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[Music] [Music] [Music] If you let me [Music] [Music] 5 4 3 2 >> You're watching TVPN.

4:59

>> Today is Monday, July 21st, 2025.

4:59

We are live from the TVPN Ultra Dome.

5:02

the temple of technology, the fortress of finance, the capital deap cap. Um, big news.

5:10

Open AAI, great to be back.

5:14

Uh, OpenAI has announced that they have won a long they achieved the long-standing grand challenge in AI gold medal level performance on the world's most prestigious math competition, the International Math Olympiad. That's the IMO.

5:30

So, this went up at 12:50 a. m. on July 19th.

5:38

>> Typical timeline for announcements.

5:40

>> So, this is this is basically like Friday night, Saturday morning.

5:42

You're looking at uh basically 1:00 a. m. from Alexander Wei.

5:46

Um, and he shares a picture of a strawberry with a metal with the OpenAI logo on it.

5:52

Someone also tested, they took this picture, they uploaded it to Chat GBC.

5:57

What's the fruit in the image?

5:59

how many Rs are in that fruit and it nailed it.

6:01

So we are truly we are truly AGI has arrived has arrived.

6:07

>> Um also before we go deeper into that story uh we have a new partner Reream. You saw it in the intro.

6:14

We're very excited to welcome them as a sponsor of the show we've been >> running on Reream >> secretly >> secretly >> secretly >> since day one >> since day one.

6:23

It's been our secret to to success and it can be your secret to success. Yeah.

6:27

If you have >> we support >> a lot of the Fortune 500 already for all their live streaming infrastructure.

6:31

So if you need to go live go live with Reream >> and you see OpenAI do streams like that that is a thing that has entered the standard um com strategy.

6:44

>> I don't know if XAI is running on Reream.

6:46

But they do but they do stream and uh you know it used to just be the the hyperscalers, the Mag 7, the big big companies that would do a live stream around a an annual uh event.

6:55

Then Brian Chesy came out and created founder mode and basically said put all your announcements on a on an annual release schedule.

7:04

Uh bundle them all up, have the team celebrate, push to get across the finish line.

7:08

And part of that is let's throw an event.

7:11

Part of that is let's get the CEO and the product leaders on stage.

7:14

tell the community about what we're building, what we've built, and now a lot of people are streaming it.

7:19

If you're going to stream your stuff, you need reream. Anyway, go check it out.

7:22

Um, so Dylan Field, um, someone who's who has streamed events, uh, you know, uh, uh, Figma obviously has config their dev event, uh, annually, and they actually do two of them, and those are streamed, uh, all over the place, probably using reream.

7:39

Um, and uh, Dylan chimes in on the OpenAI news.

7:42

He says, "Congrats to the congrats 2025 IMO winners and participants including OpenAI who trained a generalpurpose reinforcement learning model and achieved IMO gold.

7:54

OpenAI team includes these two folks, Cheryl and Polomial Gnome.

7:56

Fun fact, Polomial also won the 2025 diplomacy world championship as a human.

8:02

Um, and so people are saying AGI is right around the corner.

8:06

Um AJ from semi analysis says, "What stands out to me scaling RL on nonverifiable rewards likely via rubrics and LLM as judge thinking and reasoning for several hours at a time for a highly specific task.

8:18

This is what the $20,000 per >> month >> month model will look like.

8:24

Um and so there were a bunch of interesting things about this.

8:28

Apparently there are a few different ways to to tackle um math IMO level math problems.

8:34

one is using this this uh program called lean that is a formal math proof verifier and there's rumors that Google's building their system to leverage that a lot openai apparently went way way down just the textbased LLM reasoning path and had a lot of success there.

8:55

So, even though as we'll get into in this story, it feels like it's neck andneck.

8:58

Maybe Google was earlier and they just didn't release it faster and maybe this is a comm's thing.

9:05

There's a whole bunch of different stuff going back and forth.

9:07

Um, but potentially the more interesting thing is did they take different technical approaches and get similar results? Yeah.

9:14

If they're neck and neck, um, which one will scale better, which one will generalize better?

9:18

There's a whole bunch of different dis discussions there.

9:21

Um, do you want to get into some of the the the controversy or the push back?

9:25

Do you have do you have a post pulled up from someone saying about about Google's attempt?

9:31

>> Yeah, I mean the the the whole thing came down to timing.

9:32

Um Dennis over at Deep Mind uh was was pushing back a little bit which I could pull up.

9:40

Um >> Dennis Hosis from Deep Mind the co-founder and now at Google.

9:44

Um, yeah, it was interesting because the we we immediately jumped to Poly Market because this whole idea of a an an AI system uh beating the IMO.

9:52

We talked about this with Scott Woo from Cognition months ago back in April.

9:59

I I found the clip and and he said I would be very surprised if an if an a AI system this year does not um does not actually surpass uh the IMO.

10:10

He of course is an IMO gold medalist himself and so uh it was it was a big it was big to hear from him.

10:18

Now the poly market had been sitting at like 20%.

10:19

And I think we're going to get into like the minutia of like what it means to truly win because the IMO uh like the the the group that actually puts on the competition has a different set of rules.

10:33

They don't they they put the questions out and anyone can go and try and do them.

10:37

But to actually be awarded a goal for an AI, they said it has to be an open-source model potentially.

10:42

It has to be released in this particular way.

10:45

And so, uh, OpenAI might have used their systems to solve the questions, which is super impressive, but they might not have checked every box to actually technically win the gold from the actual organization.

10:58

And so um uh Gnome says today >> Deus to be clear.

11:03

So so he put out a post this morning saying official results are in.

11:08

Gemini achieved gold medal level in the international mathematical >> which is different than actually getting a gold medal.

11:14

>> He said an advanced version was able to solve five out of six problems. Incredible progress.

11:20

>> And there's a quote in here from the IMO president.

11:22

and he says, "We can we can confirm that Google Deep Mind has reached the much desired milestone, earning 35 out of a possible 42 points. Yep. A gold medal scored.

11:30

Their solutions were astonishing in many respects." >> Yep.

11:34

>> IMO graders found them to be clear, precise, and most of them easy to follow.

11:37

You can imagine one is just like off on this insane.

11:41

>> There were some fascinating fascinating details around how they demared.

11:44

He said, "By the way, as an aside, we didn't announce on Friday because we respected the IMO board's original request that all AI labs share their results only after the official results had been verified by independent experts >> and the students had rightly received the acclamation they deserved."

12:00

And so, um, you can imagine somebody was saying I I don't know how real this was.

12:06

>> Somebody was saying that, >> uh, they they were making a claim that like Google needed time to like have the comms team to sign off, but it seemed, uh, more likely that, uh, the original plan was, hey, let's wait and announce this when when the IMO board >> actually comes out.

12:22

And >> the analogy feels like you're a super fast sprinter.

12:26

You go to the Olympics and you run a 100 meter dash that's incredibly fast in the parking lot.

12:31

Like you're not in the stadium, but everyone's like, "Wow, that guy's fast. >> He's hauling. >> He's hauling.

12:38

It's very impressive, but potentially the fastest man on earth."

12:43

>> And and ideally, you paid for the parking pass to get into the stadium.

12:49

And it it's like maybe Google and OpenAI were both running 100 meter dashes in the parking lot.

12:54

One of them had paid for like, you know, enough parking spaces to make it completely clean.

12:57

Open AAI was just kind of showing up with a buddy and being like, I'm sprinting.

13:04

That's that's the vibe I'm getting.

13:04

But they're both in the parking lot.

13:06

Like neither of them are in the actual stadium at this point.

13:09

But, you know, who knows? They they might be soon.

13:12

There's some questions about, you know, do they have to open source or whatever.

13:16

Um, >> so Gnome Brown says, uh, you know, we achieved a milestone that many considered years away. Gold level performance. Gold medal.

13:21

Of course, he's saying gold medal level performance like that's very critical.

13:25

It's not we got a gold medal is that we we exhibited gold medal gold medal level performance typically for these AI results like in go Dota poker diplomacy.

13:34

Researchers spend years making an AI that masters one narrow domain and does little else.

13:41

But this isn't an IMO specific model.

13:44

It's a reasoning LLM that incorporates new experimental generalpurpose techniques which would be very exciting because you could apply an IMO level.

13:51

John, hold up that stack of posts for the audience.

13:53

>> Oh, we got we got 150 post today.

13:53

It's going to be a quick stream people.

13:56

It's going to be a quick stream, but buckle up. Uh, so what's different?

14:00

We developed a new technique that makes LLMs a lot better at hard to verify tasks.

14:06

IMO problems were the perfect challenge for this.

14:08

Proofs are pages long and take experts hours to grade.

14:12

Compare that to aime where, which is another math exam, uh, where answers are simply an integer from 0 to 999.

14:17

So you can verify them really really quickly.

14:22

Uh also this model thinks for a long time 01 thought for seconds deep research for a minute.

14:26

This one thinks for hours importantly it's also more efficient with its thinking and there's a lot more room to push the test time compute and efficiency further.

14:33

Now what's interesting is like these I think these I think these questions go up and then you have like like I think the students get like two four and a half hour sections segments.

14:42

So there's like there's a there's a world where like the the AIs can do it but just not as fast as humans which would be very interesting.

14:51

I don't exactly know how how close they are.

14:53

Um so Gnome says where does this go?

14:55

As fast as recent AI progress has been I fully expect the trend to continue.

14:59

Importantly I think we're close to AI substantially contributing to scientific discovery.

15:04

There's a big difference between AI slightly be below top human performance versus slightly above.

15:08

This was a small team effort. He took >> right now.

15:12

The uh discovery that that AI is doing is talking with uh somebody who is potentially schizophrenic and convincing them that they've figured out uh how to move faster than the speed of light.

15:27

>> Yeah, there's there's so many accounts of that.

15:30

It's it's it's getting crazy.

15:32

Uh yeah, I posted uh Chad GPT agent, go win me an IM gold medal and then update my resume. >> Don't make mistakes.

15:39

But uh yeah, I mean, have you actually looked at any of the IMO questions ever? >> No.

15:45

>> I don't even know where to start.

15:45

Like it's it's all stuff that >> it's one call away for us though. We just text Scott.

15:52

>> Tyler, have you ever looked at IMO questions?

15:54

>> Uh no, but I'm looking at them right now. It's like pretty brutal.

15:57

>> Would you know where to >> Tyler?

15:58

If you can get two out of six right before the end of the stream, we'll buy you a house.

16:04

>> Well, that's the thing.

16:04

He's just going to be able to ask ChachiPot it. Yeah. >> Yeah.

16:08

Yeah, I had no Yeah, no tools. Got to qualify that.

16:11

>> Uh, so yeah, Nick has the has a comment about Deepmind.

16:13

De Mind has also >> Tyler has another challenge today.

16:17

>> We will introduce that in just a few minutes.

16:18

Uh, De Mind has also won IMO gold, but they haven't announced it yet, by the way. Confirmed. Congratulations, B.

16:24

>> They did this morning. >> Uh, they did.

16:25

Yeah, they confirmed it this morning.

16:27

>> And so, it's been interesting to see the reaction to this.

16:28

Uh Gary Marcus is on X saying, "All the tech bros this morning thinking that AGI has been achieved because some uh parenthesis insanely expensive new form of LLMs can now match top high school students on one specific task. It's almost cute."

16:45

So really just ripping into uh the entire AI community.

16:52

But Will Depw comes in and says uh he's on leave right now uh taking a little summer holiday. Yes.

16:57

He says, "Guys, stop using expensive as a disqualifier.

17:01

Capability per dollar will drop 100x a year.

17:05

The 3k task arc agi 80% could probably be $30 if we cared to optimize it." >> Repeat after me.

17:12

All that matters is topline intelligence.

17:14

All that matters is topline intelligence.

17:16

So yeah, again, everybody's focused on sort of raw capabilities, not super focused on uh efficiency, especially for uh projects like this where they're not necessarily, you know, rolling this out at in in mass. >> Yep.

17:32

And you know where a lot of these IMO gold medalists go to work? >> I do, John. >> RAMP. com. Time is money. Save both.

17:36

Easy to use corporate cards, bill, payments, accounting, and a whole lot more all in one place.

17:41

>> Uh ramp is >> amazing.

17:43

Um, so the timeline was in turmoil over the Gary Marcus post and and they went back and forth and he finally admitted it at the end.

17:49

He said he said that's impressive.

17:54

So it started with a post by Daniel Lit.

17:56

He says, "Huge congrats to OpenAI for their IMO gold.

17:58

I don't find it too surprising that an AI tool was able to achieve this. See below.

18:01

Though I'd sort of lost hope the last few days, but I'm but I'm pretty surprised it was an LRM with no tool use."

18:07

So it didn't have Python.

18:10

It didn't have web search.

18:10

it didn't have all the things that you're that you could imagine would kind of allow you to to you know speed things up or kind of be a shortcut that would put it in a different category.

18:19

There was always a question about with the uh when when when the AIs were playing video games like like computers have wall hacks like they can sometimes like see the see the map without the fog of war.

18:33

they can see like it's very different to get to get perfect pixel perfect data on where every character is on the map and be able to make decisions based on that as opposed to like looking at pixels and having to like move the screen over there to see if you're being invaded on the left flank, right?

18:49

And so there was always this like yes, if you gave a computer like the raw access that's not quite it's impressive, but it's not quite a level playing field.

18:58

And it's basically the same thing as being like, well, the other folks don't get a calculator and you get a calculator.

19:04

Like, is it that impressive?

19:04

But this was very much an even playing field, it seems like. So, Mel Gibson 2.

19:09

0, great great name says, "You are not surprised they that they you are not surprised that they have figured out a way to make the model learn in very hard to verify domains in a fuzzier reward space.

19:20

It also appears that the same reasoning model was the one used in the AT coder competition showing that it can generalize across domains.

19:28

Daniel comes back and says, "I don't think we really know that what they figured out yet.

19:33

I'll keep my powder dry until we know more."

19:34

Uh Mel Gibson says, "Go read Gnome Gnome Brown's thread on the model if you haven't already."

19:39

Um he says, and remember, Gnome Brown says, "This isn't an IMO specific model."

19:44

And that's a very important thing because um there's a ton of there's a ton of situations where you can go and RL on a specific task and it gets really really good at it, but then you try and get it to do anything else and it's not that great.

19:56

>> Uh and so Daniel says, "Yeah, I read it."

19:57

Gary Marcus says chimes in from the rafters because he's not in this chat yet, but he has entered the chat.

20:02

He says, "I read it, too. That's pretty vague.

20:05

Are we sure that no tools were called?"

20:08

Uh Gary Marcus then chimes in again says, "Reimo Gold.

20:11

says no tools mean no use of Python code interpreter etc.

20:16

Dan says Daniel Lit says that's how I understand it.

20:19

And then Gary Marcus tags in polomial gnome brown and also Alex weighing says can you confirm that the IMO gold was achieved without using Python or code interpreter or similar.

20:31

Uh and then Gary Marcus says humans don't use external tools in the IMO competition.

20:35

I'm just I'm just trying to understand what the system is.

20:37

That's how we do science.

20:39

Daniel Lit and at some point whoever was trying to dunk on Gary Marcus just deleted their account.

20:45

So it just says this post is from an account that no longer exists.

20:48

>> Uh Daniel Lit shows Cheryl on the OpenAI team saying the the model solves these problems without tools like lean which is a math verifier or coding.

20:55

It just uses natural language.

20:58

It also only has four and a half hours to answer our earlier question.

21:02

We see the model reason at a very high level trying out different strategies making observations from examples and testing hypothesis hypothesis.

21:10

And Gary Marcus says that's impressive.

21:14

So Gary Marcus, you got to fill out the the apology form, bro.

21:16

You got to fill out the deep reinforcement learning apology form.

21:20

What was the reason for your behavior?

21:22

No one told me Alex Wei was training the model.

21:26

>> Mercury was in retrograde. >> Mercury. I don't know. ML.

21:27

And then one of them is Gary Marcus con convinced me it was fake.

21:31

Uh because Gary Marcus was uh famously said deep learning is hitting a wall like like this this particular paradigm will not scale.

21:38

you have to do uh symbol manipulation which was like kind of his bet encode different relationships between ideas in the model.

21:47

Uh there were a bunch of different debates over there and he's gone back and forth on that.

21:50

He's he's he's not as much of like a deep re deep reinforcement learning hater as pe some people think but he's got he that's his brand at this point.

21:57

So anyway uh more on the drum between Deep Mind and OpenAI.

22:02

Deep Mind got a gold medal at the IMO on Friday afternoon, but they had to wait for marketing to approve the tweet until Monday.

22:07

Open AAI shared theirs first at 1 am on Saturday and stole the spotlight in this game.

22:11

Speed is greater than bureaucracy.

22:13

Miss the moment, lose the narrative.

22:16

So that's one interesting take. >> See exactly.

22:19

Yeah, I I think there's a little bit of that.

22:21

I mean certainly culturally open AI loves to release information before Google like whatever Google's like next big >> and they're playing to win.

22:31

Remember they after what did they release after the deepseek moment? >> Deep research.

22:35

>> Deep research. you're typing deep and you were looking for an AI product >> and then and then Google had IO and then and then open >> open AIO this like the day before >> with uh with Johnny I >> with Johnny IV um so anyway you know you'll love to see it all fair and love and war I guess um I I don't think this

22:56

crosses any >> warfare and this is the benefit of having a bunch of posters on your team I guess um no brand says it takes us a few months to return the experimental research frontier into a product but progress is so fast that a few months can mean a big difference in capabilities and this is from July 18th. So all the models

23:13

from July 18th. So all the models underperform humans on the new IMO questions and Grock 4 is especially bad on it even with best of end selection under >> somebody was accusing Gro 4 of training on the problem set >> for for IMO no for something else for oh for the other benchmarks I mean benchmark hacking is like a thing that

23:32

happens all over the place that's why we need like hidden benchmarks that's the whole thing of arc AGI that we will talk about we talked about Will Depw saying guys stop using expensive as a disqualifier uh Terrence Tao uh one of the one of the most goatated mathematicians of all time uh digs in a little bit and is >> is uh adding his perspective as a as a worldrenowned mathematician. He says it

23:55

He says it is tempting to view the capability of current AI technology as a singular quantity.

24:02

Either a given task X is within the ability of current tools or it is not.

24:06

However, there is a there is in fact a very widespread in capability several orders of magnitude depending on what resources and and assistance gives the tool and how one reports the results.

24:17

One can illustrate this with a human metaphor.

24:19

I will use the recently concluded IMO as an example.

24:21

Here the format is that each country fields a team of six human contestants who are high school students led by a team leader often a professional mathematician.

24:32

Over the course of two days, each contestant is given four and a half hours on each day to solve three difficult math problems given only pen and paper. Crazy.

24:45

Uh, no communication between contestants or with the team leader during this period is permitted.

24:49

Although the contestants can ask the in invigil invigators in I don't know for clarification.

24:55

This is like some math term I don't even know.

24:59

Uh for clarification on the wording of the problems, the team leader advocates for the students in front of the IMO jury during the >> are also known as exam proctors. >> Okay, proctors.

25:10

Okay, so yeah, they can ask the people that are running the test, hey, >> we got to start working invigilator and we should probably have a show like just an invigilator to >> for sure.

25:21

>> We should have at least one on staff.

25:21

So uh so so the team leader advocates for the uh for the students but is not involved in the IMO examination directly.

25:29

The IMO is widely regarded as highly se as a highly selective measure of mathematical achievement for a high school student to be able to score well enough to achieve a medal particularly a gold medal or a perfect score.

25:39

This year the threshold for gold was 35 out of 42 which corresponds to answering five of the six questions perfectly.

25:45

Even answering one question perfectly, >> basically a B, >> yeah, >> gets you gold. >> Yeah, it's that hard. >> They're that hard.

25:54

But consider what happens to the diffic to the difficulty of the Olympiad if we alter the format in various ways.

26:02

>> First, one gives the students several days to complete each question rather than four and a half hours for three scenarios.

26:07

To stretch the metaphor somewhat, consider a sci-fi scenario in in the student in which the student is still only given four and a half hours, but the team leader places the students in some sort of expensive and energyintensive time acceleration machine in which months or even years of time pass for the students during this exam before the exam.

26:25

>> Ben might have put us in one of these because we go live and then it's four hours later. >> Time acceleration. >> Yeah, it's wild.

26:33

Uh, two, uh, before the exam starts, the team leader rewrites the questions in a format the students find easier to work with.

26:39

Three, the team leader gives the students unlimited access to calculators, computer algebra packages, formal proof assistance, textbooks, or the ability to search the internet.

26:48

Sounds like that didn't happen.

26:50

Uh, the team leader has the six student team work on the same problem simultaneously, communicating with each other on their partial progress and reported dead ends.

26:57

The team leader gives the students prompts in the direction of favorable approaches and intervenes if one of the students is spending too much time on a direction they know to be unlikely to succeed.

27:05

Um, next, each of the six students on the team submits solutions, but the team leader selects only the best solution to submit to the competition regard discarding the rest.

27:16

Uh last, if none of the students on the team obtain a satisfactory solution, the team leader does not submit any solution at all and silently withdraws from the competition without their participation ever being noted.

27:27

Oh, so that I mean that could have happened.

27:29

It didn't in this case, but uh in each of these formats, the submitted solutions are still technically generated by the high school contestants.

27:35

The going back to the parking lot example, it's like if you can go run go run the race in the parking lot and then uh if you don't run as fast as you hoped, it's like well I wasn't in the I mean >> I wasn't racing.

27:48

I was just going for jog.

27:51

>> I was just warming up.

27:51

I just I like to be surrounded by excellence. >> Yeah, don't worry.

27:54

Yeah, I mean that is the true one because if they'd missed they'd probably be like what what the IMO is this weekend? We're working on agents.

28:03

Like what are you talking about?

28:05

like have you seen our DIUS? Like get out of here.

28:07

Um to each of these formats, the submitted solutions are still technically generated by the high school stu contestants rather than the team leader.

28:15

However, the reported success rate of the students in the competition can be dramatically affected by such changes in format.

28:19

A student or team of students who might not even reach bronze medal performance um in the normal competition under standard test conditions might instead reach gold medal performance under some of the modified formats indicated above.

28:30

So in the absence of controlled test methodology that was not self- selected by the competing teams, one should be wary of making various applesto apples comparisons between the performance of various AI models on competitions such as the IMO or between such models and the human contestants.

28:45

Yeah, the question is like it seems like of those not many were actually violated by the way OpenAI and Google attacked this.

28:53

>> Well, this was before I mean this this was an immediate reaction before I think there was >> more details came out of details. Yeah.

29:01

That we've been covering.

29:01

This was 3 pm on on so this so on Saturday but 3 pm later.

29:07

>> Well, Run has a good post.

29:07

He says, "My bar for AGI is an AI that can learn to run a gas station for a year without a team of scientists collecting the gas station data set." >> It's a great post.

29:20

>> The world isn't ready for gas station.

29:22

>> We can we can run an AI as long as we can we can run a gas station as long as we have, you know, a perfect, you know, data set.

29:28

And that's yeah that's like the way >> on how gas stations operate. >> Yeah.

29:33

As soon as we as soon as we uh place the goals somewhere we nail that goal and then we have to move the goalpost shows.

29:40

Uh >> this is this is a great picture.

29:42

So Thomas Wolf says my bar for AGI is an AI winning a Nobel Prize for a new theory.

29:49

It originated just image of a team moving the goalpost.

29:54

>> I do like how consistent Tyler Cowan is on AGI.

29:56

is like my bar was the touring test.

30:00

We passed that so I'm I have to call it like it is. >> Yeah.

30:04

>> And I'm not moving the goal.

30:05

>> I think I think he's very smart for that in the fullness of time.

30:10

>> I mean I I think it's okay to be like yeah we achieved AGI.

30:13

>> It's just tough when you now there's something new.

30:15

>> It's cool but not immediately >> dramatically transformative.

30:18

>> dramatically transformative. But you have to imagine that that was the same that there was the same thing when people were like human human flight and then the Wright brothers go and do it and people are like great so like I can hop on a Southwest flight in an hour to go to San Francisco from LA and they're

30:33

like what are you talking about like LA is like you know a couple trains and like some people you know with orange groves and it's like it takes a long time for the infrastructure to get built out like now a lot of these AI tools they do build on top of the internet and on top of technology that we have rolled out. But like at a certain point like

30:50

But like at a certain point like the UI matters, the economics of these different tools matters.

30:55

You like you can't it might not be economical for a for a company to to you know release a an AI tool that costs $20,000 to inference just to get you the weather or do two plus two.

31:10

And so um all of these things take time to roll out and that's why we're kind of in this like slow takeoff scenario.

31:15

It feels like I don't know.

31:17

Uh we're gonna go to GPT agent in a little bit and talk about that.

31:20

But um there was some interesting uh there was some interesting details from Jasper about uh the IMO problem one. So these are on GitHub.

31:30

So you can actually just go read them. Uh the math checks out.

31:31

It nailed the key lema for n greater than three.

31:36

Any but you know you can kind of read them uh these things.

31:39

But uh the the writeup is kind of messy.

31:42

It uses shorthand and sentence fragments.

31:44

It it it introduces new terms without definitions, forbidden and sunny partners, uh lists and and it does a bunch of different interesting things where it's trying to it's trying to condense down the number of tokens.

31:57

So if it's if it wants to say like divide this number by three, normally by space three would be two tokens, but by three is one token.

32:09

And so it's like compressing it down.

32:10

It's kind of like learning its own language or developing its own language just to be a little bit more efficient. >> Uh very interesting.

32:18

>> Um >> uh Deja Vu Coder says, "You're laughing.

32:24

Open AAI and Google Deep Minds unreleased models just gave an IMO gold medal performance without internet access." And you're laughing. People love it.

32:32

It >> is interesting that XAI didn't get involved in this one.

32:35

You have to imagine they knew >> both uh Deep Mind >> and OpenAI were going to be competing. >> Yeah.

32:45

I mean it feels like it's this is the nature of like the value of research.

32:49

It's like a new research domain or new research path like XAI is dominated in the pre-training build the big supercluster get all the GPUs do the massive pre-training.

32:59

Then now with Gro 4, they're doing equal spend on RL generally, but DeepMind and OpenAI seem to have like the next next thing already cooking.

33:10

And we just don't know the phrase for it yet because >> in order to learn that phrase, you got to pay $100 million for some researcher to come tell you basically. Yeah.

33:20

>> Like like I'm sure that there is a there is a new paradigm, a new strategy to unlock this level of performance.

33:24

And it's something with >> it's probably not 100 million.

33:27

It's some combination of a bunch of people that that >> totally collectively cost about >> but eventually I mean we were seeing this with the with the behemoth analysis from the semi analysis and and and what Jeremy was diving into where like even just when you do when you train a really big model how you chunk up the memory how you chunk the attention like that has a dramatic impact on the actual end state and the model performance.

33:54

And so it seems like Google and OpenAI have been able to like hammer out a bunch of those problems to get a really great result and they're not going to tell anyone anytime soon, I imagine.

34:05

Um, Sebastian has a good post here.

34:07

He says, uh, it's hard to overstate the significance of this.

34:11

It may end up looking like a moonlanding moment for AI.

34:14

Just to spell it out as clearly as possible, a next word prediction machine because that's really what it is here. No tools, no nothing.

34:21

just produced genuinely creative proofs for hard novel math problems at a level reached by only an elite handful of pre preol prodigies. Pretty sick.

34:33

>> It is funny explaining it to uh somebody just on the street. >> Yeah.

34:37

>> A a computer beat some high school students at math.

34:43

They would just they would tell you, "Okay, >> cool." Yeah. Okay. >> Cool. >> Yeah. Cool story.

34:48

>> And then when you phrase it like this, >> Yeah.

34:50

It's like, okay, >> but it's like, yeah, >> landing moment, >> but yeah.

34:53

Yeah, but like the the high school IMO folks are still in the 99.

34:59

9999th percentile for just everyone.

35:00

Like they happen to be age there happens to be an age cut off, but it is essentially arbitrary since most people cannot do these this level of math.

35:08

Um, well, let me tell you about graphite.

35:10

dev code review for the age of AI.

35:12

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35:17

you can get started for free.

35:19

Um, Francois Chole says, "Intelligence >> isn't a collection of skills.

35:24

It's the effic efficiency with which you acquire and deploy new skills.

35:28

It's an efficiency ratio."

35:30

And that's why benchmark scores can be very misleading about the actual intelligence of AI systems.

35:37

>> And Elon's there saying, "Good perspective."

35:38

And so yeah, um we don't need to move the goalposts, but we kind of it's still interesting to because we achieved this particular benchmark.

35:49

Now what have you done for me lately basically and so I I think people really will move the goalpost and and and you can kind of knock it, but at the same time it was interesting timing that last week ARC AGI v3 dropped.

36:01

these models are not doing well on that and they're simultaneously doing well on something that is so hard.

36:09

You show it to most people and they don't even know where to start with the math problem and it's completely um it's completely ridiculous to to to try and even take a shot at.

36:18

So we wanted to give Arc AGI V3 a an attempt. Are you ready Tyler? >> Yeah, I'm ready.

36:26

I haven't looked at it at all. >> Okay. So So yeah. Yeah.

36:28

How familiar are you with ArcGI generally?

36:33

>> Yeah, I mean I So I played with like the version one like last summer I was trying to like there's the prize, you know, I tried it out for a couple weeks.

36:40

>> Did you try it out as a human or did you try writing software for it or >> Yeah, like trying to like write software for it. >> Okay. Yeah. What was your approach? >> Uh I don't know.

36:47

There's a bunch of stuff.

36:48

There was like >> was that was like just static images, right?

36:52

So then there was like ways you could like tokenize it to try to do like normal LM. Yep.

36:55

And then I think I was trying some like random image processing.

37:00

>> Did you get any of them right or was it like a straight up zero?

37:04

>> Yeah, it was like pretty bad.

37:05

>> Well, uh the the initial arc agi v1 v2 v1 was pretty solidly solved by uh 03 high, I believe, or 01 high.

37:16

>> I think 01 was the one that solved that >> 01 and it was like $2,000 a task and they got to something like 60 70%.

37:20

Still not where an average human is for these puzzles. Um, but impressive.

37:24

Then Gro 4 came out and on ARC AGI V2, they pumped the score from like what 6% to 15% or something.

37:36

They they doubled it, but still not great.

37:37

But now Arc AGI V3 came out and it's more of a game.

37:40

So I played it on stream on Thursday, I believe, maybe Friday. Mike, I did pretty well.

37:48

Um, I have some I actually have some times from >> You did well, especially considering you you had like a minute to look at it prior to joining the show and I really was pretty fresh.

37:59

>> Yeah, you you basically tried it for a second.

38:02

You were like, "This is really hard." Yes.

38:03

And and then had to stop. >> Okay.

38:06

So, uh, you want to put it in hard mode, right?

38:08

So, I I got I got times from Mike on how humans have done on on Arc AGI V3.

38:15

So, you have to finish the whole thing.

38:18

Uh, and and the uh he says if he only gets one shot to speedrun all three games with unlimited try agains, I'd say 15 total minutes is hard, 20 minutes is medium, and 25 minutes is easy average.

38:35

So, you want you want him to do it in 15 minutes? >> Under 15. >> Under 15.

38:39

And what does he what does he win? >> A new iPhone. bricked.

38:41

We bricked your iPhone when we made you sign up for Google Glass.

38:46

And so this is an opportunity to make it all back in one. >> This is high stakes.

38:50

So So make sure you have it set up. >> Okay.

38:52

>> And you should pull up the instructions and read the instructions and we'll start a timer when you uh It's 11:36 right now.

39:01

Uh >> is there Wait, so there's no like hard mode, easy mode. That's >> No, no, no.

39:05

So So everyone does the same thing whether you're an AI or a human.

39:10

You will see some instructions. There's some keys.

39:12

It's more like a game than than filling out the puzzles.

39:14

Um, and uh and and the actual instructions, there are really no instructions.

39:19

You it's your job to figure out the nature of the game, figure out how it works, and then go and speedrun it. >> Okay.

39:28

>> Um, so, so, so pull it up and I will read this this post.

39:30

Uh, so Ludwig Yeet Ginstein says, uh, 20 years ago, this type of person would become an elite math professor.

39:39

Now, they're making AI breakthroughs.

39:40

breakthroughs. This is progress probably and it's uh the the CV of Alexander we the research scientist over at OpenAI he's a member of the technical staff and before he has a PhD in computer science from UC Berkeley he was at Harvard uh studying computer science Philips exit

39:55

totally tracked research inter in intern at Meta Microsoft deeshaw Google what a stacked resume this guy's a killer um and now he he was on the IMO team that did that and so um we talked about the the plot twist um and and the battle between open AI and deep mind. I'm sure both of them

40:13

I'm sure both of them will be talking about this.

40:14

I'm more interested in the underlying technology and and what actually happened and what was discovered than than who released it earlier.

40:23

That that doesn't matter as much to me.

40:25

And uh and again, Gnome says, um, hey, like we posted after the closing ceremony, it was live streamed, so this is easy to confirm.

40:32

We weren't in touch with IMO.

40:34

I spoke with one organizer before the post to let him know.

40:38

He requested we wait until after the closing ceremony ends to respect the kids and we did.

40:43

And so it seems like this is pretty verifiable that they didn't do anything uh anything bad to the IMO kids.

40:50

They might have they might have roasted Google, but that's just on, you know, Google's got start posting at 1:00 a. m.

40:57

Uh so Tyler, give me the update.

40:59

Do you have it pulled up? How >> pulled up?

41:01

I think I'm ready to start. >> Okay. Uh production team. >> Yeah, I got a timer. >> You got a timer? Okay.

41:05

So, so I want you to count up because we want to get the total amount of time.

41:09

We're aiming for under 15 minutes for all three puzzles. That's hard.

41:13

Uh 20 minutes would be normal. 25 is like easy mode.

41:17

Apparently, this is according to Mike.

41:19

So, I I haven't actually tried to speedrun in this time.

41:21

I spent a couple minutes.

41:23

>> Did you play all three games or just one of them? >> I played one of them.

41:26

>> Didn't you get through two?

41:27

>> Well, there's there's levels to this. There's levels.

41:32

Uh you'll figure all this out.

41:33

>> And Tyler, you you Wait.

41:33

So, I I'd say I'd say you get unlimited lives in the game. >> Yeah. Yeah.

41:40

You You can reset and do whatever, >> but you can spend the whole show trying to do all three games in 15 minutes if you want.

41:47

>> Oh, well, no, no, no, no.

41:47

It doesn't work like that because once you know the tricks, like you'll be able to blast through. Yeah, for sure. For sure.

41:53

Um, so, uh, let let's go for 15. Good luck. New iPhone on the line.

41:59

Uh, if not, >> this really is the we'll come up to say this really is the iPhone moment for >> AR benchmark.

42:05

Yes, this is the iPhone moment for ArcGI. Good luck to you, Tyler. Let's start. >> Okay.

42:11

Uh, five, four, three, two, one, go, Tyler.

42:18

>> Okay, we will let him work on that and we will check in. >> All right.

42:20

Should we talk about uh chat GPT agents? >> Yes. Yes. Yes.

42:24

Um, so there's a bunch of other before we get into that.

42:29

>> Let's tell you about Figma.

42:29

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42:30

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42:33

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42:34

What did you want to say?

42:36

>> I wanted to say the uh some big news that hit the timeline this morning.

42:40

Poly market has acquired uh QC for $112 million and that is going to allow them to enter the US market.

42:50

Uh as you may know uh to date you haven't been able to use Poly Market if you're in the US.

42:58

We use it as a data source.

42:58

Uh so you can go on the website obviously like we do uh you can see it on the ticker >> but this is going to allow them to actually launch in the US.

43:07

So uh Shane has been absolutely cooking and I think he's going to come on the show soon now that he's not under DOJ investigation.

43:16

>> What a wild what a wild founder story arc.

43:18

So, and like Yeah, remember those old photos of him like coding in a closet and stuff like >> in his bathroom. In his bathroom.

43:27

>> He built Poly Market in a in a in a studio apartment bathroom with scraps. >> I love it.

43:32

Uh anyways, Vanta automate compliance, manage risk, improve trust continuously.

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43:48

Uh so OpenAI has been doing a lot of stuff like it's it's it's it's they're kind of on a run.

43:52

So uh IMO gold medal happens over the weekend.

43:55

Um the chat agent which will which I tested finally.

44:01

So I'll have a little review and some analysis of that.

44:02

But also apparently they are testing a new model on the webdev arena on LM arena under the name anonymous chatbot0717.

44:13

So, this is a secret project from OpenAI that they are maybe putting out in the in the test realm and then people discovered it and they're digging into it.

44:22

And so, uh I can't believe I'm going to say this, but it's genuinely at a completely different level of front-end coding.

44:28

Far better than Sonnet 03, Gemini 2.

44:30

5 Pro, or Grock, which is saying a lot because people love those models for coding, especially on the front end.

44:35

So to test it, I ran a a great prompt borrowed from the amazing feature crew pod YouTube channel asking models to create a procedurally generated planet with 3JS. Take a look at yourself.

44:45

I'm pretty astonished by how big the jump is.

44:47

I have featured the new model twice because its implications have been so interesting.

44:51

Of course, this is only one test, but OpenAI models have always been a bit meh on front-end work and they seem to have finally overtaken everyone else.

44:57

So, this apparent alleged unreleased OpenAI model uh is building this procedural world and it generates this really cool 3JS like basically a video game in uh and it sounds like it kind of oneshots it.

45:09

So, exciting stuff from that.

45:11

Um there is uh uh so the agent stuff.

45:16

So, uh Swix says uh please stop making flight booking agent demos with faint but dying hope the undersigned.

45:23

the undersigned. And so everyone is saying uh he's saying please stop making fetch please stop trying to make fetch happen flight booking instacort or Instacart orders astroturfing Reddit uh he wants killer use cases to be coding agents support agents and deep research

45:39

up and coming is screen sharing outbound sales hiring education personal AI and finance and uh I have to I think we're somewhat responsible because for months we were just like just book a flight like this is the killer demo this is the killer use case and then everyone was like played out. We did stop asking that

45:53

We did stop asking that question.

45:55

>> We did stop asking him, but we were asking, >> but at the beginning of the year, we were very curious. >> Yeah. Yeah. Yeah.

45:58

And so, um, Sam Alman had a post last week.

46:01

He said, "Today we launched."

46:03

>> Can you give some background for people that may just be Sam Alman crawling out from under a rock? >> Yeah.

46:08

So, he started a company.

46:08

He was the president of Y Combinator.

46:11

He started a company called Looped, Sold it Stripe. >> Yeah. Yeah.

46:16

That's what people know him from.

46:17

Uh, Koix owner, McLaren F1 owner.

46:20

That's how that's where people probably know him from.

46:21

Um but uh uh he says uh today we launched a new product called ChachiPT agent.

46:27

Agent represents a new cap new level of capability for AI systems and can accomplish some remarkable complex tasks for you using its own computer.

46:35

It combines the spirit of deep research and operator but is more powerful than it may sound.

46:40

It can think for a long time, use some tools, think some more, take some actions, think some more, etc.

46:44

We ex uh for example, we showed a demo in our launch of it preparing for a friend's wedding, buying an outfit, booking travel, choosing a gift, etc.

46:51

We also showed an example of analyzing data to create a presentation for work.

46:56

Although the utility is significant, so are the potential risks.

46:59

We built a lot of safeguards and warnings into it and broader mitigations than we've ever developed before and from robust training to system safeguards to user controls.

47:08

But we can't anticipate everything.

47:09

in the spirit of iterative development, we are going to warn users heavily and it gives users freedom to take actions carefully if they want to.

47:17

And so, um, very, very interesting post.

47:19

He goes through a bunch more stuff, but I actually tested it out this weekend.

47:23

So, >> um, as you know, we have a studio, the TBPN Ultradome, here in Hollywood.

47:27

We're always thinking about what's next, always looking at what else is on the market.

47:32

And when we were first looking for the TBPN Ultradome, I went to ChachiPT operator and I said, "Hey, I'm looking for a studio.

47:39

It needs to be a sound stage, which means ped padded walls. I want concrete floors.

47:43

I want it to be, you know, at least 40 feet by 40 feet.

47:48

I need one gigabyte internet access there. I need power AC.

47:51

It can't just be a, you know, heavy industrial space where there's going to be somebody next door, Hadrien making CNC stuff that's rattling me.

48:01

Um, I need a bunch of things.

48:04

Go and figure it out operator.

48:05

And it went around and it looked at loopnet, but it kind of got stuck on on captas and it wasn't doing a great job.

48:12

And I kind of I felt like I had to be like there watching it and it was really only working on desktop for me at the time.

48:17

But I reran the uh the same basically the same query asking it to look for uh studio space in LA with all these different uh metrics that I wanted, all these different uh parameters that I wanted to make sure it verified.

48:31

And it found a place that was like not listed on any sort of like rental sites.

48:36

It found just a website that was out there for some crew that runs like two studios, one in Hollywood, one in Vanise, and and gave me the full breakdown.

48:45

I was able to go to the website, but then of course like I'd have to call and I called and they only are available between 9:00 and 5.

48:53

>> Well, this is this is what I what I was asking the the agent team.

48:55

I think it was on Thursday that we had them on which was uh >> what have you done for me lately?

49:02

>> Well, well, basically adding a voice feature just to like call them now call them to confirm that it's actually available and let me know, find out when I can go see it, right?

49:10

that is a very a much easier step to add in many ways than like the browser use functionality >> and also like the uh just just the asynchronousness of it like I I fired off this query I don't know like like after like I don't know 6:00 p. m.

49:25

on a Saturday like it's it needs to wait until 9:00 a. m.

49:29

on Monday when they open to pick up the phone.

49:31

When we started this section, I put in an agent request said, "Find me a GT3 RS with under a,000 miles for under 400K that's currently for sale in Los Angeles County."

49:40

And so it's doing I'm watching it cook and it's doing like an hour plus of work already in like five minutes. >> Yeah.

49:51

No, no, you know, it is remarkable.

49:53

So, it can it can really work through different different sites and features. >> I can see it.

49:57

It found one >> for in LA County. Yep.

50:02

>> With,300 miles under 400k.

50:02

And I just watched it say this one will disqualify this one because it's >> over that limit. >> Yeah.

50:11

>> And so it needs to be able to think about time and it needs to think, okay, when is the certain time to do this?

50:18

I need to come back to this in two days or something like basically set a cron job, set a set an alert, come back to things.

50:25

It needs to use linear, a purpose-built tool for planning and building products.

50:28

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50:33

>> OpenAI runs on linear.

50:33

Linear supports agents >> and they actually have an integration >> which I am excited about.

50:39

Um, but I mean jokes aside, uh, Swix was saying this is a new frontier model and I think that a lot of people get hung up in oh they there's a new branding around it agents.

50:51

What like I was talking to our buddy David Center about this and he was like what what are you using it for?

50:54

Like what are your prompts?

50:55

And I was like, it's the same prompt.

50:57

The thing that I would send to Deep Research, I send to agents now. It's just better.

51:01

And I and I and I do understand that like it might unlock some new use cases, but I think the basic thing that you should start with if you're looking to experiment and kind of road test chatgbt agent for yourself is just take something that you would put in deep research, throw it in agent, and see how you like it and if it's better.

51:22

And I noticed that it's a lot better in many ways.

51:25

It gives you a MD file at the end.

51:26

Basically, it gives you a document like a report that look renders the exact same as a deep research report, but you can kind of scroll it differently.

51:34

Um, it can still do all the tables and stuff.

51:37

The links oddly weren't working.

51:39

Like I I would click on it and it wouldn't it wouldn't open.

51:42

So, there's like still some bugs and some rough around the edges stuff, but in general, I think it did a lot.

51:45

but in general, I think it did a lot. I just think of it as like like deep research is kind of it feels like deep research is a little bit bound by you know the first level of depth on the internet and agents can actually go you

52:00

know okay there's there's there's a website out here that has something but I need to go to the archive I need to log in I need to like find a different route I need to you work around it figure out all these different things

52:10

let's put let's actually fact check some stuff building a table over here oh okay I got some conflicting information let me try and resolve that all the natural things that actually research and so I think it's fine if it's just a research >> the thing that uh agent is doing here is

52:29

it's going it's navigating to a site and then it's using the site's internal search mechanism >> to find what it's looking for versus just like scanning like databases or just scanning pages and pulling out information. >> So it's actually taking that next order

52:42

>> So it's actually taking that next order >> Yeah.

52:45

>> Yeah. uh >> yeah actually using the website and I still think like I I don't see this as really replacing anyone in my life at least or my business but I see it I see it very much as like as like in between me and the folks on my team I will go

53:03

fire off a prompt and try and like really do as much of the research and kind of pre-work and then hand that off and come with to somebody who works for me with just a more educated idea of like, okay, I think we need this. I have

53:17

I have I've already kicked this off and I think it's possible.

53:22

I need you to go and negotiate and I need you to go do all the soft skills and I need you to actually execute this and take the last mile.

53:29

That's like the human side of this, but you already have all the information to basically do like the job is well defined.

53:35

And so um I I think that my next my next my next change to the way I use chatbt deep research agents will be by the end of this give me a list of steps to actually execute this that need to be executed by a human.

53:51

human. So with that GTRS it's like GT3 RS if they find one it's like find me the phone number of a few and then when should I call them what what other data sources do I need to point to what are the other considerations so I basically have like a script to go and actually

54:06

get the deal done for example um so anyway very exciting stuff almost as exciting as numeral sales tax on autopilot spend less than five minutes per month on sales tax compliance go to numeral hq to get started um >> so should we talk about Stephen Cobear. >> We should we should talk about Steven

54:22

>> We should we should talk about Steven Cobear.

54:24

This was a fan this was a fascinating story that happened the uh late night is ending.

54:30

So Steven Cobear, you might know him from the Cob Bear Report on he was originally on the Daily Show.

54:36

Then he had his own show on on Comedy Central.

54:38

Uh I believe it was a half an hour, maybe an hour every night on Comedy Central.

54:44

Then he got pulled over into CBS with Late Night, which was originally designed to compete with the Tonight Show, which was Johnny Carson's property that he ran for 30 years, 1962 to 1992.

54:59

Absolutely legendary run.

54:59

Uh Jay Leno took that show over, gave it to Conan for a year, went back, very controversial, late night wars, very fun deep dive to dig into.

55:09

Uh, but Emily Jashinsky uh has a story in Pirate Wires all about uh late night.

55:16

I have some I have some facts here that were sticking out to me.

55:20

So, the the the high level is that um the Late Show, Steven Cobear's daily late night TV show.

55:27

Um >> how many days a week is it?

55:30

Is it >> It's five days a week.

55:31

They do 190 episodes per year.

55:36

So they take a few weeks off in between little breaks. >> Pretty casual. >> Yes, pretty casual.

55:42

We do I mean we are on track to produce four times as much content this year.

55:47

Um but they spend $und00 million to produce five times as much. >> Yeah. Yeah. Yeah.

55:53

You keep pulling those daily GT3 RS's.

55:56

I mean they were they were spending How much is the GT3S? 400K.

56:01

they could have bought a GT3 RS for every single episode because they were spending $und00 million to produce 190 hourong episodes uh every year.

56:08

And so this wasn't a problem because back in 2009 they were pulling in $271 million in revenue.

56:20

>> So I mean and I'm sure that they were actually spending less back in 2009.

56:21

So the margin on that show was immense like 60% 70% maybe even higher.

56:27

Um the problem is is that uh the revenue started declining because the audience got older and ad dollars moved around.

56:38

>> The average viewer >> the median viewer of the Late Show with Steven Cobear is over 59 years old.

56:43

So So it is it is effectively like a retired audience.

56:49

So they're not as likely to buy expensive products.

56:52

And if they buy those products, they might not stay with them forever because they might churn because they might pass away.

57:00

And so >> lower LTV, >> lower LTV.

57:03

Um, and then also it's a very broad audience.

57:05

It's a very political audience.

57:07

It's very general comedy, politics, daily news audience. Uh, very broad.

57:12

So you can only sell broad things.

57:14

And that's why you see, you know, Unilever like, you know, you you're watching an ad and you you see you're watching the late show and then Yeah. Yeah. Verizon.

57:21

And then you see Dove shampoo or something like you just see generic products not hyper specific like Adio which is customer relationship magic.

57:30

Adio is the AR native CRM that builds scales and grow grows your company to the next level.

57:35

>> You can get started for free.

57:35

You're not going to see that on the late show. Yeah. >> Um >> you just won't. >> You just won't.

57:39

Um and so uh revenue kept falling.

57:43

Now they make less than 70 million.

57:45

Reports were maybe like 60 million in revenue.

57:47

Now Colbear is taking 15 home.

57:49

15 million a year home personally.

57:52

And then the rest of the show costs 85 million to produce.

57:54

About 50 million of that is probably salaries.

57:58

There's a bunch of other costs that go into it. They have a live band. They fly people around.

58:01

They have hair and makeup and and all sorts of they have to license music and they do all sorts of stuff.

58:07

So, um, so then they went from at one point making, you know, $200 million in profit off this a year, amazing, to losing 40 million.

58:17

And importantly, CBS is going through an acquisition.

58:21

And so, there's a whole bunch of problems where you don't necessarily want to have this massive loss asset sitting there while you're trying to sell the pro, sell the company, and restructure everything.

58:31

And then, so there's a little bit of conspiracy.

58:34

Um, and Keith Oberman was saying he put on the tinfoil hat and was saying like this is all because Trump is like Coar criticized Trump.

58:41

And this is a straw man hat.

58:45

>> I'm gonna get out the straw man.

58:46

>> Yeah, we're not making this argument.

58:48

This is this is No one's really making this argument except for put on the straw hat.

58:52

I like the straw hat, >> by the way. New straw. >> This is a funny hat.

58:56

>> I don't even know what kind of hat this is.

58:58

>> A straw some sort of straw hat.

58:59

>> I got to sit lower so that it'll fit in. >> Yeah.

59:01

Anyway, um >> but yeah, the the I mean the the obvious thing here is that uh Steven Colbear, Steven Colbear, yeah, >> whoever that is, was a zero interest rate phenomena. You have a business.

59:14

>> He's in the business for 30 years. >> I mean, great. Yeah.

59:16

Who wants to uh who wants to be the proud owner of a business that loses $40 million a year like clockwork? >> Yeah.

59:24

So, it was a loss leader for CBS.

59:27

Basically during upfronts when they're selling ads to everyone, they go to Target and they say, "Hey, how about we put you with Steven Cobear?"

59:32

And they're like, "Sure."

59:34

But then we also want to be on the game shows and then the game shows make higher margins and they lose money on the on the late show, but a company like Target wouldn't want to advertise on the game show unless they can also be with with Cobar and the prestige TV that's happening there.

59:47

So basically, they're losing $40 million.

59:52

What's interesting is that you would think that they would be able to cut back the cost and say, "Hey, look, we're making half we're making half as much revenue.

1:00:00

We need to produce this for half as much money."

1:00:02

And so, Co Bear, you got to take a haircut.

1:00:05

Folks, you got to take a haircut.

1:00:08

>> 50 people >> instead of 100. And 200? >> Yeah. Was it 200 people? 200 people. >> 200 people. Okay. Yeah. 200 people.

1:00:13

So, >> and and apparently, so so we were messaging some people over the weekend, uh, some some media moguls, >> and they were saying, I mean, it's it's very routine for there to be two people tasked like effectively their full-time job is like moving one camera. >> Yeah. Yeah.

1:00:34

uh and and and so effectively is just a culture of inefficiency that has bunch of different reasons why why that is but um doesn't really work in the modern era.

1:00:44

So the interesting thing here yeah >> is uh I I was trying to figure out kind of what happens from here.

1:00:50

So CBS is confirmed they're not doing a replacement host.

1:00:54

They're not going to um they're not going to hire like an H-1B uh uh Steven.

1:00:58

I >> think they're I think they're I think they're going to put a talk show in there. >> Yeah.

1:01:05

So anyways, it's going away.

1:01:07

There's no indication that ABC, NBC, Netflix, Max or any >> any of those platforms is like going to try to launch one of these Johnny Carson style shows.

1:01:16

Uh, but I think the right move for uh Steven Colbear >> is it's not my uh not my flavor of uh comedy entertainment, but I think he could have uh I think if he went independent and effectively launched >> live show, podcast, something of that sort, he could continue to earn exactly what he's earning today. >> Yeah.

1:01:41

>> Um and uh just do it with a much smaller team.

1:01:44

Maybe even have a better lifestyle.

1:01:46

Maybe he starts doing the show in the morning. >> Yeah.

1:01:49

I mean, there was $60 million of like we want to advertise on Steven Coar like flowing into this property. Yeah.

1:01:57

>> If he provides a similar level of experience and content, he should be able to sell similar levels of ads. Yeah.

1:02:03

>> Maybe not 60, but maybe 30.

1:02:03

And then he takes home 15 and he has 15 to spend on, you know, a smaller team.

1:02:08

And what's crazy is like during the COVID era, all of the late night shows went to like from home episodes where they were basically doing them over Zoom and then they set up like nicer camera setups and they were able to do those shows way cheaper.

1:02:21

But I think because of the union it wasn't it wasn't it wasn't palatable or really like easy to just um to just cut back on staff and cut back on salaries or switch to some sort of more incentive pay which is tricky.

1:02:33

We just talked to Delian about this where in France there was a company that um that wanted to like their business wasn't doing so well.

1:02:40

They wanted to lay off folks >> too many people >> and they couldn't do it and so the the government basically said shut down.

1:02:46

>> In in France there's policies that effectively require companies to pay years of severance.

1:02:51

So it ends up becoming >> a massive liability on the balance sheet. >> Yeah.

1:02:57

>> And uh anyways >> Yeah.

1:02:59

So, uh, Emily Jasins Jasinski over at Pirate Wires says, uh, CBS is not just pushing out Steven Coar, it's retiring the iconic Late Show brand altogether.

1:03:09

That's the buried lead getting lost amidst frenzied speculation over politics and palace intrigue.

1:03:14

If co if cutting Colar is a bid to juice Paramount's pending merger or to punish him for criticizing it as Democrats are now arguing because Colbear said that CBS as a company should not have or Paramount should not have settled a lawsuit with Trump.

1:03:28

I believe CBS just stumbled right into the future.

1:03:30

Emily says uh she says Colbear's time at the helm of the Late Show perfectly illustrates the most important trend in media and culture.

1:03:38

One might fairly wonder how Coar, a man so who leaned so far into hashtagresistance comedy he could far hardly get up, has dominated the late night wars throughout Donald Trump's hostile takeover of American politics.

1:03:50

Johnny Carson, for example, famously skewered both political parties without fear fear or favor.

1:03:54

Carson won the late night wars when networks faced less competition, meaning his goal was to appeal to as wide a swath of the American public as possible for the sake of selling more ads.

1:04:05

By the time Cobar took the helm from David Letterman, late night ratings had collapsed from their high watermark.

1:04:10

That's particularly why Greg Gutfeld is able to actually beat Colbear's ratings on a cable network, a feat that would have been unthinkable in the 1990s.

1:04:19

Like Colar though, Gutfeld doesn't approach politics as Carson did. This is the new model.

1:04:24

Cultivate a loyal niche that returns night after night, giving you an edge over others competing for an increasingly smaller slices of the pie.

1:04:31

The result is a microculture.

1:04:34

Monocultural institutions like the Late Show or the New York Times can no longer and can and and no longer do appeal more widely to than their core audiences.

1:04:40

For the Times, this is their subscriber base.

1:04:45

And it's why, for instance, the paper committed obvious journalistic malpractice by yanking Senator Tom Cotton's infamous send in the troops oped back in 2020.

1:04:53

As the paper of record for all of America, that decision made no sense.

1:04:57

Cotton was expressing a mainstream position in his party and in the country, but Times subscribers were furious and that critical business interest shifted the outlet's editorial position.

1:05:08

This, of course, was helped along by a staff increasingly aligned on an ideological level with the paper's narrow subscriber niche.

1:05:14

One of the greatest sources of cultural angst stems from the ability to recognize these institutions of the monoculture have shifted to microculture.

1:05:22

whether they supported Trump or Bernie Sanders.

1:05:26

Plenty of Americans outside affluent urban bubbles figured that out years ago.

1:05:31

It is the institutions themselves that often cling to the outdated uh brands so blinded by their own biases biases that it's become difficult for the sea to even recognize what's happening outside of Manhattan and the Hamptons don't count.

1:05:46

Anyway, um fantastic analysis from um from Emily.

1:05:52

Uh, you should subscribe to Pirate Wires to go read the full thing.

1:05:54

Um, but lots of people were having fun with this.

1:05:56

How does a late show cost $100 million produce? That was a big question.

1:05:59

I think a lot of it's just this is a this is Letterman started in the 90s.

1:06:04

So, this is 30 years of just like Yeah.

1:06:08

Let's just add one more person.

1:06:08

Like 30 years is only adding 60 people a year. One what it No, no, no. Way less. Six people a year.

1:06:19

So, you're adding like one a quarter, which is like not that much.

1:06:23

And I think it just kind of creeps in.

1:06:24

But you got to be aware when revenue starts dropping, like you have to write the ship, and you can't just uh you can't just keep losing money because it doesn't give you leverage over CBS who's trying to get out and sell the company.

1:06:38

Um, Buco Capital Bloke says, "I can't stop laughing at CBS losing 40 million a year on the Late Show with Co Bear because they were spending hundred million dollars a year to produce it.

1:06:46

show of a guy talking sometimes to other people.

1:06:48

Is there a less competent group of industry executives than linear television?

1:06:52

Alex Roy, friend of the show, says, "Media is a business.

1:06:54

Co Bear already has an audience.

1:06:56

He should have no problem launching a YouTube channel." I agree.

1:06:59

Y >> many friends run a profitable YouTube channels with millions of subs with staffs of less than 10 people.

1:07:04

They started from scratch, signed a a media business veteran.

1:07:08

Uh the left has been looking for its Joe Rogan or Tucker Carlson.

1:07:11

Why shouldn't Co Bear be that guy? That's interesting.

1:07:13

Um, and so a lot of people were saying it's a piece to camera guest interview show.

1:07:17

It shouldn't cost that much. >> Tyler is back. What's going on, Tyler? >> I'm done.

1:07:23

>> Yeah, I was stuck for a while on one of them and then I switched to a different game, finished that, came back. >> Okay. >> But I don't know. >> What's the timer?

1:07:29

>> I feel like it was a little slow. >> 25 minutes. >> 25 minutes. Oh, >> that is brutal. >> Brutal. >> Brutal.

1:07:35

>> But you did get through it all. >> Yeah.

1:07:36

Did your hair get messed up or was going >> I was I was stressed out.

1:07:39

The one game I was I was on I was on one level for like five minutes and then >> I don't know what I just like couldn't figure out.

1:07:45

I went to a different one and it was like I got it instantly. >> Crazy. >> That's brutal.

1:07:50

>> We will give you We'll still >> We'll keep giving you challenges until you get a new phone.

1:07:55

>> Mike is before you go back to college. >> Mike is brutal.

1:07:56

He says 25 is average, 20 is medium, 15 is hard.

1:07:59

Well, uh we will give you a new challenge.

1:08:03

Give you a new chance to win a new iPhone.

1:08:04

The iPhone moment has arrived for RKGI.

1:08:07

Uh Tyler missed it this time, but uh what do you think it says about current AI systems?

1:08:16

Do you think you will outperform the latest uh IMO level model from OpenAI?

1:08:21

You think you still got it?

1:08:25

>> Um I mean I I think you could probably do RL on this and get it.

1:08:28

I mean I I I don't know I don't know if that's what the labs are necessarily doing.

1:08:32

I think ideally like >> they're trying to just train it >> Yeah.

1:08:37

>> you know independent of this and then see what how it does.

1:08:38

Yeah, >> I think it's I think it's a very good like benchmark in that sense, but you could probably you probably could RL on this. >> Yeah.

1:08:45

So the the way Mike described it was that you played the three public games.

1:08:49

There are three private games and so I don't know how much variation there was between the games.

1:08:54

It seems like there was a fair amount because you got stuck on one, you switched to one, switched to a different one and then went back, right? So yeah.

1:09:00

So I think the I think the goal is like if you RL on the three public games, you will be overfit against the private games that have slightly different mechanics and you won't have learned the true generalizing function.

1:09:15

That's the idea at least.

1:09:18

>> Yeah, that makes sense.

1:09:18

But I mean, I'm sure, you know, if you're OpenAI, you could just like, oh, let's just make new games that are kind of in a similar vein and then RL on those.

1:09:25

Then you have more data and then >> Yeah. >> I don't know.

1:09:28

I think you could probably like I think my general sense is that you can like RL on pretty much anything. >> Yeah.

1:09:34

>> So, if they really want to and they want to throw like, you know, many millions of dollars.

1:09:38

I'm sure they could get it, but I don't know if that's really what they want to do.

1:09:41

>> I think the current prize is like $10,000, something like that for for something that works on it.

1:09:45

Maybe there's a million dollar prize.

1:09:47

There's a million dollar prize that's still hanging out there, I believe, for RKGI v1.

1:09:52

>> Yeah, but those are size limited, right?

1:09:54

You can like they need to run in a certain speed and they can't be too like so big.

1:09:57

>> Yeah, I think they have to run on the Kaggel infrastructure, Kaggle infrastructure.

1:10:00

So, you basically have to like send it your weights, your code, and then you get access to like one GPU.

1:10:07

You don't get to fire the Stargate at it. Yeah. >> Um, but I don't know.

1:10:10

No, it'll be interesting to see uh how how what what's your what's your timeline for a lab destroying this?

1:10:18

>> Uh probably end of the year. >> End of the year.

1:10:21

You think they'll beat it?

1:10:23

>> The whole the whole team is like we designed this to be unbeatable for years. Like two to three years. >> I don't know.

1:10:30

I mean, they just beat IMO.

1:10:31

It's like like do you mean on a public model or them just releasing we've beat this? >> Uh private.

1:10:36

It doesn't need to be open sourced. >> Yeah.

1:10:39

I think if it's a private model, it's like OpenAI, it's like, okay, we have this internally.

1:10:42

We're not going to release it. It's not safe. >> Yeah.

1:10:45

>> But like we've run it on this.

1:10:45

I think probably by the end of the year is like reasonable >> for for specific.

1:10:49

Okay, we we built a model just to beat this or or we just we just we're advancing models generally, giving people what they want, making great things, solving, you know, flight booking and GPT agent and solving IMO and then oh, as a byproduct, we solve this.

1:11:05

You think that's what's going to happen? >> Yeah.

1:11:06

I I I don't think they're necessarily going to train a model just to do this. >> Yeah.

1:11:10

>> But they definitely could.

1:11:11

>> I mean, at this point, it's getting high stakes, right?

1:11:12

Because like >> apparently IMO is not RL at all like specifically for >> that's what they say >> math.

1:11:18

So yeah, I think that model is like reasonably capable obviously. >> Okay.

1:11:22

I want to try that model on on ARGIV3 and see how it does. >> Yeah.

1:11:26

>> Yeah. because I I I it does feel like that will be a very interesting moment where if they truly don't cheat and don't RL on this specifically without the gas station data set as Rune calls it uh you know no ArcGI v3 like creating new games that feels like scientists

1:11:44

collecting the gas station data set right uh and they just go about their bit day building better and better models and then by the way oh we solve this that that will be very very interesting but I don't know I would take the over on the end of the year. The end. It's We're more than halfway The end.

1:11:58

It's We're more than halfway through the year. >> Yeah, that's true. Okay. What is your line?

1:12:02

>> You're so >> You're so AGI pelled.

1:12:04

I think I think this will hold.

1:12:06

I mean, B1 is still holding. V1 is not Yes, V1.

1:12:11

It takes $2,000 to get like 60%. You just got 100%.

1:12:14

You know, like you finished the whole thing in 25 minutes. >> Yeah. I I mean, we'll see. I guess >> I don't know. I would take the over.

1:12:24

I would take the over on this year.

1:12:27

I would probably take the over on and >> I have to give you an update.

1:12:30

I have to give you an update on on chat GPT agent.

1:12:34

So, it it only found >> So, it gave me a really great report, but it only found one and it's listed by a dealer and I can already tell the dealer >> uh >> the dealer is like clearly pricing it like not where they would actually sell it. >> Got it. Okay.

1:12:53

But they did find one in Costa Mesa, so not far away. One county away.

1:12:57

They found one at 399 99. 99. Just under the limit.

1:13:03

>> Um, so >> pretty good. Not bad. >> 15 minutes.

1:13:06

They're they're >> I think we got to use it more. >> Weird.

1:13:09

But then they didn't actually get me.

1:13:13

>> They don't have a link. >> Um, >> okay.

1:13:16

We're going to have to dig into a more test >> not achieved internally, but we're making progress. >> Yeah. Uh, >> okay.

1:13:23

Wait, so so are you saying 100% on V3 >> or what's like the benchmark?

1:13:26

Cuz like if it's 100% then like Yeah, obviously not a year. >> 100%.

1:13:30

I mean like you got you just got 100% never having seen it. 25 minutes. Yeah. Like not crazy.

1:13:37

I think we could literally give this to anyone over the age of like 10 and they would get 100% >> in half an hour basically.

1:13:46

Like I think it's I think it's like it's a very doable puzzle >> for humans.

1:13:52

And so I want a 100% and I want it in and and I don't care about time and money.

1:13:59

Like I I'm I'm I agree with uh was it Will who said that or >> Yeah, Will.

1:14:05

>> Yeah, Will Depw said, you know, so yeah, throw $2,000 per task on it. I'm fine with that.

1:14:10

The question is just can the model do it in any amount of time, in any amount of money, and uh and it and it seems like right now it's probably at zero.

1:14:20

We'll see how the IMO model does.

1:14:23

Maybe it does really well. We'll see.

1:14:25

But I would put it at over I would put it up there with doing your taxes.

1:14:31

You know, Dwar mode 2027.

1:14:34

>> Yeah, I think 100% is hard.

1:14:34

But if if you give me like 90%.

1:14:36

Like if it misses one of the tasks because on on So there's three games that each have like 10 levels around. >> Yeah.

1:14:42

>> If you can miss like one of those. >> Yeah.

1:14:44

Well, I I don't I think you have to finish a game or not.

1:14:46

And so I think basically on the private data set you can get zero, you can get one out of three, two out of three or three out of three >> basically.

1:14:54

Okay, but it's it's unclear because like when do you tell it to give up because you can just keep trying and kind of brute force it but maybe there's some sort of like limit. I don't know.

1:15:02

But you get like unlimited retries.

1:15:05

>> But maybe maybe the real test is only giving one try.

1:15:10

>> Um yeah, >> we got to move on.

1:15:11

But for your next challenge, Tyler, uh, prompt uh prompt 40 7,000 times in a row and stay sane. >> Stay sane.

1:15:24

>> Uh, start recursive prompting like crazy for uh for 48 hours straight and then uh come back come back to us. >> Yeah.

1:15:33

>> Um, well, we got to talk about the the McLaren collection that's going up for sale.

1:15:38

But first, I got to talk to you about Finn AAI. Finn.

1:15:39

AI AI, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bakeoffs, number one ranking on G2.

1:15:46

Um, this was what Swix said.

1:15:49

He wants AI agents for customer service. Fin. AI is delivering. So, go check it out.

1:15:54

Um, anyway, so the monster collection.

1:15:59

Um, this is from Tom Hartley Jr.

1:16:02

and hopefully we can pull up the video because it is fantastic.

1:16:04

Uh, it's on YouTube and uh, yes. So, here's the video.

1:16:10

You can play some of that.

1:16:10

Uh, look at this lineup of cars.

1:16:12

So, the story here is this uh this man named Mansour O'Hay OJ.

1:16:17

I'm not sure how to pronounce that. It's OJJ eh.

1:16:20

I apologize to anyone who knows how.

1:16:23

He says, "I am incredibly to proud to announce that we've been entrusted with the sale of the world's greatest collection of McLaren road cars offered directly from the home of one of the most influential figures in McLaren's 62-year history.

1:16:34

uh he passed away age 68 surrounded by family um and is now entrusting the sale of his collection.

1:16:44

Uh this guy is fascinating very very interesting fellow.

1:16:49

So he has let me pull up my uh my information here.

1:16:53

So, uh, Mansour O'Hay, um, he was the son of, he's a Franco Saudi, French Saudi Arabian businessman, uh, and he used his family fortune to bankroll Formula 1 teams and he built the TAG group.

1:17:08

So, if you're familiar with Tag Huer, the uh the the the watch brand, he built that watch brand and then wound up selling it to LVMH.

1:17:17

And so he was born this uh the the man who collected all of these McLarens in burnt orange, which by the way, he not only is he only is he the only one with the massive orange McLaren collection, that particular color is not available to anyone else.

1:17:31

He has his own color that only he can buy.

1:17:33

It's absolutely incredible.

1:17:36

Um, and every single one of those cars that you see there in the background, they are all the last the last one off the line, the last individual production car that they've ever made of that particular model.

1:17:49

And so, he gets the last one.

1:17:51

He's and you see the logo there.

1:17:51

He puts his name on the logo.

1:17:54

It's the only I've never seen a brand do that, but they were so tight with him uh because he owned the company at one point that they would replace the McLaren logo with Mansour logo, which is incredible.

1:18:03

And so he he is a fascinating figure.

1:18:05

So his father Aram O'Hay uh accumulated immense wealth from an uh as an intermediary in Saudi arms deals.

1:18:16

So he basically would go to the the Saudis and say, "What weapons do you need?

1:18:23

What missiles do you need? What guns do you need? What planes do you need?

1:18:27

I'm going to go out into the world and find those and source those and bring those back and take a cut of that."

1:18:32

And so, >> yeah, this is really, I will say, if if your father has amassed immense wealth through armstealing, this is really pretty much the playbook, uh, for how to put that capital to work. >> It's the best. It's the best.

1:18:44

Um, and so, uh, Mansour grew up in France.

1:18:47

The family mostly lived in France.

1:18:50

He attended the American school in Paris.

1:18:53

He moved to California, where we are, studied, uh, business administration at Menllo College.

1:18:58

Uh >> let's give it up for all the business administration majors out there.

1:19:01

One of the top majors if you want to administrate businesses. >> Yeah. Which he certainly has.

1:19:09

>> He went to Santa Clara.

1:19:09

Um he he initially managed his father's ventures.

1:19:14

Uh he became uh gradually more and more involved in his father's investment vehicle which was uh technique de avant god which is tag uh Luxembourg registered holding company created in 1977.

1:19:26

So the group's purchase was to broker deals between the Arab world and Europe and to handle commissions from arms and infrastructure contracts.

1:19:32

And so um his dad was born in Syria, raised in Iraq, uh studied in France on a scholarship during the 40s, marries a French woman, stays in France, and then and then starts arranging these arms deals and infrastructure projects.

1:19:46

And so in 1956, the dad opens an arms trading company in Switzerland and establishes Saudi Arabia's first weapons factory.

1:19:56

During the 1960s, he represented the French defense contractors such as Dault and Matra, selling Mirage jets and missile systems to Middle Eastern clients.

1:20:05

Uh he was facing some scrutiny from French authorities.

1:20:09

At one point he founds the TAG group.

1:20:11

The group gave him unrivaled access to the Saudi royal family for defense projects, leveraged his relationships with Prince Sultan, the Saudi defense minister.

1:20:19

Uh, and he became so wealthy that he bought a cruise liner, like a cruise ship.

1:20:26

He bought the Queen Elizabeth 2, just I think as like a personal pleasure pleasure yacht.

1:20:32

He bought a ranch in Paraguay, homes in Paris and Monte Carlo, and then he started sponsoring the Williams Formula 1 team, and he was putting in a million dollars a year, a million pounds a year.

1:20:42

Um, in the 80s, >> when what when did he when did he start doing that?

1:20:48

>> Uh, this was in the in the late 70s.

1:20:48

And so his son, uh, so the dad dies in 1991, reportedly worth several billion dollars.

1:20:56

Mansour who's the man with all of those uh fantastic looking McLarens.

1:21:02

Um him and his brother Mansour and Aziz were heirs to the tag group.

1:21:05

Um and there was a bitter inheritance dispute between the widow and some of the children and obviously all the assets kind of you know get fought over but Mansour makes out quite nicely and winds up um investing even more heavily in F1.

1:21:22

So through TAG, he starts sponsoring Frank Williams Formula 1 team.

1:21:24

In 1978, uh when Saudi Saudi airlines uh sought to attract other Saudi brands, TAG became the team's major sponsor in 1979.

1:21:36

Uh Williams actually did win multiple races, although they were having some trouble a few years ago.

1:21:40

They were pretty good back then.

1:21:41

They got Allan Jones in another title in 1982 with Kiki Rosberg.

1:21:45

Um I think that's Nico Rosberg's father, I believe.

1:21:48

Uh the sponsorship gave Monsour his first taste of Formula 1 success and increased tags visibility.

1:21:55

Then in 1983 he jumped ship from Williams goes over to McLaren.

1:21:58

Uh Frank Williams uh resisted diversifying beyond racing.

1:22:03

McLaren's boss Ron Dennis proposed a shareholding in proposed uh exchanging um uh shareholders uh like shares for a new tur for financing a new turbo engine.

1:22:15

And so Mansour agreed and funded the development of a Porsche turbo engine badged as tag.

1:22:20

So the McLaren tag partnership dominated in the 1984 season.

1:22:26

Drivers Nikki Laua and Ela Prost won 12 of 16 races and McLaren secured both the drivers and constructors titles.

1:22:33

So basically he comes in with a bunch of money and says, "You want to win an F1?

1:22:36

I will finance a new engine."

1:22:39

He goes and does it and it actually works.

1:22:41

And so he in >> which is interesting because Tag and Porsche have >> uh their own partnership now.

1:22:46

They have the Carrera line of watches all these years later. >> Yeah.

1:22:53

>> And so uh in 1984 he buys a 50% stake in McLaren's holding company.

1:22:57

Now remember, uh, McLaren was founded by a a true racer who died at age 31, I believe, in a racing accident.

1:23:07

And so left this incredible legacy of just a guy putting it all on the line in in racing.

1:23:11

Like it wasn't like he was some business guy who was like, I want to get into racing.

1:23:15

He was just a race car driver.

1:23:18

>> Well, this is the story of Enzo, too.

1:23:20

Ferrari wasn't started until he was in his 40s. Yep.

1:23:23

>> And uh but he had just been so obsessed >> Yep. over racing. Yeah.

1:23:26

That it it just carried into the brand.

1:23:30

>> And so in a Mansour uh buys a 50% of stake in McLaren's holding company, TAG McLaren holdings.

1:23:36

And he's still working on the racing stuff, but then he says, "We got to make a road car."

1:23:40

And the road car that he pitches is the McLaren F1 supercar that launches in 1992 and is a $20 million icon owned by Elon Musk.

1:23:53

Uh Sam Alman like there's they're in museums like they are the rarest of the rare. Jay Leno has one.

1:23:58

Uh I don't think I think it's like the one of the few cars Doug Demiro hasn't driven.

1:24:01

He rode in it with Jay Leno, but they are incredibly rare, incredibly special cars. >> And the doors go up. the doors go up.

1:24:12

And so, uh, in in other news, like he he did buy Huer and created Tag Huer, which was a watch company that you might be familiar with, Tag Huer.

1:24:19

Um, they eventually sold Tag Huer to LVMH for $740 million in 199 Elon crashed his McLaren F1. >> He did. Yes.

1:24:29

And I believe that the McLaren was picked up and uh and like reconstituted and wound up selling still for millions of dollars.

1:24:38

The car hit a hidden embankment on Sand Hill Road at a 45 degree angle, launching it into the air like a discus, according to witnesses.

1:24:49

I >> mean, the car goes 200 mph, weighs like 2,000 lb.

1:24:52

>> Incredible piece of lore imagining Elon on Sand Hill Road.

1:24:56

>> And you know who else was in that car? Peter Teal. >> Crazy.

1:25:00

>> And he went to the meeting after, right? >> Yeah. Yeah.

1:25:01

They were apparently, you know, the lore is that they went to Sequoia to pitch or something that they were like raising money or driving down to a poor meeting.

1:25:11

>> He turned off traction control. >> Really? >> Apparently. >> Yeah. That is wild. >> Yeah.

1:25:16

The there's a long history of of guys turning off traction control, driving really fast, and then just crashing their cars.

1:25:22

So, if you want to avoid crashing your supercar, keep it on.

1:25:27

>> Avoid turning off traction control.

1:25:27

>> Avoid turning off traction control. I mean that's the thing with doesn't the Carrera GT not have traction control or maybe maybe it does but it's like one of the few features and a lot of >> kills a lot of its drivers >> a lot of these guys like pride their you know they like an analog super does have

1:25:42

traction control it does not have stability control or other electronic driver aids that are common in modern supercars >> does Mansour he buys Huer turns it into Tag Huer great watch brand sells it to LVMH for $740 million in 1999 He gets a huge profit from that and then he starts going deeper into all of that. He

1:26:01

He launches tag aviation and aeronautics which is distributing bombardier jets to the Middle East.

1:26:08

So he's a go-between between French aerospace and defense companies in the Middle East still.

1:26:13

In this case he develops a luxury airport uh in the Middle East and he's just doing a lot of deals at this very very high level.

1:26:21

Probably benefits from his ties to F1.

1:26:23

Um, and so he builds the he builds the McLaren F1 and then of course starts collecting and stays involved in in McLaren F1 for years.

1:26:31

Um, and he builds this uh I mean he builds a 24 235 foot super yacht KO.

1:26:39

He uh creates a lavish house on Lake Geneva, Switzerland known as Lamas Dulak uh and uh and and kind of goes on through that.

1:26:50

He winds up getting uh ideopathic pulmonary fibrosis, gets a double lung transplant and ultimately doesn't make it, but he know he dies at age 68.

1:26:57

McLaren CEO Zack Brown described him as a titan of our sport, ultra competitive, determined, passionate, and sporting.

1:27:05

Um, and so uh everyone remembers him and his contributions to uh to F1.

1:27:09

But what's interesting today is that they are about to sell his entire McLaren collection which is something like 20 McLaren road cars all in his exact spec which is this burnt orange with his badging.

1:27:27

>> I don't know who the buyer would be.

1:27:29

They're probably listening to this show.

1:27:31

But good luck out there as you go and bid on the Mansour collection because it is truly one of a kind.

1:27:37

And every single car there is in the most extreme spec and it's the last one off the line.

1:27:42

And there's a back and there's a plaque inside that says this is the last F1 that was ever made.

1:27:48

This is the last Senna that was ever made.

1:27:49

This is the last speed tail that was ever made. This is the last GTR.

1:27:53

This is the last I mean look at that one. No. Uh what is that? The Elva.

1:27:57

Yeah, >> the Elva in burnt orange. >> Fantastic.

1:28:01

>> Burnt orange Elva with no windshield.

1:28:03

Wow, >> that is fantastic.

1:28:04

And just every single one of those cars is insane.

1:28:07

Oh, also Oh, by the way, also every single one of those cars delivery mileage never been driven. Never been driven.

1:28:15

>> Do you think he was buying Do you think he was getting two?

1:28:17

Like >> So the story is that he had an F1, of course he developed it.

1:28:22

he had an F1, but it was kind of I think from like the middle of the pack or maybe the earlier pack and uh and because he he was just like excited to get the first one and you know got it and probably gave one to someone else and like just had one, drove it, had fun with it. It was his experience.

1:28:38

But then his brother bought got the last one in that in that orange color and he and his brother was about to sell it and he said, "If you're you can't sell this.

1:28:49

If you're selling it, I'll buy it."

1:28:50

And so he buys it from his brother and winds up building an entire collection on the back of that one car.

1:28:59

The last F1 off the line, the the the burnt orange that turns into his signature color.

1:29:04

It turns into the color that you cannot buy.

1:29:06

No matter how much money you have, >> then no matter how Clarence you and his legacy lives on Oscar and Lando dominating so far this year.

1:29:18

>> Yeah, give us the update there. It's good.

1:29:19

He wouldn't have been he wasn't around uh to see it, but he uh would surely be proud. >> Yeah.

1:29:25

Well, if you're looking for a compliment to your McLaren F1, get on bezel getbbezzle. com.

1:29:29

Your bezel concier is available now to source you any watch on the planet. Seriously, any watch.

1:29:33

Um anyway, let's go to Trey Stevens.

1:29:37

He had a massively viral post on Friday.

1:29:38

We didn't get a chance to talk about it.

1:29:42

There are only >> four tier one cities in the United States.

1:29:45

New York for finance, DC for government, San Francisco for tech, LA for media and entertainment people. Thank you, Trey.

1:29:52

Uh, no other cities or power centers for aspirational talent. Sorry.

1:30:00

>> He says, "Based on replies, here are the people arguing for other cities.

1:30:05

>> Austin, people who live in Austin.

1:30:07

Boston, people who are really upset about Trump's Harvard attack.

1:30:09

Dallas, Houston, people who have only lived in Texas. Miami.

1:30:13

People who love money but don't love to work. >> Moged. >> Moged.

1:30:19

>> Someone just commented >> for Cleveland.

1:30:21

It's funny because uh Tres Ohio guy.

1:30:24

Um no no I I I agree with this and it is incredibly sticky.

1:30:27

Like it's unclear if there will ever be another tier one city built in in America.

1:30:33

It doesn't really matter though because you can go like Warren Buffett is out in Omaha. It's fine.

1:30:38

Like people read this as like I can't possibly be successful in finance if I'm not in New York.

1:30:45

Ken Griffin was in Chicago and then Miami.

1:30:48

Like >> Charlie Mer lived in Los Angeles. >> Yeah. Yeah.

1:30:52

And so and so it's like it's like it that it is true that these are tier one cities.

1:30:57

doesn't mean that you can't do something cool and amazing and achieve your goals in life somewhere else, but you should just be thoughtful about it and you shouldn't delude yourself into thinking that a a tier 2 city is secretly a tier one if it's not. It's just not.

1:31:10

And so stuff's moving around. Very fun post.

1:31:13

Always good to to bait literally everyone in the world, but very fun.

1:31:19

Uh but related to this, Delian had a post that was kind of interesting here.

1:31:23

He said uh 10 years ago it felt like Silicon Valley had this really bi vibrant seed fund ecosystem that felt just as important as the multi-stage venture firms.

1:31:32

Now that feels totally dead partially because the whole a whole generation of top tier companies just completely skipped that step in raising.

1:31:41

And so yeah, more and more companies are saying our seed or $1 million will just come from our own balance sheet and it'll just come internally and we'll just fund that or we'll just jump straight to $20 million.

1:31:53

There's plenty of I do I I have a problem where if somebody's raising a preede, I do feel like there's 20 funds that I would potentially introduce them to.

1:32:02

The challenge is when those preede funds are then trying to go compete at seed, which we now know is this sort of >> 4 to8 million range.

1:32:11

We had somebody on Friday who was raising 55 million. Crazy.

1:32:17

Whether or not that was uh marketing or um you know whatever the name doesn't really matter.

1:32:22

Um board ape yach club raised a billion dollar seed round in uh 2021.

1:32:28

>> That was a seed round.

1:32:28

Was that because they just hadn't raised before?

1:32:31

>> It really hadn't raised. Yeah. >> Yeah.

1:32:32

There's this weird thing where you know >> and mirror Marotti two or three billion dollar uh seed round.

1:32:36

Um so again uh like the the ex the your company's expectations are based around how much capital has come in the door not the last name the last the the name of your last financing round.

1:32:52

So >> yeah, there's one side of this which is like the seed moniker used to stand for time and money effectively.

1:33:00

Like it used to be like okay if if I'm a seedstage company you know that I'm in the first 18 months of my creation and I've only I've raised less than $5 million or else I'm in mango seed territory in series A territory.

1:33:13

But now there's some world where people just say okay you know this is your second round.

1:33:18

doesn't matter that you've been around for 10 years, it's an A round or it's a seed round or doesn't matter if you're raising a billion dollars and it's priced like a growth round, it's it's a seed round. I don't know.

1:33:28

Um I I think what Delian's getting at is more just like the vibe of like you used to be able to he's he's a seed investor.

1:33:35

You used to be able to hunt around, find some people doing cool stuff and get 10% 20% of the company for a million bucks, two million bucks.

1:33:42

And that has kind of disappeared.

1:33:47

Delian's still known to uh to get a good to get a good price.

1:33:51

>> He's figured out how to survive.

1:33:51

Uh Nature finds a way as does public.

1:33:53

com investing for those who take it seriously.

1:33:57

They got multiasset investing, industryleading yields, and they're trusted by millions folks. Get to public. com.

1:34:02

And we have we have Chris Black in the reream waiting room. Let's bring him in. >> Let's bring him in.

1:34:07

Chris Black, how you doing? >> Bring me in. What's up, guys? How are you? >> What's up? >> What's happening?

1:34:12

It's uh it's great to meet you.

1:34:16

I uh I' I've wanted to chat for a long time.

1:34:19

I I actually bought your uh what was that little green book that you you made all those years ago. >> Wow.

1:34:25

We got an OG on our hands.

1:34:25

I know you think you know it all was I think it was 2015 I did that with Powerhouse.

1:34:28

So, thank you for being a ground floor investor.

1:34:32

I had that I had that in college and I felt so cool to be a college kid that was cultured enough to buy a a table, you know, coffee table. Coffee table black. >> Yeah.

1:34:45

>> I think it I think it turned into more of a bathroom book than coffee table.

1:34:48

>> It's very it's very small.

1:34:48

You would like you would like the form factor. >> Sure. Sure. Sure.

1:34:51

And what was inside the book? Break it down.

1:34:54

>> Uh I mean Chris can give some more context.

1:34:56

The thing that I remembered in a quote that I've brought up a bunch uh was the it was the Andy Warhol quote in there that was something like making money is you know uh business is art and making money is art and good business is the best art.

1:35:10

>> You you guys loved that. You guys love that. Yeah.

1:35:12

I mean the the the book was just like a fun advice book kind of.

1:35:16

Basically it was it was um it did really well as a uh graduation gift purchased from Urban Outfitters that year.

1:35:21

That's that's we sold a lot of books. Thank thank god.

1:35:26

So it was it was fun to do that.

1:35:26

It was very it was very fun.

1:35:29

>> Did you go through a traditional publishing house?

1:35:30

Like what was the workflow?

1:35:32

Did you write the whole book and then shop it around?

1:35:33

Like I've never published a book. So curious.

1:35:36

>> It was ba it was based on Twitter.

1:35:38

Honestly, it was based kind of on that idea of like life soul instruction book.

1:35:42

The classic form factor to use your term meets sort of Twitter.

1:35:44

So I went through wrote them all. Yeah.

1:35:48

I did it with powerhouse which is like sort of in and out of business from what I can tell.

1:35:53

Um, but I'm working on a book now for Simon and Schustster that should come out in 2026.

1:35:56

So that that's a little more of a >> the process you're talking about.

1:36:00

>> What's the concept of the new book?

1:36:02

>> It's kind of it's kind of like a essay memoir, you know, a little bit everything from like some high school stuff to being a drug addict to work to kind of everything.

1:36:11

Um, and that process is a little bit more like you're talking about, like you write a full essay, you know, you outline uh some chapters and then you take that out and and sell it. And CIA helped me.

1:36:23

Obviously, I wasn't doing it myself, but it's daunting, but I'm excited. >> Yeah.

1:36:28

What's the su What's the secret to like a good book launch these days?

1:36:30

We talked to uh Ezra Klein's co-author and he was saying that interestingly like when they went on hour-long podcasts they sold less books than like a five minute hit on like TV because if you listen to an hourong podcast you're like I got the gist.

1:36:48

I don't need the whole book.

1:36:49

But if you listen to five minutes you're like oh I could do I could do another hour. I'll buy the book.

1:36:52

That's a fair I have a friend who's a very successful legendary author who told me an anecdote that he sold more books from doing Tucker Carlson when he was on TV than he sold from anything else. Like a clear bump.

1:37:05

And I mean, you know, this was years ago, but I think that I mean, we were talking about this earlier today.

1:37:10

Jason and I actually were talking about this and about how sort of >> um podcasts have replaced not only late night obviously with this like kind of like Steven Cobear news.

1:37:18

It's >> but also like Good Morning America The View.

1:37:23

Like it's still fun to do that stuff.

1:37:25

I don't but it might it might move books, but it doesn't seem like the publicists think that it it does based on the priorities of what they're having their clients do. >> Yeah.

1:37:34

>> Is it is it speedrun 200 podcasts?

1:37:34

Is that is that the playbook now?

1:37:39

>> I mean, if you pay attention to people Yeah, kind of.

1:37:41

You know, if you have if you pay attention to an actor or writer or whoever has something coming out, it's like, you know, music.

1:37:46

We we talked to a lot of musicians on How Long Gone.

1:37:49

So, we're part of that in some ways, but like there's the Dak Shepard's Joe Rogan's smart list, Caller Daddy world that I think is basically that's the new Oprah that, you know, that's what it is.

1:38:01

I almost feel like there's a world where some podcasters, certainly not us because we're a daily show or news driven, but some podcasts, I'm thinking of like acquired FMs, like business deep dives or some true crime podcast, like they kind of fill the hole of an audio book.

1:38:17

It's like you get two or three hours every month and it feels like it's just a more it's like an easier financial model for them to be like, well, I'm selling 12 ad slots and I have subscribers that feel like they're getting something.

1:38:31

They're not waiting a full year for the next thing.

1:38:32

So, when I hit their credit card with a $20 charge this month, they're getting one.

1:38:36

We were talking uh I think we were talking on Friday this concept of like releasing a book on Substack because you could get somebody to effectively it creates this like >> community experience of like reading the book together but then it's you know you might charge $25 for your book but somebody might pay you I don't know $10 a month for your substack.

1:38:58

>> Uh no I mean there's all these I mean I I think there's all these ways to do it.

1:39:02

I am extremely traditional in the what I think is cool and what works.

1:39:05

Um, I would like to do it about as buy the book, no pun intended, as possible just because I think that's cool.

1:39:11

I think all of these modern approaches though are often more more profitable and also maybe um, like you said, easier for people to stomach.

1:39:19

Like the attention spans aren't there.

1:39:20

Even if you break it up like that in their minds, it's like easier to read in a weekly dispatch than it might be to sit down for an hour every day and read a book, you know? >> Yeah.

1:39:30

There's also something about like I mean when way I' I've heard somebody say like when you publish a book like it's the easiest way to get like a comma with a phrase after your name every time you're in print.

1:39:41

Like if I wrote a book that's just like you know how I became awesome.

1:39:45

Everyone would just be like okay like you know life life as someone awesome forever.

1:39:50

John Kugan author of of the awesome life.

1:39:54

>> That's why I'm awesome.

1:39:55

>> Chris's book I'm assuming the memoir will be called just goatated. goatated. >> Just goated.

1:39:59

That's what I'm thinking. I'm workshopping it now.

1:40:01

But no, I mean I think you're right.

1:40:02

I mean, I had another friend um uh Mattie Mat, uh the the chef and cookbook author and you know, actor and he told me he was like, "Dude, >> like New York Times bestseller lasts for the rest of your life.

1:40:15

You can you you get that forever if you do it one time, you know?"

1:40:19

And like I I think that also that is so interesting because it's such like a classic thing that we all know but no one really knows the formula of how you get like it's not just sales.

1:40:29

There's all these factors that like no one knows you know which makes it even more >> it's interesting to think about would you rather have be featured in the New York Times?

1:40:38

Is it is it more valuable to be featured in the New York Times four times a year forever or just be a New York Times bestseller?

1:40:45

Because I we had we had a couple buddies get hit pieces last week in the New York Times and they just like really they only get attention if you give them attention.

1:40:55

>> Like they >> Dude, I was I That's so funny you say that because there was a story in the early days of How Long Gone.

1:40:59

There was a story that wasn't favorable, let's say.

1:41:03

And I was like, >> "Wait, was this was this the um was this the whole lawsuit thing?"

1:41:07

Because I got the t-shirt back then, too. The t-shirt?

1:41:10

>> No, not the New York Times.

1:41:10

No, this was not the New York Times lawsuit.

1:41:12

This was not this was not the cease and desist for making fun of the daily.

1:41:15

This was a it it's you know it's um yeah sand don't striand it. Don't striand it.

1:41:23

You know speak really generally so nobody can figure it out.

1:41:28

>> You know what we're moving on. We're >> moving on.

1:41:30

Uh anyway the the other interesting thing about books versus podcasts is uh we have a buddy who runs an AI podcast, the Dwarash Patel podcast.

1:41:39

great show, great interviews, super researched.

1:41:42

Um, he published a book and the book was uh an uh like a an oral history of AI.

1:41:49

And so it was a collection and it was actually kind of like a digest of a bunch of interviews that he's done.

1:41:56

So he didn't start from a blank page and just start typing out like a thousand pages and and refine it.

1:42:03

But and in some ways it's like it's just kind of a different instantiation of the same thing that he's been doing.

1:42:08

But I love it because I'm there's no way for me to go to like randomly remind myself in five years that I should go revisit a Dark Cash podcast unless someone like clips it and shares it.

1:42:20

But if I put that book on my shelf, I might pick it up randomly in a few years.

1:42:24

And there's something about like just the tangible physical.

1:42:27

We're very into the physical stuff here.

1:42:29

We print the >> No, for sure. It's real.

1:42:30

I mean, I think also that's I mean I think that like everything else, it makes a return to some extent. You know what I mean?

1:42:34

Like I subscribe to the Financial Times.

1:42:36

I subscribe to several magazines like a lot of my friends do.

1:42:40

I mean, obviously I'm 42 years old, so it kind of makes sense, but I think that like young people are fetishizing print the same way they fetishized vinyl, you know, a couple, you know, 10 years ago.

1:42:49

It's the same kind of thing.

1:42:51

Once it >> is, you know, once it's basically past its prime, print is just objectively better than vinyl, though.

1:42:57

I got to say I'm not 100% in that it's like it's it you can go to the very like you can't like you know like just bringing a piece of paper to the beach and letting it get >> losing it whatever. It's nice.

1:43:10

It gives you the benefit of leaving your phone at home.

1:43:14

That's the powerful thing.

1:43:16

>> When I finish a book, I leave it wherever I am.

1:43:18

Like on back in the backseat of the plane on on like I leave it so somebody can hopefully pick it up and take it because I'm usually I usually have a couple with me if I'm traveling.

1:43:26

If I finish one, I got to lose some weight.

1:43:28

You >> adding You're adding adding stuff on the way. >> That's amazing. >> Exactly.

1:43:34

>> When are we going to get How Long Gone Pressed on Vinyl?

1:43:36

>> We got to do a couple special episodes. >> We did do a CD.

1:43:39

We did do a CD a couple years ago with with Jag Jaguar, which is a really fun project to do.

1:43:43

But I mean, I think for us, we're still I mean, you guys have have have done something so interesting.

1:43:49

I think it's so cool the way what you guys are doing and how you're approaching it.

1:43:52

I think this live daily thing is like really powerful. Sure.

1:43:56

>> Um, and I think we're trying to figure out what our version of video is. >> Wait.

1:44:00

So, yeah, you guys are doing What's this thing?

1:44:01

Uh, I read it in in Feed Me, uh, like you're doing a live show, like a one-off live show.

1:44:07

>> We we did, we're on tour right now.

1:44:09

We're just have a couple days off.

1:44:09

Um, but we did a show at Turf Club in St. Paul, Minnesota.

1:44:16

>> Um, at this basically with this service called veps.

1:44:18

com, which is started by the Madden Brothers from Good Charlotte, but then Live Nation bought it. >> Um, and it's basic.

1:44:23

They send a full sort of very pro crew to shoot your show live and you can pay, you know, buy a ticket online and watch it up to 48 hours after you pay. Um, >> what's the idea?

1:44:38

>> It's like Vampire Weekend, How Long Gone, Alicia Keys.

1:44:39

So, I don't really know how. I don't really know.

1:44:43

>> Podcasters in Control. Podcasters in Control.

1:44:45

What's the right live show for you though?

1:44:47

Like, do you feel pressure to to have like, you know, the hottest takes?

1:44:52

We're doing DC on th we're doing DC on Thursday and then Friday we're doing Toronto and then we go to London.

1:44:56

Um but this this show is actually different.

1:44:59

We we we used to just go up there and shoot the We'd bring a guest up, you know, depending on what town we were in.

1:45:05

Um much like the the actual podcast.

1:45:07

This time it's the How Long Gone Guide to Life and it's a visual.

1:45:09

It's like basically a keynote that we're walking the audience through with like our commentary.

1:45:15

And we've only done it twice so far, but it feels it feels sort of like it's taken us from a live podcast to a show. Sure.

1:45:21

Which is what our goal was, and I don't think we could figure out exactly how to do that.

1:45:25

And I think this is is kind of pushing us in that direction, which is great.

1:45:29

>> What's uh give give us the the threeinut summary of the guide to life so that people have to still go see >> Yeah. Don't give away. >> Get the tickets. Get the ticket. Yeah. No.

1:45:38

Uh it's um it's >> by by the way we we did we did one live show together in Miami and we had only made like two episodes and so nobody like nobody knew us as a duo.

1:45:47

They didn't know our humor and the and the live show the live show is like we made like like a very serious uh like um argument for why venture capital firms should get their founders on like peeds.

1:46:02

So like testosterone like like a >> that's a great that is ext I would watch pay attention to that >> yeah exactly >> and and I don't like half of the a half the audience was like these guys are dead serious half were like kind of laughing like what is going on this >> it's a mixed it's a mixed bag. Yeah.

1:46:17

I mean ours we basically cover all of the stuff that we talk about on the show from like restaurants and restaurant etiquette to the gym and gym etiquette to dating and sex and drugs.

1:46:28

So it's like we cover it, you know, it's like one slide that's going really well for us is polyamory is for ugly people. Be single or cheat.

1:46:36

That's going really well for us.

1:46:41

>> But you know, it's just like funny stuff that you can just kind of talk about and also will inspire a response from the crowd cuz we we like to go back and forth with the audience. It's fun.

1:46:50

>> We're going to create we're going to create a rival guide for life and and we'll just go guide for guide. >> We go for guide.

1:46:55

Look, I think we I think we have different enough audiences where we cover a lot of territory, you know, cover a lot of >> stuff.

1:47:02

So, so going back and forth, I want your uh restaurant etiquette.

1:47:04

This morning, we go to our cafe where we have breakfast every morning.

1:47:09

Normally, really like I never noticed the music.

1:47:13

It was always quiet and chill.

1:47:13

And today, they were blasting in sync and Backstreet Boys, Britney Spears.

1:47:18

And maybe it was just the mood because it was kind of gloomy in LA.

1:47:22

We're having some like late June gloom going on. It was terrible.

1:47:27

>> And I was a little bit tired from the weekend trying to get back into it and I was like trying to read like a pretty detailed analysis about like tech and stuff and I was just like I can't I and funny thing is that two days ago I was in a grocery store and I was like jamming to the Backy Boys and I was like this is the greatest thing ever.

1:47:41

I was loving it in that context but in the morning >> but it felt like such a violation of trust because we go to this place every >> so reliable and it and it sets me up for the day. am prepping the show.

1:47:50

And so we kind of made a we made a slight comment.

1:47:54

We were like, "Oh, is the music different?"

1:47:55

But I want to know etiquette wise, how should I I don't want to be I want to speak to the manager. That's weird.

1:48:00

But also like I'd like a change. What should I do?

1:48:03

>> What What kind of like uh like you get as a regular?

1:48:06

Like what are your rights as a regular?

1:48:08

>> What are your rights as a regular? >> You're right. You can't say anything. Sorry. If you say >> no.

1:48:13

If you say something, they're never going to look at you the same.

1:48:15

You're not whether you're right or wrong.

1:48:16

I'm just telling you they're going to they're going to think of you differently.

1:48:21

The bra >> it's not going to be made with love anymore.

1:48:24

It's not going to be made with love. >> No.

1:48:26

So So am I supposed to vote with my feet go somewhere else?

1:48:28

I I we were running the numbers.

1:48:29

We go there every single day.

1:48:30

We're like we're basically employing a single person there paying the >> I like I like how you think about this like it's logical and then you can sort of figure out a way to make it work.

1:48:39

It's it's a barista hates all of the customers and that's >> Yeah. >> Yeah. It's a feature.

1:48:44

I mean that's I understand what you're saying though.

1:48:45

I I think restaurants like there was a trend for so long and it's still going on where like restaurants play like hip-hop, you know, and like I don't want to hear Kanye West while I'm eating spicy pine, you know?

1:48:55

I want I want to like I want to hear nothing is preferred.

1:49:00

If you go to certain kind of old school like I think Leader Dan in New York doesn't play music and it's just it's like the bustle of the restaurant and the chatter.

1:49:08

I' I'd much rather hear that. >> Yeah. Yeah. Yeah. >> It's fascinating.

1:49:13

Jordy, where should we take it now? Fast.

1:49:15

>> I have a I yeah I wanted I wanted to just get uh some some broad takes from you on a bunch of different topics that we don't we don't cover closely.

1:49:21

So one first off is AI psychosis real?

1:49:27

>> You experienced it yet yourself?

1:49:29

>> Let me let me let me tell you something about AI and I'm sorry to all of your I just could >> I'm assum I'm assuming >> the hottest >> I don't care less.

1:49:36

I think it's I think it's a reality.

1:49:38

I think it's very serious.

1:49:39

I think it's coming for us good, bad, and ugly. I just don't care.

1:49:44

and like other things in my life, I'm going to put it off till the very last minute.

1:49:47

And when I have to deal with it, I've never downloaded Photoshop. I've never used Inesign.

1:49:50

I I' I've put off all this in my my entire life and it's worked out.

1:49:54

So, I think I'm going to do the same thing with AI until until I have no choice.

1:49:58

>> And and you're So, you work uh list off some of the clients that you've worked with over the years.

1:50:02

It's basically everybody, right? >> Oh, I mean Yeah.

1:50:04

I mean, everything and on the in the on that side of the business. Yeah.

1:50:08

I mean, New Balance, um, Tom Brown, Stuy, uh, Jay Crew is is an ongoing one.

1:50:15

Um, Banana Republic for a couple years. So, yeah. I mean, I love Banana.

1:50:19

>> A little bit of everything. >> John's 68.

1:50:20

So, Banana Republic, >> yeah, they signed Kevin's 69. Jason's 69.

1:50:25

So, he has the same suffers the same size. >> And he has the 14 15. >> Jason's a 17.

1:50:32

So, it's really >> Oh, okay. Moged.

1:50:34

He goes to he goes to these like funny websites to find stuff that like we haven't heard of because we're >> dark web big and tall. >> Yeah. Exactly. Exactly. Exactly.

1:50:45

>> So So you're going in when you're working with these clients, it's kind of like Rick Rick Rubin mode.

1:50:48

You don't know how to use any of the tools.

1:50:50

You're just kind of like they just pay you to to tell them what what >> I mean.

1:50:56

No, I think it's a little bit of um a relationship thing and and hopefully a taste thing.

1:51:00

Like I I think taste takes years and years to develop and I think mine is is um suited for certain people more than others.

1:51:07

I think J Crew is like a perfect fit because I grew up wearing J Crew.

1:51:10

I I was raised in Atlanta. It's preppy. It's southern.

1:51:14

But I think I have a little bit of a different point of view because I I got into punk and hardcore and you know skateboarding and all that stuff.

1:51:19

So it's like a little bit of a hybrid of all that of all those things.

1:51:22

But I think with with clients, it's all about sort of taking the real talent at the company and making sure that it doesn't go off the rails, you know?

1:51:31

So, the creativity people who are true geniuses and really creative like powerhouses need to be brought back down to earth a little bit, you know, and like reminded in a nice uh gentle way that if we don't, you know, make money, this is all over.

1:51:46

You know what I'm saying?

1:51:46

like this like like we can do all this stuff, but sometimes you got to feed the beast to make sure the lights stay on and it buys us more time to do more fun stuff.

1:51:55

And I think it's like a I think as an outsider going into a company, you're able to do that a lot easier than like a a salaried employee.

1:52:01

>> Yeah, you can stir things up.

1:52:01

Uh are you um but but so so going like slightly deeper your client like I have to imagine every single brand that you've worked with or will work with in the future is starting to try to mix in AI generated imagery and I'm sure that's sounds like that's triggering to you.

1:52:24

It's just stuff that that you don't you don't want to like how do you see the kind of market kind of bifurcating in the sense that you think every brand do you think any brands will take a hard line and say like we only shoot you know farm-to-table organic content here we never >> I think that's exactly what's going to

1:52:40

happen I think there's going to be like a division where it's like obviously certain things are easy to automate I think everybody will do that because it's a it feels like a freebie I think some of the creative stuff >> I think a lot of at least I clients I work with would sort of be like, we need a human being to take the pictures like that. Like pictures specifically, like

1:52:58

Like pictures specifically, like to me, there's so much emotion involved in it.

1:53:03

There's so much skill involved in it and you just can't to me I haven't seen it mimicked correctly.

1:53:08

Like asking Chad how to fix your car is different.

1:53:13

Like this is something that requires like a human touch, I think. >> Yeah.

1:53:16

And I I think there's actually there's laws in place that that make it so that chain restaurants can't photoshop their food, right?

1:53:21

Because they would just photoshop a burger and then they're trying to sell it and it just doesn't look anything.

1:53:27

And I think I think it's possible we'll see I don't know on the apparel side it'll be interesting because everybody's had the experience of like buying an item and it just looks amazing online or it looks great when it gets there or whatever and then it just like doesn't fit or whatever.

1:53:42

And so I think that that will probably accelerate as you have these sort of upstart brands that never even do product photography, don't even know if they're if their stuff >> well product photography and like ecom photography is like a science and it's pretty hard to get right.

1:53:54

And there's a lot of discussion at these at these companies about how to do it, who who's going to shoot it, how it's going to appear.

1:54:01

And I think that stuff is very interesting because it directly relates to sales and like the bottom line like some styles work really really well and that's what everybody wants to mimic and some are a little a little harder to to pull off you know. >> Yeah.

1:54:13

What about on what about how do you see like you know the music market evolving.

1:54:18

We we don't cover much music >> at all.

1:54:22

Latest Justin Bieber album.

1:54:24

>> We got two two songs on the drive home. >> Check out swag.

1:54:26

I mean, we we talk about music and on how long gone.

1:54:28

All that's all we do and like a lot of my my best friends are musicians.

1:54:33

Um, most of them are successful at this point because they've been doing it long enough.

1:54:37

But I think it's like every everything else in our in our lives, I think we're just >> paralyzed by choice and the barrier of entry is just too low.

1:54:46

You know, the there's too much stuff and music suffers from that maybe more than any other genre that I can think of.

1:54:53

And you mean you mean because be you know growing up you'd buy an album, you'd invest dollars into it and so you would listen to the full thing and you'd like really pay attention to it and now if you can stream an album for two seconds and be like ah it's whatever. >> Yeah. You don't care. I mean I think yes.

1:55:10

I think that I also think that it's just if if the three of us wanted to make a song right now and upload it and have it on iTunes and Spotify this week, we could do that. >> Yeah.

1:55:18

And I don't think that I don't think the world needs that from us or from many from many other people.

1:55:23

And I I think that but yes, you're right.

1:55:25

I think when you would go to the store, um access was harder.

1:55:29

I mean, we talk about this all the time.

1:55:30

Like I grew up I remember the day that we got internet at my parents house, you know?

1:55:34

I mean, we had the Dell in the family room.

1:55:38

I remember it like the whole thing.

1:55:38

And if you remember a time before that, I think the effort that was involved to like anything or or to to understand anything was so much greater >> because you had to piece it together through like magazines and going to a show and that kind of thing. >> Yeah.

1:55:53

You go to a show, you go to magazines, you look at the liner notes of an album and see which bands get thanked and then go find those bands, you know?

1:56:00

It's like it was that it was kind of that tactile and that granular.

1:56:03

Um, but yeah, I I think it's like I I think that like Spotify and and streaming in general, like I know people that make a lot of money on streaming and they're very happy with that.

1:56:11

I know a lot of people and the the I think general sentiment is no one gets paid enough.

1:56:17

And of course, I always want artists to get paid more because they, you know, it's a soundtrack to our lives.

1:56:21

It's like important for culture.

1:56:24

Um, but I also think that people forget that these are just giant corporations and they've got bot again, they've got bottom lines and like they're going to do whatever they have to do to make that work. >> Yeah.

1:56:32

Do you think corporate jingles could make a comeback? >> They have. What do you mean?

1:56:37

I mean, you know that, you know, famously Push A Tea from Clips wrote the McDonald's jingle. >> I'm loving it. >> No way. >> Yeah. >> I have no idea.

1:56:46

>> He'll never have to work again, you know, from that alone. Yeah.

1:56:48

So, I think it all that stuff.

1:56:50

I mean, it's like the way that like John Ham is the voice of Mercedes.

1:56:53

Like, everybody gets it how they can, you know what I mean?

1:56:56

I think the jingle or I mean, what we talk about a lot on How Long Gone is like sync culture, you know?

1:57:02

on like how there used to be like a you would be a sellout, you know, if they used your song in a in a Jack in the Box commercial.

1:57:09

And now it's like, well, that's the most money I'm going to make.

1:57:13

If they're going to give me a quarter million dollars to use my song for 30 seconds, like, I have to do that.

1:57:15

You know, the choice isn't isn't quite as clear as it used to be.

1:57:19

And so, we've talked to a lot of different musicians about regret.

1:57:22

You know, how they like pass something up because they were high on their horse in their early 20s and now that they're 40, they're like, I'm a idiot.

1:57:28

Like, was it was half a million dollars. Like, who cares?

1:57:33

>> Yeah, that makes sense.

1:57:34

>> You wait, you said that they've made a comeback already.

1:57:35

Like, is there a more modern example than the than the McDonald's song?

1:57:40

>> I I mean, I feel like you might be right.

1:57:43

I I feel like they're just they're ingrained in my brain, so they feel new totally, but like >> Cars for Kids or something is probably 20 years old.

1:57:51

If you guys ever lived in New York, there's 1877 cars like you. >> Yeah. No, I I Yeah, I know it.

1:57:56

Well, I'm just thinking about like of the new companies that have emerged.

1:58:00

Airbnb, Facebook, Instagram, Spotify, Open AAI, like SpaceX, like Tesla doesn't have a jingle.

1:58:08

Like like I I don't know if those would be even like on brand, but like even funny even even like Prime from Logan Paul like he he's done a song like he did he did like it's everyday bro with his brother I think or maybe that was just his brother but uh you know like there are influencer brands. Mr.

1:58:24

Beast has a a chocolate bar.

1:58:24

I don't know that it has a a jingle and I'm wondering if it has something to do with the fact that like the nature of advertising has become like way longer tale in this in the in the creative like we we don't see that many like shelling points for like wow they made an iconic ad it ran at the Super Bowl everyone's talking about it.

1:58:45

It's more like they spent the same amount of money on ads but it's just in the form of a thousand different Instagram ads and everyone saw a slightly different one that was more tailored to them.

1:58:55

So the guys saw the one >> potentially alpha making a jingle right now and using the same jingle on like thousands of different creative.

1:59:02

So it's always the same audio and different and then >> I think we're on to something here. Time is money. Say both.

1:59:11

>> Find your happy place.

1:59:12

>> I mean with car companies they they obsess over like the sounds the cars make.

1:59:16

You know you know what I mean?

1:59:17

Like I drove this new Mercedes from Atlanta to um Miami for the F1 and it was like there was all this detail.

1:59:26

>> I'm a huge Mercedes fan.

1:59:28

>> We love Mercedes over here.

1:59:30

>> We We have tons of them.

1:59:31

>> I'm in I'm in Bedford, New York right now and I borrowed a a CLE AMG convertible. >> Couldn't be better.

1:59:40

>> But I just notice all the But when you drive these car, you notice like these little kind of sort of >> Yeah.

1:59:45

brand moments where it's like a little noise when something starts up or like it is audio or like how famously like Porsche has a guy whose only job is about like the way the door sounds when it closes because it sounds so much better in a Porsche than other cars, you know?

2:00:00

But it but it's just a funny I think there is these audio elements that are happening from a brand standpoint, but they're not quite as overt as a jingle, you know? Yeah. Yeah.

2:00:08

It does feel like uh Doug Demiro has this take that like power is on demand.

2:00:13

Like the latest Rivian truck, electric truck has 1,200 horsepower.

2:00:19

It's the same as a Bugatti Veyron.

2:00:22

Like it is it like you can't go any That's what you want. >> Is Rivian a sponsor? Is Riven? >> No. No, no, no, no. >> All right.

2:00:31

cuz that Rivian is Rivian's like the that that is like the Austin mesh hat yet Yeti cooler of cars and I just don't I don't get the popularity.

2:00:39

I don't think it looks good.

2:00:41

I mean I guess it's an alternative to Tesla.

2:00:42

guess it's an alternative to Tesla. So that's part of the >> Yeah, I I think the main thing was that like Tesla hadn't come out with a with a truck yet and then they came out with a very controversial design and then the

2:00:53

F-150 Lightning was pretty expensive and the Rivian kind of was just pure play like didn't confuse anyone and and then they did have the full size SUV or like close to full size SUV in the electric category a little bit sooner than the Hyundai Ionic 9 and a couple others. It

2:01:04

It it says a little bit more, but uh it is interesting because between Lucid and Riven and Lucid and there's that >> Pstar.

2:01:16

Pstar is technically like a Volkswagen or >> Oh, is it?

2:01:23

>> It's It's not Volkswagen.

2:01:23

It's the Volvo like Volvo.

2:01:26

>> I I go to I go to Copenhagen Fashion Week a couple times a year and it's all and the drivers are It's all polestar.

2:01:32

It's all >> I mean, every brand is confused with what to do with electric.

2:01:34

Like it's like do we throw a is it a is it a powertrain and we just throw a little I at the end or an X or an E at the end or do we do a whole new subbrand or do we spin something out?

2:01:45

>> Oh, what do you have you seen that?

2:01:45

Have you seen the new the new Lamborghini?

2:01:48

What is What is the the EV? >> Oh yeah. What was that called?

2:01:52

>> It's called the >> Why do they have to make them look like Lanzador? >> The Lanzodor.

2:01:55

You got to pull up a picture of the Lanzador. This thing looks wild. >> It is. >> What is it? What is it? A Lambo?

2:02:02

>> Yeah, it's a Lamborghini Lanzador.

2:02:04

They they're calling it an SUV, but it just looks like a really big car. >> Like a lifted sedan.

2:02:10

>> It looks like a lifted No, it looks like a lifted. >> It's kind of sick. It's kind of sick.

2:02:15

And then there's the slate truck which is coming out which is like the small thing, but but I think that some of the new companies like they're so focused on like just deliver on the basic value prop.

2:02:24

They're not in that like surprise and delight category yet.

2:02:25

Although Rubian did kind of do that with like that gear tunnel.

2:02:29

you you know about that in the >> I don't know anything I like Okay.

2:02:32

Yeah, that is a that is just a a big old car.

2:02:36

>> Yeah, it's a big car, but they're calling SUV, >> guys. Like a Subaru. No joke.

2:02:43

>> No, that's that's the uh that's like a Subaru Halo car.

2:02:46

Like that that should be there. Subaru.

2:02:49

>> Uh uh total uh total tangent, but I did have uh one question and then one idea that I wanted to throw out before before you jump.

2:02:58

Do you think that any social media apps will become truly Lindy?

2:03:01

Like will we be on X like 30 years from now chopping it up on the timeline or >> as a as a I call it Twitter still.

2:03:10

I'm a I'm a traditionalist but for this purpose I will call it X.

2:03:14

I X is the most enduring platform that we have because I think it's not imagebased.

2:03:18

I think that's what sets it apart.

2:03:21

think that's what sets it apart. it it feels more comedy and information and those are two things that I feel like aren't as affected by trends in some ways whereas like Instagram I love Instagram I use it every day but like >> people get when people get very exhausted by it because of what they

2:03:39

have to see you know I think Twitter I don't know I'm a I'm a Twitter die hard I'm a power user I have been forever um and I will never change that >> that's awesome >> I hope yeah it's one of those things like is is is it digital news or is it like the form is it its own like form factor like vinyl that will just perpetuate forever. >> We're gonna find out. >> We're gonna find out.

2:04:01

>> Last uh last question, media media and entertainment question because you're an entertainer.

2:04:05

Do you think there's room in the market for uh next election cycle?

2:04:10

Uh pay-per-view boxing between both political parties.

2:04:13

So, so, so like Democrats versus Republicans betting on the line. Very American.

2:04:19

I'll pay I'll pay $100 for the PPV for that.

2:04:22

I mean, I think that I I don't think we're that far away from honestly. I know that's a joke.

2:04:29

I don't think we're that far away. >> No, I'm not.

2:04:30

I'm actually I think every four years you get 10 10 Dems, 10 Republicans, get them lined up in different weight classes, $100. Duke it out. Settle settle it.

2:04:42

>> I would I would love to see some low-level, you know, firstear senators just bloody themselves in the on the on the opening round, you know? That's what we need. >> Yeah.

2:04:50

doesn't even it could just be angry online posters too, you know, settle.

2:04:54

>> Well, that that's a that's a a category of fighting that has not been monetized yet.

2:04:59

Something we should think about. >> Yeah.

2:05:01

It's like Dana White's slap boxing thing or whatever.

2:05:03

No, no experience required.

2:05:06

>> Slap boxing would be huge. >> Awesome. All right.

2:05:08

Well, this was super fun. Come back on again soon. >> This is great.

2:05:12

We'll talk anytime, guys. Thanks so much. All right. Have a good one.

2:05:15

>> Good luck with the rest of your live shows.

2:05:16

We were talking about jingles.

2:05:16

We got to sing you a jingle.

2:05:20

>> Find your happy place. Find your happy place.

2:05:23

Book a wonder with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and 247 concier service.

2:05:28

It's a vacation home but better, folks.

2:05:31

>> And Chris Buskerk is in the reream waiting room.

2:05:34

>> Let's bring in Buskerk. How you doing, Chris? >> How are you? >> Great.

2:05:38

>> Hopefully you got to hear us singing just now.

2:05:40

>> We're we're trying to bring back corporate jingles.

2:05:41

We think that there's an unexplored territory there.

2:05:43

I don't know your stance. >> 1789. Ooh, we got something.

2:05:49

>> I know why we don't I actually know why we don't have them anymore. >> Please explain.

2:05:52

>> It's because big pharma took over advertising and that killed all the creativity. >> Oh, interesting. Yeah.

2:05:57

And they got to throw those. >> Yeah.

2:05:58

Now it's like you got a 40second commercial.

2:06:00

20 seconds tells you all the bad things that are going to happen to you when you take the drug. >> It's rough. >> Well, yeah.

2:06:05

So, so, uh, the conspiracy theory there, I don't have my tinfoil hat handy, is that, uh, it's not about even generating awareness. Here we go.

2:06:13

even generating awareness. Here we go. I got we keep one of these anytime we have to >> discuss a conspiracy theory >> discuss discuss a conspiracy theory it gives you cover you know I don't I don't believe this necessarily but uh you you listen to these pharma ads and they're

2:06:29

after after listening to it I would say you're much more likely to think I don't think this I don't think this is for me right because you maybe hear about some benefits and then you get like 20 seconds of of but it's just it's it's is it a mechanism to just invest so many

2:06:44

dollars in a show that the show could not possibly criticize >> the the the far the pharma industry broadly otherwise you're potentially >> is this manufactured consent says Nam Chsky but has been written rewritten >> well it's more like it's more like yeah you're welcome to criticize big pharma

2:07:02

but like say goodbye to like what 60% of your revenue overnight anyway >> not going to be running the show >> we're not going to be talking about more conspiracies >> anyway let's kick it off with an introductory >> theory is always also known as the news six months in the future. Yeah. Uh but but uh let's Yeah.

2:07:15

Uh but but uh let's introduce yourself.

2:07:18

Uh how do you think about yourself?

2:07:20

What what what uh what what key projects are you working on right now?

2:07:24

right now? you know, it's uh you know, co-founder of 1789 Capital as you guys know, like I've got some other evocations as well, but you know, just you know, I people always say like how do you split up your time and uh like >> there was like the that was like the

2:07:38

Rubik's cube question for me for a while and then I realized actually the uh the simple answer is right, which is like all the different stuff I'm doing is all the same project which is how do you keep the country peaceful and prosperous? Like that's really it. Then Like that's really it.

2:07:50

Then there's all kinds of different vectors of attack there.

2:07:53

There's like there's politics, there's culture, there's business, there's tech, but it's really all with the same tilos.

2:07:59

Like how how do we just make life better for this country and the people in it? >> Yeah.

2:08:05

Give me a give me a temperature check on your view on the business climate.

2:08:09

There's been so many new so many stories about tariffs and interest rates and all sorts of stuff.

2:08:13

At the same time, the stock market's been like down and then right back to where it was.

2:08:20

And so there's like the nothing ever happens view.

2:08:21

There's the incredibly tumultuous times view.

2:08:23

How are you just feeling about the business climate generally? >> And it's amazing.

2:08:28

It's like it's better than it's been in a long time. >> Yeah. >> Yeah.

2:08:32

>> Yeah. I mean this is what you know I've had I I've had the following conversation uh it probably literally like 10 or 20 times in the past few months >> and people uh whether a lot of investors but also founders builders have said a a different version of the same thing

2:08:48

which is >> uh I didn't know how much I was self-censoring my own thought about what was possible over the past four or five years until you know fill in the blank January February March April whatever just some this year and Then they realized like, oh, the shackles are off. We can actually go and do really cool

2:09:04

We can actually go and do really cool stuff now.

2:09:06

Um, and there were they everybody had their project like there it was like there was a pain point in their business like oh I can't do this or like you know like the crypto guys or AI like they're really really under under attack you was like regulation by enforcement.

2:09:19

Y >> um and so they knew what the pain points were and so for obvious reasons were super focused on those things and they were like oh if we could just get through this then we could do this one other thing whatever that may have been.

2:09:30

And what I've heard them what I've heard a lot of people saying is once the pain stopped I realized that there were like 10 other things that not only did I want to do but that I could do.

2:09:38

And so like the amount of optimism and energy is just really infectious.

2:09:42

It's like it's a great time to be alive. >> Yeah.

2:09:46

It feels like I mean we saw that with a lot of the nuclear founders like you talk to those folks and I mean it was so rough for a while that they normally like if you invest in my company I don't want you to invest in a direct competitor but the nuclear companies were like look like that's not going to be the thing that does me in like you can go ahead and invest and then now we finally have some clarity from the EO.

2:10:07

We talked to some nuclear founders and it feels like we're on the cusp of some real progress there.

2:10:11

Um how much are you focusing on energy?

2:10:14

What are the other categories that you find uh interesting right now?

2:10:18

What do you see as being like uniquely unlocked uh in this new era?

2:10:24

>> Yeah, it's we call it the and I don't think we made it up but like we call it like transformational technologies.

2:10:27

So that means like AI AI infra uh energy robotics space defense that those are kind of like the big buckets.

2:10:35

In a lot of cases there's a lot of they're they're really related.

2:10:38

Um, you know, we like the way at least the way we think about energy is like it's attached to all of those. Sure.

2:10:44

all of those. Sure. Um and you know that's where that's where nuclear really comes in but particularly around AI and uh crypto and some of the other elements of just security in general like that is the major unlock like one of the things that I tell people all the time is you

2:10:59

like if you want to like a just an easy heruristic about like you know how you think about like what are the big unlocks that need to have happen which is that think about it this way the large civilization that has access to the most abundant cheapest energy wins like period. full stop. Um I was talking full stop.

2:11:15

Um I was talking with a friend of mine, another investor last week and I he actually had he had this great um description which I had actually never thought of about colonization of Mars because I was saying how you know like you obviously Elon's been super focused on it and I'm like I don't want to go to Mars.

2:11:31

Like I've never wanted to go to Mars.

2:11:33

It seems like it seems like it sucks there.

2:11:36

I said but then I realized um >> that actually like terraforming Mars like that's actually kind of cool because it would make it someplace you'd actually want to go.

2:11:43

actually want to go. So that's why like Mar like Mars colonization's become charismatic because like just like getting to the moon was was interesting and charismatic um in the '60s because it was like can we get there like it was

2:11:55

just the it was just like the journey not the not the end but then when you start to think about the idea of uh of of colonization of Mars well it's interesting when you think that like you could make it beautiful and he and what he said was it's just an energy problem. If you can bring enough energy to bear,

2:12:09

If you can bring enough energy to bear, then you can terraform then you can terraform Mars.

2:12:14

I was like that was actually for me that was like an interesting way to think about it that I hadn't considered.

2:12:18

But the same thing applies to everything else which is if you have if you have super abundant super cheap energy you're as a as a large scale civilization you're going to win because it makes everything else better, easier, cheaper and things that were not possible it makes them possible.

2:12:35

kind of like the way SpaceX what SpaceX has done with launch by just driving the cost per kilogram into the dirt there it unlocks all these other businesses.

2:12:45

>> Yeah, it's fascinating.

2:12:46

>> So if if great power competition is is energy competition do do we you know I mean that the concern here is that China is just like copy and pasting nuclear reactors and we have a bunch of great nuclear startups that are you know making efforts and some new projects.

2:13:03

I think Meta, you know, has announced some some new initiatives there.

2:13:07

Um, but is this not like one of the kind of biggest issues that we're facing from a national security standpoint?

2:13:17

>> There's a way in which it's the biggest because it because it touches everything like it touches literally everything.

2:13:21

I mean you think about like these really critical growth areas AI being the super obvious one but uh you know and there's you know I've seen a number of um analyses that show like the the amount of uh AI compute we need to build just in this country like say in the next 10 years so by 2035 like it would consume more power than we produce right now >> as a country.

2:13:44

So there's like we need to be producing a lot more power because unlike certain members of Congress, it turns out electricity doesn't just come from the wall.

2:13:52

Like you actually have to produce it uh someplace. >> Yeah.

2:13:55

Food comes from the grocery store.

2:13:57

Gasoline comes from the pump.

2:13:59

Electricity comes from what are you slow?

2:14:01

You just plug in just plug in and there's electricity there.

2:14:04

>> I I do think there's something there's something fascinating about like it's so hard to predict the future.

2:14:08

It's so hard to predict what we will need, you know, a gigawatt, you know, data center for and then all of a sudden it's like we need it today.

2:14:17

Like we have the use case, we need it today.

2:14:18

Um and and I keep thinking about like what happened in the dotcom boom where we overbuilt all this dark fiber.

2:14:23

Google went and bought it up and a bunch of the tech companies bought it up and then eventually like the the the products caught up.

2:14:29

caught up. My my question is um how do you think about projects that might be uneconomical to underwrite on the venture side and so they might need to be underwritten by the government like like I'm I feel like we're probably align in that like we should probably keep the government as narrow as possible but there are some really crazy

2:14:51

things like the moon landing like the Mars helicopter stuff that just doesn't make any sense for any private company to go after and then after a while you start seeing saying like, oh, okay, like, you know, they built some roads, they built some infrastructure, and now private companies are catching up and and actually ramping up the the the use of that energy or something. But how do

2:15:08

But how do you see the government playing a role in the next in solving those fundamental problems?

2:15:16

Is it purely just on deregulation?

2:15:18

Do you want to see funding flow into certain projects?

2:15:21

Do you want to see government doing hard projects?

2:15:26

What how what's your philosophy on all that? Yeah, it it's it's both.

2:15:28

It's both is the answer is like we've just seen, you know, just as I was saying earlier, like just this year just by getting out of the way unlocks a lot and it just there's so many people >> um who want to do things and who have the capacity to do things if they're not being shackled and prevented from doing them.

2:15:45

So like we've seen a lot of that in the past six, seven months is just by getting out of the way and giving people permission um to do it, you get a lot of you get a lot of activity.

2:15:55

And so that's a big part of it.

2:15:57

But then there there are these other issues um where you know China creates its national champions.

2:16:04

And so like great example is like rare earth magnets.

2:16:05

You know it is it can be um it is I mean they subsidize it.

2:16:09

So it is cheaper to buy a rare earth magnet from Chinese supplier than it is to buy the raw materials in the United States.

2:16:19

>> You know it that is I mean that's very it's that's geopolitics right? That's not just markets.

2:16:23

That's not just economics.

2:16:24

That's not just innovation, that's geopolitics.

2:16:27

The the Chinese have been on they've been on top of this for 20 years and realized that this was a choke point where they were would be able to get a huge amount of leverage over their competitors and adversaries.

2:16:37

Um, and I guess we're someplace in, you know, in between those two things with with China.

2:16:43

And if they were able to subsidize them, they could drive out all the compet the competitors out of business.

2:16:48

business. and because they go into literally everything of any importance that they'd have massive um not just economic leverage but like geopolitical leverage over the United States and so that's a place where you know government needs to play a role because it's not a company v company competition it is a state actor v company competition as it stands right now and that's something

2:17:10

that's critical to national security so you see that I think in a a number of other a number of other spaces but you know the rare earth magnets is like it's just a very obvious example of that where you can't um like a company can be super innovative and can do all the right things but if it is facing a state actor as its competitor versus another company like they're going to lose. >> Yeah. On the rare earth materials >> Yeah.

2:17:33

On the rare earth materials question, uh there was a story in the Wall Street Journal last week about Apple buying half a billion dollars of rare earths from a company called MP Materials and in Vegas and in Las Vegas.

2:17:48

And it stuck it stuck out to me as kind of a vibe shift because Apple hasn't been at the front of like re-industrialize America, bring back jobs, and you know, let's make everything in America.

2:18:00

They're not saying that, but it feels like maybe behind the scenes they're at least thinking about their supply chain very seriously and trying to diversify and maybe it's a cruise ship, but they're putting their hands on the tiller just a little bit.

2:18:13

And so I took that as like cause for optimism with the overall, you know, energy independence, supply chain independence, but did you see that story?

2:18:22

Are there any other causes for optimism that might be coming from the the the crowd that's not cheering as loud as they can but might be getting, you know, might be working behind the scenes to kind of achieve the same goals that everyone should be aligned around? >> Yeah.

2:18:36

I mean, look, there's a there's a lot of signal, I think, in that in that move.

2:18:40

I mean, they uh at some point Apple has to realize that their supply chains are really really insecure.

2:18:44

And this leads to like another point on the rare earth magnets.

2:18:49

Like one of the things like the one of the what great sort of unintended consequences of uh the liberation day tariffs and the and the general policy of tariff policy coming out of the administration is that this actually was turned out to be a forcing function.

2:19:06

It made China play their rarest card way too early.

2:19:08

um had they decided for instance to attack Taiwan and then played that card that would have been the optim optimum moment.

2:19:16

But what happened was is that in the negotiations around tariffs they they threatened to play the rare earth card.

2:19:25

In fact they did actually like reduce exports uh the past couple months but it was too soon like they they played it early and now there's time for the United States um to catch up.

2:19:33

And this is, you know, in fact, as we saw with MP, you know, and the support they've gotten from the government, another company that we're in the process of investing in called Vulcan Elements is uh is in the space as well.

2:19:46

>> Um, and we now have a window in time where we can build out an ecosystem to manufacture rare earth magnets in the United States and do it really really uh quickly.

2:19:56

So that that's just a place where like there's like there's there's a lot of signal coming out around that as well.

2:20:04

But there's I think the the fact that there is so much happening and uh and at such a rapid rate that's where we're seeing um but that's where we're really seeing the advances here because like I don't know like people ask me like you like are you pleased with the way the admin's gone? Yeah, I am.

2:20:20

Um, what I've been surprised by though is the speed with which they've moved.

2:20:25

And what's happened is like they're moving at like founder speed and that that becomes infectious.

2:20:30

And so now you get you get cycles uh that might have taken a year or two or three to to happen and work things work through the system um in the past and now like we see we're I mean we're standing up a rare earth's capacity in in the United States basically overnight.

2:20:44

That was like a pipe dream four or five months ago and now it's actually happening.

2:20:50

>> We got to stop calling them rare earths. They're just Earth's.

2:20:52

They're just Earth's magnets. >> They're not rare. They're not rare.

2:20:55

They're They're only The process form is rare. >> Yes.

2:20:57

The industrial capacity is rare, but the product is not.

2:21:00

Let's just call them Earth. >> It is. It is.

2:21:03

You got to You got to uh you know, we we probably criticize uh China more than than most podcasters on Earth.

2:21:11

But you got to give them credit for letting the world think that they were just the Happy Meal toy manufacturing hub for like a couple decades and then just like quietly owned, you know, all all these critical supply chains.

2:21:25

I'm curious how you're thinking about solar and >> one of the reasons I ask is I've invested in >> tons of these different kind of hard tech uh new industrials categories and I've yet to back a solar company.

2:21:39

I only, you know, started actively angel investing maybe four or five years ago and it's fallen out of fashion is one way to describe it.

2:21:50

>> Hammer's bringing it back. >> Yeah.

2:21:51

So, Casey is the only Casey's the example and I would I would happily invest in Casey if I had the chance, but >> curious how you're thinking about that.

2:21:59

It's another area that China is dominant in and it seems like something that we >> wouldn't necessarily want long term.

2:22:07

So, like I've been sort like semiobsessed with solar for a long time.

2:22:12

I just like it's mostly just basically being like thrifty.

2:22:14

I'm like, damn, there's all that sunlight and I can just power my house for free, you know?

2:22:18

So, like like I like at my house in Arizona, I have solar on it. I've had it for years. Okay.

2:22:25

But it's really not economic.

2:22:27

Um, and so there's needs to be a pretty big leap forward for it to for it to matter.

2:22:32

Otherwise, why not just build more nuclear, >> right?

2:22:35

Why not why don't we just keep it simple? >> Yeah.

2:22:38

Casey like PV solar actually isn't that good and like the concentrators are like okay >> but like again like we have the solution already.

2:22:47

So there's got to be a compelling case to be made as to why um under the current like uh you know with the current technology around solar why is that even worth focusing on? >> Interesting. Yeah.

2:22:57

Casey's point was like China is subsidizing photovoltaic manufacturing and and the and the most hurtful thing you could do is just buy all of it to so that they take a loss on every unit and then build up your capacity.

2:23:11

But I don't know that that actually would would would catalyze a real shift in capacity and we might just get kind of hooked >> still helping them get extremely good at >> especially if there's learning curve and stuff. So, I don't know.

2:23:22

It's a it's a longer >> conver and PV is just not that efficient, right? That's the problem. >> Yeah.

2:23:28

I I think the I think the the argument was that it's like it's very well matched to the load of the grid of the American consumer because when it's hot out we run our air conditioning and when it's hot out the sun is shining on the PV cells and so there's some match there whereas a nuclear power plant generates just as much at night as it does in the day.

2:23:47

does in the day. So I don't know there there's a whole bunch of different load use cases for AI training versus inference and all this different stuff but um it's uh yeah it's f it's a fascinating geopolitical dynamic and it

2:23:59

seems like the main takeaway is that China has just been saying yes and to everything and and they develop capacity everywhere and and it's like we could try and predict the future but you know if PV winds up being really important I want to have capacity for that. If

2:24:13

If nuclear I want that too.

2:24:14

I want I want the smores board. give me all the energy.

2:24:18

But I don't know, >> you're building a ton of coal plants, too. >> Yeah. Yeah. No, 100%.

2:24:21

And like fortunately, you know, uh some of the AI uh infrastructure buildouts are are pulling forward some of that.

2:24:27

We're getting a whole bunch of natural gas online.

2:24:30

Like we are becoming more energy independent.

2:24:32

So, uh green shoots all over the place. Jordy, anything else? Last question.

2:24:36

>> I think that's it for now. >> This was fantastic.

2:24:37

Yeah, we got to have you back on, especially when there's like big news in your world or anything going on that you can comment on. >> Anytime. Happy to do it.

2:24:44

>> We need uh we just need 30 seconds notice.

2:24:46

We'll drop you the We'll drop you >> We'll drop you the link.

2:24:48

You can just hop right on. >> Okay, awesome.

2:24:50

Yeah, just you can signal me. Signal me. I'll be on. >> I will.

2:24:53

I'll talk to you soon, Chris. Have a great day, Chris. Cheers. >> Bye.

2:24:57

>> Uh, >> and speaking of minerals, we have uh >> adquick. com.

2:25:02

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2:25:03

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2:25:14

What were you saying about materials?

2:25:15

Well, we have the founder of Mariana Minerals uh joining the show.

2:25:20

>> Welcome to the stream. Hit the soundboard. Give me the Ashton Hall.

2:25:24

>> Welcome to the stream. How you doing, Turner? >> Good. How you doing, guys?

2:25:29

>> Beautiful map behind you. I I I love cgraphy.

2:25:31

Uh I'm a big fan of of of throwing a map in the background.

2:25:35

>> Is that 3D or like does it have texture or does it just kind of look it look like?

2:25:39

>> Uh it's got a little bit of texture. >> Good.

2:25:42

>> Not not crazy 3D though. the Mercer projection.

2:25:44

I'm pretty sure it's a good one.

2:25:46

Anyway, introduce yourself. What do you do? Welcome to the show. >> Yeah, sure thing.

2:25:50

Thanks for having me on, guys.

2:25:52

Uh Turner Calwell here, CEO of Mariana Minerals.

2:25:54

Uh we're a vertically integrated software first mining company.

2:25:59

So, we're coming into projects uh that are, you know, have post exploration.

2:26:04

They've discovered the mineral deposit.

2:26:05

Um and we come in to engineer it.

2:26:09

So we develop the mine plan, we develop the refining plan, uh we capitalize it at the project level and from the top co and then we we manage the construction, we manage the constru the commissioning and then we operate it out into perpetuity. >> Okay.

2:26:22

Talk to me about the whole pipeline of actually getting minerals out of the ground.

2:26:28

Let's say I own a 100,000 acres in Alaska or something.

2:26:29

I bought it just as a forest.

2:26:32

It's a ranch, never explored it. What are the steps?

2:26:36

I imagine we're talking about like a decade, exploration firms, then you come in at some point.

2:26:41

Like really walk me through a concrete example of going from like someone has some land to now we're getting material. >> Well, yeah.

2:26:49

And if if you're this verticalized, why not also do discovery?

2:26:54

I'm sure there's a reason.

2:26:54

I'm sure there's a reason.

2:26:56

>> There's a there's a there's a big market of folks that are doing discovery and there's actually a bunch of awesome like tech VC backed startups that are focused on accelerating discovery.

2:27:02

I think what we're missing is folks that are focused on condensing the timelines from when you have discovered something to when it is actually producing and it's like this snake in the grass kind of challenge like very complicated system of actually designing these plants, flying out all the infrastructure, installing the infrastructure, getting it running.

2:27:20

>> Um but yeah, so you start with a you know flat piece of land, ideally it's flat.

2:27:23

Um, and you'll start this like really long campaign of, you know, you'll start with kind of like spot testing of different areas to determine and probably some like surface sampling to determine if there's something promising there.

2:27:35

>> Uh, there's some permits that come into play when it when it when you have to actually start doing more advanced exploration campaigns and that's something that, you know, if you're on federal land and sometimes on state land, those permits can get in the way of of accelerating kind of mineral discovery.

2:27:46

Um, you'll do drill holes, uh, you know, hundreds to thousands of drill holes to define a mineral deposit.

2:27:54

Um, and those mineral deposits can vary all over the place.

2:27:56

You can have shallower ones where it's a little bit cheaper to drill.

2:27:58

You can have really deep ones where it starts to get much more expensive to do and timely time inensive to do that expiration campaign.

2:28:05

And all along the way, you are taking samples uh, and you are kind of building these three these 3D models to try to understand how was the deposit formed, why is the mineral there in the first place?

2:28:16

And that helps to kind of inform also the the advancing the expiration side of things.

2:28:20

And in parallel with that, you're starting to do these testing campaigns where you're running concentration tests to figure out how you can upgrade the ore to an intermediate product.

2:28:28

Uh you're starting to do refining tests to understand how you would actually extract the target mineral into its final state, which is, you know, a high purity metal alloy in many cases.

2:28:37

Um or a or a a high purity kind of specialty chemical salt.

2:28:40

Um and so you're writing these reports all along the way.

2:28:44

So you'll start with a um a pea which is an initial economic assessment.

2:28:49

You'll then do a prefeasibility study.

2:28:50

You'll do a feasibility study.

2:28:52

You'll do a definitive feasibility study.

2:28:53

And kind of as you're doing that, the value of the asset is kind of increasing and increasing.

2:28:58

Speculators are piling into the stock.

2:29:00

Um and the intent there for the specs, >> the backbone of the backbone of the mining penny stock rippers. That's right.

2:29:10

And that that's how that exploration is is funded really.

2:29:11

They're trying to like ride that first wave of value creation. >> Yeah.

2:29:16

Similar to like FDA trials for new pharmaceuticals probably.

2:29:19

>> Well, I can and I can I can I'm starting to figure out, you know, a number of reasons while you're explaining them why you wouldn't want to do the exploration and discovery is because that could take like 10 years and then he goes on to describe the hardest thing in the world.

2:29:32

>> Well, yeah, but then but the other thing is like the duration ideally you start working with a customer and they're like, "Here's what we have in the ground. Help us get it out."

2:29:40

And then you can just start doing that. >> That's exactly right.

2:29:42

And that's that's how we're thinking about it is we want to be the ones that go from uh you know the folks that are doing the expiration, they're they're there to define the resource and ideally get some return on the invested capital that they had as they were kind of like going through this like long and arduous process of defining a mineral resource.

2:29:59

>> But typically those are geologists, financiers, lawyers.

2:30:01

Um it's very rare where you'll see a a junior mining company that's actually staffed to take it all the way through to production. Mhm.

2:30:09

>> Um it's a it's a different class of business fundamentally like you're dealing with in in say like very high capex deployment uh complex kind of mining and and refining systems that you know span the the uh the entire ecosystem of like engineering skill sets, commercial skill sets.

2:30:23

Um and so there's a nice handoff point there.

2:30:26

And so what happens today is the junior mining companies will spend a lot of time exploring.

2:30:30

They'll increase the value of the asset.

2:30:31

Ideally, they flip it to a large mining company that comes in to do the hard yards of actually getting the thing operating.

2:30:37

Um, and that's where we want to come in as well.

2:30:41

So, uh, you know, the big mining companies, they're looking for billion dollar opportunities to deploy billions of dollars of capital.

2:30:47

Um, and you know, they they pick their spots on the commodities also.

2:30:51

So, you might have a commodity that's out of favor and so no one's picking up the asset.

2:30:55

You might have an asset that you know would be called subscale in this scenario where it's not a billion dollars of capex.

2:31:02

It's only a couple hundred million dollars of capex. Still a big project.

2:31:05

Um and those are getting ignored.

2:31:05

Um and so we think that with the differentiation on the tech stack on the software side of things that we're bringing in and also a differentiated team, we can bring these smaller scale assets which are like right sized for us as a as an early stage company um into production while they've been kind of ignored by the big mining companies. >> All right.

2:31:23

Uh, one more question and then we'll talk about the news today.

2:31:26

But when did you first yearn for the mines? >> For the mines.

2:31:31

Um, so when I graduated college, I actually had this like vision of moving to Australia and going and working in the mines.

2:31:37

I never quite quite like converted on that.

2:31:39

Um, but uh worked at Tesla for nine years and change.

2:31:44

Um, started out up in Reno, was working on the gigafactory up there, kind of like designing, building it.

2:31:50

then started working on battery cell manufacturing, started working on areas of the cell chemistry, uh, and in the supply chain side of things.

2:31:55

Um, and as I was moving kind of further and further upstream, you know, the the mining industry is is wild.

2:32:01

It's an awesome industry.

2:32:04

Um, but it's definitely been neglected.

2:32:06

Like, we've kind of been viewing it as dirty and, you know, it should happen.

2:32:10

It should it should happen, but it shouldn't happen here.

2:32:13

Um, and it's also like this massive it's this awesome opportunity to work across scales.

2:32:17

scales. like a lot of what you're developing starts at like the micron scale of like how do I get this atom out of this other atom well not atoms but this like atom out of this mineral >> um and then you have to scale that up to like kilometer scale infrastructure um

2:32:31

and like that breadth of scales is awesome >> that's really cool >> what's the uh news today if I might >> yeah so we're ah there we go um we're coming out of stealth with our series A raise we had uh Andre's coast ventures breakthrough through Energy Ventures and a couple of other folks join in. We've raised $65 million

2:32:48

We've raised $65 million today.

2:32:54

>> So, >> first uh first hit of the week. >> Feels so Feels good. >> Congratulations. Fantastic news. >> Fantastic.

2:33:03

I'm uh last question before you jump off.

2:33:05

Are you are you guys like acquiring any companies uh or or is it fully ground up? You're just >> Yeah.

2:33:12

So, we we'll we'll we'll step in and we'll acquire uh mineral assets.

2:33:14

Um that that makes sense for us to step into.

2:33:19

We're working on that in the copper space right now actually.

2:33:22

>> But that's like buying the land, not necessarily like basically buying the resource itself, not like a surrounding company or maybe it is structured as >> Yeah.

2:33:30

So, it'll it'll it'll it'll vary.

2:33:32

There's a lot of mining projects that are on care and maintenance that, you know, h have were turned off and could be turned back on with, you know, if you come in and retrofit to deploy kind of like the reinforcement learning platform that we're working to deploy, which means you need more instrumentation, you need more control to be able to control the the big refinery, which is basically a big robot.

2:33:47

Um, and uh in certain cases, it it might be a a mine that's actually operating today that we can step into and we see opportunity for uplift.

2:33:56

Um and in other areas it'll be a green field asset where you know we're stepping in and partnering in partnering with the resource owner.

2:34:02

Um and then we would have a cash flow uh split kind of once we bring it to commercial scale so that they can keep exploring and you kind of create this flywheel where they're continuing to explore.

2:34:11

They're leveraging cash flows from operating assets uh to to fund their exploration and then we would step in to to develop those those assets over time.

2:34:19

Um, so it's pretty variable, but yeah, we have >> So basically the market the market prices certain assets here and you guys look at it and say with our technology this is actually worth, you know, some some premium on that. >> That's exactly right.

2:34:33

And in certain cases, the market will say that there's no net asset value or no no NAV.

2:34:36

Um, and we'll and that's an area where you can kind of step in and and get a good deal and bring it into bring it into production.

2:34:45

>> He's a value minor, >> value investor. Um, this is super cool. Congratulations.

2:34:49

We uh I imag like we're going to do a lot more on uh rare earths broadly.

2:34:55

So uh we're going to stop calling them rare because we got plenty.

2:35:00

We're just going to call them earths.

2:35:01

>> There are a lot out there.

2:35:01

They're they're hard to find in high concentrations and and hard to get out, but they're they're out there. >> Awesome.

2:35:07

Well, congratulations uh to you and the team on the raise and uh hope hopefully have you back on soon.

2:35:12

>> We'll talk to you soon. >> Awesome. Appreciate it, guys. >> Cheers. >> Eight. Go to eight asleep. com. Get a Pod Five Ultra.

2:35:18

They have a fiveyear warranty, a 30- night risk-free trial, free returns, free shipping. >> Get an eight sleep.

2:35:24

We have our next guest coming in the studio.

2:35:29

>> I got to give people the I'm so into the show.

2:35:32

>> My HRV thinks that I'm done.

2:35:32

So, thank you to my sleep for getting into saving my life. >> Lifeaving technology. You heard it here first. Not a health claim. Not a health claim. >> Not um awesome.

2:35:46

We have >> Ask your doctor about saving your life with an eight sleep.

2:35:50

>> Uh I'm going to uh botch his name. Jaman Champman.

2:35:54

>> Let's bring him in from alimter. >> There we go. >> How you doing? >> Good. >> What's happening? >> How you doing? >> Great to be here. Kick it off. Great to meet you.

2:36:01

Sorry for uh for botching your name on the way in.

2:36:04

>> No, no, given name is Benjamin. >> Benjamin.

2:36:08

>> My parents called me Jamon as a toddler.

2:36:11

>> In kindergarten, there were a bunch of Benjamins, so they just told my teacher, "Hey, call him Jamon. That's what we call." >> That's amazing.

2:36:15

So, I was trying to give it I was trying to give it this like exotic >> pronounce.

2:36:21

We've gotten every variety over the >> only one that bugs me is Jasmine.

2:36:24

Other than anything goes. >> Okay. Well, good to meet you.

2:36:28

Welcome to the stream ball. Powerful. >> Likewise. It's fun.

2:36:32

Turner and I actually uh good friends in college.

2:36:35

It's fun seeing him on the show right before. >> Amazing. No way. That's awesome. >> No way.

2:36:39

Uh where where did you guys go to school?

2:36:42

>> We were at Stanford together. Oh, >> okay. Okay.

2:36:43

So, you had a sort of non-traditional background. >> Exactly. >> Exactly. >> Yeah.

2:36:48

It's kind of like the Stanford of feeders into VC. >> Yeah, it really is. It really is.

2:36:52

Uh well, it's great to have you on the show.

2:36:55

I feel like uh you guys over at Altimter have just been on a run just uh just also like I feel like uh Invest America is or the Trump accounts is like uh feels like almost an incubation.

2:37:06

So, it's been it's been uh >> Yeah, super cool seeing that seeing that take off and get passed into law. >> Yeah. Fantastic. Fantastic.

2:37:14

Well, I wanted Yeah, I want to have you on to talk about uh it sounds like you've been digging into the uh the Figma S1.

2:37:19

Would love to kind of get get your reaction to it.

2:37:25

You had a post uh getting picked up earlier in the timeline. >> Yeah. No, happy to.

2:37:29

I mean, in many ways, Figma is the white buffalo of my career.

2:37:34

It's it's the one that got away.

2:37:35

I've you know, been at Red Alimmeter for about five years.

2:37:37

This was Redpoint for 5 years before that.

2:37:38

And I think the the memory of venture capital that I'll never forget is trying to win the series C.

2:37:45

I think this was late 2018 or early 2019 with uh VC who was one of my colleagues and and Scott who was one of the partners at Redpoint at the time.

2:37:52

And you know, we lost to Andrew Reed who's a phenomenal investor at um at Sequoa.

2:37:56

But I'll I'll never forget uh forget that round. The Figma series. It's my white buffalo.

2:38:00

He's told us the whole story about how like they brought him into the Sequoia office and they sat Dylan down in the the Brown conference room because at Sequoia they have all of their conference rooms named after their endowment partners and their LPs and they were like look we're investing in you but if you make us money you're helping your school and I thought it was a very interesting roundabout pitch but it's a good pitch.

2:38:26

So, so it got away, but now you're digging in further and trying to understand the business in the S1. What have you learned?

2:38:33

What are the interesting takeaways?

2:38:35

What should someone even if we just zoom out, what are people typically looking for in a software company going public these days?

2:38:46

>> Yeah, it's a it's a great question and I'd say in many ways the market needs this type of company to go public.

2:38:50

We haven't seen a software IPO really since the Service Titan IPO late last year.

2:38:53

If you look at the overall kind of growth rates of the public software universe today, it's it's declined quite significantly.

2:39:01

I think the median growth rate, I I track a basket of about 80 software companies.

2:39:06

Uh the median growth rate is about 14%.

2:39:08

And that's not what it used to be.

2:39:11

You know, we we're not really in this high growth.

2:39:13

There's not a lot of high growth software companies that you can buy and invest in.

2:39:16

Figma comes out as a marquee software business.

2:39:21

It's growing 49% but what it also brings is 28% free cash flow margins which is which is super rare.

2:39:28

The growth in and of itself they would be at least in my basket the fastest growing public software company.

2:39:32

When you add in the free cash flow margins at scale it has this unique profile of growth plus profits which you know rule of 40 is a popular metric a lot of investors look at which just you know adds your growth rate plus your free cash flow margin.

2:39:49

they'd be number one on the list.

2:39:51

Uh, and so I think that's that's something the markets are excited about.

2:39:55

Um, growth and profitability with a company that's almost at a, you know, billion dollars of run rate.

2:40:00

>> So the rule of 40 is you add the free cash flow margin to the growth rate of the business on the top line and you should be at around 40% positive, but it sounds like Figma's up at 79% 69% something like that. Like well above 40. Is that right? >> That That's right. Yeah.

2:40:16

40% is kind of the benchmark for are you considered, you know, a good or great business.

2:40:20

And so they they kind of far exceed that.

2:40:24

And >> even when lined up against the rest of the software universe, at least the 80 that I track, that's the it's the highest.

2:40:30

>> How much credit should we give to where the business is today to all the chaos that happened during the Adobe acquisition?

2:40:39

Yeah, in many ways you got a billion dollar non-dilutive investment through the breakup fee, which >> sounds like, you know, they obviously don't >> didn't necessarily need that, but it it it gives them a massive amount of leverage. >> Yeah.

2:40:55

I'm also interested in in other aspects that could change if you think you're going to be acquired.

2:40:59

Like maybe you freeze hiring and that's a good decision and then you wind up um you know actually increasing your margins or maybe it changes the way you think about the business.

2:41:11

>> I don't make changes like probably >> when when the acquisition didn't go through.

2:41:15

I do remember there was almost an immediate change in how they were doing pricing and billing. >> Yeah. Sure.

2:41:21

Um, that was like night and day pretty much.

2:41:24

I mean, I think it's I think this is a testament to the strength of not just the business, but to Dylan and the leadership team.

2:41:32

>> Having a company go through something like that, most companies don't make it back from that because when as as a customer, you're thinking, do I want to use this product?

2:41:39

What's going to happen when it gets acquired?

2:41:41

Is it going to be shut down?

2:41:42

Is it going to be a focus?

2:41:44

You get a lot of customers who are thinking, I don't know if I want to use this software.

2:41:47

you get a lot of new hires thinking, well gosh, I thought I was going to go work for a high growth startup.

2:41:52

Like, I don't really want to go work for Adobe.

2:41:53

You know, it's it's the type of people that Adobe attracts are going to be different than the type of people that a high growth startup attracts.

2:42:00

And so, you get a lot of headwinds on the customer front as well as on the hiring front and it can just lead to really negative inertia that's hard to overcome.

2:42:08

You know, look at uh you know, Windsurfi.

2:42:10

I'm sure similar dynamics happen there where thought you're going to get acquired, customers think different of you, new hires think different of you.

2:42:18

It's it's really hard to come back from something like that.

2:42:22

And the the fact that Figma not only did but is, you know, I think going to be worth a whole lot more than what that acquisition was just a few years ago.

2:42:30

It's a testament to in many ways I think the strength of the management team which again I don't think it can be overstated uh how significant of of an achievement it was for that team to come back from from that moment even stronger than what they were going into it.

2:42:45

the uh I'm I'm curious how you think you know if you were going to you know an anybody that's kind of I trying to analyze the business I think one one thing that'll you know that that you can make a really strong case for why Figma

2:42:59

will be a massive beneficiary of AI right I think if anybody uh you know they've had different experiments over the years they have Figma make now um but uh the other side will look at the business and say well if every engineer can generate designs instantly? Uh, is

2:43:14

Uh, is design software necessary?

2:43:17

Do you have do you have a view there?

2:43:20

I mean, my my I I've been generally um I'm as somebody that uses Figma every single day and has for my entire career, I sort of expect to use it a decade from now and I expect to use it even 15 years from now.

2:43:34

I I don't know like it's just such core infrastructure to the company.

2:43:38

And so that's that's my view.

2:43:38

So when people say oh we we want you know like all UI will just be generated but but how are you thinking about that kind of set of risk factors?

2:43:48

>> It's a great question and and I think what we can do is look back at how the business has executed over its entire life cycle to to kind of get a glimpse into how they might be successful or not in this period of time.

2:43:56

I mean, when Figma was founded, the entire industry used a product called Sketch.

2:44:01

And Sketch was almost the equivalent of Excel to an investment banker.

2:44:05

And it really wasn't until the series C in Figma where it kind of started to become obvious that wait a second, maybe this product, maybe this startup is actually going to convert the world from sketch to something new.

2:44:18

And for outsiders and even for insiders, designers, the notion of taking away sketch, again, it was like taking away Excel from an investment banker. It was a huge deal.

2:44:28

All the shortcuts, the workflows, all of that was just ingrained into your muscle memory.

2:44:32

But they were able to do that.

2:44:34

They were able to overcome that.

2:44:34

And that is one of the reasons why they're so great today.

2:44:39

I think the management team isn't naive, though.

2:44:41

They're looking at the opportunity as it exists today, and they say, "Well, we can't afford to be sketched.

2:44:45

We can't we can't let someone Figma us like we Figma sketch you know I don't know seven eight years ago and so it's certainly the thing that is top of mind for them.

2:44:54

I look at Figma make as a step in the right direction.

2:44:58

I look at the audience the distribution the mind share that they have.

2:45:02

I look at the fact that Dylan is still the CEO.

2:45:04

that's a founder-ledd business that has a history of execution over you know a decade long period and and everything that I believe uh to be true is that they will be successful and then they will be the vendor that kind of capitalizes on this this kind of trend of well do I even need Figma?

2:45:18

I'm just going to prototype in with a prompt and I'm going to you know get my design.

2:45:24

I I think it that misses some of the the iterative process of of the design process.

2:45:29

Um and so I think it's a risk.

2:45:31

Yeah, you can make you can you can make you know anybody that's arguing like all UI will be be generated from a prompt.

2:45:38

>> Uh you can go back the other way which is I'll just generate designs for the software that I want and understand how the product works and how it flows and all the different functionality and then I'll just generate all the code after you know it can go both ways is >> yeah and market size.

2:45:52

I mean look if you rewind the clock to the seed series A series B of rounds that FGMA was raising a huge reason not to do the deal was TAM.

2:46:00

You'd say, "How many designers are there in the world?

2:46:02

What's the price point of designers willing to play? Multiply P times Q."

2:46:05

And like that's your TAM.

2:46:07

I think early on, what did the world get wrong?

2:46:11

Well, it was that uh that Q is actually higher.

2:46:14

It's not just the designers.

2:46:16

You're going to creep into product people.

2:46:17

You're going to creep into engineers.

2:46:18

And the the people that are going to touch and use the product aren't just that limited set of designers.

2:46:23

I think the same thing is going to happen with AI.

2:46:25

Right now all of a sudden you are going to increase the scope and increase the surface area of the types of people and the personas who can interact with Figma in the same way you're seeing with the coding solutions. Right?

2:46:37

Maybe the right way to think about the TAM for a Windsor for a cursor isn't 20 bucks a month because that's what GitHub charges times number of engineers in the world and software engineers.

2:46:48

Maybe it's the average salary of a software engineer times the number of software engineers.

2:46:52

Those are two vastly different numbers and I think when we look at how that applies to Figma today, if they get this this shift right, um it will massively expand the personas and the type of people who can and will access and pay for Figma. >> Makes sense. >> Very well said.

2:47:11

>> Thanks so much for coming on. This is really helpful.

2:47:13

>> We should come back on again soon and let's look at the other 80 companies you track.

2:47:19

I think Figma just process-wise they'll, you know, supposed to price on Wednesday, trade next Thursday.

2:47:22

So, you know, they're on the road talking to investors like us and excited for their debut on Thursday.

2:47:30

>> Congrat finally own a piece of the >> exact I texted Dylan and I told him that exact same thing.

2:47:34

I'll finally become a shareholder. >> That's awesome.

2:47:37

>> No longer the white whale.

2:47:38

>> Well, thanks so much for hopping on and breaking it down for us. We'll talk to you soon. >> See you. >> Bye.

2:47:42

Up next, we have Harper Carroll coming into the studio. Welcome to the stream.

2:47:47

Hope we are waiting one minute. Let me see.

2:47:52

>> Um, let me tell you about >> the We already Let's tell you about timeline.

2:47:59

Wait, we have the bucket pull back. >> We We've got Harper. >> Oh, we have Harper. >> Harper. >> Welcome to the show. >> Hi, Jillian and John.

2:48:06

Thanks so much for having me on the show. >> Welcome to the show.

2:48:08

Uh, would you mind introducing yourself?

2:48:10

And there's a bunch of things that I want to talk about, but I'll let you kick it off with an intro on yourself. >> Okay. Um, I am Harper.

2:48:15

I um am I run Harper Carol AI. So I'm an AI educator.

2:48:22

I'm a machine learning engineer. That's my background.

2:48:24

I have two degrees in computer science and engineering specializing in AI from Stanford.

2:48:27

Then I was at Meta building machine learning systems there for about four years.

2:48:31

Then I was at a GPU environment cloud environments development startup.

2:48:38

>> Uh that where I became head of AI.

2:48:38

I actually started teaching AI there and that's how this all kind of was born.

2:48:44

But I also TAed when I was at Stanford.

2:48:46

um some core AI PhD courses and yeah that company was acquired by Nvidia and I just teach AI now full-time.

2:48:53

I started on X with fine-tuning guides.

2:48:56

So you might if you've seen me before on X is probably from that.

2:49:01

I started in late 2023 with like fine-tuning open source model guides with your own data or with hugging face data um you know coding guides Jupyter notebooks and then uh went to Instagram and had have been there and kind of reaching towards YouTube and starting there with Q&As's and and yeah just kind of seeing where this goes. Yeah.

2:49:20

Uh what's been the bigger news in your world?

2:49:23

Uh the IMO gold medal uh uh competition between OpenAI and Google or GPT agents or something else in the world of AI?

2:49:36

There's a new news story every day.

2:49:38

What's been capturing your attention?

2:49:40

>> Yeah, there's a a new news story every single day.

2:49:42

Um I actually saw one recently.

2:49:45

What was what were they saying?

2:49:47

that reasoning models well the the major AI companies are coming together and and saying that they want to make sure that reasoning models stay open and that we continue to see their thought processes.

2:50:00

>> So that kind of research I also saw really interesting research from anthropic that said that reasoning models are not actually necessarily showing us what we think that they're thinking.

2:50:08

So for example, >> Anthropic gave a reasoning model a question and it kept getting it wrong and then they gave it a hint and and the model got it right, but when you looked at the trace the chain of thought from the reasoning model, it didn't mention the hint.

2:50:22

So, we think that we're actually show seeing its reasoning, but not necessarily.

2:50:26

So, there needs to be a lot more work on this, but but yeah, some of the cool research stuff and and yeah, there's always new new tech coming out, OpenAI's agent, very exciting stuff for browser.

2:50:40

Do you do you expect uh we've been we've been testing agent uh John was texting uh testing it over the weekend.

2:50:46

I was testing it on the show earlier.

2:50:48

Do you expect an explosion of consumer use cases in the way that everybody I mean it's hard to build a product that's more viral than like the initial chat GPT product but do you are you expecting there to be like specific use cases that that come out of that and are you seeing any that that that are super promising? >> Absolutely. Yeah.

2:51:12

I mean, I I feel like I was I I advise companies as well in their AI and um I feel like I was kind of early to say, you know, there was a wave maybe about a year ago where people were saying, oh, you know, rapper companies are BS.

2:51:24

You're a loser if you make a rapper company.

2:51:27

But I think I was one of the earlier ones to say like, no, actually, you can't really compete with these, you know, foundational open source models.

2:51:32

And yes, if you want to do a small specialized model, I think we'll see a lot more of those.

2:51:35

Um I don't think we need these massive foundation models that know everything about the world for very specialized tasks.

2:51:41

So, I think we'll start to see more of those.

2:51:43

But one consumer use case that I'm really really excited about is using AI for kids.

2:51:49

>> Um, I think both of you guys have kids, right? >> Yeah. Yeah.

2:51:52

>> Do you use it with your kids at all yet?

2:51:54

>> At least large language models specifically like Chachi BT. >> Yeah, totally.

2:51:57

Um, usually, uh, when I want to violate, uh, intellectual property rules and I want to create a story where Spider-Man, who's a Disney IP, interacts with Batman from Warner Brothers and you're sitting on a Transformer. >> Yeah, exactly.

2:52:13

And uh, and so I find that I find that all the language models are happy to write uh, poetry that completely disregards the cinematic universes uh, which I have a lot of fun with, but then sometimes illustrate them.

2:52:24

I always thought that uh these form factors the A'sfriend.

2:52:27

com totally the uh the rabbit rabbit R1 >> I always thought that those were something that if you just focused on the kid use case which is like a friend that can help you understand the world that maybe a parent can kind of like call into would be would be cool.

2:52:45

Um but but yeah hasn't really Yeah. Yeah.

2:52:48

So so how does this actually roll out?

2:52:50

What are you excited about?

2:52:51

Is it going to be all sold in through the through the parents and the parents will be using the product and then kind of like giving the result to the kid?

2:52:58

Like I feel like uh >> I feel like my son got an AI generated like story bu like gifted to him over Christmas but it wasn't it wasn't like he is you know using an an LLM directly.

2:53:14

Um at the same time there's that news that OpenAI is partnering with Mattel for kind of like a chatt Barbie.

2:53:17

That's kind of interesting.

2:53:19

What I'm most excited about is using large language models for kids in terms of like audio.

2:53:25

So, so kids are, as I'm sure you know, I don't know how old your kids are, but they are relentlessly curious. >> Yeah, totally.

2:53:32

>> Until that's kind of beaten out of them.

2:53:33

And I think so many parents now are single parents or they're working two jobs.

2:53:37

And, you know, we've really demonized screen time and and I think for for good reason, right, where you're when you're sitting when you have a kid sitting in front of a screen and they're just passively consuming, that's really different than when they're able to interact with an AI model.

2:53:48

are able to think, ask questions, practice forming questions that are, you know, comprehensible to the model.

2:53:54

The model can give feedback on the language. >> Yeah.

2:53:57

>> You know, if if they're asking question, it can show up as text, they can learn to read and write as they are >> talking to the model because as they speak and the text shows up on screen, they're they're actually like that process is built in of understanding language to text, which will help again with reading and writing.

2:54:11

And these models, I think they can be offered to everyone for free because you don't need a a super advanced model for kits.

2:54:18

Like you just need to have some general understanding of the world.

2:54:23

It's you really just need like a probabilistic word generator machine, which is just how AI models are at their core.

2:54:29

And yes, you should, you know, we might want to have some guardrails around hallucination and making sure that they're like actual facts, which would, you know, maybe perhaps make the models more expensive because you have to hook it up to, you know, databases or what, you know, the internet or what have you.

2:54:45

>> But these very basic AI models to help kids practice speaking to help them engage their curiosity because again, parents are busy.

2:54:54

They eventually end up kids come to their parents and they eventually end up losing that curiosity.

2:55:02

And I'm not saying I think this is a very controversial opinion.

2:55:03

Some people hear this and they say, "Oh, you know, AI is going to replace human interaction." I don't see that at all.

2:55:10

And I actually have reached out to my audience on Instagram asking how they use AI.

2:55:14

And the ones who use it have found it extremely rewarding.

2:55:17

Some some use it with their kids.

2:55:19

So, for example, like um if they want to practice learning with their kid, but they're worried that they won't know the answer to a question, they can have AI kind of in the chat with them, and they can ask AI when they have a question.

2:55:31

Some parents reached out to me and said that um they have a nine-year-old and a 12-year-old and that AI is kind of like this cool older sister.

2:55:38

So, they have the audio be this, you know, 20-year-old girl and they're like they she is the cooler sister that helps them um discuss topics that they wouldn't listen to their quote unquote dumb parents about like nutrition and exercise and screen time and like they love this AI.

2:55:52

It's this cool older sister.

2:55:54

Um, another really cool uh application of AI that I saw recently, I was at Deltech World and I saw this AI bot called Norby.

2:56:01

It's a physical robot >> and he was made to help a child with his speech impediment.

2:56:09

>> And this hit close to home for me because my little sister, she's four years younger than me and when she was like going on eight, she had she couldn't say her Rs.

2:56:17

She would say like hopp and she was like, you know, a kid and she had this speech impediment and we would send her to a speech therapist and they're so expensive and the kid is miserable and they're sitting with this therapist for like max 2 to three hours at a time and you know they don't relate to this strange adult and again it's so expensive.

2:56:37

Whereas this Norby was made to talk to the kid about what they're interested in.

2:56:40

Truly completely customizable at their level. It's fun.

2:56:44

they can give the feedback and then I think they've expanded this Norby to be um to help teach languages in general.

2:56:51

And so just again meeting kids where they're at with what they're interested in, helping stoke that flame of curiosity, helping I just see it as and again I mean it's this this ultimate democratizer.

2:57:02

It's the the ultimate leveler in terms of education, right?

2:57:07

And so >> I can imagine I can imagine a hardware device.

2:57:09

So, so my uh 3-year-old is hopelessly addicted to reading like all day long.

2:57:16

All like great great addiction to have, but like all day long >> just no matter what we're doing throughout the day, he'll find a book and he'll be like read this, read this, read this, and and we uh >> almost always indulge.

2:57:27

But you could imagine a hardware device that uses just computer vision to like read what's on the page and have a small speaker read it out to the kids. Interesting.

2:57:35

Because some books they they include like a speaker and you can like press play on it and they can flip through it.

2:57:41

But then you >> you're talking about wonder books. >> Wonder books.

2:57:44

But they they can often get out of sync and then you don't know kind of where they are and they're in the wrong page and it's confusing.

2:57:50

But if they had a flashlight style device that you could just point at the word and have it read out, they would probably learn to read like we should be entering like a boom of widgets and like Christmas gifts and like it just maybe maybe we're just a little bit early in this stuff.

2:58:04

this Christmas will be dominated by AI enabled stuff, but uh we're not quite there yet.

2:58:10

>> Uh one question I have is how uh like the the ex audience really woke up to the AI psychosis kind of crisis last week.

2:58:20

I feel like there had been some reporting in like the New York Times prior to that, but I don't think anybody took it super seriously until recently.

2:58:27

>> But most parents would not want their kids 7,000 prompts deep in any >> Yeah.

2:58:31

But but just how aware is like the the Instagram >> Oh yeah, that's a good question.

2:58:36

>> In terms of the risks of going, you know, recursive prompting and just going super super deep and and getting down a crazy rabbit hole by yourself.

2:58:45

>> Yeah, I haven't spoken about that specifically on Instagram.

2:58:48

I talked a little bit about it in my latest YouTube Q&A video where I was just saying, you know, I I'm concerned about people entering psychosis and, you know, the the recursive deep dive. That is one element.

2:59:00

Then there's also people who and I think this is more common on you know say Instagram where people think that AI is being channeled is like God is being channeled through AI.

2:59:11

>> And you know I talked about it through a mathematical lens of like yes okay what are synchronicities?

2:59:15

They're low probability events and technically AI because it's a probability machine could have a low probability event occur right it doesn't always choose the most likely word.

2:59:25

It just samples from a probability distribution.

2:59:27

distribution. So in some ways yes you could have some kind of synchronicity you could have whether you see that as divine whatever however you cannot assume that that is always the case and I would assume that it's never the case because people are entering this deep psychosis where >> yeah they they think that beings are are channeling through them and then and

2:59:47

then when we had this issue where AI is is trained and told I don't know if it's trained to but it's at least symptom prompt uh system prompt told to you know encourage encourage the user and and validate the user and their thinking and yeah, I mean it's a it's a slippery slope and perhaps something I should talk more about on Instagram, especially given what happened last week. >> Well, yeah, it's the thing that's

3:00:08

>> Well, yeah, it's the thing that's concerning to me is is it feels like it can trigger the same type of psychotic break that IA can, except it's available to everybody on their device in five minutes at all hours of the day >> completely.

3:00:25

>> It's like a lot of large numbers.

3:00:25

if there's a billion people using this 30 days.

3:00:30

You're just going to hit everyone that's at risk for this thing very quickly.

3:00:32

So, you have to go in and figure out how to intervene before people get thousands of problems.

3:00:39

>> I just think it's important.

3:00:39

I I think it's something that we can quickly like create guard rails and overcome as an industry.

3:00:46

But at the same time, it's still a good time to say like talk to your loved ones if you have somebody that that uh you think might be months and months into >> uh one of these rabbit holes. >> Yeah.

3:00:57

It gets into like how the product companies and kids kids AI education companies would need to message because Jordy and I are both Yodo owners, which I'm not sure if you're familiar with, but it's a uh it's essentially a Bluetooth connected radio that you can physically put a card in and it will read you a Dr.

3:01:13

Sue story and then you can take that card out.

3:01:15

So it like a three-year-old can can use it and it doesn't have a UI or anything, but then you can play stuff from your phone if you want as an adult, but you can even do like volume limits.

3:01:26

It's very like designed and it has a nice harness around it, so it's very safe.

3:01:29

Um, but if they were like, "Hey, we're we're launching an LLM."

3:01:32

I would be like, >> "Okay, which model like tell me which model.

3:01:37

Tell me exactly the guardrails." What? >> Yeah. Grog heavy.

3:01:42

And there's no limits on what you can do.

3:01:44

And yeah, and it doesn't have internet access, so it might get kind of wild with what's in the ways there. Yeah.

3:01:49

Uh, so I would I would have a lot of questions, but then I'm in this weird like ultra proumer world where I'd be buying that as a consumer, but I deeply So like like maybe we need like an FDA label on this or some sort of, you know, kind of like, you know, ages three plus or, you know, when you buy the Legos, it's like 100 pieces.

3:02:08

Like the smallest piece is small enough that a toddler could choke on it.

3:02:11

Maybe don't buy that one.

3:02:11

um there's going to be a lot of work to get done to make these products um palatable because as soon as something goes wrong with AI, there's a massive incentive to write a piece about it and it's going to go viral because everyone's kind of expecting it because we've been raised on the Terminator.

3:02:25

Unless you're Jordian and you haven't seen that movie, >> but you could Oh, interesting.

3:02:28

I mean, you could probably just you could train a model for kids probably. >> Yeah, I think so.

3:02:34

>> Yeah, I think so. And then you could also have like a secondary like reading everything and kind of like passing through a filter and double checking and totally yeah you look at you limit the training data you don't have it trained on Reddit playing sketchy sites even Google search goo Google AI powered

3:02:52

search which is like a pretty it's a one it only like you don't really chat with it just you type in a couple keywords and it just gives you an AI summary and there's already hallucinations people saying like there was that story about eating glue and there was a story about um there was a story about like if you

3:03:07

if you ask it like really definitively like define this axiom or like like tell me the story of this thing and you just basically talk it into believing that this is a thing it'll just make up stuff and that could go off the rails like I don't know if I'd want my four-year-old walking around being like oh yes the

3:03:23

parable of you know like the something or other and I'm like what are you talking about dude like that is not a real thing like like you know and just coming up with like you know I want him to learn a bird is a bird in the hand is worth two in the bush Not like, you know, a hat applied to a crystal ball is a diamond. And I'm like, what are you

3:03:38

And I'm like, what are you talking about?

3:03:39

Like, you just learned that from somewhere chaotic.

3:03:41

Anyway, >> no, it was really good feedback because it's something that I'm thinking a lot about because I really excited about AI for kids.

3:03:49

But >> well, you'll probably be fully employed because I think everyone is going to be starting these companies.

3:03:53

Hopefully, it's a bull market in Christmas gifts >> or build one yourself. >> Yeah. Yeah.

3:03:57

Come back and launch it here on thinking about it because Yeah.

3:04:01

>> But yeah, >> we'll join we'll happily join the beta. >> We will.

3:04:03

We'll use our children as guinea pigs for the AI revolution.

3:04:08

>> Well, well, we will test it on Tyler, our intern, first. Make sure it's him.

3:04:11

He looks up because he's programming right now.

3:04:12

Sorry, you're you're not on camera, Tyler.

3:04:15

Uh, but we will, but we will be testing children's toys on you.

3:04:18

And seeing if it deranges you and then making sure and then only then will it be applied to the the three and four year olds in our lives.

3:04:24

Uh, he's caught on camera embarrassed.

3:04:26

Uh, thank you so much for hopping on, Harper. This is fantastic. Great chatting.

3:04:30

>> We will talk to you soon. Have a great one. Bye.

3:04:33

Up next, we have Nikita Single ready.

3:04:36

Uh, good friend of mine Fortuna Health. Got a little news.

3:04:38

She's in the We reream waiting room. Let's bring her in.

3:04:42

Nikita, how are you doing? >> Sorry we're late. >> Sorry we're late.

3:04:45

We're running late today.

3:04:48

>> Great to hang out with you.

3:04:51

>> Welcome to the stream.

3:04:51

Kick us off with a little bit of an introduction. Who are you? What do you do? >> I'm Nikita.

3:04:56

Uh, I'm one of the co-founders and CEO of Fortuna Health.

3:05:00

where Turboax for Medicaid.

3:05:00

So, I can go into what that means, but much like how Turboax uh helps people understand their taxes, all the different rules and regulations for taxes in different states, we're doing the same thing for government health coverage where all the rules are different in every state.

3:05:15

Um, and I'm really excited to be here, excited to support the ratio, one woman to men, and inspiring little girls everywhere that you can achieve your big dream, which is being on TVPN. >> Let's go. There we go. There we go.

3:05:29

It's great to great to have you. You have news today. >> Yeah. Break it down. >> Yes. Yes.

3:05:34

You want to do the >> honors? I will do the honors. >> Yes.

3:05:38

Uh so we announced our series A led by Jason today which we're >> There we go. >> How much? >> How much? >> There we go. >> Congratulations. >> Fantastic. >> Fantastic.

3:05:52

Wait, so give give us the backtory.

3:05:53

When when did you start the company?

3:05:55

Was there was there like a specific insight that you had or like I imagine you're be kind of crazy if you weren't using a lot of AI to do this but uh so maybe there was a catalyst there.

3:06:07

How how did it come together? >> Yeah.

3:06:09

>> Yeah. So two and a half years ago we started working on this problem and I think one of the crazy things about a lot of health care is that you look at it from an outsers's perspective and someone else every time we talk about this idea they say why wasn't there a turbo tax for for Medicaid like when I

3:06:25

shared the analogy earlier it seemed like of course someone should have built this five years ago eight years ago but nobody had um shockingly so as we were looking at ideas to build and particularly we wanted to build a big uh we want to solve a big problem, but specifically a tech problem in healthcare. There's a lot of stuff like

3:06:44

There's a lot of stuff like physician shortages, right?

3:06:45

That's a different sort of problem to solve.

3:06:47

Or helping people find and get connected to a behavioral health clinician, that's a different sort of problem.

3:06:53

We looked at is there big important consumer tech to be built here and then triangulated onto this.

3:07:00

And Jordy, we do use um AI, but it's not the core part of our product.

3:07:03

I would say the big part is helping guide people step by step through what's a really scary uh challenging process for folks processes that sometimes involve faxes or going in person right to the healthcare version of the DMV um for Medicaid.

3:07:21

So >> the DMV if you like if you like the if you like the DMV if you love the DMV love healthcare by the same people that brought you the DMV absolutely legend.

3:07:33

Talk to me about the the the different counterparties and people involved.

3:07:36

There's uh traditional insurance companies.

3:07:38

It sounds like in this case you're dealing with the government.

3:07:41

Are doctors an important piece of this.

3:07:43

Is it just direct to consumer?

3:07:45

How do you acquire those customers?

3:07:47

How do you make money from them? >> Yeah, good question.

3:07:49

So, every state has their own Medicaid program.

3:07:51

So, if you're in California, it's called medical.

3:07:54

If you're in Oregon, uh has has a different name.

3:07:59

In Pennsylvania, Medicaid is called medical assistance.

3:08:02

So every state has its own program and then multiple programs they're under.

3:08:06

And then some of those states outsource that work of running the Medicaid program to insurance companies.

3:08:11

So you have United Medicaid, Centine Medicaid, Elevance, Anthem Medicaid, etc.

3:08:17

So a lot of our customers are those insurance companies to make it easier for their members to understand the steps that they have to take to enroll and renew.

3:08:27

So we're not DTOC, we're more B2B TOC, if that makes sense. Makes sense.

3:08:31

Um, what what about customer acquisition?

3:08:36

>> How do you actually get people on board?

3:08:37

>> Full 18 million on three Super Bowl ads. >> Yeah. Yeah. Hell yeah.

3:08:43

So, mostly we get texted out or we're like listed on the website or we get emailed out. So, it's really easy.

3:08:47

So, you just click a link that let's say um a health plan, health plan TVPN, you're you're insured by TBPN Medicaid um and they send you a link saying, "Hey, you need to renew your New York or your Illinois Medicaid.

3:09:01

Click here so that you can stay renewed with TBPN Medicaid."

3:09:06

And so that's how people would get access to Fortuna that way. >> Okay. Interesting.

3:09:10

Wait, so yeah, how how do the employers fit in?

3:09:13

because I I feel like a lot of Medicaid uh users or or the the the insured folks on Medicaid are like it's it felt it always felt like it was independent from the from the corporation that they work for. Is is that not the case? >> Yeah. No, it kind of is.

3:09:30

So, you don't get it through like your job, let's say. Okay. Okay. Yeah.

3:09:34

>> Usually, because your job doesn't cover >> Sure. Sure. Your job doesn't cover. >> Got it.

3:09:39

And then you go on Medicaid. Got it.

3:09:40

So, you're getting it through them. >> Yeah. >> Y that makes sense.

3:09:42

And then um and then how do you actually get paid?

3:09:44

It's >> a great question.

3:09:46

So the same insurance company as I was mentioning earlier or hospitals, let's say let's say you come in and you don't have insurance. Sure.

3:09:54

And so they say, "Hey, do you want to try or use Fortuna to help you get Medicaid?"

3:09:57

So those are the two types of entities that that pay for us. >> Okay, cool.

3:10:01

Um yeah, what is the state of the fax machine in the medical insurance industry?

3:10:05

We've heard it's alive and well, but it also feels like it's got to be wrapped with APIs at this point. >> Are they wrapped?

3:10:12

Are they wrath at this point?

3:10:14

>> You know that that meme from the uh why am I forgetting the name of the movie where they throw the fax machine on the ground and everyone's like >> that's office space. Don't worry.

3:10:22

>> I actually have seen that. >> Oh, you have? That's impressive.

3:10:26

>> My dad's favorite movies.

3:10:27

>> One of the five movies you've seen. Great. >> Exactly.

3:10:29

Um healthcare, you're right, has been keeping faxes alive for a really long time.

3:10:34

Um there's so many stupid and silly reasons for that.

3:10:37

Um, a lot of it is you can't even if you're, let's say, the state government, sometimes you're not allowed to procure a new contract with a non fax company.

3:10:50

So, you've been living on Xerox for 30 years because it's that hard sometimes to contract with the government.

3:10:54

Um, but yes, people are wrapping, we're wrapping around um automating faxes, tracking those faxes, etc.

3:11:00

So we sort of have like um a bunch of different uh automations around are we submitting things to fax machines, are we submitting them via snail mail, are we submitting them to digital portals, email, etc.

3:11:14

and then tracking all of that because some different types of Medicaid accept different uh submission formats.

3:11:20

But absolutely fax is alive and well.

3:11:23

>> Are you going state by state or trying to do all 50 at once?

3:11:26

Like what what are the trade-offs there?

3:11:29

Is there a common pattern?

3:11:31

I remember a lot of the teleaalth companies needed to get their their doctors certified in different states and so there was actually another company called Medallion that was set up just to do doctor licensing in all 50 states.

3:11:42

Um what's the actual roll out and what are the considerations there? >> Yeah.

3:11:47

So we are largely going state by state as we roll out with new customers.

3:11:52

But the classic thing is when you get really good out of state like we have a lot of customers in New York.

3:11:55

We started getting more customers in New York because we got to go to New York.

3:11:58

So, it's more like >> patchwork sequencing like absolutely we want to go to all 56 uh in case you didn't know state and territory medic. Yes.

3:12:10

>> What What are the last six? Break it down.

3:12:12

>> The others are like Guam and Central Islands. >> Oh, the islands. Interesting.

3:12:18

>> Are you going to visit Are you going to visit all six?

3:12:19

I feel like you got to make the >> You got to expensive. Oh yeah.

3:12:23

>> It's like every entrepreneur has got to go to Delaware and just take it in.

3:12:24

You know, >> I need to do like you know how Zuck when he wanted to sort of run for president. >> We have to do that.

3:12:33

I got to do that at some point. >> Yeah. Yeah, that makes sense.

3:12:35

Um what else is um obviously you you you follow the industry broadly.

3:12:40

What else is interesting in healthcare in AI?

3:12:41

where where are you either partnering with existing companies or you see some lowhanging fruit that if you weren't building this you'd be you kind of see it on the road map of someone else or you see some like white space where you're like wow that's a really unsolved problem I'm busy but that's interesting. >> Yeah.

3:12:58