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4:05
Today is Thursday, April 9th, 2026.
4:07
We are live from the TBPN Ultradome, the temple of technology, the fortress of finance, the capital of capital.
4:14
Uh, we have a great show for you.
4:18
>> I was getting a little worried Monday.
4:20
There was not a lot of fundraises going on.
4:22
I was looking at the schedule and I was thinking, is it over?
4:26
>> And today I'm happy to report that we're back.
4:29
Uh, Andrew Dye is coming on from Allian.
4:33
Raised a $55 million seed round.
4:36
Uh, we got Cassa coming on with a 60 $38 million series B.
4:40
We got a $170 million series C later and then a hundred million dollar series E >> and then a nice little mango seed from the Enclave team to to cap it off.
4:50
But uh really fun show today.
4:53
We got Sagg and Jetty from Breaking Points, our friend over there coming on. We got Joe Weisenthal.
4:59
>> Yeah, >> wise and tall.
5:00
Uh and then CZ from Binance. >> Yeah.
5:04
uh who is releasing freedom of money detailing Binance's rise to crypto uh evolution and of course his US legal battle >> memoir and I'm excited to talk to Joe about the who is Satoshi Nakamoto and I'm also excited to talk to CZ about who he thinks Satoshi Nakamoto is.
5:21
You would imagine that he's in a position to potentially have a a good uh a good take on that.
5:28
Uh anyway, there is a ton of uh AI news.
5:30
Uh Andy Jasse released the uh 2025 shareholders letter.
5:34
Amazon is known for fantastic shareholders letters dating back to 1997.
5:38
Um I thought he did a good job of sort of resetting the AI narrative.
5:43
There's this uh AI lab horse race going on.
5:45
Of course, we've been covering it all week.
5:46
Uh anthropics mythos preview and project Glass Wang launched on Tuesday.
5:51
Quickly followed by news today that OpenAI also plans to deliver a model with advanced cyber security capabilities to key internet infrastructure providers.
5:59
And there's this debate going on over how and when these models will roll out.
6:03
Um I think this is going to be an ongoing trend.
6:06
I don't think cyber security is the last model capability that will be slowly delivered to key companies first.
6:13
Um, cyber security is a perfect fit for powerful coding agents and people have been digging into exactly how uh some of these uh zeroday exploits, some of these bugs and vulnerabilities were discovered.
6:26
And uh it makes a ton of sense that if you have a model that's fantastic at coding, it can basically try every single coding exploit, try new coding exploits uh across a huge number of open source packages, submit poll requests, and generally harden the uh internet infrastructure that we all rely on.
6:45
on. So in general it seems like the the roll out of uh Mythos although people are disappointed because they want to play with the latest and greatest model even if it's very expensive uh it seems like it's uh it's having a positive
6:58
effect and uh and should be uh a a bit of a white pill for uh containing powerful models having them have proper impacts having them have a positive impact on the American economy on our security on all these different things. Um I do think I wouldn't be surprised if
7:13
Um I do think I wouldn't be surprised if we see something similar happen in biosafety.
7:17
Now the biosafety AI research loop is a little bit longer because you might have to go to the lab.
7:23
It's not entirely uh existing in a computer in a virtual machine that you can spin up and just uh you know brute force reinforcement learn against.
7:32
But you could imagine if a model develops capabilities maybe in the next run, maybe in middle of this year, uh if a model becomes powerful enough to design a harmful virus or something like that, uh you would want the lab that creates that model to deliver that to the scientific community and companies that can protect the population against the development of new harmful biological viruses.
7:59
just like we're protecting the internet against uh cyber security viruses.
8:03
And so I I I'm I'm not exactly sure where this all goes, what the other 10 steps are, but in general, it seems like there's going to be a pattern of a powerful model becomes capable of doing something.
8:15
something. uh that it makes sense to share with the particular community that can defend against that new capability and then make sure and then the the entire community needs to make sure that that capability is carefully under control before releasing a a version of
8:30
that model that can still you know in the biosafety example like you still want a model that can help you learn about biology learn about uh how viruses are made how they mutate uh this is important for education and augmentation of the of scientist from, you know, high schoolers all the way to professionals. But the most
8:48
But the most advanced technology, it makes sense to put it in the hands of people that can actually take a real uh have a real impact on that immediately before uh rolling it out broadly.
8:59
But uh Andy Josie uh sort of zoomed out and was stepping back from the horse race because Amazon's a partner with basically everyone in the ecosystem uh and has their own models.
9:12
And so he shared this uh shareholder letter zooming out on the state of AI, the state of uh Amazon's plans and he shares a bunch of very interesting anecdotes about his personal life.
9:24
So we should read through some of this.
9:26
Uh he says, "When I graduated from college, I wanted to be a sports cer.
9:29
Uh after sending my resume to many small markets around the United States and only getting two nibbles, I settled on doing sports production at a major network.
9:37
To make extra money, I coached my former high school soccer team and worked at a retail golf store.
9:43
Six months later, a college classmate convinced me to interview at the consumer products company where he worked and I spent three years as a product manager there.
9:52
I left that job to try some of my own businesses.
9:54
After deciding the these businesses weren't my calling, I tried short stints at sales and investment banking before going back to grad school and ending up at Amazon 3 days after my last final exam in May 1997.
10:06
Not exactly a straight line.
10:10
He says AWS followed lots of squiggly lines, too.
10:12
And of course, Andy Jesse is the uh by and large the creator of AWS.
10:17
That was his major project during his tenure and founder. >> Yeah.
10:23
deserves so much credit in uh building that business.
10:26
Uh the original vision included storage, compute, payments, and human intelligence.
10:30
They had a product called Mechanical Turk where you could go and dispatch a specific task.
10:36
You would have to build sort of a web UI, but it was the original uh sort of uh data capture tool, but it could also be used for little things like uh manual translation tasks.
10:48
People weren't really using it for customer support tickets, but >> data labeling.
10:52
data labeling before you really needed mass data labeling.
10:54
But it was that type of business and there was always a question when scale started like is this just mechanical Turk?
11:02
Is this business process outsourcing?
11:06
Obviously that went on to a fantastic outcome with meta but uh it it became a different thing and quickly moved towards what we see in the uh in the expert networks and uh data collection at that's much more nuanced than uh a single task on demand.
11:20
But AWS this was in the vision.
11:22
Uh and they and they wound up um pulling away from that and sort of refocusing.
11:26
So Andy Jasse says some of those uh eg storage and compute became lynchpins in AWS.
11:30
Others didn't uh uh others didn't succeed.
11:34
We initially uh we didn't initially plan a database service.
11:38
And when we built one, our first attempt failed to get traction.
11:41
We went back to the drawing board and built new relational and non-reational databases which have resonated well and become core to millions of AWS applications.
11:48
When we launched EC2, our compute service, it was a single instance in one availability zone, Linux only with no autoscaling, load balancing, block storage or private networking.
11:58
Over the time, we added those capabilities and hundreds more services.
12:02
And you see that when you go into the AWS dashboard, it is chalk full of different products.
12:05
AWS was initially attractive to startups.
12:10
Companies like Door Dash, Dropbox, Pinterest, Slack, and Stripe were among many that built their businesses on AWS.
12:17
Uh, pundits said that enterprises and governments would never use AWS.
12:19
Wait, what is going on here? I am I >> out of order.
12:26
>> I'm I'm out of order here.
12:26
Let me find the actual link on here and I'll stop reading from the paper because I printed the wrong here.
12:34
So, uh, he says, uh, pundits said enterprises and governments would never use AWS for anything substantive.
12:39
But in 2008, Netflix, which was delivering, uh, DVDs in the mail for almost a decade at that point, decided to move all of their applications to AWS.
12:50
Then came big commitments from GE In it, and others.
12:55
And eventually, the CIA chose AWS as their partner to build their classified cloud.
12:59
cloud. growth came fast and furious and as it accelerated so too did our capital expenditures capex with dilutive with a dilutive impa impact on free cash flow and so he's he's starting to make the case that there's this trade-off between free cash flow and capex and this will
13:17
come back when he talks about his plans for uh taking advantage of the AI boom so he says at our first at at at at our 2014 more than 12 years ago AWS operating plan review the discuss started with a senior leader at the company musing, tell me why we're doing this business, like why are we doing this? It was confusing and it was very
13:35
It was confusing and it was very different from being an online bookstore and then eventually the everything store, but it felt it felt different but then eventually it started working.
13:43
So he says AWS has worked well for Amazon but a straight line not really.
13:47
Uh there's a bit there's a band I like from New Zealand called the Beths.
13:51
Have you ever heard of the Beths?
13:53
We got we got to listen to the Beths.
13:55
Uh they've written several excellent rec records with thought-provoking lyrics.
13:59
I eagerly await new releases.
14:00
And when their latest album dropped last summer, uh titled Straight Line Was a Lie, it made me think how preant that expression is.
14:09
Most long-term endeavors do not follow a linear >> top generally considered to be future me hates me and expert in a dying field. >> Interesting. >> And Little Death. >> What? What?
14:23
Yeah, I I I'm gonna listen to the Beths on the drive home today.
14:25
Uh he says >> any any Beth's uh heads in the in the chat.
14:33
>> Um the uh so he see he he's he's reflecting on his career and uh the twists and turns in building AWS.
14:39
He says, "Most long-term endeavors do not follow a linear straight line up and to the right. Progress jumps around.
14:46
It'll zig up, then sometimes stall or zag down or force you back to the starting line.
14:53
Sometimes it feels like you're running in circles, but the path is rarely straight.
14:57
That's because the world is complex and new technology, business model, invention, competitors, global issues, or people and cultural shifts can come into play.
15:06
Uh when we're in the middle of some of the biggest inflections of our lifetime, eg AI, robotics, space, industrialization, geopolitical and military conflict.
15:14
And just as proficient golfers need to be skilled across driving, approach shots, chipping, and putting, durable companies must be adept at managing different elements of inflections.
15:25
I'll share some of our lessons below and why we're bullish on what's ahead for Amazon.
15:29
So he talks about how broad Amazon is these days.
15:34
Retail, logistics, AWS, ads, Kindle, Alexa, pharmacy, there are too many new efforts to in flight to mention them all.
15:42
uh he talks about uh the the the long push to uh to bring robotic automation acquiring KA in 2012.
15:49
He also talks about uh all of the benefits that Amazon has brought to rural customers but who are often deprioritized by logistics.
16:00
This is classic thing when you launch an e-commerce site.
16:02
Do you apply your flat rate shipping to Alaska?
16:07
Because every time someone ships something to Alaska, it's going to charge you an arm and a leg.
16:10
uh he Amazon's been able to solve it through a network of that's delivers over a billion packages each year.
16:17
Customers living in over 13,000 zip codes spanning 1,200 square mile uh 1,200,000 square miles.
16:26
Um and he's also working focusing on closing the digital divide in rural communities.
16:31
So, uh things like highspeed internet access, internet, LEO, uh he's been talking about Amazon Leo, the low Earth orbit satellite network.
16:40
Um but um he he makes this point that uh Amazon must be willing to pursue parallel paths when it's unclear what'll best drive the trae the desired trajectory.
16:53
He says two is greater than zero.
16:55
When I was a kid I used to go to New York Ranger games, New York Rangers games with my dad.
17:00
I loved hockey and it was a high quality time together.
17:02
I looked up to my dad still do and hung on his every word.
17:07
One game, my dad noticed that one of the Rangers defenseman, Dallas Smith, had gone missing from the bench and stood up and exclaimed, "Where's Dallas?"
17:13
Uh, to which a nearby fan said, "In Texas, moron."
17:16
So, yes, it's very weird that his name is Dallas.
17:21
I guess is that that's the confusion.
17:23
So, yes, it's fairly obvious that two is greater than zero.
17:26
But too often companies focus on what looks most tidy instead of ensuring they have enough efforts in play to achieve an important outcome.
17:35
Let's go back to fast delivery in our retail business.
17:37
We know how much customers crave it and we see higher order completion rates when uh delivery promises are faster.
17:43
So he talks about, you know, all the things that we know about Whole Foods and rolling out more stores, rolling out more um more um uh just investments in the core Amazon business.
17:57
But then he goes on to talk about uh artificial intelligence and he says uh if there's an obvious path to changing your trajectory, take it and run.
18:05
Uh but most new jumps aren't forward like that.
18:07
There's invention and experimentation required and pursuing multiple paths gives you the best chance to find it.
18:12
When you identify disproportionate inflections, bet big.
18:16
Choosing which inflections are truly seinal versus just interesting requires judgment.
18:20
Reasonable people can disagree, but if you believe you found one of these disproportionate shifts, you want to invest as aggressively as you possibly can.
18:26
This will create investment spikes that will invite scrutiny, but the game changers don't typically accommodate smoother investment horizons.
18:32
One of these one of these seminal shifts, of course, he says, is AI.
18:35
And so, he says, "We've never seen a technology more quickly adopted than AI."
18:40
When Chat GPT launched in November of 2022.
18:42
It reached 100 million users in two months, four times faster than Tik Tok and 15 times faster than Instagram.
18:50
Chat GPT already has over 900 million weekly active users.
18:54
Both OpenAI and Enthropic have run revenue run rates reportedly approaching $30 billion.
18:59
These are breathtaking numbers for companies this soon after their commercial launches.
19:03
And he has this great throwback to Thomas Edison and the dawn of electricity.
19:07
A lot of people are looking for comparisons for what AI uh pattern matches to.
19:11
And he goes back to the first commercial power station which launched in 1882.
19:17
So at the time most people understood the first commercial power station as a way a better way to light a room.
19:27
That was going to be the main benefit of electricity.
19:31
Uh it was going to replace lamps and you were going to have electric lights.
19:34
Uh but what they couldn't see was that electricity would eventually reorganize every factory, home, and industry on Earth.
19:41
And he says that AI may have a comparable impact.
19:46
The difference is that electricity took 40 years to get where it was going and AI appears to be moving 10 times faster.
19:53
And he says that Amazon's smack dab in the in the middle of this land rush and companies are choosing AWS for AI three years after AWS launched commercially.
20:01
It had a $ 58 million run rate three years in and Amazon was already a big business at that time.
20:07
So, you know, he's talking about the twists and turns of launching AWS.
20:09
It's a >> you know, a lot of products worked.
20:12
It's very quaint to be three years in, have the backing of, you know, a ma a massive company, um, and and still three years in, only hit 58 million in run rate.
20:22
He compares it to three years into the AI wave, which of course started in 2023, basically, and now we're in 2026.
20:29
AWS's AI revenue run rate is over 15 billion in Q1 of 2026, which is nearly $260 times bigger than AWS was at the same point.
20:42
and it's ascending rapidly and so he he highlights a bunch of reasons why uh customers are choosing a AWS for AI.
20:50
Uh obviously they have a product in sort of every single category now model building uh high performance inference lower cost inference that runs on tranium their custom silicon agent building secure environments etc.
21:02
Um but he says that AWS could actually be growing faster and they are in fact limited on uh capacity. So AWS added 3.
21:09
9 gawatts of new power capacity in 2025 and expects to double total power capacity by the end of 2027.
21:18
And AWS is monetizing that capacity as fast as it's installed.
21:24
In Q4 2025, AWS reported 24% year-over-year growth and a 142 billion revenue run rate.
21:31
That's a lot of absolute growth and yet we still have capacity strains that yield unserved demand.
21:36
Uh, as an aside, two large AWS customers have already asked if they could buy all of the Graviton instance capacity in 2026, which is their widely adopted custom CPU chip.
21:46
Uh, and he says, "We can't agree to these requests given other customers needs.
21:51
You can't just say, okay, we're giving everything to one company."
21:54
Uh, but it gives you an idea of the demand.
21:56
And so, uh, he goes on to talk about the other the the other projects.
22:00
The chips business is on fire.
22:03
uh they're talking he talks about uh in the CPU space virt virtually all of the workloads ran on Intel chips until uh they invented graviton in 2028 uh has a 40% better price performance and then of course uh they're they're working on tranium and nitro as well and so um he he goes on to explore a little bit of how the AWS cache cycle works in a way that's that's that's faster than uh AWS um and it requires more short-term capex.
22:31
So AWS has to lay out the cache for land, power, buildings, chips, servers, and networking gear in advance of when we can monetize.
22:38
And so there's been a lot of reporting about uh our data centers delayed.
22:42
We're going to talk to Sager and Jetty about some of the some of the news and and whether and the political push back to the data center buildout, but um he says that uh it typically takes between six and 24 months before we can start billing customers depending on the component.
22:59
However, these capex investments fund assets with many year useful lives.
23:01
30 plus years for data centers, five to six years for chips, servers, and networking gear.
23:08
And the free cash flow and return on investment cap invested capital for these investments are cumulatively quite attractive a couple years after being in service.
23:16
However, in terms in times of very high growth like now where the capex growth meaningfully outpaces the revenue growth, the early years free cash flow is challenged until these initial tranches of capacity are being monetized and revenue growth outpaces capex growth.
23:31
We've been through this cycle with the first big AWS wave where they invested a ton of money in capex building the servers uh before they were able to ramp revenue.
23:39
able to ramp revenue. uh and he says we like the results even though we've been through that cycle of high capex drawing down on free cash flow and he says we expect to feel similarly about this next wave with a much larger potential downstream revenue and free cash flow >> and so he goes on to talk about the but I thought it was a very good letter >> yes >> touches on a bunch of different stuff I
24:01
think this is what people wanted out of Jasse yeah like about a year ago right yeah >> he was getting um you know people were were constantly ly kind of chirping at at Amazon leadership and and wanting some kind of like basically lay of the
24:19
land like this to show that Amazon had a broad understanding and and actually had uh you know real leadership and and was >> committed committed to um you know being being a real player. >> Yeah. Uh well, in other Amazon news, >> Yeah.
24:33
Uh well, in other Amazon news, Amazon Pharmacy to offer Eli Liy and company's new GLP1 pill foundo via same day delivery.
24:43
Shield Monoton says this thing is going to fly. Amazon is up 3%.
24:47
I don't know if it's on this news.
24:49
>> Yeah, it's hard to say.
24:49
Amazon's actually almost up 5% today. >> Yeah.
24:54
Uh, and I would I would expect that to be because of uh the letter, but people tend to buy a lot of GLP-1 uh drugs, too.
25:04
So, >> but it does seem like a good I mean, we were we were talking about this with the uh uh some of the the the fast ramp of that one company um in direct to consumer GLP-1 and peptides.
25:15
And there's so much skepticism about um fly by night peptide operations.
25:22
Where are they being compounded? Are they safe?
25:24
Do they contain even what you think they contain?
25:28
And giving consumers an option that's something as you know established as Amazon with all of the all of the guard rails that they have in place uh feels like a very positive uh move for consumers.
25:42
Uh before we jump into the next story, Jasse did share a letter to shareholders from 1997.
25:49
And there was I'll read the first two paragraphs.
25:53
>> Uh to our shareholders, Amazon.
25:53
com passed many milestones in 1997.
25:56
By year end, we have served more than 1 and a.
25:58
5 million customers, yielding 838% revenue growth to 147.
26:03
8 million, and extended our market leadership despite aggressive competitive entry.
26:09
But this is day one for the internet and if we execute well for Amazon. com.
26:15
Today online commerce saves customers money and time.
26:17
Time and money save both.
26:21
>> Uh tomorrow through personalization online commerce will accelerate the very process of discovery.
26:25
Amazon uses the internet to create real value for its customers and by doing doing so hopes to create an enduring franchise even in established and large markets.
26:33
Uh well they certainly did that.
26:36
Uh and and the letter goes on that to talk about h how it's all about the long term.
26:42
So even back then growing like absolute crazy still, you know, wanting people to think about uh think in decades and and so Jasse doing that now >> and they have a good track record. >> Yeah.
26:56
I mean Amazon's had decades of drawing down on free cash flow to invest in the future and uh they've had long history of communicating that effectively to the community and to the shareholders.
27:06
Um, >> I mean the level to which people miss the ads.
27:12
>> This has never I don't think this has ever happened before. >> Yeah.
27:15
>> In the history of content >> of uh of podcasting. >> Yeah. >> We miss the ads, too. >> Yeah.
27:21
All we have now is >> Well, uh we need we need some alerts because there's a there's a debate on the timeline about uh OpenAI's new cyber security product.
27:32
Uh the uh there was a post that was deleted and then uh Axios issued an update.
27:38
Basically the question was uh OpenAI is launching a a new model rumored to be called Spud trained on Blackwell sort of similar you know big model lots of capabilities uh and uh OpenAI's been working on cyber security products.
27:56
Will they gate the roll out similarly?
27:58
Are they running the same playbook?
28:00
Will they uh take a different path?
28:02
At what point will they make their models available?
28:05
And uh people are going back and forth and Andrew Curran is sort of clarifying here that the new model and the cyber security product are separate and only the spe the cyber security specialized model will have a limited release, not the new model itself.
28:20
So it looks like a general public release for Spud.
28:23
Uh Dan Shipper shared some extra uh commentary around this.
28:28
The Axio story floating around about OpenAI limiting the release of their newest model, Spud, isn't true.
28:31
He just spoke to OpenAI and it appears the story conflated two things.
28:35
They do have a cyber product.
28:36
They are testing with a trusted tester group, but this is not the same thing as Spud.
28:40
The Axio story has now been updated.
28:44
>> Yeah, there's a very there's a very strong argument to never release a model publicly that is specifically optimized for cyber, right?
28:51
Because like you're just inviting a bunch like think about like the teenagers out there.
28:55
I now get to be uh a super powerful hacker even though you're just kind of like probably should just be vibe coding like a fun little app or something like that, right? Yeah.
29:06
And so >> you you would think having some cyber security capabilities in the model would just be better if you're vibe coding a product.
29:14
It becomes secure out of the box.
29:17
box. I'm just saying I'm just saying like having this super powerful like cyber focused product shouldn't be the kind of thing that anyone like you should probably have to KYC to >> yeah sure yeah what do you think about this >> yeah I mean also I think you know when you zoom out on AI progress it is like
29:34
it is like very smooth um where like you know people were talking about this with mythos yesterday where like well actually if you run even like an open source model uh and you actually run enough times you actually can find similar you know exploits And it's just like kind of the efficiency of of the new model versus the the smaller open source ones. >> Yeah. >> Yeah.
29:52
>> So like >> like I I I'm pretty sure right now I could take you know 5.
29:54
4 >> and I could just run it a bunch of times and I could find a lot of exploits like people have the capabilities right now.
30:01
Maybe it's like a little >> flagged. >> Sure. Yeah.
30:04
But and also like yeah I think I mean at some point like a lot of the coding agents I think you'll just see like in the you know in the system prompt or whatever of the coding agents it'll be like yeah make sure you're checking to see if any if there's like big security vulnerabilities.
30:16
Even right now you can just ask you know codeex whatever you're building something like are there errors or are there you know security problems and it will solve them.
30:26
>> And this is the nature of of every uh every advanced model is that in order to understand how to fight something you'd have to know how to build it.
30:32
And this is uh this is true.
30:34
I mean, I'm sure that uh the folks at Crowdstrike or Palo Alto Networks like could definitely if they went black hat, it would be bad for everyone even in the pre-AI era. And that remains true.
30:45
And so, um having at least as much economic incentive as possible to put the resources and the tokens and the inference budgets towards like white hat hacking is good.
30:56
There's also somebody in the chat is making the comment that there's a uh there's a uh there's a lot of precedent for this with um with uh bug bounties and like time disclosures.
31:10
So oftentimes white hat hackers will go to companies and say uh we found a really bad vulnerability.
31:15
Um we're giving you 90 days until we publish it.
31:20
But it is in the public interest to know that this that this uh vulnerability exists broadly.
31:24
So, we have to release it, but also we want to give you the time to react to this.
31:30
And so, uh, it it feels like you're sort of holding that company hostage a little bit.
31:37
It can be a little bit tense, but I think if it's done, uh, it's if it's done carefully, it can be sort of a win-win.
31:42
Um, >> yeah, but I think regardless, like I think more KYC is probably the future, right?
31:48
Even if you're just talking about uh like risk of distillation stuff like this like I think I've talked about this before where like >> yeah at some point you need you need more KYC to ensure like people aren't just like you know training off the model or or doing like nefarious things. >> Yeah. Yeah.
32:04
>> Uh Meek Mill >> pulled out a slide from Bill Aman.
32:09
>> The slide says a small percentage of songs are listened to.
32:11
The overwhelming majority of music tracks receive zero or minimal engagement.
32:15
AI is poised to exacerbate this reality.
32:17
And so it shows that 02% of songs are culturally and commercially relevant.
32:23
Commercially they relevant is 10% of songs streamed a thousand to 100,000 times.
32:31
>> And then Meek is dropping that into what looks like Claude saying you're not in that 88%.
32:36
You already skipped the whole bottom of the pyramid.
32:38
You're already in that top 2%. People know your name.
32:39
They search for you specifically. They stream on purpose. That changes everything.
32:44
You already have the hardest thing, attention.
32:48
You don't need the algorithm to find you.
32:50
Your fans already look for you.
32:52
So while AI is flooding the market with millions of trash songs that nobody This is AI throwing AI on the >> This is crazy.
33:01
Your catalog just sits there collecting streams because people want Meek, not just a rap song.
33:05
and Dimes Square Holdings says, "First in my bloodline to see a rapper with AI psychosis commenting on a deck from >> I think it's a I think it's a reasonable >> it's a reasonable analysis."
33:19
>> It's a reasonable analysis.
33:20
>> I just think I I just think it's a little bit unfair for the AI to be dunking on the other AI.
33:24
Is this kind of like a crabs crabs?
33:27
There's a whole story about this uh in the journal the other day about um a uh a group a local group that's lobbying against uh data center development using AI tools chatgpt like very heavily to understand the legal code how they can uh how they can organize who they should be calling.
33:51
It sort of feels like a good use of AI in the sense that they're uh they're exercising their democratic rights properly through the correct channels.
34:00
Like it could be so much worse. I don't know. What do you think? >> Yeah.
34:03
Well, hopefully like by using the model like models enough, they'll be like, "Oh, wait. This is actually good." Yeah. >> Yeah.
34:07
Or like or like there are some parts that I like narrowly, but do we need this data center in my neighborhood? Maybe not. Yeah.
34:13
Also, specifically on this, I think it's interesting like among celebrities, it seems like rappers specifically are like really leaning in a lot more than other like >> types of celebrities, right?
34:23
You see like little baby little baby, not little baby.
34:27
Um >> uh there was a post yesterday about someone who who got paid to like set up OpenClaw forum. Yeah.
34:31
You've seen this a bunch. Yeah.
34:33
It's just funny like you don't see actors talking about their little baby was second after baby Keem. >> Yeah. That's right. That's right.
34:39
Uh, I mean, Matthew McConnA said had some words about AI saying, >> "Oh, yeah.
34:44
When he was gonna log in, he needs to log in."
34:46
>> Well, no, no, that was separate.
34:46
Uh, like, wasn't it like months?
34:48
It It was like months, months, months and months later, he was like, "This is coming.
34:53
Like, you need to be prepared for this.
34:54
You need to work alongside of it." >> Yeah.
34:56
But he's not talking about his specifically. >> Yeah. Exactly. Exactly. >> Yeah.
34:59
I guess Ben Affleck had that company, right? >> Yeah. Yeah. Yeah. But, uh, yeah. >> Yeah.
35:03
Ben Ben Affleck already got the uh the nine figure exit. He He's good. >> Yeah.
35:09
But you would you you you would imagine that uh that AI actually might be a useful tool for understanding the impact of building a data center in a particular community because everyone is debating the the economic impact.
35:20
How many jobs will be created?
35:22
What's the environmental impact and uh being able to crunch through all that all those trade-offs so that the community gets to a net like a net positive impact that the population can basically vote on and be happy about and say, "Yeah, like we made this trade-off properly."
35:37
and we feel like we're getting the benefit be because maybe it's generating a lot of tax revenue.
35:44
Maybe the tax revenue is very durable.
35:45
Maybe the tax revenue is going to the right place.
35:47
Is it going to a tax refund because or is it going towards a project that people don't actually support?
35:52
And so there's a whole other question of uh for the local community.
35:56
Is that tax revenue meaningful?
35:58
Like what dollar value do they put on new tax revenues for the city?
36:02
Depends on what the city's building or doing um with that with that revenue.
36:05
Um anyway, uh what is this post by IE gender?
36:11
>> Actually, that's not impressive.
36:11
The concept of a Dyson sphere was already in the training data.
36:14
This is like, you know, we build the D, you know, everyone builds the Dyson sphere and then someone's someone's coping and just saying like, yeah, I mean, it's not that impressive.
36:24
>> You're just watching the Dyson sphere be built around the sun thinking like, I'm not that I'm not that important.
36:28
Uh here's another like self-referential thing like you know AI should AI be used to uh fight data center construction.
36:35
Uh today Meta began removing ads from attorneys who are seeking clients that claim to be of harmed by social media while under the age of 18.
36:44
And so there's been the these class action lawsuits have been a big uh a big you see them on social media all the time.
36:54
Usually uh it's some sort of data breach or some sort of uh you know random product that they're targeting you for.
37:02
And uh I I feel like a many people just sort of scroll past them because the the the the default class action is like you wait a long time and then maybe you get a check for $5 in the mail.
37:12
Um but uh Meta has begun removing advertisements from attorneys.
37:17
Uh what is their justification for this?
37:19
Lawyers across the country are now seeking new plaintiffs in the hopes of bringing a class action lawsuit that could result in lucrative verdicts.
37:25
It's unclear if any of them have been backed by private equity as the California lawsuit appears to have been.
37:30
Uh Axios has has identified more than a dozen such ads that were deactivated today.
37:34
Some of which came from large national firms like Morgan and Morgan and Morgan.
37:40
Almost all of them ran on Facebook and Instagram.
37:41
Uh some some appeared on threads and messenger plus Meta's audience network.
37:45
One such ad read anxiety, depression, withdrawal, self harm.
37:49
These aren't just teenage phases.
37:51
They're symptoms linked to social media addiction in children.
37:53
platforms knew this and kept targeting kids anyway. >> Yeah.
37:57
So, Meta has something in their terms of service that says, "We also can remove or restrict access to content, features, services, or information if we determine that doing so is reasonably necessary to avoid or mitigate misuse of our services or adverse legal or regulatory impacts to Meta." >> Huh.
38:14
>> Is basically like we're not going to let you use our product to take legal action against us. >> Yeah.
38:20
I wonder where where the uh the class action recruiting will go next.
38:26
You know, >> it'll go everywhere else. >> Maybe out of home. >> Out of home. >> Yeah. >> Could go podcast.
38:32
>> I mean, it's such a broad case that Yeah.
38:35
Well, YouTube is >> it's easy to it's relatively easy to reach like Facebook and Instagram users. >> Yeah. Especially young people. It's everyone. Yeah.
38:42
So, they they just need to cast a wide net.
38:44
But, uh it'll be interesting to see how that how that develops.
38:48
Um, >> has anyone built an outofhome advertising network for uh classrooms? >> Classrooms?
38:54
What do you mean >> like teachers?
38:57
>> I don't think people want to add advertisements.
39:00
>> Kidding, kidding, kidding.
39:02
>> Anyway, uh, the spreadsheet will become irrelevant, says Buo Capital Bloke.
39:04
No, the spreadsheet is eternal.
39:06
The spreadsheet paradigm is capitalism.
39:08
The two are irrevocably intertwined.
39:10
We were using spreadsheets 3,000 years ago to trade oxen.
39:14
We will still be using them in 3,000 years.
39:16
Long live the spreadsheet.
39:18
And he shares a uh a stone tablet that appears to be a spreadsheet.
39:24
Uh this is in reaction to signals post that Microsoft 365 and Google workspace have maybe four to five years of relevance left simply because the document spreadsheet paradigm itself will become mostly irrelevant.
39:34
It already makes zero sense to draft, review or an analyze anything without a native AI environment around it.
39:39
That gap only widens over time.
39:42
Most communication including email, chat, status updates is heading towards agent mediated flows where humans set intent and AI handles execution. Um I don't know.
39:53
I mean it it it is like both can be true here because you could be in a world where if you need a spreadsheet like the code is written on the fly and instantiated like we saw ramp launch ramp sheets very very quickly and it was a very fullfeatured product that was clearly only possible to build that so fast like cloning Google Sheets is is used to be insane.
40:17
Uh we had some luck cloning Slack recently.
40:22
>> Our our uh our intern built like a very very convincing clone.
40:25
It's sort of crazy >> in about like an hour.
40:29
Like I actually >> I think it was on the Was it on the $200 plan? >> Wow.
40:35
Like that's it's incredible.
40:35
Um, so, uh, yeah, like I I I think there's still the question of like, you know, um, actually getting that to feature complete, maintaining it, really, you know, serving it, hosting it, that all of that seems like a hassle compared to just, uh, signing up on a consumption basis or a seatbased basis for a lot of SAS.
40:58
I'm still sort of uh you know not a firm believer in like the near-term SAS apocalypse broadly but uh it uh it does it does I I think the more likely scenario is that you will see um you will see software instantiated on like in real time.
41:17
in real time. So if you're building something and it requires a spreadsheet to visualize and you're already seeing that with a lot of the chat apps when if you ask for a deep research report or something that uh that requires sort of building a timeline or a chart it can write Python it can write HTML that will
41:34
>> the other the other thing is just giving giving customers a lot more flexibility around the product and thinking that like okay if you're buying buying a piece of software would be like buying like a home where you get the home and then you can make changes to it >> to fit your own needs over time. >> And so we'll see we'll see what
41:51
>> And so we'll see we'll see what ultimately changes, but you can imagine >> a world where, you know, it stops being I I forget who was on the show, but >> they were talking about how uh Oh, it was it was um console console. com.
42:04
>> Um talking about how uh instead of having like a request a feature button, you just let people build it themselves. >> Yes.
42:13
Well, um, there's been some back and forth on the timeline between Nate Silver and Nikita Beer over whether or not links are truly deboosted on X.
42:20
Uh, Phipe Le Moy said, "After the exchange between Nate Silver and Nikita Beer, I did a little test to check whether that was true."
42:30
And to my surprise, what I found suggests that link deboosting was indeed reversed.
42:35
What I did was randomly sample 15 tweets by the New York Times between 2019 and today.
42:40
That feels like a small sample.
42:43
It feels like you should look at maybe a larger swath there.
42:45
But he computed the weekly average number of likes and retweets they got and plotted the the results along with a trend line.
42:55
The idea is that likes and retweets are probably a decent proxy for reach and the New York Times only posts tweets with external links.
43:01
So by looking at this we should be able to see how many changes in the al any changes in the algorithm with respect to how links are treat treated.
43:07
As you can see it's pretty clear that starting around the spring summer of 2023 posts with links started to be penalized and eventually they were completely nuked until the spring summer of 2025 when a reversal to that policy seems to have started.
43:21
To be honest, this isn't what I was expecting to find.
43:24
So it even if it's just a quick and dirty test, it's hardly definitive proof.
43:30
Uh it's good news and I thought I'd share the results.
43:32
I'd share the results. There is a question of like even so links links yeah they there was clearly like a deboosting moment although some really good stuff could break through like uh there were a few examples of people just posting links to um uh links to uh the
43:50
uh uh like Google docs basically and those would still rip somehow and I don't know if that was like a specific link but >> I think one thing has remained true the entire time which is that that if If you are linking to content that is genuinely very interesting, it can still do numbers. >> Yeah. And and there is a little bit of >> Yeah.
44:07
And and there is a little bit of uh maybe some uh some feature of the New York Times where if you spent a year or two on X knowing that uh okay like there's sort of this adversarial relationship with links, you're going to open it in the browser.
44:23
You might actually just develop a different habit of okay, I go and read the apps.
44:27
Like I definitely develop the the the muscle memory to open the Wall Street Journal app regularly and scroll that news feed separately.
44:38
Uh and I don't really look for as much craw cross cross-pollination as uh as I thought.
44:42
Um anyway, we have Sager and Jenny from Breaking Points in the waiting room.
44:46
So we're bringing in to the TVPL job.
44:48
Sager, how are you doing? >> I'm great guys. Thanks for having me. >> Thanks for coming on.
44:53
Uh where should Let's start with the data center thing.
44:57
We were talking about Andy Jasse. Oh yeah.
44:59
Yeah, the tie is I'm getting brutally tied mom. >> Yeah.
45:03
Um, >> dude, uh, Jordy gets an exit and immediately starts dressing like a tech What's What's going on here, man?
45:10
>> To be to be clear, I've been I've been I've been having I I have the limited edition >> technology in motion. >> Okay.
45:19
Well, why has nobody sent me one? How come I >> dro? They're in the works. We'll send you one.
45:24
Um, >> you're going to be you're going to get to wear TVPN all day long. Yeah, >> that's great.
45:30
Uh, so we were talking about uh Andy Jassis's 2025 2026 shareholder letter, $200 billion of capex, tons of new data centers coming online.
45:39
Every this applies to every company.
45:41
>> You were hoping for a bigger number, wouldn't it? >> Yeah. >> Oh, yeah.
45:44
I mean, of course, as an American, I just want all of my farmland.
45:48
I want all the trailer parks pushed out and I just want to make sure that there's beautiful data centers uh that are just sitting on previously like taken care of and people with generations just get kicked out.
45:59
So I wanted 400 billion 600 billion something like that. >> Yeah.
46:03
I mean maybe we can start with the the the shape of the push back against data centers because it's fallen in a few buckets but uh let's just start with like the big one which is energy.
46:12
uh what are the headline numbers and fears that people are are pointing to the case studies that uh people are are nervous about the energy impact specifically?
46:26
>> Well, I think especially guys, you know, this there's a pre-Iran war conversation, there's a post Iran war conversation.
46:31
I think that's really important to say because, you know, who knows where the price of oil will eventually stabilize, but when you have high inflation at the gas pump and likely at least some moderate increase in electricity bills, we have we don't know exactly where things are going to stabilize.
46:46
You're going to have a lot more cost consciousness whenever it comes to energy.
46:49
Now, especially in the midst of a data center conversation, I know that the data center pro data center people are always telling us, don't worry, it doesn't actually impact your electricity bill all that much.
47:00
Nonetheless, there is a feeling there.
47:02
And John, I just sent you that study or that story this morning, which is very interesting.
47:06
My colleague Emily Jashinsky actually talked to me about this, but the a Wisconsin city has now been the first in the nation to actually pass an anti-data center referendum.
47:13
And so, the ballot measure is basically the last thing that the voters in that town felt that they had at their disposal to effectively ban the entire city from approving any of these new projects.
47:26
Do you guys remember the guy who went viral in New Jersey who blocked the data center?
47:32
I interviewed him on my show.
47:32
He was a longtime viewer actually of the program.
47:36
He was just like a normal uh activist type, but hadn't really engaged with it.
47:40
And he went through the zoning and he was like, "Look, these developers are making all kinds of promises and he was concerned about water."
47:46
And I know, you know, again, the pro people are are always telling me that that's not the case.
47:51
Maybe, you know, I got to see a little bit more evidence for myself, but there was an problem and city council. Go ahead.
47:57
>> Is your mic I I I don't know that we're you're on the correct mic. We might be on that.
48:01
>> The gain might be a little high.
48:01
I will I will give everyone some news about this.
48:05
Wisconsin city passes nation's first anti-data center referendum.
48:07
The vote suggests ballot measures could become a powerful new tool for grassroots activists.
48:15
>> The chat thinks it's a foreign advert.
48:20
>> Um let let's hear if it sounds any better now.
48:23
>> Is it a little better or turn down? >> I think that's great. There we go. >> Thank you. >> Amazing. >> Okay.
48:28
So, uh is so >> is this uh is this what is this local Wisconsin city referendum like the new playbook that will spread all over America?
48:40
Are there other jurisdictions that are already looking to copy and paste this?
48:44
How do you think this where do you think this goes?
48:46
>> I definitely do think it will serve as a model especially as other remember this is really a bottomup phenomenon.
48:53
at the community level and here in the state of Virginia where I live 40% of our power is actually consumed by data centers and so you've seen it became a major issue in the gubanatorial campaign both the Republican and the Democratic candidates were against data centers and both a lot of the candidates are seeing
49:13
all of the energy I'm sure around this I'm saying at the community level I'm sure you guys also have seen all of these viral videos I referenced the one more recently of this trailer park which is being basically told they have to go out because they're going to build a new one. There's the famous one recently, I
49:26
There's the famous one recently, I think it was in Kentucky, of a woman being I think she was offered like $20 million for her land.
49:32
She's like, I'm born on this land.
49:34
I'm going to die on this land.
49:36
So, I I really think that this is one of those bubbling political issues which no major polit politician, maybe Bernie Sanders, the only one that I've seen which has been willing to like jump on top of it.
49:47
Uh, but I think it's going to be a major issue in 28. 28.
49:50
I think in 28 both candidates are going to have a data center uh platform.
49:55
Maybe the Republican one, depending on who it is, is going to try and square the circle around GDP, but I don't think that voters want to hear anything about it.
50:05
That's just my my personal opinion.
50:08
>> Do is is the sense in Virginia that Virginia would would be better off if the state had never had a data center?
50:14
M >> well it it's complicated.
50:18
Remember, you know, we're full of a military-industrial complex, but uh don't forget this.
50:22
We had Amazon, remember when they were going to leave New York and they were going to come here.
50:26
They're actually going to come near where I live.
50:27
It it really didn't work.
50:29
And there's a lot of local opeds.
50:31
They're like, "Hey, we didn't get all the jobs that we were promised.
50:32
Uh Virginia threw all these tax credits."
50:35
And so people do feel really taken advantage of, I think, especially by Amazon here in Northern Virginia.
50:39
But look, the backbone of our economy is always going to be the military-industrial complex and all of these like ridiculous server farms that serve the CIA and the Pentagon.
50:47
But I mean, in Oregon, I think it was 30% of power in the state of Oregon is being used by data centers.
50:53
It's like 20% in a few uh uh different states.
50:56
Virginia is definitely we were the highest in the nation.
50:59
But I can tell you at the organic level, Fredericksburg, more of the rural communities where there are the new projects that were being us looked at all of those city councils, people were lining up for hours to campaign against this.
51:10
Same thing in New Jersey, people lined up for, you know, in the middle of the night.
51:13
And I've talked about this before, guys.
51:15
Do you know what it takes for a voter to actually care?
51:17
You could barely get people to come out for election day for the president.
51:22
Now for to come up for a local meeting against zoning.
51:24
Usually that's just really old people.
51:28
This time people are bringing their children.
51:31
They're sleeping in the room.
51:31
They're waiting all night just to be able >> What is your What is your What is your advice for uh the data center developers out there?
51:40
Cuz certainly I I like you feel you don't think that we should just not build any data centers. >> It depends.
51:48
You know, I I don't know.
51:48
I mean, I'm becoming more radical uh as as times go on.
51:51
And so maybe we do just need a butlerian jihad.
51:53
I'm testing the limits of your editorial independence, by the way. Shout out to you, Sam.
51:57
Uh but uh I mean, look, I I'm not giving any advice to the enemy.
52:01
I I think really what I would say uh to the tech community more generally, and John, you and I have talked about this is just prove to me that this is going to make my life better.
52:12
Uh and stop talking about all these scary things because I'm starting to believe you.
52:16
In fact, I do believe you.
52:17
believe you. Uh what is this new claude news that their new model is so scary they have to pre-release it to the cyber security company so that they can develop so no so that the new model can develop defenses against itself every day with you that the the fear-based
52:36
marketing like needs to stop because it's not it's not helping anyone like part of the whole back >> I don't know guys I mean Jordy you have always made the case and maybe you're right is that that's a great way to fundra every I'm the company that bought you wants more money. They have to go
52:49
They have to go and be like, "Look, we're changing the world.
52:51
We're going to destroy all these shops." Like, I don't know.
52:53
I mean, for for let's say like with Anthropic, I feel >> so so my point my point was that it it was very effective when there was no revenue in the industry, right? Yeah.
53:04
And and and it was kind of this kind of far out idea.
53:06
Nobody had had like a magical experience with AI.
53:08
They hadn't had like a question, didn't have anyone to ask it to, and then asked AI the question, they got a good answer.
53:14
question, they got a good answer. like when when when the average American had not had a very cool experience with AI, they hadn't generated an image that was, you know, photoreal or gotten help with their homework or help with,
53:26
>> you know, writing any of these things that like now everybody has had the experience of, I it clearly like was necessary to kind of marshall enough capital for bunch of upstarts to be able to compete with the biggest companies in the world on this like the the Googles of the world. And I just think at this
53:38
And I just think at this point I made the case like you know at the end of last year where it was like we need to stop we need I I think we need to stop this as as an industry because why would why would average American be excited about this if you're just trying to give them you know Terminator nightmares but clearly the entire you know some people in the industry still feel like they need to uh >> because I think they really believe it. >> Yeah. Yeah.
54:05
>> No, I think they believe it.
54:05
That's See, I'm with John.
54:06
Like I feel like Dario believes it and he just goes on every podcast in the world and says it like over and over again.
54:11
And at a certain point, especially like with the new Claude news, I'm like, "Dude, maybe I should just believe you."
54:15
And you know, people, what is it?
54:16
People are taking leaves of absences because they're afraid.
54:19
And I mean, you know, you can only call yourself the new digital god so many times before. Look, again, I'm a lite.
54:25
I I don't know a ton about the technology.
54:27
I listen to smart people like you guys and many others to try and figure out what's going on.
54:31
But if anything, I just want to be able to convey to the people who watch this show, uh, you're not very popular right now.
54:38
Uh, and especially in the midst of a global energy crunch.
54:40
Uh, I would just be real careful about strolling around town and talking about how it's going to bring jobs in because a nobody believes you.
54:50
They all think that their bills are going to go higher.
54:52
There needs to be I I think what this really needs, guys, is I don't think it can be solved at the federal level or sorry, at the company level.
54:58
level. I think the government is going to have to step in and genuinely like codify let's say the executive order that Trump wanted to put in place where every data center project is going to have to supply the initi the amount of energy that it's going to use it have to
55:12
prove it to the local city council to the state to the feds like there needs to be genuine democratic buyin if we're all going to decide like this is cool for us and I'm not sure that uh I'm not sure really that the tech companies are ready for that although maybe Sam is uh you guys saw saw his new social contract. I I was about I was going to
55:29
I I was about I was going to do a segment about it on my show, but I didn't have I didn't have the chance because of this entire Iran war thing.
55:36
But I mean, look, I mean, clearly he's he can foresee what the problem is.
55:38
I don't really agree with some of the stuff he laid out, but yeah.
55:43
Anyways, >> yeah, it was notable.
55:45
So, uh Deus had an interview with with Harry Stebings uh this week. It's just 30 minutes.
55:49
You you would probably appreciate it because Demis is, you know, one one of the the the godfathers.
55:54
Uh and he even was kind of talking about potentially uh you know one solution to this is like sovereign wealth funds like investing in the labs getting a piece of it so that every sort of citizen benefits.
56:08
I thought that was notable because it was, you know, Google and and uh you know, the Gemini team is the most heavily funded lab in in the entire world.
56:18
And um so we'll we'll see how this stuff works out.
56:24
How in in Virginia, uh Tyler Tyler on our team just dropped a a truth nuke.
56:30
He said in some localities in Virginia, 31% of total local tax revenue is from data centers.
56:35
Is there is there like do you think that uh like like I guess like part of what I'm trying to wrap my head around is like it seems like there are plenty of places in the United States where that uh putting a data center somewhere that would generate a huge amount of of of local tax revenue would be a net positive. Right. >> Maybe.
57:00
>> Maybe. And I believe that you're right that that >> individual areas should be able to decide is this an industry that we want to support is this an industry that we want as a part of like personally do I want um you know uh uh people you know
57:14
drilling oil like you know 10 ft from my property line like probably not right but there are places in the United States where people have decided we're going to drill for oil here and and we're going to you know be okay with those trade-offs and So I think uh I I I
57:32
generally you know I I've said this before I think there's a lot of reasons for somebody to like citizens need to understand okay what is the benefit of putting this data center in our county in our town and it and it needs to be it needs to be um there needs to be some
57:48
positive benefit other that for for the local community and so I think we agree there because >> you're not going to be using the models because the data center could be halfway around the world or in >> you still get you still get access all the AI tools that you want. It doesn't
58:00
It doesn't need to be in your backyard.
58:01
And so I believe >> to Tyler >> uh to who's in the chat.
58:06
But I mean I I do think though that that tax argument the problem is that largely again I'm speaking from a voter level is they do not feel either that impact or that they often like with the Amazon you know example that I gave you is that we give these tax credits away and then the promises a lot of these things don't end up happening. Come on, guys.
58:27
This is a tale as old as time.
58:28
Every state in the country, remember when Amazon did that ridiculous pony show for every state to throw whatever it could to them and then they ended up Yeah. for HQ2.
58:36
That's the project I'm talking about is that Virginia, where I live, also did that.
58:42
And then, of course, you know, local politicians feel very burned and a lot of the voters do as well.
58:45
But ultimately, Jordy, I don't think we're disagreeing, man.
58:48
Like, local control is really what it's all about.
58:51
>> That's what I'm saying.
58:51
And and I also think the feds though I do think that you know considering the way that Trump and the AI industry are so like they really do need each other just because of the way especially now after Iran.
59:01
My god uh can you imagine you know like look at how much he's he's reacted to market swings.
59:08
One of the fears that I had really was that a lot of this you know you're talking about sovereign wealth funds John you and I know the amount of Gulf money slloshing around Silicon Valley.
59:16
I'm like guys like we're about to see force majour just get declared.
59:21
I mean, if you see even 10% go down from QIA, SIA or any of these other investment funds, you're like, that's like an extinction level event for a lot of these or they might reallocate.
59:31
They might start funding all these defense tech companies and not investing in data centers.
59:37
And don't forget that an Amazon data center was struck by Iran in the UAE.
59:41
I believe a couple of different tech infrastructure places were explicitly declared war on by the Iranians.
59:48
So I I do think that there's an element here where what we're what we are watching uh play out I think politically and even geopolitically is that foreign you know adversaries can see clearly that this is a potential pain spot for the US economy here in the US.
1:00:03
the administration is really aware of this, but there's also just this rising kind of populist tide against the data center movement and and against I think really like abundance style asurances uh from politicians and from companies that after 40 years now I mean before data centers it was Walmart and before that it was something else.
1:00:25
there's always going to be like a small guy versus a big guy feeling especially in rural parts of the country and you know I'm from Texas Jordy with the oil industry so I I get exactly what you're talking about right like there's a symbiosis of we actually get rich off
1:00:38
this stuff so we're okay with drilling for oil but you know there has been enough stories also even there where people go bust as a result and there's a lot of animosity towards the oil industry especially pre-shale revolution after things petered out And uh you know
1:00:56
I don't know I' I've just seen this go politically in a lot of interesting directions enough to see that a something is happening b is that the tide is not only just turned but I think coming very explicitly and if what I would really advocate for is a genuine
1:01:11
democratic process cuz that's what it's all about like people just feel like this is out of their control about AI especially they're like I want impact I want a say and I don't think they're wrong to say that >> the flow for for getting some sort of resolution on the federal level. Is that
1:01:23
Is that like a new bill or something or like obviously this is going to happen after the midterms, but then uh yeah, and it's going to try and tie a bunch of these different questions in a bow around safety and cyber security and data center buildouts.
1:01:38
Like is there is there a world where the like a good data center exists in the sense that it supplies its own power with clean energy? It's not an eyesore.
1:01:47
it's either buried or covered in trees or beautifully designed and it doesn't have any environmental impacts.
1:01:54
Like I is there is there a world where someone could get behind a data center at that level? >> Yeah, absolutely.
1:02:01
You know, and that's kind of the thing.
1:02:02
Why are we just talking about data centers?
1:02:03
I I talked about this before.
1:02:05
I read once a report of a guy who just came from China and he said nobody in China cares about power with data centers because they have a ton of power.
1:02:11
He's like we have energy, dude.
1:02:13
He's like, "Bro, we don't care."
1:02:15
He's like, "Yeah, you can build you can build a data center. We're good.
1:02:16
like we have cheap and abundant power.
1:02:18
So if we have cheap abundant power all over the nation, no one will care either just about data centers, especially if we have, you know, cheap electricity, if there's just if there's no concern on the power generation level, and this is why, you know, I'm a huge advocate of nuclear power plants, whatever, renewables, I I don't even care at this point.
1:02:37
Shale gas, let's put it all in together.
1:02:39
But I actually think our grid and the delay of our grid and and really just the knowledge right now, we're not investing a lot more into it.
1:02:45
doesn't seem like things are propelling.
1:02:47
That's what makes it a zero- sum game.
1:02:49
It doesn't need to be this way.
1:02:50
Like really, what we need is just a ton of power.
1:02:53
If we have a ton of power, then we don't care about anything being built. >> Yeah.
1:02:56
So, is is codifying the uh the rateayer protection pledge into law good move?
1:03:04
>> It would be a good move, but I don't think it's enough at this point.
1:03:05
There's so much distrust, guys, like at the local level and on the political level.
1:03:11
Uh I I recommend you follow Ryan Gduski.
1:03:14
He's done some more recent work on the data center question.
1:03:17
He's been talking about this.
1:03:18
He's like, "Guys, this is just laying out there for any politician to pick up."
1:03:21
And I'm talking about it from an anti- data center uh position.
1:03:25
He's he's much more of an expert on polling than I am.
1:03:26
Go and check out his feed and some of the work that he's done, especially not just on feelings against AI, but data centers cuz he I think he crunched the numbers.
1:03:34
I know it was within the last couple of weeks that he looked at the question and he was he just said there's an overwhelming animus and that people are angry.
1:03:41
So it's not just again let's be very clear it's about a feeling of lack of control over you know you're coming to take my job you're increasing my electricity you're changing my nation and I have to have a say as a citizen.
1:03:54
So that's not just no longer about electricity that's about the whole picture of like technology and oligarchy and the economy.
1:04:01
So you're fighting against a very very big force right now in the country. >> Yeah.
1:04:07
No it makes a ton of sense.
1:04:07
Thank you for coming on and breaking it down.
1:04:10
Uh, I'm sure we will be talking about this.
1:04:12
>> Have you have you tried have you tried just out of curiosity to just not use any AI?
1:04:16
I mean, it's impossible to not use AI now because every company for the most part is is using it.
1:04:21
But have you tried to do your own personal like pause just for like a few weeks? >> You should try.
1:04:27
I want the like you should let's get you back on the schedule for a few weeks from now >> and in the meantime promise you will not use any any AI at all until your next >> guys.
1:04:40
It would be so hard because even the chess board behind me has builtin AI. It's everywhere.
1:04:44
Yeah, it's got the builtin it's got the chest. >> No, it's fine.
1:04:48
You can just No, just don't play chess, bro. It's fine. I can't do it.
1:04:52
Just get just get a Just get an old school board.
1:04:55
>> I've been on one by the game.
1:04:55
Uh this is I've been completely oneshotted by the game.
1:04:59
Anyway, yeah, >> thank you so much for coming on. We'll talk to you soon. Sorry. Great to see you, guys. Appreciate it. Always helpful. We'll talk to you soon.
1:05:06
>> Uh up next, we have Joe Weisenthal from Bloomberg and Odd Lots.
1:05:08
Uh here to break down the New York Times analysis of the strongest Satoshi Nakamoto candidate. Joe, how are you doing? >> Look at that. >> I'm good.
1:05:19
Uh >> look at that sweater. >> Yeah. What do you think? >> You look fantastic. I love the green.
1:05:25
You think the green works green here?
1:05:26
The green is great and the color coming out the top.
1:05:30
>> That's actually what I meant.
1:05:30
I when I said what do you think?
1:05:31
I was like oh actually I'm wearing TVPN green for you guys. >> Yes.
1:05:36
Glad you guys noticed the gesture. >> Well, welcome back. Nice to see you guys. Congratulations.
1:05:42
>> Is the New York Times the most underrated company in the world? >> Yeah, of course.
1:05:46
It's the It's the most Yeah, of course.
1:05:48
It's the most underrated tech company and the most underrated news company.
1:05:50
the number of haters that the new and undererated.
1:05:56
>> The thing though is to be fair that's the hater comment like that's just a gaming company.
1:06:00
>> But look like it's extraordinary juggernaut both tech and news and so many people have some sort of criticism of it or whatever and find a reason to hate it and everyone can find good reasons to complain about the media.
1:06:14
>> But it keeps on winning in ways that I've certainly been uh very surprised about.
1:06:17
So um I was really excited.
1:06:17
I know the topic at hand.
1:06:20
I This is one of my f Satoshiology is like one of my favorite topics.
1:06:24
I was super excited to see that they took a stab at finding out who it is.
1:06:28
>> Did you have a candidate in mind before this piece dropped?
1:06:31
Had you watched the HBO documentary that actually pointed to a different suspect?
1:06:38
>> Yeah, I've read a lot.
1:06:38
I actually didn't watch the HBO documentary in in part, I guess, because it was just so heavily criticized, etc.
1:06:45
that I like maybe I don't need to watch it.
1:06:47
I had often often found the um the Nick Zabbo, he's one of the candidates.
1:06:52
I had always found that one to be fairly compelling. Yeah, me too.
1:06:58
>> And you know, in my first read of the New York Times piece yesterday, I thought it was I about Adam back like I knew he had been in the mix.
1:07:04
Y >> it struck me that most you know the piece didn't have a smoking gun, right?
1:07:10
And that's sort of what we're all waiting for.
1:07:11
We want that smoking gun whether it's some sort of digital signature or an email. It didn't have that.
1:07:17
It was sort of lingu a lot of it was sort of linguistics like oh it he makes it's and it's wrong or hyphens wrong.
1:07:24
I make those same mistakes too.
1:07:24
I don't know everyone everyone makes those mistakes.
1:07:28
So I wasn't totally convinced but then I read it a couple of more times over the last you know 24 hours.
1:07:32
I read it again right before I came on this cuz I wanted to be prepared to chat with you guys and I'm like I've been like upgrading my odds that um that it is Adam John Keru has correctly has correctly identified him. >> Yeah.
1:07:48
What what have you worked with any journalists like uh John Keroo before?
1:07:52
It feels like such a lost art and it's so delightful when someone has a chance to I it seems like this was reported for a year or more.
1:07:59
Like he really he had the space and the breathing room.
1:08:01
No, I I love it and I like I said whether this was right or wrong is one of my favorite topics and it is one of these things where like over the years you know a handful of journalists have like I can be the one to crack this which actually like brings to my mind one of the more fascinating aspects of Bitcoin period. >> Yeah.
1:08:23
>> Which is it's amazing to think that like okay here is this thing it's kind of like a digital gold and so forth.
1:08:28
like a digital gold and so forth. That's a new kind of money and whoever Satoshi is he or her group of people whatever maybe it is Adam back maybe it's not but the opse I mean can you even fathom being online for several years in a way that could not be traced back to you
1:08:45
definitively like I wouldn't even know where to begin I wouldn't even know where to begin how to like interact online in a way that like I could ensure my anonymity and I think one of the fascinating things about Bitcoin is that it does have like this >> founder creat creator myth. This sort of
1:08:59
This sort of um this sort of uh the divine the divine birth by this entity that left no earth almost no earthly trace is as much as a fascinating part of the story almost as Bitcoin itself as a technical accomplishment. >> Yeah.
1:09:15
And also just the fact that then Satoshi even like it wasn't an effort to remain anonymous in perpetuity.
1:09:21
It was like then Satoshi went dark and and nothing's moved on the wallet and it's just been this like uh you know that's obviously fueled the theory that uh that potentially Satoshi passed away or something. >> Yeah.
1:09:36
So the question so here's a question that I have.
1:09:38
So one of the stronger arguments or one of the pieces of evidence that the article in the New York Times points out is that Adam Bag it's well known he has a long history with the cipher punks.
1:09:49
had been interested in privacy and digital money for a long time going back to at least like the mid90s etc.
1:09:57
>> He had invented hash which was uh you know which basically laid the foundation for proof of work which of course is elemental to mining.
1:10:04
So he was like right there.
1:10:07
Now one of the arguments that the piece makes is um Adam back like disappeared didn't have much of a digital trace of those first couple of years when Bitcoin was taking off.
1:10:16
So maybe that was when he had slipped into Satoshi mode.
1:10:19
On the other hand, >> there was no way that anyone in 2008 or 2009 or 2007 could have known really what a gigantic phenomenon Bitcoin was going to be.
1:10:32
>> Why, you know, like Adam Beck clearly was very comfortable talking about many of his projects under his own name. He talked about hash.
1:10:40
All of these people had been talking about their work in applied cryptography for years under their own name. >> Yeah.
1:10:48
>> So have not having been able to know how big of a deal Bitcoin was going to be.
1:10:53
Why would this particular project suddenly oh he would like have the foresight to like oh I have to be pseudonmous for this particular project.
1:11:03
I don't totally understand why someone who had like talked about digital money, digital money for years under his real name would have had reason to think, okay, with this project I'm going to have to talk pseudonmously or anonymously.
1:11:15
That is not entirely obvious to me. >> Yeah. Yeah.
1:11:20
>> Yeah. Yeah. Uh >> like again in retrospect like sure like in 2026 we could look back yes it makes a lot of sense that this person would have like the pseudonym aspect but when it's just a bunch of people >> part of the community trying to solve the problem of petope payments who have
1:11:36
been using their names why suddenly like when this these pieces come together this way would the creator feel impelled to be private in a way that they didn't feel impelled to be private with all the other Bcash hash digital gold etc That's not totally obvious to me. >> Well, the way that I mean obviously the
1:11:52
>> Well, the way that I mean obviously the way you're talking about it is I'm becoming more suspect that it was in fact you >> behind. >> No.
1:12:00
>> Well, so here so this is a Yeah.
1:12:00
Wait, John, it sounds like you you don't find this component. >> No, I Yeah.
1:12:05
I I I just uh I I feel like after watching a number of projects sort of sputter where they did have a specific founder that could be uh just not even attacked but just like the the motivations of that individual could be questioned and and there's so much like risk tied to like a single person.
1:12:27
It doesn't strike me as that cra I mean clearly someone went anonymous, right? >> Yeah.
1:12:33
One one exercise is like is there a person that if if if it came out and we could determine that it was act entirely factual that this one person >> who who's the kind of person that that would make the Bitcoin sort of trade up in value, right?
1:12:48
Because there's like I can't really think of anyone.
1:12:51
I can think a lot of different groups that it would trade down dramatically.
1:12:53
It comes out oh some government entity, you know, uh you know that that that goes down uh dramatically.
1:13:01
dramatically. Um, and so there's not there's not a lot of like ROI for anyone on a personal level if they're if they're >> one of the funny things so one of the funny things about Adam specifically if you go to like his Twitter profile it
1:13:16
says you know it lists his accomplishments and it says he is the inventor of hash hash in parenthesis Bitcoin mining and it what's funny is many people over the years have actually accused Adam of overstating ing what his claim there. It's like yes, there is
1:13:32
It's like yes, there is clearly a lot of overlap between hash and the notion of proof of work that was elemental to how Bitcoin mining worked, but hash itself is not Bitcoin mining.
1:13:44
It is a sort of a thing that preceded it was one of the antecedants or the preced whatever to Bitcoin mining a similar technique the whole proof of work concept.
1:13:52
So there's been this claim that actually one of his issues is that he overstated his invention or role in the creation of Bitcoin which is very funny like if if it turns out it's him that for a long time the accusation was that he over overplayed his role.
1:14:05
he over overplayed his role. And then the other thing that's strange is that like since you know he's had like so and this ca this is mentioned in the New York Times piece he was one of the guys who last year or whatever launched it one of these Bitcoin treasury companies right like a micro strategy like entity
1:14:25
that was just going to hold a lot of Bitcoin and does that sound like something Satoshi and Nakamoto would do in my opinion not really but then the flip side is well that's like the best OBSE in the world do a bunch stuff that feels a little bit scammy, feels a little bit cheesy, feels a little bit like um opportunity. >> This guy is definitely broke. There's no
1:14:42
>> This guy is definitely broke. There's no way. There's no way.
1:14:44
There's no way he's got, you know, the the tens of billions of dollars.
1:14:50
>> Yeah, >> that's what I'm saying.
1:14:50
So, it's like on the first pass, I was like, "No, like Satoshi is not going to like launch a little like mini me micro strategy company.
1:14:58
This does not seem very likely."
1:15:00
But then the flip side is, man, if you were someone who like maybe some suspect of being Satoshi, what would be the thing that would be the least Satoshi like thing to do and throw people like maybe it would be like create a Bitcoin treasury company?
1:15:13
>> Or if you were Satoshi, but you lost the keys in some sort of silly mishap, then you would want to get back in the game because you're still a believer, but you don't have access.
1:15:23
>> Anyway, last question. Yeah. Yeah, sure. >> Yeah.
1:15:25
Last question on the on the Bitcoin thing.
1:15:26
Did you ever go down the Paul Laroo route?
1:15:28
And did you ever were you ever a Paul Laroo believer? I was really convinced. >> Paul Laroo guy. Which one was that?
1:15:36
>> So he he uh was a former criminal cartel boss informant to the US uh drug enforcement agency.
1:15:43
He created TrueCrypt and was really early in uh basically spamming like the classic email spam of like uh you know mail enhancement.
1:15:54
He would spam that out, scam everyone.
1:15:57
He became so deeply entrenched that at one point he didn't just own a uh like domain name and he would switch the URL.
1:16:08
He owned a tldd or like a registar so that no one could kick him off and he could create unlimited new websites. >> That's pretty funny.
1:16:16
>> So he would just create a new website every day and so the Gmail filters would get confused because well we've never seen this one before. >> I love that.
1:16:22
Uh, >> you know, the thing is I've always thought like that I I don't know if any of you have ever read it, but there's an amazing book uh by an NYU professor Finn Bruntton called I think it's called Digital Money. Okay.
1:16:32
And it's about the prehistory of Bitcoin.
1:16:35
So, it's about this community of the cipher punks in the '9s and ' 80s and actually even going back to the 1970s. Yeah.
1:16:41
where people were talking about this fact that as the world was going to go online, it would be very difficult for me to send you a payment without the need for like a third-party database.
1:16:51
The idea of like we need something that's cashlike, a bearer instrument on the internet. Yeah.
1:16:59
And I think this is like a really important thing to know is that there have been there was a small group of people that basically for three decades or more before Bitcoin had been trying to solve this problem.
1:17:09
And so like in the the New York Times piece the it points out that back had been talking about all of these things that Satoshi had been talking about.
1:17:17
And my first response is yes.
1:17:21
>> Of course they did because this was this core group of people who for years understood that in the online context if if payments were ever going to be a thing we would need a third party.
1:17:30
And if there was a third party they can block a transaction they can reverse a transaction.
1:17:35
They can penalize you for making a bad transaction etc.
1:17:37
And so this was understood by some people from day one of the, you know, pre- internet that this would become an issue.
1:17:44
And so I'm not surprised that they were all using roughly the same analogies and so forth. >> Yeah.
1:17:50
The book is digital cash, the unknown history of anarchist, utopian, technologists who created cryptocurrency.
1:17:57
And I will recommend a book to you about Paul Laru, about Paul Laroo.
1:18:03
I think it's called The Mastermind.
1:18:04
Uh, and I believe it was optioned into a movie. I'm not sure.
1:18:07
I think uh Michael Man was going to do it and that would that sounded really good.
1:18:12
But uh the book is fantastic.
1:18:12
Anyway, is that was really fun.
1:18:16
>> Has this been like a like a nice reprieve for you from covering the war?
1:18:21
How have you been processing the the constant girrations in the oil market and the broader financial market?
1:18:25
Uh it it feels like such a hard uh thing to cover, but obviously you've been doing a great job with OddLots and beyond. >> Thank you.
1:18:34
The stakes are I mean it is a hard thing to cover.
1:18:36
It's an awful thing to cover, right?
1:18:38
It's a war and wars are awful and the stakes are so, you know, there are so many ways that wars can get more, as catastrophic as they are, get even more and more catastrophic.
1:18:47
So, it's like, you know, it's but it but it's also like an extraordinary story for the things that we like to cover, which is like understanding the real flows of the economy.
1:18:57
And you know, prior to this war, I had not fully appreciated essentially just like how I mean, I knew about for oil, I was aware that the straight of Hormuz was a very big deal. Yeah.
1:19:10
>> But like the degree to the fallout, whether we're talking about like fertilizer, whether we're talking about um not >> real estate in real estate in Dubai, you guys had a great >> real estate in Dubai, of course, which real estate in Dubai, which you know, we probably you guys probably know more people than myself.
1:19:25
elevated to camping out to Dubai for the low taxes and stability and then suddenly you know you're like oh this could be >> honestly credit credit to Americans like Dubai has just not been that popular.
1:19:39
>> I think it's different it's very much yeah European thing when when I was out there I mean it very much is like a melting pot.
1:19:45
I've been there a couple times and >> very limited number of Americans and the American the Americans that are there for the most part aside from on like you know scheduled you know >> fundraising trips are not really in the same type of like business community that that you and I are in.
1:20:06
>> Yeah, it does seem like a more of like a British thing specifically in terms like oh going there for the low taxes or the stability etc.
1:20:13
stability etc. But yeah, like all of these things getting upended or the specific not just oil and gas that yes that goes out of the straight of Hormuz obviously, but then like this specific acuity then pain points that are being
1:20:26
felt in Asia specifically and how they're already having to go into sort of like a 1970s rationing mode where you see these headlines about if you have, you know, if your license plate ends with an odd number then you can drive on this date. I mean the economic
1:20:39
I mean the economic reverberation, it was clearly the biggest sort of global econ story since co >> Yeah.
1:20:46
I was reading this article in the in the economist this weekend uh in Buttonwood about how it feels like the market is not actually able to process what a 20% decrease in in uh in oil rates is.
1:21:00
And it feels like I don't know if that's just like hope that there will be a taco that there will be a quick resolution but uh the the the key stat that they were latching on to was that even if the everything was world peace tomorrow just bringing resources and infrastructure back online just starting the flow and moving the ships again takes you know three months, six months.
1:21:24
And so you will see reverberations through the economy for for months if not years even if you know we get a good outcome immediately which is what we're all hoping for. >> Yeah.
1:21:33
Some sort of benign outcome.
1:21:33
But like but this is the weird thing to and you're spot on and this is the weird thing which is that if you talk to the commodity guys they're like this is unbelievable.
1:21:42
This is like a scenario that we couldn't even really have contemplated.
1:21:46
And then you look at the stock market and you know oil is up a lot.
1:21:49
It's not like oil markets are not registering.
1:21:52
It's up a lot, but um but then you look at the stock market and it's flat on the year like as of the time I w or it's like down. 3%.
1:22:00
>> I mean it's stunning because you have to remember that even like the last thing we were all talking about prior to the war was like oh every legacy business model in the world is going to zero because AI is getting so good.
1:22:10
So that was the first two months of the year.
1:22:15
And then the third month of the year is this war that massively shoots up the price of oil.
1:22:20
Kind of like takes the prospect of rate cuts um off the table.
1:22:25
And we're looking at a market that's flat on the year.
1:22:27
Like it's really like you know I try to I'm sort of an EMH guy and so I always think if I'm missing something I just trust the market.
1:22:34
It's very strange, you know. It's very strange. >> It is very strange.
1:22:38
Uh have you have you found any particular corners of the economy that are serving as white pills these days?
1:22:44
Because it feels like a year ago things were sort of it was there was there was political chaos.
1:22:49
We were talking about the tariffs and whatnot, but uh it felt like in broadly most industries were uh sort of seeing reasonable advances.
1:22:57
Things were much less controversial and we're in a much more tumultuous time.
1:23:03
>> I mean I it's hard to it's hard to disagree with that.
1:23:05
disagree with that. I mean I think that there's basically I think most people say there's basically two parts of the economy that are growing and one is anything related to AI and data centers etc obviously and the other is like home healthcare jobs and I don't think much has like changed on that front and
1:23:22
unfortunately like okay like again let's just go back to the world of February 26th before the um strikes had begun >> you know we the issue was we were already still at that point well above target for the Fed's inflation now reason to think maybe it's trending down, maybe there's some softening, etc. >> But even with just essentially two
1:23:40
>> But even with just essentially two cylinders out of >> I don't know if the cylinders analogy is great because I don't know how many cylinders but two cylinders really firing like okay ongoing need to like provide people healthcare and then AI even with that the economy was like under a certain level of like strain with price stress. Yeah.
1:23:58
And so then you add in okay now like all forms of commodities are going to be more expensive.
1:24:05
They're spending of course wars are very costly from an expenditure perspective.
1:24:10
And so where does that leave the rest of the economy that's not AI or healthcare?
1:24:14
AI or healthcare? I have yet to see I don't know I'm certainly not feeling white pill to the extent maybe the the closest is like look I would say there there I there there's still evidence a little bit out there that for example that we're not seeing the evisceration
1:24:32
of tech and software jobs the way some people might have anticipated and there continues to be like evidence like oh actually like that sort of like the the economist optimism that maybe AI will create demand for software engineers because there were more things that could be softwareized. I actually think
1:24:46
I actually think maybe that's looking okay that thesis and so it's white pilling in the sense maybe we don't have like the total evisceration of the sort of the labor market like that part.
1:24:59
>> Um we actually got a good jobs report last week on um the good Friday report.
1:25:03
So like I there are things >> and and we trust all the jobs reports now.
1:25:07
We we could definitely lean on >> the revisions have been a little tumultuous for me.
1:25:12
>> There have been a lot of revisions.
1:25:12
It's very tough to measure the economy, but I um I I salute our brave stat statistitians at the Bureau of Labor Services.
1:25:20
>> And we did and we did talk to some other folks who were looking at like private market data, payroll data, and and and there were green shoots there as well.
1:25:28
So I I I'd be I'm optimistic that that holds.
1:25:30
Um yeah, I've heard I've heard the most optimistic take about uh >> just uh more companies building more new things.
1:25:37
We've built a bunch of internal tools here.
1:25:39
uh the actual um like NPS score for most AI apps is actually very high even though AI as a concept pulls very poorly.
1:25:49
So there's this there's this difference there.
1:25:52
>> What does NPS stand for?
1:25:53
>> Net promoter score or like approvals approval rating.
1:25:55
approval rating. So like people may give chat GBT directly like an 80% approval rating and it has like a lot of it has a lot of good reviews in the app store for example and if you just ask them about that or or what they're building with cloud code they'll say oh they'll tell you an amazing story of some custom software that they built for their
1:26:12
business that they would have had to spend a million dollars on a consulting group to do it and it maybe would have been really tricky to get it to math out but then they'll just tell you like oh yeah we needed this dashboard and we just made it in a day or or a couple weeks So people love their specific things they built and but then it's like terrible and they hate Yeah. No, I mean
1:26:30
No, I mean look I mean I think this is actually seems to be a recurring phenomen over the last several years to some extent said this about the economy generally like I'm doing okay.
1:26:40
I my financial situation is actually fine but the economy is like really terrible.
1:26:45
So it would be kind of interesting like if maybe there was a pattern that we're seeing across domains where you know everything else I was yeah I like AI I like how it's doing I like this thing I built etc. It's all terrible.
1:26:57
Maybe that's just sort of like a general disposition that people have towards a lot of things.
1:27:03
Yeah, it's the Kylo Scandlin vibe session concept.
1:27:04
And >> people maybe they're happy in their >> maybe they're happy or they're happy in their relationships, but they were like, "Oh, but dating ever for everyone else is a total wasteland.
1:27:15
Everyone these days maybe that's actually kind of a thing." >> Last question.
1:27:20
Any prediction market predictions on your side? >> What do you think?
1:27:24
We had an episode um I'll take we have an episode out today with Tomas Pedy the founder of IBKR which is also one of the most impressive impressive trading entrepreneur.
1:27:33
They're take getting prediction mark they're really getting into prediction markets.
1:27:38
So I think u my prediction is that um it's not just going to be like a two entity race for that much longer.
1:27:43
I think like um I think as it gets bigger there's probably too much money to be left on the table for it to just be these two companies that most people never heard of up until like a year ago. >> Yeah.
1:27:56
No, makes a ton of sense.
1:27:56
Uh well, thank you so much for taking the time to come with us both. >> Take care. >> Thank you. We'll talk to you soon. >> Cheers.
1:28:04
>> Our next guest is Andrew Dye from Allian.
1:28:06
He's the co-founder and CEO with Big Rays coming in to the CBP and Ultra.
1:28:13
Let's bring in Andrew from the waiting room.
1:28:16
Andrew, how are you doing? >> Hi. Good. Thanks.
1:28:20
>> Thanks so much for taking time to join us.
1:28:21
I would love to hear a little bit about your background.
1:28:23
Uh maybe we should start uh even before Google Brain and Deep Mind.
1:28:29
Uh what was your academic track like going into uh TAC?
1:28:36
>> Um yeah, so I grew up in the UK.
1:28:36
Um I lived in Manchester and Sunderland and London all across following my uh dad's work.
1:28:45
Um and uh ended up in London, did my high school there.
1:28:48
I went to the University of Cambridge uh for computer science and then I went to the University of Edinburgh for my uh PhD in AI.
1:28:57
>> And what did you work on when you were at Google?
1:29:00
>> Um at Google I worked on a whole bunch of things. I worked on Google Now.
1:29:02
I worked on smart reply and smart compose.
1:29:07
Uh but really I had a paper about um 12 years ago where we proposed language model pre-training and supervised fine tuning >> and that's the paper that all the GPT papers site and >> wow >> uh here we are today >> turned out to be a big deal. >> Yeah. >> Yeah.
1:29:22
uh did uh did the >> Wait, yeah, sorry. >> I don't know.
1:29:25
I don't know if you're going to dig in deeper there, but but at the time when you were writing that, how how much conviction did you have around the paradigm?
1:29:33
Did you expect >> and scaling laws in particular?
1:29:39
>> Yeah, I knew it was going to be something big.
1:29:40
Um, and I could tell because when I was giving my poster at Europe's that year, um, one of the inventors of like LSTMs, which was the biggest >> model at that time, they said it just works.
1:29:53
Like the method just works.
1:29:55
>> Uh, and there I could tell, oh >> yeah, there's something something happening here.
1:29:58
But I never imagined it would get to this scale and I never imagined I've been doing it for more than a decade. >> Yeah.
1:30:04
So, uh, >> did you go to Nurup's uh, this last year? >> Uh, yeah. Yeah, I did. How has it changed? How has it changed? >> It's all now.
1:30:15
>> A lot of language >> and VC.
1:30:16
A lot of VCs sneaking around too. >> Lot of VCs. That's right.
1:30:22
>> Well, then uh yeah, take us through uh the this company that decide to launch the decision to launch this company.
1:30:27
Uh what you're thinking uh needs to be different about the current strategies employed by AI labs. >> Yeah.
1:30:36
So, our company is built around visual reasoning.
1:30:38
uh as a first class citizen, multimodal reasoning.
1:30:42
>> Uh so looking at all the labs uh you see there's a lot of focus on text on language >> um that's been very effective right we have new paradigms in cyber security right now uh but um the visual capabilities are kind of getting left behind and there you have problems where the models are on visual problems are at the level of like a preschooler uh of like a three-year-old.
1:31:05
>> Can you give me an example of that? Yeah.
1:31:06
What does that look like in practice? Yeah.
1:31:08
So in practice, uh you can tell these models to generate a pool table and they will make a perfectly good-looking pool table, right?
1:31:15
But if you ask them to count the number of bowls on the table or count the number of bottles in a bar, then they will just hallucinate.
1:31:22
They'll be off sometimes by a large amount. >> Yeah.
1:31:27
So I I've seen sometimes uh the reasoning models will ingest an image and then wind up writing a bunch of like Python code to basically like count pixels and do things like very much not the way I would imagine the way a normal human would process counting something.
1:31:45
I at one point I was asking uh to estimate the height of a desk and uh it was you know writing all this math to to to uh to sort of manually you know try and understand the size of things which which we re meant re it was a reasonable approach.
1:32:00
It wound up just being a normal sized table which was sort of underwhelming.
1:32:02
Um but uh how are you thinking about the the actual uh development and what you want to do differently?
1:32:09
Are you are you focused uh more on a new architecture, new data sources, uh more scale?
1:32:18
What's the shape of your of your uh strategy here? >> Yeah.
1:32:22
So, we are basically a full stack team.
1:32:24
We have experience with pre-training, data, multimodality.
1:32:25
So, we are essentially building specialized models that includes new architectures for visual reasoning.
1:32:33
um a very specialized uh sets of data with specialized data processing and new algorithms.
1:32:41
So we expect to be running the full gamut of uh changes and this is really needed to really make a breakthrough in visual reasoning.
1:32:49
>> What does good training data look like today? Is it is it synthetic?
1:32:51
Is it uh images, videos, 3D, you know, virtual worlds?
1:32:57
Like what what's the shape of what's valuable?
1:33:02
>> Um as you can expect is a bit of everything.
1:33:03
everything. all but yeah definitely definitely natural data so data that's not generated from a model is more valuable and more useful um data from a model that's synthetic data has the risk of putting the model into like a weird place where it just outputs like m
1:33:20
dashes or just like tries to repeat the same thing all the time but yeah data around the natural world around the 3D world that's invaluable >> what do you think the cyber security analogy is for uh visual reasoning Like cyber security is so equipped for textbased models, coding agents. Um the
1:33:36
Um the entire cyber security threat can sort of be understood as a big string of text more or less.
1:33:45
Um where do you think visual reasoning goes in terms of uh applications? >> Um yeah.
1:33:52
So for applications, one of the most promising ones that um we're seeing is engineering.
1:33:57
So right now all these um engineers, mechanical engineers, hardware engineers and also architects, they're drawing all these uh diagrams in CAD software which has been developed around you know the last few decades but there hasn't really been AI breakthroughs there.
1:34:13
People are still doing basically the same thing they've been doing for the past few decades.
1:34:16
Um and so what we will do is we will produce models that really understand these drawings.
1:34:23
these drawings. um like uh say you have a real estate floor plan and you want to say make this bedroom bigger or add a extension to my house right now that would take weeks and lots of manual time and then you have to follow building codes uh make sure like everything is correct um and that's because there's
1:34:42
there's not really any reasoning uh in our visual reasoning our current models and so we think there's a huge potential >> one of the hardest one of the hardest times we've ever laughed on this show was was reacting to a a floor plan that was generated by AI and it looked so high fidelity. Every line was perfect. Every line was perfect.
1:34:59
It didn't have any of the fuzziness that you've expected from earlier models, but when you dug in, it made no sense.
1:35:03
There were like 12 toilets and two baths and it had one big it didn't really understand the problem. So, very exciting.
1:35:12
Uh, well, you raised some money. Tell us about it. How much did you raise?
1:35:15
We want to hit the gong for you.
1:35:17
>> Yes, we raised $55 million.
1:35:17
Oh, >> congratulations >> from who?
1:35:25
>> And that's from Spiker Ventures, Menlo Ventures, Automator, and Nvidia and 49 participating.
1:35:30
And we have some great angels there, including Jeff Dean. >> Jeff Dean. Awesome.
1:35:34
>> He's been on a he's been on angel investing ter.
1:35:36
It's really exciting to see.
1:35:38
I mean, obviously, he's a legend, but uh he's clearly very optimistic about all these different approaches uh going forward. So, very excited.
1:35:43
Uh well, thank you so much for taking the time to come.
1:35:46
Great to meet you, Andrew. We'll talk to you soon.
1:35:47
Have a good rest of your day. >> Cheers.
1:35:50
>> Uh up next we have Lumini and Cassava Dina Kuran in the waiting room.
1:35:54
We'll bring him in to the TVPM Ultra Dome.
1:36:00
They have raised a $38 million series B to scale AI automation for health systems. How are you doing? Good to see you. >> What's going on? >> Doing doing great. Great to see you both. >> Great to see you.
1:36:08
Um I believe it's your first time on the show even though we've met in the past.
1:36:12
Uh please introduce yourself and the company. >> Yeah.
1:36:16
Uh I'm Quav, one of the co-founders and the CEO of uh of Lumini.
1:36:20
Uh help uh large health systems uh drive automation in their operations and back office.
1:36:26
>> What is uh so is this a diffusion story or is this a uh like a foundational AI research problem like what what what is the secret to actually driving improved healthcare outcomes in large in these larger organizations?
1:36:39
Yeah, I think you know the the models have kind of got to a place uh probably in the last maybe 6 to 12 months where um where some of the opportunities to actually drive automation end to end in a very reliable manner is is very possible.
1:36:53
So it's 100% a diffusion uh story at the moment because the reality is like uh you know American healthcare still runs on faxes uh in many ways and so you're kind of at this opportunity now to to dramatically change how uh how it's done in the first place.
1:37:11
>> So G uh would love an example of like a specific back office task.
1:37:13
Is this like passing information to insurance providers processing claims like what what are some specifics?
1:37:21
Yeah, I'll give you a very uh concrete example.
1:37:23
Um, so imagine like you know um one of the customers we work with is the Cleveland Clinic.
1:37:30
Um, and uh they're obviously one of the most advanced sort of academic uh research organizations as well as hospitals in the in the world.
1:37:36
Um, and so uh there are patients who come from all over the world to Cleveland Clinic and the way they actually get uh care is initially through uh something called a a referral.
1:37:49
a referral. um right and and that referral basically uh gets sent from um you know small clinician practices to massive hospitals that are based in you know even all the way from the Middle East and uh they're all uh unfortunately
1:38:04
um or key central lumini sent via a fax machine um and these are sort of documents with handwritten notes where people are sent saying hey this is Kesh he has some u unique sort of um left knee pain uh that require requires you know a specialized attention. Um here
1:38:20
Um here are the details and there's a huge sort of operations team on uh uh the Cleveland Clinic side where their job basically is to look at every single document read every single sort of um handwritten note.
1:38:33
Uh and by the way these facts >> so so sorry to interrupt but you guys so so just so I have it correct you guys are making humanoid robots that can write handwritten notes to fax back through a physical fax machine to the original sender.
1:38:47
You know, I think five years ago that would have been an easier solution to solve uh in healthcare uh than than try to get it implemented.
1:38:54
But but uh it's all all enterprise software.
1:38:58
Uh so it's it's just literally a virtual inbox agent that uh you know triages each referral that comes in uh puts in the high-risisk patients first and then processes the referral um in an automated way.
1:39:09
But that that's sort of an example of of many other problems that obviously exist within the the operations of the health system. >> That makes sense.
1:39:15
And so are you guys uh doing the kind of forward deployed model where you basically say, "Hey, we we have a good understanding of current AI capabilities.
1:39:23
If you let our team into your space, we'll figure out individual workflows to automate or what's been the the the approach so far?
1:39:32
>> Yeah, I mean um healthcare is extremely nuanced.
1:39:34
Uh you have to understand the specifics pretty pretty deeply.
1:39:36
Um and so without actually being on the ground living in the offices of your of your customers, it's difficult to sort of scale solutions.
1:39:44
And so you know about 20% of our team comes from Palunteer and so we've taken a very deep uh forward deployed approach uh to every every customer you work with and you know we work with some of the largest institutions in the country and so sort of it lets us afford to actually be able to to do that.
1:39:58
How much about uh deployment diffusion is uh gated by regulatory or approvals versus um it's a less maybe you know obviously there's a lot of technative people in these health care systems but uh they might be a little bit less online a little bit less uh aware of the of the progress and so there's just an education element um versus you know understanding the cost tradeoffs and actually implementing the the the processes.
1:40:26
the the processes. I mean there definitely a a massive amount of like uh barriers to entry and being able to actually drive uh or or actually implement um uh AI systems in these places prim and for good reason right like this is like extremely extremely uh sort of sensitive healthcare data uh that's that's flowing through these systems and so there's the right amount of sort of guardrails put in place uh but once you're in uh there's a dramatic
1:40:55
amount of work uh that's uh that can be done by software And that can be done by you know um AI in the first place and uh it's uh it's sort of a you know there's definitely areas we shouldn't touch like deep deep clinical decision- making and
1:41:08
and threads around that that you know this is why we have doctors um but there's a huge amount over a trillion dollars just like wasted administrative uh operations work that that uh yeah today uh can be done by software systems. >> How are you thinking about onrem these
1:41:21
>> How are you thinking about onrem these days um with the AI context?
1:41:26
to mean these models are so big.
1:41:28
The latest ones seem to run on NVL72s.
1:41:30
That feels like a big lift in capex if you're going to stuff that in a closet somewhere or in the local uh IT cabinet.
1:41:37
Where where do you see uh like are we going to be seeing like local inference happening for uh for regulatory reasons or is it more about uh just interfacing with on-prem systems because they exist and then this will be actually an accelerant to cloud adoption.
1:41:59
um you know we've offered on prem to every single health system we work with really but only only you know 10 to 15% of them have actually taken us up on it and um and so that's an interesting sort of one data point but the primal reason to offer onrem in the first place is cuz
1:42:15
uh because of the amount of data that you're sort of handling and you don't want those u that that data to basically uh leave your leave your premises in the first place and so uh we've chosen to go go onrem with with you know even certain workflows uh with with large health systems. Um but but funnily enough uh we
1:42:30
Um but but funnily enough uh we thought it was going to be a massive um need u when in reality uh it's it's definitely a check box that they do to make sure that you can actually do it versus actually deploy some of this in in in full production. >> Interesting.
1:42:45
I mean um how how dramatically is uh is this the the the the quantity of data produced in health care environments growing right now?
1:42:55
We looked at this one company that was uh just a an audio recorder that would transcribe everything that uh someone would say.
1:43:04
We've seen a bunch of these targeted in in tech audiences, but this one was specifically for doctors to take notes and then have a running transcript of everything that they said as opposed to needing to scribble a bunch of notes.
1:43:19
it feels like we could be at uh some sort of like data production uh inflection point but what are you actually seeing in terms of the quantity of data that's being produced in the healthare system?
1:43:29
>> Yeah, I mean there there sort of obviously a variety of folks who've done uh research on this but I think the um health healthcare has like eight times more data than the next largest enterprise industry on the on the in the country and over over 90% of that data um is unstructured.
1:43:45
So these are all like sort of you know uh contracts and PDFs and handwritten notes and text that's like floating around the the the IT systems that exist.
1:43:54
Um so it's it's obviously a massive uh opportunity and and problem at hand. >> Yeah.
1:43:59
Well uh congratulations on the progress.
1:44:01
Give us the details about the round. >> Yeah.
1:44:04
Uh we raised a $38 million uh series >> um uh fantastic uh led by the Pak 15 team which is a Sequoia India uh group along with General Catalyst um as well as uh YC and uh and a bunch of others.
1:44:22
So uh uh yeah grateful for all the support and and uh interested in continuing to deploy pretty deeply.
1:44:29
>> When did you go through YC?
1:44:29
Uh we actually started in summer 20.
1:44:32
Um so yeah, I've been I've been sort of uh in the game grinding uh for the last uh I love it five and a half plus years.
1:44:43
>> Yeah, but I mean what you you caught the perfect inflection point.
1:44:45
I'm sure you've done a ton of work to set up for the success and take advantage of the progress in AI broadly. So congratulations.
1:44:52
What what a fantastic story. >> Thank you so much. >> Great to meet you.
1:44:56
>> Have a great rest of your day. We'll talk to you soon. Goodbye. >> All right. Yeah.
1:45:00
>> Up next, we have Brian Manning from Zona Space coming in with a new series C announcement building a GPS alternative network.
1:45:09
>> Brian, >> what a setup. >> Beautiful setup.
1:45:12
I assume you're in your factory.
1:45:14
Take us through uh an introduction on yourself, the company, and where you are. >> Thanks, guys.
1:45:19
Yeah, know it's super excited to be here.
1:45:20
It's been an exciting day.
1:45:21
We're uh fresh off this morning uh the announcements and launch of our new satellite factory here in San Francisco uh which coming on the heels of our $178 million series C raise uh that we announced a couple weeks ago. >> Thank you.
1:45:36
So a lot of exciting things happening.
1:45:39
U so what what we're doing what we're building here is we're basically building a new GPS. >> Yeah.
1:45:44
And so we're building a network of these small satellites that are 20 times closer to Earth than existing GPS to provide extremely high accuracy, extremely high reliability navigation capabilities.
1:45:56
You know, I came from SpaceX. Our CTO came from Ford.
1:45:59
Originally, the company was designed around providing autonomous vehicles, the level of certainty and accuracy need they really need to scale.
1:46:06
But we started finding pretty quickly after that that there are 7 billion plus GPS devices around the world.
1:46:12
every single one of them is looking for better performance and that's exactly what we're we're building a network here to provide. >> Okay.
1:46:19
So, uh 258 satellites going into low earth orbit.
1:46:23
You're building them in that factory I assume.
1:46:25
But, uh you're probably have a you know deep supply chain and partnership.
1:46:30
I imagine that they launch on other rockets.
1:46:31
Um uh what what is uh what is key about what you're building?
1:46:38
Where are you partnering?
1:46:39
where are you doing R&D uh before the actual satellites get built and sent to space? >> Yeah, for sure. It's a good question.
1:46:47
So, with satellite navigation, most people always focus on the satellites cuz satellites are cool and that's always the fun thing to focus on.
1:46:53
Um but a satnav system is really three pieces that you have the ground segment which is you know mission operations kind of control segment.
1:47:01
You've got the satellites and then you've got the user equipment.
1:47:05
And then the user equipment is is arguably the most important, but it's also the most overlooked.
1:47:08
So, we are building the satellites, we're building the ground segment, and then we've partnered to integrate our capabilities into all the different user equipment that's out there.
1:47:19
And so, that's the chips that would go into, you know, everything from a a dog collar to a phone to a tractor to a car to military devices and everything in between. Yeah.
1:47:29
We've designed our capability to be just a software update so that you know we can integrate in with these you know billions of devices that are are going out there.
1:47:36
Um and we've been able to demonstrate that on over a dozen different receivers um with the satellite that we launched last year that's up in the air now. >> Got it.
1:47:46
So uh yeah can you give me an example of So a dog collar has a GPS uh chip in it.
1:47:52
It's currently interfacing with uh satellites that are higher in orbit and uh with a software update, you won't actually need to swap out the chip.
1:48:02
You'll be able to get uh more accurate uh GPS data.
1:48:04
What is the benefit of this particular new new constellation? >> For sure.
1:48:10
So there's three big areas that we've seen customers really need better capability and it is we try and make it simple to remember by precision, power and protection.
1:48:17
So there are some customers that are, you know, GPS in the automotive world, for example, can tell you, a human driver kind of reliably what road they're on, where our system is designed to extremely reliably tell them not only what lane they're in, but if they're in the center of that lane or not.
1:48:34
>> Well, we deliver that through a signal that's 100 times stronger than GPS, which means it's strong enough to punch through jamming.
1:48:40
It's punch through trees, even punch through a couple walls.
1:48:43
So, back to the dog collar.
1:48:43
Right now, everybody just accepts that like when you walk inside or when you go indoors or you go into your house, GPS just kind of disappears and location, you know, doesn't really show up anymore.
1:48:56
>> With ours, our signal is strong enough so that you you can see if phto in the kitchen or in the backyard or at least knowing where they are at all.
1:49:03
Uh where you just can't do today with an existing GPS.
1:49:06
I heard this story years ago that I have no idea if it's true that G the the current GPS constellation is higher resolution for military applications than for civilian applications and the technology is not actually the problem.
1:49:24
It's more that there are specific rules about the level of resolution that GPS data is is like turned over to private companies. Is that true at all? >> Sort of.
1:49:34
So there there's bits of that that are are true and some I think there are just some misunderstandings. >> Okay.
1:49:41
>> Uh that are pretty common in the world.
1:49:42
So the military does have a different um GPS service than civilians do.
1:49:46
The big difference between the civilian GPS and the military GPS though isn't the accuracy.
1:49:52
It's actually more on the security aspects.
1:49:55
And so there's more protections that exist on the military service um to prevent, you know, bad actors from being able to fake the signal or being able to use the signal.
1:50:05
And that's one of the big gaps in the civilian market today is that they don't have access to a service that gives the the level of protection that's needed.
1:50:14
And so you can kind of think of it a GPS signal.
1:50:16
Imagine taking your social security number and your date of birth and your mother's maiden name and everything and putting it on a postcard and mailing it through the mail.
1:50:24
That's kind of what GPS is today that everything is just wide open.
1:50:27
Um where what we're providing is a capability that's more similar to the military one where everything is secure, encrypted, protected, but making that available to civilians so that you know you can trust taking your hands off the wheel in the autonomous car and know that that signal is coming from us that it has the protection.
1:50:46
Uh it's not coming from a bad actor. >> Okay.
1:50:48
So the software update handles like it sort of enables the encryption uh as well I assume. >> Yeah.
1:50:56
So effectively you can almost think of our service in a similar way to you know if GPS is like FM radio it's the free service.
1:51:02
We're more similar to like XM radio or satellite radio where we broadcast out and everyone can listen to it but until you type in the subscription key >> you don't know >> the data doesn't work.
1:51:13
>> Yeah that makes sense.
1:51:13
That that's what I was going to ask like business business model but um >> uh how how big or small are current GPS devices if you want to basically have an air tag that you can throw in your shoe so you can be uh so you can know where you are or the dog collar.
1:51:30
This feels like there's a we've been on a miniaturization path for a long time. Where are we now? Where are we going? >> Yeah.
1:51:40
So the the size of the device, I mean, we've got chipsets that we're working with that are I think like 3 mm by 3 millimeters.
1:51:46
So it's something that's you probably 10 of them on the end of your out of your hand. >> Yeah.
1:51:52
>> Um it's GPS is really one of the superpowers of GPS and what we're building also is that it is a one directional broadcast.
1:51:59
So it's a receive only signal that it doesn't do.
1:52:04
Your GPS device >> like GPS doesn't know where you are.
1:52:07
It only can tell you where you are.
1:52:09
So there's no personal privacy concerns or anything like that.
1:52:12
It just gives you the data to figure out where you are.
1:52:14
Y >> and that enables it to also be used in these ultra low power devices because they just have to listen.
1:52:19
They don't have to actually talk back. Yeah.
1:52:22
>> So it enables you to provide this into you know as you pointed out things like the dog collar, the cow tracker.
1:52:26
You know we've even seen people with like peel and stick packaging labels that we're we're starting to work with that you can put on the side of FedEx package to track it. Wow.
1:52:34
So it is getting into smaller smaller devices and in the world of AI everything wants to know where it's at. >> Yeah.
1:52:42
>> And the more accuracy you can provide with more availability and just enabling these things to know where they're at more of the time unlocks so many new insights and you know logistics visibility and whatnot that that really just doesn't exist today when GPS can't get into the place where the thing is at.
1:53:00
>> Tell us more about the factory. Um, >> yeah.
1:53:02
And and you know, hard a lot of the the sort of space companies that come on the show are obvious are based out in Southern California.
1:53:08
What have been what have been the pros and cons of building uh in the Bay Area? >> For sure.
1:53:15
That's very good question.
1:53:16
That's something we we've had people ask before.
1:53:18
If you open up our satellite and look inside of it and we laid it out on a table, most people look at it and say, "This looks like the guts of a desktop computer."
1:53:26
There's a bunch of circuit boards.
1:53:28
boards. I mean there's certainly solar panels and propulsion systems and other things around it but the the core like the heart of it and a lot of pieces that that we've designed and built internally here have a lot more in common with a desktop computer than they do with you know 747 and LA has you know a lot of great talent a lot of you know big
1:53:46
aerospace talent with Silicon Valley is in many ways you know the heart of compute yeah >> all these you know the chipsets and a lot of the the talent the people that we're looking for you know it's a lot of electrical engineering a lot of software engineering ing a lot of mechanical engineering to put the pieces together. Uh which is you know the whole founding
1:54:01
Uh which is you know the whole founding team came from Stanford.
1:54:02
Um so we all kind of naturally landed here which which had the right resources around us.
1:54:10
Uh the factory that we're stood up here is you modeled more after you know a supercar assembly line than it is after a typical satellite assembly line.
1:54:17
And so it's something that you know this satellite factory is built to start providing you know multiple satellites per week where to put that in context the US currently produces maybe two navigation satellites in a year.
1:54:29
Uh where with what we're building here you we can produce that many satellites in a week which really just brings an entirely new capability to the world at a pace that's never been possible before.
1:54:41
>> What's the regulatory side of the the the picture?
1:54:42
Do you have to get uh FCC clearance for your designs?
1:54:45
Is there a is there a wait and see period?
1:54:48
Is that being accelerated at all by new tools and the ability to proofread documents with AI? Anything like that? >> It's Yeah.
1:54:58
So you very uh astute question from the space world that anything spectrum related.
1:55:03
We started working in the spectrum engineering years before we started working any of the satellite engineering because we knew that that would be the biggest challenge.
1:55:11
And one of the things that we've done that's very unique is with all the spectrum engineering we've done, we basically figured out how to provide a service that is in the GPS bands right next to the GPS signals without actually causing any sort of interference to those signals, which is incredibly difficult to do because you GPS broadcasts at about the power of a light bulb from an earth and a half away from Earth in distance.
1:55:34
And so it was just such an incredibly weak signal that there's a lot of people that told us when we started the company like there's no way you'll ever figure out how to put a high power signal next to these GPS signals without causing interference.
1:55:46
>> And a lot of people still didn't want to believe it until we launched the satellite last year and were able to show look there's our signal, there's GPS, it's 100% fine.
1:55:56
>> Um and it's it's not only say fine, it's it's really necessary in the world today with so much you know electronic warfare and jamming and other things.
1:56:02
You really need these high power signals to be able to fend off interference, whether that's interference from, you know, a wall or a roof or interference from somebody trying to jam the signal and prevent uh the capability from getting through. >> Yeah.
1:56:16
Yeah, that makes a lot of sense.
1:56:18
Well, congratulations on the new factory.
1:56:20
Thank you so much for coming on and breaking it down for us.
1:56:22
>> Thank you guys so much for having us here soon. >> Yeah.
1:56:24
Have a great rest of your >> We'll talk to you soon. Thanks.
1:56:26
Up next we have Cody Blumenfeld Gance from Chapter raising a series E to expand Medicare navigation and launch financial products.
1:56:38
>> Not with us the waiting room.
1:56:41
>> We're waiting uh in the >> ACA got his M64 >> and he showed the packaging.
1:56:46
It says brought to you by the crack team at Mod Retro.
1:56:51
>> At Mod Retro >> Crack Team. >> The Crack over there.
1:56:53
I saw some people playing cruising cruising USA cruising world.
1:56:58
Maybe something like that.
1:56:58
Uh, this is gonna be fun.
1:57:01
>> What do What do you think they mean by crack team though? >> Crack team.
1:57:04
>> If you look at this, if you look at the the packaging, it doesn't say brought to you by the cracked team at Mod Retro. It just says crack team. >> I don't know.
1:57:12
>> So maybe this is some new slang. >> They cracked it open.
1:57:14
Well, uh, we have our next guest in the waiting room.
1:57:17
Let's bring in Cody Bloomfield Gance from Chapter into the TV Ultra Down. Cody, how are you doing? doing well. Thanks for having me.
1:57:25
>> Thanks for hopping on.
1:57:25
Uh, please introduce yourself and the company. >> My name is Kobe.
1:57:29
Uh, I run a company called Chapter.
1:57:31
We are a Medicare navigation and retirement platform.
1:57:33
I started the company a few years ago after seeing my parents struggle with the Medicare process.
1:57:38
Pretty much every person in this country who's over 65 or retiring has to deal with Medicare.
1:57:43
Um, and I was just uh really appalled at how bad their experience was and wanted to make it much better.
1:57:49
That's what we've been up to. >> Yeah.
1:57:51
early on uh when you kind of discovered the problem, did you assume that that there was companies already solving it?
1:57:58
Well, and that you know when you when you talk about the scale of the market, it's like everyone over we're an aging country and everyone in in retirement uh for the most part is dealing with this.
1:58:10
>> Um what did you what did you find and then what gave you the confidence to to um start the company?
1:58:17
Uh I found really poor uh experiences all around.
1:58:21
Uh most Medicare brokerages in this country are um heavily incentivized to push plans that pay people uh that pay brokers more rather than focusing on what's best for the consumer.
1:58:31
Um and there's really no good technology in the space at all.
1:58:33
Um so you really have a combination of sort of mom and pop brokers.
1:58:37
You can think of these as local real estate agents and then you have these legacy call centers that are basically just like marketing orgs that are very bad at what they do.
1:58:46
um and really nothing in between that really prioritizes the consumer's interest.
1:58:50
Um so, uh when my parents were going through it, they had to deal with faxes and phone calls and they got really bad guidance.
1:58:55
My mom actually now has uh lifetime late enrollment penalties because she was told to sign up too late.
1:59:01
Yes, the government imposes lifetime penalties on people if they sign up late for Medicare. >> Good.
1:59:07
Uh yeah, talk to me about uh then how it seems like reaching the potential customer or user as early as possible is critical.
1:59:15
What's the customer journey to actually uh get on chapter or work with an advisor?
1:59:21
Uh how do the users actually find the product?
1:59:26
>> We take an really heavy AIdriven approach, but we augment humans with the AI.
1:59:30
So, we have one of the smallest teams um probably of any tech company and especially any Medicare company for our scale and we're really proud of that because we're pretty sophisticated users of AI.
1:59:40
>> Um and so a consumer will find us through one of our partners.
1:59:42
We do almost no direct to consumer work.
1:59:44
It's all through enterprise partners. Yeah.
1:59:47
>> Um they'll find out about us through their financial adviser or their health system or hospital.
1:59:52
>> Um they will give us a call, fill out some information, and they'll be connected to one of our full-time employees who's a licensed Medicare adviser.
1:59:57
that Medicare adviser has a lot of tooling at their at their fingertips that we've built to make sure they can deliver really high quality guidance all the time for every single person.
2:00:06
>> And and what does that tooling look like?
2:00:07
Is it is it visualizing and analyzing numbers and sort of instantiating spreadsheets and dashboards and charts or is it actually going and filling out forms and dealing with like legacy government systems that can be abstracted into something that's just more usable?
2:00:23
>> All of the above and a lot more though.
2:00:25
I'll give you a couple of examples.
2:00:25
Um, one is, uh, every single insurance carrier has a different portal that one has to use to look up information and fill out forms.
2:00:33
So, we have to automate all of that and they don't, most of them don't have APIs as you can imagine. Yeah.
2:00:38
>> Um, so that's kind of the automation of uh, filling out forms and paperwork.
2:00:42
>> Um, the for any given uh, Medicare plan recommendation, we have to know every doctor that that person is in network with.
2:00:49
We have to know every prescription that that person takes.
2:00:51
In order to answer the what sounds like a very simple question of what prescription will will what will a prescription cost on a given Medicare plan at a given pharmacy >> that requires tens of billions of records to know just that one question and that's one of many elements.
2:01:06
So we do a lot of work to obviously our Medicare advisors are not crunching those numbers every time they talk to someone.
2:01:12
So a lot of that to surface the right answer to the to the Medicare adviser. >> Yeah.
2:01:16
Uh you guys just surpassed 100 million uh uh run rate.
2:01:19
Uh what seems pretty fast for uh for company in in healthcare uh which typically you know this isn't like selling like some some image image gen model or something like that.
2:01:35
Uh what is what is bestin-class?
2:01:38
Who are you guys going up against from a kind of zero to hund00 million run rate?
2:01:42
Uh I'm assuming you guys are one of the the faster uh in history, but uh I'm curious.
2:01:49
>> I I don't think of ourselves as a healthcare company really.
2:01:51
I think of ourselves as a really good tech company.
2:01:53
So we compare ourselves to the fastest growing companies.
2:01:55
We grow as fast or faster than companies like RAMP, companies like Glean.
2:01:58
Um we went one to 100 mil in run rate revenue and I think about two and a half years.
2:02:03
Um so I really think about us as just like what do great tech companies do and we try to orient the team around that because the bar is just too low in healthcare.
2:02:09
So then what is the uh what is the funnel to to actually grow the business?
2:02:13
What is the what is the flow?
2:02:16
You said you don't do consumer marketing.
2:02:18
Um is this like you said enterprises?
2:02:21
Are you uh do you have SDRs?
2:02:24
Are you going outbound to companies and and financial advisory groups?
2:02:27
Um what is that uh go to market motion actually look like?
2:02:32
>> We do have an enterprise partnerships enterprise growth team. Yeah.
2:02:34
Um >> the team the whole team is about six or seven people.
2:02:37
Uh so as I said we're very small and we take a lot of pride in having a really high bar for talent.
2:02:43
>> The whole the entire company is >> no no team enter team is >> but but all of all of our sort of corporate headcount product engineering growth uh legal etc. We're about 30 people. >> Wow.
2:02:56
>> That's still that's remarkable. Well congratulations.
2:02:59
Uh you just raised a round. Tell us about it.
2:03:02
>> Yeah uh we raised about $100 million uh led by Al Gore's generation fund. Thanks Massive. >> Absolutely massive.
2:03:14
>> Thank you so much for taking the time to come chat with us.
2:03:15
Congratulations on all the progress and thank you for everything that you do.
2:03:19
>> I'm sure you'll be back on probably multiple times.
2:03:20
We'll talk to you soon at this rate.
2:03:22
>> Have a good look to it. >> Goodbye. >> Cheers. >> Bye.
2:03:25
>> Up next, we have CZ from Binance.
2:03:25
He is the founder and former CEO.
2:03:28
He released his book, Freedom of Money, detailing Binance's rise, crypto's evolution, and his legal battle with US regulators. CZ, how are you? >> I'm good. I'm good. Thank you.
2:03:39
Thank you for >> Thank you so much for hopping on.
2:03:42
Uh tell us about the book. What was the goal?
2:03:45
Is this an attempt to set the record straight or just tell your story?
2:03:50
What what what motivated you to write a book at this moment in time?
2:03:54
Um I think it's really just to tell my story and then um I was bored for I had nothing to do for a couple years.
2:03:59
So I started writing a book when I was in prison. >> Okay.
2:04:03
>> And then uh I just finished when I got when I got out.
2:04:06
So um I thought you know it might be interesting story to share and you know let people know what my view is. >> Yeah.
2:04:14
What do you what do you think people get wrong about your story?
2:04:18
Well, I think a lot of traditional media uh have many misconceptions about crypto uh Binance, myself, etc.
2:04:23
So, I think there's a lot of uh media that's not accurate about crypto.
2:04:28
So, I think this is a very good chance for uh for me to share my perspective >> and have people understand crypto better.
2:04:36
>> What specifically do people get wrong about crypto or you or Binance? >> Sure.
2:04:41
I mean like from 2013 right people think that bitcoin is only used by drug lords or for illicit activities.
2:04:46
The truth is actually uh if you look if you look at percentage wise illicit activities in crypto is actually much much less than in traditional finance.
2:04:54
much less than in traditional finance. M >> um and then by extension a lot of the crypto players a lot of crypto platforms get hit and recently you know there's more attacks about you know um uh just just random attacks on me about how I do business who who I have connections with
2:05:12
so I'm a simple tech guy so I just wrote the book you know the the way I wanted to tell it it's a pretty simple language pretty straightforward book >> this is a simple guy this is a simple guy >> what uh >> I think I'm a relatively simple guy >> yeah how have you been processing ing the the new regulation that's been proposed uh in the in the United States. What do you think uh needs to change in
2:05:31
What do you think uh needs to change in the crypto industry?
2:05:34
Because I I I take your point about uh you know uh the the amount of elicit activity might be lower than in in cash or the traditional financial system, but you know the goal I think for everyone would agree is is to get that to zero.
2:05:47
And so what what do you like about the new regulation?
2:05:50
What do you think is is reasonable uh to ask for?
2:05:56
>> Well, I think right now US is making really good progress on crypto regulation.
2:05:59
The Genius Act was passing last July, but I think right now there's still quite a lot of debates based on my layman understanding. I'm not an expert.
2:06:06
I'm not a lawyer, not a not a regulatory guy, >> but um seems like no, there's a lot of debates about uh stable coin interest rates.
2:06:13
Um so um I think it's a big important issue, but from my perspective, any clarity is better than none.
2:06:20
none. So and um we will not I think the current iteration of regulations will not get get everything right on the first try right so there'll be some collaboration over time >> um so I think it's more important to make progress and move forward yeah >> how how are you thinking about the broad
2:06:37
tradeoff between uh decentralization anonymity and then uh oversight regul and regulation like uh it feels like we've been moving towards more oversight more regulation more KYC we've heard from some crypto leaders that that can lead to data breaches and other problems. But where do you sit on the
2:06:53
But where do you sit on the level of regulation in the crypto industry broadly?
2:06:59
>> So I think right now the crypto industry is to be honest is too transparent.
2:07:01
It's actually extremely easy to track crypto funds.
2:07:05
Um like the blockchain is a public ledger and then if you couple that with a a few centralized exchanges KYC information, you can track most of the transactions pretty accurately.
2:07:14
So u I think right now um there's a lack of preserving of privacy but right now the problem is many of the regulators and law enforcement people don't know how to use it yet.
2:07:25
Uh some people do I think some of the US law enforcement actually knows it quite well >> in other countries they know they know it much less.
2:07:32
it much less. So hopefully we'll get to a balance where I don't know where the optimum balance is but there should be an optimal balance where you know we satisfy all the regulatory requirements but we also need to protect individual privacy right for example I'll give you a couple examples
2:07:47
>> please >> u for example like if if this company if your company pays everybody in crypto >> and if you get one payment today on the blockchain you can just trace to the address that he paid you and see how many addresses that address paid in the last a week can figure you can figure out everybody's salary. Yeah. Yeah. >> Right.
2:08:05
So that's a privacy issue. Yeah.
2:08:08
>> And if you if you stay at a hotel, you pay for the hotel, then people know where you if people know your address and the hotel address, people will know that you're going to stay at that hotel, which for some people may create security issues, right?
2:08:18
So there's little problems like those that are not solved yet.
2:08:23
Um so we need to we need to strike a balance.
2:08:25
Um it's hard to say exactly where the balance is, but I think over time we we'll get there.
2:08:31
uh how are you thinking about the interaction between AI and uh crypto generally there's been a lot of excitement even from uh people in AI about uh crypto and the and the intersection but I'm curious if uh what what your overall view is and then uh if uh if it's positive some maybe specific examples of where you you expect to see it manifest first. >> Sure. Absolutely.
2:08:56
Yeah, I think well uh both AI and blockchain are big recent new big industries.
2:09:01
I think there's really three big technologies in my in my adult lifetime, right?
2:09:05
There's a AI, there's blockchain, there's internet like it's on those levels.
2:09:09
I think a AI AI is going to use crypto for payments for transactions.
2:09:14
Um they're not going to use no they cannot KYC through a bank.
2:09:18
They cannot do um they cannot do a selfie.
2:09:21
They don't have a passport etc.
2:09:23
And also u payments in every country is a little bit different >> whereas crypto uh blockchain is the same across different countries.
2:09:29
So uh one you integrate with a blockchain once it works globally um and it also handles microtransactions large transactions etc.
2:09:38
And also crypto is going to increase the amount of transactions significantly.
2:09:42
So the traditional payment rails may not be able to handle that.
2:09:46
I think blockchain also have a lot of benefit from AI.
2:09:48
I think right now a lot of the applications are in blockchain quite difficult to build.
2:09:52
Um I think with with AI we can probably build like know safer um safer tools for people to do self-custody and uh safer tools for people to transact.
2:10:02
So and I think so uh today the two industries to be honest have not really leverage each other that significantly but I think in the future they will.
2:10:12
>> How are you thinking about the risk of quantum computing to the cryptocurrency ecosystem broadly?
2:10:18
Um I think there's several risk but I think overall though um any technology improvement is always going to be good.
2:10:25
More computing power is good for crypto.
2:10:27
>> So uh quantum may break the existing encryption mech mechanisms but with quantum computing there's probably new well there will be new encryption algorithm there are already quantum approved u uh encryption algorithms that quantum computers do not have an advantage to crack.
2:10:41
So we just need to upgrade the protocol to use those encryption mechanisms.
2:10:45
Also more computing power with quantum that's probably newer encryption mechanisms we have not even thought about >> um that we can use quantum to encrypt and decryption is always going to be much harder. >> Sure.
2:10:57
What about uh non non quantum hacking uh throughout the crypto boom there's been so many upstart projects.
2:11:07
Many of them have been able to get to escape velocity and they're still around today.
2:11:11
a lot of them have had to go through hacks and and and adapt.
2:11:13
And it feels like with the moment that we're in in terms of AI's effect on cyber security, we could potentially be looking at maybe a bifurcation between the the the projects that have the resources to actually harden themselves against new cyber security threats and those who are maybe smaller upstarts and don't.
2:11:34
How do you think that effect plays out?
2:11:38
I actually think AI is going to improve security for uh for most projects.
2:11:40
Um like um um anthropic cloud, right?
2:11:42
So now they're I think if you play like like that, you could potentially discover many flaws at least they claim um in many projects.
2:11:54
>> But I think projects can also use use their tool uh to fix their security problems.
2:11:58
I think a big company like that they already make a lot of money.
2:12:02
They don't need to exploit smaller projects to hack to do illegal stuff.
2:12:03
So I think right right now with the AI tools that's available the developers can use those tools to find their own problems.
2:12:11
So uh but of course if you don't if you don't do that then the hackers may do that for you.
2:12:15
Um which is a typical problem in we have today anyway.
2:12:20
>> So um I think with AI security is actually going to get become better.
2:12:22
I don't think it's going to become worse.
2:12:25
>> So um so I'm pretty comfortable about that.
2:12:29
>> Do you know who Satoshi Nakamoto is?
2:12:32
>> Uh no unfortunately I don't.
2:12:32
Uh, even if I did, I would have said no, but I honestly don't. >> Okay.
2:12:37
Do you have have how have you processed that question of who is Satoshi?
2:12:41
Have you wrestled with it?
2:12:41
Have you done a bunch of research to try and figure it out?
2:12:46
Have you had various suspects at various points in time, favorite pet theories, wildcard theories, or has it sort of been a quick ride to sort of process that and then let go of that desire because it's the unsolved mystery?
2:13:00
And >> this is an interesting point.
2:13:02
I should have put this in my book.
2:13:03
Maybe maybe the next edition.
2:13:07
>> But I've come to peace with it.
2:13:07
Um I think I'm curious obviously and if there was one person I really want to meet in the world that that would probably be him.
2:13:14
But I think there are negative consequences if if we find out who he is, >> right?
2:13:18
For for example, if I couldn't lie on the oath um if people say look, have you met Tatoshi?
2:13:23
>> If I say yes, then you know that's going to all hell's going to break loose. >> Sure.
2:13:27
>> I think it's better if we don't know who he is. Yeah.
2:13:29
um it's better if he um and without knowing him that uh we don't have a founder centralization. >> Yeah. >> Right.
2:13:36
For example, if you look at Ethereum Vitalics there, right? So there centralization.
2:13:41
>> What makes Bitcoin unique is that we don't know we the founders no longer participating.
2:13:45
He's he may not be around.
2:13:47
He may not be participating.
2:13:50
>> So uh that makes it more decentralized.
2:13:52
Um I think that's a good thing and we should come to terms I came to terms ter terms with it quite a while ago.
2:13:55
So even though I'm curious, I'm not actively looking. Yeah.
2:14:02
>> Have you ever thought about doing a anonymous project or do you have a reflection on why we haven't seen more projects effectively run at least to my knowledge the Satoshi playbook of maybe it requires some crazy OPSAC to go anonymous for a couple years.
2:14:19
But if it worked for Bitcoin, I would imagine that somebody would have thought, I'm going to do the same thing for this new project with slightly different opinions about how the the the technology is built.
2:14:31
I I haven't seen it happen, but what's your what's your take on the idea of a new attempt at a Satoshi like founder in the crypto industry?
2:14:42
>> I actually really want to see that too.
2:14:44
Um I think that's really really cool idea to be honest, but I think also very hard to do.
2:14:47
Most projects fail even with the founders heavily promoted.
2:14:50
We know who they are etc.
2:14:52
Um for a new project without knowing the founder there's less trust in the community.
2:14:57
Bitcoin was the first one somehow got you know slow it started very slowly.
2:15:01
It took many many years for it to get to where it is today.
2:15:05
Um and for a new project to do that it's very very difficult and there there have been anonymous projects that you know that are basically rugps right.
2:15:14
So um there also the other side of it people people lose trust with anonymous project.
2:15:19
So um to do what Bitcoin did is very very difficult.
2:15:22
I would I would actually love to see more anonymous fully decentralized you know projects.
2:15:29
But what you mentioned is the OBSAC is also extremely hard.
2:15:33
>> It's so hard today to not leave any trace both digitally and physically. Right.
2:15:36
So um the fact that nobody has really announced who Tatoshi is means that his offse is crazy. Um I don't I think 99.
2:15:44
9 nobody else can do it really at this point. >> Yeah.
2:15:49
>> Uh what what do Americans miss about uh crypto adoption globally here?
2:15:53
I mean so many at least at least younger generations almost everyone has some exposure to digital assets or some experience buying selling maybe not uh maybe not using it functionally for payments but obviously it's very different uh in other parts of the world with with uh uh you know less um centralized financial institutions.
2:16:20
Yeah, I think America for the last few years uh before the Trump administration was you know fairly anti-crypto.
2:16:25
So many of the uh funders left uh many of the projects left and many of the liquidity left right there.
2:16:32
The biggest crypto exchanges are not in America um today.
2:16:37
Uh the biggest blockchains, the biggest stable coin, they're not America based.
2:16:41
So I think America misses that liquidity quite a bit.
2:16:43
Um, America right now has very forward-looking regulations and now people flocking back.
2:16:48
I think the talent pool's coming back, but some of the larger players are not backing America yet.
2:16:54
So, I would love to see that changing.
2:16:56
Um, I think right now crypto if you if you buy crypto, Americans are probably paying the highest fees in the world.
2:17:02
Uh, whereas if you buy anything else, America's usually paying the lowest price.
2:17:06
Um, so the uh the cost to American consumers today for accessing crypto is quite high.
2:17:11
Um so that's a disadvantage that America has today.
2:17:14
But uh America has a large economy, a lot of entrepreneurs, a lot of VCs and good liquidity in traditional markets.
2:17:20
I think um and u uh I think America has definitely has the um ability to catch up very quickly.
2:17:30
>> Uh you were born in China.
2:17:30
How are you thinking about geopolitical relations between the US and China?
2:17:34
Tensions seem to have been rising for years. There's trade tensions.
2:17:39
There's all sorts of geopolitical tensions.
2:17:41
Is there any hope for deescalation between the two countries?
2:17:47
>> Um, I'm not an expert on the geopolitics of between different countries and also um my label understanding is both countries have leaders with pretty big personalities. Yeah.
2:17:57
>> So they're very hard to predict.
2:17:57
Um I think the um the uh President Xi in China is easier to predict than President Trump.
2:18:04
President Trump is like a wild card, right?
2:18:06
Which is which which is in which is in his advantage.
2:18:08
is in which is in his advantage. um you can't predict what what he's going to do and u but I do think both both countries are large countries now with leaders who are smart and who are business driven they want the economy to grow so if that's the goal then there are certain
2:18:24
then I'm optimistic that you know there's certain outcome to be reached >> between two countries there's usually a fairly large zone of overlap that you can reach deals uh right now it's just the personalities and also both countries are quite proud so they they're all hard negotiators >> the negotiations at that level takes time Yeah. >> Um, so, uh, but I I am, uh, I'm fairly
2:18:40
>> Um, so, uh, but I I am, uh, I'm fairly I'm fairly optimistic that, you know, both the two countries will work hard something that's beneficial for both.
2:18:50
>> Uh, you've written the book. What's next for you?
2:18:51
What do you think the next decade looks like?
2:18:55
>> Um, I'm actually not too sure exactly.
2:18:57
Um, so I'm doing like a few different things right now.
2:18:59
Um, I'm running investment fund.
2:19:01
Uh, well, I'm not really running it, but like know I support it.
2:19:05
>> Um, I do some mentoring in the space for new entrepreneurs.
2:19:07
Um, I run a u uh a free education platform, a Google Academy um that provides free education to 240,000 kids now.
2:19:15
Um, and we've only been at it for like a year and a half.
2:19:20
>> Um, and then um I also um yeah, so and then I also advise different governments on crypto policies.
2:19:24
So between those four things that keep that keep me pretty busy, the book was actually a huge distraction for me.
2:19:30
I can imagine >> it took a lot of time.
2:19:32
It takes a lot of time to write a book.
2:19:35
>> Um but I'm glad know it's it's out there.
2:19:37
Um, and there's an audio version coming out soon.
2:19:38
And then after that, I'll put that I'll put that on pause.
2:19:42
Uh, just let it be for a while and then figure out what to do. Yeah.
2:19:46
>> What was the strategy for the audiobook version?
2:19:48
Did you narrate it yourself?
2:19:50
Hire a human narrator, use AI?
2:19:54
>> So, um, um, one of my friend Michael Santos is going to narrate it. Okay.
2:19:56
So, um, um, um, he we had this sort of agreement verbally from a long time ago.
2:20:03
And also Amazon doesn't allow AI um uh uh generated voices. >> Interesting.
2:20:08
>> Yet I didn't know that.
2:20:09
>> Um so you'll be a human read uh or audible.
2:20:13
Um and then uh I've been playing with AI quite a bit myself.
2:20:17
>> The AI cloning of of voice is I can't tell the difference from my own voice. Yeah.
2:20:21
Um it's and it's just better. It reads more smoothly.
2:20:25
>> Um it's better than my own reading.
2:20:25
So in certain uh we on certain other platforms or in certain other countries we may use an AI generated voice that clones my voice to to try to read it.
2:20:33
Uh I haven't finished that yet.
2:20:36
Um there are still little quirks here and there.
2:20:39
Some sometimes AI make very obvious mistakes.
2:20:42
Um you know you it pronounces Chinese names wrong which I would not make that mistake.
2:20:48
>> Uh you pronounce this sometimes you will say like when I write $400 you say $400.
2:20:54
Um, so I would not make that mistake, but 99% of the time he actually reads better than me. So, um, we'll see.
2:20:58
Uh, so I might do two different audio versions.
2:21:02
U still playing around with it. >> Yeah.
2:21:05
>> I wonder after Jasse's letter today if he's still going to be anti anti- AI voices. >> Yeah. Yeah.
2:21:12
>> Um, I did have a one last question. I'm curious.
2:21:14
How how did you process the prediction market boom over the last two years?
2:21:18
there had been, you know, long people had long had predictions that uh prediction markets uh would intersect with with crypto and and be really big.
2:21:29
And yet there was attempts in the 2010s that didn't really reach uh critical mass.
2:21:34
Um so I'm curious, you know, how you process that that that entire period. >> Yeah.
2:21:40
>> Yeah. So I think I today I do think prediction markets has a huge potential and it's already pretty big like the the top players are pretty big already and there's like hundreds of thousands of upcoming platforms as well and also if you look at the regulatory landscape um
2:21:55
the CFTC chairman uh Michael Silic he talks about prediction markets multiple times I every time I watch him talk he seems to mention prediction markets so it seems like the regulators and the um traditional markets also moving in so um And as you said there have been many attempts previously but then timing is important. Um some ideas you know even
2:22:14
Um some ideas you know even even though the ideas are very obvious if you implement them too early they don't get traction you have to implement the right idea at the right time.
2:22:22
I don't know what all the ingredients are for predition markets but somehow now seems to be the right time.
2:22:28
The previous attempts struggled um and now it seems to be taking off.
2:22:33
So I'm a big proponent for for anything that's new and interesting and I think prediction markets are very interesting.
2:22:38
They're the price discovery and truth discovery.
2:22:43
They're kind of using price to discovery truth, right?
2:22:45
So u which is actually a very which is usually the reverse for what we do.
2:22:49
We like information drives trading volumes.
2:22:51
So that that so that's a very interesting dynamic.
2:22:53
Um I think uh and also um uh the easy labs the fund I I'm involved with uh we invest in multiple prediction markets.
2:23:01
So, we'll see which ones work, but I do think that it's a huge potential and it's it's hot. Yeah. And it works.
2:23:08
>> Are you How are you thinking about any of the previous crypto booms or narratives or themes uh coming back?
2:23:17
Things like NFTTS or crypto gaming?
2:23:17
Are you optimistic on any projects, Dows that uh had their moment in the sun and and didn't quite re release uh reach escape velocity?
2:23:28
Do you think anything will have a second wind in the near future? >> I do think so.
2:23:33
I think um many things will have a second wind, but the second wind will most likely be a little bit different, right?
2:23:38
There'll be something that's, you know, um like even prediction markets today, they're different from the sort of prediction markets four, five years ago.
2:23:45
>> Um so every iteration there will be some tweak.
2:23:48
Um and it's usually that little tweak that makes it a little bit different and maybe the micro environment.
2:23:52
So I do think that some of the things that you know that were there like I think Dows will not disappear. Mhm.
2:23:58
I think Dows haven't really took off to be honest.
2:24:00
You know, the concept being there for years.
2:24:01
It's like you know in the 19 even in the 2010s video streaming doesn't really work right like know this type of even today this this type of call sometimes internet doesn't work sometimes the microphone doesn't work right.
2:24:13
So uh uh you know we get into those situations a lot.
2:24:15
So um a lot of things take a lot of time to mature.
2:24:20
So I think the Dows the NF NFTs um uh again I don't the next iteration may be slightly different but you may still be called NFTs or NF2 it may be a different name um but I think um tokenizing art is probably going to come back at some point multiple times.
2:24:36
>> I don't know when it will really hit big and stay NFTTS I think honestly we saw we saw like a we saw we saw a rise and then and and then a downward trend. >> Yeah.
2:24:44
So, um, it's hard to say, but I think all of those things eventually will should be much bigger than they were today. >> Yeah.
2:24:50
Well, thank you so much for taking the time to come chat with us. Uh, congratulations.
2:24:54
>> Congrats on the launch.
2:24:55
>> I recommend everyone go check it out and hear uh CZ's side of the story. Thank you so much. Have a great day.
2:25:01
>> Thank you so much for having me. Thank you. >> Talk to you soon. Goodbye.
2:25:02
Uh, there's some lore on the timeline.
2:25:06
Bluetooth is such a strange name for technology.
2:25:10
Apparently, it's named after a Scandinavian king who united Norway and Denmark.
2:25:14
And the logo is a combination of two Norse runes. I like Bluetooth.
2:25:16
Uh anyway, let's bring in our next guest, Tal Hoffman from Enclave.
2:25:22
He's the founder and CEO here to tell us about Cedron. How are you doing? >> What's going on?
2:25:30
>> Hey, thanks for having me. How are you? >> We're good.
2:25:32
Uh please introduce yourself and the company. >> Yes, please. Uh so, I'm Dal.
2:25:35
I'm the co-founder and CEO of Enclave. Mhm.
2:25:40
>> Essentially, we're an AI code security platform um using LLM to find critical vulnerabilities in code bases. Yeah.
2:25:46
>> The way traditional scanners want. >> Yeah. >> Um yeah. >> So, huge week.
2:25:50
Uh take us through how you've been processing it from your perspective.
2:25:54
What is AI actually capable of doing? What is not there yet?
2:25:57
Uh how have you been processing all the news around AI and cyber security this week?
2:26:04
Yeah, I think what uh Tropic has done is like tremendous for the industry.
2:26:07
Um I think it's a tremendous leap forward for security.
2:26:12
Um I think the real novel thing that they did they did besides finding the unknown unknowns the vulnerabilities that have been there for decades. >> Sure.
2:26:22
>> Uh were able to exploit autonom autonomously vulnerabilities.
2:26:27
>> Uh essentially exploitability is the name of the game as I see it right.
2:26:29
U because a vulnerability that's not explo exploitable is not worth as much until right now unless something changes.
2:26:37
Uh so I think it's a huge leap forward.
2:26:40
Um and I think they've done very correct moving deploying it safely.
2:26:45
Um yeah I think it's very exciting for anyone that's in code security including ourselves.
2:26:54
>> And yeah how do you see yourself fitting in?
2:26:56
Tell me about the shape of the business, the strategy, uh how you want to roll out your products. >> Yes.
2:27:02
So I think uh especially with MOS and the recent changes, I think that it's going to be um asymmetrically deployed.
2:27:10
Um and so I think that this creates an opportunity for other organizations that do not have access to the technology >> to be proactive about it and and procure whether it's for to us or our competitors.
2:27:23
I think it's uh net positive for the industry um especially uh with new attack surfaces being exposed uh and created and with new teams uh from regular developers to go to market and uh everything in between deploying more code.
2:27:40
Um so I think it's a tremendous opportunity. Um yeah.
2:27:46
>> How are you thinking about interfacing with project glasswing?
2:27:48
Do you want to fold into that and then be able to uh do things on top of the private models that are maybe deployed these in this asymmetric way or uh do you want to use other models and sort of figure out a different uh way to differentiate and add value? >> Yeah.
2:28:07
No, I think we want to go and partner with entropic that has done great work and open AI and all those big lab.
2:28:14
>> I think uh the alpha is currently in using them.
2:28:16
Um so definitely want to partner with them.
2:28:18
We are talking with them.
2:28:20
>> Uh again I think they are doing a tremendous job but I think ultimately most organizations do not currently have access to this technology and they need an independent uh system level reviewer that's able to constantly uh like deploy the state-of-the-art.
2:28:39
>> Tell us about the round. You raised some money. >> Yes. >> Yeah. Yeah. Yeah.
2:28:42
So, uh, we have raised, uh, $6 million led by 850.
2:28:44
Um, and then we have another a bunch of exciting investors on board like >> Levi, >> brother.
2:28:59
>> Mother, Mark Benny of U. >> Whoa.
2:29:04
>> Yeah, >> you got the dolphin in. >> Dolphin. >> The dolphin.
2:29:08
You don't you don't see him him ripping ripping personal check.
2:29:10
Uh la last question from my side.
2:29:12
What what have conversations been with uh with customers like who who do you need to get to?
2:29:17
Who are the key stakeholders?
2:29:17
Uh how how diffuse is the understanding of cyber security threats these days?
2:29:23
Uh and what are you educating customers about most frequently? >> Uh yes, I think so.
2:29:30
We have just out of beta just released the product.
2:29:33
Uh I think for us we're trying to cater to both the security practitioners at the end of the chain like we've we are seeing very uh we are seeing a lot of anger from them to have their own CL code their own cursor write their own shiny object uh so we want to empower them but I think most importantly um we want to empower developers uh to be able to deploy safely and quickly because it's becoming very concerning.
2:30:00
Yeah, >> we can see we have some new zero days that we'll be publishing soon following responsible disclosure >> and I think that like security is going to be uh very big as a role the new job you see how sexy security has become the last couple of weeks.
2:30:16
Um so I would say like ar your security personnel u but ultimately this whole thing is very good for them.
2:30:23
for them. Um you can assume that bad state actors already utilize uh those those zero days so eventually um as more organizations get exposed to this powerful tech that is LLM powered security research um the safer it becomes um and I think it's become very
2:30:42
obvious we don't have to do much education it's like the the opportunity is very obvious the problem is very obvious >> how are you thinking about the business model do you want to uh sit between the code that's written and the pull request and the code review phase. Uh do you
2:30:55
Uh do you want to be actively monitoring systems in production? Both.
2:31:01
>> Yeah, definitely both.
2:31:01
Uh but we are trying to be um like to prevent those issues to begin with whether it's through GitHub through the P request through cloud code, MCP, through cursel uh but also yeah definitely also prevent production and I mentioned exploitability.
2:31:18
Um so context is most important here is look and looking at your and I think this is something that whis has done a great job with sure is looking at the cloud environment the run at the cloud environment at the runtime see what's exploitable what's not because you can have a 10.
2:31:32
0 zero CVSS vulnerability that's completely irrelevant uh because it's not exposed to the internet.
2:31:39
Um so yeah, we want to be both preventing but also finding uh live uh vulnerabilities, but right now we are focused on code. Yeah.
2:31:48
>> Yeah, makes a lot of sense.
2:31:48
Uh well, congratulations on the round.
2:31:49
Thank you so much for coming on and breaking it down for us and have the rest of your day. We'll talk to you soon. >> See you soon. >> Goodbye. >> Cheers.
2:31:58
>> Um what else is in the timeline before we wrap up the show?
2:32:00
Uh Yahoo's G800 is at Augusta.
2:32:03
If you got really good SEO between uh 1994 and 1999, then messed everything up after that, your executive team in 2026 will still have a G800 money, says Chris Baky. That is very funny.
2:32:14
And Preston Holland is chiming in with some crying emojis.
2:32:16
Um >> Secretary Kennedy >> new podcast, >> the Secretary Kennedy podcast.
2:32:23
Derek Thompson says, "The urge to pod cannot be denied.
2:32:25
Tech VCs and David Rubenstein are richer than God.
2:32:28
What do they want to do in their enormously valuable spare time? Fire up a mic and pod. Yeah.
2:32:33
What does Jamie Diamond want to do after JPM?
2:32:35
Start a media company, i. e. pod. Again, RFK Jr.
2:32:37
is in charge of all government health policy.
2:32:40
What does he want to do with that power? Pod about it.
2:32:44
>> Uh, in this uh Will highlighted Jeremy's post, posting is the end state.
2:32:48
It's the treasure that waited that awaited Alexander at the end of his conquest.
2:32:54
It's all that's left for man after gaining the world.
2:32:56
It's all there is at the very end of it all.
2:32:58
Celebrities, billionaires, industrialists, scholars, all wind up as the humble poster. >> Poster.
2:33:04
Uh, David Rubenstein's podcast is deeply underrated.
2:33:07
If you're not already listening to it, the David Rubenstein show, peer-to-peer conversations, airs on Bloomberg television.
2:33:13
He's also done history with David Rubenstein on PBS.
2:33:15
Uh, he is the chairman of Carlilele Group.
2:33:18
And, uh, yes, truly, uh, very successful, but still enjoys a recorded conversation.
2:33:25
Um, in other news, uh, The Acquired Podcast just released a new website, acquired. fm. >> Stunning.
2:33:32
Many people are calling it the most beautiful podcast website in history. >> It's incredible.
2:33:36
Really, really well done.
2:33:37
Uh, every time you mouse over something, you get a vinyl record that pops out.
2:33:41
Uh, I'm very excited to see uh, the physical instantiation of this and and it fits the brand perfectly.
2:33:46
Uh, it's a great uh, uh, so many iconic episodes, so many iconic interviews.
2:33:50
So, congratulations to uh the folks at Acquired.
2:33:55
Every company has a story.
2:33:55
Uh really, really welldesigned.
2:33:58
>> We got to have him back on very soon.
2:34:01
>> Uh but thank you for being with us today. We'll see you tomorrow.
2:34:05
>> It's been an honor >> and a privilege to podcast with you today.
2:34:09
>> We'll see you tomorrow.
2:34:09
Leave us five stars on Apple Podcast and Spotify.
2:34:10
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