum computers like is crypto actually the most important thing that you need to be worrying about or is it like the nuclear codes that are >> so surely those are stored >> Yeah, you're probably right with the nuclear codes but uh in terms of just like fiat stored in a bank there are a series of backups that are offline.
52:32
There's even paper backups at certain points and so uh like the financial system although they probably don't want to talk about it does have the ability to like effectively roll back.
52:38
So if there was like some massive quantum hack and like all the Morgan Stanley or JP Morgan accounts or Goldman Sachs accounts were like drained uh they would just be like let's revert but you can't do that on a blockchain necessarily.
52:50
So uh but there is still the dynamic of like what happens if you crack Bitcoin?
52:56
Like how much are you stealing?
52:56
How many new bitcoins you >> Yeah.
52:58
I mean really if you like steal any bitcoin bitcoin just goes to zero.
53:02
probably the point, >> but that's obviously still a threat.
53:05
Even if you just have some malicious actor who's just like, I'm going to take out a short position on Bitcoin, tank it, and profit from that.
53:12
That that could potentially uh be disruptive, certainly disruptive to Coinbase business.
53:17
So, good to see them taking it seriously.
53:19
Anyway, MongoDB, choose a database built for flexibility and scale with best-in-class embedding models and reankers.
53:25
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53:28
Uh, let's go to Scott Besson.
53:30
He was complaining about the food in Davos and he did an interview on Real America's Voice, I guess, with Jack.
53:40
Uh, and >> so, so again, if you're looking at Davos as though it's a bunch of kick streamers.
53:47
>> Yes, that is the correct >> has effectively been just clip farming [laughter] >> this whole time.
53:54
>> Okay, let's watch the Scott.
53:55
>> They don't like carnivores here in Davos with the with the food.
53:57
You're you're not a huge fan of the food here, I heard, by the way. You know, I I No.
53:59
And [laughter] no, I you know, I I I I don't know if you remember a couple years ago, one of the recommendations from the the the Davos elite was we could all be eating bugs and insects. >> Yeah. The insect food. >> Yeah.
54:14
I tell you, after after a couple of days of the food here, I I may switch to to bugs and insects.
54:20
>> You take the insect food up.
54:22
>> Unless that's what it is.
54:23
>> Or or I'm going to bring snacks fell off. They did.
54:26
Do you remember they were really people really pushing this?
54:28
They were saying, "Oh, the protein content is so high."
54:34
>> And I think humanity rejected it.
54:34
Uh >> well, you know, you know the story of Magic Spoon.
54:43
>> Were they going to put Cricket? No.
54:45
Originally, >> they did a previous company called Exo. That's right.
54:49
>> It was an American insect food company.
54:52
Uh, they made some protein bars using Cricut flour from pulverized house crickets. Uh, >> house crickets. >> House crickets.
54:58
I guess >> that sounds like you're taking the pets.
55:01
>> They did a Kickstarter in 2016.
55:01
They raised $55,000, which was more than their $20,000 target. Uh, they raised uh $5.
55:09
6 million in series A funding. I wonder from who.
55:12
There's a article in the journal.
55:15
There's an article in Business Insight. Nas invested. No way.
55:20
Legendary rapper Nas invested in a company that makes protein bars out of crickets.
55:24
>> Okay, so on the Exor Protein site now, all their bars are sold out.
55:28
No, a couple you can still get banana bread cricket breakfast >> company was acquired in 2018. Aspire Food Group.
55:36
>> You can get salted caramel. >> Yes. >> Cricut bars. Okay.
55:40
>> And you can just get one pound of Cricut powder.
55:41
[laughter] >> You can get a quart.
55:44
>> They should just get into selling live crickets.
55:45
Just ju just deliver them.
55:45
get your enemies addresses and just deliver them.
55:51
Uh, no, but uh, so I I I think >> 1800 cricket >> I think they would they I mean the team certainly found a niche a weird like, you know, breakthrough.
55:59
You're going to get a lot of earned media with a with a bizarre ingredient like that, but the ultimate traction I think people just have an aversion to bugs and and they it just conjures, you know, images of bugs crawling around like it. >> Yeah.
56:12
And so they sold the company, but then they started Magic Spoon, the not Qriket based, >> which just immediately ripped. >> It ripped. Fantastic business.
56:22
>> And I'm sure you've seen a ton of uh you know podcast ads about Magic Spoon and everyone's familiar with that company.
56:28
>> Uh so you know they they if you're in crickets, if you're in bugs, pivot to cereal, I guess.
56:32
Uh and that's what Besson's saying.
56:34
He's saying he wants Pop-Tarts.
56:35
Pop-Tarts basically Magic Spoon.
56:37
Magic Spoon might even make Pop-Tarts. I don't know.
56:38
Uh, Entropic published a new constitution for Claude.
56:43
The constitution is a detailed description of our vision for Claude's behavior and values.
56:46
It is primarily written for Claude and used directly in our training process.
56:52
>> Was it written by Claude?
56:52
Did Claude write its own constitution?
56:56
>> That's a good question. You'd think yes.
56:57
>> Rahul over at RAMP said basically TLDDR is I love you, you love me.
57:01
We're a happy family with a great big hug and a kiss from me to you. quote.
57:08
[laughter] You say, "You love me, too."
57:11
>> You really know the Barney song. >> It's amazing.
57:14
>> I didn't just sing it as a kid. I studied it. >> You studied it? Yeah.
57:18
>> Um, uh, more importantly, >> yes, >> Buzz Balls is [laughter] >> incredibly important. Thank you.
57:25
>> Is selling a $35,000 diamond engagement ring shaped like its drinks.
57:28
The ring will be auctioned on eBay starting February 3rd.
57:32
Uh, so I don't how is it how is it actually going to be?
57:35
Is 35k like the >> opening opening bid or or maybe it's it's $35,000 worth of diamonds.
57:41
It cost them $35,000 to make it and they're going to put it on eBay.
57:46
Starting price 100 bucks and then it'll get bid up, I guess. I don't know. Yeah.
57:50
>> Um proceeds will from the sale will benefit a heart related charitable cause.
57:56
>> It's kind of odd for an alcohol brand to be like we're we're >> I don't know. That's cool.
57:59
I mean, if you're if if anyone out in the audience is wanting to propose and like doesn't really know how to is struggling to figure out like the right kind of like moment or way to propose.
58:11
>> This is like a buzz out of the box.
58:14
>> That's the woman in your life.
58:16
>> If she catches it, she has to marry you. >> She has to say yes.
58:20
>> Uh, is this rage bait? Is this good marketing?
58:22
Do you think this is good for Buzz strategically? What do you think?
58:26
Uh, I don't know if it's I mean I I I find plenty of moments to talk about Buzzball already. Okay. So unnecessary.
58:33
I mean it is it is gimmicky but the whole brand is sort of gimmicky to begin with and so it doesn't feel out of context.
58:40
It doesn't feel like they're trying to be a serious company and then they did something wacky on the side and I'm confused.
58:46
This like feels within the the within the Buzz Balls lineage within the Buzz Balls uh brand world very much so. Uh anyway. Whoa.
58:56
>> If you're heading to Cisco AI Summit, be sure to bring some buzz balls because on February 3rd, Cisco is bringing together leaders from NVIDIA, OpenAI, AWS, and more to discuss the future of the AI economy. >> We will be there.
59:09
>> The whole thing will be live.
59:09
We will be there for >> Did you know >> what >> do you know who came up with the idea for Buzz? >> Absolutely not. I have no idea.
59:18
>> A public high school teacher. >> What?
59:19
Uh Marily Kick, a former public high school teacher, has become one of America's richest self-made women after selling her ready to drink cocktail business buzz balls for at least 500 million. >> 500.
59:30
>> What started as a side hustle has now transformed into one of the biggest brands of the ready to drink cocktail industry.
59:36
Kick founded Buzz Balls in 2009.
59:39
Inspired by a simple idea while grading papers by her pool.
59:44
I thought I shouldn't have this glass container out here.
59:46
I should have a plastic pool safe type of cocktail.
59:50
From this spark of inspiration, Buzz Balls was born.
59:52
Fun, high-proof cocktails served in colorful plastic spherical containers.
59:56
Buzzballs quickly gained popularity is now sold at supermarkets, liquor stores, and convenience stores.
1:00:03
>> She says, "I've been living the American dream. We've built a legacy.
1:00:05
We've become a contender in a space [laughter] where women never went."
1:00:09
Brutal >> says the brand has grown intentionally distributing 29 countries with an estimated annual revenue of $500 million. >> Wow.
1:00:18
>> This is incredible story. >> Monster company.
1:00:21
>> In April of 2024, the drinks firm uh Sazzarak acquired Buzz Balls in an allcash deal 500 million.
1:00:27
Though kick suggest the figure is much higher. >> No way.
1:00:32
[laughter] >> Kick is an absolute dog.
1:00:34
It has also cemented her place among America's richest self-made women with Forbes estimating her net worth at 400 million after taxes.
1:00:42
So yeah, of course >> she's going to 10x that. Get involved.
1:00:46
I'm sure she's cooking >> on her next idea. >> Run it up.
1:00:50
>> Uh Kick's journey is remarkable because she never raised money from investors.
1:00:54
She bootstrapped her business on the show.
1:00:56
>> She used a small inheritance, maxed out.
1:00:58
>> Where is the founders podcast episode about her?
1:01:00
>> And took out a loan from a local community bank to get started. I scraped and scrambled.
1:01:04
He says, "I took every bit of every penny I could find and poured it into the business." >> That's incredible. >> Amazing story.
1:01:11
>> Her unique company started making a profit in the second year with 1 million in sales and 100k in profit. Not bad.
1:01:14
By 2014, the brand was expanding quickly and the drinks were sold at major retailers.
1:01:20
By 2019, annual sales were over 100 million.
1:01:25
>> Get her on the Davidson Center. >> Wow. She I mean, she's elite.
1:01:26
A key to Buzzball success was owning its supply chain.
1:01:30
>> [laughter] >> She vertically integrated on day one like >> like most like DOC founders in in in [laughter] California like can't figure out how to get off a copacker.
1:01:40
>> She moved production of the patented plastic spheres and the spirits used in buzz balls in house to ensure the brand's quality and reliability.
1:01:45
Despite many investor offers over the years, Kick held on to her company until she found the right partner.
1:01:50
I wanted somebody that was going to come in and have big guns. >> Big guns.
1:01:54
She's she explained sro which owns over 400 brands brought the resources and the expertise to scale buzz balls. >> Wow.
1:02:03
>> The kick and her family are still part of the business.
1:02:04
I didn't sell because I didn't like what I was doing or wanted to leave.
1:02:07
She explains I sold for the exponential growth and because it's selfish to hold it it back. It really has legs.
1:02:13
From a teacher grading paper by the pool to a multi-millionaire sent me kick story shows the power of a good idea and the determination to make it happen. That's hilarious.
1:02:26
>> That is an incredible story.
1:02:27
>> We got to get her on the show. >> I love it.
1:02:29
>> Uh, let me tell you about Console.
1:02:31
Console builds AI agents that automates 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets.
1:02:38
And before we move on to our uh to our lightning round, let's debate Kylie Robinson's latest post.
1:02:48
She says, "Do you think if the AI companies IPO this year will get insert frontier lab arenas like the Crypto. com arena? What do you think?
1:03:00
Should there be a Gemini arena, an anthropic arena, an open AI arena? Should they do this?
1:03:06
Is this good for the brand?
1:03:07
They're already buying uh Super Bowl ads, so it doesn't seem out of the question.
1:03:10
What do you think the probability is?"
1:03:12
Yeah, I feel like uh these type of uh advertising on like an arena like that, you typically see this with like somewhat commodity like products that are sure >> that are in large markets but are uh you know in the case of like crypto. com.
1:03:31
>> They're just compet like the the products crypto.
1:03:33
com is very interchangeable with Coinbase, right?
1:03:38
give them Bitcoin or whatever digital assets you want.
1:03:42
And so they're really just competing on brand entirely.
1:03:43
And like >> the way that you're seeing the market evolve like I don't I don't know that.
1:03:52
>> Yeah, they're competing on technology like how does the model actually answer? What are the benchmarks?
1:03:55
They're competing on product like how does the app work?
1:03:58
How what what are the mechanics? What can you do?
1:04:00
Can you generate images in there or not? Can you generate video? How good is the video?
1:04:05
Uh does it does do deep research quickly?
1:04:06
Like there's a million different things. How's the voice mode?
1:04:09
Like they're they're definitely playing like a product race right now.
1:04:11
There is a marketing race. >> Yeah.
1:04:13
I guess the question is >> at the same time, >> was there ever was there any of like the OG search companies?
1:04:17
Did they ever get out and did Yahoo ever have a >> I don't know. It's interesting.
1:04:22
But uh I do know that uh it's interesting that she mentions the Crypto.
1:04:26
com Arena here in Los Angeles, the former Staple Center, because Crypto.
1:04:30
com is not a public company.
1:04:32
So there's nothing that says that you can't buy an arena before you go public.
1:04:35
Uh, who knows, maybe we will have a Vanta arena by the end of the day.
1:04:41
Automate compliance and security.
1:04:44
Vanta is the leading AI trust management platform and I'd love to head to the Vanta arena no matter where it lands.
1:04:51
Um, anyway, we have our Lambda lightning round starting now with base 10.
1:04:58
We have Turin, the co-founder and CEO of B 10 in the reream waiting room.
1:05:02
Let's bring him in to the TV Ultra. How are you doing? >> Hey, how you guys? >> Good to see you. >> Welcome back. >> Welcome back.
1:05:11
>> Thanks for having me again. >> You've been busy. >> You've been busy. Give us the news.
1:05:15
>> Yeah, look, we've had a crazy year.
1:05:15
Um, you know, we're 10x over last year.
1:05:20
[laughter] >> Um, >> 10x alert.
1:05:22
Hit the gong for the 10x. >> Sorry to interrupt.
1:05:29
>> All right, back back to you. >> Back to business.
1:05:32
Last time I was on here, I was telling you about our series D.
1:05:33
We've raised our series D now.
1:05:37
>> We've raised 300 $300 million is a $5 billion valuation >> uh led by IBP and Capital G with participation from Nvidia and a few others.
1:05:46
>> Um look um it's just been I just to remind you guys where like what we do.
1:05:51
>> Yeah, please um AI infrastructure platform.
1:05:53
We focus on production grade inference serving the fastest growing companies in the world.
1:05:56
So a bridge open evidence cursor notion clay gamma writer you you know you look at that that crop of companies and how they're growing and you know we're playing a supporting role in making sure that they can run their models >> as fast and reliable as possible.
1:06:08
Um and you just on the back of that um you know we realized how big this could potentially be. >> Yeah. Yeah. Go ahead. >> Take it Yeah.
1:06:17
Take us through how quickly enterprises are ramping up running their own models.
1:06:22
Like if we go back to 2022, uh Google had Palm internally.
1:06:26
They hadn't really launched Gemini.
1:06:29
OpenAI had GPT3 and then they launched Jad GPT.
1:06:35
Uh but Microsoft had you know they were vending GPT4 through uh through Bing and stuff like but big companies were not really running their own large language models. Is that roughly correct?
1:06:47
But now it feels like we're in the hundreds of companies.
1:06:52
But out of the Fortune 500, like how many how many companies are actually running their own models at this point in time?
1:06:58
>> Yeah, I look I I I think it's still relatively small but growing growing rapidly.
1:07:03
I think, you know, if you go and look at like when we go and speak to enterprise customers, it's still incredibly early.
1:07:08
But I think what they are doing is that they're looking at, you know, the these other companies that, you know, they, you know, you and I would probably agree that are the for future Fortune 500 kind of eating their lunch and if they don't like figure out how to move at that pace, I think they'll just be left behind.
1:07:24
And so like what we we focus really really heavily on you know those really fast growing companies because we we think not only are they going to be the future Fortune 500 but the Fortune 500 are going to look at them as like how do we bring these models up to speed as quickly as possible. >> Yeah.
1:07:41
And so I mean that makes perfect sense in the case of uh of a company like Cursor.
1:07:45
Obviously they're they have a ton of training data.
1:07:47
They have a need for a custom model.
1:07:48
Uh are we years away from someone like a Coca-Cola or you know developing their own or how does that how does that play out?
1:07:57
that how does that play out? Yeah, >> I I I I think look there's two things that are happening right which is >> like if you go look at open AI anthropic adoption at these at these company it is there is definitely it is definitely there um once you've proven out these
1:08:10
use cases internally then you just have to think about better faster more specialized more secure running on prem all these sets of problems and so you know that is coming like is it like six months away is it 12 months away is it 18 months away who knows um I think the other trend
1:08:27
>> that is pushing ing um the enterprises online is RL which is like how how do you take these open source based models um and RL them and get them to be as good if not better than um these frontier models for very specific tasks and you know that's a big focus for us as well we recently made an acquisition
1:08:44
around that um but we do think that'll be a big driver of enterprise adoption of these >> mod walk me through the push back from a large enterprise uh that says yeah it's great I I can train a custom model on my business, but I looked at the smaller models for a variety of benchmarks. And
1:09:03
And it feels like the big models just sort of are better at the small models tasks as well.
1:09:11
Like I should just use the latest and greatest big model for everything because the frontier is better at the specialized tasks as well. It just oneshots things. >> Yeah, totally.
1:09:22
Well, I I think the um and I I think honestly a lot of the times they'll be valid there.
1:09:26
You be like, "Yeah, like I I I don't disagree with you."
1:09:30
I think what what you will see though is that as the frontier is getting better, open source is already >> um you know, if you go look at the open source models that are out there today like the GLMs, the coins and um and the deepse it's not like they are 18 months behind. Yeah.
1:09:45
>> You know, some would argue that they're, you know, within a quarter and for certain tasks are better.
1:09:49
The complexity actually comes around honestly from enterprises.
1:09:53
Not so much like can I get a better outcome. Yeah.
1:09:55
It's hey >> you know these large um lab companies have massive inference teams. >> Sure.
1:10:02
>> Um do I have the skill set to be able to run the service at scale? Yeah.
1:10:05
Within my premise with all my enterprise requirements. Got it.
1:10:10
>> That's ideally where we can help in and be that partner to them to bring them online. >> Okay.
1:10:14
So, walk me through uh what it looks like when a Fortune 500 company says, "Okay, we're getting off of just a generic model.
1:10:21
We want to do something that we have control over the inference.
1:10:25
We're working with base 10.
1:10:25
We're doing uh you know, we're doing some custom RL.
1:10:30
There's going to be some proprietary data in there. Who's involved?
1:10:31
Are they hiring you or consultant to set up the RL environment?
1:10:36
Who's doing the training?" Walk through all that.
1:10:40
>> Yeah, I think just engineers and infrastructure engineers.
1:10:42
I think that that is like one of the realities right now is that I don't engineers who don't know how to grapple with AI just you know they don't I don't know if they exist in the future to be honest.
1:10:50
Um but um that being said like for a lot of engineers it's like hey how can we make it as easy as possible for you to take this custom model deploy it scale it up either you know in our cloud or within your own cloud and so that is you know the job of the software.
1:11:06
the job of the software. We have a a really amazing for deploy team that is very happy very happy to help um if necessary but our goal is also just you know to enable them to do these things and and that is happening I think it's early though especially the enterprise >> from uh from your view do you think we
1:11:23
need more Neolabs like based on the conversations that you have with customers >> okay I'm look more models are great I think more people developing models are amazing look I I'm making a met uh with my career with this company on on the long tale of models and that their existing models outside of you know two amazing companies. Um and so I think
1:11:45
Um and so I think more people developing models just gives consumers and developers more choices down the line and like look do we need more of the same? Probably not.
1:11:54
But like you know all all these companies have their own takes um on on on the problem.
1:12:03
uh help me understand your current thinking around model routers, routing inference across uh big heavyduty models that might be very expensive like using all parts of the parade of frontier.
1:12:14
Uh what are you seeing on uh on the inside on uh are are companies trying to handle parceling out the workloads themselves or do they want that to be something that's off the shelf that you sort of provide?
1:12:30
What are some of the trade-offs that people are considering these days?
1:12:33
>> Yeah, look, I I think it's a spectrum.
1:12:33
I think, you know, the the most advanced companies are 100% doing that.
1:12:37
They are breaking up they're breaking up their >> their tasks u almost like model by model and then figuring out how to route.
1:12:47
>> I think less sophisticated folks um or people earlier in their journey, yeah, probably better way to put it um are relying on other people to do that.
1:12:53
And you know, the model the model companies are doing this themselves.
1:12:57
I I think um the place where I struggle a bit is like you know some of these routing things are just you know routing for failover which is hey model just stop working. >> Sure. Sure. Sure.
1:13:08
>> But like we we believe that like reliability like should should be table stakes. Yeah.
1:13:12
For serving models and you know ideally you don't have to build across what happens when X model provider falls over Y model provider falls over and have that t and that is a different routing problem.
1:13:23
Routing based on capability is happening.
1:13:24
it is happening outside the model.
1:13:27
It's happening inside the model and as the longtail model comes on come online for specific model tasks.
1:13:34
I think there's more and more going to be the case that that is being handled by inference company or inference platform like banan as well. >> Yeah.
1:13:42
I mean that's certainly happened in the database market like you have a big postgress installation you don't have a my SQL installation there as like a backup but you might have a reddest casting layer in front of it right. Yeah.
1:13:50
Um, so, uh, what is what help me understand that at the hardware layer?
1:13:56
Uh, I know you're you have some insight into Nvidia's strategy here.
1:13:59
I'm very interested in uh how you or other partners, other uh folks in inference might be thinking about the future of Nvidia's like big powerful racks versus their more legacy chips that might be depreciating, but you could still run a great model on it versus some of the more exciting stuff that's happening with Grock in the future. >> Yeah. Yeah. Yeah.
1:14:21
Look, I I don't have a ton of strategy. They're very good. I could hypothesize. Okay.
1:14:26
You know, look, they're amazing partners to us.
1:14:29
I I think we we are chip agnostic and we think look every every um task and it will have different requirements from a latency perspective from a cost perspective. Yeah.
1:14:42
>> Even what type of model runs on it and so yeah so like we use A100s we use A100s but we also use E200s and GB200s and as >> as you know we get these you know new these new types of chips or across we'll be working on them as well.
1:14:55
Like if you think about the Nvidia graph stuff, you know, what are they solving for?
1:14:58
It's like, you know, it's kind of breaking out pre-fill and decode.
1:15:01
You're using GPUs for pre-fill, you know, the computebound problems.
1:15:05
You can sac saturate the GPU.
1:15:07
You can do batching and have really good throughput, but then you have the LPUs or like the gro chips or the decode which are memory bound.
1:15:15
You're not doing a lot of new math per token.
1:15:16
Why this is hard is that that's a pretty complex um orchestration problem between of handling um workloads that are doing stuff on GPUs and on LPUs.
1:15:28
I think Nvidia's, you know, obviously built amazing software around this um to break out, refill >> and decode Dynamo is the name of the software that know we work pretty heavily with.
1:15:38
But like I think that would just be a new type of chip that the chip providers >> um provide.
1:15:42
And you know I think um one thing I don't think you can understate is how much how much how powerful um Nvidia supply chain is CUDA is >> CUDA is and and their their ability to >> um you know be dynamic with architectures changing and I think yeah >> um you know we we have very very much bought into that ecosystem and what that enables especially for inference and customers.
1:16:07
Can you give us your take or any insight on how companies at the application layer are kind of wrestling with uh the like laziness specifically like everyone at this point has experienced you know product like uh ask asking you know basically uh you know wanting a product to be able to do something that you know it can do and then and then uh you know running into this like laziness element.
1:16:30
What uh >> what what do you mean by laziness?
1:16:34
I I don't quite get that.
1:16:35
Uh I would say like you know thinking about uh let's let's pick the you know biggest uh not to pick on anyone but like the biggest consumer AI app chatbt right like everyone has experience asking chatbt to do something that you know it can do >> and like sometimes it will just kind of like circle around or or like not really get to the thing that you want it to do >> um even if you're paying for it on like the max plan or something like that.
1:17:01
And so and and so I would like I would assume that every company at the application layer >> that gets to the point where they're caring about margins >> is like starting to get to the point where they're like okay like you don't always cuz sometimes the model can be lazy and you're like great like >> yeah you got me quick >> you got me you got me what I needed and I can just move on.
1:17:21
Yet other times it's like wildly frustrating because it's like, you know, asking if like it's like asking an employee to do something at five o'clock and they're like, "Oh, like, you know, [laughter] >> I I mean, isn't that like to to me that's like what defines a great application layer company, right?" Like the >> Yeah.
1:17:38
The ones that aren't good are just wrapping around, you know, GPT and you or or whatever model.
1:17:42
And, you know, you as a user are left to figure like deal with that laziness.
1:17:47
with that laziness. I think the best application layer companies, you know, be >> it's like serving the right amount of intelligence for the >> tax and and setting up the harness and how to use it for the problem that your user is asking you to solve for them or
1:17:59
you were trying to solve like you know I if open if if a company like open evidence was just you know doing something the lazy way that would not only be really really expensive but they wouldn't do a really good job of solving that problem for their users and it wouldn't be a great business in the long term. like you know what makes these
1:18:13
like you know what makes these companies so good is how they use the models, how do they use multiple models and how they architect that to you know the thing the user is asking them and then >> then layering in how do we do this efficiently so we can make a business out of it and like you know to me there is going to be a great divide in solving that laziness problem.
1:18:31
I think it's a good way to put it actually.
1:18:34
>> You said two things that I'm sort of having trouble reconciling.
1:18:36
you said that uh you're chip agnostic, but then you also praised the the the dominance of the CUDA ecosystem.
1:18:43
Uh is it is it getting easier to implement LLMs in a way that run on multiple chipsets?
1:18:50
We've obviously seen uh really strong performance from deep mind on the TPU stack and anthropics talking about TPU now.
1:18:58
Um but for a long time the narrative was like, oh, it's going to be really cumbersome to replplatform off of off the CUDA ecosystem.
1:19:04
How are you thinking about uh yeah just multi-chip architectures these days?
1:19:11
>> Yeah, I I mean look I I think it is getting easier >> but it's not it is not easy you know.
1:19:17
[laughter] >> Welcome to entrepreneurship >> but you know like you know it's a and like look just sitting on top of like you know that's why like Nvidia is such a great partner for us.
1:19:24
It's like sitting on them doing the stuff you know we were I mean did you guys play FIFA or anything like that when you were growing up with Madden?
1:19:31
Like >> I was more of Counterstrike, Call of Duty. >> Sure. Starcraft. >> Yeah.
1:19:37
>> It's pretty amazing that when we are doing stuff for GPUs today, we're downloading from this a website looks exactly the same as the Nvidia driver page. >> Oh yeah. [laughter] >> 2000.
1:19:47
But that is also amazingness of it of like how rich that is and how powerful it is.
1:19:51
And I think that is, >> you know, yes, it is getting easier and like like a diversification is great everywhere downstream, but also like Nvidia is just amazing at what they do.
1:20:01
and and and >> and and and being able to run a model on AMD does not necessarily mean that it will inference at a lower total cost per token or vice versa might be a little higher on certain models blah blah blah uh and so yeah there's all these different trade-offs but that's why companies come to base 10 correct >> totally and that's why the open source ecosystem is so important right that's why you know like
1:20:25
>> you know you you mentioned databases earlier like I think similar to databases >> at the in the fullness of time open source has the fastest run times >> and so I think that will like with Nvidia you will see that which is like you know do you know who's going to be really good at running stuff on Nvidia chips is going to be Nvidia who's going to be really good at stuff running stuff on AMD chips is going to be AMD and so
1:20:46
working with these providers of chips I think to get the best run times from them >> um is very important and I think like this cross compilation stuff while important you know I I'm a little skeptical I'd say it's just like you know like it's fant principle for me to think that we would be better at running um software on Nvidia chips than Nvidia or or better >> yeah at the lowest level obviously there's all the orchestration software
1:21:10
stuff that we are building that we think is very important but we also very very invested in those ecosystems >> well I believe in you I think you can do it but no I I take your point of course uh well congratulations on all the
1:21:20
progress thank you so much time to hop on the stream and uh have a great rest of your day >> sure you'll be back on >> any day now [laughter] >> hopefully not Um, thanks for having me and um, appreciate you guys. >> We'll talk to you soon. Goodbye.
1:21:33
>> We'll talk to you soon. Goodbye.
1:21:35
>> Phantom Cash, fund your wallet without exchanges or middlemen and spend with the Phantom Card.
1:21:40
Up next, we have >> Bryce. >> Bryce from Nominal.
1:21:45
I believe Bryce is the brother of the previous guest from Nominal, Cameron McCord. >> Technology Brothers.
1:21:56
>> Wait, no, not brother. >> Sorry. Uh, co-founder. co-founder. >> Got it. Okay.
1:21:59
Well, you know, you build a business with someone for a while.
1:22:03
People just assume you're brothers, but uh anyway, >> sec second spouse is what I like to say, but >> yes. Yes. Exactly.
1:22:08
Thank you so much for taking the time to get where you call.
1:22:12
>> Where are you calling in from >> guys?
1:22:14
Uh hello from Daytona, Florida. >> No way.
1:22:19
>> You are in you're >> you're in the garage.
1:22:23
You're in the pits at the Rolex 24. So fantastic. Um, we are here.
1:22:28
So, I'm a phenomenal uh, you know, the company Cameron, Jason and I co-ounded.
1:22:33
Uh, we announced our partnership this week with Pratt Miller Motorsports. >> That's amazing. Congratulations. >> Thank you. Thank you. >> Great timing. >> Um, >> oh, come on. >> Come on. >> Come on. >> That's fantastic. >> Yeah.
1:22:48
If if you uh if you don't know who Pratt Miller Motorsports is, you know, they are the heart and soul of the Corvette racing team in the Ma Race series.
1:22:57
So, you know, this is this is fullon heavy metal sport dynamism right here.
1:23:04
>> This is >> Hey man, I'm about I'm about 30 feet from a McLaren.
1:23:07
Anyway, all you know, this entire garage is full of pretty probably every every famous sports car, you know, but um I don't know if you know, but the most dominant of them all for the last 30 years has been this yellow Corvette right here. >> Very nice.
1:23:22
>> And that yellow Corvette. Um >> look at that. Wow. >> No sticker. >> There we go. >> Incredible. >> Uh how's good stuff?
1:23:31
>> Have you caught any of qualifying yet or have you just been too locked in?
1:23:38
Yeah, this is the epitome of uh forward deployed because we just sent a founder to make sure this went perfect.
1:23:42
Um but it's been it's been really fun.
1:23:44
Yeah, I've been here for a couple days.
1:23:45
Um we are so think like last night we were running our late night practice sessions.
1:23:52
Uh so Daytona itself is a like brutal race to start the season. It's a 24-hour race.
1:23:58
Um, I'm not sure if you like me have now seen a best picture nominee, but uh, in the F1 movie, Brad Pitt's F1 movie, the first seven or eight minutes is actually Sunny Hayes, Brad Pitt, racing here at the Rolex 24.
1:24:13
>> Um, and it's him racing the night shift. So, >> yeah. >> Um, Amen.
1:24:16
Um, yeah, him racing night shift.
1:24:19
So, you know, last night's practice session, every team gets one night to go out and actually like see the race conditions at night.
1:24:24
um you know different temperature profiles, totally different um you know race profile.
1:24:31
You have like I found out like at turn five right here you have headlights from the parking lot that you have to deal with like >> yeah it's been a wildly interesting journey but um you know on the you know on the nominal partnership side it's also been just really fun to see like you know we've we've had a lot of wonderful meetings and things about strategy and race strategy and this and that but like you know we are watching it come alive here.
1:24:53
Um, so a lot of the practice and qualifying and everything else has come back to uh, you know, how do we help them use a lot of data to win?
1:25:01
>> And the the pressure is on, right?
1:25:03
They're going for the fifth fifth win this weekend. Is that right? >> Impressive.
1:25:10
>> We've been following we've been following a little bit mostly the mostly the Shopify team.
1:25:13
We've been following a lot Toby and really there's a lot of tech people out there. It's great. >> There is.
1:25:21
Yeah, you the the tech community here is like small but strong.
1:25:25
It is like the epitome of motorheads.
1:25:25
Um you know it's people that late in life, you know, found thermodynamics in their life and are like this is the coolest thing ever.
1:25:32
This is way cooler than Kubernetes. Like >> it's the best.
1:25:35
[laughter] >> It's the best. Yeah.
1:25:36
And and for us, we're we're the timing is great.
1:25:39
We were at the track uh with with a friend of the show uh Paul on on Sunday and we were just doing like really quick laps.
1:25:50
We'd go out for like five, you know, five 10 laps and then take a quick break and kind of like settle down and we'd be spinning out on like the [laughter] like the fifth on like >> and like realizing like actually like when you're going like these endurance races, it's it's >> also just like from an engineering perspective, you know, you take the car out for a couple laps and you let it cool down and check the tire pressure.
1:26:11
Like 24 hours is endurance, not just for the humans, but for the actual vehicle.
1:26:16
So can you talk a little bit about uh what goes into bringing that level of performance to the vehicle, what your role is, who the key players are in your world, who are you interfacing with? >> Yeah. Oh my gosh.
1:26:28
Um okay, so yeah, 24 hours is brutal. You are right.
1:26:31
Um you know, the the rest of the season there there is a 12-h hour race in the season.
1:26:36
I think that's in Sebring, but you know, the rest of the season is 1 2 3 4 5 6 hours and you you know, you rip the car as hard as possible. So big 24-hour race.
1:26:44
the strategy you're bringing in is much more around, you know, of all the things you have to care about more than anything, the cars get beat to hell. But, uh, it's fuel.
1:26:51
Um, you know, it's like this this bad boy will burn a full tank of fuel about once an hour.
1:26:55
Um, and so a lot of the pitch strategy, a lot of like the totality of the race comes down to really like managing all 24 hours well.
1:27:04
Um and so our our role in this, you know, we we come alongside this absolutely elite engineering team um and help them, you know, make those make those calls.
1:27:15
Sometimes it's the high, you know, highest level.
1:27:16
Um you know, do we need to switch drivers earlier?
1:27:18
Do we need to do something else?
1:27:19
I have a >> I'm going leave another Oh, okay. I got a fun one. last night.
1:27:23
Um, one of the things we were looking at is I can't give away all the secrets, but I know everyone says they do this, but Pratt Miller like actually does this and does it better than anyone else.
1:27:32
But, um, last night they were talking about, you know, managing fuel from a like, uh, consumption standpoint.
1:27:38
So, think like, you know, we're watching how throttling is happening, a bunch of other things.
1:27:44
think when this comes into play is the car is, you know, you're behind someone else and your goal ends up being how can I get them to stay on the throttle as much as possible cuz if they burn more fuel than I burn >> and we both go into the pits together, the long pole in the tent of a pit stop is refilling the tank.
1:28:02
>> So they refill for 5 seconds, we refill for one second and we run right past them. Interesting.
1:28:07
>> Um, and that type of stuff like that is not a like trivial thing to do.
1:28:09
Like that is complex math happening.
1:28:11
That's tons of different telemetry, you know, like nominal.
1:28:15
And to be clear, like Prep Miller has building been building elite software here for 25 years.
1:28:20
I was in like the third the second grade when they started building race software, you know, like um this is much more around like >> teams like this are amazing because they just are obsessed with winning.
1:28:33
Um, and so this whole partnership has really blossomed out of like that openness.
1:28:37
You know, like we have plenty of wonderful, elite, amazing customers that have interesting things that they've built and like, you know, there's a journey with getting them to like really adapt the way that we think engineers should work in nominal where Pratt Miller is like, "Okay, cool. I have all of this." >> It's an engineering.
1:28:53
It's an engineering sport.
1:28:55
It's an engineering sport.
1:28:55
Like I imagine a lot of those engineers could go in a second and walk down to Elsa Gundo and be hired on the spot, right? So, um, >> amen.
1:29:05
The amount of, uh, the amount of people that have left the Pratt Miller team to go to like the Anderles of the world, there's a lot.
1:29:10
So, um, you know, bypass light, please stay. >> Please stop poaching.
1:29:17
>> But, uh, zoom out for me and and, uh, try and make a little bit clearer uh, the involvement of nominal in this, how the products being used, where the end points are.
1:29:28
Are you working on manufacturing new parts for the car, managing supply chain, uh testing, like what else uh goes in and then maybe contextualize it with the work that you do with other defense contractors and other businesses? >> Yeah, totally.
1:29:44
So, think like Pratt Miller selected us and brought us in think like how can we transform how engineers and all of their partners so they they don't just build these two cars, but they also build three more Corvettes in the field for other teams.
1:29:55
uh you know how can they come in and like rethink fundamentally testing telemetry decision-m across race operations.
1:30:01
So these are producing terabytes and terabytes of data this weekend.
1:30:05
Um you know we have to do a whole lot with that during the weekend to make really good calls.
1:30:09
And way more importantly we need to like catalog and catalog and index and manage like all of this volume of data.
1:30:16
And then like you know what we do for the team is like it's not just about these 10 races a season.
1:30:21
like you win when you have the same system integrated into your driver sim.
1:30:26
>> Brett Miller's also been way far ahead in the way that they think about driver sims in the sports car racing league.
1:30:30
So all of the data from the driver sim is making it back into nominal.
1:30:34
Um, you know, we're helping them do like actually like rethink the like procedural operations of that and automating a lot of pieces of that.
1:30:40
And this is like almost verbatim, you know, how companies in aerospace and defense, how companies in energy, you know, how our customers go get this work done across the board.
1:30:51
It's just they have like win or lose on the line.
1:30:53
So, um, they just they rip it out of our hands.
1:30:58
>> What about the other simulations that go on during a race series?
1:31:00
I'm thinking back to the F1 movie.
1:31:02
Most people are familiar with the scene where the F1 car is in the wind tunnel.
1:31:06
Uh, everyone can visualize the wind or the smoke flowing over a vehicle.
1:31:10
Is that the type of data that someone could pull into nominal and then analyze or are you acting more as just like a data layer and then there's another visualization software that would pull for that specific task?
1:31:21
I imagine that there's a lot of point solutions still in place, but how do you fit into that? >> Totally. Okay.
1:31:28
I'll I'll tell you about the old world and we'll go to the new world.
1:31:31
So, um, they have a team here that manages like all of the Corvettes on the field.
1:31:36
So, not the Pratt Miller race team, it's like the Corvette racing team.
1:31:39
Um, you know, I last night was sitting with them and watching them flick through somewhere between six to eight different pieces of software to like root cause a problem.
1:31:46
Um, a little bit of analysis here, a little bit of data management here, go find the thing over here.
1:31:51
Like, nominal has been built on the principle of like clarity really, really fast comes with an into stack.
1:31:55
Um it is how you manage the data.
1:31:58
It is how you monitor the data and it's how you analyze the data.
1:32:01
So >> you know these engineers happen to nominal um and they're doing everything from figuring out you know yes wind tunnels and other things are important that's you know it's ultimately like small small parts of the team thinking about something like aerodynamics you know like way more of the team is thinking about um you know how are these settings affecting you know this particular force.
1:32:21
So it's pressures, temperatures, voltages, vibration, um video data, log data, um you know, all the different word people use in engineering, multimodal, you know, like all the different types of angles um that you need as an engineer to make a judgment call.
1:32:35
Um but at the end of the day, it's like, you know, we want to help them make really good judgment calls and then have a really good record of why.
1:32:42
And if they can do that really fast, like we've kind of succeeded in the partnership.
1:32:47
>> You mentioned like terabytes of data coming off the car.
1:32:49
What's the telemetry like?
1:32:51
Like how is that actually is it like a are they connected to Wi-Fi?
1:32:53
Like how how do you get the data off the car while it's on the track? >> Oh man.
1:32:58
Um that is a fun complex thing.
1:33:02
>> Um okay so you know every race actually just has a lot of regulation here.
1:33:05
Um so like NASCAR you can't pull any data off the track.
1:33:10
>> Um F1 has like a mesh network where they purchase ripping streams all day long.
1:33:17
Huge really high data rates like kind of all the things.
1:33:19
Um, sports car racing is actually like a really interesting middle ground here where um, they do have telemetry coming off the car that, you know, race engineers are sitting in double decker, you know, fold out pit stations, >> TV and stuff. >> Oh, yeah.
1:33:32
With everything around them, it's like monitoring monitoring the situation.
1:33:36
>> They're situation monitors. We love it.
1:33:38
>> It's it's the epitome.
1:33:38
Um, and yeah, so they'll they'll have data come off the car, but then the really interesting part is like it can't be that high rate of data.
1:33:44
They're only allowed to bring very specific sources.
1:33:46
Um, and then every time it comes in for a pit stop, um, they'll do things like they put an umbilical into the car and that is like actually how they have a secure communications line with the driver.
1:33:57
>> The rest of the race, everyone can listen to everyone else.
1:34:00
>> But if you want to if you want to give your driver a little edge and do it and then >> Amen.
1:34:05
[laughter] Um, and and then if you want to get the high the high volume data off, there's a technician that goes in and like, you know, pulls out a data stick and puts in a new data stick and all that starts go getting processed. Phenomenal. And another tool.
1:34:18
So, um, that's the that's the fun. >> That's amazing.
1:34:21
Well, good luck to everyone.
1:34:23
Thank you so much for taking some time out of a busy day to come chat with us. >> Yeah.
1:34:27
So many so many more questions. This was awesome. Well, that's great.
1:34:29
My only ask is please I need you to if you don't have a team in IMSA I need you to pledge allegiance to the yellow Corvette.
1:34:39
>> That's the only thing plans for the weekend.
1:34:40
Rolex 24 I love an American manufacturer.
1:34:44
>> He loves he's uh he's got his eye on the the ZR1 X already. So >> it's a good car.
1:34:50
>> Anyway, >> great stuff. Great hanging, Bryce. Good luck this weekend.
1:34:53
>> Have a good rest of your day. >> Finn.
1:34:55
AI AI, the number one AI agent for customer service.
1:34:57
If you want AI to hust to handle your customer support, go to Finn. ai.
1:35:03
>> And up next, >> go in the chat. Forward deployed CEOs. That's the new meta. >> I like it.
1:35:08
Our Lambda Lightning round continues with Max Sparrow, the what do we call him? A slop janitor. Pangrim Labs. Yeah, slop janitor. Pangram Labs. Max, how are you doing?
1:35:17
Thank you so much for taking the time to hop on the show. How you doing? >> I'm great. I'm great.
1:35:22
Yeah, just cleaning up slop on X. >> It seems like it.
1:35:25
Uh, when did this project start?
1:35:28
I feel like I've been start I I've seen most of the viral stuff uh in the last few weeks, but have you been building this company for a while?
1:35:35
Give us a little bit of the prehistory.
1:35:37
>> Yeah, so the company's been around for about 2 years.
1:35:39
We've been building models to detect AI generated content and just building doing a lot of the research. >> Yes.
1:35:46
[snorts] >> And trying to be the most accurate in the market.
1:35:48
But it wasn't until like end of 2025, December 29th actually was the first day where I launched the Twitter bot and it's really just blown up since then.
1:35:58
People are using it on articles on basically all these long form posts that people are just posting slop. >> Yep. >> Online.
1:36:06
>> Are are you already monetizing it?
1:36:07
Because I imagine you have a ton of attention, ton of people that wind up on the tool.
1:36:10
Uh I interact with it mostly through I see the screenshots that people post or I see your post.
1:36:14
Um, but are there businesses who have an incentive to partner with you?
1:36:18
Are you talking to big platforms, small companies?
1:36:22
Like, uh, have you have you started like what what does the business look like today? >> Yeah. Yeah.
1:36:27
So, individuals can either sign up for a free account on Pangram.
1:36:31
They can get a Chrome extension and check things uh in the browser or you can pay $20 a month to get access to um, a lot more checks.
1:36:40
>> Uh, but we also work with internet platforms.
1:36:42
So, one of our biggest customers is Kora.
1:36:44
customers is Kora. So they send most of their content through Pang just to understand like is it AI generated or not because that's against their policy and they want to keep the platform high quality and so yeah we've had a number
1:36:55
of API users a bunch of different internet platforms >> large and small people basic like either like officially rling on you or like basically DIY reinforcement learning by just uh generate me an essay go into Pangram it's at 100% make some changes and remove the m dashes. Okay, it went down
1:37:15
Okay, it went down to 70%, rewrite a couple sentences and just keep iterating until I get it down to 0%. >> People are trying.
1:37:23
I think that's part of the fun is like that this is such an adversarial space.
1:37:26
And so like part of keeping up with it is just making sure Yeah.
1:37:31
We're robust to these gpo attacks and this like RL >> Yeah. >> Uh on the model. >> Yeah.
1:37:37
Uh, does it make you mad when people are sharing an article on X and it's obviously written by AI, but they're just like, "This is the be this is the most >> well-written essay I've ever studied I've ever read on this topic. Changed my life. >> This changed my life. >> Oh my god." Infuriating.
1:37:53
And the person probably spent like 15 seconds just typing in chat GPT. Make it really deep. Make it really good. >> Yeah.
1:38:02
>> The worst one that I read was >> Yeah. Yeah. Tell us.
1:38:04
was this like um the one that went viral about the like supposed Uber Eats or Door Dash whistleblower. That's right.
1:38:10
It was like they wrote on Reddit.
1:38:12
Their entire post was AI generated and they're talking about how like you know the company's so evil.
1:38:17
Um and it I think it went viral just because people wanted to believe that it's true even though it's like obvious slop.
1:38:25
>> Wait, were you able to clock that as AI just personally or with Pangram?
1:38:28
because when I read it, it didn't jump out to me as AI generated, but there were other flags that just seemed like factually in uh inaccurate or uh just inconsistencies and like logical >> to me it immediately read like fanfiction.
1:38:44
It was like I'm on a I'm in a public library laptop. It's like who does that?
1:38:51
>> Uh like you can just post on Reddit anonymously.
1:38:53
Like Reddit is not going to come and like arrest you. I don't know.
1:38:57
>> Anyway, uh yeah, but yeah.
1:38:57
How did you clock it personally with the tool both? What were you thinking? >> Yeah. Yeah. I was reading it.
1:39:02
I'm like this reads like a sto this reads like a story and not like real life somebody writing this and then I checked it with Pangram said 100% AI.
1:39:09
I went to the comments and there already other people were saying that you know this is obviously AI. >> Okay. Yeah.
1:39:16
And and then uh yeah talk about the the the impact like are you is this an AI safety project?
1:39:22
Do you think that there's uh there's like a societal uh you know disaster that comes from AI slop?
1:39:30
Is it something we'll adjust to?
1:39:32
Is there a white pill good outcome here?
1:39:34
How do you like process the the the like philosophical part of your work? >> Yeah.
1:39:39
So, I mean I think a lot of the big labs are already doing a great job on the internal AI safety side, which is making sure Claude doesn't go out and like autonomously decide to kill everybody.
1:39:49
But I think there's this like application layer, the like external AI safety of like can people use AI for harm?
1:39:58
And I think this is a great harm that people just like aren't really like thinking or even trying to tackle.
1:40:01
I think like this threatens um the internet as we know it today.
1:40:06
I I don't if you're aware of like dead internet theory of just the idea that it the internet is just going to become bots talking to bots and it's like a ghost town where people can't participate anymore because their voices are drowned out by bots.
1:40:19
And I think we're very much at risk of this if we don't have any technology to solve it.
1:40:25
>> What do you think about the inverse?
1:40:25
I I posted that uh you could probably drive someone insane by just quote tweeting everything that they say with the 100% AI panggram screenshot because so I I I write a daily newsletter and I write about 500 words and I always I never use AI to write it or even proofread it. There's typos in there.
1:40:44
Um, so people will still accuse me of using AI and so we're like maybe we need to live stream me typing it or something and I don't know, it just doesn't matter.
1:40:53
But it is sort of infuriating when you take half an hour, you write out some thoughts and then someone's like, "Oh, this is AI or share the prompt."
1:41:00
Even if they're joking, it's like kind of gets under your skin.
1:41:03
What What do you think about that? >> Yeah. No, it's it's annoying.
1:41:04
And I mean I think that's another reason why like we're building this technology is there are other AI detectors out there that have 1% or 5% false positive rate.
1:41:11
And so they'll like incorrectly flag a lot of things even like the Declaration of Independence.
1:41:18
And so we so Pangram has a 1 in 10,000 false positive rate.
1:41:21
So the goal is we are almost never flagging something incorrectly.
1:41:25
If we say it's human like we're we know it's human. >> Yeah.
1:41:30
>> Are you working uh with any of the big dating apps yet?
1:41:32
I imagine that uh this is something they'd want in kind of like actual like on on the user side as you're uploading because they want to not have AI generated content because that would create a bad experience for users broadly.
1:41:48
>> I cannot say I' I've heard some like about some issues from people who work in dating apps. Sure.
1:41:55
>> And I think um the issue is growing.
1:41:55
I heard an interesting story from a a former uh dating app engineer who said that there they had bot problems 10 years ago.
1:42:05
People would just go and write a Python script to just swipe on everyone and just send like basic messages.
1:42:09
Um and he said that when they detected bot activity, if they ban them, the the the botter would just create another account.
1:42:16
So what they did was they put them in like bot hell basically where they would only talk to other bots, which is a funny solution because then their system says, "Hey, I'm still on the app. It's still working.
1:42:25
I'm still seeing all the API requests. Everything's working.
1:42:28
Um, but they're just only interacting with other bots.
1:42:31
But you can imagine getting false positive into that and just it being the worst experience.
1:42:35
You're like, I didn't meet anyone.
1:42:36
Everyone out of this app's a bot.
1:42:38
So, there's a whole bunch of funny funny nuance things.
1:42:39
I do want to ask about uh image image uh generation, image detection.
1:42:44
Uh, that somewhat relates to >> Yeah. Yeah.
1:42:46
So yeah, what I was trying to get at is like where I I assume over time like most AI most written content will have been run through some type of model before it's published almost like a spell check even.
1:42:58
Uh so I'm trying to think about like where where do you really not want AI content, right?
1:43:01
Like I don't care if somebody uses >> an uh a Gen AI to make like a head shot, right?
1:43:09
Like if they just want a head shot that looks somewhat like them, >> they might go into Photoshop anyway and add some color correction, increase the contrast, >> pimple or something.
1:43:19
>> Not that big of a deal.
1:43:19
But where where I do think is like the probably the most pressing issue right now.
1:43:24
It's just like any anything news related.
1:43:26
any anything news related. So if like if you're if you're sharing things that are like news or or any content that people are using to understand the world >> like I could imag like like are we moving to a world where you'll have to add like a panggram watermark to the to
1:43:41
the post like >> like like is that the kind of behavior that we want because like if you if if an AI generated image goes up two million people see it and then six hours later it gets community noted and says like okay this is this was uh generated by AI, it's too late. Like 2 million
1:43:57
Like 2 million people like, you know, may thought it was real.
1:44:02
>> That's a huge problem.
1:44:02
And actually like this is happening today.
1:44:04
So if you know like all the like the Russian troll farms where they're like posting comments and like uh news articles, they've basically Russia has expanded this to basically just use LLMs that they've fine-tuned themselves.
1:44:18
And they've we've seen news websites come out of Russia that just have 50,000 articles that are completely AI generated.
1:44:27
Most of them are like normal news and then some of them are really pushing the like pro-Russia anti- Ukraine stance and they're just posing as like random like Oregon local news and >> Yeah.
1:44:41
And these are crazy and and they're popping up faster than uh we can take them. >> Yeah.
1:44:46
>> Yeah. like we can actually the white the white house shared an AI generated image >> AI modified image yes >> AI modified but >> got community noted on axe got quote tweeted but uh yeah I mean it's an increasing increasing issue uh what uh what is the state of potential bots on
1:45:04
other platforms uh it's great that you've got the bot working on X but uh it seems like we really need it on Facebook I I you know if there's a couch the size of a room that is in the shape of a gorilla There should be panggram in the comments saying this is AI generated. So the uh
1:45:18
So the uh that the elderly generation perhaps is protected from slop.
1:45:26
>> So next up for us is Reddit and LinkedIn. >> Okay.
1:45:30
>> So I think Reddit there's a bunch of viral posts that are AI generated.
1:45:32
I think people know that they can karma an account and then sell it to a bot farm or something.
1:45:40
And on LinkedIn, I think it's just funny because like people are like genuinely posting slop. Like they're not bots.
1:45:47
They're just like Oh, yeah.
1:45:49
>> posting AI slop every day. >> Yeah.
1:45:52
>> Uh are what is the state of of wiring up a bot on a modern social network these days?
1:45:59
I feel like a lot of the APIs have closed down a fair amount.
1:46:00
closed down a fair amount. uh is it something where you need to have a relationship with the business to actually run a you know a useful bot that I would say I as a user I want this it's not malicious activity but you're still getting API access you could slop yourself if you wanted to you have the access so what's involved in actually spinning up a bot and keeping it online
1:46:22
and keeping it posting regularly without hitting rate limits >> so for Twitter is actually pretty easy um I mean besides having to pay $200 a month And then if we pass some limit um well now they have usage based API but
1:46:37
otherwise before this the next tier up was $5,000 a month which is absurd but um >> I for a for a startup that has funding if you're growing like it's it's not you it's not >> prohibitively but you can't do that as a hobbyist. >> Sure. >> Sure.
1:46:54
>> But yeah it was not too bad with X and then the other platforms seem to be a lot more locked down.
1:46:58
So, LinkedIn, I've been waiting for API approval for two weeks now.
1:47:03
>> Um, and Reddit kind of same thing.
1:47:03
But, I mean, Reddit seems to be pretty bot friendly, so I think we'll get there eventually.
1:47:09
>> I've never seen a reply bot on LinkedIn, but >> have you been surprised by conversations with any of the platforms?
1:47:14
Because in some ways, they just want more content that's engaging.
1:47:17
And so, there's kind of like this dilemma where they might say like, "Yeah, we're looking to crack down on on, you know, fake imagery."
1:47:23
But in reality, they're like, "Okay, this is driving engagement.
1:47:29
>> This is not like, you know, it's a it's it's like even with X, people have always said like, do do they really want to crack down on bots or like do they just say they want to crack down on bots?"
1:47:40
Because in some ways, like it's just driving notifications for people that might not otherwise be having a lot of uh activity.
1:47:47
>> One man's slop is another man's fame on [laughter] >> the the LinkedIn trust and safety folks seemed so resigned.
1:47:52
It seems like they're having such a bad time.
1:47:54
Because in every single text box there's a little like write with AI button.
1:47:59
So like in I want to compose a post I write 20 words and then have it expand it out into like a long essay.
1:48:06
Or same with like inmails.
1:48:08
They'll AI generate inmails that are customized for the person's profile.
1:48:12
And so like they can't actually do anything around like AI slop or using AI as a signal because it's so integrated into the platform at this point.
1:48:21
And I think to the detriment of the platform, like the quality of content there is so low now.
1:48:27
>> How many words how many words of text do you actually need to detect if something's a >> Yeah, I've seen some people tag uh Pangram with like someone will post like one sentence and it's just [laughter] like I don't know.
1:48:38
I don't know if it's a hallucination or something, but it's it's a funny funny meme.
1:48:40
So, so our our official line is 75 words, but I made it smaller for Twitter. Yeah.
1:48:46
Because obviously there's so many uh short posts and typically >> what is going to happen is just going to say it's human like >> unless it's like really obviously AI or like as an AI language model, >> Sure. Sure. Sure. Yeah. >> Yeah.
1:49:01
The main it it almost doesn't really matter because >> like I really want to know if something's AI if it's really long. Yeah, totally.
1:49:09
I only want to read this for the most part if I know that somebody put in a lot of effort to like, you know, actually >> say something.
1:49:16
>> And there is the flip side which is like I I'm if if if someone does a really cool deep research report in one of the LLMs and they just shared a link to it and they're just like, "Hey, I was interested in this particular research report. I generated it.
1:49:28
You can just click here and read exactly what I what what the prompt result was."
1:49:32
Uh, I might be down because I like reading deep research reports sometimes if if I prompt them and I might be interested in what you prompted.
1:49:40
Uh, the funniest uh the funniest short Panggram uh uh request is always someone will say, you know, is this article AI?
1:49:47
And then Pangram will come back and say, yeah, it's 100% AI and then someone say, is that is is the request to call Pangram AI?
1:49:55
And Pangram will say like [laughter] no, it's not. It's human.
1:49:57
No, >> but uh anyway, so so so what's next?
1:49:59
Uh what's next with the business?
1:50:03
What's the state of the company?
1:50:04
How large is the company?
1:50:06
Where where do you see this all going?
1:50:09
>> Um, so far we're I mean we're pretty small.
1:50:11
We're still seed stage nine people.
1:50:13
Um, but uh since July we've grown 25x in terms of users and number of queries. >> There we go.
1:50:27
We've seen a lot of we've seen a lot of interest basically in this um consumer level interest just like I want to know what's slop or not.
1:50:34
I I'm not like a teacher. I'm not a writer.
1:50:36
I just want to know that what I'm reading is authentic.
1:50:40
And so >> what's next for us?
1:50:44
>> In my opinion, look forward to a Chrome extension that's like ad block but for slop. >> I like that.
1:50:49
>> It's going to automatically slop block everything that's slop on your on >> on the internet. You own sloppern. com. >> I do not. >> You should. >> It's not for sale.
1:50:59
Somebody else somebody else beat you to it.
1:51:00
But uh >> somebody has it. >> Oh well.
1:51:04
>> Well, congratulations on the progress, the virality.
1:51:06
Uh I love seeing it and thanks for all the hard work.
1:51:08
Uh it's >> really really doing uh good for the world >> for sure >> in the slop era. >> Yeah. >> Thanks so much.
1:51:15
>> Have a good rest of your day. We'll talk to you soon. >> Talk soon. >> Bye.
1:51:19
>> Let me tell you about Plaid.
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1:51:31
>> Next up, >> next up, >> actually >> we our next guest will be in the reream waiting room.
1:51:38
>> Still waiting on Russ from >> In the meantime, uh we have some massive news.
1:51:43
Johnny Carson's former LA estate just listed for $40 million. Little teaser. The mansion section.
1:51:49
We will be getting to it later in the show, but uh the Los Angeles estate that late night TV legend Johnny Carson once called home has hit the market for a dash under 40 mil.
1:52:01
All proceeds from the sale have been earmarked for three charities.
1:52:04
Cedar Sinai's medical center, the David Gaffin Foundation, and Share, which supports disabled, abused, and neglected children.
1:52:10
Uh Compass is sharing the listing.
1:52:12
He's a longtime host of the Tonight Show, which and he died in 2005 at age 79.
1:52:17
an absolutely legendary uh talk show host.
1:52:21
Uh big inspiration for me.
1:52:23
If you haven't listened to the Johnny Carson uh episode of Founders, you absolutely should. It's fantastic.
1:52:29
Uh also, we we re we previously reviewed his other house uh the Malibu compound that recently hit the market for $110 million.
1:52:37
Um >> still sitting on the market.
1:52:39
So, originally built in 1950 for Mvin Loy, the late film producer and director, best known for his work on The Wizard of Oz.
1:52:49
Have you seen The Wizard of Oz? >> YES. >> WOW.
1:52:52
>> BUT I think I was like forced to watch that in school at some point. >> Yeah.
1:52:56
The Yellow Brick Road, Dorothy. It's Toto. It's good.
1:52:58
Uh the the estate rests, this particular estate rests on 1.
1:53:03
5 acres in the prime East Gate Enclave.
1:53:05
A gated driveway bolstered by a security booth empties at an expansive motor court with two garages with room for four vehicles with sprawling stucco and stone accented structure at its center offering six bedrooms and 11 bathrooms.
1:53:20
It's 9,000 square feet across a single level.
1:53:22
It's introduced via a marble clad foyer with access to an elegant wet bar equipped living room that wraps around to a cozy wood panel den.
1:53:32
I like that the sound of that den.
1:53:34
You love a wood panel tent.
1:53:36
>> I love wood paneling generally.
1:53:36
Ideally, mahogany, the official wood of business.
1:53:40
>> We need We need a mahogany sponsor.
1:53:43
Truly >> huge missed opportunity.
1:53:44
They've been mahogany strongest soldiers. >> We love mahogany.
1:53:48
Uh from there, a spacious living room sports a fireplace and pocketing doors spilling out to a pillared loia.
1:53:54
Loia, I'm not familiar with that word.
1:53:57
While a formal dining room connects to a kitchen with an eat-in island and a breakfast nook, a soaring rotunda flows to a posh primary estate, which has a fireside sitting area, and dual walk-in closets and baths.
1:54:10
It has a tennis court, >> of course, >> a basement with a wine celler, detached two-story guest house that once housed Carson's office.
1:54:17
Uh, the amenities continue outdoors.
1:54:19
The manicured grounds host a sund deck encased pool and spa flanked by an open air cabana cabana with a fireplace as well as a lighted tennis court and a viewing pavilion holding a kitchenet and powder room so you can view the uh the tennis that's played.
1:54:34
Per the Wall Street Journal, Carson had to convince Joanna to relocate from the east coast to the west coast.
1:54:38
She was truly a New Yorker at her core, so it was hard to move her out to California.
1:54:43
Uh the nephew said who's of >> one and a half acres in Bair. Will that do it?
1:54:49
Not a bad not a bad option.
1:54:49
Uh well there are some other there are some other stories in the uh in the mansion section which we should go through.
1:54:57
Uh first let me tell you about railway.
1:55:01
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1:55:09
>> I loved hanging with Jake yesterday.
1:55:10
>> He is potentially a Joe Rogan CEO.
1:55:13
Fantastic conversationalist. Fantastic.
1:55:16
uh the way he breaks things down, tells stories.
1:55:18
I I really enjoyed that conversation. He'll be back.
1:55:19
He's he's on a generational run and congratulations to him again on the good news.
1:55:25
Uh so, the Call of Duty creator Dave Anthony has a custom Bair mansion.
1:55:29
It just sold for $22 million.
1:55:29
Uh and we will tell you more about this property uh after our next guest joins because we have Russ from LiveKit >> in the TVP Ultradom.
1:55:41
[music] Welcome to the show. How are you doing, Russ? Yo, Jordan. Uh, how you doing? It's great to be back. Good to see you guys. >> Thanks so much. Uh, first kick us off. Give us the news. What happened, >> dude? The news.
1:55:54
Uh, Live Kid is a unicorn. >> Woo. >> Whoa.
1:56:04
a $100 million series C at a $1 billion valuation led by Index Ventures, Salesforce, Altimeters in, Red Points in, and you're now a billion dollar company. How does it feel? >> Feels amazing. >> Is the job finished? Is the job finished? >> Yeah.
1:56:19
Overnight true overnight.
1:56:20
>> True overnight success. >> No, definitely not.
1:56:22
It's days zero, but yeah, it took 20 years. Um, pretty incredible.
1:56:27
>> What were the key growth unlocks, the key KPIs?
1:56:29
What was the first slide in the deck that got the the deal done?
1:56:32
Uh is there a break in the graph or has it just been continual growth and you're ready to take the next step?
1:56:40
>> Yeah, I think it's really been kind of uh I think like voice AI has really just started to grow and explode and you know I kind of uh I sometimes refer to us as the accidental AI company because uh >> we never meant to be an AI company.
1:56:53
Um we were video conferencing live streaming infrastructure and then we started to work with OpenAI on Chhat GPT voice mode and uh everything changed at that moment. Um >> yeah.
1:57:06
>> What what uh what do you see as a key uh like user experience UI features to a great voice mode experience?
1:57:12
I I I I deliberately daily drive all of the major LLM platforms now and I'm starting to notice little subtleties about does this one have uh the ability to go back 15 seconds, forward 15 seconds, make it like a podcast player, more familiar UI.
1:57:30
What do you think is the most important for uh a potential customer to if they're implementing a voice experience?
1:57:37
How much should they make it feel like a podcast versus uh you know an avatar that they're interfacing with?
1:57:41
um what's your what's your feeling on that?
1:57:45
>> I think it depends on the use case.
1:57:45
So I think if you were to separate it into two broad buckets, I think that there's like the personal assistance, right, that you kind of talk to as a friend or a companion for those kinds of use cases, I think feeling very humanike.
1:57:56
So latency I think is an important factor across both like B2B use cases and B2C use cases.
1:58:03
But um I think especially true in the B2C use cases, you're you kind of expect that a an assistant you talk to is going to feel like talking to a human being.
1:58:13
Um and have like a level of empathy that is not always necessary in a B2B use case.
1:58:19
So for a B2B use case, I'll give you an example like if you're trying to do patient intake at a hospital um using an AI >> call it on the phone like really the goal the the job to be done there is to get on my doctor's calendar, right?
1:58:31
It's uh do you need it to sound like a human or to respond with the absolute lowest latency possible?
1:58:38
No, you need it to be reliable.
1:58:41
So, you need to make sure that it's going to actually, you know, qualify the the user calling in, make sure they have insurance, um figure out what's uh their uh, you know, affliction and then get them onto the the doctor's calendar, you know, 99.
1:58:54
999% of the time or 100% of the time.
1:58:57
And so the [clears throat] reliability uh of the voice agent is most important for the B2B use cases.
1:59:02
And then maybe like the the empathy and realism is is uh more uh critical for for kind of these B TOC use cases.
1:59:12
>> What are your predictions or keys to success with the new Siri?
1:59:15
There's been a bunch of news about uh Apple did a deal with Google. They got the best model.
1:59:22
They got a great model uh powering it, but there's a lot of work that they need to do on the actual voice experience side.
1:59:28
Uh what what would your be what would your best practices be for Siri v2?
1:59:36
>> Siri v2 I think like uh the two most important things I think the realism aspect is is going to be there.
1:59:40
I mean if they're using a model from Google like Gemini live uh their their kind of voicetooice model is quite good.
1:59:47
Um feels quite realistic.
1:59:49
feels quite realistic. maybe uh one area where it could use a a bit more it could it could use a bit more empathy uh in some places I think and they just uh acquired a company um called Hume in the space which has a pretty strong like kind of
2:00:06
>> yeah that's right >> yeah yeah the licensing deal so they that that model has a lot of like emotion and can does like sentiment analysis in real time and so I think I think that'll be an important unlock for for Apple as they're using the the Google model for for this uh new Siri. Um I think the other thing is just like
2:00:23
Um I think the other thing is just like having access to you know the right knowledge and reliability.
2:00:27
Like the thing that just kills you with the original version of Siri is >> it's not reliable.
2:00:32
It like can't do half the things and sometimes it it does like a web search when you actually just want an answer and it it's uh so I think like the the reliability of it and and making sure it has access to the right tools and can invoke those tools at the right time.
2:00:46
I think that's going to be another critical thing.
2:00:47
But you know Apple's Yeah, >> pretty incredible when they when they focus and try to nail an experience.
2:00:51
Um, so I think I think they'll I think they'll get it done.
2:00:56
>> One one interesting thing about Siri is uh there there is a woman who voiced Siri, there's like a singular voice and I think everyone uh no matter how much they use Siri, if they hear the voice, they're they're familiar with that identity.
2:01:09
How do you think about companies that offer uh either one singular voice and they just build a brand around it and that is really an embodiment of this particular AI system.
2:01:21
They give it a name and a personality and it has one voice versus giving the consumer the option to have multiple voices or even steer the voice over time with like real-time sentiment analysis.
2:01:33
>> Yeah, I think it depends again on the use case.
2:01:35
So I think I'm glad you brought this up.
2:01:36
So for Apple for like Siri 2. 0 0, right?
2:01:38
We're talking about >> um we're talking about a digital assistant or a voice assistant that is running at like the scale of the entire world, right?
2:01:46
Like Apple devices are everywhere.
2:01:49
>> And so when you think about a delivering a great experience at scale like that or at that level of scale, >> you have to think um about kind of how do you meet the user where they are.
2:01:59
So to speak on voices in particular can't just be one voice.
2:02:04
I mean like uh it has to speak different languages. Well, right. That's one thing.
2:02:09
It uh culturally like um you know, you have to think about accents and like some of the paralinguistic cues, you know, if I say um or the way that I the way that I speak >> also varies or the way someone speaks varies across cultures as well, varies across languages.
2:02:25
There's different customs.
2:02:26
And so if you're trying to build a a voice assistant that can meet the needs or feel like the right experience at the scale of the entire world, um you have to go really deep on kind of all of these different aspects, conversational dynamics, what are the right voices, do they have the right accents, um do they speak the right languages reliably?
2:02:46
All of that stuff uh matters.
2:02:49
And um >> and so that's a you know that's that's something that at Apple's scale uh and scope they have to solve that for something that's a bit more contained like at a hospital in a particular part of the US you may you may not have the the same kind of constraints or requirements.
2:03:06
>> What uh what's your opportunity in robotics?
2:03:11
>> It's the it's the next big wave.
2:03:11
I think that like uh robotics has kind of this 80% overlap with with voice AI in that um you can think of like a humanoid robot which are a lot of the robots that are getting built now by companies.
2:03:27
You're not going to interact with that that robot um with a keyboard.
2:03:28
Um you're going to you're going to talk to it and it's going to have this additional capability where it's going to have eyes and be able to see you and move uh in you know in response to what you do and your actions.
2:03:40
And so you're going to talk to that thing and uh that's the overlap, but then there's a lot of other new stuff that you have to do in the robotics use case because it has vision um and because it has limited connectivity.
2:03:53
So that robot may be out there in the field.
2:03:56
It may not always be able to to connect to the network.
2:03:58
You may need to be able to do things kind of locally or on a local network um if connectivity is compromised.
2:04:04
So there's like a lot of opportunity to build in the robotics space.
2:04:08
It's still a bit earlier uh than than I would say voice AI is now in terms of like how it's scaling up and being adopted, but it's uh it's a wave behind voice AI that I think is going to be even bigger than voice AI.
2:04:22
>> Are you tracking benchmarks around latency?
2:04:23
I'm interested to know what you think about uh the progress to reduce latency in voice interfaces and particularly what the bottlenecks are.
2:04:32
Do we need to just distill models down further?
2:04:35
Do we need custom silicon?
2:04:35
Are there going to be dedicated chips AS6 for inferencing um voice models?
2:04:41
Because I'm not sure if you've seen those Instagram reels where people are doing like the human impression of chat GPT voice mode and they sort of like pause and it's it's funny.
2:04:52
It's a very >> talk about the guy who's like I'm I'm lying in front of the train tracks.
2:04:55
So yeah, you've probably seen these and you're seeing you're seeing your product in action.
2:05:02
Honestly, it's a great ad for for voice mode, >> but it feels it feels very much like we're we're almost in like the dialup internet era of these voice interfaces where there's this like little delay and that's clearly going away, but I'm interested to know like technically what what needs to happen to remove the delay from voice interfaces. >> Yeah.
2:05:23
>> Yeah. So the way to think about it is that there's kind of a bunch of different components to this end to end experience of like I speak >> model thinks model speaks back right um and along uh along that kind of path you have the network latency um I I'm speaking only to the primary components
2:05:42
there's a bunch of little things too in the middle as well but there's network latency so getting the voice from me to the to the machine um wherever it's located then there is like the process of understanding when am I done speaking that's called turn detection like when
2:05:57
have I done am I done sharing my thoughts and then the model can now speak back to me or think and then speak back to me so there the the step of figuring out when is the user done speaking that introduces some latency then there's the actual inference part of it and it depends on whether you're using a full voicetooice model so a
2:06:14
model that takes in voice directly and spits out voice or whether you're doing a cascade approach where it's uh the first model converts it into text the next model is the LLM and then the next model is taking the tokens coming out of the LLM and turning it back into speech. Um, if it's the kind of the cascaded
2:06:29
Um, if it's the kind of the cascaded approach, then you have like three different spots where additional latency can come in, right?
2:06:36
Like there's three models here.
2:06:37
They all have to run um and then they have to pass information uh between uh each of those models.
2:06:42
So there's another latency or place where latency creeps in.
2:06:46
And then when the model finally spits out voice, whether that's from a a TTS model or from the the voicetooice LLM itself, then you have latency of the network where the AI's voice travels over the network and then it's played out on my on my phone.
2:07:02
And so it turns out you can actually like shrink the latency in each of these different components.
2:07:06
Where are you going to get the biggest biggest bang for the buck?
2:07:09
I would say there's two places where you get the biggest bang for the buck.
2:07:12
The first one, three places.
2:07:15
The first one is uh that kind of three models or one model.
2:07:18
So is it voice going straight into the model and then being processed and then spit out or are you actually doing this kind of like handoff uh between three different models?
2:07:28
That's the first spot where you're going to get a big reduction in latency.
2:07:32
The second place where you'll get a big reduction in latency is um on the turn detection piece.
2:07:37
So figuring out like when is the user done speaking um and you know having the delay be as short as possible between okay the user's done speaking let me pipe the data straight into the model or maybe I'm already streaming it into the model and then it's deciding when the user is done speaking um and has its response ready to go and then the third place is uh on queuing.
2:07:57
So like you have many many people that are trying to hit these models at once they're all using voice mode or etc at the same time.
2:08:03
um how do you figure out how to load balance uh that workload that demand that users have that speech data that the users are are sending to the model?
2:08:11
How do you figure out how to make sure that there's a model already waiting and consuming that speech versus making a queue up and wait and then this person goes and gets a response and this person goes.
2:08:21
So doing the load balancing across those GPU workloads is another and then and then as you mentioned I think like you can get a speed up on the model side from hosting on on better hardware or >> you know chips that are dedicated uh to to a particular type of particular type of architecture. >> Yeah. Yeah.
2:08:38
That makes a ton of sense. >> Yeah. >> Uh that's exciting.
2:08:40
Are are you focused uh like you're raising a lot of money right now.
2:08:45
Is this focused on OPEX capex?
2:08:48
Are you going to build your own data centers?
2:08:50
Have you have you cons confronted like the build versus buy debate internally?
2:08:56
>> Yeah, I think for data centers, I mean, we have really healthy margins now, so there's no um there's no pressure to go and you know, build our own metal yet, but uh we'll we'll get there over time.
2:09:05
Um you know, that's something that we've always talked about uh eventually kind of kind of fully vertically integrating the stack.
2:09:11
But um you know, I think that uh the capital for us is is going to be used in in two primary ways.
2:09:16
I think the first one is that we started our life as like network infrastructure.
2:09:22
>> Um but it turned and and that's used to be the product that we sold even for voice AI companies but it turns out that like >> when we had when we were selling voice network infrastructure um someone would say well how do I uh how do I like test this model you know I built it with your software and now I'm running it on your network like but how do I test it?
2:09:38
We're like well go over here uh use this vendor and figure it out like glue glue this stuff together.
2:09:44
And then they were like, well, how do I deploy it?
2:09:45
And we're like, well, you know, use this vendor.
2:09:48
And then they're like, well, how do I observe it?
2:09:50
And like, you know, all the data generated, like, do I use data dog? What do I do here?
2:09:53
And we're like, well, you can kind of piece it together this way.
2:09:57
And um, we kept hearing this over and over and over.
2:09:59
And then we said, okay, well, we're just going to start building out all the pieces because right now building a web application is very familiar, very easy, and you usually have one single platform that allows you to build out the entire thing, right? Like Nex.
2:10:12
js JS has kind of become this default Nex.
2:10:14
js and Verscell have become like the default platform for building out a web application but a voice AI application a robotics application these things are actually very different from a web application.
2:10:26
It's a completely different architecture.
2:10:27
At the top of the iceberg, it looks like, oh, well, instead of typing and and clicking a mouse, now I'm talking um and the AI can see me.
2:10:34
But just that kind of change at the input layer underneath changes everything about the underlying architecture of how that application is built and all the infrastructure you need to get that thing built.
2:10:49
And so what we're doing is we're really building every single piece of that across the entire development life cycle so that you can start with LiveKit from zero just a dream scale to the moon in production >> in reality with LiveKit and you don't really need to like go anywhere else.
2:11:07
You can do everything within the platform.
2:11:08
And so the first part is just building out >> this product, right?
2:11:11
The surface area of it is much wider than where we started.
2:11:15
So that's the first thing for the capital.
2:11:16
And then the second thing is is you know really investing in Devril and some go to market around education like helping developers understand how can they leverage this platform to accelerate what they're trying to build.
2:11:30
Um you know it's like lots of sample apps and workshops and and things like that.
2:11:35
um events uh to to make sure that people know that there's this tool that's kind of magical and can accelerate, you know, their their roadmap and and and their uh their kind of progress towards the vision of what they're trying to do. >> Yeah, makes sense.
2:11:48
Well, congratulations again.
2:11:50
Thank you so much for taking the time to come chat with us and hope you have a great rest.
2:11:56
>> Yeah, have a great weekend. We'll talk to you soon. >> You too. You too. Appreciate it. >> Goodbye.
2:12:00
>> Let me tell you about Figma.
2:12:00
Figma make isn't your average vibe coding tool.
2:12:02
It lives in Figma, so outputs look good, feel real, and stay connected to how teams build, create codebacked prototypes and apps fast.
2:12:11
Um, back to the Rob report.
2:12:15
Uh, Call of Duty creator Dave Anony's custom Bair mansion just sold for $22 million. It was down in price.
2:12:24
They first listed it 18 months ago for 27 million and subsequently undergo it underwent a number of price drops.
2:12:30
Uh he was the pioneering video game writer, director, and producer.
2:12:32
He offloaded the residence in the posh Bair neighborhood of Los Angeles.
2:12:38
He acquired 15 years ago. In 2010, he paid $3.
2:12:39
5 million for it, did some renovations.
2:12:45
Now, he has sold it for 22 million.
2:12:45
The sprawling brick and limestone home sold to an unidentified buyer repped by Ron F.
2:12:54
Ron Smith and David Berg of Compass for 22 million, which is a lot less than the creator of the blockbuster Call of Duty Black Ops franchise originally wanted.
2:13:01
However, it's still a whopping $18.
2:13:03
5 million more than his he and his wife paid for an existing 1940s house on the Hillside property before raising it and embarking upon a custom rebuild in 2018.
2:13:13
So, they bought it in When did they buy it?
2:13:16
They bought it 15 years ago and then 18 years go by then they do the custom rebuild. Wow. Uh completed in 2022. >> Fantastic. >> You're a fan.
2:13:26
Uh it's it's set on a gated and hedged hillside parcel spanning almost 3/4 of an acre.
2:13:30
The Orin Dothan designed abode now offers seven bedrooms, eight full baths, and two powder rooms in roughly 9,000 square ft of Hshshaped living space across three levels.
2:13:45
[snorts] English country inspired interiors by Marie Carl Car Carson and ML design.
2:13:51
Sport plastered brick walls and floors clad in wood imported from Germany's Black Forest.
2:13:56
Plus, smart home and security systems.
2:13:58
Standing out on the main level is a fireside living room with a vated oak beam ceiling.
2:14:02
>> John, if you've seen Star Wars, you'll you'll love this room.
2:14:05
>> That's That's Have you seen Star Wars?
2:14:05
I have seen Star Wars, Jordy.
2:14:07
I've seen all of them multiple times. I am a fan.
2:14:12
The kitchen is outfitted with a fossilized stone eatin island uh decor and sub-zero appliances and a windowed breakfast nook with built-in banquet seating.
2:14:22
While the primary suite has a projector and a retractable 100 ft screen.
2:14:26
Wow, that is a big TV uh or projector.
2:14:30
Uh a seating area that opens to a balcony and a marble bath anchored by a nickel soaking tub.
2:14:34
Uh lower level features a soundproof movie theater.
2:14:37
So they have a hundred inch projector in the master and then you go downstairs and there's a soundproof movie theater. This guy liked media. Makes sense. >> Film enjoyer.
2:14:49
>> Maybe he was playing Call of Duty on these uh on the movie theater screen.
2:14:51
Uh it has cashmere recliners and an entertainment lounge with a bar and a climatized wine celler.
2:14:56
And upstairs a mirror gym in a dark hued study.
2:14:59
We love the dark hued studies here.
2:15:02
This is the second one we found so far. Uh it's also soundproof.
2:15:07
has a wet bar and bookshelves concealing a server area that doubles as a panic room. Interesting.
2:15:12
Outdoors, uh, the grounds host a tiled zeroedge pool with a Baja shelf and spa, grilling station, fire pit, conversation area, and fountain with lights and jets choreographed to music. Interesting.
2:15:24
There's also cobblestone motor court flanking a two-car garage.
2:15:28
Born in Liver Liverpool, England, Anthony relocated to two in 2004 to Los Angeles where he worked on Call of Duty, one of the bestselling video game franchises of all time with more than half a billion copies sold to date.
2:15:40
His breakout came in 2010 with Black Ops, which he directed and wrote.
2:15:46
He also wrote and directed the sequel.
2:15:48
Uh he went on to launch the gaming studio Deviation Games, which recently closed up shop.
2:15:52
As of now, he's reportedly pursuing a new challenge professionally.
2:15:55
Well, we'll have to have him on the show and get him get the update what he's doing next.
2:15:59
Uh, have you played Black Ops or were you strictly Modern Warfare? You played Black Ops?
2:16:05
I enjoyed Black Ops as well. Were you, Tyler?
2:16:06
Were you a Black Ops kid? >> Yeah, Black Ops 2.
2:16:09
>> Black Ops 2 was the one.
2:16:10
>> Yeah, I guess Black Ops 3 maybe. >> Sort of underrated.
2:16:12
I I've always been a fan of the single player uh the experiences I think more than the average.
2:16:17
The multiplayer is still like fun.
2:16:19
>> You mean like zombies or >> No, campaign. Campaign.
2:16:20
I feel like uh there was actually one Call of Duty recently.
2:16:24
would be just a campaign. >> I like the campaign. It's very cinematic.
2:16:28
It's like a James Bond movie.
2:16:30
You know that meme of uh you know what Greenland's going to look like.
2:16:32
And it's the it's from I think it's from Black Ops 2 where they're on the snowmobiles and they're shooting people through they're going through the forest. That's an iconic scene.
2:16:39
I like the big set pieces. I like the stories. Yeah.
2:16:41
It's not the might not be >> That's probably the most memorable campaign moment in any >> No, it's definitely No Russian. >> Yeah. No Russian. >> Yeah.
2:16:51
Did you ever play that, Jordy? >> Wow. No Russ gamer over here. Which version? >> Fake gamer.
2:16:56
It's in Modern Warfare, right?
2:16:59
>> I actually don't know.
2:16:59
I think it's Modern Warfare. >> Yeah.
2:17:02
No, Russian is they go It was a very controversial scene.
2:17:06
because you you play you go behind the scenes and you're you're embedded as a as a Russian uh you're doing like a false flag attack basically and your job is to like shoot a bunch of people in an airport which is very aggressive, very controversial uh super dark but uh certainly memorable uh as is Shopify.
2:17:26
Shopify the commerce platform that grows with your business and lets you sell in seconds online in store on mobile on social on marketplaces and now with AI agents.
2:17:34
Let's head over to Montana.
2:17:36
>> Okay, we're going to Montana.
2:17:38
>> A booming mountain town with Montana's most expensive real estate.
2:17:40
Once a remote ski outpost, Big Sky has transformed into a destination of wealthy home buyers.
2:17:45
Uh in southwestern Montana near Yellowstone National Park is Big Sky Mountain Community that emerged around 1973 with the opening of remote ski area Big Sky Resort.
2:17:54
Over time, Big Sky has transformed from a scattering of residences and businesses into a true town.
2:18:00
Lately, the 10-year Big Sky 2025 plan added business uh added >> added new worldass ski infrastructure and modern luxury residential resort to reshaping the property landscape.
2:18:12
This is helping push Big Sky to the top of the state's price charts with a median listing of 3. 05 million in December. >> Mhm.
2:18:22
>> Uh despite this growth, the community keeps an authentic Montana feel.
2:18:27
Dressing up still means putting on cowboy boots, jeans, and maybe, just maybe, a cowboy hat.
2:18:32
Town Center is a new newer commercial and housing hub with a mix of dining, shopping, hotels, and recreation.
2:18:38
Nearby, the established Meadow Village has a small business area.
2:18:42
Let's give it up for small business areas around the country.
2:18:45
[music] Uh, and a residential feel.
2:18:47
Together, these two districts have merged into Big Sky growing downtown. Lone Mountain Ranch.
2:18:53
Uh this historic guest ranch with a western vibe dates back to 1915.
2:18:55
So before I guess the town actually formed.
2:19:01
It's known for antler adorned horn and cantal restaurant.
2:19:05
>> We got to give some tips to folks who are heading out to Big Sky.
2:19:07
There are memberships that you must obtain.
2:19:09
Big Sky has three exclusive ski in ski out private residential clubs.
2:19:14
You got the Yellowstone Club founded in the 1990s.
2:19:20
offers classic timber aesthetics, private ski terrain, and a Tom Wescop Don designed golf course.
2:19:26
In addition to a variety of housing options, Montage Big Sky Resort opened in 2021 and is within Big Sky Peaks community, which you mentioned.
2:19:37
It has 139 room hotel and private residences.
2:19:40
Ownership provides an opportunity to join Spanish Peaks Mountain Club.
2:19:44
And then there is the one and only Moonlight Basin Resort.
2:19:46
on the grounds of the Moonlight Basin Club.
2:19:52
>> Yeah, this just opened.
2:19:52
I have two friends there right now.
2:19:54
It looks It looks incredible. Uh and they have homes.
2:19:58
Uh Montage is set up where I think it's only fractional >> for their residences, whereas uh Moonlight Basin, the one and only, you can actually buy entire homes.
2:20:07
the business model of just buying a bunch of land >> for cheap and then building a bunch of homes and selling them.
2:20:16
>> Uh >> it really is sort of like a Montana forever environment.
2:20:18
You know, Silicon Valley talks a big game about like building new cities. >> California forever.
2:20:24
>> You head out to Montana and they're like, "Yeah, we built three of these like just recently.
2:20:26
We built like whole cities."
2:20:28
Uh ski season is obviously the big headliner.
2:20:30
Big Sky Calendar is actually a tale of two high energy peaks.
2:20:34
Winter at the ski resort spanning 5,850 acres and one of the largest in the US is the undisputed king.
2:20:40
But in the summer, the Big Sky PBR claims the throne as the premier event.
2:20:45
It brings together the world's elite bull riders to an outdoor arena in Town Center, pairing the raw grit of professional bull riding with pyrochnics and mountaintop sunsets.
2:20:56
We got some advice for the buyer.
2:20:58
The majority of the full-time residents typically live in the vicinity of Meadow Village or Town Center where there are more condominiums.
2:21:06
A real estate broker says within a quarter mile outside downtown, there are single family homes, part-time and second home residents, and the o on the other hand often buy in the mountains where there is ski access.
2:21:18
Bolis suggests keeping an open mind.
2:21:21
Some prospective buyers initially want a single family residence, she says.
2:21:23
But even those who thought they needed a four or fivebedroom house may be swayed by a well-designed condo aesthetic or the convenience of being able to easily lock up and rent out the unit.
2:21:36
>> Alex uh Alex Waters, who we were with on Sunday with Paul, uh he is running the racing program out at Willow Springs.
2:21:44
He's setting up a new members club in uh in Bosezeman >> uh that allows you to buy garages >> uh which means that you can you will have a primary res or not necessarily a primary but you will have a residence on
2:21:58
Montana which means you can get away with uh not uh oh >> there was a loophole with you could set up an LLC in Montana buy a car and then uh avoid the 10% sales tax or whatever it is whistling diesel But that's been getting cracked down on. It never really
2:22:15
It never really was obvious that it was legal at all.
2:22:17
I think it I think it wasn't. I think it wasn't.
2:22:22
>> It also aesthetically was a little offensive to some people.
2:22:24
They said there was sort of a carve out if it was like, oh, you had to do it because of certain regulations, like a certain car couldn't get approved.
2:22:32
But, um, there were there were a lot of people that were like, "Hey, you bought a $800,000 car.
2:22:39
Why can't you just afford to pay the taxes, the sales tax or whatever?
2:22:41
Um why are why are you nickel and dimming?
2:22:45
Like can you really afford that Lambo if you can't just put a California license plate on it?
2:22:49
Um there it always had like a little bit of like an aesthetic like h you're you're you're skipping >> Well, some some people were doing that specifically because their cars wouldn't pass small in California. >> Yeah.
2:23:00
If they're old or retro, like you sort of get a pass.
2:23:03
>> Um >> graphite code review for the age of AI.
2:23:06
Graphite helps teams on GitHub ship higher quality software faster graphite.
2:23:11
>> Uh, did you see Aman is headed to sea? >> No way. >> Got a video here. >> Okay, let's play it. >> Pull up this video. >> Yeah, >> Aman at sea.
2:23:20
They're calling it a philosophy in >> Is it a It's a boat. It's a cruise ship. Let's play this. >> Looks nice. Got a nice big bedroom. This is on a boat.
2:23:31
[laughter] Is this AI slop?
2:23:34
Is this AI or CGI or is this real? We now we need to know.
2:23:37
Let's go to the comments. Oh, the goat.
2:23:42
[laughter] I I honestly thought that goat was in the video. I That did fool me. The horse. That is a big boat. Wow.
2:23:51
Does look like they they they actually built this [music] thing.
2:24:00
That will this get you to >> They're gentrifying cruises, John.
2:24:05
>> Incredibly, absolutely incredible.
2:24:05
You truly nailed [music] it.
2:24:07
Wow, the comments adoring. People love it.
2:24:13
Aman Gati is the embodiment of space and seclusion.
2:24:16
Comprising just 47 spacious suites, the yacht is imbued with the same quiet elegance as Aman Sanctuaries on land with unparalleled surface from the onboard team attuned to disc.
2:24:26
So, it's a big yacht, John, but it's a lot of people. >> Yeah.
2:24:31
>> You're looking at hanging out with like it's over 100 people with the staff.
2:24:33
I would assume you got 47 suites, couple people per suite, and then staff.
2:24:37
That's a lot of people to be on >> uh on a boat.
2:24:42
I'm sure it'll be an amazing experience.
2:24:44
Are you are you signing up?
2:24:47
>> I would I've been anti- cruise for a very long time.
2:24:51
I I think that there might be an over rotation against cruise culture.
2:24:56
It's been uh it's been degraded in many ways where many cruise ships uh the the the aesthetics are very like okay you're just basically drinking gambling the whole time and it's sort of like boring and bland.
2:25:07
Uh and it's certainly not the correct cultural way to visit a c a country like if you're just like yeah I've been to you know France. No I didn't go on land.
2:25:17
I was just on this boat drinking and gambling the whole time.
2:25:22
Um, it's a little bit it's a little bit it feels uncultured sometimes, but I think that uh certain cruise ships might offer specific things that people might enjoy.
2:25:32
It depends on depends on uh what what you're what what you're going for and what the community will be like on the boat, what the goals are. Who knows?
2:25:41
It's all slot machines on the Ammon.
2:25:44
>> I stayed in Montenegro for a couple weeks once and it was so funny because you'd just be in like the most quaint little village. >> Yeah. Yeah. >> Like by the sea.
2:25:51
There's tiny little boats out. >> It's totally idyllic.
2:25:55
And then just like this massive cruise ship would just like roll into the port of this tiny town and it would kind of it would kind of kill the vibe.
2:26:04
>> I like the smaller boats.
2:26:04
I like a catamaran, something you can scuba dive on.
2:26:08
>> I guess like my I guess like my big question with the Aman cruise is >> like if you're staying at Aman >> it's probably think like 50k for the week >> for a room. >> Mhm.
2:26:21
especially during peak season >> and and so assume and like renting like a pretty nice yacht with a full staff that's private. >> Yep.
2:26:33
>> Is like probably that's >> around the same. Yeah. >> Yeah.
2:26:35
Potent potentially like slightly more.
2:26:37
But I I'm not sold that this is going to be that great of a trait.
2:26:42
>> Uh well the So the thing is >> especially if you're going with friends like do you want to go on the Aman Do you want to go on the Aman >> boat? Yeah.
2:26:49
>> boat? Yeah. and you've got you're sharing it with a hundred other people or do you and and like >> friends want to get your own boat >> you might like hanging out with other random people that are there at the on the Aman boat like there might be serendipity that comes from the
2:27:02
community that might be a >> I've met some cool I've met some cool people if you get like a hundred of your boys just load the whole thing boys maybe like 200 pack them four in each suite you know you take the mattress off the bed and then half the dudes sleep on the box ing and then half the dudes sleep. >> That would be that would be such a funny
2:27:20
>> That would be that would be such a funny bit to run on the Aman is basically pick the most like figure out like what is like the least desirable dates like next year >> for cruising in general and then all of your friends book it at the same time.
2:27:33
It's like a fraternity offsite.
2:27:35
>> Yeah, that would be good.
2:27:35
But yeah, I mean there's nothing wrong but even then at that point you could how it would be cooler to rent >> your crew in there.
2:27:42
It would be cooler to rent 10 yachts with your friends all at the same time and then just like park them and hang out.
2:27:49
>> I like the idea of just smuggling as many of your boys into one room as possible.
2:27:54
>> Be like, "Sir, uh, you you selected just two guests.
2:27:57
Why are there 14 dudes in your room?
2:28:00
>> Why do you have 30 cot to add to your to your to your room, sir? What's going on?"
2:28:07
You're like, "Don't worry about it."
2:28:09
>> [laughter] >> The other the other thing with with the man is the most like first world problem ever.
2:28:14
ever. But like some of the menus are just like so, you know, makes sense, but like so focused on like sushi and so raw fish heavy >> that at some point you're like I need to venture out like by like day five you're like >> well I mean I think that is the actual
2:28:33
value prop with the ammon is that you're you're potentially reducing the standard deviation or like the the uh the variable experience because if you're chartering something privately and you're and you're getting a a private boat like you might have an amazing captain or you might have a mediocre captain. You kind of got to figure out
2:28:48
You kind of got to figure out the reviews and process that and then oh the chef how are they doing and then all the crew are they all good?
2:28:53
Whereas Aman, you kind of know that there's like a standard that's being held within that group and that uh everyone will be trained to the same standard that there will be an organization that's maintaining some sort of base level of experience.
2:29:06
And so uh I don't know anyway 11 Labs build intelligent real-time conversational agents reimagine human technology interaction with 11 Labs.
2:29:15
Uh we had some breaking news yesterday.
2:29:18
Caroline Ellison has been released from federal custody.
2:29:21
She of course was involved in the FTX drama that erupted a few years ago.
2:29:26
She's out and Martin Skrey quote tweeted us into the oblivion ratio to us by changing our [laughter] changing He didn't even use Nano Banana Pro.
2:29:38
He just scribbled all over our trading card and said snitch. >> Honestly, it worked. Yeah, I did.
2:29:42
I was thinking like that felt very fast. >> It does feel fast. It does feel fast.
2:29:50
But I'm excited to see what she does next.
2:29:52
Will she build something?
2:29:52
You know, we've seen uh some other folks get out and go on to redemption and uh we will see.
2:30:00
Hopefully at some point she tells her story.
2:30:02
It'll be interesting to see her side of it.
2:30:04
Maybe she has convincing arguments.
2:30:07
>> I heard she uh wrote a book. Really?
2:30:07
I think there was some leaks.
2:30:08
I don't know how how true it is, but apparently she she was writing. >> Okay.
2:30:12
Well, >> Jay Yarro uh is sharing uh Joe was highlighting Intel sold off after earnings yesterday.
2:30:21
Uh and Jay is particularly disappointed because he says >> I'm a US citizen and our sovereign wealth fund owns this one. [laughter] >> Yeah. Bad day.
2:30:32
Bad day for >> We all lost something today.
2:30:35
>> Bad day to be a uh to be a US citizen.
2:30:38
What >> uh do we should we talk about uh >> the the the news on Intel really quickly.
2:30:43
Intel post loss after spending increase uh swung to a loss for the fourth quarter on Thursday and forecast further losses in the in the first quarter as the company spends heavily to ramp up production of its latest chips.
2:30:55
Company reported a net loss of $333 million for the last three months of the year and analysts were expecting them only to lose 294 million.
2:31:03
So they lost more than expected. revenue was 13.
2:31:06
7 billion and a year ago it was 14. 3.
2:31:09
So revenue is declining, losses are expanding.
2:31:15
It's a bunch of bad news. Um shares fell 6.
2:31:18
7% in after hours trading.
2:31:21
Uh the CEO Lip Bhutan said, "Our priorities are clear.
2:31:24
Sharpen execution, rein reinvigorate engineering excellence, and fully capitalize on the vast opportunity AI presents across all of our businesses."
2:31:34
Uh the CFO said industrywide support supply shortages were a factor weighing on results and said the problem would worsen in the first quarter of or 2026 before starting to ease in the spring.
2:31:48
Well, I'm rooting for Lip Bhutan.
2:31:50
I'm rooting for folks over at Intel.
2:31:52
I'm rooting for the American taxpayer who owns a little bit of Intel.
2:31:57
So, good luck to all of them.
2:31:59
Let me tell you about Octa.
2:31:59
Octa helps you assign every AI agent a trusted identity.
2:32:04
So you get the power of AI without the risk secure every agent, secure any agent with Octa. >> Well said, John.
2:32:11
Uh we should talk about this out of home campaign.
2:32:14
>> Open AAI has purchased a ton of billboards.
2:32:17
They have hit San Francisco.
2:32:20
Um we got a whole bunch of folks at Clay, Valos, Decagon, Unified GTM, and Christina of course from Vanta uh is sitting there on the billboard.
2:32:30
I like the aesthetic, the black and white, the big there's a lot of white space in the design. It's not too cropped in.
2:32:37
I think they I think they executed these billboards very well.
2:32:40
And uh and and it's it's fun.
2:32:43
OpenAI is such a it's easy to collapse it into it's just a you know app on your phone.
2:32:50
It's a singular business, but they do have a lot of partners all over the startup ecosystem and they are uh paying tribute to them with this uh out of home campaign.
2:32:57
I like to think about the 10 people left in San Francisco that have never heard of AI or OpenAI or GPC and they're just very confused walking around looking at these nice pictures.
2:33:11
>> It I mean it is it really is for the builders.
2:33:13
builders. It is it is another example of uh San Francisco billboards being very uh insular insider jokes like you know there aren't that many people in many cities that would be able to identify all these founders by name or know these
2:33:27
companies even especially at the size they put there they didn't even put taglines they just put the this person's name building this company you have to know it's an if you know you know campaign but I think there's a lot of people in San Francisco that do in fact know. So, congratulations to everyone
2:33:40
So, congratulations to everyone that is sporting uh their their fits on a billboard in San Francisco now on an AI's dime.
2:33:48
>> Well, let's head over to Fa Fa Lee. >> Yes.
2:33:51
>> According to Natasha at Bloomberg, she's in the fundraising market with talks, early talks, advanced talks, we're not sure, but their talks to raise >> 500 million at 5 billion.
2:34:01
Uh I do I do think when you think about the leverage that uh founders like Feay Lee have to be going out and raising this much money this early and just still being like sorry the most I can give up is 10%.
2:34:15
It's like they all want to do >> these 10% or less.
2:34:19
>> She deserves the goat sound effect.
2:34:19
She deserves the goat on the screen cuz she's a true >> goat on the screen.
2:34:23
We got a goat on the screen >> former TVPN guest.
2:34:26
Very happy to have chatted with her.
2:34:29
uh uh her company World Labs has been posting some very interesting demos.
2:34:36
Obviously, there was that box that you could see a virtual 3D world inside. That was very cool.
2:34:40
Uh, and the way she talks about it is funny because it makes me feel like she's a gamer and now I just want to, you know, get on Rust with her and and and experience whatever game she plays because she's she's sort of becoming an important player in uh in like the future of video games, potentially the future of gaming, the future of the metaverse.
2:35:01
Um, and I wonder I wonder if she has any favorites or or has has uh has dabbled on uh on COD late at night on voice chat screaming at people.
2:35:12
>> What's what's going on with uh so Green Oaks Alimter >> Yes.
2:35:18
>> have initiated a trade dispute with the government of South Korea.
2:35:20
They're suing South Korea >> of unlawfully attacking e-commerce giant >> Kong. >> Kong. >> Yeah.
2:35:27
Um, uh, I think Neil went into detail on on their investment in coupon on, uh, invest like the best. >> Yes. Yes. >> It's a great episode.
2:35:38
>> It feels rare to have the venture firms be doing this suit, the lawsuit or to initiate the trade dispute.
2:35:43
initiate the trade dispute. is interesting like where where this lawsuit is sitting because typically you know if you if you back some company and then they get in a dispute with the local government um the company is the one that's sending their lawyers but in this case it is green oaks and alimter
2:36:00
uh but people are coming out in force supporting Neil Meta Gary Tan said Neil Meta is who you want by your side when it gets real not a lot of investors would go up against a sovereign to defend a founder South Korea's government is about to find out that Americans don't take wealth to being bullied. And Brad Gersonner gets in the
2:36:14
And Brad Gersonner gets in the replies with the American flag and the salute.
2:36:20
Let me tell you about Cognition.
2:36:22
They're the makers of Devon, the AI software engineer.
2:36:24
Crush your backlog with your personal AI engineering team. We're sure. >> Substack.
2:36:32
>> What's going on with Substack?
2:36:34
>> They're going into television.
2:36:35
>> They're going into television.
2:36:36
>> They're taking on big TV. >> Big TV.
2:36:38
They say according to Max they're launching Substack TV app on Apple TV and Google TV.
2:36:42
Users will be able to watch video posts and Substack live streams.
2:36:47
>> Uh I think this is a so much of Substack's opportunity right now is just that X is rolled into XAI >> and is like not operating you know totally as like a pure play standalone company. >> Yeah.
2:37:02
>> And so yeah I think >> Substack has been has been definitely ramping up the video functionality.
2:37:07
We've done some live streams there.
2:37:07
Um there's a lot of opportunity and it's a very interesting community.
2:37:11
I think that's the strongest thing about Substack is just that uh it's a very high signal place.
2:37:17
high signal place. Like if you were I'm I'm I'm you know the Substack experience is not scrolling random posts random creators but I feel very confident about if Substack were to serve me a random piece of content that was doing well across the Substack network I would
2:37:34
enjoy it because the creators that choose to be on Substack there there are just so few like >> you could see you could see a new kind of like we were talking about Vimeo earlier the the dynamic they used to have between Vimeo and YouTube where Vimeo was a super intentional place. You
2:37:47
You can see something emerging again where like Vimeo is like maybe or sorry, Substack TV is like a somewhat more intentional version of of YouTube just because it is like based on like your actual audience less around just like raw discoverability now logging onto the Substack TV app and like seeing exactly content just from the people that you know.
2:38:10
And also with Substack, if you're trying to create like a signal on a piece of content, the fact that people pay is really, really high signal.
2:38:22
Like, it's hard to clickbait someone all the way to putting their credit card down and being like, I support this creator and I'm willing to pay, you know,5 or $10 a month for who knows how long.
2:38:33
And so, uh, that just feels like a really, really strong signal to pull across the network if you're surfacing things.
2:38:40
It's like, yes, this person isn't just good at clickbait.
2:38:43
They're not just good at driving traffic.
2:38:44
They're not just good at thumbnails and titles and hooks.
2:38:48
Like, they are good at at creating such a response from their community that their community puts down their credit cards.
2:38:54
And in the case of like Emily Sunberg at Feed Me, maybe they pay more than they have to uh because people really do enjoy the relationship they're having with the creator.
2:39:02
And so Substack has been very very unique in that.
2:39:04
Um anyway, um there are always more posts.
2:39:12
>> Did you see these people uh clearly have not read uh Rocco's Basilisk? >> That's what they say.
2:39:19
>> They're tearing up the Whimos in SF. >> That's not good news.
2:39:22
>> We pull up this video here.
2:39:24
>> They're really jumping on this.
2:39:24
This is a new one cuz Whimos have been getting stomped out.
2:39:28
>> This is a new >> two words I haven't said put together before.
2:39:31
They're really breaking the windshield. Wow. What is this?
2:39:32
Did the Whimo drive through a particular protest?
2:39:36
Did these people just um did these people just descend upon a random Whimo?
2:39:41
And also like this is a crime. This is property.
2:39:46
>> What would your mother say? >> Yeah.
2:39:47
Also, I'm just thinking about like the Whimos aren't cheap.
2:39:49
Like you're going to be hit with like a $500,000 bill even if you just have to pay for repairing the Whimo. Um very very odd.
2:39:58
But of course, people are calling to give the Whimos weapons and people that is the rallying cry of tech.
2:40:02
I don't think Google will be doing that anytime soon.
2:40:06
I think there were other ways to solve this.
2:40:07
But it is terrifying if the bird and lime the bird the bird CEO if he was looking at this would be having a little bit of PTSD.
2:40:17
>> You remember bird graveyard that account. >> Yes. Uh yes. Yes. Yes.
2:40:20
Uh the autonomous uh technology really uh needs to get put through the ringer.
2:40:26
Although a lot of I mean the New York City bikes seem to have been you know made it through the whole uh destruction phase and seem to be continuing to exist at least. Um anyway um what else?
2:40:39
Uh Sam Schaer had a post here that I wanted to read through.
2:40:46
He said, "I'm waiting for Bangers to post.
2:40:48
The atbangers account on X apparently has not been posting very often.
2:40:52
He's waiting for the Tesla Roadster.
2:40:53
He wants another Starship launch from SpaceX.
2:40:56
He wants Apple's folding iPhone and he wants Da Punk to be resurrected.
2:41:00
I thought it was a good list.
2:41:02
I think the another Starship launch from SpaceX.
2:41:05
That's like for sure going to happen.
2:41:08
Uh Apple's folding phone maybe next year. I don't know.
2:41:13
We'll have to talk to Mark German about it, but it seems like it's coming. Certainly working on it.
2:41:15
The Tesla Roadster, that might be a ways away.
2:41:20
that feels like that project has been uh fully mothballled in favor of other things like Optimus and data centers in space and whatnot.
2:41:26
But I would still love a Tesla Roadster. There's still something.
2:41:30
It is remarkable how few electric sports cars there have been.
2:41:33
Obviously, there's the hypercars like the rima and uh the uh what is it? The Ferrari there.
2:41:40
There's a few other like hyperars uh in the electric world that are like a million.
2:41:46
>> Ferrari has like this really weird >> it's the pen and batista.
2:41:48
The Batista is oh, I think over a million dollars in fully electric and uh has not been met with positive reviews from the car community, but if you put that that level of performance in something that costs $200,000, it is a different equation.
2:42:04
And I mean, you take the Cybert trucks aesthetics and you take those type of design risks and if it's low volume, you could at least create something that's >> yeah, >> you know, curious to see on on the street.
2:42:16
And uh a Halo car would be would be fun. I'm excited for that.
2:42:19
Um anyway, >> uh funny funny story out of uh from Semaphore.
2:42:27
Liz Hoffman writes an entrepreneur 13 hours in Davos jail. The food was phenomenal.
2:42:33
>> Says uh Sebastian Heinman stint as a suspected terrorist started in the most Davos way possible, hunting for something to eat.
2:42:40
The 31-year-old entrepreneur and first-time World Economic Forum attendee was scouting for a salmon roll at a party hosted by Digital Life Design Tuesday night at the Grand Hotel.
2:42:49
He set the prototype of the machine he hopes to sell, a verification device to uh to fraud proof money transfers on a pillar.
2:42:57
When he came back, it was gone.
2:42:57
Hotel security was waiting to tell him the police had some questions. I'm the idiot in this.
2:43:03
Heimman, founder of startup uh Vertico readily admits it's a black cube with hot glue blobs and wires coming out the side.
2:43:11
He left it unattended in a small town police state.
2:43:13
Uh what followed was 13 hours in the custody of the fatigue clad but unfailingly polite Swiss belief we spent all week thanking in broken German.
2:43:23
Seapur reviewed his release ticket from the police which said that Heinman was noticed within uh WF 2026 security zone with a tech device that seems suspicious and its use for illegal purposes could not be excluded.
2:43:37
Uh, and uh, anyways, uh, the view from a Davos jail cell.
2:43:41
At the Belvadier Hotel security, there's this detective, mid-40s Swiss, who searches me, extremely thorough.
2:43:46
They handcuff me and put me in the back of a BMW. Nice. Nice. Swiss police. Uh, uh, riding in style.
2:43:51
I meet another officer who has the best English.
2:43:56
The jail is right next to the train station.
2:43:57
They bring out a fingerprint scanner and the guy tells me, "I want to see if you're an international spy."
2:44:01
I asked for my Lunesta pills because I have insomnia.
2:44:06
and he said, "I can't give it to you because I don't know if it's cyanide." >> Whoa.
2:44:10
>> It was an insane story.
2:44:12
>> You walk into the office and there are two cells.
2:44:13
Everything is all painted white. >> Mhm.
2:44:16
>> Very antiseptic and Swiss.
2:44:16
There's a metal bed drilled into the concrete and a toilet sink combination.
2:44:20
I love this founder's like there just like hustling trying to trying to get some customer interest and just goes to Davos jail and was like, "Well, I may as well make the most of it.
2:44:30
Try to try to try to get a story out of this."
2:44:33
Uh, anyways, there's a metal bed drilled into the concrete and a toilet sink combination.
2:44:36
They said it was spring water, so the water was good to drink. The food was phenomenal.
2:44:41
Better better review than uh Bess.
2:44:44
[laughter] >> They brought it from the hospital apparently. Chicken lasagna. Amazing.
2:44:50
The only complaint I have was the smell.
2:44:52
The next morning, they bring this guy named Chris, a technical expert.
2:44:53
He says, "Come out here, explain your tech." I do my pitch.
2:44:56
I say, "Look, I'm not a very good hardware engineer, but I'm a great user of AI.
2:45:00
I was one of the top users of cursor last year.
2:45:03
I did 43,000 agent runs and generated 25 billion tokens. We open my machine.
2:45:10
Chris and I go line by line through the code.
2:45:12
I don't know the language the code was written in because it was written with AI.
2:45:15
So Chris actually explained the code to me.
2:45:18
They come back and they say, "You're free to go.
2:45:19
You can take all your stuff with you, but you're banned from Davos between now and 6 p. m. on Friday. >> What?
2:45:26
>> I'm going to apply for another hotel badge next year."
2:45:29
>> So anyways, insane story.
2:45:29
Don't don't bring your hardware device that you don't fully understand with a bunch of hot glue and a in a plastic box.
2:45:36
Uh very >> very very sketchy, but uh good got a good story out of it. >> Uh yeah.
2:45:44
Uh the other interesting takeaway from Davos, Alex Heath summed it up uh in the sources. News newsletter.
2:45:51
He says, "After my conversations with AI leaders this week in Davos, I came away with the impression that the industry has collectively decided to gang up on open AI."
2:46:02
And so you saw Demis and Daario hanging out talking about how much they're open to collaboration, open to pausing, if that makes sense, open to working together.
2:46:11
Um, and uh, and you know, Elon on stage, but not a lot of open AI love from all the other lab leaders.
2:46:20
sort of an interesting dynamic, the open the anti- OpenAI alliance.
2:46:22
I was also following the Kawashi market on will Elon win his case against OpenAI. The volume's gone up.
2:46:29
Uh it's now at 58% chance that Elon wins his case against OpenAI.
2:46:35
So like we're getting close to 5050.
2:46:38
The market's pretty stable.
2:46:40
Nothing's really moved it significantly one way or another.
2:46:42
Uh, but I'm sure it'll be moving a ton uh later once we have more news that comes out, more uh back and forth, more people sharing facts and figures.
2:46:53
>> Uh, there was some uh reporting from the New York Times on Cash Patel's demands for a work trip to the UK.
2:46:59
A lot of people were getting very angry about this, but I want your reaction, John.
2:47:05
So, every May there's a Five Eyes conference with the head of every intelligence agency.
2:47:07
This year, it was in the UK.
2:47:10
Cash Patel is going in the leadup to that his detail that starts making crazy requests.
2:47:15
You can tell me if these are crazy.
2:47:17
He's got special requirements on everything and the Brits are getting pissed.
2:47:21
Before the conference, his staff says he's unhappy because he doesn't like meetings in office settings.
2:47:26
What he wants is social events.
2:47:29
He wants Premier soccer, Premier League soccer games.
2:47:32
>> Now, now that's deeply unamerican.
2:47:34
>> He wants to go jet skiing. Okay.
2:47:36
>> He like a helicopter tour. >> That's fun. >> So, >> yeah.
2:47:39
Yeah, I wanted to ask is this fair?
2:47:40
He wants to go and develop, you know, relationships.
2:47:43
>> I think you need to go much further.
2:47:43
You you don't want to ask to go to some soccer match, do some European nonsense.
2:47:49
You want to ask for American football match.
2:47:51
Bring the NFL over there.
2:47:51
Yeah, the Super Bowl's happening.
2:47:53
I want the All-Star game play here while I'm in town.
2:47:57
Bring Bring the Patriots.
2:47:59
>> I also think you're you're excited about helicopters.
2:48:00
You're excited about jet skiing. Why not combine the two? Combine the two. >> What's that?
2:48:06
>> Like bring them out at the same time. Head down to the lake.
2:48:08
Head down to the lake or the river, right?
2:48:10
And just be zooming around together. Yeah.
2:48:13
>> Jumping off, you know, trading trading places kind of thing.
2:48:16
>> What about wing suiting?
2:48:16
Let's get some wing suiting going.
2:48:17
[laughter] >> Some bungee jumping.
2:48:19
I I want to do, you know, uh that Red Bull jump from space.
2:48:24
That's what I want to do on my trip.
2:48:26
We're going up the [laughter] edge of space. Felix Bombgartner. Yeah.
2:48:27
I'm jumping out of the weather balloon uh into into the central London.
2:48:35
>> Yeah, that that's that's a that's a good bit.
2:48:36
bit. you're going going to tour another another country and meet with people and say like actually I want to go to space >> very high up >> I want to go to space >> I want to go to space um in other news Eric Jorgensson has announced pre-orders for the book of Elon Musk it's 61 days
2:48:51
until the launch David Senra who got an early copy and he says it's awesome he highly recommends pre-ordering if you're not familiar with Eric's previous books he wrote the the almanac of Naval Ravakant uh which uh did sit fantastically well sold a ton Jack Butcher is involved in the book of Elon. That should be very fun. And Naval That should be very fun.
2:49:09
And Naval wrote the forward which is very cool.
2:49:14
>> Uh equipment share went public today. >> IPO >> YC Winter 15. >> Yeah.
2:49:19
>> They say from Missouri to 373 locations nationwide, 7,700 team members and 8 billion of fleet under management.
2:49:28
They built the operating system.
2:49:29
Construction has been missing. Yeah.
2:49:32
>> Um, our friend Mitchell from Lead Edge is a big investor. >> That's right. >> In equipment share.
2:49:39
>> We're working on getting the C CEO on any any day now.
2:49:41
Uh, but congratulations to >> uh the entire uh team and cap table at equipment chairs. >> That'll be fun.
2:49:49
Well, it's time to plant the bomb and wind down the show.
2:49:51
Thank you so much for listening and tuning in today. We had a lot of fun.
2:49:56
Uh we >> we hope you have an incredible weekend ahead.
2:50:00
Yes, >> only three more sleeps till we're back here.
2:50:04
>> We'll be counting them down.
2:50:06
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2:50:08
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2:50:12
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2:50:15
>> Go browse around on their website. >> Around.
2:50:17
There's a lot of good stuff. >> A lot of good stuff.
2:50:18
And >> thank you to our whole team. >> Yeah.
2:50:20
Thank you to the team, Tyler. >> Bunch of legends. >> Bunch of legends. >> The whole crew. And you guys chat.
2:50:24
We will see you on Monday. >> Cheers, folks. Goodbye. Terrorists win. >> Nice work, brothers.
2:50:34
I'll see you on the next one.