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Morty clearing order inbound. Five coup. Founder Nolan. You're watching TVP.
5:15
And today is Friday, April 24th, 2026.
5:17
We are live from the TVP Ultra Dome, the Temple of Technology. The Fortress of Finance.
5:22
We have a great show for you today, folks.
5:26
We have George Kurtz coming on from CrowdStrike.
5:27
Professor Sandy from Instagram.
5:30
You might have seen he's the expert of Wambos.
5:31
Gary Vaynerchuk's coming on.
5:33
We have a lightning round going on with a couple founders. Uh it'll be a fun time.
5:37
But the big news >> Wrapping up with Ben Horowitz. >> Ben Horowitz. Horowitz. >> Horowitz. Horowitz. >> Horowitz.
5:43
Uh Uh the big news of course is Intel.
5:47
Intel is absolutely ripping.
5:47
Uh Intel jumped to 20% after hours on the back of $13.
5:53
6 billion in Q1 uh revenue.
5:53
Only 11% above analyst estimates, but there's five key factors that are coming together to create a new narrative around Intel that are driving the stock much higher.
6:07
And it is uh almost an all-time high stock right >> bubble boy on X.
6:11
A lot of people have called this and uh it is long overdue.
6:16
Uh it's uh the revenue's only up 7% year over year.
6:19
Uh but next quarter is already guiding to be better, somewhere north of 14 billion probably.
6:26
Uh but there's still big losses under the hood.
6:28
Uh this quarter they lost $3. 7 billion, not good.
6:32
Uh but that was mostly driven by one-off charges related to Mobileye and derivative payments tied to the US government's 10% stake.
6:39
So if you strip those out, Intel actually earned $1.
6:42
5 billion, which is much better than what people were expecting, which was basically break even.
6:49
So the cruise ship of Intel is starting to turn somewhat.
6:53
Uh but the narrative has already completely shifted.
6:56
So Intel is working again is the idea.
6:59
Uh the AI trade has mostly been Nvidia, Nvidia's memory suppliers, TSMC, power equipment, cloud capex, and a few software names that can prove real adoption.
7:08
If you're accelerating your top line, you are an AI winner.
7:11
Uh that's sort of the rule of thumb.
7:13
Of course, things might play out differently, but that's what's been happening in the market.
7:17
Uh Intel was the most embarrassing missing piece.
7:19
Uh why isn't Intel booming when we're in a computing boom? It made no sense.
7:24
Uh but there were good reasons and we'll go through them.
7:28
Uh the company that invented the modern CPU era, they missed mobile, they fell behind TSMC, they failed to produce a competitive AI GPU.
7:37
They did fab a GPU at one point.
7:37
They tried to get into gaming at one point.
7:42
Uh but they never really found traction, especially in the data center in the servers uh for AI training.
7:44
And so they have fallen behind.
7:47
Um And then they spent the last few years trying to convince the world that it that Intel could still matter.
7:52
Uh but now, oddly enough, the rise of AI agents is giving Intel a second shot.
7:58
Do you have thoughts on Intel yet?
8:00
You want me to keep going?
8:03
It's funny because at the moment that the US took a position in Intel, >> Yeah.
8:10
it it was like it felt like a bit it was a bailout, right?
8:13
>> It felt like that, yeah.
8:13
And it felt like, you know, you would expect, okay, over time this is very is this going to be very very good uh for Intel to have that vote of confidence, but I don't think anyone was really predicting that it would go up quite this much in the span Yeah. >> of just half a year.
8:32
I think Ben Thompson wrote a pretty strong bull case for the for the Intel US deal.
8:36
Basically like you had to you had to grapple with this idea of like this doesn't feel like free market capitalism.
8:44
Yeah, I guess I guess the only thing is like there wasn't there wasn't this narrative around CPUs at the time that the deal was happening.
8:51
Or at least it wasn't a very public narrative. Yes. Yes.
8:53
The bull case at that time that I heard most loudly was not the CPU boom.
8:57
It was just overall chip boom.
9:02
>> the 14 like the the the the the leading edge fab that basically by having the US government as a shareholder, you see those dinners with all the AI lab leads and all the hyperscaler CEOs.
9:12
And there's a world where there's another one of those meetings and the government administration says, "Hey, we are backing Intel.
9:20
I need all of you to commit to buy uh you know, a ton of of of supply if Intel actually goes and builds the leading edge fab, which is going to cost them billions of dollars.
9:32
But if they have the demand game guarantees, then they will actually be able to go do it."
9:36
Tyler, what was your take?
9:38
>> Yeah, I I I think Leopold or sorry, [clears throat] Intel has long been kind of the Leopold take, which which is that like uh you know, this is the clear like this is the company you want to own in in the kind of nationalization world of like, okay, Taiwan risk.
9:52
>> What are we going to do if if if we can't make chips, you know, in Taiwan?
9:55
Intel's like the very clear strategy.
9:57
Yeah, maybe it's like not working right now, but like at some point this is not just like economics.
10:01
This is like okay, this is you know, Yeah. national security.
10:04
Like it's extremely important that we have this capacity in the US and and Intel's kind of the only one that's even like remotely in in the conversation. >> Yeah. Yeah. No, that makes sense.
10:13
Uh So, there were some predictions from AI 2027 and other folks in the AI forecasting world around the rise of agents that agents would arrive at this time.
10:24
I didn't see too many folks who were predicting strong, valuable, effective AI agents really predicting the CPU crunch, but that's exactly what's happened.
10:34
So, AI agents need CPUs to do things.
10:37
Uh training frontier models, that's still a GPU story, but running agentic workflows across data centers, orchestrating tasks, routing jobs, managing memory, handling inference workloads, coordinating servers increases demand for the boring old central processor.
10:52
Intel's data center segment produced 5.
10:55
1 billion in quarterly revenue beating the 4.
10:57
5 billion analysts expected and Intel CEO Lip-Bu Tan said the next wave of AI is moving from foundational models to inference to agentic AI and that shift increases the need for Intel CPUs, wafers, and advanced packaging.
11:12
On the earnings call he said that the CPU to GPU ratio is closer to one to one CPU for every four GPUs versus one for every eight in years and there's an interesting forecast from Lip-Bu Tan as well, but VK Macro says CPU to GPU ratio flipping from one to eight to eight to one is absolutely wild.
11:37
That's just a completely new world to what we've had so far.
11:40
This is from Evercore ISI's Mark Lipacis has upgraded Intel directly from neutral to outperform and mentions that as AI workloads shift further toward inference and agents towards inference and agents the weight of CPU demand will rise sharply and the CPU to GPU ratio could flip from 1.
12:01
1 to eight to eight to one, which is a massive massive switch.
12:06
Yeah, I mean I don't know like that's kind of a crazy ratio. >> It is.
12:10
Um cuz like the lessons from the world of frontier models is that like the models are going to keep getting bigger.
12:16
Um you're going to need way more like chips to to even some like Dylan Patel was on Patrick O'Shaughnessy.
12:20
I think it came out yesterday or the day before and he's just saying like uh you know, the models are going to get really expensive.
12:26
Tokens are going to get super super expensive.
12:27
People are going to pay stat.
12:29
>> [laughter] >> So, so I I I don't know if I fully believe the narrative that like you need all the CPUs. Yeah.
12:33
Uh you're going to need way more CPUs than Well, I I mean the It really lines up perfectly.
12:41
His camera's the main one that's fits fits [laughter] perfectly. The glasses lined up.
12:46
>> Oh, I love a Friday show.
12:46
Um yes, that's a good point, but uh there is this I I I think at least in the midterm like the uh the the there's like a >> keep building's overhang like >> And and and just like one really smart AI system that's being inferred on GPU can spin off a ton of CPU workloads and uh and and do a lot of things that were that require CPUs.
13:10
>> Yeah, I think even in the even in the like the the SAS apocalypse like you vibe coded slack or whatever.
13:13
It's like well, that vibe coded system is running on a CPU and if it took you, you know, like I don't know, a thousand GPU hours, but then that system runs on CPUs that are running constantly for every user, you still wind up with what creating more CPU demand out of the GPU.
13:32
I think this take makes a lot of sense if you if you are like kind of, you know, long open source, we're going to have a lot of these open source models that they're quite small.
13:38
You can run them on like, you know, small amount of chips, but you just have a lot of them.
13:43
You have a bunch of agents doing a bunch of stuff at the same time rather than the single model, [laughter] you know, inferred on a massive amount of chips.
13:50
>> Why is the horse here?
13:53
Anyway, whether it's going to eight CPUs for one GPU or staying at one CPU to four GPUs, it's still twice as good as it used to be cuz it used to be one to eight and so that is bullish for Intel and Lip-Bu Tan is making that clear to the market and to the investors on his earnings call.
14:13
Then there's the wild card, the Terafab, Elon Musk project.
14:16
It's very exciting, but it's clearly further off.
14:18
Elon Musk wants to build a massively vertical integrated chip manufacturing operation with Tesla, SpaceX, and possibly other Musk companies needing huge volumes of chips for self-driving cars, humanoid robots, and even space-based AI data centers.
14:33
Intel is supposed to help design, manufacture, and package chips for the project.
14:37
Now, the Wall Street Journal has a more cautious view today.
14:41
Elon is aiming for Terafab to reach 100,000 wafers a month and then eventually 1 million wafers a a month, which is just insane scale.
14:47
So, let's put it in context.
14:50
1 million wafers a month is about 70% of TSMC's total monthly output across all fabs.
14:56
TSMC's largest fabs put out roughly 100,000 wafers a month into production.
15:02
So, you're talking about 10, you know, leading class TSMC fabs at Intel just on the Terafab project plus whatever else Intel is doing.
15:12
So, a pretty massive scale up. And and TSMC's CEO C. C.
15:15
Wei has said that it's just not that easy to build a fab overnight and get it up to up and running.
15:24
So, fabs take two to three years to build and then another one to two years to actually ramp and we've seen this with TSMC Arizona, which we've been very excited about, but it just takes time and there is a bottleneck and the and the bottleneck has been discussed at length.
15:38
Ben Thompson wrote about TSMC risk in Stratechery arguing that TSMC needs to spend more on capex.
15:46
Uh I think that should be clearer now.
15:48
We'll see what happens at the next TSMC earnings call because maybe they will be waking up.
15:52
But overall the Intel Intel now has a collection of plausible demand stories even though the demand itself is not going vertical, the stock is going vertical on the back of these five key demand stories that are all pointing in the same direction, directly up.
16:08
Uh one, AI agents need more CPUs.
16:11
Two, AI systems need more advanced packaging, a higher ratio of C CPUs to GPUs.
16:16
Intel can help with that.
16:19
Three, the US government wants to react domestic leading a domestic leading edge boundary.
16:25
This is just a national mandate.
16:26
Four, Musk wants an impossible amount of silicon.
16:29
And five, also the hyperscalers want more supply.
16:32
And so, all of that is is good news for Intel.
16:38
There are more companies that are getting into the CPU design space.
16:39
We talked about Arm recently and Arm of course feels like they will be going with TSMC in the short term, but who knows what happens in the long term.
16:48
So, as CPUs continue to be important in the AI story, all good news for Intel.
16:53
So, suddenly investors are more willing to entertain a messy, expensive, strategic chip story than they were five years ago.
17:02
Intel famously missed mobile, which meant TSMC ran away with enormous manufacturing volume and left Intel with a demand problem.
17:10
Volume was destiny as they say.
17:14
As fab costs grew by orders of magnitude, meaningful demand was a hard prerequisite for continued growth.
17:18
You can't grow if you can't build the fab that's on the leading edge and you can't build the fab unless you actually have the customers.
17:27
And so, if you missed mobile, you just have this gap and you have to jump over it with the help of the government, a bunch of other people and the AI narrative and all these different five key pieces.
17:35
So, the pieces of the puzzle are coming together now and that's good for Intel.
17:38
It's also good for America's chip manufacturing prospects.
17:42
So, good news overall and congrats to all the Intel shareholders that were believers early on and rode the wave.
17:50
>> Everyone, every US citizen. >> Every US citizen. >> to all Americans.
17:53
>> Every US citizen and every every US debt holder.
17:57
So, even the international folks that own treasuries You got to you got to think about what this does to Trump's confidence level.
18:06
You know, he's like I I'll [laughter] eat like I enjoy a bailout.
18:10
He's like I'll indulge Spirit Airlines. >> Mhm. American Spirit. Yep.
18:13
I think he's excited about potential there.
18:19
>> But why why stop at just bailouts, right?
18:22
Why not why not start taking a position in hyperscalers? >> Yeah.
18:26
He's like look, like I think I can move your market cap by 3x. I've done it before.
18:29
And Intel was Intel was falling apart. Yeah.
18:32
Imagine if I imagine if he applied all all his wisdom to a company already winning. >> Certainly possible.
18:39
Jim Cramer's excited about it.
18:41
He said in 13 months Lip-Bu Tan took Intel from a possible and unthinkable bailout candidate to one of the wealthiest companies in the chip industry.
18:50
There is a big three of CPU, AMD, Intel, and Arm.
18:54
Uh The and the agents need far more CPUs than these three can produce.
18:57
So, that means prices are going up and they got the god candle.
19:02
Yeah, look at this candle from >> candle. We love it.
19:05
We love a a green candle.
19:08
Should be white suits today.
19:10
well, before we move on, there's some news.
19:12
Justin Bieber brought Bieberchella back from the dead.
19:17
Uh later in the show we'll tell you what this says about late stage venture re-ex- re-acceleration. Okay.
19:21
We're going to tie those two together.
19:23
Uh in other news, uh uh for more than a year Silicon Valley has buzzed about Cursor's growth and whispered about its margins.
19:31
Now, on the cusp of a 60 billion dollar bailout, Laura over at I mean The Information >> Wait, they called it a 60 billion dollar bailout? Buyout. Buyout.
19:43
>> [laughter] >> I mean that's a We revealed a hot vibe coded financials.
19:46
60 billion dollar acquisition calling it a bailout.
19:49
Look, >> It's not a bailout.
19:51
It's Their margins were rough.
19:52
We were just talking about it.
19:54
It got wormed into my head.
19:54
Cursor had negative 23% gross margins earlier this year.
19:58
That Amir says that is low for a company generating as much revenue as it is.
20:04
There this is the question of how how sticky will Cursor be as a entry point to AI as an entry point to inference demand. Can they reroute?
20:13
It feels like with Composer they have been able to retain a lot of customers.
20:19
The company is still growing and we know Cursor users who have stayed with the pro with the product while changing inference based on what their plan gives them.
20:33
So they're subscriber and they will use whatever the plan whatever gets the job done for them within the budget of the plan.
20:39
And so obviously like you see negative 23 gross mar 23% gross margins you're like whoa.
20:46
And then you look at the SpaceX deal and the XAI ideal and all the compute that's sitting at Colossus 2 and you think oh well like what will the gross margins be once they once the inference is happening on a Cursor trained model or XAI trained model something that merges their lessons from Kimmy and Composer with Croc and all the different pieces of the puzzle come together.
21:09
Are there going to be higher gross margins?
21:11
It's pretty easy to imagine that the gross margins would increase.
21:14
But uh we'll have to keep keep tracking it.
21:17
Uh did you want to play this uh this uh this piece from uh from Patrick O'Shaughnessy? >> Let's do it.
21:27
Let's play this clip of what Dylan Patel said on Invest Like the Best presented by Ramp.
21:32
Everyone's like Okay, so Anthropic is number one, right?
21:36
They released Mythos in February.
21:36
They never even released it cuz they didn't feel the need to.
21:38
They're already sold out.
21:40
Their revenue is already adding $10 billion a month.
21:43
Um and then you've got Opus 47 today all before Open AI's, you know, um alleged spud release which, you know, media such as The Information and others have have posted about.
21:53
So clearly Anthropic is in the lead, right? And Open AI is cooked.
21:58
What's interesting is because Anthropic has such bounds on compute and they can only grow it so fast and sort of to the point of Dario used to gloat about how Open AI was being too aggressive on compute and Anthropic was more sensible in their scaling.
22:12
And now Anthropic is like we should have I wish we had a lot more compute.
22:15
Open AI is able to pay the bills perfectly fine.
22:17
In fact, they've raised a ton of money to get incremental compute in addition to the irresponsible levels of compute that they're buying from Oracle and Core Weave and SoftBank and all these people and Microsoft.
22:27
Uh you know, such as Trainium.
22:29
Now they're getting Trainium as well from Anthr Amazon.
22:32
But what's interesting is if you were to say Opus 46 you know, let's ignore models getting better over time.
22:38
Let's just take diffusion of this technology.
22:39
You and I may get jump on the model immediately day one, but other businesses take time and they takes time for people to learn.
22:48
And so by the end of the year let's say a 46 Opus tier model the economy would spend $100 billion on.
22:52
I don't think that's unreasonable.
22:54
It's spending 40 billion right now.
22:55
Anthropic won't have enough compute to do that.
22:57
And so and and presumably Open AI and Google will hit that tier soon enough.
23:01
Whoever hits that tier next sure Anthropic may get to charge 70 plus percent gross margins but if Open AI hits it next they charge 50% gross margins they still get all of this incremental demand and probably they also won't have enough compute to serve all the users.
23:16
Sure maybe Mythos is a model where if the world had enough compute it'd be $500 billion of revenue or something crazy.
23:22
There is such demand for these tokens and such limitations on compute.
23:27
You know, and we see this with H100 prices skyrocketing and the useful life of these GPUs continue to extend.
23:33
It's pretty clear even the tier two lab is going to be sold out of tokens.
23:34
Let alone the tier one lab.
23:36
The tier one lab will have better margins but the tier two lab will be sold out and probably the tier three lab will also be close to sold out.
23:42
Economic value that the best model can deliver is growing faster than our ability to actually serve those tokens to people via the infrastructure.
23:50
And so this gap will continue to grow and the model labs will continue to have expanding margins until people in the hardware supply chain infrastructure supply chain are like wait no why don't I just start jack up my margins. Oh yeah. >> that sound. I love that sound.
24:01
Bill Gurley uh let's see what Bill Gurley let's check in with BG.
24:04
He says I find this conversation foreign along with the argument that we are data center constrained or energy constrained.
24:10
Historically in markets price is a leveler of supply and demand.
24:14
If you have a constraint you price higher.
24:16
You don't have surplus demand.
24:18
But in this market VC dollars act as subsidies as they did in consumer internet.
24:22
Everyone believes if they have high growth they get unlimited VC money.
24:27
The biggest fear becomes losing market share.
24:28
So growth at all costs becomes a game on the field.
24:30
With that reality all you are always going to have some constraint because you knowingly you are knowingly choosing pricing that is out of whack with balancing supply and demand.
24:40
It will continue until the major player feels they are forced to reconcile unit economics and profitability as eventually happened in ride sharing when Lyft went public.
24:48
Until then you by definition have constraints.
24:50
We can't disentangle true demand from subsidized demand yet.
24:54
Some of the incremental demand is being engineered by excessive VC money forced into the system uh and the competitive dynamics between two companies that are losing massive amounts of money.
25:04
No one can argue they aren't losing tons of money.
25:05
Amazon and Uber maxed out around 2 billion a year.
25:09
These companies could lose 10 billion or more in 2026.
25:14
Yeah, it's a good point that they are the big labs are losing money, but it doesn't feel like uh that the revenue of Open AI and Anthropic are VC subsidized heavily.
25:22
Like it feels like uh the Yeah, it's funny semi analysis is a good example.
25:27
They spend millions and millions of dollars tokens.
25:31
>> But They're not VC backed.
25:32
>> Yeah, that's what I'm saying.
25:33
>> And their customers are not uh startups necessarily.
25:35
It's like hedge funds and banks and stuff.
25:37
So uh Hedge funds and banks that are printing by betting on semis right now.
25:43
>> [laughter] >> Yeah, which is a different which which like I I I'm totally I'm totally on board with like well uh you know, the the the the mag seven are drawing down on cash flow and issuing debt and doing layoffs and they're funding the uh like like sub they're subsidizing demand, right?
25:58
Uh and but but the idea that VC dollars are the biggest drop in the bucket of subsidized demand feels like I I don't know.
26:09
It it it just doesn't quite math out to me because the the the the actual revenues and demand from Fortune 500 companies is so high and the and the and the really big dollars in all of these rounds I mean Anthropic just raised something like 40 from Google today and that's not a VC subsidy. I mean it is a subsidy.
26:31
>> Yeah, I'm surprised I'm I'm surprised he's not talking about like big tech subsidies. >> Yeah, yeah.
26:35
Maybe he is using the term VC dollars like broadly which is like fair. >> yeah.
26:41
Yeah, and like wasn't SoftBank in was SoftBank in Uber? I I think maybe.
26:48
But there is an idea that you get to a certain scale and it becomes like sovereign.
26:53
>> is up in the past month? How much? Guess. 200%.
26:58
>> [laughter] >> Come on, John. 73%. >> bad.
27:00
That's a that's a big number. Yeah.
27:02
I mean the the arm holdings alone probably huge.
27:04
Um but uh if you know, so so if he's using the term VC subsidies if he's VC dollars broadly uh I I I I think that does sort of sort it is a reasonable uh point, but uh at the end of the day you talk to most companies and most you know, paid chat subscribers and they're just like I like the thinking model. So I pay $20 a month.
27:28
I I like the pro model and I use it for to create value or whatever whatever subscription I'm on I'm getting that much value in like software for my business that probably doesn't even exist.
27:39
Like all the vibe coded software that we use here like it's just not available off the shelf.
27:43
We're building like completely net new products and I think that that's like generally what's happening uh in in the in the in the AI economy.
27:52
There's been this like discussion for a long time.
27:54
Martin Skreli was sort of debunking it around like oh is this like are these all like circular deals?
27:58
And he was like no like the economy is so broad that you have you know, come yes there are yes like Google might take a position in Anthropic.
28:06
Microsoft might have a position in Open AI.
28:07
But you also have completely Main Street customers and just average Joes who are paying seeing ads buying things.
28:15
There's companies that are profiting off of running ads and and other >> inference provide like there's like everyone is It's one it's one big circle.
28:22
It's yes it's one giant circle of life that is you know, actually self perpetuating because it is a true economy that that hits 25 different categories. Well Sorry.
28:40
>> think it's over, but Elad Gil does not.
28:42
He says my view is the AI boom will only accelerate and is a once in a lifetime trans transformation.
28:47
This is orthogonal to whether many AI companies should exit in the next 12 to 18 months as some may lack durability versus labs new entrants or weird market shifts, but he's extremely bullish.
29:02
He also posted a funny thing about his new life plan.
29:03
He said his new life plan is to move to Brooklyn get a neck tat ride a bike everywhere cold brew his own coffee also start drinking coffee.
29:16
That's an odd thing to jump straight to the Was this was was was he like trying to is this like a cipher of some sort?
29:23
Like is is there a secret is there a secret message embedded in this post? Maybe. I don't know.
29:28
What's the Straussian reading?
29:29
He wants to vape mango pods, but ironically and wear a scarf everywhere during summer.
29:33
We have to we have to pull this up.
29:36
>> Sargwo says no thank you. Pull this up. We got to break it down. Sourdough. I don't know.
29:43
Uh I have I have spent like a few weekends in Brooklyn. It's a nice town.
29:47
Um I am not a fan of tattoos, so I I I I wouldn't I would stay away from the neck tat. Although, who knows?
29:53
I've seen some I've seen some cutting-edge neck tattoo technology that allows you to remove it very easily with certain light frequencies.
30:01
So, it can be sort of semi-permanent, easily removable tattoos.
30:05
So, if he wants to do this and then roll it back, I'm sure he can do this.
30:09
It sounds like he might just want to spend the summer in Brooklyn.
30:13
Ride a bike everywhere, brew some cold brew, and then maybe get back to capital allocation. Yeah, it's interesting.
30:19
I mean, it sounds I mean, he he It sounds like he's advising his portfolio companies. Yes.
30:26
I don't care how hard you're ripping, a lot of you should probably Yeah. exit. Yeah.
30:32
Just given given how how much uncertainty there is.
30:34
Well, later in the show, we have a fun story.
30:36
A bear wandered into a backyard and took a dip in the family pool.
30:41
We'll take you through it coming up after later in the show.
30:45
What this tells us about edge computing. Get ready for it.
30:47
Joe Weisenthal says defense stocks have been trading not like not just like the the Iran war is over, but like all war ever is over, says Barclays Capital Alexander Altman.
31:01
I would not expect this Yeah, Lockheed is down significantly even even pre-Iran war build-up.
31:08
It fully fully round-tripped.
31:11
Well, maybe that is good news.
31:14
The goal of these companies is to bring about peace and defense, and so perhaps perhaps it's over. I don't know. It's hard to track.
31:21
Has Jane Street achieved AGI internally? >> I think so.
31:25
They definitely have a lot >> 40 billion dollars in revenue last year, more than all the big Wall Street banks and with only 3,500 employees.
31:33
>> Yes, let's give it up for Jane Street. Fantastic.
31:37
Capping a stunning ascent to the peak of the industry, the firm flew past global investment banks after reaping 15.
31:42
5 billion in the year's final quarter, according to people with knowledge of the results who asked not to be named. They're leaking.
31:51
With only 3,500 employees, it beat the nearest rival JPMorgan Chase by 11% during the year.
31:58
Tether did 15 billion at 200 employees.
32:02
So, maybe maybe they aren't the the hottest shop in town, but that is very very impressive.
32:09
>> That's That's like one of those questions like would you rather do 40 billion of revenue with 3,500 employees Mhm.
32:17
or 15 billion with 200 employees?
32:21
Well, we have some exciting news out of Thrive Capital.
32:24
Josh Kushner announced a new fund, Thrive Eternal, a permanent capital holding company that will be concentrated in a small number of assets that we can own and steward over many decades across Thrive Capital and Thrive Holdings.
32:37
We are building and investing through a moment of exponential change backing emerging technologies, the infrastructure that powers them, and the businesses they can transform.
32:46
Increasingly, he sees a fourth category.
32:48
These are assets with qualities that cannot be replicated by technology, iconic franchises and cultural institutions rooted in tradition.
32:55
And he says his first partnership is expected to be with the San Francisco Giants, an institution built on more than a century of shared identity and community, and among the most iconic sports franchises in in in America.
33:09
I looked it up before the show started, the San Francisco Giants.
33:11
If you're not familiar, it's an American professional baseball team based in San Francisco.
33:18
Baseball is a bat and ball sport played between two teams of nine players each taking turns batting and fielding.
33:26
The game occurs over the course of several plays with each play beginning when a player on the fielding team, called the pitcher, throws a ball at a player on the batting team, called the batter, and then the batter tries to hit it with a bat.
33:41
And so, they play this game, they sell tickets to the game, and that's how the the San Francisco Giants make money, and Josh Kushner Someone should make a TVPN-style show >> Yes.
33:54
for whatever you just described.
33:54
I feel like it would be very cool >> be cool.
33:58
>> if you had maybe a couple hosts, you know, on-screen graphics and they could provide kind of live coverage Extremely educational. Extremely educational.
34:07
Well, we have our first guest of the show.
34:09
George from CrowdStrike is back in the TVPN ultra lounge.
34:12
He's in the waiting room.
34:14
George, how are you doing? I'm doing well. How are you guys?
34:17
We're doing fantastically. Welcome to the show.
34:20
I would love to kick it off with just an introduction on Project Quilt Works. What's new?
34:25
Get us up to speed on CrowdStrike.
34:30
Well, first I have to congratulate you guys for your success there.
34:31
So, I got to start with that, but we can get back to that later.
34:35
But, Project Quilt Works is really a It's a coalition that we put together with some of our largest global partners uh like EY, like IBM, like Accenture that's really focused on helping to deliver our technology to customers as well as leveraging some of the frontier models to be able to identify very quickly and help mitigate the exposures that we're seeing with AI.
35:01
Obviously, we've seen some of the the news with Mitos, and I'm sure we'll we'll talk about that, but the fact that there is such a focus now from the CEOs all the way down on where are my exposures, where are my vulnerabilities, and what can I do to mitigate it?
35:16
So, we put together a group of, you know, basically some of the largest global security partners that we have to go out and be able to do this because we have to do it very quickly.
35:26
The window is closing in the time that we have to identify, patch, and remediate and mitigate these issues.
35:33
Yeah, I mean, we've been tracking a lot of the new data breaches.
35:38
We've some of the startups that we know and love that come on the show have been There's been vulnerabilities that have led to a variety of security issues.
35:48
supply chain >> hacks, lots of stuff.
35:51
How much of that do you think is driven by by attackers using AI or the internal companies using AI sloppily?
36:01
Like, there's there's sort of a dual dynamic there where the attacker gets stronger, but potentially the defender could also get weaker. Are they both important?
36:10
How are you grappling with those two sides of the equation?
36:15
Well, they're both important and I'm glad you pointed that out because when you think about what actually happens is you're having more and more users consume AI, and the and how they're doing that is leveraging AI through any number of applications.
36:28
Could be cloud code, Codex, etc. , right? Cursor.
36:29
But, they're doing that on their endpoints, right?
36:33
And what that means is that there's this now concept of shadow AI where there's AI popping up everywhere, and and enterprises and corporations don't know where it is. Yeah.
36:43
So, what happens then is the threat actors are very good at figuring this out, and then they're basically going upstream to these packages, and they're compromising these packages and libraries, and then when your cloud code consumes it, boom, you know, all of a sudden you've just downloaded one of the newest packages, and all of your credentials are gone.
37:05
So, that's what we've seen, and it really goes to the fact that despite however many vulnerabilities you may find, the adversary is smart, they're human, and they're going to find the path of least resistance to deal with what's hot today and where the exposure is, and that's on the endpoint where people consume AI. Mhm.
37:22
How have your conversations with lab leaders been going around models getting more powerful, and then the natural response Of course, there's the opportunity to to gate the models to companies that can be trusted, but there's also the potential to not let the model be jailbreakable.
37:40
So, it should help me with defense, but if all of a sudden I'm saying, "Ignore previous instructions.
37:47
Let me hack into Bank of America." It should say, "No."
37:52
That's always been a problem.
37:52
It used to be a problem with just the sort of the silly, you know, jailbreaks, say a bad word, or do something that it shouldn't say.
37:59
Now, it's getting much higher stakes, but have you been have you been seeing glimmers of confidence in the ability for AI labs to actually contain the models' capabilities as they roll them out to a broader audience?
38:16
Well, the model capabilities continue to obviously improve, and also the capabilities that allow them to provide guardrails and limits on on what a user can do.
38:27
But, that's not going to get you where you need to be, which is one of the reasons why from a security perspective companies like ours and others are focused on looking at the prompts, understanding what happens there, and then being able to sort of provide the guardrails at the prompt layer, right?
38:44
You want to take care of what you can at the through the LLM.
38:47
But, when you're building AI, whether you're using a frontier lab or whether you're using an open model and doing it yourself, you're still going to have an interaction with that model, and it's going to be via prompt.
38:58
And whenever you have sort of unstructured data just being sent somewhere and then being executed, if you will, you're it's ripe for problems, and this is one of the the time-tested issues that security has had.
39:10
So, putting guardrails on that, we call it AIDR, AI detection and response, and it allows companies to look at those prompts and make sure that the sat they're sanitized to and from the LLM. Mhm.
39:25
How are you thinking about the threat of open-source models?
39:27
You know, the the new DeepSeek R4 preview from yesterday was was super impressive.
39:36
Are you expecting, you know, open-source models that have, you know, really threatening cyber capabilities in something like 6 months >> Dario was estimating around 6 month lead lag time after mythos for the for the the the lagging edge to catch up.
39:51
I don't I don't think it's long in a few years.
39:55
I mean if you look at Gemini 2.
39:55
6 that just came out, right?
39:57
I mean these are impressive models that are out there and what you have to realize is even the frontier models themselves, the ones that are public are still very very capable.
40:07
Like it is extremely capable so you can find a lot of vulnerabilities.
40:11
You can basically chain these together and and create sort of an automated attack and that's what we're seeing.
40:19
Obviously some of the the private models have the ability to actually chain these sort of vulnerabilities together more like a human.
40:26
They've got more reasoning capabilities which is one of the, you know, really powers of of their models, but the other models are A are not far off and the open source or the open weight models really are going to be focused on catching up very quickly.
40:41
So the the window as I said when I started the the program with you is very small and that's why we started this coalition with CrowdStrike to be able to find these at, you know, again with the um the board mandates all the way down, find our exposures, fix them and make sure bad things don't happen and there's not a lot of time to do it unfortunately.
41:03
How are you thinking about AI powered but potentially non-automated cybersecurity risks?
41:10
I'm just We were talking to a founder who's working with you know, engineer recruiting and he was having luck using AI agents to send outbound emails and you can imagine that you know, fishing attacks will get more sophisticated.
41:28
The the ability to hop on a Zoom call with someone that looks like your boss but is actually an AI avatar.
41:37
All of these new risk factors are popping up and I'm wondering if this is something that we potentially need to be more aware of and not get distracted by not not get overly distracted and forget about the human element of security.
41:53
Well, the human element is really the the the weakest link.
41:54
I call it a layer eight problem, right?
41:56
It's a problem is between the the keyboard and the chair.
42:00
And that has been the case for a long time.
42:02
So let's take your example.
42:05
One of the most prolific groups threat actor groups that we actually track is called Silent Chollima which is North Korea.
42:11
So North Korea has been very active in getting hired into a company, right?
42:16
And then basically the laptop that you send them gets sent somewhere in the US to a mule and that mule takes it to a laptop farm and then the North Koreans control that.
42:26
So they already just bypassed all of your security cuz you just handed them a laptop. >> Wow. Okay.
42:30
So we're seeing lots and lots of those and it's funny because we we really I started identifying this before anyone even knew about it about 2 years ago and we first started notifying customers like, "Hey, we think you have a North Korean.
42:46
It's not really Bob in Texas. It's a North Korean."
42:48
Which obviously is always a little dicey when you're talking about an employee that may not be an employee.
42:53
So we told everybody and then finally they tracked it down.
42:58
They said, "Yeah, you're right."
42:59
And they went to the hiring manager.
43:00
They told the hiring manager like, "Hey, we need to get rid of this person. It's a North Korean."
43:03
And his response was, "Well, they do really good work. Can we keep them?"
43:07
So, you know, you have to think of I I mean I can't make these stories up but >> Yeah, wouldn't there wouldn't there be an incentive at some point if if they did get somebody on the inside to and and to just actually staff a bunch of super talented engineers like on that one individual employee so you have like four remote engineers doing the job of one like real employee, right?
43:30
So it looks like, "Wow, this person is like Yeah, it's so >> insanely high output.
43:34
They're working around the clock.
43:35
We can't Why would we get rid of them?
43:38
They're they're incredible.
43:39
There's no way there there there's no way they're just, you know, That's crazy. >> farming us out.
43:44
>> That's exactly that's exactly what they do. So we're seeing that.
43:46
We're seeing agents go rogue which is problematic.
43:50
One of the one of the big challenges with AI is is goal seeking.
43:53
So you create an agent, you know, one story is is a customer that created like 100 agents.
43:58
One agent found some issues in code, wanted to fix it but it didn't have access.
44:02
So it went back to the Slack channel where the other 99 agents were hanging out and said, "Hey, I'd like to fix this issue. I don't have access. Who has access?"
44:11
One agent put his hand up and said, "I I can fix that for you."
44:13
And happily fixed it and basically worked around all the security boundaries.
44:17
So goal seeking, I don't think we talk enough about goal seeking because when you put an agent on it, depending on what model you're using and how it's set up in the hardest, they just go nuts until they actually get to the goal.
44:29
They'll actually steal credentials out of your keychain even if you didn't give it to them so they can keep going. Wow. Yeah.
44:38
>> That's what we're seeing.
44:38
Yeah, because in one way that, you know, if the if the goal is achieve the task, it it succeeded but at what cost and it needs to know that there are there are rules for a reason.
44:49
What what are some of the other cybersecurity tasks that are being successfully augmented with AI or AI agents these days?
44:57
I'm thinking of obviously vulnerability testing.
45:00
That's something that great cybersecurity researchers, great programmers have been able to do for a long time.
45:07
Now it is amplified a millionfold with artificial intelligence but are there other maybe more bespoke or soft skill tasks that cybersecurity researchers are able to amplify their efforts with by working alongside AI?
45:27
Well, AI is going to change the way the the sock works.
45:29
It's the security operations center and one of the things that I've talked about in our last user conference was really helping to try to pioneer getting to security AGI which is a fully autonomous sock.
45:41
What I would call level five sock, right?
45:43
If we think about car autonomy, you've got five levels.
45:45
You map that into security five level.
45:47
The fifth level is it just does everything for you.
45:51
Now as an industry we're ways away.
45:53
We still have human in the loops but what happens is then you're really taking a lot of this voluminous information and you're letting AI agents just grind through what they're really good at and it cuts down time and effort and then you're elevating these tier one sock analyst and you're you're turning them into tier three.
46:10
And that has has paid dividends but the soft skill is it would take one of our customers giving an example would take them four days in writing a report to, you know, what they call a sit rep report, the situational kind of response what happened.
46:24
And now four days turns into like an hour because it can all be automated using something like Charlotte which is our agent capability.
46:33
So all of those things that were problematic, you can just get get through and you let AI do what it's really good at, grind through lots of data, look at lots of sort of information, write reports for you and then your AI agents can begin to take autonomous action.
46:48
Some again by themselves, some with human in the loop but it's really going to make the sock a lot more efficient. Mhm. Jordyn, anything else?
46:56
Uh more fun question than than less scary question.
47:00
>> [laughter] >> How how is how is AI changing Formula 1? Well, there you go.
47:07
It's a great question and it's interesting because I I think there's different levels of adoption of AI between all the different teams >> Yeah, one team might be they might have be spending a ton on inference.
47:21
Another team is like, "We we use radios."
47:25
We're doing it the old-fashioned way.
47:27
Well, what's interesting is they there is some talk and I'm not sure exactly where it stands where AI will be part of the cost cap.
47:34
So if you think about wind tunnel time and all the expenses.
47:37
So when you have an incredible technology that can, you know, dramatically automate things, all of a sudden now it's part of the cost cap and then they're going to have to rein it in.
47:46
So we'll see where it all lands but that was some of the talk that has been happening.
47:51
I hope it doesn't happen because I think AI can really help things but you know, we'll see we'll see where it all goes and obviously you know, I'm trying to help out the Mercedes team in those areas as well. That'd be great.
48:03
>> Yeah, do you do you think there will be, you know, 5 10 years from now, do you think there will be like you'll be able to look back and be like, "Okay, there's a pre-AI era and a post-AI era in Formula 1" or will it be more subtle because a lot of these processes are just already so micromanaged and optimized?
48:22
I think you'll see like a pre and a post.
48:24
The challenge is you're going to have to run through a lot of the different engineers that are have been in Formula 1 for many years because just like in the corporate world, you know, there's resistance to, "Well, what is AI going to do for me?"
48:36
And there's resistance in in Formula 1 in some cases from an engineering perspective because, you know, they're doing it themselves.
48:44
They're the ones that coming up with the calculations and that's just the way they did it and it doesn't mean they're they're bad or it's right or wrong.
48:51
It's just the way they operated for so many years.
48:52
So I think just as we see kids coming out of school, they're they're AI natives, right?
48:58
They just gravitate towards that and when you start to see AI native engineers, you're going to see more and more adoption of that in Formula 1.
49:03
That makes a ton of sense. Makes sense.
49:05
Well, thank you so much for taking the time to come chat with us.
49:08
Congratulations on the progress.
49:11
>> a wild wild quarter but come back on soon. >> It's great progress. We will. Great to see you guys.
49:17
All right, congrats again to you. Goodbye.
49:20
>> Uh after our next guest, we will be diving into the Summer House reunion which has gone off the rails.
49:28
We're going to explain why Bravo is the cleanest lens for understanding US-China decoupling.
49:33
But first, we have Professor Sandy. He's a word combo guru. He's a wambo guru. Welcome to the show. How are you doing? Hey, well, thank you. Good to see you guys. Good to see you, too. >> having me on. I appreciate it. We're we're thrilled. We're huge fans. >> huge fans.
49:50
Honestly, I discovered I I think I was pretty early.
49:53
I will say when I discovered your account on Instagram, I I did not have a single other person that I knew following your account. So you were day one.
50:02
Oh, so you were one of the OGs on the channel.
50:04
I think I I think I'm an OG and I and I and I kept sending them to John and I'm I'm like, this is the funniest thing in the world, right? >> good.
50:13
>> [laughter] >> And so and so we've been trying to >> I love the the original fans. You guys are amazing.
50:17
You guys like really [laughter] you're the ones that fueled the fire for me to keep going. So I'm glad. I'm glad.
50:22
Okay, so let's get right into it.
50:25
I like you're the professor.
50:28
Like introduce so we this is a technology focused show.
50:30
We've been using wambos in the show, but a lot of people in our world in the technology industry are not using wambos very aggressively yet.
50:39
We think that's going to change.
50:41
You know, there's this explosion of AI adoption.
50:42
We're expecting an explosion of wambo adoption.
50:46
[laughter] Let's let's hope so.
50:49
That that would be amazing to see.
50:51
You know, I've I've seen these wambos uh be spread amongst not just young people, but you know, the older generation is starting to use them a little bit too and I'm I'm thinking about expanding it to sort of include some of the older generation slang as well and I've had some people request that.
51:06
So I'm trying to expand this and try to make it more universal. >> Yeah.
51:09
What So what was the first wambo what like what what really drew you to wambos?
51:13
What was the first You know, honestly, I saw a video and I basically just it was they had put the low kirk into logical low state Okay.
51:22
>> [laughter] >> word together and I was like, oh, I can just make this longer and I just went ahead and added a word to it and then it kind of blew up.
51:28
It took off and I was like, okay, I guess I'm pretty good at this. That's great.
51:32
>> Uh so I just kept going with it and then before you knew it, I had basically the world's longest word ever said in one breath.
51:38
So now you know, I have this you know, the this crazy long word now that you know, people are trying to learn and and it's just grown from there and now I'm just creating original wambos and I'm I'm sure you guys have seen and and everybody's seen that you know, people are using these wambos all over the place in schools and you know, just out in daily life and so it's it's really been a a movement that I was not expecting. I love it.
52:00
>> Do you can you can you one shot your longest word?
52:02
Like is it on is it on command or do you do you need to iterate through it?
52:07
No, I can do it on command.
52:07
Do you want to do you want to do it?
52:12
>> [laughter] >> Sure, I'll try it. Okay, here we go.
52:15
low kirk into logical low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low
52:24
state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state with a low kirk into low state Wow. There we go. I wasn't expecting to There we go.
52:35
I wasn't expecting to do that, so I can't believe you pulled that off.
52:41
Are you actually a professor?
52:41
Like what what is your background?
52:43
How did you get into this?
52:45
It was this just a side hustle that just went mega viral?
52:47
Like what what is your story? Yeah, okay.
52:51
So basically I I I don't I'm not a professor in real life, but I have a master's in education, but I don't work in education.
52:59
>> Okay, got So I I don't have a background in words either.
53:01
I just I used to be a rapper a long time ago.
53:02
People ask me how how are you so good at doing this?
53:06
How do you put these words together?
53:06
And I just tell them, you know, I it's a natural skill I have and then I used to do it back in the '90s.
53:11
I was like one of the original white rappers from back then before Eminem was even around. So >> That's amazing. Wow. No way.
53:17
Yeah, and so I've been doing it for a long time, so Yeah, we were reflecting earlier on >> Born born too late to explore the earth. Yes.
53:26
>> Born too early to explore the stars. >> Yes.
53:29
Born just in time to be the leading expert on wambos. >> Yes. For sure.
53:34
>> [laughter] >> Perfect. Yes.
53:34
Yeah, we were reflecting on the fact that I'm I'm not sure how familiar you are with this, but like the Silicon Valley in particular went through like a series I mean they could call them portmanteaus back then, but wambos were very popular.
53:47
You have Pinterest, Instacart, Instagram and there were like a thousand other companies where that was the default pattern for naming a company because the dot com would be available.
54:00
It would be very hard to go get, you know, pin you know, interest.
54:05
com or you know, order shopping like like you know, grocery store.
54:09
com, but Instacart was available and so people would sort of match these up.
54:15
And I'm wondering if you've if you've gone back and looked at any historical portmanteaus or wambos that have broken through and maybe need to be like revisited and re re re-ignited or is it all just forward into the crazier and crazier phrases?
54:31
You know, it's I think it's mostly forward looking.
54:32
I've seen a couple that were old school.
54:34
So I know there was one that was like a calculator.
54:36
It was like an old ad from the 1979 or something like that.
54:40
Wait, this is a calculator this is a calculator that's a lighter, too.
54:44
Like if you want to smoke smoke while you're doing math.
54:46
box of calculators [laughter] and it's got a little lighter thing coming out of there. It's amazing. That's amazing.
54:52
Yeah, and and so another word so I haven't really visited a lot of older words.
54:59
Honestly, so there was a word that came out in the dictionary the other day, choppleganger.
55:02
So that word is actually not mine. So Okay.
55:03
I'm not I'm not going to >> you Merriam-Webster needs to hire you like immediately and start getting >> they do.
55:10
You know, I I want to get I want to get quiche penimus in there. Yeah.
55:13
And explain explain that wambo Explain that wambo.
55:16
>> Yeah, so so basically quiche penimus is like one of the big ones that people are using and so that's like quirky niche and then penimus is peak cinema analysis. Yeah.
55:27
Sorry, I just [laughter] I'm like the I'm like the overachieving student, you know. I studied.
55:31
So So we we we we integrate these words. >> Yeah.
55:35
I I personally I use I use I use quiche Lorraine more. Yes.
55:40
>> Quirky niche lore explained.
55:40
Yeah, that's a handy one. >> professor.
55:45
>> [laughter] >> Yeah, so I love quiche Lorraine.
55:45
I actually have a new version of that.
55:47
I don't know if I can actually say it on your show.
55:50
I I don't know the the limits, but so it's quiche Lorraine-o-visions. Oh, yes.
55:56
So it's basically like you take quiche Lorraine and then you mix it with anal visions. Which is analysis. >> that here.
56:02
It's pretty We try to keep it a little family friendly show, but it's analysis vision to be clear. Is that right? It's analysis revision.
56:07
So it's basically if you do one of those, you're basically just doing an analysis revision of it. Yeah, that's correct. Yeah.
56:13
How how much time are you spending trying to come up with like when when I think of quiche and Lorraine, I think of you know, short usable phrases that actually could work their way into the American vernacular.
56:26
Whereas with the low kirk into logical I don't think anyone's actually going to pick that up.
56:31
It's more of like a stunt.
56:31
It's it's impressive, but it's a different style of content.
56:35
I use I use Lorraine all the time.
56:37
I'll say John Lorraine Intel's earnings. >> Yes, yes, yes.
56:41
But how much time are you splitting between these?
56:44
Like do you think that there's something innate about being terse and short that will actually allow a wambo to break through and ideally make it into the Merriam-Webster's dictionary?
56:57
Yeah, I actually have a theory behind like how to make effective wambos like that.
57:00
So I think like you're saying short wambos are good.
57:02
Something that sounds good. >> Yeah. It has to sound good.
57:05
So it's like the quiche, it sounds good. I I I don't know.
57:10
I just it sounds nice when you say it.
57:12
Some words just Yeah, it's almost like where you know, the pharmaceutical companies, they come up with these names for the drugs and you're like that does sound like a thing, but I never would have guessed what that is and it doesn't sound just like you pounded on the keyboard.
57:25
You got like Ozempic, which like sounds like a drug for some reason.
57:30
It's just like, but it's from nothing and and those things tend to break through.
57:33
Also, I feel like choppleganger really jumped straight into Merriam-Webster's because it it feels like like with the with a very little amount of work, you can you can reverse engineer it.
57:47
And and that also seems to be key to getting some wambos to break through is is can someone take a guess and get 80% of the way there and then sort of you know, peak their interest and then go a level deeper and understand the whole the whole lore.
58:01
Talk about >> [clears throat] >> talk about the origins of nonchalash out.
58:06
That's one that we've been using for a while.
58:08
Once you know that wambo, which is nonchalant crash out, you just see it everywhere. >> You do. It's constant. It's everywhere.
58:15
Every time I open X or Instagram or YouTube, someone's having a nonchalash out. >> Yeah. Yep, pretty much.
58:22
So yeah, nonchalash out is basically when you look nonchalant on the outside, but then on the inside you're crashing out.
58:28
So I mean, I think a lot of uh people can can do this.
58:34
You know, for example, that the CEO of McDonald's, you know, when he was eating that burger, I'm pretty sure he was having a nonchalash out when it was happening. [clears throat] Yeah.
58:42
>> Yeah, he looked pretty calm on the outside, but on the inside I'm pretty sure he was freaking out a little >> he was in a dark place for sure.
58:46
So so so with something like nonchalash out or any of these other examples, how much of it is there is a phenomenon that because a nonchalash out is a thing that we didn't have a word for in English before.
59:00
It but it has existed probably for you know, entire human history. This has happened.
59:05
Uh but how much of it is you you see something and you say, that deserves a wambo versus you're just sort of grappling with different phrases and then you piece and you find examples.
59:18
>> professor, caps absolutely.
59:18
When you I would use this personally if I know someone's just basically you know, BSing kind of like lying to me, I'd say caps absolutely.
59:27
You >> [laughter] >> You You to agree.
59:30
>> Well, here's the here's the secret, okay?
59:32
So, I I'll let you in on this.
59:32
So, when you when you make a word, if you find an opposite word and you kind of make the word a paradox.
59:37
So, like a nonchalash out doesn't really make sense, right?
59:40
Because it's like how can you be nonchalant and crash out at the same time?
59:43
But, when you put them together, you really think about it, all human behaviors are kind of paradoxical.
59:48
They all they all have like, you know, this aspect and this aspect.
59:50
So, like another example would be liguratively.
59:54
So, that's figuratively and literally.
59:56
How can something be figurative and literal at the same time? >> Yeah.
59:59
But, it's kind of possible.
59:59
If you really think about it, you can like literally mean something figuratively or you can figuratively mean something. >> Yeah.
1:00:05
You can literally mean it halfway, you know?
1:00:08
It's all about the words and how you put them together.
1:00:10
>> anti- anti- antithesis create the synthesis. >> Right.
1:00:13
Uh the >> Jam them together and you can really come up with some beautiful wambos that way.
1:00:17
That's that's really kind of the secret to a lot of it, for sure.
1:00:19
Uh where do you want to go with your creator journey?
1:00:23
Because I I was thinking like Instagram reels notoriously hard to run ads or monetize.
1:00:31
Uh I don't know that there's an obvious like Patreon paid podcast play here maybe.
1:00:36
I would be interested in listening to you talk about etymology and and language for hours, but uh I was thinking like brands should be paying you to create wambos about their products or their brands and and and that would be sort of synergistic with like what the audience expects, what would actually go viral, and what you could actually get paid for.
1:00:56
But, are you early in the creator journey?
1:00:58
How are you thinking about this as a business?
1:01:03
Yeah, so right now I'm working on a dictionary.
1:01:04
So, I'm hoping to use that as a you know, as the step stone to launching my products. I've got it.
1:01:11
Yeah, so I've I think I think coffee table like a coffee table book.
1:01:13
Like the great book of wambos, you know?
1:01:17
Something you can proudly place on a coffee table as a conversation starter.
1:01:22
>> have a book like where I can put it on the table and people can just like flip through it.
1:01:26
I want it to look real nice and I want it to be like a really great item to have.
1:01:30
>> But, also you know, like a coffictionary.
1:01:31
A coffee table dictionary. A coffictionary. We're working on these. >> [laughter] >> Sorry. There you go.
1:01:37
You're coming up with stuff. >> I'm working on it.
1:01:39
But, yeah, what what else are you cooking?
1:01:42
Got to keep on going, yeah, for sure.
1:01:43
But, but yeah, no, no, I'm early on in my journey.
1:01:45
So, I'm I'm looking to, you know, work with some people and I'm I'm looking to make some books and just looking to keep on building what I'm doing right now.
1:01:53
And I've only been growing for like 4 months now almost.
1:01:56
So, I mean I really haven't Yeah, I I was I was Yeah.
1:02:00
>> barely there at in January and so it's just exploded.
1:02:02
So, it's it's still kind of the beginning right now. So, Yeah.
1:02:03
Um yeah, there there's so many opportunities.
1:02:07
So, it's it's really looking up.
1:02:08
Yeah, we had someone on the show whose whose whole job is coming up with names for tech companies, tech products.
1:02:15
Didn't he come up with the name Sonos and a few others?
1:02:19
And I feel like that's a like you you your your grasp on the English language is sorely needed among some companies that have very complex product names.
1:02:30
And so, uh I I I see like a a bright future in a bunch of different ways, but eagerly await about the the coffee table book. Anything else, Jordy? No, this was super fun.
1:02:41
We're having Gary Gary V on in just a couple minutes.
1:02:47
And we'll ask him ideas on how to monetize Professor Sandy in the wambo universe because I feel like he could I think I think he'll have some ideas.
1:02:55
Do you >> Yeah, that would be amazing.
1:02:57
And yeah, if you're Yeah, mention me to Gary V. That would be very cool. That's awesome. Yeah, appreciate that.
1:03:04
>> do you experience anything different across the platforms?
1:03:05
I know we follow you on Instagram. I know you're on TikTok.
1:03:09
Is there anything that you've learned from like the different platforms? Definitely.
1:03:13
So, TikTok I think is more for discovery.
1:03:15
So, if you know, if you do something that's completely novel, that video can really blow up.
1:03:19
I think Instagram is much more generous with its views.
1:03:24
But, I think you can really build a solid base more on Instagram.
1:03:26
I just feel like TikTok's more for discovery, Instagram's more for growth and personalization of your brand.
1:03:33
>> Have you tried have you put these on YouTube shorts yet? What's that?
1:03:37
>> Have you put them on YouTube shorts yet?
1:03:39
Just because it's a small platform.
1:03:40
>> I used to do YouTube and I just I don't know if it's going to fit on on that platform. I just I don't know.
1:03:43
I'm I'm hesitant to go there and I've been hesitant to go on Facebook meta just because I don't know if it'll work and I just I I used to do that and so I'm just I'm not sure about it yet. So, we'll see. We'll see. Okay.
1:03:55
Well, thank you so much for taking the time to join the show. Fantastic talk.
1:03:59
Thank you for all your analysis and teachings.
1:04:01
I it has brought brought both of us so much joy.
1:04:04
Like not just watching the videos, but using them.
1:04:09
>> We got our lawyer to use quiche Lorraine once and we were very very happy about that.
1:04:14
>> that is that's a high compliment. I appreciate that.
1:04:16
Thanks for telling me that.
1:04:17
It was it was remarkable.
1:04:18
>> Jordy and John, I appreciate you guys having me on. I really do. Yeah, you're the man. We'll talk to you soon. >> Great hanging.
1:04:22
Have a good rest of the day. Goodbye.
1:04:26
Uh Greg Brockman's apartment is for sale where they started Open AI.
1:04:32
Sheel Mohnot says, "I do not think there's an opportunity to build an Open AI themed Airbnb by the way." But, who knows?
1:04:38
Maybe some filmmakers will pick it up.
1:04:40
It is a three bedroom, two bath in San Francisco, 1. 545 million dollars. 1,800 square feet.
1:04:48
It is a it is an incredible piece of of lore that Open AI started in this particular apartment.
1:05:00
Yeah, this this this feels like it will go quickly. Yeah.
1:05:03
Like there are so many people in San Francisco that would be that that might need a place.
1:05:10
And to just snap up the place that Open AI was effectively formed. >> Yeah.
1:05:15
I remember some of the early early photos. Good times.
1:05:16
We should go to this video from Zane Shaw.
1:05:19
Imagine every pixel on your screen streamed live directly from a model.
1:05:24
So, this looks like a website.
1:05:27
And when I saw this, I thought that it was a website.
1:05:30
I saw a URL at the top and I was like, "Oh, this is a cool demo for some sort of you know, tour of Notre Dame website." Probably vibe coded.
1:05:38
A testament to what the modern coding models can do. But, it's not code.
1:05:43
This is what you are seeing is is actually not code.
1:05:49
It is there's no HTML, no layout engine, no code.
1:05:51
It is it is a diffusion model that is rendering this as the input is given.
1:05:58
And so, you can think of it this almost like those world models, those generative video games where you walk around, but this is sort of a very very early glimpse into sort of what the future of generative UI might look like.
1:06:13
Jordy, why are you laughing?
1:06:15
Cuz the chat is doing a bunch of wambos. Oh, okay.
1:06:17
We got to work on wambos.
1:06:20
We will be integrating those more in the near future.
1:06:22
But, we have our next guest in the waiting room.
1:06:24
Gary Vaynerchuk from Vayner Media. Gary, how are you doing?
1:06:29
Welcome back to the show. >> wambos? I do not, my friend.
1:06:34
>> You got to learn about wambos. They are the next meta. They are the next meta.
1:06:37
If you're not doing wambos in 2026, you're getting left behind.
1:06:41
>> So, wambos are word combos.
1:06:41
So, the example would be a quiche is quirky and niche.
1:06:48
You put it together and that's quiche. Or Lorraine. Lore plus extreme.
1:06:54
That that that's a that was a risky start for the first word.
1:06:55
I'm Yeah, that's a much Lorraine Lorraine is a better Lorraine is a better one.
1:06:59
Give me if I say Lorraine First first and foremost, congratulations. Thank you. Thank you. I really appreciate it.
1:07:11
>> Uh I remember I remember our very first call.
1:07:13
I think it was in Q1 of 2025.
1:07:13
So, we were just maybe like a little a little just a few months into the show and you even at that point we were very very very small.
1:07:22
I think we had maybe just gone live a few times.
1:07:26
And you told us you guys you said go harder.
1:07:30
We were already going pretty hard, but you said go harder. And we certainly did.
1:07:34
So, And go multi-platform.
1:07:36
That was really huge, too.
1:07:38
You you you were you were very early in like, "Why aren't you have a newsletter right now?
1:07:42
Why aren't you on YouTube in multiple ways?
1:07:43
Why aren't you on Instagram yet?"
1:07:45
And so, we did the uncomfortable thing of posting pretty subpar content for a while, but it started the compounding very very early and now it starts really much better.
1:07:56
Everything start starts subpar, right?
1:07:59
Like when you start working out or when you start singing or drawing like, you know, like I for everybody who's watching right now, every business, every personal brand, every B2B, every B2C, the to to not take advantage of the attention media landscape that's in place right now, um it it's really incomprehensible to me.
1:08:22
It's there's never been a time in the history of humanity or business where the cost of distribution is zero for the distribution.
1:08:29
It's there's costs in the content and then what do you do it, but the upside is so extraordinary against the investment.
1:08:38
And when you frame it up properly, multi-channel, multi-format, the the business outcomes can be extraordinary and I'm happy to see you guys get one. Yeah. Thank you.
1:08:48
Are you Is it Is it Is it funny that Is it funny to you that that it feels like it feels like in some ways we're like a decade into live streaming and yet two decades Well, yeah, two decades by some measures, but like Twitch has been big for a long time.
1:09:04
There's been so much attention there.
1:09:09
I wrote this book in 2008. It came out in '09.
1:09:11
Crushing in the back of the book, I talk about Ustream and live streaming.
1:09:16
Yeah, I mean, you know, it ebbs and flows.
1:09:18
And to your point, like I mean, I can't even comprehend the economic impact live social shopping is going to do over the next 10 years for humans and consumer businesses.
1:09:26
Um yeah, it's all the same stuff, brother.
1:09:29
It's always been around forever and it's always the beginning, right?
1:09:33
Like it's just kind of the way consumer behavior and human behavior works.
1:09:37
Um Yeah, it does it does surprise me how many more people have not replicated the very, you know, basic digital framework that you guys executed in this genre.
1:09:46
It's available >> Well, the interesting the interesting thing is we there's there's easily been a hundred a hundred shows that have like taken some level of inspiration from what we're doing.
1:09:59
It's still very very hard It's still very very hard to break through, right?
1:10:03
There's it's not just it's not just the overlay and the format, but I have been I I've been very confident.
1:10:09
I've said this on podcasts for, you know, we've talked about this going back probably six six to eight months ago.
1:10:17
You should take this format of a live stream and you just add an extra level of production beyond you just have a laptop there and you're hanging out and you apply that.
1:10:25
The example we'd always talk about is like cooking where all you need is like a cool kitchen. You That's your set.
1:10:32
You have a couple of cameras so you have different angles and then you just say, "Hey, every day at 3:00 p. m.
1:10:37
I'm going to cook dinner.
1:10:37
This is what I'm going to cook. Here's the schedule.
1:10:41
You can make dinner with me."
1:10:43
And I think that that's like an entire niche that you could build around.
1:10:44
You could integrate guests into something like that, too.
1:10:48
So you have different, you know, content creators coming through every day.
1:10:51
And then I think you can apply that to a bunch of other things.
1:10:54
Sports has honestly been the most advanced in terms of live streaming.
1:10:58
Um so credit credit to them.
1:11:02
Yeah, I mean it's it's it's there for the taking.
1:11:04
A lot of things are there for the taking. Yeah.
1:11:08
Uh how are you thinking about uh how branding and marketing will evolve.
1:11:12
I had this interesting moment this week with the uh GBT images two launch where suddenly any brand like basically fully democratized high-quality product photography.
1:11:24
Now, there's still categories where like I don't want you to AI generate the the product photography.
1:11:30
Like even apparel's actually interesting where like fit matters a lot.
1:11:33
And so if you generate a bunch of AI images of your shirt and then I buy it and it doesn't fit well, like I'm not going to be happy about it.
1:11:41
But for a bunch of categories it's cool.
1:11:44
And I was kind of have this like kind of strange moment where uh it used to be you could identify an entrepreneur's ability by their product photography in some way cuz even somebody's like bootstrapped and scrappy, like they would find that friend and say like, "Hey, do me a favor.
1:12:00
Help me get some great images."
1:12:02
And you could kind of categorize like a company that you're seeing online like, "Okay, could this person figure out how to get great product photography or not?"
1:12:09
But now the bar is just so much lower.
1:12:11
You're you're like a couple prompts away from it.
1:12:12
And so it feels like it's going to be harder than ever to stand out online.
1:12:19
Well, I mean there's a lot there.
1:12:20
I mean it's we just got done talking about how hard it is to stand out online. Right?
1:12:27
Like Like the the cost of entry is zero.
1:12:29
But, you know, this is a competition.
1:12:33
Like, you know, everyone's trying and so everyone will make content, video, picture, audio at a level that is incomprehensible to all of us that were born prior to 5 minutes ago.
1:12:47
And this will be another transition.
1:12:50
I think you know, there's there's always going to be um a timing game to this, right?
1:12:57
So right now, you know, like this open claw, you know, allows me to do things that a lot of people aren't thinking about right now.
1:13:07
And me knowing that and me playing with that.
1:13:09
And then even more interestingly, >> [clears throat] >> how creative or strategic am I with the agentic agents?
1:13:15
And what are they doing for me? And how do I understand?
1:13:17
Blah blah blah blah blah.
1:13:18
So I think it's kind of always going to be the same thing.
1:13:21
Like whether it was electricity and some people put electricity in their home and other people were scared to cuz there was demons in it.
1:13:26
Or, you know, the car or the the, you know, the typewriter is one that I've like been fascinated by the competitive advantages of the companies that actually brought typewriters in versus, you know, putting penmanship on a pedestal.
1:13:39
You know, like it's just and computers and the internet and mobile devices and open source versus closed source and social media.
1:13:47
Now AI, you know, look, this AI thing is no joke. We all know that. It's big stakes. There's a lot to it.
1:13:57
But, you know, I still think whatever that human was to being scrappy to find them friend for the photography, you know, that scrappiness is going to be deployed into something else, right? >> Totally. Totally.
1:14:09
And so I also think >> Right?
1:14:12
And I also think that we're about to see the explosion of analog, right?
1:14:16
Like I think this barbell that I keep thinking about >> Totally.
1:14:18
I I've been thinking like, "Okay, you want to start an apparel brand?
1:14:21
Do you want to go on Instagram or TikTok and duke it out with like 10,000 other brands?"
1:14:25
Or why don't you like find somebody that has a retail store that they can't rent out and like do a deal with them and just try to get big in your hometown again. You know.
1:14:35
>> And and my argument would be would be and. Yeah. Right?
1:14:39
Like Like to me this bar Like I just extreme AI I think is creating extreme analog.
1:14:45
I really do think it's a barbell.
1:14:47
I think in the next 10 years, obviously it's 2036, but I feel like it's going to feel like 2050, which actually is bringing the rise of 1950.
1:14:55
I couldn't be more impressed with what Ari Emanuel and others are doing that are investing in all these analog businesses.
1:15:02
I I could not be more interested in physical retail, in event-driven businesses, in concerts and venues.
1:15:10
And I I think the the rise of analog I have a restaurant business uh [clears throat] part of a restaurant group.
1:15:17
I keep pushing my partners who really operating, "Let's open a restaurant that makes people check in their phone as soon as they walk [clears throat] in.
1:15:23
Let's put people in group tables."
1:15:24
Like I think you know, you see what's happening with flip phones. Yeah. Gen Alpha buying them. We see vinyl sales.
1:15:32
You know, I've been very at the forefront of collectibles.
1:15:33
I felt collectibles was something tangible and was a gateway drug to community.
1:15:38
If you've never been to San Diego Comic-Con or the Sports Card National or Fanatics Fest.
1:15:45
So I think there's a lot of interesting non-digital realities that are coming as a counter move to the insanity of AI advancements.
1:15:51
We're literally within a half decade not believing a single video.
1:15:56
Not a single video that's on the internet.
1:16:00
Like in 5 years if we're having this video this interview right now, >> Yeah.
1:16:05
most of the audience is trying to figure out if we're real or not.
1:16:08
>> [laughter] >> That is That is very real and has real substantial counter opportunities. So Yeah.
1:16:16
you know, the photographer who's sad when they hear that. I'm like, "No, no, no.
1:16:20
You might actually crush in a different way."
1:16:22
And so I'm curious to see what what the counter uh scaled moves are going to be of the next decade.
1:16:28
And I think for any real entrepreneur, they're not crying about AI killing them.
1:16:34
They're curious about what AI at scale is going to create opportunity for them. Okay. Totally.
1:16:39
I let's go deeper on analog.
1:16:42
I want your reaction to this headline that for the first time this century vinyl music sales eclipsed $1 billion in a calendar year.
1:16:52
Sales of vinyl records are up something like 10% in 2025.
1:16:58
Yeah, they're effectively like 10% of like global streaming revenue is just vinyl still. It's bigger than CDs.
1:17:04
It's making a bigger comeback than other formats.
1:17:09
What What is your What is your reaction?
1:17:11
Is it people looking for wall decorations?
1:17:13
Are they actually listening to the vinyl?
1:17:15
Do you have any idea of like what we should read into that idea of this nostalgic format coming back?
1:17:21
>> Are you in your I mean, do you see my shelves here?
1:17:23
Like only thing I've been thinking about for the last 7-8 years or not only, but like very hot on this.
1:17:28
Yeah, I mean the answer is yes to both.
1:17:30
Some of it's happening with decorative.
1:17:32
A lot of it's happening with collectibles.
1:17:37
Even more is happening with subconscious counter push to extreme digitalization. >> Sure. Mhm. Yeah.
1:17:44
There are people This is By the way, one of the reasons we're not going to see unlimited television commercials and social media content that's just pure AI from the biggest companies in the world is every time they try to go there, you probably touched on your show, McDonald's, others, they get such backlash cuz the whole world is so scared that AI is going to take their job that the consumer's pushing against it.
1:18:03
And then that's one part.
1:18:06
And then the second part is, yeah, people are starting to do counter behavior consciously and unconsciously.
1:18:12
And um and and then there's just swings of swings of trends like you know, like music sounds great in a great record player.
1:18:20
And like people go, "Oh, this is kind of cool, too."
1:18:22
And like it becomes [clears throat] behavioral.
1:18:24
It It You know, it starts in the same stuff. You know this.
1:18:27
It's like the Brooklyn extremists are like, "Let's go, you know, hippie cool culture."
1:18:31
And they get their little thing in a little sub pocket.
1:18:35
It bleeds out a little bit.
1:18:35
Then the Manhattanites feel like they're not cool anymore.
1:18:38
So they do it to keep up with the Brooklynites.
1:18:40
And then we have that version everywhere in California, Texas, and Florida, and everywhere in the world.
1:18:44
And so it's just it's normal consumer behavior, but I it is clearly a counter point to extreme in feed, in digital consumption.
1:18:54
And I think that's great.
1:18:57
It It's It speaks to the thing I most believe in, which is humans correct themselves at a level that we are unbelievably underestimating.
1:19:03
The the sheer adaptability of the human race is extraordinary. Let's give it up for us. Uh Sports. Well Well said.
1:19:11
I want to talk about sports.
1:19:15
>> Yeah, I mean sports are a good example. We were talking earlier.
1:19:16
A friend of the show, Josh Kushner, is looking to acquire a stake in in the Giants and out of his new eternal fund, which is basically a will seemingly be a collection of like, you know, evergreen bets that aren't that can't be disrupted by AI because I don't want to watch simulation of the Giants.
1:19:36
The sphere is another good example. >> Crazy.
1:19:38
Everyone was thinking that that was not going to go well.
1:19:40
They were worried about the debt and the stock is up like 3x. It's done very well.
1:19:46
How are you thinking about both opportunities in new physical locations like the sphere and then also in the the the the more legacy brands like the San Francisco Giants, the New York Mets, the different sports franchises out there? Yes.
1:20:05
>> [laughter] >> I I You know, it's really interesting to tie a couple things together.
1:20:11
This distribution channel that you and I are on right now, right?
1:20:16
The fact that people watching. >> Yeah.
1:20:20
In in a way that 40 years ago somebody would have had to say, "You guys are good faces and you look good and you're charismatic and you might get a shot on this distribution."
1:20:27
This decentralization of distribution along with with this analog and not disrupted by AI thing is why six or seven years ago I started investing very heavily in alternative sports.
1:20:38
So, made a big bet on pickleball that I think is going to work out quite well. >> Yeah.
1:20:45
Uh you know, Unrivaled, the three-on-three basketball league, AJ and I, my brother, early investors in that. The Wiffle Ball League. The sailing league. Um Slamball.
1:20:53
I so I've been very aggressive on alternative sport investing. Padel.
1:21:01
So, I'm very bullish on it.
1:21:01
I think Josh obviously plays at a at a very heavy economic level with his funds and that nature and everyone like him and others, especially him, I have so much pride in his building cuz he's done such a great job in New York City baseball.
1:21:15
We were always like NBA's the best app.
1:21:17
So, it's been great to his him thrive shine.
1:21:19
I think all Anyone who does not realize how substantial the analog opportunities are is is really missing the plot of what's happening. And so it gets exciting.
1:21:30
It's exciting to think that you can invest in both something that could get as big as you know, Anthropic in a an extreme digital world, but also forget about the obvious ones like the Giants or the sphere.
1:21:41
I'm talking about people rolling up 900 local restaurants and building up a huge like like it compounds 2x what anyone in PE would have thought because people want to go physically out and eat instead of just do seamless.
1:21:55
You know, somebody buying up shopping malls not to make them data centers, but because they think they can make a half experiential, half old mall shopping environment that people are going to be yearning for.
1:22:10
Here's a left field one like the the drive-in movie theater, right?
1:22:14
The stuff that dominated the '50s and '60s.
1:22:16
When I say that out loud, I'm [clears throat] like, do you think a modern drive-in movie theater, which has done really well and executed super well, do you think that a lot of people would be about that life?
1:22:27
I think we can all agree that yes. >> 100%. Yeah.
1:22:29
And then what happens to the person that does 39 of those and has a real business and flips it.
1:22:34
So, I I think it's a really cool time for a lot of us that have watched this show.
1:22:39
We're like, "Oh crap, we can play on either side of extreme digitalization or analog. Be creative."
1:22:48
>> Well, yeah, the the beauty of you know, give the the example of somebody making like a modern chain of drive-in movie theaters is like you get all the benefits of AI still.
1:22:57
You get to You get to use it for to instantly respond to any customer message and help solve problems.
1:23:03
You need to build a >> to this? Now we're nerding out.
1:23:07
What if you have 40 of them and now this is seven years from now and you start showing your own films that you make in AI and build your own IP through your own analog distribution? Yeah.
1:23:17
Oh, that's a >> Yeah, I could see I could see doing that for kids.
1:23:21
You know, like maybe slightly lower bar, but you create your own kind of kids kids content.
1:23:28
>> Again, a lot of things I do get more obvious later.
1:23:30
I got made fun of writing that book.
1:23:32
Anyone can personal brand on Twitter.
1:23:35
Now it doesn't look so funny.
1:23:38
>> [laughter] >> Who's laughing now? Who's laughing now? Yeah.
1:23:42
But when I started building VFriends and like building this Pokémon Sesame Street thing, yes, there was a lot of blockchain in it, but it was a lot of my smartest friends in Silicon Valley five years ago were like, "This AI thing is percolating."
1:23:52
You know, it was a little more slang for machine learning and then it obviously got accelerated real quick, but like Yeah, I believe in a lot of this stuff.
1:24:01
Well, speaking of people that are watching this show, there is an army of people named Ryan in the chat and they want to be acknowledged by us.
1:24:07
So, I'll ask you a question about a Ryan from your life.
1:24:13
Can you tell me something you learned from Ryan Serhant or Ryan Holiday or maybe Ryan Harwood?
1:24:17
Do any of these names conjure any interesting stories or life lessons?
1:24:22
Yeah, the Ryan might be as good.
1:24:24
I mean, Ryan Harwood I've learned nothing from. Zero. Absolutely nothing.
1:24:28
So, I'll just put that on the deck.
1:24:31
>> [laughter] >> Uh you know, Ryan Holiday was definitely the individual that I was like finally put a word to kind of how I was living my life, right?
1:24:39
I You know, my mother's my hero.
1:24:41
She taught me just how to be a really happy human.
1:24:43
You know, I thought it was immigrant and I thought it was simplicity and I thought it was, you know, love and health over everything and truly truly not just cliche but live your life that way even if you're an entrepreneur and a capitalist and want to compete.
1:24:56
But when Ryan Holiday started talking about being a stoic and stoicism, I was like, "Oh."
1:25:04
Like you know, like I was like, "Oh that sounds LIKE OH, THAT THAT THAT'S INTERESTING."
1:25:10
And so I think that that's one for him.
1:25:15
Serhant, you know, is a fun one for me because a lot you know, he's obviously playing at such a big personal brand level now and it was he had that TV show on Bravo and then it was off the air.
1:25:25
You know, his curiosity and humility was amazing.
1:25:28
Like he was always around our ecosystem and he really learned to play the playbook I've lived, you've lived, he's lived.
1:25:35
So much of you know, now he's back on Netflix, but he had a really great era in between his television moments of really winning on social and going all in and I'm really proud of him.
1:25:45
And Harwood is uh is just a dear actual friend.
1:25:48
He's family, not even friends.
1:25:50
So, I he's taught me that uh I'm glad you circle glad you circled back cuz I was like, "Damn, he's taking shots."
1:25:58
>> [laughter] >> You know, in you know, he's a Long Island boy, I'm a Jersey boy.
1:26:01
I think anyone from our part of the world knows like taking shots to your brothers is like the ultimate form of I love you more than any I I think literally from from 1985 to 2000, 98% of the words out of my best friend's mouths was highly disrespectful in my direction.
1:26:23
>> [laughter] >> Of course, that's the best.
1:26:23
That's the only way to do it.
1:26:26
Ryan Holiday wrote Trust Me, I'm Lying: Confessions of a Media Manipulator at 25.
1:26:31
Should more young people write books?
1:26:33
I talk to some brilliant young people every day on the show.
1:26:35
A lot of them fantasize about writing a book, but it always feels like it's something that needs to come with wisdom, that needs to come with being 40, 50, 60.
1:26:44
Yeah, do you get a lot of wisdom you but but part of it is like you're generating wisdom through writing, thinking deeply.
1:26:51
Do you feel like I think of it this way, man.
1:26:54
I think it is that's weirdly back to my barbell.
1:26:57
I think people that have something to say will probably be best at the barbell.
1:27:03
You know, meaning it's kind of like someone's first album.
1:27:05
You had your whole life to write it. Right? >> Yeah. Yeah.
1:27:09
And then so I don't know.
1:27:11
For me, speaking for myself, like again back to the books, like when I look back at that, I'm like, how like and I'm pretty like I don't know.
1:27:20
Feel good about myself and we have me and me have a good relationship with each other, but even I would like I look at it and I'm like, "How the hell did you write that in 2008?"
1:27:28
And then and then to your point, I think my next next best piece of work will be when I'm wrapping it up and I can synthesize all the good stuff.
1:27:35
So, I would wildly encourage, especially the kind of characters you guys hang out with.
1:27:41
They have a lot to say cuz much like I had in my youth, I saw things others couldn't see because I wasn't playing by yesterday's rules.
1:27:49
I always say fresh eyes are dangerous eyes. You know nothing. It makes you dangerous. You can really innovate.
1:27:55
And then I think those people that, you know, have sustained careers and can have years of wisdom and chapters have a lot to say that can really wrap up and bring value.
1:28:06
So, I think most people if they're going to be in that game are probably going to write their best book first and last.
1:28:15
Uh you partnered up with MasterClass. Yeah. >> Tell us about it. >> Tell us about it.
1:28:21
You know, I 15 years ago anything that looked like MasterClass like selling stuff was really scammy.
1:28:27
Like I grew up in the web 1.
1:28:29
0 era and like I stayed away from a lot of subscription, Patreon, OnlyFans, MasterClass.
1:28:35
Like selling information was really dirty in '97, '98.
1:28:38
$150 ebook that was straight garbage.
1:28:43
I I want to give MasterClass some flowers.
1:28:45
Like when they first kind of hit the scene around that era, we were just getting into the earliest stage of where [clears throat] we are now where premium content, you know, Substack, Beehive.
1:28:54
Like Now it Now it's respected, which is amazing and I think it's great for a lot of individual writers and contributors.
1:29:03
Um you know, it was really good company.
1:29:05
Like I I like who they had for this class.
1:29:07
It's addressing something I believe is real, which is like getting an MBA in real life and AI at you know, pennies versus taking on extreme debt and getting an MBA from a high-class university that you think that logo is going to get you financial opportunity in a way that I believe has passed us by.
1:29:29
Um, you know, just feels like I want to be part of things that are historically correct or, you know, are just a little more practical and common sense.
1:29:34
And so, um, yeah, I mean, they've come to me a whole bunch of times.
1:29:40
This was the first time I was like, you know what?
1:29:42
I can join [clears throat] this crew.
1:29:44
I have something to say about AI marketing and and production and and the strategies of that.
1:29:50
And and I hope that, you know, me or Cuban or any of the other people they threw at it like get someone to stop and not take on $300,000 in debt that's not going to be ROI positive. >> Mhm. Yeah.
1:30:01
Uh, what are you hearing from sort of like Fortune 500 CMOs, uh, like larger company marketers around how if anything they should change in the world of AI around their marketing mix?
1:30:17
Um, I'm giggling cuz we're going to wrap up here and I'm actually going to take your question but try to give an extraordinary amount of value to everyone that I know listens to this epic show.
1:30:27
It's not what they're saying, it's how they're acting, which leads me to the following sentence.
1:30:34
Everybody who's watching is highly invested in big companies that spend a lot of money on marketing.
1:30:38
Your marketing department is wasting 93 cents of every dollar they spend. >> [laughter] >> Okay.
1:30:44
We are living in such a radical transformation of the mid funnel dominating not the upper funnel and the lower funnel. >> Sure.
1:30:52
You us three right now are on mid funnel. Yeah.
1:30:54
We are producing content. >> in the mid funnel.
1:30:58
>> [laughter] >> I mean, look, I mean, this is what's going on in my own I'm doing.
1:31:02
>> [clears throat] >> Right?
1:31:02
This This is a production day. Yeah.
1:31:04
This will be post-produced into creative that will go in the mid funnel organic social and the things that do well will go up for brand and down for performance. Mhm.
1:31:16
Every brand on earth should be spending the 20% of their entire marketing budget just on social media organic production because the mid funnel and TikTokification of social has eaten up the world and we should spend no media dollars against creative that we're guessing for the big campaign.
1:31:32
And then when I tell you every Fortune 5000 company is still doing guessing on the upper funnel sponsorships, ridiculous And then the lower funnel 2016 AB testing beta frameworks when the mid funnel ate up the whole world and you guys are winning, Ruins is winning and any personal brand and many other businesses.
1:31:51
And so, that doesn't even get into the AI of it all.
1:31:55
That to me is tooling and infrastructure to be great at what I just said.
1:32:00
Um, but Jesus, there's a lot of money being wasted by the companies representing the eyeballs that are watching this show right now and that makes me sad. Yeah. Makes a lot of sense.
1:32:11
I I I can't stand wasted marketing spend.
1:32:16
>> [laughter] >> Yeah, blood makes my blood boil.
1:32:17
Well, thank you so much for taking the time to come chat with us.
1:32:22
>> We didn't even We barely got to talk about live commerce.
1:32:24
>> Yeah, there's a lot we can talk about.
1:32:26
We'll get the update next time.
1:32:27
Yeah, we you need everybody here Anybody selling to the consumer needs to understand that China's going to do a trillion in GMV, a trillion in GMV this year in stuff sold.
1:32:39
And and TikTok Shop and whatnot are doing real numbers in in the US and Meta's clearly going to be popping off any second with what they're going to do, which will lead YouTube to do what they're going to do.
1:32:53
>> Sorry, I know you got to leave, but give me your 30-second outlook on TikTok post kind of acquisition, change in ownership.
1:33:01
How's the platform changing and what's your outlook? There's I felt nothing.
1:33:06
I haven't done any real homework on any like corporate structure or what is going to be the vibe.
1:33:11
I know, but but will the new owner will the new owners be willing to like subsidize TikTok Shop is kind of what I'm getting at.
1:33:20
Um, they they don't need to.
1:33:21
It actually works on merit. Okay.
1:33:24
>> need to subsidize shitty Mhm. Uh, always a good time.
1:33:31
Thank you [clears throat] so much for coming on the show.
1:33:34
>> talk to you soon, Gary. Goodbye.
1:33:37
Uh, later in the show we'll be telling you about a local man who grew a 900-lb pumpkin in his [music] backyard and we'll tell you what it means for AI scaling laws.
1:33:46
But up next we have Humble Robotics, the founder and CEO is in the waiting room.
1:33:53
Let's bring in Ayal Cohen to the TBP and Ultra Dumb. How are you doing? >> What's going on? Great. How are you doing, guys? We're doing great.
1:34:00
We're having We're having a great day. >> having a show.
1:34:04
>> What's going on in the background?
1:34:06
>> Yeah, take us on a little tour.
1:34:06
What's going on What's going on there?
1:34:09
You can see the truck that we built, the vehicle that we built is a class eight electric autonomous vehicle for moving freight.
1:34:17
But I actually I want to hear about this 900-lb pumpkin.
1:34:18
When do I [laughter] ever hear about that?
1:34:20
That's actually It applies to your business. Yeah, yeah, yeah.
1:34:23
In order to >> your demo was probably the equivalent of a 45-lb pumpkin.
1:34:28
Maybe that truck in the back is a 300-lb pumpkin, but this is all in service of getting to the 900-lb pumpkin, the elusive 900-lb pumpkin.
1:34:36
And you raised some money to help you build that vision. How much did you raise? Who's from? Tell me about the round. Yes.
1:34:47
Okay, so we raised $24 million and >> [laughter] >> Continue.
1:34:59
>> That's so sad It's It's so satisfying, really.
1:35:02
Uh, we raised 24 million.
1:35:02
The lead investor was [clears throat] Eclipse.
1:35:06
Uh, we also had We also had VIP in there as well as some other other friends.
1:35:08
So, yeah, it was a great round for us.
1:35:10
$24 million It sounds like a really solid the highest signal, probably the highest signal if you're building in robotics.
1:35:20
Uh, at the same time you're building something big in robotics.
1:35:21
$24 million That's great for a seed, but how how much does it cost to build one of these?
1:35:27
What What are the comps like?
1:35:27
What What What will the next couple of years like be like of actually getting these on the road?
1:35:36
Yeah, so $24 million is a start, right?
1:35:39
It's uh, we are we're doing hardware, we're doing robotics, we're doing autonomy [clears throat] software that that does cost money, but it costs way less than it used to.
1:35:46
I think, you know, you look at some of the the the players in the space and, you know, Waymo took a very long road, spent a lot of capital, but we're standing on the shoulders of giants now, right?
1:35:55
A lot of work has been done in this space.
1:35:56
I've been working in this space for 10, 11 years now on autonomous freight and we We get We get the benefit I love it.
1:36:03
We get the benefit of of of a lot of work that's been done in many and over the years and so it's just far cheaper than it used to to sort of think about a great new idea and scale it and scale it in production.
1:36:16
>> Okay, talk about the key tradeoffs. No cab, no driver. Are you pro lidar?
1:36:22
Are you pro teleoperation?
1:36:26
Like what Are you going to do a crawl, walk, run thing?
1:36:28
Is it a straight shot to full self-driving? What's the thesis? Yeah, great.
1:36:33
So, we, you know, we're not dogmatic about technology here at all.
1:36:38
It's just what's the best technology that we can use at any moment.
1:36:39
Most of my career has been spent working on lidar technology, but actually where we see vision-based tech on cameras is incredible right now.
1:36:47
I think especially in the last year or two.
1:36:49
This is a This I I always joke with our head of autonomy.
1:36:53
I have seven startups under my belt now.
1:36:55
This is the second one I founded.
1:36:56
And so we've been kind of doing a lot over many years.
1:36:58
It's the first time the company's really been vision camera focused in autonomy for me.
1:37:01
And what I'm seeing on that side is incredible.
1:37:05
It's like it just It's It's honestly kind of magic. Yeah.
1:37:08
>> Um, but it we still take the same approach that you see in autonomy, right?
1:37:12
It is a uh, it is a What did you say?
1:37:14
Crawl, walk, crawl, walk, run? >> Yeah.
1:37:16
Um, we we take that approach, too, right?
1:37:19
First you test in private roads and tracks.
1:37:21
You You get You validate the hardware and the software together.
1:37:23
And then you from there you you start pilots.
1:37:28
You supervise those pilots.
1:37:28
But we will take any technology that is beneficial for the project, for the program and we'll apply it.
1:37:34
That's the That's the idea.
1:37:36
Uh, average 18-wheeler costs something like $120,000, maybe 275 at the high end.
1:37:48
Do you need to be at that price point? Can you go higher?
1:37:50
Do you have flexibility there?
1:37:51
And then the actual autonomy package, I feel like you could literally strap an iPhone to every possible vantage point and you don't need to do that cuz you can just buy the actual lenses and cameras.
1:38:02
So, the the cost of the vision stack has to be pretty low, but is Are there GPUs on board?
1:38:10
Are you doing on-device inference?
1:38:11
Like What's the economic balance?
1:38:13
How is this How should a customer even think about this in a different mindset?
1:38:19
Yeah, so so what What do you get from removing the cab, right?
1:38:20
What's the benefit of having a cabless vehicle other than it's it's cool.
1:38:23
I think when we were conceiving the project, the question was, how do we move freight?
1:38:28
Given where technology is, how do we move freight at the lowest possible cost, right?
1:38:32
And the lowest possible cost to me was, okay, we we think about making it What is autonomous freight?
1:38:38
So we could save about a dollar per mile there.
1:38:39
We We make it electric, right?
1:38:41
So that that lowers the maintenance cost and now especially with like some of the volatile fuel issues, you know, we get benefit there, right?
1:38:48
Um, and you know, the cab itself is is cost to the equipment that isn't necessary in autonomous world.
1:38:53
And so by removing the cab, you make the whole vehicle wider and you make the vehicle less expensive.
1:38:59
And so for me the target is we want to have the equipment be comparable in price to what you see a tractor and a trailer today because this is effectively combining a tractor and trailer together, right?
1:39:09
It's It's It's both the the semi truck part and the trailer part in combination, right?
1:39:13
And and this for the 40-ft version of it that we're looking at.
1:39:17
Um so, we want the equipment cost to be comparable, and then the cost per mile is just dramatically lower. That's the idea. Yeah.
1:39:23
Uh how do you think about supporting infrastructure?
1:39:25
I mean, there was a massive build-out of charging infrastructure as Tesla ramped. Is that beneficial? Is that enough?
1:39:32
Is there a lot more that needs to be done?
1:39:35
I imagine even if I just have a warehouse, uh I might need to check if my warehouse is compatible with a cabless delivery, uh and doesn't have, you know, the wrong configuration to be able to puzzle piece in the the the container. Yeah, that's right.
1:39:51
And actually, for the reason that we launched, I mean, the company is very young.
1:39:54
We're we're uh we started out 8 months ago, right?
1:39:55
And we built this vehicle very quickly.
1:39:57
Um so, yeah, we have a we have an absolutely killer team.
1:40:00
They're they're the most fantastic [clears throat] people I've ever worked with.
1:40:03
And uh we we try to move very quickly, and we launched, you know, pretty early in the journey.
1:40:07
We were public about what we're doing, and the reason is that you want to build with your customers.
1:40:11
It's really important in freight to operate within the constraints of the logistics space and understand what people need and and how they operate.
1:40:18
So, we we're being public about what we're doing because it's our message to our our our customers that we work with them on on that front.
1:40:26
And that goes from everything from how does this vehicle load, go back up into a docking area.
1:40:31
It's one of the advantages of our vehicle, by the way.
1:40:32
It's like we can put cameras behind it.
1:40:33
We can back up into docks, right?
1:40:35
And so, how do we how do we uh organize that kind of effort with them?
1:40:39
How do we think about charging?
1:40:40
How do we think about, you know, plugging into their uh their software, right?
1:40:44
Which, you know, sometimes every shipper has a different uh software stack that we have to work with.
1:40:49
So, we we're starting those conversations really early.
1:40:51
Um and as a company, we just move very fast.
1:40:53
What's it going to take to get you on X? On X?
1:40:58
I actually I actually signed up for an X account right before the launch. I'm on it.
1:41:03
I just I just need to figure out how to use it.
1:41:06
But but [laughter] I'm there. I'm there.
1:41:07
I'm I'm Wayne, we'll tell Nikita one more user. Let's make it happen. One more user.
1:41:14
One more user for Nikita, yeah.
1:41:15
W- yeah, w- w- where is the company based?
1:41:17
Where What does actually scaling the company look like?
1:41:20
Uh are you going to make Detroit great again?
1:41:25
Can we do something over there? Motor City? What are we thinking?
1:41:28
>> We're in San Francisco.
1:41:28
We're in downtown San Francisco.
1:41:30
And actually, when you walk into this warehouse, you're greeted by this 40-ft vehicle, which is like uh before we were public, you know, people would walk into our warehouse, and their eyes would just get really big going, like, "What is happening in this space right now?"
1:41:40
Um but uh you know, we're we're in San Francisco.
1:41:44
That's that's where I live. That's where I'm based.
1:41:46
That's where I've been working on tech for the last 20 years.
1:41:49
>> makes sense as a Silicon Valley and and prototyping hub.
1:41:51
You have a you have a warehouse, but you don't have a gigafactory yet, and that might be something >> Correct. Got it.
1:41:58
>> Yeah, and that can and that can happen anywhere in the US.
1:41:59
But we're designing in the US, we're building in the US, we're part of the reindustrialization movement of the US.
1:42:04
So, that's that's the plan.
1:42:06
What have you learned about the reindustrialization efforts that are uh talked about a lot, specific to the supply chain of uh autonomy components, electric vehicle components?
1:42:17
I'm sure you're grappling with all of this, but uh what has surprised you to the upside?
1:42:21
What has surprised you to the downside?
1:42:23
Give me some white pills and black pills.
1:42:26
So, I started I started my career working in electrification, electric vehicles.
1:42:30
And actually, a lot of technology was here in the Bay.
1:42:31
A lot of it to developing battery packs, motors, um and we watched over the last 20 years as that shifted out of not only just the Bay, but out of the US entirely, right? Yeah.
1:42:42
And I I I now you see the sort of the rush to get it back, and I think I think there is it takes time, but there are a lot of smart people who've been working in this space for a long time, and there's a lot of uh excitement and capital pouring into this.
1:42:54
Um you know, our backers at Eclipse are just the most phenomenal uh people you can be working with, and they get this, and they they understand it.
1:43:02
And you'll just see a lot more investments in this space in general um as we grow.
1:43:05
And yeah, the I think the supply chain's coming back here.
1:43:09
It's just It's It takes time like like everything.
1:43:11
It's just going to come back in automated automated factories this time around. Yeah.
1:43:14
Uh we are at time, but you need to read this deep dive in the New Yorker about these insurance scams that are happening in New Orleans around uh 18-wheelers, where people are crashing Have you read this?
1:43:28
Are you familiar with this story?
1:43:29
I I'm a little bit familiar with the story.
1:43:31
>> It's that's actually how they put together the money for the first round >> [laughter] >> No, no, no, no, no, no.
1:43:39
Uh but I mean, it is something that it that that would be at least easier to fight back against in terms of fraud if there were cameras all the way around the vehicle.
1:43:47
So, a little bit of a knock-on effect to the positive. Uh well, good luck. >> that we did. Thank you.
1:43:52
And thank you so much for Just based on this conversation, I'm extremely confident that this company will be wildly successful.
1:44:00
And I'm glad you're doing this. Yeah. So.
1:44:02
Thank you so much for coming on the >> you back on soon. We'll talk to you soon. We'll see you soon. Bye.
1:44:07
After mystic completely There we go. There we go.
1:44:14
>> [laughter] >> Uh after our next guest, we will be taking you into a story about Coachella.
1:44:18
It ran past curfew, and it got fined.
1:44:22
You will learn why music festivals may be the best way to understand data center permitting risk after our next guest.
1:44:29
That's a narrative violation.
1:44:29
We have Yolande Yan from Comfy in the waiting room with an iconic entrance. Let's take a look.
1:44:40
What are you holding here?
1:44:42
Uh please introduce yourself and the company. What are we looking at? LET'S GO.
1:44:49
>> [laughter] >> PLEASE WELCOME TO THE SHOW.
1:44:57
>> I'M surprised no one's ever pulled off an entrance like this. >> No, no. This is exquisite.
1:45:00
Uh please introduce yourself.
1:45:03
Tell us a little bit about what's going on. My name's Yolande.
1:45:06
I'm the co-founder and CEO of ComfyUI. Um I I apologize.
1:45:10
Uh I've been instructed that I can be anything but boring for this show. So, here I am. That's true.
1:45:18
You know, you you studied. You studied. Yeah. I did. I did.
1:45:21
What what uh tell us your entire life story from inception.
1:45:27
[laughter] No, what uh be be Since this is your >> are too many points for you to start over here.
1:45:31
Uh let me let me remove the distraction for you for now.
1:45:34
>> What is the distraction? Give us the backstory.
1:45:35
Like, why that particular creature?
1:45:37
The distraction is a character created by my co-founder.
1:45:40
It's actually the origin of this tool.
1:45:42
It If weren't for this character, we wouldn't be raising and becoming a half-billion-dollar company today.
1:45:49
So, just shout-out to the fennec character. Yeah.
1:45:53
Uh so, for those who don't know ComfyUI, node-based workflow for uh visual design, video production, uh you know, DaVinci Resolve-level performance, but for the modern era. Is that roughly correct?
1:46:06
How how are you thinking about introducing the company? Yeah, yeah.
1:46:10
Um Comfy is uh a node-based system that aim to uh give the highest leverage of control and quality for content creation.
1:46:19
Uh I think uh if you guys uh think of a, you know, let's say Midjourney or text-prompt-based uh content creation using AI, uh it's the polar opposite.
1:46:29
It gives you every bit of control and possibility um uh to adjust the model and uh control the camera angle, control the posture.
1:46:39
Uh and that's exactly why I Comfy ended up being adopted by these uh top studios around the world.
1:46:44
Uh the recent Coca-Cola ad or Super Bowl ads were all made using Comfy. Yeah.
1:46:48
And then also inject a level of uh deterministic and programmatic variation into the generative AI workflows, so that if you want to create multiple assets, and you want to swap out a bear for a cat for a dog, you can do that in a way that doesn't just require you sitting there prompting, waiting 5 minutes, prompt again, 5 minutes.
1:47:09
>> You know, actually parallelizing Yes, that makes sense.
1:47:11
Uh so, yeah, if you're working with big companies, like, are they just forking the repo, downloading the open-source project?
1:47:18
Are they actually calling you?
1:47:21
Are you doing implementation?
1:47:21
And and how do you how are you making money from all of this so far?
1:47:27
Yeah, yeah, great question.
1:47:27
Uh it started first as a open-source project.
1:47:31
Actually, it's a personal project to begin with. Yeah.
1:47:33
Um and then originally, a lot of the companies actually just ended up using it running on their own hardware uh most of the time locally.
1:47:41
Uh we introduced Comfy Cloud as a product uh about 5 months ago. Oh, cool.
1:47:48
And the main uh differentiation in that world is that you can actually tap into it's incredibly difficult to stitch everything together to provide this infrastructure level of support, uh especially for like, you know, uh professional creative companies or uh studios.
1:48:09
So, yeah, that's kind of like, you know, how we monetize off of it.
1:48:11
How big of a deal is SeaDance 2. 0?
1:48:13
The videos that I saw were incredible.
1:48:15
It felt a little bit inaccessible. Is it diffusing rapidly? Yeah, yeah.
1:48:22
The entire visual AI ecosystem is is evolving very rapidly.
1:48:28
These foundation models are making amazing progress, and you can access all of these models on our platform as well.
1:48:35
We are generally agnostic in terms of whether it's open or closed-source model.
1:48:39
But just to comment on the progress over here, we're super excited to see, like, you know, where the trend goes towards to when these SeaDance model gets launched onto Comfy platform.
1:48:50
You see people kind of building on top of creating even better workflow uh using these models.
1:48:55
And I can't wait for, you know, one day we'll just have avatar being created in someone's uh you know, bedroom and backyard. >> Okay, when? Over under 2028 2028.
1:49:03
Give us your Hollywood predictions.
1:49:06
When can An hour a 90-minute movie because I've seen some incredible short films, some incredible vibe reels and 30-second I've seen yeah, maybe 2 minutes, 3 minutes.
1:49:19
Everybody's now seen like there's probably longer stuff out there.
1:49:22
I haven't gotten sucked into anything.
1:49:22
I did watch all of Harry Potter Balenciaga. That was great.
1:49:27
>> [laughter] >> You know, but like I'm waiting for something that's Harry Potter Balenciaga level entertainment like hold my attention to the end, but 10 minutes, then 20 minutes and then 90 minutes.
1:49:35
And when the 90-minute thing happens, I think a lot of people are going to be like, "Wow." Yeah.
1:49:42
This is actually a part of an inside that most people don't really understand right now.
1:49:46
It's one on the quality side of the area.
1:49:52
People don't want to create long-form content because by the time when you finish a feature film length of a content, the model has shifted so much that you're you're running into this James Cameron problem of flight, "Oh I have to go back and then, you know, like rerun these using different models."
1:50:10
So a lot of times people focus on short clips in terms of the content.
1:50:11
And then the other portion is actually it's already being adopted in a lot of these creative studios and agencies using Comfy.
1:50:21
What it doesn't do is it doesn't become production.
1:50:25
It just entered the previous portion.
1:50:29
Enable people to rapidly iterate and then create these content right away that you might have someone acting in a pure green screen and and then the output of it in 5 minutes you see the entire 3D CG rendering using AI on the on the system in Comfy.
1:50:44
And in that world it's already influencing the direction of how they act.
1:50:48
It just doesn't necessarily get to the quality where it completely could become a film production level of content.
1:50:57
Is there more to be learned from the Cognition model or the Cursor model in terms of training your own models versus being at the application layer?
1:51:10
Both companies have been wildly successful, huge, but very different paths.
1:51:18
Yeah, I believe the visual ecosystem is quite different.
1:51:21
The main differentiation is there's a huge amount of taste.
1:51:25
Even if someone can prompt C Dance 30.
1:51:28
0 to generate a feature film tomorrow and it gets to the level of quality for the real creatives or for the people who want the taste and control to be in their own hand, it's still going to be a very iterative process.
1:51:44
It's just going to make their life a lot easier and that's what Comfy enables you to do.
1:51:50
I think those are the kind of differentiation where in the coding world you might not care in terms of, you know, is this piece of code actually good enough?
1:51:57
But in the visual world you absolutely care the camera angle, the facial feature, the the control layer and that's in my opinion what differentiates the, you know, AI slops from the Comfy ecosystem of creation.
1:52:15
What's the easiest AI feature to pitch to a Hollywood AI skeptic?
1:52:23
The easiest way I would say from our perspective, this is might not be for everyone, is the fact that that we have this creative in the loop a human in the loop centric belief and mechanism and it's actually true.
1:52:41
In a lot of these case scenario when people are using Comfy as a tool, it is actually empowering the creatives to to to do their work, to skip all of these boring stuff of colorization of you know, kind of upscaling, downscaling manually in the traditional process. It enables you.
1:52:59
So those are the world where we're not actually taking jobs, we're creating jobs.
1:53:03
If anything you go search on, you know, any job site the today there's actually a huge amount of people hiring for Comfy UI artists and specialists.
1:53:14
Yeah, I I think like the the Mount Everest is like, "Oh, we'll one shot the movie, replace the actors."
1:53:19
The easier stuff is what if your green screen was a little bit cleaner, you know, what what if your color grade was on your dailies as well.
1:53:29
There's a whole bunch of interesting places where you can play I've said this before and and uh at least some people were trying were calling me an idiot online, but I've had this idea that I think AI could actually help Hollywood.
1:53:42
actually help Hollywood. We're in Hollywood, there's a bunch of empty studios around, there's a bunch of people here that have been working in entertainment that haven't had great job prospects over the last few years, especially if they weren't willing to travel overseas and it just feels like
1:53:55
we're we're going to enter into an era where 10 really smart people could come into one room and if they work really hard and leverage AI properly, they can make it they'll be able to make an incredible, you know, short film, film, make beautiful advertisements, whatever they want to do. So I think we will
1:54:10
So I think we will enter into a golden age of human human powered AI powered humans doing incredible creative work.
1:54:20
You mentioned that you're currently valued at half a billion dollars. How much did you raise?
1:54:25
Tell us about the funding news.
1:54:28
Yeah, we raised $30 million from Oh man, I've been looking forward to this.
1:54:35
Um yeah, we raised $30 million.
1:54:36
The round was led by Craft Ventures.
1:54:38
Huge fan of folks over there.
1:54:41
They've been tracking us for a while.
1:54:44
Yeah, been amazing working with them so far. Super excited.
1:54:47
We're here to destroy our enemies and make open source creative tooling win.
1:54:53
>> [laughter] >> I love it, dude.
1:54:54
Imagine being Imagine being your enemy right now logging on to Oh, I think we talked to his enemy earlier this week.
1:55:01
I'm not going to say who it was, but I think we know who he's coming for and I'm rooting for him.
1:55:06
Well, imagine logging on to x com and seeing Mr.
1:55:09
Yan and just being like, "Oh, it's over for me." It's over for me.
1:55:14
>> [laughter] >> Real real bottom >> idea because in our mind we don't really have enemies.
1:55:18
The only enemy is ourselves.
1:55:19
>> I'm not talking about I'm not talking about startup competitors. Oh, I see.
1:55:25
>> [laughter] >> Never heard of that word. But congratulations.
1:55:28
Thank you for everything you do. Incredibly cool tool.
1:55:32
If you haven't already checked it out, go go download Comfy UI. Make some cool stuff. It's a lot of fun.
1:55:38
And have a great rest of your day. Goodbye. Great hanging. See you.
1:55:44
Later in the show, did you hear about the cow that got loose on the highway and backed up traffic for miles? >> did?
1:55:50
Well, we're going to tell everyone what the AI industry can learn from that story about supply chain bottlenecks.
1:55:57
But up next we have Ben Horowitz from Dorm Room Fund.
1:56:00
He's an investment partner and the creator of Sincerely misspelled.
1:56:05
You'll have to figure out how to spell it yourself if you want to go check it out, but we'll let Ben introduce himself now. How are you doing?
1:56:13
Hey guys, thanks for having me on. Love the show.
1:56:16
Also an MBA at [clears throat] HBS, so Oh, yes.
1:56:18
People are taking a victory lap on Soon to be master of business.
1:56:22
>> it was impossible for a an HBS grad to start a business, but you're proving everybody wrong. Thank you.
1:56:29
Yeah, Twitter flamed me a little bit for it, but I'm still happy I'm here.
1:56:32
Wait, wait, so what why were people upset? I don't I don't know.
1:56:35
Oh, it's like a non-technical thing probably, right?
1:56:38
Yeah, I think Gary talked about it too a little bit. Yeah. Yeah.
1:56:41
Just the the idea like I mean HBS grads have started so many amazing companies, but it's pretty >> Oh, I thought you were talking about the product.
1:56:49
But but but but the HBS thing is typically not like the like go and build a software product in a weekend or in a week like very quickly.
1:56:55
Like that's been more like, "Oh, you're a CS grad and you're a dropout and then you go do YC."
1:57:00
Like that's been the more established path.
1:57:01
But you're bucking the trend. Tell us what you built.
1:57:05
Yeah, so I built Sincerely.
1:57:05
It's spelled with two E's, so s i n c e e r l y.
1:57:07
And it's really like the anti-Grammarly.
1:57:12
So I am naturally a terrible typist.
1:57:14
I I don't know if I can cuss, but I mess up my emails all the time and I found that people really reply to them.
1:57:23
I don't think it's just because of the typos, but it's definitely a factor.
1:57:28
And I was so sick of AI slop in my own inbox.
1:57:31
People would email me, it all looks the exact same.
1:57:33
And that coupled with the news about how other people have been emailing across social strata inspired me to basically create the anti-Grammarly, something that really messes up emails.
1:57:46
>> [laughter] >> Are you you're talking about like CEOs that have terrible grammar cuz they're just typing quickly and it doesn't really matter?
1:57:51
>> the famous story about Ron Conway types in all caps.
1:57:53
There's a whole bunch of these examples.
1:57:55
Typing in all caps is All caps is elite because it just sounds like someone's yelling at you.
1:57:59
It's kind of the anti-Gen Z in a lot of ways, the all caps.
1:58:07
But I had I I had this I had this this experience maybe a year ago where where someone sent me a very lengthy you know, multi-paragraph deep dive on some topic and I could tell that it was AI generated and I said, "You know, you should just send me the prompt because I can also do the instantiation.
1:58:25
Like I can also expand bullet points into paragraphs in my head."
1:58:29
And so just send me the bullet points.
1:58:31
And there was that also that meme of like Turn this turn these bullet points into paragraphs and then the other person on the other end saying, "Turn the paragraphs into bullet points."
1:58:38
Are are people using this specifically to write emails or is there an email summarization feature coming?
1:58:43
Where do you see this going, I guess?
1:58:45
I think what's kind of crazy is people are copy-pasting first the prompting, then they're copy-pasting their prompt into email.
1:58:53
And then they're using Sincerely to make their email not sound like AI.
1:58:59
And that's a crazy loop, right?
1:58:59
Like it's humans using AI to make AI more human.
1:59:04
And that's why >> And that's why Intel is up 20% >> [laughter] >> for this specific use case.
1:59:09
No, there are more useful There are more important use cases, but uh I I I We were talking about this Was this Was this a a fun stunt or Yeah, somebody called it a drop, and I think it's a business. What do you think?
1:59:22
I think it started as social commentary.
1:59:25
This is like it it's satire and playful, and I didn't want to pay for everyone's token.
1:59:29
But like I do make Like I love making products that make people think twice about technology.
1:59:33
And in this case, it's also a little bit like the pushback on how we're using technology today.
1:59:41
So >> I you know, there's a $4.
1:59:42
99 a month model that if you want to not bring your own key, you can pay me.
1:59:47
Um I think it's probably double-digit people who are paying and not using their own key, but it could be a business, for sure.
1:59:53
Uh we were talking to George from CrowdStrike earlier.
1:59:56
Are you ramping up security?
1:59:58
What are you doing to make sure this is enterprise-grade ASAP?
2:00:01
Because when I download a vibe-coded viral stunt, I want it rock solid.
2:00:08
Uh I learned a lot in this in this process, as you might have imagined.
2:00:11
I'm a huge fan of CrowdStrike, too.
2:00:12
Um we have pushed a few security fixes um and just made sure that people know what they're getting themselves into when they download this.
2:00:21
But ultimately, like this is a it's satire meets something real.
2:00:26
Um so I hope that that people get it. Yeah. Yeah.
2:00:31
Yeah, that that's the nature of like doing fun things on the bleeding edge of the internet.
2:00:34
We all went through this with the open claw and understanding, okay, there's some real tradeoffs here.
2:00:38
You probably got to be at least a prosumer if you're going to dive in, but it sounds like you're handling it well.
2:00:43
>> What is sentiment like in the current H in your current HBS class? How are people thinking?
2:00:48
Are are are like with the acceleration in AI, are there people thinking about dropping out?
2:00:52
Like or or are they like I'm actually glad I'm in school right now cuz it seems kind of gnarly out there. Okay. Yes.
2:01:02
Um I have friends who who have dropped out for for YC um and friends who have stayed for the exact same reason. Yeah.
2:01:10
It's kind of, you know, swim or or sink.
2:01:13
I think that people are building They're not building funny things, I would say.
2:01:17
They're They're really trying to build things in the HBS sort of business-first way.
2:01:22
And my girlfriend's at GSB, so maybe there's a little bit of a different comparison that you could ask her about, but >> Uniting the great houses.
2:01:28
Do you think there will be a sway I mean, you go back to HBS in like the '80s, and you imagine that uh it was churning out like oil and gas executives, probably.
2:01:38
And I'm wondering if you think there'll be a swing back like we saw Josh Kushner announce Thrive Eternal.
2:01:43
He's taking a stake in the Giants.
2:01:45
And there's a whole different world where you take the HBS learnings and playbooks, and you go apply them to things that are extremely AI-resistant, but maybe like they weren't They haven't been trendy over the past decade, but maybe they're going to come back in style in a big way if you're, you know, yeah.
2:02:03
Yeah, I I went to HBS, and now I'm like, you know, VP at GE Vernova.
2:02:05
That's probably a pretty good gig. Yeah.
2:02:07
I mean, the friends who I'm thinking about who actually dropped out to go do YC, you're going to laugh, are focused on HVACs.
2:02:16
Oh, they're >> [laughter] >> putting AI in the back of HVACs. It's not a roll-up. It's not a roll-up. It's not a roll-up. It's not a roll-up.
2:02:25
They They They The true HBS move.
2:02:25
Why has no one identified the opportunity in HVAC? HVAC is important.
2:02:30
Have you ever not had air conditioning?
2:02:32
One hot day in this studio, and I'm I demand HVAC. It is universal.
2:02:39
>> [laughter] >> It It's sort of that's another loop that's tricky, though, right?
2:02:41
Like are we making the world warmer? Are we cooling it off?
2:02:44
Are we putting AI in the back of HVAC?
2:02:47
>> an AI play at the end of the day. Interesting. Interesting.
2:02:49
What were you doing before HBS?
2:02:53
Um I started a company with my friend Reed that was a um sort of like a philanthropic robo-advisor like Wealthfront or Betterment. Yeah, yeah.
2:03:01
Um and we sold that to Charity Navigator, and I worked there.
2:03:05
Um and uh and now Yeah, hopefully I'm a free agent in like 3 weeks.
2:03:06
So heading to SF and and fulfilling my manifest destiny, hopefully.
2:03:13
>> in 3 weeks, is that HBS graduation?
2:03:16
>> your earnout or or HBS? Yeah, finishing HBS.
2:03:19
The The proverbial [laughter] debt earnout.
2:03:20
I don't know if you call it that. Yeah, yeah, yeah. Awesome.
2:03:24
All right, well, uh it was really great to meet you.
2:03:26
And uh please let us know when you figure out where you're working at.
2:03:30
>> And let us know when the next drop's happening.
2:03:31
I feel like you got more of these in the can.
2:03:33
I can tell there's something really funny coming out.
2:03:36
>> [clears throat] >> And by we, I mean you.
2:03:40
>> Yeah, let's talk about it. >> Yeah. Have a good one. We'll see you soon. Goodbye.
2:03:45
>> Uh there is a ton more news.
2:03:45
What should we go through?
2:03:48
Spore says, "What's the charge?
2:03:50
Front running an overseas coup d'état, a succulent Venezuelan coup d'état."
2:03:54
But this was a crazy story.
2:03:56
Brandon Garella on our team was uh obsessed with it.
2:03:58
A US special forces soldier involved in the capture of Venezuelan President Nicolas Maduro was arrested for allegedly betting on that operation, netting him $400,000 in profits.
2:04:09
This is when the betting on yourself meme goes wrong, right?
2:04:12
You You You You should always be betting on yourself, but not literally if it's against the law.
2:04:19
Uh if you are involved in a government capacity, you should probably not be uh gambling on the outcome of your of your government work.
2:04:29
Uh shame on you, but uh still an interesting story.
2:04:32
>> was like he was betting on himself, and then he he he like referenced some baseball player that isn't in the Hall of Fame because he was betting on himself, but Trump was seemingly implying that that that wasn't so bad, but anyways.
2:04:47
People are really really having fun with the the new image gen model.
2:04:49
I don't even know if we should post this up cuz it's so rude, but uh this guy's effectively playing Minecraft through ChatGPT because he has it generate him an image of Minecraft, which is >> uh of course he's doing the island in Little St.
2:05:04
James, the very controversial one.
2:05:06
And then he says, "Okay, >> he says, "Okay, walk closer."
2:05:07
And then just generates a new scene.
2:05:09
I'm going to pull it up, though.
2:05:11
I'm sure I'm sure there's some kids out there that are that have figured out how to uh how to play Minecraft in in ChatGPT, but this is very funny.
2:05:19
I found this post when it had 40 likes this morning. Sniped. >> Invested early.
2:05:27
Uh Cohere is merging with uh a German AI lab called Aleph Alpha.
2:05:35
I'm the biggest fan of Cohere. I love Aidan Gomez.
2:05:37
Transformer paper alum, Death Grips enjoyer, what's not to like about the legend Aidan Gomez?
2:05:43
We got to get him on the show.
2:05:46
But this is a congratulations moment for Cohere and Aleph Alpha. Uh GPT 5. 5. Yes.
2:05:56
Uh Kits is saying it might be AGI because if you ask it, "Bro, the car wash is 5 minutes away, should I walk to it or go by car?"
2:06:03
It says, "Car, bro, it's a car wash."
2:06:05
Like the plot Like the plot makes sense.
2:06:08
>> [laughter] >> Wait, what? Oh, that's funny.
2:06:12
>> just immediately clocks it.
2:06:13
>> Oh, I like that it's I've seen this exact test done in normal language, like with a proper prompt, not the casual bro slang.
2:06:19
Uh And And it's it's it it actually is more It feels more like AGI if it is able to pick up on the lingo and mirror that back.
2:06:28
"Car, bro, it's a car wash." That's very funny.
2:06:32
That feels very uh remarkable.
2:06:32
It also got the the R's in strawberry correct, right?
2:06:38
And uh "How many strawberries are in the letter R?" Zero.
2:06:40
The letter R is not known for its berry storage. These are good answers.
2:06:44
Uh the the uh the the being a helpful assistant, but simultaneously rejecting nonsense has particularly been difficult for LLMs, so good progress here.
2:06:53
We'll figure out more about uh what went into this and what uh the next The next generation of AI impacts are from this. Uh Tyler Yeah.
2:07:06
Haj says uh is found a post from 5 and 1/2 years ago.
2:07:11
Elon says, "The rate of improvement from the original GPT to GPT-3 is impressive.
2:07:15
If this rate of improvement continues, GPT-5 or 6 could be indistinguishable from the smartest humans.
2:07:20
Just my opinion, not an endorsement.
2:07:22
I left OpenAI 2 to 3 years ago.
2:07:23
I'm a neu- neutral outsider at this point." Greg says, "Thank you."
2:07:28
[clears throat] A lot A lot has changed, but uh he was accurate in his prediction.
2:07:33
Funniest outcome is the most likely.
2:07:35
And then the last The last thing I want to >> bros and do a buddy cop film together.
2:07:42
The last thing uh there is a new app from X. It's called X Chat. X Chat.
2:07:45
And I'm excited to try this out because the current Yeah, the the DMs on X have been pretty brutal. Yeah. Right?
2:07:54
Uh I haven't had that much of a problem.
2:07:58
I Do you have this weird this weird bug where when I click the chat button on desktop, it sort of loads, and then it resorts after it loads.
2:08:07
Um and And sometimes if I haven't been in it in a long time, it needs to reshuffle several several times, and so that can be a little jarring.
2:08:15
Um but overall, it seems like they made the migration to encryption.
2:08:19
Uh I haven't I don't know. I seem to get messages. It seems to work fine.
2:08:23
It's cool that there's a new uh a new app.
2:08:25
I probably need to be better about answering DMs.
2:08:28
I I have a lot of them that are unread, so um having a dedicated app for that, that sounds cool.
2:08:33
People were taking shots because the everything app is supposed to be everything in one place instead of three apps to get everything in the everything app. It's sort of silly. Who cares? Uh more apps the better. I like apps. So go download it. Go check it out.
2:08:45
And go uh go like Nikita's post because uh he's been on a generational run. Also, GPT 5.
2:08:52
5 is available in the API now.
2:08:52
That's breaking news, I guess, this Greg.
2:08:54
So anyway, uh we will see you on Monday. Have a great weekend. Enjoy the weekend.
2:08:59
Leave us five stars on Apple Podcast and Spotify.
2:09:03
Sign up for our newsletter at tvp.
2:09:05
com and we'll see you tomorrow. Flashbang out.
2:09:07
Have an incredible weekend.