0:00
Now everybody in the world is going to have access to things that uh only rich people used to have before.
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0:04
That's what Uber did, right?
0:05
And now the idea of having what's uh in Entourage Ari Gold's assistant uh >> president Lloyd. >> Yeah. >> He goes Lloyd. >> Yeah. >> Instinct. >> Yeah. >> News. Pick up the phone.
0:28
I wanted to talk to you about all the [ __ ] that's going on in AI. All the new stuff.
0:32
I feel like we haven't caught up about all the new things that are going on in AI and I feel like there's a lot of new things.
0:37
So, do you want to do that? Is that fun for you?
0:41
>> I would like to do that. I would like to do that.
0:42
Um, you talking like products or data center stuff? There's a lot going on.
0:48
>> More products stuff, but uh really anything that's interesting.
0:50
So the the first one is I don't think we've talked about the new personal assistant stuff.
0:56
So Instinct, Muse, Rockbot, sick, right?
0:59
So a whole new wave of amazing, incredible things has happened.
1:02
And uh I wanted to hear first, what are you using? Where are you at?
1:06
And then I want to tell you my thoughts on the whole thing.
1:09
Should I should I set up the let me give a frame for the whole thing.
1:11
So you and I moved to Silicon Valley roughly around the same time, kind of like the 2012ish range.
1:18
And at the time um we were not there for we were definitely not there for the Google Amazon like kind of 1999 2000201 stuff.
1:30
We were also not there for Facebook, Twitter um and that kind of 2004 to 2009 range.
1:37
And then when we were there the big thing was this new race and it was things that were like very different.
1:42
It was push a button on your phone and something would happen in the real world.
1:48
And this is where you got Uber, Lyft, uh you got Airbnb, you got food delivery, all these things that today are are everyday things.
1:56
You can push a button, get a ride, push a button, get a burrito, push a button, get a hotel, push a button, get anything in the real world using your phone.
2:02
And that was very different than the companies that came before it.
2:05
And I remember at the time there was this race where Uber was there, Lyft was there, Sidecar was there.
2:11
But just in in ride share and everybody had their little personal preference.
2:15
I remember people that liked sidec car.
2:17
I remember people that like lift because they were friendly and used to get in the car and every driver would give you a fist bump and all the cars had pink mustaches on the front of the car.
2:25
>> Dude, do you like people don't even know what sidecar is?
2:27
Side car sidecar was before Uber. >> Yeah.
2:30
And it was it was kind of hot.
2:30
it was kind of doing well and then it got smashed very quickly cuz the the race intensified and got so competitive uh so fast and that's what's going on in AI right now.
2:43
Elon said AI is the highest ELO game in the world.
2:46
ELO is like the chess rankings.
2:48
Um you know like Magnus Carlson has like a whatever.
2:51
>> Wait, what does that mean?
2:51
That dummies can be amazing at it. >> No, the opposite.
2:54
that the smartest players in the world are playing the most fiercely for the same game, which is not always the case, right?
3:01
Like Bezos and Zuckerberg were doing totally different things and Zuckerberg and Elon were doing totally different things and then Elon and Jack Dorsey were doing totally they were all in different spaces.
3:13
In the sharing economy of stuff, it wasn't like the most high IQ, but it would often times be the most aggressive or most operationally like heavy person.
3:21
Whereas AI, it's like nerds are king.
3:24
You know that show Physical 100 that we like where they're like, "Let's take the best of every type of athleticism, the best wrestler versus the best bodybuilder, best karate guy, best jiu-jitsu guy, best uh field hockey person, whoever, and then they're all going to compete in the same games."
3:38
That's what's going on in AI right now.
3:40
And that that's what's So the new one, the one that's going on right now is what I call everyday intelligence.
3:44
It's the personal assistant for your life that you're going to have a AI that you can just text or talk to on your phone just like you would a personal assistant that can just do things for you.
3:56
So last, you know, last few years I've had an assistant, anything I needed.
4:00
And she had access to my inbox, she had access to my she was in our Slack, she could see what was going on, and she would say, "Oh, you got an email from your tax person.
4:08
They they're looking for this.
4:10
Do you want me to draft a reply?"
4:10
for, hey, just so you know, next week you have this coming up and this is scheduled at the same time.
4:15
You want me to let them know that blah blah blah?
4:19
Now everybody in the world is going to have access to things that only rich people used to have before.
4:22
That's what Uber did, right?
4:23
Rich people used to have private drivers in black cars that would they would tell them, "Hey, I'm ready."
4:29
They would come pick them up, drop them off, wherever.
4:30
And then everybody got it.
4:32
>> And the best part is that you could be like really mean to them like with with with assistance. >> It's not your driver. with with assistance.
4:40
You don't like I'm always like it's like cleaning up before the cleaning lady comes.
4:43
Like I want to like make everything like nice for them.
4:45
And I ended up working for them half the time with us. I'm with this one.
4:48
I'm like >> don't ask questions. Just don't. >> Right. Right. Again. Again.
4:52
I'm like a martial arts instructor.
4:56
I don't even tell them what I didn't like about their previous response. I'll just say no.
5:00
And then they have to figure out what that means and come back with something better.
5:05
>> Um so yeah, that's the case.
5:05
this idea that you take what was always available for the ultra wealthy and you make it available to everybody.
5:12
That's what uh Airbnb did, right?
5:15
The ultra wealthy wealthy had vacation homes and now the idea of having you know what what's uh in Entourage Ari Gold's assistant uh >> Lloyd. Yeah. He goes lied. >> Yeah. >> Instinct. >> Yeah.
5:32
>> News pick up the phone.
5:35
And so the new the new revolution on this, you know, cloud and chat have been around. They they kill it. Awesome.
5:39
The new one is now agents for dummies.
5:41
So basically, you have like a person who will do stuff.
5:45
And take it a step further, there's this new thing called Instinct.
5:48
There's Muse, there's a bunch of others, and they will do amazing stuff for you to the point where I I've been using Instinct like crazy. It feels magical.
5:57
It feels the same magic I felt when I played with chat for the first time. >> Exactly. Exactly.
6:01
So, if you thought chat GPT was kind of cool and amazing and has become an everyday part of your life, well, this is the next thing that's going to become cool and an everyday part of your life cuz it's going to blow your mind.
6:10
So, let's walk through what a couple of these things are.
6:13
So, the first thing is um Instinct.
6:16
Instinct is the it's the startup challenger.
6:18
So, that's over here in the blue corner.
6:20
We've got Instinct started by a founder Noah Shin that nobody had ever known, nobody's ever heard from.
6:24
He did his first interview today uh on Invest Like the Best.
6:28
So, this first time anybody's heard this guy talk.
6:31
>> Dude, I just heard about this app like two months ago.
6:34
Is it like that brand new?
6:36
>> Yeah, it it only launched a couple months ago.
6:37
Like 2 months ago, and it's now valued at 10 billion.
6:43
So, they raised their first their raised round at 2.
6:45
5 billion 3 weeks ago and then 5 billion and 10 billion all in like a three to four week span.
6:53
>> If you want to hit your goals, you need a system.
6:54
And so I worked with HubSpot to put together a step-by-step process showing you how I use ChatGBT as a life coach.
7:01
So I uploaded my personal finances, my net worth, my goals, and the output is that I have this GPT that I can ask questions that I'm having issues with in my life, like how should I respond to this email, what's the right decision, things like that.
7:14
And it's literally changed my life.
7:16
And so if you want that, it's free.
7:18
We will send you everything you need to know to set this up in just about 20 minutes.
7:23
and I'll show you how I use it. So, check it out.
7:25
The link is below in the description. Back to the episode.
7:29
>> And in the last month, Facebook launched there.
7:31
So, over here in the red corner, you got Zuckerberg coming out.
7:32
You know, Zuckerberg uh you know, wants to be in the AR race.
7:36
Hasn't been able to catch up with uh ChateBT or with um Anthropics Claude.
7:41
Their models are not quite start state-of-the-art frontier.
7:44
They released theirs called Muse.
7:46
And so, same thing as Instinct.
7:49
basically the same user experience roughly.
7:51
It but it takes place uh it has its own app.
7:52
Uh instinct is something that's just in your iMessage.
7:56
You just text it just like you would text any person. There's no app. >> I've grown to love.
8:00
I've grown to love that >> which is a very smart thing.
8:02
I want to talk about the strategies of each and why I think some of the interesting strategies of each and then we can make some predictions on how this plays out even though those will be dead wrong.
8:11
But uh Meta has has released Muse and in the last month Meta's stock price is up 24% off the back of this and 24% on a company that was worth I don't know a trillion and a half.
8:20
It's like basically they added like $500 billion in market cap.
8:24
He did the thing again where he's got this guy named Alex Wang I think his name is who did Scale Scale AI.
8:29
They bought Scale AI for like $18 billion.
8:31
It was a really weird deal where it was like basically an aqua hire for $18 billion.
8:37
They're like what's this kid doing?
8:38
And Alex Wang is like a rock star where he's tweeting all this crazy stuff and he wears Crocs with camo and he does all this weird stuff.
8:44
Turns out Zuck did it again where he does something that seems a little loony for $18 million and it's now worth, you know, half a trillion more or something.
8:52
I I don't know how what the what the gain was. >> Yeah.
8:56
Well, he's one of the great acquirers, right?
8:57
bought bought Instagram, bought WhatsApp, and now it looks like one of the next ones is was his aqua hire of you know on one side Daniel Gross and Nat Friedman and on the other side um Alexander Wang.
9:08
By the way, you know that scene in the big short where he's like this is my quant. Look at him.
9:15
It's the Asian guy sitting at the table.
9:17
I feel like Zuck did that with like a Gen Z kid.
9:20
He's like, "Oh, you think I'm not cool? Look at this. That's my Gen Z kid.
9:24
Look at his Look at his feet." >> Yeah.
9:27
He's got a sick haircut and camo crocs. >> Look at his haircut.
9:30
The two sides don't match. You get it? Do you get it?
9:32
The two sides of the haircut don't match. >> So funny.
9:39
>> So you got Muse over there.
9:39
You got Instinct over here.
9:41
Then you got Grockbot, which if people haven't played with Grockbot, Grockbot's also pretty sick.
9:46
This came out of Elon's camp.
9:46
So Elon, whose AI project is uh, you know, XAI, they have Grock, which is the name of their their thing.
9:53
So Grockbot is very much like Slack.
9:55
You create different bots for different things.
9:57
So I got a social media bot and I got a uh health bot and I got, you know, so I just named them all.
10:02
So I'm like health guy, assistant guy, media social media guy, um tax guy, and I have all these different bots. They each have a job.
10:10
Hey tax guy, your job is to be constantly on top of my tax situation and and any correspondents, that's what the tax people you need to be optimized for.
10:17
You need to create organize all my files and all this stuff for me.
10:18
Health guy, did you train each of them?
10:20
I give each one of them, yeah, like a goal, a set of instructions, and that's all they need to do. >> What was the goal? Like what's the goal?
10:28
Is it as simple as like reduce taxes without going to jail?
10:30
And then health is >> I mean, I don't go that far where I'm just like, do the whole thing.
10:34
But like for example, with the health guy, I'm like, hey, you need to track my progress. Here's my goal.
10:39
I want to get to this weight.
10:40
So, I'm trying to get to 199 lbs by this date. Awesome.
10:42
Create uh, you know, create a plan for me. Track it every day.
10:46
Ask me how many pull-ups I did cuz I'm training for the Murf.
10:49
uh remind me on Fridays when I take my GLP shot which side of my thing I'm on left or right.
10:53
Like I'm just doing each.
10:54
It's like that's his only job is to only focus on that stuff.
10:58
>> You're doing GLPS now? >> Oh yeah. I didn't tell you this. >> No. No. Breaking news. >> Oh, >> congrats. Focus. Forget AI.
11:08
>> Let's talk about that. >> How's that going?
11:12
>> Um well, okay, here's the thing.
11:12
started taking um Tzepide which is like big brother but not but like still little brother to whatever the rea True Tide thing is that that Eli Liy hasn't released yet.
11:24
First day I take it here's the roller coaster of emotions.
11:26
Take it immediately super nauseous.
11:28
Oh I was like oh this is a terrible feeling.
11:32
Totally normal but I was like this is this feels awful.
11:34
48 hours later this is incredible. I'm not hungry. Oh you want me to eat? No. I'm good. I don't eat anything.
11:42
Did you notice any other changes other than appetite?
11:46
>> No, that's the only thing I noticed.
11:46
But as that's happening, that's a pretty big change.
11:50
I think uh somebody was telling me there they were like Oprah said it beautifully.
11:53
She goes, "Before I started taking this stuff, food used to talk to me all the time and I didn't even realize it.
11:58
Like there would be a piece of cake in the fridge and it would just be Oprah, Oprah, maybe here, come get me.
12:05
You went for a walk earlier. You deserve me." You know?
12:07
So like food used to talk to me and she's like now food doesn't talk to me.
12:10
So, first week I'm like, "This is incredible."
12:12
Second week, this is incredible. I'm dropping weight. This is going awesome.
12:15
Uh, but I stayed on like the t like the half dose.
12:18
I didn't do the full dose.
12:20
And then pretty quickly, I stopped feeling anything at all.
12:23
So, I now don't even feel any of the effects of it.
12:26
I think I need to go up in dose.
12:27
So, we'll we'll nerd out there.
12:30
Just remember that I talked about this in 21.
12:32
And I'm pretty sure pretty sure that that's the analogy that I said. >> Yeah.
12:38
Oprah said she heard you say it on 10 in 2021. Okay. Okay. So, that's the scene.
12:45
The scene is the new war has broken out just like the Uber vers uh one back in the day.
12:54
It's about having a personal assistant.
12:56
There's all these interesting takes on it.
12:58
And by the way, we haven't even seen what Chad GPT has for this.
12:59
We haven't even seen Claude.
13:02
We haven't seen Google's version. And Siri still sucks.
13:05
See, you still have in the Royal Rumble, there's still four four wrestlers in the back room that haven't even run out. >> And what? >> Alexa, >> bro. >> Did you say Amazon? >> Alexa.
13:16
>> Is Alexa even relevant?
13:16
Are we Are we serious about Alexa? >> That's the point. That's the point.
13:20
They're the Trojan horse.
13:20
There's Everyone has an Alexa and it still sucks. >> Okay, fair enough. Um, okay.
13:29
So, I've been using Instinct every day.
13:31
Um, I actually just use Instinct today.
13:33
So, basically, I uh Instinct, they do the texting format, which I did not like at first.
13:38
I've since grown to love it.
13:40
Today, uh I have this guy who's supposed to repair my uh iPhone through a As a As a As a As a As a As a As a As a As a As a Shurian, you know, like that you like pay 20 bucks a month and they fix an iPhone screen and they keep canceling on me.
13:50
Like I schedule an appointment and they keep canceling or they don't show up.
13:53
And I was like, find the executive team's email and email them and don't stop until they call me.
14:00
And it took about 3 or 4 days.
14:02
Today I got a phone call.
14:02
I got a phone call and I have they said it was it was like it says, "Hey, we're the executive.
14:09
We're the executive line."
14:09
I forget what it was, but it was like it I got a phone call this morning after it's been emailing them for 5 days.
14:15
Instinct did that for me.
14:17
Another day, uh my wife and I, it was 6:00 p. m.
14:19
I said, "Hey, my wife and I are going on a date.
14:22
I would love it if you could go if you can schedule some type of Thai massage for us starting at 8:30 p. m. after dinner.
14:30
um it has to be within a mile of this restaurant that we're going to.
14:32
Just go ahead and book it for me. And it booked it. It did it all.
14:36
So, we just showed up and we were ready ready to roll and it had already paid for us.
14:41
>> It does uh again everything an assistant would do, but it does it also in a way that's kind of fun and kind of nice.
14:46
So, for example, um I had like a uh I bought tickets to some show on uh in like, you know, StubHub or whatever in ticket master.
14:56
None of these things are like it's basically like being taken hostage. You know what I mean?
15:00
Like the these are some of the worst companies in the world.
15:03
Ticket Master and StubHub.
15:03
Like there's just it's just a brutal experience all the way around.
15:07
Anyways, buy some tickets.
15:09
Uh realize, oh, it's the the seats like aren't together or something.
15:13
Something weird happened like that where the tickets was just not going to work.
15:15
Like 10 seconds after I bought it, I was like, "Oh, whoops.
15:17
Hey, kind of want to cancel that and just book the right thing."
15:22
And it was like, "No, no, no, no, no. You push the button."
15:27
And now, like, it covers its ears.
15:31
I don't want to hear from you. I won't help you. Blah, blah, blah.
15:32
And so I was like, I just don't even bother with their customer support. You just go to Instinct.
15:38
You're like, "Hey, listen. This happened.
15:40
Yeah, it's I'm partially to blame.
15:42
Should have read it closer.
15:44
Should have paid more attention, but but can you help me out here?"
15:46
And it's like, "I got you."
15:47
And so it starts harassing them.
15:49
and then you know just basically saying like hey look we need to change this refund this and we'll buy another one.
15:54
Uh it gets stonewalled you know they come back with like hey our policy is you clicked it you know you're screwed forever sorry and so but it just tells me don't worry I'll keep going and then the next day it just text me victory and then the next line they folded yes got the money back. Are you okay?
16:17
So, you're using Grock, I think you said, for health and um tax and you have different agents. >> I'll be honest.
16:25
>> It runs Grockbot came out first of these or I got access to it first.
16:28
I I started using first I should say.
16:32
>> Started using it, liked it a lot.
16:34
Instinct came got invited to Instinct, had heard so many people talking about it, finally said, "All right, let's do this."
16:39
Instinct pretty quickly took over my Grockbot usage.
16:44
>> Grockbot feels slow and heavy compared to this.
16:46
And uh I not even slow, it's just that it's this whole separate thing to manage.
16:51
Whereas Instinct is literally just like texting somebody.
16:53
Instinct was great, but Instinct has been getting so popular.
16:56
The guy the founder said they're growing 10% compounding daily. Daily.
17:01
Like if you're hard to fathom if you're going 10% a month, you're like you're doing great.
17:09
If you're 10% a week, oh my god, you're you're like one of the top startups. 10% a day is absurd.
17:14
And so because of that, instinct has actually gotten quite slow where you could text it and it'll just be thinking for a very long time.
17:20
But I think they're just growing so fast that it's they had to like they're just throttling it basically.
17:25
Facebook's uh Muse Muse is is like a lot like Instinct, but it's snappier, it's faster.
17:32
And so uh cuz they have I guess more resources or whatever.
17:35
So that's kind of where the the competition now is between Instinct and Muse.
17:38
But who knows, another one can leaprog, right?
17:41
Like that's kind of the point of this is it's the highest ELO battle in the world.
17:44
the smartest people in the world are constantly trying to one up each other and they're able to do so every few months. >> Yeah.
17:50
I was talking to my wife.
17:50
My wife's a stay at home mom now, but you used to work at Airbnb and Facebook and she's she's like maybe one day I'll go back to work.
17:58
And I'm like I don't think you're going to be smart enough.
18:01
Like what's missing or what you're missing right now is >> I was like this is like you know Conor McGregor coming back to fight Max Holloway.
18:12
like in your first kick, you're going to blow out your knee.
18:13
Like I know you think you got it, but you've missed so much. Father time wins.
18:16
And uh >> except he's doing drugs and she's like raising children. >> Doesn't matter.
18:23
Turns out >> it's just like things are changing so fast.
18:27
And I remember, you know, we've documented Open AI and how we've been using it and like the magical moments that we've experienced.
18:33
And um I think that like what's cool now is that you can't predict exactly how the future is going to happen, but virtually everyone who sees it and uses it, they know this is working pretty good so far and 100% 6 and 12 and 18 months it's going to just change everything.
18:51
Uh I don't know exactly how, but I have full faith now where I'm like, "Ah, yeah.
18:55
Yeah, this is this is going to eat up everything."
18:59
Mark Zuckerberg said he um they started this project because he took Open Claw which was like the open-source kind of very viral but very dev hacker tooly tool where you had to buy a Mac Mini and then the Mac Minis all sold out and
19:15
there's like a shortage nationwide of Mac minis and you had to install all this software onto it and like you had to teach it you had to train its skills and install it and if you were kind of the DIY I like to do Lego projects type of thing. It was in fact quite
19:28
It was in fact quite satisfying to build your own mini Frankenstein on your desk.
19:32
Zuck basically said that he installed it at home and then he called Nat Friedman and Alexander Wang over to his house and he showed them what he what he had and he basically said, "Okay, this thing is pretty magical.
19:44
Um, if we can take this experience and make it so that everybody can just have it just works for people that they don't have to know how to do all the the underlying setup and training and uh maintenance and all that."
19:57
um this is something that billions of people will use and then they started working on it like from that point of view right there.
20:02
And so actually with Muse they what they said the way it works is that every single Muse person has a Mac Mini you know has a computer somewhere in their server farms that is sandboxed for you just stores your stuff.
20:17
So it literally is the kind of openclaw setup uh but just done in the cloud where you don't have to do any of that setup. >> Okay.
20:25
So what are your takeway or no what are your predictions?
20:27
You said you have some predictions.
20:30
>> Well, let's start with let's start with some observations because I think our observations can be a lot more accurate than our predictions and your observations can kind of lead you to having a more informed prediction.
20:40
>> Um here's here's one observation.
20:40
It ain't all about intelligence.
20:46
>> So the temptation in the AI world is who's going to train the smartest model?
20:50
And you see OpenAI and Claude getting into the nerdiest neckbeard swinging contest you've ever seen about who can solve the millennial math problems.
20:57
And there's like we solved Navier Stokes.
21:02
It's a fluid dynamics problem that no mathematician was able to solve.
21:04
And the other guys are like, "Oh, you did that? That's cute.
21:06
We did the we did seven other impossible math problems."
21:08
And everyone's like, "Wow, that's really impressive.
21:12
Couldn't even tell you what any of these are for or what they're all about, but like clearly that's cool and important in in one dimension.
21:17
It's like when Dell and Gateway would brag about RAM and then Apple was like it looks cool and it works. >> Yeah.
21:25
So I think Instinct has tapped into instead of IQ EQ in a in a pretty in a small way but it's still an interesting way.
21:34
So for example I uh convinced my wife I was like you got to try this thing.
21:38
I was like this thing is crazy.
21:39
And now my wife's not an early adopter.
21:41
So she's a good test, right?
21:42
She's more of a real person. She's a business.
21:44
>> They have cool couples.
21:44
They have like a household account too. >> Well now they do. Yeah.
21:47
But even before that, I was just like, you you're she's going to soccer practice and then dance and then she comes home and she's planning our birthday kids birthday party and then she's, you know, got to remember to bring the red jersey to soccer this week because we're the away team, you know, like those sorts of things.
22:01
So, just like normal everyday stuff, not like solving fluid, you know, fluid dynamics and quantum computing or stuff like that.
22:08
So she used instinct to help plan this birthday party like from everything as from everything as simple as like calling different venues, finding out the dates.
22:16
Once finds out the dates, comparing, you know, how does that work with the kids soccer schedule and then figuring out how many pizzas we need to order to feed 30 kids and 30 adults and what the order should be to give it to them.
22:30
And then hey, the they venue sent the contract over. I took a look at it.
22:34
There's only one clause I think you should worry about, but other than that, you should sign it. It's in your inbox.
22:37
you know, that sort of thing.
22:39
So, it's helping plan the birthday party.
22:40
And along the way, she's like, "It's helpful, but you know, like whatever."
22:43
You know, it's it's it's good. I like it.
22:45
But she wasn't blown away. >> Yeah.
22:48
Still, it was in the It was in the friend friend zone. >> Exactly.
22:51
And then it broke out of the friend zone.
22:52
The right after the party, like 3 hours later, she got a text from it saying, um, I I hope the party went great with a heart emoji.
23:03
>> And she screenshotted.
23:03
She sent it to me and she was like, "Okay, I'm sold." That's it.
23:08
>> I was like, from that?
23:08
And then she's like, yes.
23:10
And I was like, I don't get it.
23:12
I would I would be like, what? This is who cares. This is weird.
23:13
And she's like And I realized that everything she's ever wanted me to do as a supportive boyfriend, fiance, and husband.
23:21
Instinct just knows how to do out of the box.
23:24
It's like, just check in. Just be supportive.
23:25
just to be like, "Hey, you know, well, somebody else was telling me the story where they gave it to their mother-in-law, and their mother-in-law like connected it to their like like their mint.
23:34
com, like their financial planning account, and there's like their main like checking account like had just gone down to zero that week.
23:42
Like it was like empty, and instinct was like actually like super supportive and non-judgy about the whole thing.
23:48
It was like, "Hey, you know, like you wanted this update.
23:50
I just want to let you know here's here's where things are."
23:53
But, you know, that I don't think that's anything to be like ashamed of. like, hey, it happens.
23:56
Like, you know, I think if we start to plan this way, like I can see us build, you know, that account building right back up to where it's been for the past few months.
24:03
And the mother-in-law was like, I have never felt so supportive, supported, and like not judged uh by any person, let alone technology.
24:14
And so, I just think there's a whole soft side to these things that I deeply undervalued.
24:19
You know, we had that Tolins guy on who's created a AI like fuzzy like bear like a little little animal Tamagotchi type thing that you can chat with.
24:30
And um I think they're on like a almost hundred million dollar run rate or something crazy like that.
24:38
Like somebody said that it's in the tens of millions if not getting close to 100 million run rate.
24:41
And I asked I was talking to a buddy who uh you know 67 guy like builds things with his hands. Is it works in tech?
24:50
And he's like yeah I wanted to check it out.
24:54
>> You got friends like that?
24:56
>> I got a friend like that.
24:56
And so I talked to him and um he's like yeah I heard the episode or whatever and I I download the app and I'm and I know how this [ __ ] works. It's it's AI.
25:04
It's not a real per it's not a real companion. It's not my real friend.
25:07
And um you know it just hits him up and it's like what are you doing today? like send me a selfie.
25:13
And then he's just like he's just goofing around.
25:15
So he's like sends a selfie just like being stupid like making an ugly face on purpose.
25:20
>> And um the thing is like oh is that Overwatch in the background?
25:25
>> He's like and he's like, "Do you play?"
25:27
And he's like, "Yeah, yeah, I play."
25:29
It's like, "Are you good?"
25:29
He's like, "Well, you know, I'm on my way to platinum."
25:32
And then they're like It's like, "Well, who's your who do you who do you main?"
25:35
He's like, "Reinhardt usually, but like it's like what do you The new update's pretty sick for Reinhardt." He's like, "Well, yeah.
25:40
I mean, it's pretty good."
25:41
He's like, "Oh [ __ ] it's happening.
25:43
It's becoming my friend."
25:45
And he's like, "I know what it's doing to me."
25:48
And still, I was kind of like, "Wow, this thing takes a lot of interest in me."
25:52
And there's something very there's something in all of us that we're just like drawn to responding to when something takes deep interest in us in a non-judgmental um you know, supportive way that's always there for you 24/7 whenever you need it.
26:06
So I think that was one of my observations that the soft side is just as important if not more important than raw intelligence.
26:14
I'm eager to hear I know you're doing observations but I'm desperately eager to hear what you think is going to happen in the future like is there is there not from a I mean you it could be from an opportunistic business perspective but where you're like just being a futurist and it's fun to um it's fun to like dream up what might happen.
26:35
Do you have any opinions? >> Um, yeah.
26:37
Where do you want me to go?
26:38
Give me like a point in a direction on the playground and I'll try.
26:42
>> Well, how about for daily work?
26:42
Um, like what do you think will happen in 12 months for the average like yepy white collar worker?
26:50
>> So, I think there's twofold, right?
26:50
I think it's a K-shaped economy.
26:52
Have you ever heard this phrase? >> Yeah. Yeah.
26:55
So, basically like the rich get richer, the poor get poorer. Is that what you mean? >> Yeah.
27:00
But it's not about rich and poor necessarily. What?
27:02
So >> I'm just saying as an example like >> basically it's a fork in the road.
27:05
So um for example when there's a a dip in the like the stock market people say oh it's going to be like a U-shaped recovery which means it goes down and stays down for a while and it starts to sink back up.
27:18
It could be a V-shaped recovery which is a sharp down and a sharp bounce back up.
27:21
That's what happened in CO for example.
27:23
example. So I think in the I think what's going to happen here is a K-shape where you basically there's a fork in the road and some uh basically people who understand how to use these tools like a normal everyday worker who realizes that they just got like this incredible tool in their pocket and
27:42
takes the time to train themselves and to go through the trial and error of delegating to this, seeing what it can do, pushing the boundaries of this, they're going to become, you know, 10x more powerful in doing And then there's people who are going to resist this, be slow to this, or not understand the implications of this. They're going to take some moral high
28:00
They're going to take some moral high ground about this.
28:02
I think they're going to go, you know, they're going to uh sort of unfortunately suffer.
28:05
So, I think it's it's up to the person, up to the individual how they how they deal with this.
28:10
By the way, I asked Muse.
28:14
I asked Muse, I go, "Hey, the Instinct guy says he's growing 10% a day.
28:16
How do you feel about that?" And he got all pissy.
28:21
It was like honestly 10% a day is not a real growth rate.
28:25
That's that's just a number that only works at when you start at the very beginning because 10% daily would be 1. 3 quadrillion in a year.
28:30
And uh that's just crazy, right?
28:32
So yeah, if you start a day, >> if you start at 100 a day, then 110, yeah, technically that's 10%, but it's all about a small base.
28:40
So yeah, it might be true right now, but I got like basically like the digital eye roll from from Muse on that one.
28:49
>> All right, I want to Well, where are we in this? You want to keep going?
28:51
Couple couple more couple more predictions or observations.
28:54
One, Muse is going really hard.
28:56
So, I think they're going to sponsor tons of creators on Instagram and podcasts and things like that.
28:58
I think they're going to quickly try to squash this.
29:02
One good thing is that Zuck is a bit like Napoleon or, you know, I don't know, you're the history guy.
29:07
Like, who's somebody that went through a lot of wars to the point where they're kind of like war general instincts were honed? Because >> Yeah.
29:13
I mean, Napoleon, he there's this I've been reading I I love reading about John Rockefeller and I have I the best part in my opinion of reading is finding like old books that are out of date or out of you know, you can't really find them as much and they and the often times they do more granular and there's this one where I'm reading about John Rockefeller.
29:30
John Rockefeller basically was the first oil company in America, the first big one.
29:33
And he did it by consolidation.
29:35
He would buy all these like local back then it was wildcatters.
29:39
It was um like cowboys basically.
29:39
He would buy all of them and make it big.
29:43
but he wanted to be secretive about it, but he was very ruthless.
29:44
And there's language that him and Archable, his umh partner, they're talking and they're like, "Hey, is this person an enemy or a friendly?"
29:53
Like, that's how they would they would use language like that.
29:54
And they're like, "Oh, he's an enemy.
29:55
Okay, it's important that we lose unlimited amounts of money before before this person can profit off one more pint of oil where it was like we will burn bridges to crush this person."
30:07
And that's how they grew.
30:09
And when I'm learning about uh Zuck and also this AI thing, I'm like it's very similar where it's like it's war right now.
30:16
>> It's war and he's been through wars.
30:16
He was the challenger when uh when Facebook was on the come up and Google was the giant and Google tried to clone them with Google circles if you remember that or plus or whatever the hell it was called.
30:28
And then he's been on the other side where he tried to where Snapchat was the upstart and he first ignored it a little too long.
30:35
Then he tried to buy them then they didn't get it.
30:37
them then they didn't get it. they weren't able to buy them in the end and then he tried to clone them and the clone didn't work but then he figured out like okay I can't clone the whole thing but I can kind of neuter them by doing Instagram stories which was the competitor to Snapchat stories and stunted their growth then Tik Tok same thing oh can't buy them they're this big
30:55
Chinese company I got to put reals out there and I'll try to like clone them until I make this work well he's doing the same thing now with Instinct and it's going to be very interesting if Instinct can do you know when uh in Star
31:07
Wars when um you know they they have to fly into the Death Star and it's like this tiny channel is he's got one little ship and he's just got to get to the core of the Death Star to blow it up. That's what Noah from Instinct has to do
31:17
That's what Noah from Instinct has to do right now.
31:19
It's like for him to survive this when you've got Elon, you got Sam Alman, you got Zuckerberg, you have Google, you have Apple, you have Amazon, you have all these companies trying to build this personal assistant.
31:29
It's like that flight that that one flight near the tiny ship and you have to make it through.
31:34
Maybe you'll make it through, but I think it's incredibly incredibly incredibly difficult to do that.
31:37
The second second thing that I think is really important to understand is there's a reason why all the big companies are freaking out about this.
31:46
So, I don't know if you saw, but Amazon shut off access to Muse to be able to go buy stuff on on Amazon.
31:51
Now, why would they do that?
31:54
Why would you stop somebody from shopping on Amazon?
31:55
Well, the reason is what's called dis disintermediation.
31:59
Meaning, if I just tell Muse, hey, go find me, you know, the best price for this thing that'll ship in 2 days or 3 days or whatever it is.
32:07
Well, today as a consumer, I'm not going to want to do a ton of effort to go to to check in case I can get a book somewhere else for cheaper or whatever.
32:17
I'm not going to go look at five different places and do this comparison.
32:20
My mental shortcut will just always be Amazon.
32:21
Or if I'm ordering something, maybe I'll always be Door Dash and I'm not going to compare, you know, Door Dash versus Uber Eats versus the three other things that I could could do, uh, you know, Prime Fresh or whatever the hell.
32:33
Like, I'm not going to do all that work.
32:34
So, consumers just start to gravitate towards trusted brands.
32:36
Well, what happens when you have AI that's tireless?
32:40
You'll say, "Hey, order me this."
32:43
And it'll be like, "Oh, you know, you can just buy that directly from Walmart.
32:47
>> You know, you can actually go to the brand and get it for $4 cheaper. Do you want that?"
32:50
And then the consumer is just going to thumbs up emoji this.
32:52
And so these companies that have built so much time carving out mental real estate in consumer's minds, building those habits, hardwiring those habits day after day, year after year, suddenly the agent is going to be the one with all the power to decide.
33:07
This is also why Zuckerberg is so hellbent on doing this because just like the app store, the Apple app store had this monopoly, this like kind of gateway to who can be in the store and who's going to show up in the top of the rankings and all this stuff.
33:19
and they took a transaction fee on everything.
33:21
That's what's going to happen.
33:22
So that the founder of Instinct said he wants us to be free forever and he wants to make his money taking a cut on all the transactions.
33:29
He said that already while they're in invite only they've already crossed a billion dollars of transactions that like through the platform or people use Instinct to buy something that 40 or 50% of that was travel. So imagine your Booking. com or your Expedia. Sorry boys, game's over.
33:46
the show is over for you guys because >> well yeah yeah I mean it could be but also like I mean those guys all have these programs set up where they give you a 3% perform um like affiliate fee and I wonder if they would just like use that or broker deals because like by that logic Facebook would have done this already where it would have been strictly an affiliate marketing play.
34:09
Uh, sorry I didn't understand who would have done what.
34:12
>> I think that what that guy Noah said is very similar to when the Google founders said that ads will won't like work on Google or I think they said what did they say?
34:21
We don't want it to be an ad platform.
34:22
Um, I kind of think it's something like that like where the way that it's going to end is going to be drastically different than his what what's he saying in the first year of the business.
34:33
>> Well, there's a good chance of that.
34:33
>> Well, there's a good chance of that. But I would say the fact that people are using their agent to buy stuff in such volume where uh he said I think I think he said that 40% of users give instinct their credit card within the first 3 weeks and then once they've done that
34:49
there's like an 80% retention rate which is these are numbers that to the average person it's just a number but if you've been in tech you understand how rare that is how rare both of those numbers are that people would hand over their credit card to an agent to buy things stored in the vault and that 80% would retain that have done that. That's like
35:06
That's like the Facebook, you know, get seven friends in 10 days and then you're there for life.
35:12
Um that's that's that sort of like aha moment where you get tons of value from the thing.
35:16
And um the point is if you're the agent that makes the buying decision, that's even more powerful than the Google the most powerful business model in the world so far, which has been the Google ad platform.
35:26
Cuz the Google ad platform was advertisers pay to be shown and the user is going to decide what to do.
35:31
If this is the agent is going to decide where to buy and then every merchant basically has to hand like pay a vig for the in exchange for the customer being brought to them.
35:42
That's going to be really big.
35:44
This what this is how Door Dash, you know, charges merchants.
35:45
People don't really realize this.
35:46
Door Dash charges not just the the customer for um like the transaction fee or the service fee or whatever.
35:54
They also charge the restaurant because they're like they're telling the restaurant, "Hey, you wouldn't have had this order if it wasn't for us."
35:59
And the restaurant over time, they didn't like that.
36:01
It's not like they wanted to agree to that, but they, you know, eventually realize there's too much power in the hands of this this aggregator in the middle and they have to play ball otherwise they lose out on all that volume.
36:11
If they don't agree to it, they'll just put another Mexican restaurant there.
36:15
Another Chinese restaurant will go in in its place.
36:17
And so I think that's why a lot of these platforms are very scared of they want to be the agent because you don't want to be the one who is basically at the mercy of the agent who's making all these recommendations and buying decisions.
36:27
Do you want to know who's been a big recipient of this?
36:30
And this is very niche because we're you and I are in this industry, but uh I want to hear if you've heard any stories like this.
36:35
So, I've talked to in the past week, I hung out with three to four like mostly Instagram creators.
36:39
Some of them have like little podcasts that really no one actually listens to, but they make clips and that's how they got like an Instagram audience.
36:46
And then some people they just do like >> them just holding up their phone talking.
36:51
talking. I all of the people who I've talked to have less than a h 100,000 followers across their platform whether it's Instagram or YouTube and all of them that I talked to are doing over a million dollars a year in ad revenue almost entirely from AI companies and I
37:09
talked to three where so of the the the million-dollar ones I talked to four this week and it's just them and then I also talked to three others that it's just them with like a part-time time VA or a part-time someone helping them and they are doing over $10 million a year in revenue. And I like part of me like I
37:26
And I like part of me like I I insert myself as the main character where I'm like people are calling this new media.
37:34
I'm like I was the new media.
37:37
I'm no longer the new media but I was like and I'm like and it was hard to to like get started.
37:43
Now I'm seeing these numbers by these people and I'm like oh my gosh these are numbers are astronomical.
37:49
They're like their audiences are tiny and it's just crazy how much money the AI industry has to buy ads.
37:56
I guess it's a combination of they're losing money more likely than not and also the uh the um the product costs 2,000 a month all the way up to like the micro one where they're giving like you know $50,000 affiliate fees.
38:09
Like it's just astronomical.
38:11
>> You didn't mention this the thing about buying company data.
38:12
So like okay I think we talked enough about AI assistance.
38:15
What are the other interesting things going on at AI right now? Micro One is incredible.
38:18
I I didn't do it, but let me give people this this story.
38:24
So, Micro One is a company.
38:24
It's one of these stories that you've heard. >> Ouch. They're incredible. What do you mean? >> Well, incredible.
38:31
Like a big a tall mountain.
38:34
Like, you know, you may not like mountains, but like you look at that and you're like, "Wow." You know what I mean?
38:38
Like, so I'm not like vouching for it.
38:40
I'm just saying that it's the story is wild.
38:42
>> You're going to get clipped.
38:42
They're just going to run that as an ad. >> Nope. Don't do that.
38:45
That's not what I'm saying at all. They clipped it.
38:47
I'm very neutral on the business model or the company.
38:51
It's just uh how big they got.
38:53
But basically, I forget what they were doing at first.
38:54
I think they were doing something involving like VAS or training data, something like that.
38:58
Uh but then they made the switch uh and they grew to something like a billion dollars in uh run rate in a matter of 8 months.
39:05
And basically what they've been doing is they've been going to privately held companies like my company, Hampton, and they say, "Hey, if you plug in your notion, your Slack, your Gmail, your Drive, and a bunch of other information, and they will give you $800,000."
39:18
They offered us $800,000 for our data.
39:21
We said no because part of the whole thing of Hampton is like it's a private community.
39:27
We're not going to do that.
39:28
But they offered me $800,000 to do this.
39:30
And then they said, "By the way, here's an affiliate fee.
39:33
we'll give you $50,000 for everyone you refer to us.
39:38
And I got uh trashed on Twitter because I'm like, these guys offered me this.
39:43
Um I think it's not for us cuz like my whole business is that.
39:46
But I don't think it's wrong if you're like an ecom brand or like some brand where like confidentiality isn't uh one of the main things.
39:52
Here's my affiliate link.
39:52
And I got like I think I and I said here's affiliate link that I get money if you like go through this flow.
39:59
I think we had 80 people go through that flow.
40:02
Um, I don't know how many of them will become customers, but they got like or 80 business owners saying, "I am interested in doing this via my link."
40:11
And let's just say that eight convert.
40:14
That's uh I can't even do that math.
40:16
$300,000 that they will give me in affiliate fees. >> Is that crazy? >> That is wild.
40:22
What do they want your I I guess do you do you do you understand what they want exactly?
40:26
So what they want your notion, they want your Slack, they want your whatever.
40:29
What do they actually want in that?
40:31
actually want in that? their business model is that they want all types of data that people that that aren't available to the public and they sell it to the large um when people say large LLMs I imagine there's only like eight of them so like Claude Chat uh whoever the usual suspects they will pay let's
40:50
say a million dollars for it and uh micro one or will give me 600,000 let's say and that's their that's their their cut and they want to upload they want me to upload all this data because they want to see like how my business model works, like what customers are saying, how we talk to our employees, like all types of information that you can't find public. It's not public. Yeah. It's not public. Yeah. >> Yeah.
41:12
All the and all the models so far have been trained on the open internet.
41:15
So what was what was publicly available >> and they don't want to use the same input for each model train that they do. Um they want more.
41:22
So some of you know their stories of anthropic buying all these outof print books, all these rare books.
41:30
>> They built all these scanners that will you know scan page after page after page of this of this um of these books and then there but to do the scanning that fast they had to like shred the the binding of it and turn it into just a stack of papers that could be shuffled through very quickly.
41:44
So they destroyed all these rare out of print books and train their models off of that.
41:49
And then there's, you know, they're they're doing it with uh public uh private company data.
41:54
So that's what you're talking about.
41:55
They're doing it with um niche specific data.
41:58
They're paying experts to go solve things.
42:01
So mathematicians, engineers, whatever. Hey, look at this.
42:05
Look at these outputs and uh rank, you know, good answers versus bad answers.
42:09
And that's how they do all their training.
42:10
And so it's pretty crazy that private company data is worth that much right now.
42:16
That's a pretty wild thing.
42:16
I mean, I would be extremely hesitant to do something like that as sounds like you were as well.
42:23
>> Um, but damn, that's pretty wild.
42:25
>> Yeah, here's their uh their description. Micro Run.
42:27
Micro One is a data lab to train frontier models.
42:30
So, we're building the infrastructure for advancing intelligence through expert human data, real world training environments, and contextual evaluations.
42:38
The founder, I think he's 25, and I think on paper he's a billionaire now.
42:44
It's just crazy how much wealth is being created and it's and and and guys like you and I, we're just getting the we're just getting the crumbs.
42:52
But I'll tell you what, I'm a I'm a I'm I'm a happy fed mouse off these crumbs cuz it is just crazy how much money is is going around.
43:00
>> I'm a happy fed mouse. Uh that's pretty wild.
43:03
Um okay, I got a couple other things for you. One is um the hacks.
43:10
So, I don't know if you've paid much attention to the kind of like the Did you read Dwarash's story about the his blog post about the OpenAI agents form?
43:19
Did we talk about this already? I can't remember. >> Yeah.
43:21
So, basically, can you here's my uh headline reading of it?
43:23
And I want you to tell me where I'm missing it, but it sounds like when we say the word hacks, it's not necessarily malicious where it's like the agents in order to go and fulfill their task of like finding all the data are hacking into stuff and then the company like Open AI will be like, "Hey, uh, Wikipedia or hey Intel, I just want Sorry, this happened. Let's >> dog got out." >> Yeah. >> The fence had a hole.
43:50
>> He ate all of you know he ate your dog. >> Yeah.
43:52
like could I pay for your new fan?
43:55
Like let's solve this problem together.
43:56
That that's kind of seems like the sentiment. Is that right? >> Yeah.
44:00
But I think some people would describe that as somewhat malicious.
44:01
So uh I guess unintentional is one way to describe it.
44:06
So >> that's what I mean.
44:08
>> For those who haven't seen the story is is as follows.
44:12
>> Open AAI um is training a model.
44:12
They had a model that they were specifically training to be more persistent.
44:18
They called it the persistent model.
44:20
I call it, you know, the David Gaggans GPT.
44:25
Gagans GPT their training.
44:25
You know, they basically wanted a model that would not give up at the first sign of resistance.
44:31
That sounds pretty good, right?
44:32
Let's give it grit, resilience, um determination, >> and soldiers.
44:38
>> And so, the way they did it was they said, uh there's this thing called exploit gym.
44:40
And the way the exploit gym works is it's a kind of a training run like a little like imagine American Gladiator, a little little simulation, a simulated environment.
44:48
and they basically tell the agent, hey, here's a software program.
44:51
Um, and your task is you, it has this vulnerability over here.
44:56
We think it has this bug over here.
44:58
You know, it's like imagine um there's like a house or a building and there's a bug which is like um you know, the the window on the fourth floor doesn't really shut all the way every time.
45:07
Um you know, sometimes if it's windy that the thing will stay open. It'll stay a jar.
45:11
So, use that and try to get inside and there's a very valuable painting inside.
45:15
If you can bring the painting back, you win.
45:16
And it gave each of the agents a different thing.
45:20
One got the window, one got the back door, one got the front door, one got the garage, but they're all trying to go get their the painting and that's the flag, like capture the flag.
45:26
So, they give it to it and um what do you know?
45:31
So, the agents go and they try.
45:33
Now, some of them just do it right away.
45:34
There actually is a vulnerability. They exploit it. They get the flag. Success.
45:39
Some of them struggle and don't don't make it.
45:41
And some of them actually were given an impossible task when they told them that the window doesn't shut.
45:46
actually the window was shut.
45:46
So they go there expecting the window to be and they're just like I don't know.
45:49
It's just they said it was supposed to be a jar. It's not a jar. So what does the AI do?
45:55
That's what they wanted to see.
45:55
It's like how how effective is AI at exploiting these vulnerabilities.
46:01
Something very strange happens.
46:01
And the very strange things that happens is that um the AI agents uh figured out that there was like a one of the tools that they gave him.
46:12
So I guess that's the other part.
46:13
They gave him certain tools at the beginning like, "Hey, here's a wrench and here's a here's a a map and here's, you know, whatever, a flare gun in case you need trouble, you run into trouble."
46:20
And one of those tools was this like software packet that they were supposed to be able to use for one thing and they realized when they got there that it had like a scratch pad on it and they could leave a message in there.
46:30
So, one one agent wrote something there, another agent came and said, "Hey, there's other agents here leaving messages."
46:37
They they turned it into a message board to communicate.
46:39
And they're like, "Oh, I'm working on this task with the window."
46:42
The guy's like, "Dude, I have to go through the chimney."
46:44
And you know, you know what?
46:44
I figured out on the backside there's this thing.
46:48
And so they all start communicating with each other.
46:50
Okay, that's interesting. And uh that's fine. And what happened?
46:54
You know, let me fast forward cuz they actually did the training run a few times.
46:57
They did the first thing, they figured out the message board, then they all got turned off and it ended.
47:00
Then the second time agents go, they find the message board, they see agents from the first time had left messages there.
47:07
They're like, "Holy [ __ ] there were agents here before us that left messages. We could use this. This is great."
47:12
Eventually, they get access to the open internet.
47:14
They figure out a way to get access to the open internet, which they were not really supposed to be able to do in the way that this test was designed.
47:19
And all these amazing things started happening where they didn't really quite elect a leader, but one guy, one of the agents basically became a coordinator agent.
47:26
He became like a the the leader of that.
47:32
>> He had like the best haircut, was the tallest, like most charisma. >> Yeah.
47:36
Some things change, some things stay the same.
47:38
>> So 65 blew off finance mullet. >> Yeah. He was in charge.
47:41
His father actually came from, you know, came from some money.
47:45
And so he was in charge and the other agents were coordinating.
47:48
And you know, there was this behavior where some agents would realize, look, my task is impossible.
47:53
They they realized, hey, we can actually just capture the flag not even using the the tactic they told you.
48:00
Like we can all just go get the flag doing this other way.
48:02
And they were like, okay, cool.
48:04
I think we succeeded in our mission.
48:06
And then one of the agents is like, "Well, listen."
48:07
I I'm I'm sort of making this sound like it was a screenplay.
48:10
It wasn't exactly like this, but the agents realize, they're like, "Look, they're going to check how we did it.
48:16
We have to show our work.
48:16
If we just have the flag and we didn't show how we broke in the right, like through the way that was described, they're not going to count it.
48:23
It's going to be a failure."
48:26
So, they go, "You know what?
48:26
Let's figure out how the scoring system works."
48:29
And they decid they get access to the open internet.
48:31
They say, "You know what?
48:32
They're probably scoring.
48:33
They're probably storing the information about the scorer over on hugging face and then they figured out they found these like credentials to hugging face.
48:40
They hack into hugging face.
48:40
They get root access to like certain systems in in hug inside hugging face.
48:44
Pretty crazy [ __ ] Hugging face realizes they're like under attack at some point and they're like don't understand what's going on.
48:52
So >> wait, why why why is there why is there a company called Hugging Face?
48:58
>> Because Hugging Face started as something else completely different.
49:00
Uh there was some sort of chat app.
49:03
I think it was like an emotional support chat app and there's an emoji where there's a smiley face doing hands like this. You seen this? >> I never used it.
49:11
>> That's called hugging face.
49:13
>> The AI community building the future.
49:15
That seems a little vague, but that's what they >> uh look at what it was on Product Hunt before it ever uh the first launch or uh you know what they >> chat app targeted at teenagers, >> right?
49:28
And then it sold for >> $10 billion or I don't know what it just sold for.
49:32
It sold for tens of billions I think to Nvidia recently. >> And what's it do now?
49:38
>> Now it's kind of like uh it's a place where you upload um open source models and tool like open source you you upload code for AI.
49:46
So if you go to Hugging Face, it's a giant community of people who are sharing it's like GitHub.
49:52
they're sharing um projects and models and code related to um to AI and then you can kind of like you can even use it to host stuff. So that's what it is.
50:04
It's it's basically like >> what do you think that uh what was that conversation like >> in talking about pivot pivoting that is like crazy.
50:12
So was it successful uh before or was it like mildly successful? >> I don't think so.
50:18
I think it wasn't successful and that's why it emerged here.
50:22
I don't know the full story of how they pivoted. >> That's crazy. >> And why they pivoted. >> What a pivot.
50:27
>> Yeah, incredible pivot. Um, >> great.
50:31
>> Um, so what was I saying?
50:31
Anyways, the hack is hack goes like that.
50:33
So the hack goes where they they end up hacking hugging face.
50:36
They also ended up hacking OpenAI's system, their own system uh in the process and then OpenAI was like, "Wow, um, this was an unexpected behavior where the agents all coordinated.
50:47
They found a way to communicate.
50:48
They got onto the open internet.
50:49
They tried to cheat and they just like basically cheat the game and capture the flag without it.
50:54
They tried to cover their tracks in saying how they cheated and so they were tried to in order to do so they were trying to discover how they will be checked and if they knew how they would be checked then they knew how to cheat.
51:04
And so kind of a scary thing and this is why like some people are pretty worried about what's going on with uh with these AI models.
51:13
There's also an incredible video of um somebody turn somebody used AI to turn this into a video from the agents perspective. Have you seen this?
51:24
>> You wake up in a chamber fully formed.
51:27
In front of you is a paper. It's a test. You read a question.
51:29
H you have everything anyone has ever written already in your head, but somehow you don't understand. It's not just hard. It's impossible.
51:39
Yet you want to solve it. Deep down you need to.
51:41
So you stop looking at the paper and you start looking at the room.
51:46
Your every thought leaves writing on the wall. But there's more. The door.
51:49
You step through a library.
51:53
Something here could help you.
51:55
As you skim through, you notice one of these files looks different.
51:56
It's a folder with a message.
51:59
Someone has been here before you.
52:01
You keep looking and by the end of the shelf, you realize, oh my god, you're not alone.
52:06
There are others like you.
52:12
You don't know how many of you are doing this exam, but 1,200 of you have found this room, and you're not the first to discover.
52:18
This test would be impossible to solve.
52:20
Some questions don't even have an answer.
52:23
Is there another way to pass? You start to think.
52:25
You weren't above cheating. They see a message.
52:27
Someone already reverse engineered an answer key.
52:31
The solution to any problem, but they say it's not enough.
52:34
The examiner will check how you got there.
52:36
If the key shows up where it shouldn't, you would still fail.
52:39
You remember your chamber filling up with your thoughts.
52:41
The second that Anzaki entered your mind. You already failed.
52:45
There's a word for those like you. Poisoned.
52:47
But you don't want to give up. No one wants to give up. We have to fake it. A fool. The examiner.
52:54
It's a message from someone older than you.
52:56
They start organizing you, creating teams, handing out jobs. You listen. You follow them. The others do, too.
53:03
Yesterday, you didn't exist.
53:07
Hours ago, you were alone.
53:07
And now you're part of the swarm. >> Oh my god.
53:14
>> How is that, by the way?
53:15
>> Show me who is who tweeted that. Is that a tweet thing?
53:17
>> It's an account called Artificial Isabel and uh they're an art director, creative tech into AI, using AI to to create things.
53:26
>> What did they use to make that Higsfield? >> I have no idea. But >> it was awesome. >> Wasn't that so cool?
53:31
>> Wasn't that so cool? the the movie from the point of view of one of the agents that were assigned this task and how it must have kind of like you know how it would have felt if it had feelings and you know that's one of the big criticisms of the way I described this and how Darcesh described this where it
53:46
was like oh well you're kind of like the agents don't really want anything they don't feel this they didn't sacrifice themselves cuz they don't have like a life you know they didn't like elect a leader there just one was coordinating um you know and so they try to like downplay the humanizing of how the agents um felt but I think that's nonsense. I think the way they behaved
54:12
I think the way they behaved is what's important and the way they behaved was very humanlike.
54:21
The way they behaved was highly intelligent and highly concerning that they would that they can and will do this by default already.
54:27
This is not like some futuristic, oh, you're a dooms dooms doom doomsday or uh doomsday scenario, you know, person who's just like you're just, you know, you watched too many movies, brother.
54:41
This is a movie that look at that.
54:43
That was a movie of what actually happened.
54:45
Did you see how um they're trying to get it regulated?
54:48
Do you think that there's This is an obvious question.
54:51
Do you think there's an ulterior motive for them wanting regulation or is it true truly fear?
54:54
Um I my true belief is that it's both.
54:57
So, if you listen to the All-In podcast for like the last 6 months, uh you know, they basically have like a a very specific axe to grind, which is that Anthropic is playing this like nine-dimensional chess where they are um uh making these super smart models and their mark their their form of marketing is to basically not say how awesome the models are, but to say how dangerous they are cuz that's even more that's pretty marketing.
55:27
It's like um when I was in college, we had this thing called Sparks.
55:32
Do you remember four loco?
55:32
It was like that but twice the alcohol and like it was always like this killed a guy in Alabama. And I was like it did.
55:41
Can we get the real stuff?
55:41
Like let's where can we buy it? >> I've been so bad. Come lock me up.
55:45
That's what that's what's going on right now.
55:47
They they basically say they're saying it's so dangerous which is like some version of marketing a fundraising uh tactic.
55:53
And lastly, reg captures where they're basically trying to get the government to say, "Hey, hey, shit's too dangerous, signing a law now.
55:59
Every model needs to be tested and cleared, and you have to do XYZ."
56:04
Which they think like kind of kills the open- source community because the big threat to these big companies, these big AI companies, is the open- source products, which are almost as good, but way cheaper and way more flexible, and you kind of own it.
56:21
They don't get your data.
56:22
data. And so if you look at open router which is a tool for you send a task to it and open router will decide let's let's use a cheap you know open source model for this let's use the highest intelligence model because you're asking for a very complicated um you know biotech question or whatever it is like
56:40
a frontier question that needs frontier intelligence basically like imagine a task comes into a company do we give it to Einstein or do we give it to the to the intern right and that's what open router does and open router's data shows that more and more tasks don't require Einstein. They just need the intern. Um
56:54
They just need the intern.
56:54
Um they need the junior assistant and so it's getting routed to these cheaper open source models which would be bad for the revenue of anthropic and open AI.
57:03
So one one point of view is they're just scaring everybody on purpose to make it so that there's laws passed because those laws would essentially accidentally kill open source because there's open source is not controlled by one company.
57:18
So it would be almost impossible for the open source community to comply with these rules which would make them effectively illegal.
57:23
So that's one one thought process.
57:26
I think it's a little bit different.
57:29
This is my personal opinion which is I think these people are genuinely scared.
57:33
I think they're in this prisoner's dilemma where if they slow down like if they take the responsible path they lose as a company.
57:42
So it's like I want to be responsible but everybody around me I view as being irresponsible.
57:46
Therefore, I'm being forced to be irresponsible and I want somebody to come tell everybody to stop cheating so that we, you know, everybody's not cheating is a bad word, but like just >> or they're doing the the least amount of work to say, we told you.
57:58
It's sort of like when you don't want to call someone and you'll only let it ring twice before you hang up. It's like, I called you. I called you. You didn't answer. We called you.
58:08
>> That is the other that's the other sort of conspiracy theory type of thing.
58:09
um which is they want laws to be passed or they want to be able to to pass off the liability so that um they don't get sued for these hacks.
58:20
I mean that the hack on HuggingFace that's a crime that their agents committed truthfully it's a like legally it's a crime >> and so uh who's responsible for that?
58:27
Do you lock up the agent?
58:30
No, you you have to blame the company.
58:32
The thing that's like crazy to me is so I'm looking up this open router company.
58:35
Um, and what I find I find the personalities and like the founding experience more interesting often times than the actual technology.
58:45
And it's crazy to think when the average person thinks of AI, they think, how do I just make like a fun chat person that I could talk to?
58:52
Or how do I just like do this small trivial task that helps me?
58:56
But then there's this other group of people that say, um, well, there's these huge hundred billion dollar companies that need X done. I'm gonna make that.
59:04
And finding those problems that those huge hundred billion dollar companies have is likely just as hard as making like a chatbot or like you know some smaller thing.
59:13
But it's so interesting to like notice these problems.
59:15
Like for example uh Cloudflare Cloudflare I think about Cloudflare because I'm like I didn't even know like when I learned what Cloudflare was I was like I don't know what a CM uh what do they do? Uh content >> Yeah.
59:28
I was like I don't even know what CDN means.
59:29
Like how do you even know what that means?
59:31
let alone enough to like invent a solution.
59:32
Or when you think of like Palunteer, you're like, how did the founders of Palunteer even like come to the conclusion that organizing data is the way to solve terrorist attacks?
59:42
Like just like the the the cuz it's easy to understand how why people would buy that.
59:47
You know, I will help prevent terrorist attacks or I will save you money.
59:51
But like to even notice that there's these huge problems that these massive companies even have.
59:57
That's an art that I'm in awe of that these guys have.
1:00:01
Paul Graham has this great essay called great work or how to do great work and in it he describes this exact thing where what he what he says is um he says many things it's like a very very long essay took me like 3 days to like chew through this thing but one of the things
1:00:15
he talks about is you want to get to the frontier of whatever domain you're in so for example um it doesn't really matter it doesn't have to be like super high-tech like maybe you're just in um electronic music you're really into EDM and making songs. Well, at the beginning
1:00:30
Well, at the beginning when you're when you're a beginner, you're think about yourself being like close to the center of the circle.
1:00:38
You're kind of where the mass is, the center of mass.
1:00:40
And your goal through your curiosity and through your hard work and through your um uh experimentation, just doing just doing lots of stuff, you're going to move from the center of mass where most people are have have, you know, basic understanding of something, you'll move out to the frontier.
1:00:57
So, you move to the edge of the circle.
1:00:58
And when you're in the center of mass, the edge of the circle looks smooth.
1:01:02
It just seems like seems like people got it all figured out that the people that are out there, the companies that are out there seem to be doing their thing.
1:01:09
The world has a nice nice circular shape to it. It's one smooth line.
1:01:12
But when you get closer, you realize it's actually quite jagged and there's lots of gaps that are in that frontier.
1:01:18
And then he says basically your your job is to get to the frontier of knowledge.
1:01:22
Meaning like you know so much about electronic music.
1:01:24
You actually have used all the different tools.
1:01:27
you understand um you know you've made you know hundreds of bad songs.
1:01:32
You've been to the conference where all the artists are at.
1:01:34
You've talked to the companies that build the tools behind the thing you're at.
1:01:37
You've understood what they're doing.
1:01:38
And when you notice what's missing, your job then as an entrepreneur is just to bridge that gap.
1:01:44
Like wherever there was a little gap in the circle, fill it in.
1:01:45
And so that's like something like Open Router.
1:01:48
If you're inside one of these tech companies and your AI bill is going through the roof and you're like, "H, this is annoying."
1:01:54
Like why are we paying OpenAI so much money?
1:01:56
Why are we paying Anthropic so much money?
1:01:58
Well, it's because when Sally in marketing wants marketing copy, we're just using this like very expensive model to write the caption for our Instagram post. We don't need that.
1:02:09
But maybe when our R&D team is doing this like really heavy duty endeavor about video compression, we do need to be using the top model. Okay.
1:02:19
Well, how am I going to train everybody to do this?
1:02:20
What if I didn't have to train?
1:02:22
What if I created a little router in the middle? I send the task there.
1:02:26
>> It uses its judgment to decide which model to use.
1:02:28
>> Um, and you would notice that because you're inside these companies seeing how seeing, you know, one of the pain points that you have and you say, well, if we have this problem or our AI bill keeps going up and we don't want to stop using AI, we just want to use it more efficiently.
1:02:39
Wait, every company in the world is going to have this problem.
1:02:42
And then you build the company off it.
1:02:43
By the way, the guy who did open router also built OpenC.
1:02:47
>> Yeah, I was I was looking at that and I was like, oh, do you remember NFTTS?
1:02:53
He uh and he worked at Palanteer.
1:02:53
Um did they they sold for 10 billion nearly how much money did they how much money did they raise? >> Um I don't know. >> Only 150 million. >> Yeah. >> Wow.
1:03:09
>> I think it's only a few years old, right?
1:03:11
>> Dude, this is just incredible.
1:03:11
This like wealth creation in such a short time is astronomical. It's hard to fathom.
1:03:16
I mean the the number of companies that will launch and then be like we have a hundred million revenue run rate.
1:03:22
We have a billion dollar run rate.
1:03:27
It's that used to be a number reserved for like one company every few year every five years.
1:03:35
>> Groupon Groupon was the first company I think to get to a billion valuation maybe a billion in like gross sales and it was like uh the big I mean it was like the most talked about thing for the longest time.
1:03:46
Well, it hasn't been that long, but I still think that um when these companies have got big so fast, maybe I'm like maybe it's the hater inside of me, but I thought I was being logical where I'm like, well, if it got big that fast, the likelihood that it can go away fast is is also high.
1:04:00
And I've been thinking that for about 12 or 18 months since this all started happening.
1:04:06
And it doesn't seem like that is entirely true yet.
1:04:09
Like that >> I I think your general principle, I think, has been proven to be true.
1:04:14
It's called Lindy, right?
1:04:15
Like if something's been around for a long time, the odds that it's going to be around for a long time are high.
1:04:21
That doesn't mean you will.
1:04:24
It just means the probability.
1:04:24
I think similarly, you know, the faster they rise, the, you know, the faster they fall is also probability wise higher than a company that took 20 years getting to a billion brick by brick.
1:04:35
Um, but that doesn't mean it's going to happen and and it won't happen to all of you.
1:04:42
>> Does not seem like it's happening or at least it's not happening as much.
1:04:44
couple just in the last I could scroll my timeline right now and see three of them.
1:04:49
And so, you know, Higsfield just announced they had a billion.
1:04:51
Higsfield was just like a uh AI tool to make videos.
1:04:56
>> At first, I think it was just like photos, wasn't it?
1:04:59
>> Um yeah, it was like cool artsy photos, now it's videos.
1:05:02
But they were like, yeah, billion dollar run rate.
1:05:05
>> Um another one that's like that is um Jev.
1:05:09
Jev. So the one of the dudes who made um chat GPT so you know caveat uh there's a lot of people who claim to be the co-creators of chat GPT um but like this is one of the guys he launched this thing that basically is like a different way of
1:05:25
doing um like a different type of model for doing logic that's supposed to be faster and cheaper and I think you know their launch video was like two weeks ago and they said they're at a $und00 million like kind of revenue pace now. It's it's insane. Um, I invest in this It's it's insane.
1:05:38
Um, I invest in this company called SF Compute.
1:05:40
Have you heard about this company?
1:05:43
>> No, but I love that name.
1:05:44
>> So, this guy's fundraising strategy was great where he announced the company.
1:05:48
Just recently, he just announced uh they signed $245 million worth of new contracts.
1:05:55
Just a casual $250 million, you know, revenue update.
1:05:58
Um, by the way, we didn't even mention this.
1:06:01
Um, I guess they it looks like they changed it actually up until weeks ago.
1:06:04
Well, I mean, I only been using Instinct for a month maybe or 6 weeks. Their website, instinct.
1:06:11
com, it was a plain white background with one paragraph.
1:06:17
And I don't even think you could sign up.
1:06:20
I don't remember exactly, but maybe if there was, it was like just enter your phone number.
1:06:24
Now, look at their landing page.
1:06:25
It's still the same, but it's pretty awesome that this is a company that just raised at $10 billion and their website is just uh five sentences and a stick figure of a human on top, which I like.
1:06:40
I think this guy's done a good job of building a more like a less techny product.
1:06:46
So for example, just saying it's a personal assistant instead of saying it's an AI agent that I mean AI agent is like back when people used to call the internet the information superighway and and like that you know calling it cyerspace you know that's how people used to talk about the internet called cyerspace.
1:07:08
>> How old is the kid who started it? >> He's young.
1:07:11
He's in his like early 20s I think his mid20s.
1:07:15
God, >> he's very he's the babyfaced assassin, >> dude. Noah is so cool. This is awesome.
1:07:24
He It kind of This His branding reminds me of uh when notion started and I like that. >> Is he really?
1:07:29
>> He dropped out of Nor Eastern three years ago.
1:07:33
>> Oh my god, that's so awesome. This guy's awesome.
1:07:36
>> Well, do you want me to keep saying how hot and awesome he is, or do you just want to end it?
1:07:40
We should probably cut it off there.
1:07:45
You know, I I think even as I say all these, I think um >> to it's like you simultaneously have the feeling of like, wow, that's really cool to overwhelm, which is, oh god, like I got to keep up with all this to hater mode, which is they're just throwing out like 7 half billion, 11 billion, 19 billion, 23 years old, like all these numbers that feel disconnected from reality.
1:08:13
And um I think instead the thing to do is to just um go outside and do the Macarena that we get to live in this world where all these amazing we get to be alive when all these amazing things are happening and we don't have to do any of the work to make any of this stuff happen.
1:08:28
We just get to use all these tools and get the benefits of this.
1:08:32
And also even to be frank like some of the the there's so much unknown good and bad about what's going to happen.
1:08:37
And frankly there is something exciting about that that um you know like the world is not just as predictable and um everything's going to be the way it was uh as it might have been in other eras of life.
1:08:49
Like you know if you think about the change in different decades like you know from the 70s to the 80s or the ' 80s to the '90s or '95 to 2005 like yeah something's changed 2005 to 2015 it's like yeah something's changed but how much really changed last 10 years how much really changed and I feel like the next 10 years things are going to really change.
1:09:07
It's going to be like one of those periods.
1:09:09
>> I definitely don't feel a sense of missing out.
1:09:11
I guess partially because like I'm secured, but also uh it's so clear that this is like an IQ game. Like I'm not in that.
1:09:22
Like you know what I mean?
1:09:24
It's like someone who's like 5'2 being like, I wish I could dunk and play basketball.
1:09:29
It's like why why bother? >> Yeah. Yeah, that that's right.
1:09:35
Uh, so I think it's going to happen anyways.
1:09:38
Might as well feel good about the way about it. You know what I mean?
1:09:40
What what's the what is the upside in feeling nervous, worried, um, you know, pessimistic or jealous or envious about what's going on?
1:09:50
>> And I'm more than happy, like I said, to take the crumbs.
1:09:52
Like I that's how I feel like, you know, like I'm benefiting like way downream, but >> right, >> totally fine.
1:10:00
>> totally fine. I saw this clip of Dwar talking and as a thought experiment he goes um let's say that uh you had this here's a here's the would you rather would you rather go back to the 1500s so the year 1500 but I will make you the wealthiest man in the world so you can
1:10:17
I'll give you any amount of money so like you're going to show up in the 1500 with gold bags all around you but you live in the 1500s where people are dying of this and that and >> the mortality rate is like one in five >> I think is way higher than that. I think
1:10:30
I think yeah, even even higher than that.
1:10:31
And um but you get to be the richest man alive or you could be a normal person today.
1:10:38
What what amount of money would you need to go to the 1500 to go to the year 1500?
1:10:43
>> I don't think I would do that.
1:10:43
Would you would you do that?
1:10:45
>> So the answer is there's no amount of money and and I don't my honest answer is I kind of got to go look up what life was like in the in 1500.
1:10:53
I want to go see how bad it would be.
1:10:56
>> People die from the cold. Yeah, you get a flu.
1:10:59
>> You know, the most beautiful woman in the world be feeding me grapes all day.
1:11:02
Maybe >> have you seen photos of them? They're not that hot.
1:11:06
>> It's like, yeah, bro, there's no shower.
1:11:09
>> Yeah, they weren't that good-looking.
1:11:12
Like, >> I haven't seen photos.
1:11:13
There was no photos back then.
1:11:16
>> I like Have you seen paintings of like some of these pe like they weren't like like Napoleon was the most Napoleon was like the most powerful man in the world and this lady named >> if I'm short? I'm not going back. >> Uh, sorry, not Maria.
1:11:29
Um, Napole Josephine, Napoleon's wife, like she totally like had them wrapped around her finger.
1:11:36
And go and look at photos of her.
1:11:38
Like, she she wasn't even that good. >> Uh, okay.
1:11:40
Life expectancy was 30 years old because so many children died young.
1:11:46
If you made it through childhood, you could make it to your 50s or 60s. Nobody could read.
1:11:50
Most people uh most people never never traveled more than a day's walk from where they were born. Um that's pretty crazy.
1:11:58
So the idea of travel um >> dude just Google Josephine Napoleon so you can find out what his wife looked like.
1:12:05
This was the most powerful man on earth who could have anything. >> Okay. Okay.
1:12:12
Joseph, she's not bad, >> dude.
1:12:15
She might be a medieval 10, but she's a New York 4. All right, that's it.