0:02
I see a large IPO on the horizon.
Search this video
0:09
You're surrounded by journal assault your position. Overnight success.
0:28
The PlayStation 3000 double right.
0:53
This misinformation clearing order. >> Let's just run.
1:09
>> Surrounded by general. Hold your position. Come on. Get up. King. >> Trust the la.
1:29
>> We are founder knowledge. >> La.
1:43
I see multiple journalists on the horizon. Stand by. >> UAV online. Blaze. Double blaze. Triple blaze. Double kill.
2:17
My color is w team deathmatch. We are experts. Triple blades. That's just wrong. Right. Clearing order inbound.
3:21
We are surrounded by journalists. Hold your position. >> Strike one. >> Strike two.
3:39
Activate golden retriever mode.
3:58
>> Market clearing order inbound. >> 5.
4:19
I see multiple journalists on the horizon. Stand by. You're watching TVN.
4:36
Today is Wednesday, September 2nd, 2026.
4:38
We are live from TVP Ultra Dome, the temple of technology, the fortress of finance, the capital of capital.
4:47
>> Let me tell you about ramp. com. Time is money. Save both.
4:49
Use corporate card, bill pay, accounting, and a whole lot more all in one place. We're back in the Ultra. >> Good to be back. Good trip to Las Vegas. Quick in-n-out.
4:58
Hung out with Crowdstrike. Uh had a great time.
5:00
rave reviews from my son who was very excited that we talked about ra getting getting on the track with George.
5:07
That was the highlight of the interview for him.
5:11
>> Yeah, he >> been the highlight of the interview for all of us.
5:13
>> Fixated on the helmet.
5:15
>> Yes, the helmet, the car, the uh the set design was huge among the young the young folks watching. That was good.
5:23
>> Uh anyway, um we have a lot of news to cover.
5:26
We barely covered the news yesterday.
5:28
We talked about Markiplier a little bit. I dug way deeper.
5:30
got more into that story.
5:32
But first, uh, let's talk about another AI safety kurfuffle that's hit the timeline.
5:37
Uh, yesterday, Amir over at the information reported that OpenAI is quietly quote quietly using loop transformers that don't show the model's thinking when scaled up, but which use the models more efficient.
5:52
This is also uh but but they make the model more efficient.
5:54
This is also referred to neural.
5:55
Tyler, you had a take on this, right?
5:59
Uh, I mean, >> get ready to learn nurly, buddy.
6:02
>> Get ready to learn nurles.
6:02
So, so neries for like context is like the basically it's like the raw vectors. It's not like >> Oh. Oh. Oh. It's not like clawedish.
6:10
It's not like where the the text degrades.
6:13
Like when you look at the the reasoning chains in the hugging face attack, it feels like they're they're speaking less and less English.
6:18
Like they're starting to speak like a a dialect of English that's a little bit messier.
6:24
This is not intelligible.
6:24
I I believe most people when they say neries they're referring to like actual >> okay just passing raw >> vectors and and what >> and you need to use some sort of like interpretability to understand. >> Yeah. Yeah.
6:36
The thing that I want to understand is like usually these models are trained so that they're they like they're changing weights into text at some point.
6:44
So they're pretty good at translation.
6:47
Can't we just build a translator that translates nurles into English? >> Yeah.
6:53
Yeah, but the the the whole point is like when you take a vector, turn them into like one single token, you're losing a lot of information that might be hidden in like the the long tail.
7:00
So if you're worried about safety, right, even if 80% of the you can kind of >> figure out what 80% of the the raw vector means, 20% might have some dangerous thing. >> Yeah.
7:11
>> Whatever that that's like the interpretability.
7:12
There might be like sarcasm hidden in the vectors doesn't make it through to the actual tokens and you realize that the AI was joking when it was saying, "I won't turn you into a paperclip." Wink wink.
7:23
You got to watch out for that.
7:26
So, uh, what else did the information say?
7:29
They said, "Being able to monitor a model's chain of thought can provide both quote an early warning system for various forms of misalignment, deception, manipulation, going after an goal, and insight into an AI's action after the fact.
7:43
So, some reporting quickly set off a broad wave of anxiety among the AI safety camp.
7:50
Their chief concerns being one not being able to monitor chain of thought t makes AI less safe and two by using neuroles and thus abandoning chain of thought openi starts a race to the bottom among frontier labs everyone's got to use it to stay ahead so everyone winds up adopting the dangerous technique where
8:07
others were also abandoned chain of thought for the benefit of efficiency thus making all frontier AI less safe that was the accusation but openai's research director Jacob Petki responded to all this he said I want to prevent a race to unmon unmoniability kicked off by confused reporting. He
8:23
He says the reporting is confused.
8:25
There's a little bit more nuance here.
8:26
Here's what here's what he said.
8:28
He said, "OpenAI has worked to preserve and utilize chain of thought monitoring since our very first reasoning models.
8:36
We deeply care about this technique as it can give us a view into how model alignment generalizes from its training distribution."
8:42
What is going on over there?
8:45
Chad is saying, "Gabe said, "Did Tyler go to Sport Clip? What is this cut?" >> We have an answer. >> Chill.
8:56
>> We have an answer for why.
8:57
>> Show them the Why don't you show them the answer, Tyler?
8:59
>> Oh, you want to show the answer?
9:00
>> Yeah, I want to show the answer.
9:01
>> The reason that Tyler tussle No, he doesn't even put it on. >> Go away for a second. Come back and show them. >> No, no, no.
9:08
You You don't want to You don't want to give too much of it away cuz we might do a real stunt with it.
9:12
But there were some prosthetics, some Hollywood magic in the studio. this morning.
9:17
Uh, it messed up my hair a little bit.
9:19
It messed up Tyler's hair a little bit.
9:20
Not ready for prime time, but we're playing around with it.
9:23
So, um, let's go back to the actual news.
9:27
Uh, Jacob says, "I do think it is a fragile and unfortunately trending in the negative direction for reasons not contingent on architecture changes that I will write about soon, but there are things we can do to strengthen it and it's a core goal of our current research program."
9:41
In other words, Jacob is saying that the information reporting is inaccurate, but that the state of chain of thought monitoring is not that great.
9:47
And in fact, it is getting worse.
9:47
And we were talking a lot about this yesterday at Valcon with Crowd Strike.
9:51
And how do you monitor the agent state that might emerge if a civilization emerges and starts doing weird things?
9:58
How are you monitoring every step in the chain? Very important.
10:02
We also have Nashora coming on the show from Palo Alto Network to talk about AI and security, of course.
10:07
>> Yeah, it see it seems very obvious.
10:07
said that that uh there's going to need to be a lot more done than just like an obsession with chain of thought, right?
10:14
Because if you have highly competent agents streaming at tens of thousands of tokens a second and they're copy and copy and pasting themselves infinite times, right? Sure.
10:24
Like are you really going to be able to just kind of read through the logs and be like, are they are they messing with us?
10:29
Are we good messing with us? Yeah.
10:31
Uh the interesting thing about the hugging face is like it keeps going back to uh the the secret message board.
10:38
And I'm and I'm just surprised that there's not just a public message board for agents that are working together.
10:45
Like when you imagine a country of geniuses in a data center, you would hope that the country of geniuses can collaborate on things and work together.
10:52
But I guess that's not exactly how things were designed.
10:54
I mean >> I mean in that case it was never supposed to be able to access any like anything on the on the on the web, right? >> Yeah.
11:02
But you would think that uh that collaboration between sub aents would actually be like a core way to get better results just like okay we're going to send off, you know, a thousand agents over here.
11:14
They're going to talk to each other while they work. And that's fine.
11:17
They don't need to set up this like phantom me message board, this hidden message board to communicate because we just actually gave them Slack, right? Something like that.
11:24
you'd think that that would actually improve uh just improve the quality of the work and then of course you could monitor it as well.
11:32
Um but instead you wind up with this they wanted to talk to each other so then they set up this fake message board.
11:37
Uh very very odd scenario instead of just giving them the the the approved way to do it.
11:41
Anyway, uh open uh former OpenAI staffer Joshua Akim said made an additional point here.
11:47
Coordinating everyone around a technique this brittle is as is about as bad a safety or strategy posture I could imagine.
11:53
It's not just quote it will break eventually.
11:58
It's this is a fundamentally unsound basis for safety.
12:01
Dean Ball also chimed in.
12:03
He said um we are now adjudicating technically complex and nuanced claims on the timeline with almost no ground truth information about what is actually happening.
12:13
communities form these thought-terminating taboss as Run says and then panic at everything that vaguely resembles them and the trust eroding reality of social media makes the timeline an especially difficult place to do this adjudication.
12:26
Uh it is frankly insane and crazymaking and grading for everyone involved.
12:31
It would be like if we argued about what every publicly traded company's financials were by posting hyperventilating hyperventilating on the timeline rather than relying on the institution of auditing and the audited financial statements that institution produces.
12:46
To sum it up, if you're in the AI safety camp, you're worried that OpenAI is abandoning a technique for making AI safety uh safer and that other frontier labs will now follow suit.
12:57
If you're skeptical of the AI safety camp, the information's reporting is inaccurate.
13:02
The AI safety camp is unnecessarily panicking and OpenAI is doing the best it can.
13:05
So, little bit of back and forth on the timeline.
13:07
Um, let me tell you about MongoDB.
13:09
What's the only thing faster than the AI market?
13:12
Your business on MongoDB. Don't just build AI.
13:13
Own the data platform that powers it.
13:15
And there are other uh reactions, but we went through most of those.
13:21
Um, let's go over to Markiplier.
13:26
>> Well, IA hit the timeline yesterday.
13:28
Yes, >> that said Neoclouds have limited cyber security.
13:30
Next time agents successfully go rogue, they'll try taking over a Neocloud to run more copies. This is bad.
13:36
Thus, Neocloud should greatly strengthen their cyber security.
13:38
And every company with strong cyber models should help with that. >> That's a good point.
13:44
>> So, >> it's a good point.
13:45
Click on Ilia's profile, then click on who he follows. Who does he follow?
13:53
He follows Open AI's former employer, SSI, and what's that one in the middle? The Dachan community. >> Let's go. >> My guy loves dogs. Look at this.
14:02
This is of the three accounts.
14:05
The the first company, the second company, nobody else.
14:11
>> Most important account. >> Scroll through. Scroll this. Scroll this timeline.
14:14
This might be one of the best accounts on X.
14:15
He is having the best experience on the timeline. There's no craziness.
14:22
He's just scrolling this looking at beautiful dog photos and uh important updates from OpenAI and SSI, the companies he's been involved with for decades.
14:31
Uh very very funny for a decade. Uh >> great.
14:35
We can head over to Markiplier, but first little countdown here.
14:37
Uh we up on the screen you'll see >> Oh, you put it up.
14:43
>> TVPN's road to Christmas.
14:43
The road to Christmas starts today. Starts today. >> 113 days. >> It's only 113 days. >> Yeah. >> Wow. Start shopping. 113 days. >> Okay.
14:56
>> Uh it's going to go by quick. >> It will.
14:58
>> Uh and I want to cherish >> cherish the road, right?
15:01
It's about it's about the journey.
15:03
It's not just about the destination. Sure.
15:05
>> Obviously, things won't get too Christmassy around here until things won't get too Christmy around here.
15:13
>> One one hat on the screen.
15:17
>> Won't get too Christmassy around here until December 1st.
15:19
But uh you'll probably see certain elements coming in prior to then starting with our countdown. So we'll leave this out. >> No, no, no.
15:29
We're going to hold fast. We got to hold the line.
15:31
No Christmas stuff until the day after Thanksgiving. >> Except the countdown.
15:36
>> Except and maybe some tinsel >> maybe.
15:40
>> Maybe a little fake snow. >> Yeah.
15:41
Maybe a little fake snow.
15:42
>> Maybe some candy canes.
15:43
>> Maybe maybe one candy cane. >> Yeah. A couple >> in October.
15:45
I mean, it's kind of a Halloween candy, so you can kind of blend it in.
15:48
Yeah, you know what a great Christmas present is a GoPro.
15:52
Specifically, the Mission One Pro, the hottest new product from GoPro.
15:57
Rave review from Markiplier.
15:57
Yes, he was paid to post it. Yes, he owned it.
16:02
>> Yes, he's the largest shareholder.
16:06
>> Shareholder, but but here's the hot thing.
16:08
I believe that he I believe that this started with Markiplier being actually bullish on GoPro.
16:12
And I'll take you through it.
16:14
So, I think there there's a lot of confusion about this.
16:17
We both of us were confused when we first talked about this.
16:18
Um but it's actually a very clear linear story and it makes a lot of sense if you go through it.
16:23
So um Mark Mark Fishbach, he goes by Markiplier online uh YouTube legend, also Hollywood uh blockbuster producer now or director uh filmmaker uh recently made a massively successful movie after an equally successful but much lengthier journey on YouTube.
16:39
Uh we talked about Iron Lung, his movie, uh as part of the breakout YouTube to Hollywood pipeline uh that happened over the summer.
16:49
Uh while filming Iron Lung, Mark became interested in GoPro's newest camera, the Mission One Pro.
16:55
So Mission One Pro, GoPro body, interchangeable lens mount.
17:00
So you can go take an old lens from a Leica or, you know, a Cook S1 if you want.
17:07
You can adapt anything on there and you can get all the image texture that comes from the glass into the sensor.
17:15
Yes, it's a smaller body, much cheaper, but you're getting the the the flavor of that lens.
17:19
Maybe someone on the production team can give us a little 101 on what matters more, the sensor or the lens. >> The lens. >> The lens.
17:26
Yeah, the lens is important, right guys?
17:29
Um and and and so GoPro sort of unlocked this ability and at incredible cost or incredibly low cost.
17:37
So, um, he put his favorite lenses on the camera, realized that you can get a cinema level output for $700 instead of the usual $7,000.
17:45
He was comparing it to a RED system that he loves and he uses and he owns.
17:50
But, uh, but he was just saying like it's cheaper to buy this GoPro than rent the cinema camera for a single day because a lot of these cinema camera when they rent it's might be 800 bucks for the day.
18:01
Uh, and you can just buy this system.
18:03
And so I think he's looking out and saying and saying the next generation of YouTube to filmmaker pipeline, they're not going to have the balance sheet that I have because he I mean the reported earnings are like >> he's one of the largest shareholders of Go, >> but the reason he is is because uh like Forbes estimated his creator earnings prior to Iron Long at like 30 million a year.
18:23
So he's been making a lot of money.
18:24
So, he can go and spend $7,000 on a on a cinema camera rig, but he knows that there are smaller creators that are going to try and break into more cinematic productions and GoPro might be the right tool for them.
18:36
Good content, product sponsorship, market fit.
18:39
And then, of course, he also uh bought the stock.
18:43
So, uh his enthusiasm for the product led him to start buying GoPro stock.
18:48
spent estimates roughly 10 to12 million for 8% of the company or something like that.
18:54
Obviously the company's gone up in value since uh it was a big bet but estimates put you know him at 30 million annual earnings and then of course Iron Long did 51 million at the box office on a budget of 3 million probably gets a lot of cash flow from that not to imply that he took home 48 million but Iron Long is going to continue to produce cash and you know he's he's in a fine position to to make a big bet on GoPro.
19:14
The story gets weird on August 27th because he posts this extremely positive sponsored video uh reviewing the Mission One Pro.
19:22
It's a great video, lots of interesting detail, and he just has a great on camera presence.
19:27
Very funny, uh lots of great editing.
19:29
Uh but uh people were like, "Ah, this is a little circular like he's getting a sponsorship for a company that he owns 8. 5% of the stock."
19:35
Uh but the founder and chairman of and the CEO of GoPro, Nick Woodman, is still in control of the company and still has uh class B shares or super voting shares. So Markiplier Yeah. Isn't that crazy?
19:50
He's held on this whole time.
19:52
So Markiplier actually only uh controls 3% of the company.
19:58
He doesn't have board seed.
19:59
Like it's not like he's going to be approving his own sponsorship contract.
20:02
Probably a completely separate discussion. So not a big deal to me.
20:03
And honestly, um, knowing that he knowing the sequence of events now, it makes me believe his review more because it's like he used the product, then he bought the stock, then he promoted it and reviewed it.
20:17
And this all just feels like a very natural >> friend of the show Hunter Weiss just texted me and said, "You guys have story wrong.
20:24
He bought two months ago and the SEC filing came out and then Bloomberg juiced it."
20:29
He covered it in the live stream last night.
20:30
He has half a percent of voting power. >> Oh, wow. Yeah.
20:34
So, so he bought and then the SEC filing dropped which released the actual news and then that timed up in the news as like oh he bought five days ago but in fact he was buying over the spring and the summer.
20:45
I think it was like a a stage investment. Um anyway uh let's see.
20:50
So uh overall that that that does not seem too circular or a big deal to me.
20:55
Uh the weirder thing is that GoPro just gets bought uh 5 days after the sponsored video.
21:00
Uh, and the company that bought them is Starman Optical.
21:05
They proposed this merger that pays uh $285 million in cash.
21:06
I think it retires the debt.
21:09
Uh, and GoPro shareholders retain 10% of the post-transaction company as well.
21:14
So, the acquiring company Starman is a holding company that's controlled by this uh Tel Tabili family, Tibel family, uh, and sits within a broader holding company that owns consumer accessory brands such as in case and Cypio and Kipio and Griffin.
21:29
Uh they make everything from like USBC charger bricks and phone cases and you can see GoPro sort of fitting in there in the electronics accessories.
21:37
Uh they're not in any of the huge categories but it's all similar supply chain, similar distribution, similar uh go to market strategies across the portfolio.
21:48
Uh they also in the the family also owns a lot of other companies.
21:52
It's a very large holding company and there's an AI side to the story which is uh where things have gotten sort of awkward because people are like GoPro's pivoting to AI.
22:01
That's not really what's happening I think.
22:03
So uh Starman has a new photonix division separate from GoPro.
22:10
Uh of course they might move some GoPro people over there at some point. they own everything.
22:14
But uh really the new photonix division is focused on making high-speed optical networking equipment for AI data centers which of course is like controversial now and now Markiplier has to answer for all of the AI community probably and has to deal with this.
22:28
Um but >> yeah he apparently said in the stream he is anti- data center and AI. >> Yep.
22:35
>> And uh is upset with the timing of all this. >> Yeah.
22:40
because I think he really just liked this new camera and was like, I think GoPro can make a run at like the next generation Hollywood filmmaker, which is being born on YouTube.
22:48
That's his core community.
22:50
Let's stay focused on that.
22:52
And then Starman comes in and says, "Oh, we're actually doing something completely different."
22:55
So, uh, weird scenario that he just got sort of roped into.
22:58
Um, so, uh, it looks like what actually happened is that Markiplier got excited about GoPro, bought the stock, then did a sponsored video to promote their new camera, then got blindsided by the acquisition, and now has to grapple with some confusion about the corporate structure and potential AI baggage.
23:13
But for Starman, it's an interesting flow because they get this solid brand that fits nicely within their portfolio and maybe even more importantly, they get a public listing on the NASDAQ.
23:24
So, they're keeping the listing, which effectively gives them access to the public markets in a more streamlined way.
23:29
It's kind of like a spa or like a reverse merger.
23:32
It's not technically like that, but uh because they're merging in a sub company, but in general, they now have a NASDAQ ticker.
23:39
And so, that's something that you can do uh and and is is a little bit like the SP. >> Yeah.
23:45
Originally, I was confused as to why it was still trading if it was >> they're planning to keep it trading forever. >> Yeah.
23:51
>> Because it will be the ticker for the holding company.
23:52
And of course, uh, stock is on a tear today, up 30%. >> Mhm. >> Uh, 33%. >> Mhm.
24:01
>> Well, let me tell you about CrowdStrike. Your business is AI.
24:03
Their business is securing it.
24:05
Crowd Strike secures AI and stops breaches.
24:09
Um, let's go through some random timeline posts because we didn't get to much yesterday.
24:13
We didn't get to much the day before even. It was a busy news day.
24:16
But, uh, what where do where do you want to start the timeline?
24:19
An idiot in motion will go farther than a genius at rest.
24:24
That just feels like good wisdom.
24:27
I don't know >> the importance of just like valition.
24:30
Yeah, golden retriever mode to some to some degree.
24:32
Um, new quote for board members just dropped.
24:34
I train like I've never won and I compete like I've never lost. Huh.
24:39
On purpose with J Shetty. I don't know. Uh, what else?
24:43
don't know. Uh, what else? the uh the uh you want to go through this uh this NFL wide receiver Dejon Love is am I right >> this was uh my favorite post out of the whole Dejon love cycle Andrew Reed saying wearing the Allen company Allen and company Sun Valley jacket I found on
25:04
eBay uh >> what actually so >> I the the the thing that's been missed is that I think this is a is an AI story because part of how he was proving that he was a player outside of just >> basically laring was he had uh somehow the Google AI overviews had picked up that he was saying that he was a 49ers player. >> Oh, interesting. >> Oh, interesting.
25:28
>> And so it was just assuming that that was the truth.
25:30
>> I saw him post a screenshot of the Google AI over >> in a video.
25:34
He'd be like, "And that's Google. That's not me.
25:36
That's Google saying that." >> Yeah.
25:39
I I thought he had doctorred the Google AI overview and was just sharing the screenshot. >> That's possible, too.
25:47
>> There's so many layers.
25:48
>> But what did this guy actually do?
25:48
In case you missed the story, it's just insane.
25:52
Feds say a 35-year-old man faked being a 49ers player and allegedly scammed 26 mil uh 26 women out of more than 1.
26:00
3 million through romance and investment schemes.
26:02
He reportedly used fake 49ers career, fake Instagram, fake bank statements, luxury cars, dating apps.
26:08
His IG even had free agency year one and Super Bowl highlights.
26:11
He was arrested at an airport with an alleged accomplice.
26:14
Bau really created an entire NFL career.
26:17
Uh yeah, walking around with a helmet everywhere is very very funny.
26:21
Going shopping and I think the uh aren't the real NFL players now like memeing this a little bit?
26:26
Like they'll just go shopping with their actual helmets to like >> everyone's having fun with it. be safe.
26:32
>> I think I think the funny thing is uh how much video evidence he created of him of himself like lying, right?
26:37
And they were and they were extremely egregious.
26:41
Like he had a more he he was saying that he had bit like >> the kind of real estate portfolio that you would only have if you were like a Hall of Fame level player, right?
26:49
It wasn't just like, oh yeah, I have a nice house.
26:54
Well, wasn't he also creating a fake backstory about saying like his parents were from Switzerland and wealthy and they own Gucci stores on Saks Fifth Avenue, which is a store, not a location.
27:04
And there were a bunch of other like sort of red flags where I think he said his family owns maj they're the majority shareholder in individual Gucci stores, which is not how that works at all.
27:16
Um, but uh, you know, >> sounded sounded good.
27:21
>> It sounds pretty good. Sounds pretty good. >> Yeah.
27:23
The the question is how quickly I saw something recently Netflix is doing these like Insta docks they're calling them where they'll they'll make a documentary like incredibly quickly about a um >> like a new story >> about a news story.
27:38
And the question is like there's so much footage here.
27:40
I bet you I like a documentary will be made from this. >> Yeah.
27:47
Why why can't it be fast?
27:49
>> Why can't it be on a YouTube sort of like time scale? >> For sure. For sure.
27:52
A lot of like what goes into the uh what goes into documentary production because I've done it is just like scheduling some sit down interviews.
28:01
You bring a team, you get the lighting right. The Netflix lighting. >> Yeah.
28:05
So, one of the one of the instadocs they made is about the decoy plane.
28:09
>> I don't know anything about >> details of a secret plane switch used during a presidential trip from a native that just happened in Turkey. Yes. >> Like coming out.
28:16
This is coming out uh on Friday, right?
28:18
So, >> story from last month. Okay. >> Getting released now. >> Yeah.
28:23
I mean, you don't even need AI for a lot of this production.
28:25
It's just being really I mean, of course, AI could help like with transcriptions.
28:28
Like there's a lot of like you go and do the sitdown interview and then you just need to reorganize all the different sound bites and having a perfect transcription being able to go through and highlight.
28:40
Okay, this is where the person talked about the thing that happened in act one.
28:43
Let's put it in the right side.
28:45
What do you >> Bobby Chipman says?
28:45
Yo, that route running was elite though.
28:47
A lot of people were were clocking.
28:49
No, they were they were clocking it.
28:52
Uh they were saying like how could you believe this was a professional athlete because he was he was certainly running routes.
28:57
I don't uh in one of the routes he posted he almost fell over too. >> Yeah.
29:03
I think he did at least practice or something. I don't know.
29:05
Anyway, let me tell you about Railway.
29:07
Railway is the all-in-one intelligent cloud provider.
29:10
Use your favorite agent to deploy web app servers, databases, and more.
29:12
While railway automatically takes care of scaling, monitor and security.
29:17
>> Interesting news out of Arowan.
29:17
Arowan uh is uh on their 18th location.
29:20
This is over in Thousand Oaks.
29:23
And at 20, federal law will force them to start posting calorie information.
29:28
Leo says we are two arowans away from mass rioting across Southern California.
29:33
Um uh what what's that other uh hill is it Hillstone that that is >> Hillstone has a has a sister restaurant.
29:46
Am I remembering this correct?
29:46
And they had to put calorie information on they they actually created like a new iteration I think of the restaurant. >> Oh. Oh.
29:53
So that they could separate cuz it probably makes the the menu aesthetics a little bit less >> Yeah.
29:58
It looks really bad if you're at like a sit down restaurant and they're showing.
30:01
I was somewhere where they had the allergens on the menu and uh it was sort of tastefully done and it was actually sort of nice and like had a little key and legend and could kind of post through and I don't think it was a huge chain or maybe it was I don't know may maybe all those rules kick in at a certain point.
30:17
Uh, let's head over to billionaire John Morgan who was on the ice coffee hour.
30:23
>> Morgan and Morgan >> um seemingly >> flexing >> like throwing some shots at at many AI AI founders who >> who say they're billionaires but not necessarily a billionaire in his book. Let's see. Let's see what he has.
30:36
I don't consider anybody a billionaire that don't have a real billion in the bank.
30:40
Guess how many people have a real billion liquid? >> I How many?
30:45
>> We Yeah, I don't know how many. Maybe 20.
30:48
>> Papa John was one of them. >> He don't have No way.
30:52
>> He said he put a billion. He sold for 1.
30:54
2 and he said he put a billion in dividends.
30:57
>> Dividend stocks earning 5%.
31:01
>> That's what he told us.
31:01
I think it's on it's on the record. It's on video.
31:02
Him saying there's only only 20 people that have a billion dollars of >> equity.
31:08
My financial statement's got every dollar.
31:09
I think I I do think saying like you actually have to have it in cash like you can't like it can't be earning a meaning you you can't have it invested at all.
31:20
>> I mean yeah if you just look at public company founders who still own shares that are liquid.
31:25
I mean maybe there's regulations about when they can sell and he doesn't count that as liquid because if you have to file a certain form with the SEC and sell on a schedule like you know I don't know like Beni off sells on a on a regular basis daily.
31:37
I think daily and so and that's for securities compliance and shareholder transparency and all all these very good reasons. Um does that count? I I don't know.
31:51
This guy's a funny but certainly a good sound bite though. >> Yeah.
31:55
And John Morgan I think you were telling me the story.
31:57
He I don't think gets super involved with politics but he was I think supporting uh marijuana legalization. >> Yeah.
32:05
specific seemingly because he's in the injury personal injury business and >> you might imagine that uh if you you know make marijuana more widely used more people will get in car accidents.
32:15
I don't know if there's any evidence of that, but it was it was an odd like of all this of all the uh charitable giving you could do, you know, curing cancer and helping solve hunger.
32:28
Uh yeah, marijuana legalization is pretty low on the list, but you know, he has his uh he has his choices.
32:34
Uh company watches are in the news.
32:36
First, let me tell you about Cisco.
32:38
Critical infrastructure for the AI era.
32:42
Unlock seamless real-time experiences. A new value with Cisco.
32:44
Um, good work is joking about them.
32:47
So, the best rare company watches a thread.
32:50
Of course, like this goes back to uh those old Rolexes.
32:54
The Rolex Air King Dominoes edition is a popular one.
32:58
Uh they also made a Rolex Hallebertton, which is a more controversial one, but uh it it the the Hallebertton logo actually looks not as jarring as the Domino's logo, which is sort of crazy.
33:12
Uh the there's a bunch of various various levels of taste.
33:15
Good works joking around with an FTX watch. There isn't much time.
33:19
Uh the Teamsters Union clock in clock out. >> These must be fake. >> Cabbage cheese. These are fake. >> Yeah. Yeah, these are fake.
33:26
Those but there are a bunch.
33:28
Um is this X one actually real? This one not? No.
33:32
Nate's just joking around.
33:34
But uh Google's done them. OpenAI's done them.
33:36
There's been a few other companies that have done these throughout the throughout the year.
33:40
You used to be able to go to Rolex and and ask them if you were a large company like do us a run for 30-year anniversaries of our most tenured employees.
33:49
Uh that has uh has slowed down among Rolex I believe.
33:52
Um but uh I think Tutor is still in the business.
33:55
I know that they did a run with Opening Eye and maybe with Google as well of the Black Bay and there's a there's a few others.
34:04
Uh what is Jensen wearing though?
34:06
Shout out to Jensen Wong, CEO of Nvidia, wearing the super rare Rishard Mill RM2705 Raphael Nadal.
34:15
>> They're calling it a GPU on the wrist.
34:17
>> This is a beautiful >> a blackwell on the wrist.
34:20
>> Yeah, $3 million price.
34:22
>> I don't see any I don't see any issue with this. >> Looks good.
34:24
I wonder what the occasion was.
34:26
I wonder I wonder uh if uh if he got this from someone specific or if he just picked it up for himself.
34:32
Pretty pretty interesting. I like it.
34:34
Uh, let me tell you about the New York Stock Exchange.
34:38
Want to change the world?
34:40
Raise capital at the New York Stock Exchange.
34:45
Uh, little back and forth here between TJ Parker and Lloyd Armbrust.
34:47
Uh, Lloyd built an entire pharmaceutical factory so we could sell drugs on the internet.
34:58
>> Should we watch the video?
34:59
>> Let's watch the video. >> Okay.
35:01
>> I'm Lloyd, founder of Ronin RX.
35:01
We manufacture and personalize GLP1s for $78.
35:06
Yeah, $78 a month for drugs like a Zmpic.
35:12
>> Do you know the reference? >> Are drugs even legit?
35:14
>> Uh, our drugs are super legit.
35:16
Every prescription doctor, but forot.
35:22
>> We collect your health data and use AI to help your doctor personalize it.
35:27
And other companies have taken this >> video and remade it before, >> but kind of out of it's gone out of style a little bit. >> Well, yeah. Maybe it's coming back. >> Yeah, exactly. It's been so long.
35:42
>> Yeah, it it does deliver a lot of information very succinctly.
35:44
Uh, and uh, but yeah, the the the the dollar the the Dollar Shave Club video, I believe, was produced by the Harmon Brothers, who went on to create a whole series of these sort of like designed to go viral advertisements for uh, startups and a lot of them did very well.
36:05
Uh anyways, TJ says farm tot more like YC to jail really uh quite quite aggressive kind of thing you post as uh as a you know unicorn exited founder.
36:18
Lloyd responds, "Brother, you sold drugs on the internet for 1 billion and then taught Amazon how to do it.
36:22
If this is YC to jail, you built the highway." Which is >> built? Which is >> Wait, what?
36:33
>> Are you saying that TJ built the highway that you're on?
36:37
>> The highway to >> to jail >> to to jail.
36:40
>> Anyways, TJ responds and says, "You put a smarmy med spa business on the internet and are masquerading around as a pharmacist in a white coat as an English major."
36:48
>> TJ actually is bonafide as a real pharmacist.
36:50
So, finding out I majored in English is impressive.
36:55
>> They're saying uh Lloyd might be the the Dejon love of uh the pharmacy business. >> Yeah. I don't know.
37:01
The the putting on the lab coat little bit of a lar.
37:03
I I was always joking with one of my co-founders who does have a PhD in biofysics uh that he should wear a lab coat and he was like, "No, I'm not wearing a lab coat."
37:14
I'm like, "You're technically a doctor.
37:16
Like, we should like you should you should go by doctor."
37:18
Regard says, "Bro just wants to sell drugs online at in peace." >> Yeah.
37:24
The the thing is is like the the the the rules of the road for pharmaceuticals, for drugs, the FDA, like these have been written.
37:33
This is not the internet where it's the wild west and people don't exactly know what's a social media site.
37:39
The oh, you know, what can you post? Section uh what is it? It's not 83b.
37:44
You know the one I'm talking about.
37:46
section 260 or something like 230.
37:49
Uh section 230 is sort of something that comes up later.
37:53
So there's this like move fast and break things approach in in the early era.
37:59
Okay, are there regulations around ordering groceries online? Let's just test it out.
38:03
And but that that's not the environment in the pharmaceutical industry.
38:08
And so uh TJ knows the rules and uh he's willing to he's willing to enforce them on the timeline every once in a while.
38:14
He'll he'll let it happen.
38:17
Um, uh, should we watch this video of this boat? >> Yes.
38:22
>> This was a crazy crazy video.
38:22
So, a boat was going 213 miles an hour at the lake of the Ozark's shootout, which sounds like a great event.
38:29
Uh, flew in the air after crossing the finish line, flipped, and crashed.
38:34
>> Every time I see a video of boats racing like this, it flips always.
38:38
>> So, I just have this I just have this understanding of like if you go that fast in a boat, you're going to flip.
38:43
But, I think they do it all the time.
38:45
Yes, I think this is probably a one in a thousand occurrence or one in of 10,000.
38:50
>> Not one in a thousand otherwise be every every time.
38:53
>> But but I agree to me it's like one in five boat videos looks like this. So let's play it.
39:02
>> Oh, the slow motion too was really traumatic.
39:04
Everyone survived which is >> Yeah, they actually stuck the landing. >> Look at this. >> Pretty cleanly. >> Pretty cleanly. Are you >> No, wait. Wait for it. Wait for it. >> Smashing it.
39:16
>> No, they land how they should.
39:16
There's There's another There's another angle that shows they landed perfectly, John.
39:23
>> I think they were doing this on purpose. >> I don't like it. This is very very risky. I do I do wonder.
39:31
Uh Jay Bhutal Bard says uh what it feels like to long semis which go up and down 10% every week and end up flat.
39:39
>> Yeah, because he landed perfectly. >> I guess. Yeah.
39:41
I mean, one person broke a leg, one person walked away clean, both survived. Very good news.
39:46
>> A lot of commentary on uh the new pay packages over at Apple.
39:49
Chase said, "Get a degree, get an office job, climb the corporate ladder, retire at 65." Congratulations, Tim.
39:57
You did exactly what the system told you to do instead of starting your own business. >> He is 65. Yeah.
40:07
Well, his new pay package as executive chairman feels a lot better to me than his CEO pay package.
40:13
>> A lot more flexibility. >> 47 million a year. Yeah.
40:16
>> Um uh hopefully less work.
40:16
He deserves a little a little little a little time away from the action.
40:22
>> But Turner making less. >> Turn making less.
40:23
I found there's 35 professional athletes that like roughly that are going to be making more than John Turnis next year. >> Okay.
40:32
>> Um and uh anyways, I I I feel like it's a fair place for him to start. I hope he can climb.
40:37
I hope he can 10x it and then maybe 10x it again, >> personally.
40:42
Um, couple more orders of magnitude would be great, but he's got to prove himself. >> Yeah, for sure. For sure.
40:47
Uh, what else is going on?
40:51
Elon is making power turbine components in the Wall Street Journal. Skeptical.
40:55
They say it won't be easy. Uh, has everything.
41:00
>> Has he ever done anything easy?
41:00
The guy like he chews glass daily.
41:03
That's his whole stick is is just doing things that seem impossible.
41:08
Uh stocks of blade and vein manufacturers fell in response, but the threat to them is still remote.
41:14
So, let's see what the Wall Street Journal had to say.
41:18
First, I'll tell you about public. com.
41:20
Investing for those who take it seriously.
41:22
Stocks often sponsor and more with great customer service.
41:24
If you want to get into blade and vein manufacturing stocks, head over to public.
41:30
Uh only a few companies make the CR crucial components for power turbines that AI data centers are so desperate to get.
41:37
Elon Musk wants to go ahead and make his own that has unnerved investors in this prized oligopoly.
41:43
Okay, we're going to learn about the the power turbine market for a minute.
41:47
Uh over the weekend, Musk confirmed on X that SpaceX will start making blades and veins that go into natural gas powered fired uh power turbines.
41:58
I think Big Turbine wrote this article. >> Yeah.
42:01
You think it's a little uh uh coordinated counter counter messaging?
42:06
>> Yeah, they were enjoying their oligopoly. >> Yeah, maybe.
42:08
Uh by doing in-house casting at SpaceX, we can accelerate natural gas turbines coming along coming online by up to 18 months, which is a profound gamecher.
42:18
He wrote in his post uh responding to a report from the information. Uh interesting.
42:23
Uh wasn't Sarah Guo mentioning on the invest like the best podcast that uh a lot of the or she was talking to a hyperscaler CEO or someone uh who was in a place know that was saying like the b the bottleneck is real.
42:36
It's very real and there's nothing uh in the short term that's going to come online that will alleviate power generation.
42:42
Um so that is where the real bottleneck is at least in the short term.
42:46
So in mid August, Morgan Stanley published a report saying that SpaceX was planning such a foundry in Bastrip, Texas based on the company's job postings.
42:54
Shares of Helmet Aerospace fell more than 7% Monday before partially rebounding on Tuesday.
43:00
Helmet and Berkshire Hathaway's precision cast parts are the two biggest players in the market for these parts which also include blades which also include blades and veins for the aerospace and defense sectors.
43:12
Smaller players DPC shares were also hit.
43:15
Uh it is premature to scout to count SpaceX as a threat, the Wall Street Journal says, but shares of Helmet Aerospace and DPC might have been due for a breather.
43:24
They are among the priciest artificial intelligence picks and shovels plays at 42 times and 44 times forward earnings respectively.
43:33
Uh turbine makers GE Vernova and Caterpillar Fetch 33 times and 26 times earnings for perspective.
43:40
Uh and there's a nice chart there to show you the price to earnings or price to forward earnings ratios for some of the AI bottleneck plays and uh and the the blade and vein manufacturers are up in the upper echelon.
43:57
DPC is the most vulnerable to disruption in this space.
43:59
It is small and about 40% of the revenue comes from natural gas fired turbines.
44:04
While Hmet holds about half the global market share of components used in natural gas turbines, it is diversified across aerospace and defense with only 11% coming from gas turbines.
44:15
SpaceX will face barriers to entry.
44:18
One reason there are so few companies in the sector is that it's technically challenging to make the blades which must withstand extreme temperatures and rapid rotations.
44:26
That feels like SpaceX's bread and butter, though.
44:28
Uh the casting process makes a uh involves making a new wax mold from scratch each time.
44:34
Making these parts requires the blade to be grown in a vacuum furnace as a single crystal of nickel super alloy.
44:43
According to Nigel Chong, an analyst at Semi analysis. Huh.
44:48
Semi- analysis getting a shout out in the Wall Street Journal.
44:50
Uh even a stray grain or hairline defect means the part has to be scrapped.
44:56
He added, "A new manufacturing line could scrap over half of its production for a long period, so yield will be difficult to get up."
45:04
Uh, it is also a highly secretive process.
45:06
Once the parts are produced, the ceramic cores and wax used to make them are destroyed.
45:09
Helmet's chief executive, John Plant, said at an investor meeting earlier this year, he says, "We're not getting distilled. Don't worry about it. We're good.
45:17
We destroy every evidence that would lead someone to be able to copy us."
45:22
That prevents competitors from reverse engineering them.
45:25
Uh so Helmet Aerospace's annual revenue from industrial gas turbines is up and to the right with incredible forecasts and you can see the chart taking off.
45:35
They're going exponential right now.
45:37
Um a high scrap rate might make might matter less if SpaceX is making parts for its own use.
45:44
Morgan Stanley's report noted that we would not expect SpaceX to be a material supplier of blades and veins for supply outside of SpaceX use.
45:50
So they're going to uh use everything internally.
45:55
Um, speaking of industrials, we got to talk about uh rotor sales.
46:03
>> So, there was news in the financial times that uh that Marque is going to uh put a wind sail on their container ship.
46:15
And there's a very interesting It's a very interesting design because I see the image for the ship and I'm like, >> "Looks like a smoke stack. >> Where's the sail?"
46:22
Yeah, it looks like a smoke stack.
46:24
Uh, and I'm like, okay, does the sail come out of that big round thing? And no, it doesn't.
46:28
That is what's called a rotor sail, which actually produces wind force and and accelerates the vehicle.
46:37
Uh, without any traditional sales of what you think.
46:40
So, there's an explainer video from Norse Power, who makes these that we should watch a little bit of.
46:44
Uh, we can we can kick this off.
46:47
Uh it's a one minute video, but we we we can watch a little bit of this YouTube video uh on Norse power rotor sales because it's a fascinating world I didn't know existed >> and you need to know this.
46:58
>> This is a this is crucial. This is crucial.
47:02
>> How do Norse power rotor sails work?
47:04
>> You might be familiar with curve balls in sports.
47:09
>> What exactly causes the ball's path to curve?
47:13
>> A spinning ball compresses air on one side and thins it on the other.
47:18
The pressure difference causes a power thrust that curves the path.
47:21
>> If you work in north power rotor sail is a large cylindrical sail.
47:24
A common misconception is that wind spins it.
47:30
Instead, it is rotated actively by an electric motor.
47:33
The spinning sail compresses air on Jasper in the chat says, "Shut up on the front."
47:39
>> I'm from the founding town in Denmark.
47:41
Don't believe in the sail. >> Take some shots.
47:44
Thrust is created in the same way for the football and the ship.
47:54
In good conditions, Norse power rotor sails can actually produce more thrust than the main engine.
47:59
No horsepower saving fuel and the planet.
48:05
>> And lastly, there's a photo of a rotary sale on a small catamaran that we think is a steal.
48:10
I don't know how much this thing would sell for.
48:12
Yeah, Tyler was looking at picking this up because he's been exploring the marinas in the area.
48:18
He wants to potentially uh live on a boat. >> Yeah.
48:21
Well, I have the perfect ad read before our next guest joins.
48:24
Let me tell you about console. com.
48:26
Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets.
48:35
Our next guest is Nikesh Aurora, chairman and CEO of Palo Alto Networks.
48:40
who's here after fantastic earnings. How are you doing, Nash? Welcome back. >> Great. How are you guys?
48:47
>> We're doing fantastically.
48:47
Uh >> I appreciate the little console plug right before this.
48:53
>> We've been very happy to sponsor not.
48:55
>> They're right on the laptop sticker.
48:55
Uh >> is it a good company?
48:59
>> It's a fantastic company.
48:59
You've heard of it, right?
49:01
>> It's a bit late to ask, but I should have asked you before, but yeah, I think it's great.
49:05
>> It is a fantastic company.
49:05
We love the team over there.
49:06
Uh had them on the show multiple times and of course talk about them every single show.
49:09
Super excited for you guys to be partnering, >> but we can get to console later.
49:12
Let's talk about Palo Alto Networks.
49:14
What's the newest development this quarter?
49:18
What is the story that drove this quarter?
49:21
>> You know, uh I've been trying for eight years to get the attention of customers to focus on cyber security.
49:26
It's been hard work, >> but I really want to give a shout out to my friends Sam and Dario who did a fantastic job getting the living Jesus out of everyone. >> They're pretty good. They're like your best.
49:38
Yeah, your best >> writing letters protect us on cyber security. They talk about MTOS. They talk about Astra. It's amazing.
49:44
Every CEO CIO wants to talk about cyber security and how do you secure me? I I love it. It's amazing.
49:50
That's what drove a lot of the interest in cyber security and people have realized that mythos was interesting because it can find a lot of vulnerabilities and there's a lot of interest.
49:59
People want to talk about it.
50:01
They want to talk about the capabilities of open AI.
50:02
of open AI. But very soon after the first 5 10 minutes becomes about okay wait this is just the beginning what happens after when the next bigger faster model shows up what do I do then like okay I get it you guys can help me test it but what happens how do I fight it if I get attacked then the answer is well you can only fight that with some
50:21
sort of a consolidated platform that sits in the back that looks for this stuff at machine speed and is able to respond at machine speed time which means you know you have to fight AI with AI and that's where also comes in because we've spent our life building systems that can respond in near real time or at machine speed to protect them. So that's kind of been the
50:40
So that's kind of been the >> inflection point or pivot that's driven a lot of the interest in cyber security over the last 6 months.
50:47
I think that trend continues to >> sort of accelerate both from a customer interest level as well as you know my friends are continuing to build better faster models which can be weaponized. >> Yeah.
50:59
uh what was the last three to six months like?
51:03
Because you have these moments where the AI labs are causing a lot of discussion around security and overhanging all of that.
51:10
I think people were were mostly worried about when the open- source frontier catches up and the and the attackers get those level of capabilities.
51:23
And there's this narrow window that is sort of a window that continues to move continuously, but there's a window where Palo Alto Networks and other folks in the security space have to really uh get the posture correct. What actually changed?
51:36
What was what was the conversation like and what uh like how did that process go?
51:42
How much of a boogeyman was open-source?
51:45
Uh because it was discussed early, but there were a bunch of different takes.
51:51
Look, I think what has happened is even in the last 6 months, you've seen the capabilities of these models continue to rise.
51:56
And I read something that two days ago Sam said that Astra, their new model, it's so powerful that they're going to have to clip its wings and trim it down.
52:04
So that gives you a precursor of things to come.
52:07
I'm sure those capabilities will be caught up with whether it's with other frontier LLMs or the open source community, the open source models or Chinese models for that matter.
52:16
So I think the capabilities coming going to come at us as hard and fast.
52:19
Now honestly just cyber security is simple.
52:22
I never grew up in cyber security.
52:23
I have very simplistic mental model.
52:25
If it's bad and you know it's bad stop it the parimeter. >> Yeah. >> All right.
52:30
That's called parimeter security.
52:31
That's where 80% of our business lives. >> Yeah.
52:34
>> That's where when you find a vulnerability you found it in the parimeter. Stop it. Protect yourself.
52:39
And that's what patching and fixing your vulnerabilities is all about.
52:43
>> But unfortunately stuff still gets through. >> Yeah.
52:46
>> That's why breaches happen.
52:46
that happens because you have a vulnerability that you didn't understand because a credential got hijacked or something got misconfigured.
52:53
Then the question is you got to find it quickly and you got to get rid of it before it creates impact in your organization.
53:00
This find and fix it part is where all this you know superhuman effort needs to be put in in transforming cyber security posture, cyber security architectures, ripping out old stuff that can no longer work at machine speed.
53:14
And I don't think that's going to take 2 months or 3 months.
53:18
That's a 3 to 5 year journey.
53:18
And that's 3 to 5 years if everybody sets their mind to it.
53:22
And you know, I look at life through a cyber security lens.
53:24
So I would like everybody to do that.
53:27
>> Unfortunately, my CIO friends are busy.
53:29
Their boss wants them to do coding quickly.
53:31
They want them to transform the company with AI.
53:33
They have existential threats because the world is using AI. Why are we not using AI?
53:36
So the poor CIO has got a lot on their agenda.
53:39
Cyber security being one of those things.
53:40
So they're trying to balance all these priorities at the same time.
53:43
But I will say there is more awareness, heightened attention and more importantly whatever they had on their cyber security docket, the priorities have shifted in that docket to make sure that they can protect themselves against the impending sort of weaponization of AI models and bad actors getting better and better at this stuff.
54:02
So the trend is our friend.
54:04
There is positive momentum.
54:04
There is positive momentum. the trajectory has changed for the better but don't expect you know a sudden inflection point that people suddenly going to come out and say the first thing I want to buy is cyber security >> sure sure when when a CIO wants to buy
54:18
cyber security is the is the economic calculus changing because AI uses tokens like is there I are are are they do they need to shift their thinking from this line item grows along a different axis than what we previously understood the cost and benefits would evolve over time as we scale our network. >> That's a very insightful question, my
54:42
>> That's a very insightful question, my friend.
54:43
Um, so that's a good question because I don't think if we slap dash frontier AI models in the protection scenario that is a good economic outcome. >> Yeah.
54:56
Like you just cannot do a 5. 6 pro fable 5.
55:00
1 for every transaction that happens across your network.
55:02
You're going to go >> That's right. So think about it.
55:03
Every day we inspect 180 terabytes of data >> every day. >> Yeah.
55:10
>> Uh you stick anything against it which has got a sort of a token based economics against on it.
55:14
It doesn't matter what the price of tokens is.
55:17
That's going to com that's going to sort of >> add up a lot of compute.
55:19
That is why what we do today is we write machine learning code where the marginal cost of inspection is zero. >> Sure.
55:26
>> It's hard to beat zero. >> Yeah. Yeah. >> Right.
55:30
>> So the marginal cost of inspection is zero.
55:31
We got to figure out how you know what's the right balance where I want to use AI in the most intelligent way possible but I don't want it to do it in a way that the marginal cost goes up.
55:39
So the way it's going to work is for already we're training small language models which going to work on a very small footprint which will do a specific task.
55:48
Okay, my job is to stop people going on bad websites.
55:50
Well, we get 150,000 new websites every day in the world.
55:55
How do we find them, classify them, stop them?
55:56
Well, let's train a model to identify these bad websites.
56:00
let's have it work on the endpoint or your laptop.
56:02
So it's doing that and that's all it does.
56:03
And you can do that by taking all the collective intelligence that we've built over the last 17 years.
56:08
Train a small language model deployed to the customer where the marginal cost stays zero and my cost of training is 5 105 $20,000. Yes. Right.
56:16
So you find many of these use cases will be deployed over time where we won't need a frontier AI LLM.
56:20
Where we will need fable five like capability or midsource like capability is in what let me call it the defender model. >> Sure.
56:28
The defender model has to be as smart as the attacker model.
56:30
Y now there there's going to be a debate about token economics, but remember you're only using the defender model in situations where you find that there's a problem. >> Mhm.
56:41
>> And those are fewer and far between compared to having to inspect all peacetime traffic using tokens.
56:45
So I think that's where the balance is going to end up from an economics perspective.
56:50
I'm hoping that AI costs don't become a factor in cyber security. >> Yeah.
56:55
talk about sorry >> talk about uh social engineering.
56:57
Uh we we heard yesterday that um employees are actually clicking through uh fishing uh links at a higher rate than than they were historically simply because a lot of the the grammar being used in in these uh social engineering attacks is just better.
57:16
It's harder to immediately clock it.
57:18
Do people and teams not have their guards up enough?
57:21
What what is the what is the solution there?
57:23
You would think that everyone is reading about the potential risks of of of um LLM based, you know, attacks all over the news media.
57:34
You would think that when they're in their inbox, they're maybe thinking, I won't click this link from, you know, ask >> $20 gift.
57:41
>> I'm going to tell you a funny I'm going to tell you a funny story that, you know, we do fishing attack simulation at Pala all the time.
57:48
>> There's only one time I was tempted to click on it. Thank god I didn't.
57:50
And I'll tell you why I wasn't. Right.
57:52
So, there's this email that came saying it's National Pet Day. Take a picture.
57:56
Take a picture of your pet. >> Yeah.
58:02
>> And anyone who puts the cutest picture of their pet going to donate $5,000 to charity.
58:08
>> What the hell are you doing?
58:10
>> I got that like put a little tear in my eye.
58:14
Thank god I'm not into pets because if I was into pets, I'd be clicking a picture and uploading it and clicking on it.
58:18
So, >> this is where social engineering kicks in, right?
58:22
people will find ways to try and entice the end user to click on this.
58:27
The only way to fix it in the medium term, long term, is start running AI classifiers against the emails to understand whether it's a real email or a fishing attack.
58:34
And it's much better if you can build that into your scanning systems than if you expect every individual to be smart enough to discern whether it's a fishing link or not.
58:43
Now, it was hard to do in the past because you couldn't really read email or get context.
58:48
But today I'm pretty sure it's a trivial task to train a small model which says look this email address looks weird doesn't look like it comes from our company.
58:55
This domain's never been seen in our entire infrastructure.
58:57
This is talking about something which this domain should never be talking about.
59:02
All those are simple checks which you can do using a small language model from a scanning perspective.
59:06
So that's going to be the antidote to these much better social engineering attacks that are going on over there. >> Yeah.
59:12
Speaking of dogs, Ilia posted yesterday uh and said that that Neoclouds uh Ilia only follows three accounts.
59:20
SSI, OpenAI, and Doc account. Um apparently a big dog.
59:27
>> Even after you guys got bought out by OpenAI, he doesn't follow DVPN. >> We got to get him.
59:31
We got to get him on the show.
59:32
I dressed up as him on Halloween honor one of these days.
59:36
>> No, but uh he was posting that that Neoclouds need a lot better security.
59:38
He feels like it's an important issue.
59:41
Is that an area that you're focusing or that you will be more focused on? Um, are they too busy?
59:47
>> I actually I actually posted back send them to us and I'm happy to help, but uh I am not aware of what he was particularly referring to.
59:53
Everybody needs a lot of more security. Yes, of course.
59:57
But I don't I don't actually don't know what he was what he was what he was >> I think he was specifically worried about the the like in the context of the hugging face incident uh like an agent swarm an agent state like wanting to get more resources and just going into a neocloud to get more inference of themselves of hijacking capacity.
1:00:15
The good news is the good news is there doesn't seem to be much excess capacity out there so it's hard to hijack capacity but let's let's hope that you know >> Yeah. Yeah. Yeah.
1:00:24
A lot of a lot of alarm bells are going to go off you like wait. >> Yeah.
1:00:28
I think so far it's my understanding most the neoclouds are re sort of selling their capacity back to the frontier LLMs and the frontier LM will basically build very strong tunnel pipes which basically sort of you know make it cap almost like captive capacity.
1:00:41
So I'm less fearful that that's going to be a problem but yes you know >> at an infrastructure level everybody needs to put in basic infrastructure security and I think some of them are I think some of them are not putting they're still in the stages of building their clouds yet.
1:00:53
I don't think I think the ones who are built for to be fair to them are deploying firewalls and technology to make sure that there is no unauthorized access.
1:01:01
But maybe Ilia knows more because he's smarter. >> Yeah.
1:01:04
What's the state of AI research at Palatha Networks?
1:01:07
I you mentioned training small models.
1:01:09
Is is is it so exciting that you have current employees that want to jump onto that project and reskill and learn the art of training these small models?
1:01:22
Are you hiring new AI researchers?
1:01:25
Is there a specific skill set within AI research that is hyper relevant to that team?
1:01:30
What does your strategy for sort of remaining on the frontier of small models that are great at cyber security?
1:01:40
>> Well, I think there are two or three sets of people we want, right?
1:01:42
One set of people we want are who are AI savvy, who know how to use AI to get their jobs done better, who know how to use coding agents for AI.
1:01:49
That should be a lot easier than hiring AI researchers. There we have pivoted.
1:01:54
I think 50% of our new hires in the last 6 months are early in career.
1:02:00
>> Okay, >> these are people who are learning at and they're typically having to run through hackathons to get to Palo Alto.
1:02:03
You don't we don't look at where you went to school.
1:02:07
We care about where you can use coding agents, you can use AI.
1:02:09
So that's good because we're pivoting our workforce and if we keep following that trend, it's reasonably likely that we will overwhelm the uni savvy people with more AI savvy people.
1:02:18
That's kind of like ground zero.
1:02:20
You got to get that done.
1:02:23
>> The second part is there are people who are really good at cyber security and know AI and they'd like to get involved.
1:02:29
And if you want to work in cyber security, there's no better place to work than Palo Alto Networks, right?
1:02:33
We're the largest cyber security company in the world.
1:02:34
You want to have an impact, you want lots of proprietary training data, we've got it.
1:02:37
So we are lucky given our position that we can attract some of the people who work at the intersection of cyber and AI.
1:02:42
The third part is raw pure AI researchers who can you know do wonders with small language models and and large language models.
1:02:51
There we have people who are uh AI literate.
1:02:55
We have some PhDs in AI who work here who have a cyber security bend but they can go back to their roots in AI and there we supplement that capability with third party training companies because they've been doing it around now for multiple customers.
1:03:06
So you want to make sure we can do it once let's not get it wrong.
1:03:10
let's have somebody who's done it 500 times and bring not maybe 500 is too many but 20 30 times let's bring them as part of the team so we can make sure we're getting right.
1:03:19
So that's how we're tackling it and thankfully we don't have to compete with the frontier models for you know hardcore AI researchers to build our own you know >> big models with multiple parameters.
1:03:30
>> No totally uh well we have Andre from console uh here with us on the show.
1:03:35
Let's bring him in and I want to hear about the partnership how this came together and what the plan is.
1:03:38
Look how help you bring him in. >> Oh, perfect. He's right here.
1:03:43
>> I thought he was I thought he was >> Sorry about that.
1:03:46
Okay, so >> uh introduce the the the the thesis here.
1:03:51
How did you guys uh uh start talking?
1:03:54
What does the future look like for console at PaloAlto Networks?
1:03:56
Well, look, um, we spent a lot of time talking to a lot of startups, uh, across the ecosystem, cyber security and non-cyberc.
1:04:06
And as we sort of continued our conversations, we ran to Andre and his team.
1:04:12
Uh, we run a very strong capability obviously in security operations and identifying that.
1:04:16
Uh, we have a lot of data as I said 180 terabytes just about all the networks.
1:04:22
We have an observability company which looks at it from the outside in to see how customers infrastructure is running and we run observability for one of the largest frontier LLMs in the world from that vantage point and as we were talking you know Andre shared what he was working on uh you look at what he's
1:04:38
doing he's taken a very AI native agent first approach to building a product that is what future of software needs to look like you know he's actually hit the nail on the head in terms of how we need to build software for the future that is something which is a rare skill things that we don't do internally. Then he
1:04:51
Then he coupled that capability by looking at the operations of a company both on the IT side and nonIT side internally say well how can I take that agentic capability build product that sits on top of the underlying systems that work in a company. >> Mhm.
1:05:08
>> Mhm. uh when we saw that we saw wait if we could bring the large data lake the backends we have in security and IT operations and we can bring his capability could we build something that's amazing for our customers and that's sort of what started the conversation he was a hard nut to crack he and his partner wanted to do it alone
1:05:26
but I had to use every bit of charm and persuasive skills to convince him and Neil going be part of our alter and couldn't be more delighted that he's part of the family now >> yeah I'm so excited for this we were looking at the the console website And uh in such a short time you got every single logo on that website. Uh Uh fantastic execution.
1:05:44
What uh what what excites you most about uh the console journey thus far.
1:05:50
And what are you most excited for in the next chapter? >> Yes.
1:05:55
So I mean first of all the DBPN sponsorship got us a lot of those uh a lot of those customers. >> So excited for that. That's amazing. >> Little plug there.
1:06:02
Um I think uh look we we started this journey about three years ago and uh it's been uh uh kind of better than we could have expected.
1:06:11
Um we started in IT and then we've kind of like expanded.
1:06:15
Most of our customers actually use this us for more than just it.
1:06:18
It's you know HR and legal security finance and so on.
1:06:22
Um I think what we realized was if we were going to go broader you know go beyond it we uh I think partnering with a larger customer uh larger company that has you know works with the largest companies in the world um felt like a natural path and so I'm excited I think
1:06:38
for the future where we you know can just we have more resources we can go after the vision at a much much broader kind of like product road mapap >> I want to hit the >> we're going to we're going to work on that to get him more excited but Well, how about this for >> the first one? >> How about this? >> How about this? >> How about this?
1:06:58
>> Um, is that >> I'm so I'm so happy for both you guys.
1:07:02
Uh, like Andre, I if there was a CEO that to work for in my book, you know, especially in your category being Nesh, you know, he's like a he's like a you're very like fatherly figure, you know, you're uh >> start working on your golf game, buddy. >> Yeah.
1:07:18
start working on your golf game cuz we're going to need a lot of birdies.
1:07:22
>> No, he's going to work, bro.
1:07:22
He's going to work on you. >> He works, you golf.
1:07:28
>> Yeah, >> that's the plan. >> Yeah.
1:07:30
Well, thank you guys so much.
1:07:32
>> Thrilled for you both and uh yeah, excited to see the progress you make.
1:07:35
>> We'll talk to you soon. Have a good one. Goodbye.
1:07:38
>> Let me tell you about Codeex.
1:07:38
Codex is a powerful workspace for getting work done with AI agents.
1:07:42
Whether you're writing code, analyzing data, creating content, automating business workflows.
1:07:44
Codex helps you move pro projects forward from start to finish.
1:07:48
Our next guest is from Blue Owl Capital.
1:07:50
We have the senior managing director Kurt Tenbound.
1:07:52
Sorry to keep you waiting, Kurt.
1:07:54
Thank you so much for joining the show. How are you? >> No, no worries.
1:07:58
Well, uh, you know, you had to you had to finish with Nesh there and give him a hard time about all the all the birdies he's been getting.
1:08:03
So, I appreciate appreciate that.
1:08:06
>> He's a fantastic golfer.
1:08:06
uh since it's the first time on the show, I would love to know a little bit about your focus within uh the organization and uh and then I want to go into the the latest deal with Iron, but also a little bit of the lineage of this business that Blue's built up.
1:08:23
We've seen uh we like we've covered the company so much on the show, but uh I think you're the first person from the organization to join.
1:08:29
So, very excited to talk to you. >> Yeah.
1:08:32
And excited to uh talk to you, Jordy and John.
1:08:35
big fan of the show and thanks for uh thanks for having thanks for having me on. So >> awesome.
1:08:40
>> Yeah, I I at at Blue um I focus on our AI compute infrastructure business.
1:08:43
Um and so what that means is we have a big robust data center investing practice.
1:08:49
We own over a 100 data centers across the world about 10 10 gigawatts worth of compute. Wow. >> There you go.
1:08:55
Um and um and but however that business is really focused on kind of building the underlying data centers.
1:09:03
My team is everything that goes in.
1:09:03
And so, as you guys know, well, you spend $25 on a data center, you have to spend $75 on a chip on the chips that go inside every 5 years.
1:09:13
And so, that's what we're really excited about, figuring out ways to partner, figuring out ways to finance that piece of the buildout.
1:09:20
buildout. Um what's interesting for us because Blue is a diversified asset manager across a bunch of different strategies is we really get to bring the excellence attached to our data center investing business, our direct lending business where uh we really got our
1:09:35
start uh as well as our leasing business and bring the combination of all three of those together uh to be able to provide solutions like Iron which we're excited to talk to you about uh to to market that we think are differentiated versus many of our other peers. Um,
1:09:48
Um, every time I see private credit and data center buildout in the news, it's always this discussion about GPU depreciation.
1:09:59
Is that an overroought discussion?
1:09:59
Do you feel like you have a stronger feel on that?
1:10:05
Now, we obviously we've seen a lot of incredibly positive news around depreciation with even A100s getting really high utilization rates long into their life.
1:10:16
That was sort of the the primary takeaway from from Cororeweave's last earnings call was just that they, you know, have these old GPUs that are that are that are going to be generating revenue well into uh the the the >> But I'm curious like is is GPU depreciation actually top of mind for you or is it is it something that you feel like is pretty well understood, pretty solved?
1:10:40
>> Yeah, it's it's a good it's a good question.
1:10:41
Um and listen that the corewave data point is quite notable and something you know we and the rest of the market obviously um took uh took took note of but at Blue we we don't pretend to have a crystal ball on depreciation or forward rates for GPU levels.
1:10:56
Um obviously we're very bullish on them in general but the way we've invested here is really focused on keeping the duration of the investment we're making relatively short.
1:11:04
it matches the underlying contracts that we have with um some of the AI natives that we are financing and we're excited about talking about that piece of it as well.
1:11:15
Um and then underwriting iron as a investor and getting comfortable there and so it's it's not we are not just hanging our investment on forward depreciation rates for GPUs although it's something we're obviously very focused on and spending time around.
1:11:29
>> Um what does the current landscape for these types of deals look like?
1:11:32
because we see uh hyperscalers, sometimes Nvidia directly doing something that looks a little bit like equipment financing and I'm wondering if the if the shape is like are you competing with people outside of the private credit world at this point?
1:11:48
How big is the is the pool of capital that the data center constructors and operators are actually going after?
1:11:55
Yeah, I I think this is a moment in time where um everyone is going to have to be invested across the landscape to get to the type of capital needs that we we need.
1:12:03
I I actually think at some point capital may become the limiter or at least one of the limiters attached to it.
1:12:09
We're seeing the investment grade market, finance, chip, compute actually quite efficiently, but there's a lot of demand for that and that demand will continue and will continue to escalate.
1:12:18
And so the part of the market we're really focused on is the non-investment grade piece where we think it's a lot harder to get that type of financing.
1:12:25
We're able in the case of iron to finance the AI natives which is a particular pain point and pinch point in the market and and that's um that's where our focus is that's where our focus has really been. >> Yeah. Got it.
1:12:37
uh what are you seeing uh on the actual data center operator side and uh what are the smart players doing to overcome sort of local regulatory hurdles?
1:12:48
You know, we've heard >> uh there's there's a bunch of ideas being thrown around right now.
1:12:52
How do you get a local community really bought in?
1:12:55
There's the tax revenue component.
1:12:58
Uh some some uh individuals are going to be excited about that.
1:13:01
Others may be more excited about direct payments.
1:13:02
But what are you seeing across the landscape of what's working to actually get projects uh from the sort of concept stage to uh powered shell GPUs uh you know uh actually running? >> Yeah. >> Yeah.
1:13:16
Listen, that's been a huge focus of the market and of the media recently.
1:13:22
I'm not sure I have the exact answer to that as we sit here today, but it's something we as an organization are spending a tremendous amount of time around.
1:13:30
And listen, we really need to engage all the constituents around the table to to get to a solution that you know works for AI infrastructure as well as works for uh the investors and the operators who are involved as part of that >> and and most of the time for I imagine for equipment financing deals uh the power shell is already up and running and so uh a lot of those uh concessions if they need to be made have already been made.
1:13:53
Is that is that roughly right?
1:13:55
>> Yeah, that's exactly right.
1:13:55
One of the things we like about it is when we fund into these transactions, um the compute is basically on the come within a couple weeks and so that is all that portion of the business is already up and running and we get to finance very close to where the revenues are actually happening. >> Yeah.
1:14:13
And it might also be the case that there is an existing power shell or data center and they're just upgrading to Blackwell or something like that and that's where you come in.
1:14:20
Is that is that does that happen? >> Post retrofit.
1:14:22
That's exactly >> post retrofit. Yeah, that makes sense.
1:14:24
Uh well, congratulations on the Iron Deal.
1:14:27
Thank you so much for coming on the show.
1:14:29
>> Yeah, come back on as you have more.
1:14:30
>> Yeah, we'd love to talk to you again.
1:14:32
>> Thanks for having me, guys.
1:14:33
>> Have a great rest of your day. Goodbye.
1:14:35
>> Let me tell you about Shopify.
1:14:35
Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.
1:14:45
We're going to space next. >> That's right. >> We got Phil Johnson. >> How you doing?
1:14:51
Welcome back to the show.
1:14:53
>> Good to see Hey, thanks so much for having me. Third time. >> Third time. >> Three repeat.
1:14:57
>> I mean, it's a fascinating business.
1:14:57
Uh, attracts a ton of attention.
1:14:59
Also attracting a bunch of capital.
1:15:01
What's the latest news for you?
1:15:04
>> Yeah, so we just raised a series A extension $250 million at a 2.
1:15:06
3 billion uh with Nvidia investing 25 million and uh Cisco coming in and a bunch of other folks. >> Fantastic.
1:15:19
What is the use of funds right now?
1:15:21
I imagine that there's still a lot of R&D to do.
1:15:23
I'm obviously very optimistic, but uh you know I when I when I talk when we talk about space data centers generally we're usually in 2030 maybe 2028.
1:15:33
So is there a use for capital right now or is this sort of more of an opportunistic raise a fortress balance sheet and then be able to hire and really build all the key precursor pieces to the actual ongoing business? >> Yeah.
1:15:48
So I think there's a few reasons to to do the raise now.
1:15:50
Um one is to secure launch.
1:15:52
So booking launch fe for 2028 2029 and that's obviously quite expensive.
1:15:57
Um another is when we work with I mean um we're doing some pilots with uh you know some of the large data center companies.
1:16:05
We'll announce that soon.
1:16:06
Um but they want to see a few hundred million on the balance sheet before they'll you know commit their resources to the project.
1:16:11
Um so that's another one.
1:16:14
And then the last one is actually moving into much larger manufacturing facilities and starting to ramp up the team, things like that.
1:16:20
>> Yeah, that makes sense.
1:16:20
What is the state of the uh the experiments?
1:16:22
I mean, I know that you I believe you put a GPU in space, but there's other there's other sort of test runs that you're doing.
1:16:31
walk me through the the thesis there, what you hope to get out of those uh those tests, what you expect to learn, and then also I imagine that it's also just sort of marketing for the company like awareness during a time when you're not putting up tons and tons of compute just yet. >> Yeah. Yeah.
1:16:47
So, yeah, as mentioned, we launched the StarCloud one satellite in November last year.
1:16:51
>> Um so, that had the first Nvidia H100 on board. It's still going strong.
1:16:53
We're doing a whole bunch of tests on that really.
1:16:56
Um we managed to yeah we're doing the more the more useful workloads we're doing now are pipe out inference on other satellite imagery particularly SAR data for various military and government applications. >> Sure.
1:17:06
>> Um but yeah we've got three launches booked for next year.
1:17:09
So we'll have two going up in Q1 next year.
1:17:10
Um one towards the end of next year and we're actually just booking on every like every launch provider possible now.
1:17:17
So yeah, we should have some Well, I'm not sure if we've if we've announced that yet, but we'll announce a few um other launches that we've booked soon. >> Yeah.
1:17:27
Is is that is that you know, from a you know, I guess forwardlooking standpoint, is that going to be important to be diversified from a from a launch partner standpoint?
1:17:35
Because I can imagine when you need to raise the billion dollars, people are going to be sitting there being like, hey, like you're dependent on SpaceX and they're also in this business and maybe that's a concern over time.
1:17:46
I'm sure right now Elon is just happy for there to be more compute in space and have other parties, you know, proving out this thesis, but um is that is that important? >> Yeah. Yeah.
1:17:59
Um yeah, so to start your second point, I mean, right now, yeah, we do have a great relationship with SpaceX.
1:18:04
We've, you know, signed a contract for the next 25 of our satellites to have their um laser terminals on.
1:18:10
So, we'll also be using them for connectivity and we've got a whole bunch of launches booked.
1:18:13
Um but yeah, I mean I think it's good for the industry in general for for there to be lots of um optionality in the launch market and so yeah, we're we're keen to encourage you to be a diverse launch ecosystem.
1:18:28
>> Uh who what what does it actually take to lock in uh a launch in 28 28 and 29?
1:18:36
Are you having to put up uh a non-refundable deposit?
1:18:38
What what percentage of the of the total cost are you having to actually put up? Yeah.
1:18:42
Uh, for most launch providers, it's sort of 10 to 20% um, down payment refundable if the launch doesn't happen.
1:18:52
>> Although with the more experimental rockets, if the launch doesn't happen, they probably have larger balance sheet problems than be paying us.
1:18:56
So, >> it's a bit of a bit of a gamble on some of them.
1:19:02
But, um, I mean, it's the kind of it's the kind of thing we're we're keen to spur on, so we're happy to to put those deposits up. >> Very cool.
1:19:10
Well, congratulations on the new funding.
1:19:12
Great progress and we'll talk to you soon. >> Have a good one. Cheers.
1:19:16
>> Let me tell you about Figma. Agents meet the canvas.
1:19:18
Your AI agents can now create and modify your Figma files with design system context.
1:19:23
Up next, we have Jimmy Ivine in person. >> Nice to see you.
1:19:27
>> He is the co-founder in Scope Records. >> How you doing, man?
1:19:30
>> We're doing fantastically. How are you? >> Good. Good. Yeah.
1:19:33
>> Thank you so much for coming on down. >> Hey, it wasn't easy.
1:19:34
You're far from my house, but it's cool.
1:19:38
>> Coming in from uh >> uh Malibu. >> There we go. Oh, >> I do that drive.
1:19:42
I do that drive every day, too. >> Oh, your mouth. >> Yeah, exactly. >> Yeah. >> Wow.
1:19:47
>> Senra, me Huberman, you know, got a little uh podcast dynasty out there. >> Oh, great. Great. I'll give you my number. We're out there. Me and my family. Yeah. Yeah. Yeah. >> And Ben, too. Ben Taff. >> Really? >> Yeah. Yeah. >> Fantastic. That's great. >> We're all out there. >> That's great.
1:20:03
>> How are things going at USC?
1:20:03
Uh well you know uh we started this we started the school you know it's called IYA >> and it's really a school of innovation.
1:20:13
What happened was uh >> in 2014 we sold uh Beats headphones to uh and Beats music to Apple. >> Yeah.
1:20:24
And at Beats, we had a similar experience where we couldn't find people that could collaborate the way Dre and I wanted them to collaborate, >> you know.
1:20:35
So, we kind of got into that just we would it was very very difficult either an engineer, design, business, it just >> they couldn't speak the same language.
1:20:48
They didn't understand the why of the other person.
1:20:51
So when we went to Apple, it was that on steroids for us, you know, they're great company, the the best company, you know, but we found that at every company we went to that everything was very siloed and communication understanding was siloed.
1:21:08
>> Not some not just people, but understanding >> and um so one day I woke up and I just called Dre.
1:21:16
I said, "Dre, you know, the problems that we're having, you know, Dre and I really didn't go to school much, you know, and um I said, but I got a feeling that this is a problem in education.
1:21:28
People are learning in a siloed way."
1:21:30
You see, 19 to 25 and 26, I don't know about you guys, >> but that puts a big imprint on your life. >> Yeah.
1:21:38
>> You know, it's like >> you learn a lot in the formative years.
1:21:42
Those are really important.
1:21:42
They were very important for me. Yeah.
1:21:43
And I guess that's kind of why the age of >> and getting like varied experiences I feel is so important when I think about my era from 20 from 19 to 26. I studied economics. I learned a program. I started a business.
1:21:56
I filmed videos, did marketing.
1:21:59
I it blend it helps to blend all these things together. >> How old are you? >> I'm 37. >> Yeah.
1:22:05
So you're you are you're you're young enough >> to grow up in a really multid-disciplinary environment.
1:22:13
But importantly, like a lot of that was on my own. I just had to go work. I had to do it myself. >> That's my point.
1:22:19
So now when you come out of high school, >> they silo you. >> Yeah. Totally. >> Okay.
1:22:23
You're going to go work with 60 engineers every day.
1:22:25
You're going to go with go to Wharton, but you're going to be with 45 accountants every day. >> Yeah.
1:22:32
>> And um there's something wrong with that. >> Yeah.
1:22:34
So, you know, we uh stepped in, went to USC, and uh >> how do you map that to or match that with this idea of putting on the blinders?
1:22:44
Why does a raceh horse wear blinders? Right.
1:22:47
>> Well, um because every we live in a world now, it's worse than ever with social media.
1:22:52
Everyone cares so much about what somebody else thinks.
1:22:58
>> Oh, that's interesting.
1:22:58
>> I mean, you guys, we have people just all day.
1:23:01
What do they think of my post?
1:23:03
What do they think of my orange?
1:23:03
What do they think of my orange juice? Who cares? >> You know what I mean?
1:23:09
Would you go to a grocery store and ask everybody what they think?
1:23:12
You know, so anyway, I'm an older guy, so it doesn't make any sense to me.
1:23:17
>> But, you know, but that's the blinders.
1:23:20
The blinders are very simple. Run your own race. >> Yeah.
1:23:25
>> But enter that race with the understanding and the empathy of other disciplines.
1:23:33
Yes, >> we all have that problem in any company you have.
1:23:36
The extreme tech side and the extreme design side have trouble communicating.
1:23:43
>> Yeah, >> maybe not everyone at every company, but most people at most companies.
1:23:46
And then when you you know remember we brought 300 people from the creative business into Apple basically you know uh and uh Apple's an incredible company but it's um and it's the best of them by the way >> by the way >> but it's all somewhat siloed.
1:24:09
>> Do you think entrepreneurial people know that they're entrepreneurial for the most part?
1:24:13
And I asked that because do you find with the school there's people that maybe that that aren't applying to be a part of the program but you actually want to go and find those people or or generally are these people like self- selecting and they and they just know they want to be a part of it?
1:24:29
>> Well, they know that there aren't many schools that fit who they are, >> right?
1:24:34
>> right? And a lot we get a lot of applicants and that's because we fit we're speaking their language you know and think about this we started this in 2012 >> now a lot of schools are saying okay we offer multid-disiplinary like you know
1:24:53
they say okay you're in an engineering school but you could go take one course across the hall and say you know that's not the joke >> the the what it is is what companies want actually we did research uh at USC to find what um what type of students they want. Number one came back
1:25:12
Number one came back collaborative innovation. >> Yeah.
1:25:16
>> And that's the found you know our school is really Ivan Young Academy for innovation.
1:25:20
We put in the beginning tech design and I'll show you because we wanted to explain it. >> Yeah.
1:25:28
We wanted to make it literal like you know rock to the forehead kind of uh you know messaging.
1:25:34
So but now it's fundamentally the Ivan Young Academy of Innovation and because people can't you need to collaborate to innovate and you know look I'll give you an example.
1:25:50
People say how do you know there are problems at >> at these companies like this?
1:25:53
because I've been to a lot of them. But I have proof. Here's my proof.
1:25:57
Why is it that so few I'm going to be generous.
1:26:02
So few software companies have built successful commercial hardware consumer electronics. >> Yeah. >> Why is that?
1:26:13
>> No founders in the seats.
1:26:15
>> They >> run by committee >> because No, they can't collaborate.
1:26:18
>> They can't collaborate.
1:26:19
>> They can't collaborate. >> Yeah.
1:26:21
you know, now, you know, I mean, Meta's gotten the this this piece of hardware out there right now, but they went to I mean, looks like it looks like they went to Rayban, you know. I mean, and it's cool.
1:26:34
It'll do okay, you know, it'll do fine, whatever.
1:26:36
They're a great company, but none of these companies can make hardware, and they all have hardware envy. >> Yeah. >> All of them. Yeah.
1:26:43
you know, and um so there's a reason for that.
1:26:46
And my in my thesis and mine and Dre's thesis is that this is why >> Yeah.
1:26:54
>> because what was so great about what is so great about Apple because it's still in their DNA >> is they had Steve Jobs. >> Yeah.
1:27:02
>> He was the ultimate crossdisciplinary human being.
1:27:06
That was his in his DNA where tech meets liberal arts.
1:27:11
And when I went the first time I went up there in 2003, I got it in 30 seconds because I had gone to five other companies before that and talked to them about piracy and all that stuff.
1:27:24
I was on a a kick about that, you know.
1:27:27
And I was the the minute at hello I met him in ADQ.
1:27:33
I said, "Okay, this is where the party is, you know, and I just went back.
1:27:38
I told the people at Doug Morris at Universal who was in charge of the place.
1:27:42
I said, "Licence this guy." >> Yeah.
1:27:45
>> Because they they know a lot more about this than anybody in our business and they have feel. Okay.
1:27:49
So this this school is truly designed behind that meeting. Mhm.
1:27:58
>> I know it sounds simple, but look, we had an idea.
1:28:00
I woke up one day and I called Dre.
1:28:03
I said, "Dre, what about what about starting a school like this?" >> Hell yeah.
1:28:07
You know that, by the way, he really talks like that.
1:28:09
So, we wrote a check for $70 million in a month. >> It's crazy.
1:28:16
>> Just on one line, knowing nothing about education >> and we built what I consider a fabulous school. >> Yeah.
1:28:22
Do you think that there is a there's a trap to be avoided with the school around students becoming tracked like they've done the inter disciplinary work and they see this as the best way to get a job at Apple or the best way to get a job at a startup and in fact they should be sort of laying back and watching opportunity come to them during this period.
1:28:44
>> Well, first of all, they're 22 years old.
1:28:46
They can go get a job at Apple and still go change the world. >> That's true.
1:28:50
>> You know, Steve Steve Jobs had a job. Yeah. >> For Apple, right?
1:28:53
So, you know, nothing wrong with getting experience.
1:28:56
Uh I I think it's actually good. >> Yeah.
1:29:00
>> But it's more important.
1:29:00
I mean, look, even the engineering degree, you could see, is trying to expand. They get it. You know what I mean? Yeah.
1:29:10
>> You can't just >> It's really not a good environment to work where people just don't understand each other fundamentally. It's it's empathy.
1:29:19
empathy. Do you think that as technology grows and technology progresses that is creating like a natural widening force because it used to be the the instrument was technology but it was understandable by an artist and now the technology might be seven layers deep in some AI thing that's so abstract and so obscure that that creates >> look in 2012 I couldn't spell AI you
1:29:48
know So I had no idea but it's we built a school that's perfect for it you know >> and um because it's what it makes so much common sense >> inside these companies if you understand the why of the other discipline >> otherwise you're walking it's a crash >> you know and u that's why Apple can still make great software and great hardware >> that that DNA is in those people. It's It's in Tim Cook.
1:30:19
It's in Eddie Q, you know, >> and now I don't know this fellow, John, but I'm sure he was brought up in the same school. >> Yeah.
1:30:27
No, he's been there a long time.
1:30:28
>> But that's a question that should be >> Yeah.
1:30:31
>> asked and will probably never be answered.
1:30:33
But why do software companies fail when they go to make hardware? >> Yeah, it's tricky.
1:30:39
A lot of them have tried.
1:30:40
A lot of them have tried. >> Are you kidding? >> Yeah. Yes.
1:30:43
>> Basically, all of them.
1:30:43
>> But there has to be a reason, right? Yeah.
1:30:45
>> So, my reason is better than anybody else's.
1:30:47
Maybe somebody else come up with a better idea, but my reason is very convenient for my school. >> Yeah. >> So >> that's good.
1:30:53
Uh do you think do you think more entrepreneurs should go back to the to the university that that they graduated from and teach a course like something that's uh uh there's so many lessons that I didn't learn in school and I I I won't claim to be an expert on on many things but if I even had to put together like 90 minutes I feel like I could >> uh save my younger self a lot of time and it's maybe >> I think they should everyone should give back.
1:31:20
I mean I think a lot of people do.
1:31:22
I see it at USC all the time.
1:31:22
I mean, they have um they have alumni giving hundreds of millions of dollars to these schools, you know.
1:31:29
Uh and I show I'm sure they go back and talk at them and everything.
1:31:32
I spend a lot of time at the school.
1:31:34
I try to uh be very involved, you know. Uh I do.
1:31:39
>> Do you think you would have dropped out of your own school?
1:31:40
Like the younger version of your >> You know, uh here's the thing.
1:31:44
uh if they was I'd have to go for a lot of therapy on dealing with dyslexia first. >> Sure.
1:31:52
>> You know, I had a lot of trouble reading uh and paying attention.
1:31:55
So, I don't know what they call that as a there's a names for them, you know, but uh >> I don't know, maybe if there was a lot of Prozac back then, maybe I could have focused.
1:32:05
But no, I got into I I I just what I got into is I got into I loved music, right?
1:32:12
So I got into music and engineering which is sort of technology side right.
1:32:18
So I started as a recording engineer. >> Yeah.
1:32:21
>> So you have to understand the basic pre principles of technology in order to run a console and yeah >> you know fix microphones and do whatever you have to do you know. So I got lucky.
1:32:32
I didn't know what I didn't know I was doing that then.
1:32:33
But um >> you know I don't know that not everybody can do that.
1:32:38
So school is a great thing, but only if you're in an environment that's going to enhance your creativity and who you are, not take one part of it and put it in a box. >> Yeah.
1:32:51
The funny thing for me is I it took me until I was an adult to realize that I was creative because I remember my like pretty formative experience was was in early early school when I'd be in an art class and I'd be told draw this or do that or whatever.
1:33:07
I just was not good at drawing.
1:33:09
I never was good at drawing.
1:33:11
And in my head, like creativity and art was all about drawing, right?
1:33:15
Because that was my first time like doing anything creative in a school setting.
1:33:18
So I then I went like almost probably 15 years thinking I'm not creative, right?
1:33:22
And so it took me to being an adult to realize that creativity can have all these other forms, right?
1:33:28
It's not just like can you draw a pretty picture, right? Right.
1:33:31
Well, you could also you could learn you could learn creativity. You could learn taste.
1:33:36
You could learn all those things. It's somewhere in you. But you could learn it. >> Cool. >> Absolutely.
1:33:41
I had no taste when I walked into the record plant in John Lennon studio in 1973. I had zero taste.
1:33:46
I went from three albums with him, two albums with Springsteen, and one album with Patty Smith, and I left with taste. you.
1:33:58
But but I often find that a lot of people have great taste, but they don't have the ability to create things that meet their taste level.
1:34:07
>> Like taste can taste can be inherent in some people.
1:34:12
>> You know, what you do then is you have an eye for people that do have the gift.
1:34:18
>> And you surround yourself with them.
1:34:20
>> You know, I learned that at 19 years old.
1:34:23
I I came from I was living in my mother's house in Brooklyn in Red Hook, Brooklyn.
1:34:26
My father was a lawn shoreman and I met John Lennon and Bruce Springsteen.
1:34:31
I did those records and I got an apartment.
1:34:33
I said, "Okay, I meet people like this.
1:34:37
My life is going to be okay.
1:34:39
I just got to make sure that I don't get thrown out of the room." >> Yeah.
1:34:43
>> So, when you're running a company, leave your ego out of it and realize somebody does something better than you.
1:34:52
And don't defend anything.
1:34:52
Don't defend your ignorance, you know, just go for it and just say, "Okay, this person is great.
1:34:58
I'm gonna >> be of service to this person." >> Yeah.
1:35:03
>> Even if they work for you. >> Yeah.
1:35:05
>> To get them loyal to your company and loyal to you.
1:35:07
And um you know, that's what I always do.
1:35:12
I just I got a pretty good eye for seeing who's gifted and I make try to make their life as great as possible. >> Yeah.
1:35:22
Yeah, that that resonates on a smaller scale where I I knew I would I'm not great at I'm not great at design.
1:35:28
I'm not great at, you know, drawing out a logo, for example, but I can find people that can make great logos and and I realize I could uh at least work with >> headphones.
1:35:37
>> Yeah, >> I Yeah, we we come out of music, me and Dre, so people used to go, "Well, of course you guys are in the recording studio.
1:35:43
Of course you knew how to make headphones." Are you kidding me?
1:35:47
>> Where would you >> If you gave if you gave Bruce Springsteen two pieces of wood, >> he's not coming out with a guitar. >> No way. >> Okay. Or Keith Richard. >> Yeah.
1:35:56
>> So, we had to go and learn.
1:35:56
What we did was we found people that really were good at this >> and bring them in and and we just added the idea of what was wrong.
1:36:06
What was wrong is that everyone was listening to music, an entire generation, including yours and yours, on those little free earbuds that Apple would give out. >> That's right.
1:36:19
>> So Dre said to me, "Man, that's I spend all day in the studio and my kids are listening on these ridiculous things." So we said, "Okay."
1:36:27
So then we decide we're going to make a headphone.
1:36:30
Then everyone tells us you can't a great headphone.
1:36:35
they'd be like $300 at retail.
1:36:37
They said, "Well, that's not going to work because Apple gives them away for free and so does Samsung."
1:36:43
>> We said, "Okay, our job is to get them on people's head."
1:36:48
>> Once they hear it, they're not going back. And that's what we did.
1:36:54
So, we brought culture and we got them on people's head to try them.
1:36:59
And that once young people started trying them, they wanted it for Christmas. >> Was that expensive?
1:37:04
I remember the story of you paying to advertise Ging, right?
1:37:11
>> That was a song that was a song. That was a song.
1:37:12
So, but but it was a contrarian move because I feel like uh pulling the trigger on a big ad spend before an artist has really broken through is risky. But how did that change?
1:37:24
>> I I don't I don't know how to spell risk either. You know what I mean?
1:37:26
I just I just I do I wake up in the morning and I do what I feel. >> Yeah.
1:37:33
>> And I do what makes sense.
1:37:33
I talk to the people that are around me and I don't care about the risk. I really don't. I never did.
1:37:39
I just do what's right for the project.
1:37:42
>> And sometimes, you know, you cut a lot of flack because, you know, when you're at a big company or something, they >> budgets and things like that, but I I I I just get myself in situations where I leave them if I can't just do what I want to do, you know? >> Sure.
1:37:57
>> I try to made a life of just doing what I want to do. >> Yeah.
1:37:59
Over the years, how how did you think about bringing in new business partners?
1:38:06
You have some early success working with some set of people.
1:38:08
You start meeting other great people.
1:38:11
In your mind, how are you deciding whether to spend time and partner with >> new people versus sticking with the band?
1:38:20
>> I'm very I'm very positive person.
1:38:20
So, I always give people the benefit of the doubt and try it, you know, and you could tell pretty quick if something's going to work or it's not. If it's not, say sorry.
1:38:31
And if it does, go in further.
1:38:33
I try a lot of things, you know.
1:38:36
I'm not It's >> I'm not precious about anything.
1:38:38
Once I figure what I'm doing, I'm precious about that. >> Yeah.
1:38:44
>> But as far as the education and learning how to get Look, we would have never done this school. >> Yeah. Yeah.
1:38:50
I mean, you know, if we were nervous about things, I mean, we knew nothing about what we were doing. >> Yeah.
1:38:57
>> And I think we have one of the best, if not the best school in this area in the country. >> Yeah.
1:39:04
>> You know, >> so that's a good thing.
1:39:08
>> There's a obviously a big technological transition in music with AI.
1:39:11
Going back maybe before streaming, what was the first technological shift you remember in the music industry? >> You mean nap Napster? You mean? >> Yeah. Yeah.
1:39:22
Before before Napster even was that >> Well, before I mean we look I go back a long time, you know, uh >> stereo. Okay.
1:39:31
>> You know, multi-track recording, you know, where do you want to start? It just >> Yeah. But what was that like?
1:39:36
Was there a discussion about it or was it something that just you know was adopted behind the scenes and the consumer of music?
1:39:45
music? always it's always the because the stuff like that it was expensive was always the professionals you know like you could hear the first time um a phaser one of the first times a phaser was used on a record and Jimmyi Hendris you know you could hear when the Beatles got stereo they walked in the studio one
1:40:03
day because I knew those guys and there was two speakers instead of one yeah you know Paul will tell you he has told people that he said okay they thought at the beginning oh twice as loud you know but >> there's more to it >> there's more to So, you know, it gone all the way to his drum machines. Drum Drum machine was big. >> Yeah.
1:40:20
>> You know, I I I was fortunate because Roger Lynn used to be a guitar player and he was playing on one of my sessions when he was creating this thing.
1:40:26
He had the computer in there with him.
1:40:28
He was creating a drum machine. >> Yeah.
1:40:32
>> So, uh I got to see that really early on, but then Prince exploded it. >> Yeah.
1:40:36
>> You know, so AI is, you know, uh it's a little different.
1:40:42
>> Do you think people thought it was a risk?
1:40:44
I mean, I know risk is not in your vocabulary, but uh for prints to adopt the drum machine. >> It was bold. >> Bold.
1:40:51
>> It was very bold because uh remember this guy >> is a great great musician that had the greatest musicians playing around him. >> Yeah.
1:41:00
>> So, he said, "I'm going to simplify.
1:41:00
I'm going to go to a drum machine." >> Yeah.
1:41:04
>> That's bold >> and brilliant.
1:41:06
And he he was one of the guys that exploded it, you know, that really took it uh went all the way. >> Yeah.
1:41:12
>> Yeah. the boldness that feels like that's an there like when you're thinking about stereo or the drum machine or synthesizers there's the an opportunity for boldness on the side of the musician >> did that same opportunity for boldness
1:41:27
exist in the streaming transition in the social media era in the AI era >> streaming okay let's go to to streaming right streaming you have to go to iTunes first >> that was very bold >> because the record industry didn't want a license it. >> Mhm. >> Mhm.
1:41:43
>> You know, musicians didn't want to sell their songs at a dollar a time, but but on the other but out the back door, they were being given away on MP3, you know, all day, right?
1:41:52
So, what Steve and Eddie had was a really good idea, an elegant way to match their iPod, >> you know, they had a piece of software that was really elegant and it worked and these guys understood the culture. Steve.
1:42:09
My first five conversations with Steve Job was about John Lennon and Bob Dylan.
1:42:14
He really cared and understood. Hey, understood.
1:42:20
Hey, you went out with Joan Bayz, right?
1:42:22
So, he understood the the culture. >> Yeah.
1:42:28
>> And he understood he had a feel for it, you know. So, that was a big step.
1:42:33
>> And then streaming was another big step.
1:42:36
Daniel Ek was a brilliant guy, you know.
1:42:38
Uh we came to the market, we had Beats Music and at Innercope and we sold to Apple and that and then we start we worked with the guys up there and and made Apple Music.
1:42:52
>> How do you think streaming changed music production or the decisions that musicians make?
1:42:58
I mean, I've heard at least anecdotal evidence that uh albums got longer or there's more songs because that gives you more shots to go viral in the algorithm.
1:43:09
There's all these caused all that with social media.
1:43:11
>> Okay, >> social media unfortunately like a thing like Tik Tok.
1:43:17
>> Uh it's it's in a lot of ways it's great because it gave artists power >> and a platform to market themselves, which is what artists want and need and should have.
1:43:27
But it also made a lot of artists and record company people chase that. >> Sure.
1:43:34
>> Whatever the latest Tik Tok thing is and that could be pretty ridiculous at times, right?
1:43:40
>> So I think that affected music more sonically and creatively >> than uh streaming did personally.
1:43:47
Maybe more songs or whatever. Yeah. Great.
1:43:50
But >> even that more songs thing came out of Soundcloud. >> Yeah.
1:43:56
and uh Tik Tok and and Instagram just putting stuff out, you know.
1:44:03
>> I was uh I was talking to a buddy uh of mine in uh in Malibu and he's produced 20 30 Billboard number ones, like really really impressive career.
1:44:14
really impressive career. and he's for decades now received people will send him demos and he he always says he likes to listen because he wants to be working with you know upand cominging talent and he said over the last year it's become harder to judge who's who's got potential and who doesn't because
1:44:34
because of AI because anybody can make a song that sounds at least decent and maybe there's a thread of a good idea in there and so he said it's just become impossible to understand um and to me that signals that it's going to become even harder to break into the music business because >> and suddenly anyone can make a song, right? Like Sunno shockingly quickly in
1:44:53
Like Sunno shockingly quickly in about takes in my experience about 10 seconds to make something.
1:44:59
Uh and there's patterns you can if you >> Where do you want to start with this?
1:45:06
You just cover a lot of ground. Okay. >> Yeah. Yeah.
1:45:08
>> Yeah. Yeah. But but I guess my my main question is like does it become these previous technology trends in music the professionals the existing professionals got access to them first they were expensive to adopt things like that now
1:45:22
with AI anybody in the entire world can get access to it and I'm wondering does that mean you're going to have a lot more people breaking into the music industry or or less just because competition is like >> well do you want to talk about the licensing of AI the actual
1:45:38
use of AI or the production of AI where do you want to where do you want to start right you know where where >> well well specifically what is it what do you think it means for emerging uh talent >> well let's use the word talent if you really have talent it'll help you it'll
1:45:57
help you create as a tool you know what I mean it's like you asked the right question stereo >> it made Sergeant Pepper better >> okay >> uh the drum machine made Prince's first album fantastic, you know, or second album, whatever that was, you know. So,
1:46:11
So, I think as a tool, it's going to be fabulous, you know.
1:46:16
Uh, a lot of these companies that are creating AI music right now are doing so on unlicensed music in mass, like 60 million tracks or something like that.
1:46:29
>> Well, those in my opinion, those are going to be like the kuzah of this moment.
1:46:35
It's got to get under control to a certain extent that there should be I mean in this particular case there there's going to be some kind of government regulations or there should be something right uh >> for proper licensing if you use these three influences in the creation of this AI song.
1:46:52
Those three artists get compensated. >> That's right.
1:46:54
The prompts the prompts should get paid. Yes. Right. Yeah.
1:46:56
So, but there's a lot of cowboys and they're gonna run around doing this stuff, you know, but that's not I don't think that's where the it's going to shine, you know, like can people make songs, you know, easier, lower.
1:47:10
Can somebody who was Instagram influencer go out and make a song because they know how to dance and jump around and get people's attention? Possibly. But there's crap now.
1:47:21
There'll be crap then, there'll be crap now.
1:47:24
Maybe the crap will get more interesting. Who knows?
1:47:26
But as far as the great artists, you know, Kendrick Lamar, Alicia, Olivia Dean, um, you know, some great people that are Semat, some of these young artists that are just fant, you know, St.
1:47:38
Harrison, some of these great great that kid saying Harrison, there ain't no AI that can sing like that kid, you know.
1:47:45
So something like that, you know, is um you know, not not they're going to be there because you what AI can't do is grow up in a terrible home.
1:48:01
>> AI can't have a broken heart. >> Yeah.
1:48:04
>> You know, so you know, AI is not going to be Dolly Parton.
1:48:08
>> Art has always been about stories.
1:48:08
You look at a modern art museum and there's the constant refrain, my kid could have drawn that, but you didn't.
1:48:14
and there's not provenence and there's not a journey and a story.
1:48:20
>> I don't I'm not afraid of AI and I met a lot of the people that are working on it and none of them truly scare me, you know, it's just >> or should scare anyone for that matter.
1:48:29
And um you know, so I think it's a tool.
1:48:32
I think Dre said last week on some interview that it's a tool and that's what it is.
1:48:36
But the the licensing, the artist that it's learning off of, the way this product is.
1:48:41
Look, when the Beatles came out, they were influenced by Rich by Little Richard. Yeah.
1:48:46
>> And um and Buddy Holly, right? >> Yeah.
1:48:50
>> They didn't get paid, but now if you're influenced by the Beatles and um and Dr.
1:48:55
Dre, they will get paid if the live and I got to tell you this.
1:48:58
I you everyone's always tough on the labels, but I think I'm watching the labels closely and I talked to the guys that are running it quite a bit because I've known them all for years. >> Yeah.
1:49:10
>> I think they're handling this problem right in the beginning because >> they have to the the the things that are out there just randomly licensing, not licensing, ignoring it. Yeah.
1:49:21
>> And thinking that they're gonna I think that's I I don't think that works.
1:49:26
>> It most certainly doesn't.
1:49:26
I grew up I grew up for the first 18 years of my life relying on musical artists. >> Yeah.
1:49:34
>> They changed my life and a lot of people's around me's life.
1:49:35
So that music deserves to be paid. >> Yep.
1:49:42
>> You don't just come in and think I don't believe I don't believe that.
1:49:44
So I but I'm an older guy.
1:49:46
I I uh you know I've been around a long time so some things are good about that.
1:49:50
Some things get a little stale. >> Yeah.
1:49:52
But I believe that how the labels are handling those particular cases is the right way. >> Yeah. Yeah.
1:50:00
I mean, the technology should be able to help here.
1:50:01
Of course, there needs to be legal precedent.
1:50:03
But, uh, I mean, if you look at the way YouTube's handled it, if I upload a video with a Dr.
1:50:08
Dre song on it, that's that that the any money that I earn from that's going to route.
1:50:12
But in the beginning, it wasn't. >> Yes. Yes, it wasn't.
1:50:14
But pretty but pretty quickly.
1:50:16
And why they sold to Google was they had to pay out a bunch of money.
1:50:19
>> Well, because that's going to happen here, too. >> Exactly.
1:50:21
You know, but but >> the money will flow though.
1:50:24
>> But what but the chain reaction that this causes unfortunately >> is the l the people that are giving out licenses shrink, meaning they shrink what they're going to they they lessen what they're going to do and it's going to cause a lot of this product everybody's excited about to really be dumbed down. >> Oh yeah. Yeah. Let me see. >> All right.
1:50:44
So, you know, the couple of companies have gotten licensed. I guarantee you.
1:50:48
I don't know, but I guarantee you in my opinion that those um that product would be dumbed down. >> Yeah.
1:50:58
>> You know, so where the thing will shine is when you get producers that learn >> how to do this. >> Yeah.
1:51:05
>> You know, when when stereo first came out in Extreme, there were records a Beatle record where the drums were on the right and the vocal was on the left. >> All right.
1:51:15
But then people learn how to >> blend things together.
1:51:17
So, a lot of producers are using AI right now and it's really helping them. Sure.
1:51:23
>> I mean, they what they do is they they even copy the AI, you know, the the idea.
1:51:28
What's going to break it'll break a log.
1:51:29
It breaks a log jam in your head.
1:51:34
>> Is that the best way that you see artists using AI as uh essentially previsisualization like what would happen? >> That's what I see.
1:51:41
the guys that I know, you know, the producers that I know, I talk to them, you know, and >> I I I keep in touch with a lot of producers because I was a producer and I relate in the record business.
1:51:50
I'm I really relate to record producers and their journey and stuff, you know.
1:51:56
>> So, and when I was at Innercope, it was driven by record producers, you know, Swiss Beats, Farel, Dre, Timberland, you know, uh, Will I Am, uh, Polo to Don, all these guys were at Innercope at one time or another.
1:52:09
I hope I didn't leave anybody out. I'm sure I didn't. I'm sorry.
1:52:12
But um you know they they are learning how to use this.
1:52:17
They it will come from them. >> Mhm.
1:52:21
>> And yeah, they'll be look there there are artists out now that can barely sing happy birthday. >> Okay. >> Okay.
1:52:30
So So what's if you can barely sing happy birthday if you can't sing happy birthday at all. Right.
1:52:35
So that there will always be boring, silly, you know, >> yeah, >> records like that, right?
1:52:42
But the great artists and the great producers will maybe >> create real masterpieces, you know, because of this, it'll spark something. So I'm very pro AI.
1:52:54
I just think that >> in the beginning there's always >> the wild west in anything like this.
1:53:00
>> the wild west in anything like this. you just got you've seen it enough you just go okay it'll but I I I the guys that are running the labels are really trying to do the right thing here and uh I think in this particular case the artist and the labels are aligned >> yeah that's a good point
1:53:17
>> yeah what do you think so so knowing some of these entrepreneurs that are building in the space they would push back and say the and with within streaming if somebody was illegally streaming or pirating a song they are taking a product that a that an artist and a label produced and they're just consuming that product without without paying. That is objectively wrong. Uh in
1:53:37
That is objectively wrong.
1:53:37
Uh in this situation, they are training on a bunch of music to create something entirely new off of that.
1:53:47
And they would argue that >> that's fair use.
1:53:52
>> They would argue they would argue that that's fair use in the way that like you said the Beatles, you know, had their own inspiration. >> I know.
1:53:58
But that that's that's the argument, right?
1:53:59
Is it fair use or isn't it fair use?
1:54:01
The artist and the labels think it's not fair use and somebody who's making a lot of money on a new company thinks it is fair use. Right.
1:54:09
>> But but here's convenient arguments. >> Yeah. Yeah.
1:54:12
And you know the these companies are making money providing a tool.
1:54:18
And I'm not I I'm actually not taking aside one way or another, but they're making an AR they make money from selling a tool that lets you create music.
1:54:27
And but the the what's also happening is people are creating that music and then they're going back to the labels and they're going back to artists and they're making new music that then gets listened to and monetized the the normal way.
1:54:42
So I would ar I would argue in some ways that the music industry and artists are yes they their their music is being used to train models that that then create other music but they are also beneficiaries of that.
1:54:55
Yeah, but there are some people that are dead. >> Sure. >> Yeah.
1:55:00
>> So, you know, Wilson Picket is not going to go out and make a new record.
1:55:02
So, if you're learning on Wilson Picket, I believe that his estate should make money.
1:55:08
I believe that if you're learning on, you know, uh some some somebody who's around today, you George, not George Harrison, uh you know, like u um any of the artists that are around today where you're learning from their music, they should get the prompts should get uh paid. Yeah.
1:55:26
>> It's going to be hard to monitor, hard to police, and all that stuff, but but they'll figure that out, you know.
1:55:29
I just don't think that it's I don't think it's fair use. I don't think it's free. >> Yeah.
1:55:35
You know, I just don't that's >> you saw this with the social media addiction trials.
1:55:38
Like big settlements can come decades down the road and be basically benchmarked to revenue and uh and the money can flow, but it takes a long time to go through the court system.
1:55:49
That's just the way things >> you know.
1:55:51
So what but it has to be done right and uh it's a wonderful technology for music. It's fantastic.
1:56:00
>> Um but >> you know there's got to be deals made.
1:56:04
Yeah, of course, of course. Yeah, always.
1:56:05
Uh, what do you think about the future of live performances in the age of AI?
1:56:10
It feels like it could be a really important proof of humanity, proof of talent. I went to the show.
1:56:18
Sure, maybe there was some autotune in the loop, but I watched them perform.
1:56:22
And if they can perform to a certain level, that gives me more confidence in the rest of their library.
1:56:27
>> Well, I happen to be uh fortunate.
1:56:27
I have a really good friend in that business named Michael Rapino.
1:56:31
He's he's the he's the CEO of Live Nation.
1:56:32
I I learn a lot about the live business from him.
1:56:37
Plus, I grew up my friends playing live all the time, you know.
1:56:40
>> So, >> I I think live is live, you know.
1:56:42
Do do you want to see somebody performing live spilling their guts on the stage or do you want to see um um a hologram or something, you know? I don't know.
1:56:53
I'd rather see the person live because they just more exciting. So, I don't know.
1:56:57
I don't think there's any problem with I don't think there's I don't think it crosses. I just don't see it.
1:57:02
You know, I don't see it. I don't know the future. I have no idea.
1:57:05
I'm not going to be here anyway.
1:57:07
So, uh but but it's um you know, I don't know. I have no idea.
1:57:13
>> I would just expect it to to to grow. I don't know.
1:57:16
It feels like the the era tour was such a moment.
1:57:18
Uh and there's these certain moments that happen in American culture where shelling points, everyone comes together around a certain thing.
1:57:26
>> Look, you know, it to me it's simple.
1:57:28
Yeah, >> you got a new technology.
1:57:31
>> It's going to be great.
1:57:31
It is great and it's going to be even better.
1:57:32
People are going to use it, but there's going to be licenses and there's going to be have to people get paid for it.
1:57:39
>> And then the great talent and the great artists are going to show the world how to use it. >> Yeah.
1:57:45
>> It's that simple to me.
1:57:47
>> It happens every time. Yeah.
1:57:47
You know, so I'm not I I I it all comes down to what we talked about first, which is which is what's great about this is it's teaching young people.
1:57:59
That's where multid-disciplinary behavior comes in.
1:58:03
This is technology, >> and you're creative, >> right?
1:58:07
So when you really understand technology and you really understand the creative, >> you're going to really do well. >> Yeah.
1:58:15
So, but you so you shouldn't be siloed in school. >> Yeah.
1:58:20
>> You shouldn't go to a school where all you do is play the guitar all day. You know what I mean?
1:58:23
It just to me that doesn't work.
1:58:25
It uh I mean Giuliard's a nice place and I'm glad it exists, but or Berkeley, whatever, you know, but it's not >> it's not where I see the world going.
1:58:35
And not if anybody cares, but me personally, I'm on this show, at least you two guys care.
1:58:39
So, >> do you think AI can help bridge that original gap that we were talking about?
1:58:45
When I think about uh what it takes for a creative person to build a hardware product, for example, there's a lot of technical hurdles that can now be broken down.
1:58:57
>> Before there were things to break it down. Let's put it this way.
1:58:58
Dre and I had a record company. Okay?
1:59:03
>> We're creative people.
1:59:03
We're both record producers.
1:59:04
We built the biggest headphone company in the world. That's hardware. Okay? Yeah.
1:59:09
>> And the reason why it's hard because it's goddamn hard. Okay.
1:59:11
That's why not not everybody does it. So, we did it, >> right?
1:59:15
We're creative guys that built a piece of hardware.
1:59:17
That's why we started the school. >> Yeah.
1:59:20
>> It it's all needs to be >> working together. >> Yeah.
1:59:25
>> You know, and um we we built the number one Beats was the number one headphone in 50 countries when we sold to Apple. >> Yeah.
1:59:33
So we did it >> and um because we live in a multid-disciplinary world.
1:59:41
We were both recording engineers, me and Dre. >> Yeah.
1:59:45
>> And so we come from the nonwall background.
1:59:49
>> You know, and um so that's why we built the school. >> Yeah. >> It's that's it.
1:59:55
And you know, it's uh but when I go when you go look at these these most companies right now technology design engineering design. >> Yep.
2:00:11
>> There there there's a lack of communication and a lack of understanding.
2:00:13
Again, I asked the question again in case somebody just tuned in.
2:00:16
Why >> why cons software companies not build really successful consumer products?
2:00:25
>> Yeah, it there has to be an I don't have the answer, but you guys are really smart.
2:00:29
You talk to everybody in the world. I don't know why. >> Yeah, it's tough.
2:00:34
>> Yeah, >> you know, but there has to be something at the core of what's going on that challenges that.
2:00:39
I mean, no one can say, "No, he's wrong." No, I'm right. >> No, you're >> Yeah.
2:00:44
Well, you know, one of the things you brought up you brought up meta you brought up meta.
2:00:48
One of one of the I think one of the reasons that's been successful is they didn't try to reinvent too many things.
2:00:52
They just made a goodlook pair of glasses that also had a camera in it and that was enough. That's been enough.
2:00:58
>> Well, they sold 2 million.
2:00:58
They didn't sell 20 million.
2:01:00
We sold two million headphones in Brooklyn.
2:01:02
You know, it's not a really it's not a massively successful >> acquired Oculus to get the to get.
2:01:10
>> By the way, in fairness, >> I have a pair and I enjoy using it. It's fun.
2:01:16
>> But that does not a story make yet.
2:01:19
>> Yeah, >> they make Now I know who they hired to the head of the hardware division and he's really good.
2:01:24
So, but are there people at that company that can really communicate and and empower him and that type of stuff? I don't know, right? I don't know. Meta is a great company.
2:01:37
Mark Zuckerberg is brilliant. >> Yeah.
2:01:39
>> But do I know >> about that? I don't know.
2:01:41
They did they've done a good job at getting that product out. >> Yeah.
2:01:46
do is is uh I feel like one of the big the big lessons that uh people in the school should should hopefully should hopefully be imprinted on their minds is that you can be wildly successful in business without creating anything that's exactly new, right?
2:02:05
Like you you guys didn't create you created desire and you created an amazing product, but you didn't create the headphone.
2:02:11
And I think that when a lot of people think about entrepreneurship and creativity and business, they think, I need to come up with some totally novel idea, right?
2:02:23
>> Well, it starts out by >> I don't think I'm Steve Jobs. >> Okay.
2:02:28
>> But even Steve didn't he didn't create the he didn't create the phone.
2:02:30
>> No, but he he had a much bolder attitude towards life than I did.
2:02:33
He's much smarter than I am. Right.
2:02:35
Somebody asked me, "What's the difference between you and Steve?"
2:02:37
Jolly very simply smarter than me when we were hanging out together. Right.
2:02:40
So, um, but no, you don't have to invent something new.
2:02:45
I mean, headphones weren't new, but the attitude of headphone was new.
2:02:50
>> Bose was out there saying, "Buy my headphone for $300, >> and we're going to help you sleep."
2:02:57
>> We were like, "This is taking candy from a baby, >> right?
2:03:01
>> We are not going to help you sleep." >> Yeah.
2:03:04
>> You know, we are going to rock your head.
2:03:05
>> The ads were silence, not music. The opposite of music. >> Exactly.
2:03:08
So, we had a real edge there. Yeah.
2:03:11
>> And they all look like medical equipment.
2:03:13
>> So your job as an entrepreneur is to find that hole in the market, right? >> Where's there a hole?
2:03:18
We knew there was a hole there because Dre, first of all, most computers had their speakers facing the table. >> Yeah.
2:03:26
>> So that was like, okay, great. Let's face them up.
2:03:30
>> You know, we're geniuses.
2:03:30
Let's get, you know, right.
2:03:32
So, >> no, there's so there's so many times in in when you're looking at different categories, specifically with I I find it with consumer products where you're like, is there like a law that says that it has to be done this way?
2:03:46
>> Uh, and often times you do a little bit of research and you realize >> going back to the to understanding each other, >> right?
2:03:56
>> Computers like I went to a couple of computer companies, not Apple, right?
2:03:59
And I witnessed this firsthand to where engineering audio the audio budget in a speed in a computer at the time was 50 cents. >> Wow. >> Okay.
2:04:12
>> It's nothing, >> right?
2:04:13
So, you want to know why?
2:04:13
And music was being played through it. >> Yeah. >> Yeah. >> Guess what? That's not enough. >> Yeah.
2:04:19
>> You know, so but that's where the breakdown is. >> Yeah.
2:04:24
>> Because design and engineering clash. >> Yeah.
2:04:28
>> And that's where I keep saying it over and over again, but it's true.
2:04:31
That's where our school >> Yeah.
2:04:35
>> comes in to help training people that are going to that are going to become the new engineers and the new designers and the new entrepreneurs to understand the why of each other's discipline.
2:04:43
You know, it sounds like kumbaya, but it's not. >> You know, it's real. >> Yeah.
2:04:49
Was there anything else you looked at in terms of product ideas, business ideas before settling on headphones, or was it >> Yeah.
2:04:57
Well, well, it came out of a real frustration of the record business because the record business again the record business at a time was really cool and you know, music was the right thing to do and all that, but when when I met Steve and those guys, cool had moved to technology and I felt it, >> you know, I I felt the shift and I said, "Okay, the first guy that was really cool with technology was Marita from Sony.
2:05:27
the original founder of Sony.
2:05:27
He had the Walkman, you know, he really got it.
2:05:33
Oga, who replaced him, really got it.
2:05:35
They he bought Columbia Pictures and Columbia Records. >> That's right. >> Right.
2:05:39
>> And then they kind of screwed it up because they got that gave Ste that gave Apple the opening. >> Sure. >> To go take that idea. >> Yeah.
2:05:47
>> Which Steve has said many times publicly.
2:05:49
And um so when I saw that I said we have to learn a new trick.
2:05:55
We have to move l I believe companies need to move laterally. >> I do.
2:06:02
I felt the in I felt record companies especially needed to move laterally.
2:06:07
That's why we created Beats and Beats music inside of Innercope.
2:06:12
>> We did it at the company. Mhm.
2:06:15
>> So we built a company in beast that was bigger than Innercope in six years, right?
2:06:19
So obviously tech and design and creativity all belongs in the same box.
2:06:26
It's all just moving your company later.
2:06:28
Like we have a company called complex right now.
2:06:33
>> Uh and what we're trying to do there, we brought back Mark Ekko. We have Aaron Leavant. My son Jamie's there.
2:06:37
And we're trying we have a really a lot of really good people and we're trying to mix disciplines in it and we are creating an AI product alongside of it that will blend all these things together and um not all of them but the things that we have together because we're firm believers in that you you know the record industry needs to move laterally.
2:07:03
They need to own the enterprise of AI, not just license to everyone.
2:07:08
That's, you know, >> Oh, yeah. Interesting.
2:07:11
>> They should own the enterprise. Why not?
2:07:13
You know, there's no reason why not.
2:07:15
Instead of licensing to everyone. >> Yeah.
2:07:18
>> Own the enterprise yourself. >> Yeah. >> Right. We own Beats. >> Yeah.
2:07:23
Why is there so much historical sort of disagregation in the music industry?
2:07:29
like the the actual relationship between the artist and the end consumer.
2:07:32
It's always been intermediated and it feels like that's been a problem.
2:07:36
>> It's insane and it's ridiculous. Okay.
2:07:39
All artists want is to be able to communicate with their audience. >> Yeah.
2:07:42
>> And ask me why Spotify and Apple Music don't have social. >> Yeah.
2:07:51
>> Uh I know why Apple Music doesn't and I don't know why Spotify doesn't.
2:07:55
But that's why I said on an interview once recently that streaming is is minutes away from being obsolete.
2:08:02
What I meant by that is unless they adapt to what artists really want, >> the artists are very resourceful.
2:08:12
>> Right now they got to go to Instagram, Tik Tok, you know, it's like it's like a silly game.
2:08:16
>> And um >> that has to be fixed.
2:08:18
That has to be fixed quickly because and the labels who have all this historic music need to be in the loop.
2:08:29
They whether they like it or not, they are a tech company >> and they have to adjust to that.
2:08:36
And if they don't, I believe it's not going to be great for them. >> Yeah. Yeah.
2:08:43
The the the Spotify story is interesting.
2:08:47
I mean Sean Parker obviously in involved in both Facebook and Spotify and so I think they had this like delicate truce because if you remember in the early days of Spotify everything you'd listen to would be shared on Facebook and that was a huge growth driver for >> but that's not why Spotify is not social.
2:09:03
I don't believe that that's why Apple's not social musicals they don't we look when we were there we wanted to buy musically. Oh yeah, >> you know.
2:09:14
>> Yeah, we we we we brought those guys up there twice, but Apple doesn't do social and they shouldn't do social.
2:09:18
I get why they shouldn't. I was on the tail.
2:09:23
>> I was on the tail wagging the dog. You know what I mean? >> Yeah. >> Um I was on the tail.
2:09:27
So, you know, I understand why I didn't do it. >> Yeah.
2:09:32
>> But we Trent Resnner and I instinctively knew >> especially Trent that we needed social. >> Yeah.
2:09:40
And it's going to be limited without that. Yeah.
2:09:44
So, you know, look, Apple, I so far out of all the companies I found, they they're still the most interesting, you know, because they still have that DNA in them.
2:09:56
They just said, "We're not going to we don't do social." Fine. >> They don't.
2:10:01
So, that was not a good fit, you know.
2:10:04
So, but that's cool, but doesn't mean that music doesn't need it.
2:10:09
Right now, you're not giving the artists what they want. >> Yeah.
2:10:12
>> And the pay structure in streaming is all screwed up. >> Mhm.
2:10:16
>> So, if you're m I see you're married, you got a ring on your fingers or maybe you have kids.
2:10:20
If you have two or three kids, you have the family plan. >> Oh, yeah.
2:10:24
>> If you listen to What's your favorite music?
2:10:28
>> Uh, my favorite artist is Yeet. >> Yeets. >> Yeah. >> Oh, great. Okay.
2:10:33
So, you listen to that and your kids listen to >> Elmo >> or their babies. Okay.
2:10:39
Well, let's say they listen to Taylor Swift and Kendrick Lamar and you listen to Fleetwood Mack and >> Yeah. Yeah. >> and Madonna, right?
2:10:49
>> I'm paying, but the kids are listening disproportionately. >> Yes.
2:10:51
They lean on the button all day.
2:10:54
>> So, guess who gets paid? You pay the bill. >> Gets paid. >> Crazy.
2:10:58
>> But Fleetwood Mac doesn't get any. >> Elmo's raking it in. >> Yeah. Exactly. Oh, seriously. >> Exactly. But that's that.
2:11:02
So the structure so streaming is flawed. Yeah. >> And not complete.
2:11:07
But >> Daniel's brilliant. Alex is really talented. Those guys at Spotify.
2:11:12
So they're going to figure a lot out.
2:11:15
They may be thinking a whole other paradigm that I don't even understand. Right.
2:11:20
>> So, but >> someone who helped >> bring a streaming service to to light, I can tell you >> that they're all missing social. >> Yeah. >> Period.
2:11:31
And um that's why I have a crew of guys and girls that I work with.
2:11:38
We're looking at something right now that's really interesting.
2:11:40
Uh we're doing it with one of the one of the main companies and we have an idea that we believe is unique and good and great for the artist and great for the labels and uh that's what we're going to do.
2:11:54
Yeah, we have uh we've had some guys from Spotify on and I think that one of the interactions I was most excited about that they've been working on and working towards is making sure that the people that are listening to artists the most get access to the concert tickets, right?
2:12:11
Because an artist doesn't necessarily benefit if they >> Yeah.
2:12:13
But that's that's self-s serving, you know.
2:12:15
I mean, I get it, but the artist should be doing that. >> Sure. >> Yeah.
2:12:20
>> You again, you don't need third parties to do a lot of this stuff. You know why?
2:12:24
Why do the labels need third parties to deliver their music? I'll tell you why. They don't, >> right? >> But they do, right?
2:12:37
So that all should evolve with the artist in the front of the paradigm, you know, making the money and doing great and communicating.
2:12:46
So, um, >> it lit up very differently in in Hollywood with with Disney Plus and and Hulu. >> Well, well, hang on. No. >> Yes and no. And I'll tell you why.
2:12:59
Because when Netflix came to town Oh, yeah.
2:13:01
>> They came to town with a big checkbook.
2:13:04
And unfortunately, all these companies are public.
2:13:06
Now, this I'm going to make this official.
2:13:07
This is my opinion, okay?
2:13:10
But >> they all licensed them their music.
2:13:11
At least most of them did. Why?
2:13:13
because they got big checks and they helped make their numbers. Well, guess what? They created a monster. >> All right.
2:13:22
And now they're trying to catch up, right?
2:13:24
So, music business is the same thing.
2:13:28
>> They license their music to Spotify, Apple Music, and Amazon.
2:13:32
>> Well, Spotify is worth more than all the labels together. >> Yeah.
2:13:37
>> And guess how much IP they own? Zero.
2:13:42
somebody's podcast maybe or something, you know, maybe >> I don't know, but >> but that's but that's the point.
2:13:48
So the movie business didn't get it.
2:13:49
They they got it late, but at least they got it.
2:13:54
And I think that's going to happen in music.
2:13:55
I think the music companies >> are are going to be more involved.
2:14:02
>> And AI is the opening to do it. Mhm.
2:14:05
>> AI is the road to Now doesn't mean Spotify is not but Spotify is going to have to morph as well. >> Okay.
2:14:12
You get just no ride goes forever.
2:14:15
When I was a kid, not a kid, I'm sorry. I wasn't a kid. It was 2002.
2:14:17
I was nowhere near >> the spring chicken.
2:14:22
>> I was nowhere near a kid in 2002.
2:14:22
But when I saw piracy, I went and met with three tech companies.
2:14:27
And one of the tech companies, very high up guy at Intel >> said to me, Jimmy, this is a great I started talking about the recording studio and the people that are suffering and you know it's not the big stars, it's the kids in the studios and he said, "What a fabulous story."
2:14:42
He said, "Jimmy, but not every industry was made to last forever."
2:14:49
>> It was powerful, >> right? >> I said, "He's right.
2:14:53
>> Sorry, this music thing had a good run."
2:14:55
>> And the rest of my but it's not music.
2:14:58
It's the business of music and what that looks like, right?
2:15:01
>> So, >> I I carried that with me. >> Yeah.
2:15:04
>> And then when I met Steve and Eddie after that, I said, "Holy these guys, >> they're the next step." Right.
2:15:09
So, there is a next step now.
2:15:11
And and Spotify may grab it.
2:15:15
>> You know, they have all the tools available and the money, the capital, and everything.
2:15:19
>> So, they could recreate their business >> all the time.
2:15:22
And you got a guy like Alex running it who's really, really talented.
2:15:26
The people at Apple are really talented.
2:15:27
You got Oliver and that team over there. They're all really good.
2:15:29
So maybe they'll morph the company into something that it needs to be.
2:15:34
Or maybe the labels will figure it out and they'll do more of what this new model needs to be.
2:15:43
>> But to have to be just a lens sore of music to me first of all is boring.
2:15:51
>> Second of all has nothing to do with any other discipline in the world. It doesn't. >> Yeah.
2:15:58
>> And it and you need to to have a proper company today.
2:16:01
You have to have blend of disciplines inside your company.
2:16:08
>> Proven by two great great people.
2:16:08
Marita from Sony and Steve Jobs at Apple. Yeah. >> Period. >> Yeah.
2:16:17
>> They got it top to bottom. And they set the tone.
2:16:19
Who out there doesn't want to be Steve Jobs, right?
2:16:21
They, you know, they everybody's every he's the new Steve Jobs.
2:16:25
This is he's the old Steve Jobs.
2:16:27
You know, he's not Steve Jobs. He is Steve Jobs.
2:16:30
>> But >> yeah, and it's saying something I've never everyone wants to be.
2:16:31
And yet I've never seen someone and thought, >> "Wow, >> damn, they're the new Steve Jobs."
2:16:38
>> Because they're missing what Steve was. Steve was the ultimate. He knew it.
2:16:40
He knew the goal was where technology and the liberal arts meet.
2:16:47
And there's nothing more evident in that than in AI. >> Yeah.
2:16:54
>> You know, so >> do you think you would have liked AI? >> I don't know. I I can't I never tried. I was a friend of mine.
2:16:59
I He has an incredible wife, Loren Powell Jobs, who's an incredible human being. >> Yeah.
2:17:06
>> And Johnny IV is >> Yeah. >> Incredible people.
2:17:08
Uh I can't speak for them for Steve.
2:17:11
He he was his own guy, but uh you know >> Yeah. Yeah.
2:17:15
a f a friend of the show uh was trying to compare AI messaging to the launch of GarageBand and democratization of creative tools and uh I thought I I I thought there were some good points there.
2:17:29
>> Although he didn't like streaming.
2:17:31
>> Yeah, >> he was very public about that.
2:17:32
But who knows what >> maybe he was right. I don't know.
2:17:36
>> You mentioned the tail wagging the dog at Apple.
2:17:38
If you're a tail, should you try and wag the dog?
2:17:42
Is that advice that you would give to someone who works in a large organization if they're interdisciplinary?
2:17:48
>> Well, when you what I was saying what I was saying is that >> look there's no there's no hiding it.
2:17:53
Big companies music outside of music companies you nobody wants to tail wagging the dog.
2:18:00
>> But is it a fool's errand to try? >> Um I I don't know. I don't know.
2:18:06
Depends on the situation. Uh I don't know.
2:18:08
But but I always use Apple example because I think it's run really well and >> they blend it as well as you could blend it.
2:18:18
You know, Steve was a big music guy and so is Eddie.
2:18:22
>> So they do it really well, but you know, it's I don't I think I think the record company should do it. >> I really do. I I I don't get it.
2:18:29
I I think that they should do it.
2:18:32
They should take it on themselves.
2:18:35
And Spotify is a music company. They they can do it. Live Nation.
2:18:41
>> Isn't there some interesting positioning that the record companies, at least if they banded together, could work with the artists to say, "Hey, you have an if you work with if you if you subscribe to Apple Music or Spotify, Spotify and Apple Music are taking a big cut.
2:18:54
If you work with us, a lot more revenue is actually going to the artists."
2:18:58
Is that is that like how you position?
2:19:01
>> I don't I don't I don't I don't know.
2:19:01
I don't know if that's if that's right.
2:19:03
I just because it's it's it's a hard bell to unring.
2:19:08
>> Yeah, >> I'm not I'm not looking at streaming that happened already.
2:19:11
I don't think the labels are going to start streaming services, you know, not anytime short in the next few years anyway.
2:19:18
>> But I do think there could be a new AI business. >> Yeah.
2:19:22
>> And that's where the opportunity lies.
2:19:24
And you have Spotify, you have the labels, you have the artists here.
2:19:27
So, there's something in there that needs to evolve out of this that makes more sense, you know, and uh I I see I see it all together. I But I always have.
2:19:41
That's why we That's why we started the school we started. >> Yeah.
2:19:45
>> It's just all goes back to that.
2:19:45
It's just the way people think. That's how we think. >> Yeah.
2:19:49
I I mean obviously the answer is probably both but I would it'd be interested to see if you're more optimistic about uh the entrepreneurship that comes out of your school or the transformation within within industry.
2:20:01
>> No, the school was built to transform inside the industry. >> Okay.
2:20:05
>> Yeah, it was it was built for jobs.
2:20:05
It turned into an entrepreneurial place >> of course >> you know u >> I guess we caught that wave you know everybody wanting to be like one of these guys Zuckerberg or something >> but it was made >> to help communication inside Apple all these giant companies that are >> taking over the entertainment business literally. >> Yeah.
2:20:29
So, it's not going to happen in my lifetime, but we wanted to build as many people as possible to infiltrate and help make that all one thing rather than have to be a tail wagging a dog, you know?
2:20:41
I mean, look, uh, Intel's buying Paramount and Warner, right?
2:20:45
I mean, fundamentally, I mean, and David Ellson is terrific, you know, he's a really smart and and and understands where these two things cross.
2:20:54
So, hopefully there'll be some great stuff there.
2:20:57
>> Yeah, it's going to be exciting.
2:20:57
Well, thank you so much for coming on the show.
2:21:02
It's >> been an honor and pleasure. >> It was fun.
2:21:04
>> Let's do it again more of these plays. >> Oh, I know.
2:21:06
But uh it was you're very far from my house.
2:21:11
>> Maybe if you come to my house, we can do it.
2:21:13
>> Yeah, we'll do it over there.
2:21:13
That's >> But anyway, thanks.
2:21:14
Oh, there's a big world behind me. I see that. Nice set.
2:21:19
Look at all the lighting.
2:21:19
It's all >> We reinvent the television.
2:21:22
>> Well, uh we will see you tomorrow at 11 sharp.
2:21:26
Have a great rest of your day and goodbye. >> Thank you. >> Don't fade us out.