0:00
[music] I see a large IP on the horizon.
Search this video
0:09
You're [music] surrounded by journals. Hold your position.
0:22
[music] Overnight success.
0:28
The place maker 3000 double blade [music] right misinformation. clearing order inbound. >> Let's just roll.
1:09
>> We are surrounded by general. Hold your position. Come. Get up. Trust the experts here. [music] Five. We are founder Mal.
1:40
[music] I see multiple journalists on the horizon. Stand by. [music] UAV online. [music] Blaze blade. [music] Double blaze. Triple blaze. [music] Double kill. Fight. Wrong. Cop win. >> Team deathmatch. We are expert. Triple blade. Let's [music] just roll. Right.
3:07
>> Clearing order inbound. Come on. [music] Get up.
3:21
We [music] are surrounded by journalists position. >> Strike one. >> Strike two.
3:43
Activate [music] golden retriever mode.
3:58
Marky clearing [music] order inbound.
4:03
>> 5 I see multiple journalists on the horizon.
4:20
Standby founder >> naughty naughty.
4:31
[music] >> You're watching TVPN.
4:35
Today's Monday, August 3rd, 2026.
4:38
We are live from the TBN Ultradome, the temple of technology, the fortress of finance, the capital of capital.
4:47
Let me tell you about ramp. com. Time is money. Say both.
4:49
Easy use corporate cards, bill pay, accounting, and a whole lot more all in one place.
4:54
How was your weekend, Jord?
4:55
>> Uh, my weekend was good.
4:56
>> Yeah, >> my weekend was a little hot here in Southern California, but uh all the more reason to get to the beach, enjoy the nice weather.
5:05
>> It's been a good [clears throat] summer >> on a boat. >> That's nice.
5:07
>> What more can you ask for? >> That's nice.
5:08
Uh we got a great show today. >> We do.
5:11
>> Uh unfortunately only one venture capitalist and I think that's [snorts] because it's August. >> Oh yeah.
5:17
>> You're going to see us really struggling.
5:18
>> It's going to be hard to get those VCs to >> get those VCs every other month. >> It's hard.
5:23
>> They're happy to jump on same day moments notice.
5:26
>> You know it's important. >> We got one today. >> Yeah, we got one.
5:29
>> Sean Magcguire coming on with Isaiah Taylor announcing a $1 billion series B led by Sequoia. >> Very excited.
5:37
>> Very excited for that conversation.
5:37
We got Justin, co-founder of Base Power, another $1 billion round series D.
5:40
And then we have uh the very the the founder of the demon robot. Yes.
5:49
>> That you may have seen last week.
5:49
It's a centaur with horns. >> Bo Geston.
5:54
>> And uh we're very excited to talk with Bo and and get a sense for what went through his head >> when he made robot like that. >> Can you stop? [laughter] Can you not?
6:06
Can we pull up a picture of the robot?
6:08
[clears throat] Uh, I want to I There it is. There it is.
6:09
So, this is the friendly robot that B is excited to get into disaster zones to help rescue people.
6:17
>> And apparently the horns are critical because there are cameras on the end of each horn and that allows to see the ground, which couldn't couldn't put those cameras anywhere else.
6:27
I guess >> it'll be a lot of fun.
6:30
>> Uh, and then closing out with Ron over at Intology, but >> fun.
6:34
>> Let's get into the show.
6:34
What happened over the weekend?
6:35
Did anything happen over the weekend, John?
6:38
>> Uh there were there were a couple things.
6:39
Uh the the big uh the big debate that I was tracking sort of outside of tech, but tech adjacent was uh the cancellation of Hank Green, the YouTube creator.
6:49
Not quite a cancellation, uh more just some backlash.
6:52
Hard to always put a uh a proper sizing on a mob when a mob comes after a creator.
6:58
Uh but uh Hank Green, the YouTuber and really media entrepreneur, uh he's grown a huge business, which we can sort of go into.
7:09
Uh is getting pillaried on social media over using chat GPT for research.
7:12
Very controversial these days.
7:16
Only a billion people do it, [laughter] but and it's the number one app in the app store, but he's getting he's getting a lot of backlash from certain members of his audience.
7:26
I don't want to characterize the whole audience as being part of this, but uh it's a very sill silly.
7:30
>> There's at least thousands of people.
7:32
>> It seems like it's always hard to tell.
7:35
I mean, thousands of people that are liking a post about it.
7:36
There's like maybe dozens of posts.
7:38
I don't really know how to put how to put a scale on these things, but uh Hank Green is definitely going through it having to sort of apologize or qualify or sort of, you know, state that he will adjust things in the future.
7:50
Uh and it's just sort of interesting to hear how he went through this process.
7:53
uh what he says is going to change and where the backlash is coming from because there's a lot of misunderstandings about it.
7:59
So um and what's interesting is that he is a science and education creator and science and education are potentially the most affected by AI right now.
8:07
And so uh it's a real challenge to simultaneously say I'm going to cover math.
8:15
I'm going to cover science but I'm not going to touch AI. That AI stuff's bad.
8:19
Because as we also saw over the weekend, AI is making a bunch of advancements on math.
8:25
We've been saying this for a while, but the latest version uh of the story comes from Nome Brown polomial over at OpenAI.
8:31
He says an an internal version of Astra, OpenAI's next major frontier uh ma next major model family solved 10 major open problems in mathematics, quantum complexity, and theoretical computer science.
8:44
the the achievements are so so extreme at this point that I don't even think it's worth us trying to break them down.
8:51
Like we did that with the uh distance problem.
8:55
>> Tyler is going to run a 5K here in the Ultra Dome to do a little victory lab for the research team.
9:02
>> But not everyone is impressed with it because Gary Marcus says, "Wake me when Astra solves a significant open world problem that doesn't revolve around formal verification."
9:11
And uh of course Daniel Eth e says the goalposts are on a completely separate planet. Uh it is a good point.
9:20
Obviously AI is doing better in formally verifiable tasks.
9:22
Uh at the same time still impressive because there's a lot of things that are useful and verifiable like did this drug cure your cancer or not or did this job get done or not.
9:34
Like we've been using these recommener systems for lots of things.
9:37
They're very valuable all over.
9:37
Uh but it is funny uh the debate over is this AGI, is this ASI, those terms will always be vague and we dig in. >> Going back to Hank. >> Yes.
9:50
>> So all he did was admit that he used some sort of AI tool for research. >> Yes.
9:57
So I will take you a little bit more through it.
10:00
First I'm going to tell you about Shopify.
10:00
Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on market places, and now with AI agents. They got AI on Shopify.
10:07
So, if you're selling something, you're you're you're using AI.
10:11
So, uh Hank Green, he's an OG YouTuber.
10:14
He joined YouTube in 2007, I think less than two years after the platform actually launched.
10:19
Uh and he grew he got a lot of views, but he also built a huge audience and uh created a real media company around it.
10:27
So, he has uh Vlog Brothers, like a vlog channel.
10:30
Then he has Crash Course, which is a really really huge educational channel.
10:35
Uh he runs VidCon which is basically the the premier conference around YouTube and the creator economy.
10:44
I've been I think once or twice.
10:44
Uh it's a lot of fun and uh over the last 20 years he's become one of the most trusted educational creators on the platform.
10:52
He's also just like he gets the vibe of YouTube very well because he's been been around it so long.
10:55
Never really stepped back fully, but uh always been, you know, solid audience there.
11:02
Um, so last last Wednesday he published an episode of a show called Ask Hank Anything.
11:07
And it's an interesting concept for a show.
11:08
So he brings on a guest, but then instead of just doing the interview, tell me your life story, ask the ask the guest a whole bunch of things.
11:16
The guest brings questions for him about science or whatever, they they have a big long conversation.
11:22
And if there's something in the show that he can't answer on the fly or he's not prepped for, he will go do the research and then get the actual answer and then cut that into the final episode.
11:32
So, you'll be watching them hang out.
11:35
They'll talk about some odd thing.
11:35
He was talking about this.
11:39
Have you heard this Kiki and Bubba thing?
11:40
There's like two words that uh that one uh basically there's two shapes.
11:46
One's like a fluffy cloud, the other's like spiky uh spiky like star essentially.
11:51
And if you ask people generally which one would you assign the word Kiki to and which one would you assign the word ba to?
11:57
People always pick buba is the cloud and Kiki is the spiky one.
12:02
And it's like the sound of the word has a shape to it even and this is just something in our language that shows up all over the place.
12:09
So he's like telling the story of this like just somebody ran a science experiment.
12:13
They you know put a bunch of people here.
12:15
They pulled a bunch of people.
12:16
They put together this result and this is what happened.
12:18
And so he needs to compile all of that quickly because you get off the show, you have your rest of your job, but then you have to go answer these questions and have all the information.
12:26
And uh and of course he uses all sorts of research tools.
12:30
Um but uh he was accused specifically of using Chachi PT to write the script, which is interesting because uh after the episode went up, manager Jojo posted a clip of him from the episode and accused him of using Chachi PT to write the script.
12:43
Uh, the key line is Hank saying, quote, "I appreciate the push back."
12:49
And that's sort of an AI phrase, but that wasn't one of the really trigger AI phrases like, "You're absolutely right," or, "It's not this, it's that."
12:58
Uh, I appreciate the push back is something that the AI models say occasionally, but you wouldn't think it would make it into a script, but that's why people jumped on it.
13:06
They were like, "Wow, he was so careless that he left in a turn of phrase that was the model talking to him about, I appreciate the push back."
13:14
Uh, that's not what happens.
13:16
He's actually responding to the guest pushing back on him and about this concept and then he answers it.
13:22
But, [clears throat] um, >> uh, he was just talking, but it's but it feels out of out of place because he's talking to the camera at that point.
13:31
Even though in the video he's talking to the guest after the fact, the way it's edited is him direct to camera.
13:36
So him saying I appreciate the push push back to the camera. What is this beans? I don't know.
13:43
Uh but him him saying that I appreciate the push back uh feels a little weird when you just watch it, but it makes sense in the context of the longer video.
13:51
Um so uh the headlines proliferated over the weekend to the tune of Hank Green accidentally reads AI prompt feedback left in his script.
13:58
Uh Hank has to not has to deny this, but he goes on to admit that he does use chat GPT for research.
14:08
Uh this did not land well.
14:08
People don't like the idea of him using CHP research.
14:13
Uh and [snorts] clearly it's just a small subset of his audience that actually takes the time to flame online about AI usage.
14:19
But uh it is a there's still dozens of posts maybe hundreds of posts about how AI cannot be used for research because it hallucinates or it removes some key human element of the process of learning something like that.
14:32
Uh it's very odd for anyone who's used modern models because uh there's a lot that AI can't do well uh yet.
14:37
But uh pulling a bunch of links and quotes together from across the internet is something pretty good at >> [clears throat] >> um and it's definitely reliable for that.
14:48
Uh, and so Hank clarified the script was not written by AI.
14:51
He was just going on Chhat GPT and saying like, "Hey, where where did this original research come from?
14:56
Pull up the paper, download the PDF, crunch it all together for me, you know, pull some quotes from it.
15:01
Uh, change this into a different format.
15:03
I want it in this units instead of that units."
15:05
Those types of questions.
15:07
Um, but um, he still said that he has not been happy with how he's been using AI and may wind up publishing less as a result.
15:15
He feels like he's on a little bit of a treadmill because he's more productive with AI, but then he posts more and then that's a feedback loop.
15:22
And of course, like at this point in time, he's like built his career over 20 years.
15:26
He has a very sustainable business.
15:28
He probably doesn't need to be on on as much of a treadmill as perhaps an early stage creator might be.
15:31
Um, so it doesn't feel like it's total audience capture, but there is this interesting opportunity here that I was sort of uh just identifying.
15:41
Uh, like AI is clearly this wedge issue.
15:44
Billions of people use AI and get value from it, but at the same time, it's deeply unpopular.
15:47
And there's lots of people who like to post angrily online about how AI is bad for a variety of reasons.
15:53
But education and science in particular are going to be intertwined with AI for the foreseeable future.
16:00
Like every advancement in science is going to be AI enabled.
16:03
And so if you're a science educator and you constantly have to be dancing around AI and be like, "Oh yes, like they solved this math problem, but I don't like it because AI was used."
16:12
well, you're going to wind up just not being able to talk about math or science or whatever's happening because you're you're constantly doing this dance around AI. Um, and so that's fine.
16:23
There's that audience that will love that.
16:25
Uh, but there's also an opportunity for a new audience that's maybe a little bit more nuanced about this and maybe just, yeah, it's fine that you use that for doing research.
16:36
Uh, maybe as long as the script sounds good, I'm fine.
16:38
or as long as you uh are clear about your policy, which is odd because that's what he he was always clear.
16:45
He's just still got attacked and had to go on this defensive.
16:48
I I believe he has like a published policy around how him and his employees at his media company can use AI or do use AI or don't in various scenarios.
16:58
Um but this was the first time I've seen a like real backlash to just pulling that up on on chatbt.
17:02
Uh, I totally understand there.
17:07
I mean, there are people that could just use AI to generate the video [laughter] >> and not be involved at all or use it in the script or use an AI voiceover.
17:17
>> It's just funny because I have this uh this reaction all the time. >> Yeah.
17:23
>> When I realize a video on YouTube is just fully it's a fully AI generated script.
17:28
Somebody's just reading over. >> Yeah.
17:29
Or or AI voice is reading it. Yeah. Uh Yeah. Yeah.
17:31
It sort of just depends at the end of the day.
17:33
It's just like is the is the content quality?
17:35
Is the insight uh valuable?
17:37
And what I would go to Hank for would be uh he does a bunch of research across a whole bunch of tools.
17:45
Google, chat, whatever he uses.
17:47
Read a book, read papers, watch documentaries, listen to podcasts about a topic and then tell me what Hank thinks is interesting about that that the the filtering process and the taste is what >> Back in your day growing up, did teachers ever say, "I really don't want you using Google for the homework."
18:04
>> No, there was never push back against >> Google didn't exist.
18:09
>> There was push back against Wikipedia.
18:10
It was it was like, "Oh, Wikipedia is unreliable.
18:12
anyone can edit Wikipedia, so don't use Wikipedia as a source.
18:15
Um, which really just means >> Well, that was fair.
18:19
Go to the go to the original.
18:21
>> And it's kind of the same thing with Chad PT.
18:22
It's like don't like go to the source that Chach links you.
18:24
And if that's a paper and it's academic and it's hosted on the right thing and it's has the right uh the right um provenence, then it's okay to use. Um I don't know.
18:36
It'll be interesting to see how how this all fares.
18:37
there's uh there's a lot of backlash, but uh it it was sort of like a a lot of people in tech, I think, were getting like sort of whiplash from from watching uh all of these arguments pile up.
18:47
Someone put together a cool chart here of uh the good arguments and the bad arguments from the pro-AI crowd and the anti-AII crowd.
18:55
So, an example of a good argument around this from the pro-AI crowd would be AI is a powerful and capable tool.
19:03
And then uh like a bad argument from the anti-AII crowd would be AI is useless in re in research slash in general.
19:08
Um but there were bad arguments that were put forth by pro- AAI people.
19:13
Uh something like you use you use uh you use data centers like Hank uses data centers and it's like yes YouTube is hosted on a data center in >> so are you to write this comment.
19:26
Yes, but that's not that the the actual like data center that's required to host an online comment is wildly different than a massive Gen AI system like cooking tons of tokens and actually uh setting the GPUs on fire, right?
19:40
Uh and then a good argument, the best argument from the anti-I crowd was said that AI usage in science communication reduces trust at least a little.
19:49
Uh which is which is interesting.
19:52
I mean, uh, yeah, you do have to check these things.
19:53
And we do see tons of examples of people actually leaking, uh, you know, AI phrases and and weird AI, um, like hallucinations into scientific research.
20:03
There was that example of there was some PDF that was scanned and there was a word on in one column and a word in another column that got bled together when the document was imported and then a whole bunch of AC a whole bunch of scientific research started referencing this phrase that doesn't exist and just came from basically a hallucination or like a a quirk of the optical character recognition.
20:27
So anyway, uh they canled my goat for using LLM to search papers that he would need to read to make his videos.
20:34
They want him to use Google search like a caveman in big 2026.
20:36
That about >> the crazy thing is I don't Can you Can you even turn off AI mode in Google now? Maybe. >> I think you can. I think you can.
20:45
You could use Duck Duck Go.
20:46
I don't think that has AI yet. We'll see.
20:49
Anyway, uh Jeremiah Johnson says, "I'm fascinated by Duck [laughter] Duck."
20:55
>> Wait, is it really by Duck Duck? >> No. No. No, wait. Are you You're serious? >> Yeah. Go to duck. ai. com or no, just duck. ai. >> I like duck. >> That's a good name. DuckAI. There you go. >> Using GPT 5. 4 Nano. >> There we go. Okay. >> Unavoid unavoidable. >> Wow. Yeah.
21:11
Uh the market has spoken, I suppose. Yeah. What do people do?
21:14
I I I imagine you can turn off AI mode somewhere in the settings.
21:18
Uh, or at least you could uh or or at least you could um you know get some sort of Chrome plugin that that that deletes that like an ad blocker if you really really cared.
21:31
But uh it seems like a lot of work at this point.
21:33
Anyway, um >> this was uh interesting.
21:36
Ryan Lo on X is sharing a heartbreaking essay by a mathematician last week before this most recent news drop.
21:45
So this was before Gnome Brown >> Yeah.
21:48
uh showed uh the uh recent breakthroughs by Astra said, "There is nothing I can do.
21:54
There may be nothing you can do.
21:56
I have no prescriptions, policy recommendations, or coherent call to action.
21:59
I just want to be honest and open about my emotional and spiritual response. I want to feel seen.
22:05
I want folks like me to feel seen.
22:08
I need the architects of our new mathematical paradigm to look me in the eyes and acknowledge our shared humanity and soul before they deliver the coupe degra.
22:17
I need most of all for us to understand what we are really doing.
22:22
>> The dark knight of mathematics.
22:22
Kerwin Hampshshire, mathematician, researcher from the University of Auckland who recently authored the viral essay, studied mathematics. Um, interesting.
22:31
I I it feels like um I would be surprised if if mathematical education goes away.
22:40
It feels like a lot of these problems should be interesting to apply.
22:44
But I understand that that's a different that's a completely different discipline.
22:49
discipline. Um it will be interesting to see what happens next because there are more advanced problems the the the the Millennium Prize problems P versus NP Navier stroke Stokes right uh there there are a number of problems that are still unsolved what happens when they're all solved do we create new problems
23:09
where do we go from there do we start applying them in different ways what do you think Tyler >> yeah I mean obvious like >> got any advice for mathematicians >> I I think so so in this art article he says like math Maticians are paid to like solve >> 21-year-old podcaster has advice for math. >> Exactly. [laughter] Like so he says like >> Exactly.
23:25
[laughter] Like so he says like mathematicians are are paid to solve theorems which like look I I don't obviously I'm not in academia but like it seems like that it's like kind of their job but also it's like you're in a university, right? It's like teaching. >> Yeah.
23:37
I mean there's plenty of there's plenty of math professors that they sort of try and solve theorems but also mostly teach and uh you know don't solve that many theorems or >> Yeah.
23:45
And also like presumably if you can solve all these conjectures like there's going to be new questions that open up.
23:50
This is like the entire history of all science, right?
23:53
>> Yeah, it will be interesting to see the application of this stuff because it's so abstract at this point and and and uh it's it feels like it's very everyone's saying like okay based on this like this is going to like flood through material science and flood through uh chemistry and biology and that would be awesome.
24:11
everyone would love, you know, oh, all of a sudden like the electric cars have twice as much range because we solve some fundamental thing.
24:16
Um, it'll be interesting to see where the new bottlenecks are.
24:21
There of course will be always math professors hate AI for one simple trick, just scale, scale, scale, I suppose.
24:28
Let me tell you about Railway.
24:30
Railway is the all-in-one intelligent cloud provider.
24:31
Use your favorite agent to deploy web apps, servers, databases, and more.
24:34
While Railway automatically takes care of scaling, monitoring, and security. Boom.
24:43
Um, >> what else is going on? >> Lots of Yeah.
24:46
Uh, this [laughter] I just like this Gary Marcus.
24:50
Uh, he's really uh he's really in the arena with this.
24:55
Um, there's this uh post.
24:55
I >> It's a really good bit. >> Which one?
25:00
>> Like I the Gary Marcus bit. >> It's not a bit. He really believes it.
25:04
>> No, but I think at at some point he flipped into bit mode. >> The pure LLM. Yeah.
25:08
So he he he will always uh take issue with the idea of something being a pure LLM.
25:13
A pure LLM solving something. And uh who is it?
25:15
Ham says the LLM use a calculator. Burn the impure bro. Horses are very useful.
25:22
This is likely not a pure horse.
25:25
Pure horses still can't carry an entire family and they don't have wheels.
25:35
Oh, the goalposts are on a completely separate planet now.
25:38
Uh, [laughter] first they came for the mathematicians and that sucked because I was a mathematician and really did not expect that, not going to lie.
25:47
Uh, it will be interesting to hear from Terrence Dao.
25:50
He's been talking about how he uses AI and math and has been uh sort of a white voice every time I've heard him talk.
25:57
So, uh, will be interesting to see how he reacts to the latest round of of advanced mathematics.
26:01
Uh what John what is left?
26:04
>> It's time >> what >> it's time to talk about the rise of one person $1 companies. >> One person $1.
26:12
>> Now in the Wall Street Journal >> million dollar companies of million-dollar companies with just one employee.
26:17
>> Let me tell everyone about console build.
26:19
Console builds AI agents that automate 70% of IT HR and finance support giving employees instant resolution for access requests and password resets.
26:26
>> Wall Street Journal is saying AI tools make it easier for founders to get started alone.
26:30
and many stay that way as they grow.
26:33
Ben Broca launched a company last December that offers AI tools to entrepreneurs. >> That name's familiar.
26:38
We've had him on the show.
26:40
>> Already added 10,000 paying customers and is on track to bring in 10 million in revenue this year.
26:45
One thing he hasn't added any other employees.
26:48
The 40-year-old is part of a class of entrepreneurs who are launching and often running new companies on their own.
26:54
Artificial intelligence tools answer Broca's emails, help write and debug code, field requests from customers, sign up new subscribers, and grant refunds when issues arise.
27:01
Broca relishes his ability to make whatever decisions he wants on his own, often from his sundrenched Saucelo, California living room.
27:10
I think compromises make lukewarm results, he said.
27:14
>> Uh, once upon a time, running a business of a certain size required a team.
27:16
AI is turning that assumption upside down, and more aspiring entrepreneurs are going it alone.
27:22
An analysis by the payments company Stripe, uh, Tyler, look up Stripe, shows there are thousands of solo operators on the company's platform that are generating over 1 million in revenue with their ranks doubling between 2023 and 2025. >> That's pretty crazy.
27:37
So, this is on Pulsia, right?
27:40
>> No, no, no, no, no, no. >> Oh, on Stripe? >> Definitely not. Okay. >> This is just Stripe. >> Okay.
27:44
Um the number of solo I'm sure I I would be curious if Pulseia has any companies that do more than you know >> a thousand >> $1,000.
27:53
[laughter] >> I mean you were looking at those >> cuz cuz to be honest cuz to be honest like I actually do think success for Pulsea is like >> just making back a do like even a dollar more than you're spending on on Pulsia, right?
28:06
Because >> there's a YouTuber who's been demoing different AI systems, Fable and Soul and Kimmy, and saying like, "Go make me money."
28:15
is like basically the only prompt.
28:17
And he lets it cook for like a week.
28:18
And uh he'll be on like a 200 month $200 a month subscription.
28:21
See if it can make six cents. See if it can make $10.
28:25
And he's getting closer every time.
28:28
And he of course has to do some things.
28:30
Set up API keys and do little things.
28:33
But it's an interesting uh experiment.
28:34
Ben Awad, you should go check it out.
28:36
>> So, the number of solo operators, according to Stripe, also crossing the $10 million threshold nearly tripled in that same span.
28:42
In the past, people without business contra contact contacts or particular savvy might not have known how to get their ideas off the ground, said Ernie Tedeshi, Stripe's chief economist.
28:53
Now, AI can be a built-in business partner. >> Yeah.
28:56
Wait, how does uh how does Stripe know if you're a solo operator?
29:01
Like if you're because if you're a podcaster and you set up a Stripe account to accept money from advertisers, you could be having a million dollars move through there.
29:09
But if you hire an editor or not, that doesn't necessarily show up in Stripe.
29:14
So they must do some sort of polling and ask.
29:16
>> Yeah, I think I think in your account at some point you say, "How many employees do you have?" >> Okay.
29:21
Then if you say, "Yeah, I just got one."
29:23
>> But I guess one question I have one question I have with the data is like, "What if you just set up your Stripe account and it's like, "How many employees do you have?"
29:29
you just one and then you wind up adding people and you don't go on update. Yeah, possible.
29:34
>> Yeah, because they don't have the the payroll.
29:36
I I don't know how I don't know how they would have >> visibility into >> into payroll, especially like >> Yeah.
29:44
>> Uh individual employees. >> Yeah. Yeah.
29:46
>> Um they do have a sense for how many people obviously are like added to your account, but sometimes it's like true account if you add your CPA. >> Yeah.
29:53
>> You know, and and that's a contractor, not an employee. Yeah.
29:55
AI's ability to handle various administrative tasks makes it potentially useful for launching solo businesses in many fields.
30:01
But the technology's ability to handle key tasks in tech like coding make that field a particular hot spot.
30:07
Analyzing Census Bureau data, Bank of America's Institute economist Taylor Bowley found that among all industries, new business applications in the information sector >> uh have seen the biggest percentage increase nearly 45% over the past year. Yeah.
30:20
Uh at the same time, the rate of information sector applicants saying they plan to hire workers has experienced the sharpest decline of any measured industry.
30:26
This census data set doesn't track solo operated businesses, but the numbers broadly show in tech and beyond that applications are flat among businesses likely to hire workers, but generally rising elsewhere.
30:37
Economists say that's a strong sign that solo up operators are in the upswing. Wow.
30:41
Yeah, that chart is really up and to the left.
30:47
Uh new business formation.
30:47
This is in the information sector in particular.
30:49
I I want to know more about what uh what these [snorts] people are doing because um at the same time we saw levels.
30:57
io talk about like the the indie hacker sort of uh seeing declining revenues or or more headwinds there because the little SAS product that they would that an indie hacker might build.
31:09
Um I'm thinking of like those those oneoff websites like like YouTube downloader44k. com.
31:17
It's just like a piece of software that people land on through SEO or like something that is like an image background removal website and it just does one thing and it does it pretty well and it scales to six figures or seven figures.
31:29
Those little sites are now getting sort of eaten by models and eaten by other people and you might be able to v code your own but at the same time like they might have a long long term. Tyler update. >> Okay.
31:40
So, so they basically calculate the number of like soloreneurs based on uh how many people have like there's like special plugins or platforms that are directly for like the soloreneur. >> Mh.
31:51
>> So they basically use that to like uh get a proxy of the general like percentage of solo people on Stripe >> on Stripe.
31:58
Oh, they have like a special flow for solo printer. Interesting. >> Oh, cool.
32:03
>> So they say that they're almost certainly underestimating the number.
32:06
Hey, Julian Weiser, I know him.
32:06
Uh, says, "The bar is getting the bar for getting started has never been lower," said Julian Weisser, who runs a San Francisco based accelerator for solo founders working in tech.
32:17
The accelerator, which offers founder seed money and mentorship in exchange for an equity stake, attracted 4,500 applicants for 10 slots made available in its most recent cycle, nearly five times the number it drew when it launched last May.
32:31
Now, he's been growing this a lot, but that that is staggering.
32:35
A lot of people want to be uh solarreneurs.
32:37
Uh going it alone with AI can still be surprisingly expensive.
32:41
Broca said he was losing money on many customers accounts while paying to access anthropics cla to run his clients requests.
32:47
That AI company as well as others charged based on usage.
32:50
He has since switched to free open- source models from China.
32:53
Uh Broca says he has raised $30 million from investors and at the same time has saved millions in salary since he hasn't needed a team of software engineers.
33:01
Another risk if it's easy for one entrepreneur to launch an AI assisted business.
33:05
Copying them can be easy too.
33:07
This creates anxiety for founders like Troy Johnson.
33:08
Johnston who runs an AI assisted business alone in Orlando, Florida.
33:13
Everybody has the sword and we all have the ability to unshath Excalibur.
33:17
Now Johnston, what a great quote for the journal. >> I love it.
33:23
[laughter] >> Oh, he's 40. He used an AI.
33:24
He used AI to code an app that helps people get the most out of credit card benefits. Huh, that's interesting.
33:32
Pick pick which card you want to use because you might have multiple cards.
33:37
One that's good for dining and you build an app for that.
33:40
There's been a few apps that do that.
33:43
The points guy had a whole blog around it, whole media company around it still does, but um uh interesting to sort of like yeah go and go and actually vibe code that.
33:52
A lot of the things it's like you could probably just use the models themselves for this.
33:55
Uh just have a thread that says, "Hey, these are the cards I have.
34:00
go pull all of the data when I'm about to buy something. Let me know.
34:03
But at the same time, there might be some value for something new uh with a deeper integration somewhere.
34:07
Uh the company makes around $3,000 a month in profit with no employees and continuing to grow.
34:13
What a run for John Troy Johnson >> story >> who loves who loves King Arthur related metaphors for business.
34:21
>> Uh what one per what one person businesses will mean for the labor market remains to be seen.
34:25
Polling has shown that Americans are worried that AI will replace jobs and top economists are wrestling with that possibility too.
34:29
But AI is also creating lots of new jobs and the goat alone entrepreneurs show the technology can both open doors and limit employment opportunities.
34:37
If everyone's hiring less but you get four four times more firms, what does that do to headcount?
34:42
Said Rembrand Coning, an associate professor at Harvard Business School who studies entrepreneurship.
34:46
He co-authored a recent study that found that among 50,000 startups the researchers examined those focused on AI tended to operate with 25% fewer employees.
34:57
It's interesting because haven't we seen that that like the ramp data that said that uh AI AI adopting companies were hiring faster but maybe they still operate lower operational headcount but hiring faster because of hiring growth.
35:13
There's like three different factors that are going on here sort of mixing all together.
35:16
Uh Coning, the professor also believes in a s uh believes a soft hiring environment that has left some people mired in logging job searches has encouraged more to try their hand at launching businesses. That makes sense.
35:28
Some founders cite different motives.
35:30
It's a perfect storm of post-pandemic burnout and a re-evaluation of one's priorities and also booming AI and a sense of what's possible, said Samir Ahmad, 39, who lives in Breningsville, PA.
35:39
Two years ago, Ahmad decided to leave the corporate job he had worked at at Verizon for almost two decades to start a solo coaching and consulting business.
35:49
He had been seeing social media posts touting the ease and virtues of AI, which he liked to chart uh which he used to chart a business plan and help with marketing.
35:57
It was like my chief of staff, second in command.
35:58
The business ultimately petered out within months though and Ahmad is back to full-time corporate role with a utility company.
36:06
For Claire Vo, uh, 41, AI helped turn her passing impulse into a business.
36:10
She was working full-time as a tech executive when she tapped AI in late 2023 to help code an app that would help manage documentation and design for new products with customers ra ranging from financial services to healthcare firms.
36:26
I was copying and pasting from Chad GPD, said Vo, who lives in San Francisco.
36:28
Uh, she put her app online for $1 a month. Wow, that is cheap.
36:33
Uh, and within weeks people download >> I thought we didn't know how to make apps that cheap anymore. >> Yeah.
36:39
I mean it is a subscription at least not one time but uh she put it online for a dollar a month and within weeks people downloaded thousands of times.
36:46
Nearly three years later VO's company which he ran solo for nine months before hiring an engineer now has a hund,000 users and is on track to make seven figures in profit this year. Wow, that's remarkable. At a dollar a month. That's crazy.
36:59
AI handles the company's marketing, sales, and customer support. Well, AI is a shortcut.
37:03
VO said her network and credibility in the industry were key.
37:06
I think people overindex how on how easy AI is and underindex on how much I did to get to this point.
37:12
She said she's still >> Yeah.
37:16
I I just want to see I [snorts] want to see five companies >> that uh make more money from their business than they give Pulseia every month. >> Yes.
37:27
Uh, so, so Pulse has has some public dashboards for how much people are spending or something like that.
37:33
>> Yeah, they have a public dashboard.
37:36
Let's see if I can find that again.
37:40
>> While you're doing that, let me tell you about Cisco.
37:42
Critical infrastructure for the AI era.
37:44
Unlock seamless real-time experiences and new value with Cisco.
37:51
And if Jord's continuing to look, I'll also tell you about public investing for those that take it seriously.
37:56
They got stocks, options, bonds, crypto, treasuries, and more with great customer service.
38:02
>> Trying to find the dashboard.
38:02
I was looking at the dashboard that was showing >> there's some there's Okay, I think Tyler found it. Thank you, Tyler. >> Yeah.
38:12
So, right now you can see all the different things that the companies on Pulse are doing or at least some of them >> right now.
38:18
So far today, >> companies on Pulse Pulse have spent $373.
38:26
Is that today >> on ads >> today? >> Yeah.
38:29
>> Well, it's still morning. >> It's still morning. So, we're we're pacing.
38:32
We're only about I don't know what time zone this is in.
38:34
But yeah, the the the big question is like is any of this stuff actually working or is it more like kind of a video game effectively? >> Yeah.
38:44
>> That uh people just enjoy like watching the machine hum, but there's not really much happening.
38:50
much happening. I mean that was the thing for Midjourney and Sununo I think in in many ways like Midjourney when it launched people >> totally I mean >> no >> okay hear me out >> okay I'll hear you out >> okay when Midjourney launched >> the steel man
39:07
>> when when midjourney launched people were like this is going to take artists jobs and it was like okay so if that plays out then I'm going to go to the MoMA and there's going to be a show for someone that just prompted midjourney and the highest auction at Christy's is going to be some midjourney artist. And
39:23
And that's not really what happened.
39:25
Like people aren't using midjourney to make fine art.
39:30
But people love midjourney.
39:33
Like they love the activity of going on midjourney and generating and prompting and getting an image back and then and then maybe they send it to their friends.
39:40
Maybe they use it a little bit, but it's not exactly the same of like the process of becoming a fine artist.
39:48
It's more like they're enjoying the process of just making.
39:50
It's more like just having a guitar that you just like to practice and noodle on versus like actually being a touring artist.
39:56
And so like that's certainly my experience with Sunno is it's fun to try and make a song and then listen to it and then be like wrestling with the thing and and and it's possible that that could be the same activity for like okay I'm gonna go build an online business, see if I can get something out, but it's not really like a job.
40:16
It's more of like an entertainment product. Yeah. I don't know. What do you think? >> Yeah.
40:20
I mean, you could easily see it turning into like Enders Game scenario where it's like a game and then it's like, "Oh, that was actually a real business you were starting."
40:25
Ender, you know, >> you offshored the last job.
40:27
[laughter] You sent you sent all the labor overseas.
40:34
You rolled up the entire HVAC industry.
40:37
That wasn't a simulation. No.
40:37
Uh do uh based on my steel man, do you agree or do you still disagree?
40:43
No, I just think that you could use MidJourney to create a beautiful asset that you could get some enjoyment out of or you could use it for your business or whatever you're doing. >> Yeah.
40:53
>> Um or to just create AI art.
40:53
Uh and you could use Sununo is just like deeply entertaining.
40:59
You go on there and 5 seconds you make a real song that sounds like it was recorded in a real studio. >> Yeah.
41:07
>> Yeah. And there might be something to like okay it is fun to go and build a SAS product like it is fun to go the pro like the game it's a game right I don't know Tyler >> uh okay just on your example earlier of like the MoMA artist like that's like the insane long tale of artists >> that's not like the average you know center of the of the curve artist that
41:28
like >> okay >> majourney like maybe is like doing a similar thing to what are producing >> maybe yeah maybe I don't know I I I I would just be surprised if uh if if the I don't know may maybe the way to put it is like I'd be surprised if like the like the majority of midjourney users are using the product >> as a as a like a an artist career path an artist career path. Like they're
41:56
Like they're like, "Okay, I got my image.
41:57
Now I need to get it printed.
41:59
Now I need to go do a small gallery show.
42:01
Now I need to go talk to an auction house.
42:03
Now I need to go and pitch it to a bunch of collectors and like and go through the process of being an artist.
42:10
I think a lot of people are just like cool I got an image. Like this was nice. Like job's done.
42:14
Now back to whatever else I was doing.
42:16
Oh, like I have some free time.
42:18
I could go play a video game.
42:20
I could go listen to music.
42:21
I could go generate some images and have fun with that and see what those are like and then just enjoy them myself, right? I don't know.
42:27
I I I think there's like a smaller tighter loop with some of these services that might be, you know, overridden.
42:34
And I'm wondering if there might be one in the like design a business like gamification of business [clears throat] world. I don't know.
42:41
It does seem >> Ben Ben has done a really good job positioning Pulsea and like you know using some different methods to get attention.
42:48
I I have some something I feel like I have a little bit against the whole thing because I just get spammed me DMs from him.
42:54
doesn't follow me on X, but he spams me with messages asking uh >> asking for different things.
43:01
Uh which I just think is uh >> Yeah.
43:05
>> I think is somewhat entertaining if you're trying to run the anti- AI slop company, right? >> Yeah. Is it?
43:09
I thought it was pro AI slop.
43:12
I thought that was the whole name was >> very He's saying this is not slop.
43:15
This is uh >> because there is a world where you're like it's slop but it's good slop and like it's fine.
43:21
Like there there's a lot of programmers that say like yeah the answer for more slop answer for slop code is more slop and it's like it'll be fine.
43:29
It's not it's not a problem.
43:29
Uh you might not like the way the code is written but it doesn't matter as long as it works.
43:34
Uh you might not like those artifacts in the AI image but it's fine because it it illustrated the point just like you uh wanted.
43:41
Um anyway, Tyler, do you have something else?
43:44
>> Yeah, I was just say like yeah slap is like a temporary term at some point the running actually becomes good.
43:48
M yeah the writing >> the whatever the the output of the model.
43:54
>> Yeah, writing does seem behind a little bit.
43:57
>> You can it's like verifiable. >> It's not verifiable.
44:00
>> No, people say it's good or bad. >> Yeah. Not not fast enough.
44:02
The loop isn't tight enough.
44:04
And there's too many people that say it's good when it's bad.
44:07
>> You can make it >> maybe. Maybe.
44:09
>> Uh it's it it did get a lot better. >> Still once a week. It got a lot better.
44:14
Someone prominent hosts fully AI generated content. Yeah.
44:17
What was happening with the cash?
44:19
Like, >> no, it just happens. It happens once a week. It's just an iron law.
44:23
Once a week, someone really really talented and smart post something that is just entirely AI.
44:31
>> Maybe we maybe we got to rip it.
44:31
We got to try it just to feel something cuz maybe maybe it's like a forbidden fruit like the full just like just like go to go and prompt like write me a blog post thought leadership about business. That's the prompt. Copy paste. Rip it.
44:47
Maybe it's also a strategy.
44:47
You have something that's like you really want to get out, but it's a little bit boring.
44:52
And so you know that if you use AI to write so much ratio, way more people see it.
44:58
And as long as the first few sentences are kind of deliver the message you want.
45:03
>> This is [laughter] good. This is really good.
45:06
>> Yeah, I I think we got to do it.
45:06
We We'll test it on Tyler's account first, though.
45:09
[laughter] >> Joe Weisenthal. >> Yeah, let's do.
45:13
I love all the AI people who are like, "Nobody's prepared for what's coming."
45:17
It's like, maybe just speak for yourself. >> Joe's ready. Joe's ready.
45:21
No, it is it is very funny that there's this whole there's this whole meme of like no one knows what's coming. It's not priced in.
45:30
It's like all anyone talks about ever.
45:32
It's on the front page of the Wall Street Journal every day.
45:36
>> Lots of people are talking about this.
45:37
>> And most people that say nobody's prepared for what's coming will not give you a really concrete >> Yeah. What is exactly?
45:45
>> Like the last time we had this like nobody's prepared for what's coming moment was um >> what was the guy who was comparing AI to COVID back in March? >> Was that Schumer? Matt Schumer. >> Yeah.
45:57
>> So, uh something big is coming. >> Yeah.
45:59
Something big is happening.
46:01
>> And it's like, yeah, something big is happening.
46:02
Like the models are getting better.
46:04
Like the math is is getting solved.
46:07
But uh like you can still go outside like like at this point in 2020 unemployment had spiked to 10% and like it it was very much like you're a bold patriot if you're going outside like it was a crazy crazy time and now it's like yeah there might be some softness in the in the job market like a hedge fund blew up.
46:29
There's like there's things that are happening, some big things, but >> but the hedge fun the hedge fund blew up from being >> a little too bullish like things maybe like they got the you know the the basically directionally correct but got the timing wrong.
46:46
Uh Mike Isaac says, "Yeah, these MFs don't know how much I got stockpiled in my basement." >> Yeah.
46:53
And Joe says, "These MFs don't know that if a man has a why, he'll find his how." [laughter] >> Well said. Well said. >> Yeah. Yeah.
47:04
Buco Capital was was having fun with Kevin Roose over at formerly New York Times now hard fork independent. I don't know.
47:10
Uh is it did they did they take the a did they take the IP?
47:14
Are they still using hard fork outside of NY? I don't know.
47:17
But uh Buku just says, "Weird comment for a guy writing a book on AGI.
47:21
He is exactly and literally wrong.
47:23
Everyone is pricing it in.
47:25
Why do you think OpenAI and and and anthropic are priced at$1 trillion dollars.
47:29
What nobody is pricing in uh is that besides coding and math, very few domains have embedded verification.
47:36
And so, but uh Tyler over there thinks that uh you can you can formally verify whether or not the Odyssey is a good book in in lean or something.
47:46
>> Well, I think we can >> I think we can formally verify that Tyler's goated, right?
47:49
A lot of people would say like it's kind of like gray area, right?
47:53
You can't >> totally define what it means to be the greatest of all time. Yeah.
47:59
>> But >> you've been working on that quantifying aura.
48:02
>> As long as it's fully quantifiable, you'll be able toify it. Yes.
48:08
>> Uh Andrew Curran says, "Shorten your timelines, friends.
48:10
I've started this account to say this and in many ways have posted for the past four years has been saying the same thing.
48:15
Some of you increasingly feel it.
48:17
We passed the threshold in November.
48:19
We are already inside the singularity.
48:20
Lots of people are are picking up the the we're no longer in the foothills of the singularity.
48:26
We're in the singularity now.
48:28
Uh Demis on stage at Google IO just a couple weeks ago, couple months ago, saying we're in the foothills.
48:34
Well, now we're on the mountain.
48:36
Uh if you followed this account for a long time, Andrew Curran says, "I apologize for losing my mind a few times using GBC 3.
48:41
5 and then Bing forced me to update all my all of this at at once in one shot."
48:47
And that was the correct time to up to update like talking to 3.
48:51
5 and and the first chat PC moment being Sydney that it was if you if you updated on that you did very very well across everything both with the growth in the labs and the growth in the in the data center buildout and everything like that was the key moment.
49:09
>> Also there was a moment in 2020 this was coming up over the weekend. Yeah.
49:13
>> That somebody used GPT3 to generate like a fully functional React app. Do you remember this? Yes.
49:19
>> I forget what it was called.
49:19
It was called like the something the >> um but anyways that in in hindsight was like such a big moment. >> Yeah.
49:29
>> Um but at the time it got like 2,000 likes and people were like wow this is really cool. >> Yeah.
49:33
But no one no one took it from there to be like businesses will be spending hundreds of billions of dollars on this in just a few years. >> Yeah.
49:42
like or I mean a lot of people did honestly like tons of tons of people across venture and private market public markets.
49:49
>> A lot of people did but way more people didn't update any of their behavior. >> Yeah. Yeah.
49:54
I guess uh it's mind-blowing to me how few people realize their lives and everything they know will change drastically in the near future.
49:59
At this point it should be pretty clear says Jerry Turrek. Yeah. Wild times. Elon Musk says 100%.
50:06
He's completely agreeing.
50:09
Let me tell you about codeex.
50:11
Codex is a powerful workspace for getting work done with AI agents.
50:14
Whether you're writing code, analyzing data, creating content, or automating business workflows, Codex helps you move projects forward from start to finish.
50:22
Um, we got to look at this simulator.
50:24
You're into racing simulators. I got to up you.
50:27
I got to oneup you with a train simulator. Look at this guy. This uh this guy on Z80.
50:33
me has said uh has built a full scale train simulator controller.
50:41
For the three years, I've been building a physical train simulator in my apartment modeled on the UK class ADX passenger train.
50:47
I've been trying to replicate the instruments and controls in the real cab as closely as possible. Look at this. >> This is amazing.
50:55
>> In many cases, managing to acquire real components and in others building my own replicas.
51:00
I've gone down rabbit holes for design from custom CAN bus transceiver board and a variety of daughter boards to tie the simulator together to the actual panels all of which on the consoles and instruments are mounted.
51:12
I usually wait until I complete a component or step before I write a blog post.
51:15
But over the last half year I've instead made forward progress on several disperate aspects of the project.
51:22
Therefore, this blog post will update as a status update on many of those aspects.
51:26
>> I'm feeling the acceleration.
51:29
This is such a cool DIY project.
51:29
Imagine just sitting there driving train in the train simulator.
51:34
The >> So, one thing I'm not seeing is any type of visuals.
51:38
So, is he >> like you mean you mean the the software that's driving the uh >> Yeah.
51:46
To to me, he only cares about the tactile experience of pushing the buttons, right?
51:50
like he's optimizing for actually feeling like he's in the uh in the >> in the train.
51:57
But no, there is a screen and that screen is running a game that simulates a train.
52:02
The name of that game, >> Train Simulator.
52:05
[snorts] >> You can get it at train-simulator. com. It's also on Steam.
52:09
Uh yes, uh Train Simulator Classic, uh is I believe the one that he's playing.
52:14
Um but, uh yeah, he's playing the full full Train Simulator.
52:19
Simulator. uh AWS sunflower I don't know anyway funny funny story uh Bology is moving to Kazakhstan this is huge for the Boro community [laughter] >> not >> absolutely huge for the Boro community uh he posted a video
52:34
>> this is Kazakhstan let's see >> this is a beautiful video I I I I have no doubt it's a beautiful place uh it's a little bit crazy because uh his network school I thought of as sort of a like a startup incubator a uh a Y combinator adjacent entity. Um he was in
52:49
Um he was in Singapore for a while then Malaysia and now maybe Kazakhstan.
52:55
Is he did he actually move to Kazakhstan or is he just like touring and vacationing there?
53:00
Because um what is the actual story? >> Here's the news.
53:03
He says, "I'm pleased to announce that a memorand a memorandum of understanding has been signed between the Republic of Kazakhstan and Network School.
53:11
Our new campus will become a haven for global techno optimism with expedited visas, streamlined redomicillation and active recruitment of talent.
53:21
Um, excited for Biology, excited for Kazakhstan, excited for network school.
53:29
Biology is very smart and very entertaining and I've enjoyed having him on the show.
53:34
I do think um I do think it is uh very funny to be trying to recreate the incredible techno optimism that many different sub communities already have in the United States. >> Yeah.
53:51
>> Where he uh you know where he effectively had all of his success at Coinbase and Andre Horowitz and sure many other businesses.
54:01
Um, and uh, I think it is, this whole chapter is deeply entertaining to me.
54:08
The Kazakhstan chapter, >> it's just, [laughter] it's such a funny place. Uh, King in the castle. I love it.
54:14
Uh, so quick tip for anyone who's planning to do sort of like the the by coastal thing, San Francisco, Kazakhstan, uh, you're in for like a 30hour trip because there are no non-stop flights.
54:30
I think uh you have to connect in Istanbul, Frankfurt, Seoul, Doha or Dubai.
54:35
Um you're looking at 25 to 35 hours depending on the layover.
54:42
That is really really far.
54:42
The Miami thing was a was a tough pitch because you know so much activities happening in New York, so much activities in happening in San Francisco.
54:53
Um and it was still hard to get people to relocate like great engineers.
54:55
Uh they come out with the beauty.
54:58
>> No, I mean this is just truly >> full send >> the toughest possible cell.
55:04
>> I think he's trying to I think he's >> weed out the week.
55:07
>> I think well I think in in some ways he's been so successful that he wants a challenge that to him feels almost impossible which is to convince the best and brightest from all over the world to to move to Kazakhstan.
55:19
Um, it's it's I know so many I mean some major selection bias here, but I know I know a bunch of bright people that are not >> US residents >> and they would do anything to be able to be >> in Kazakhstan. >> Not [laughter] quite. Maybe now. Maybe now.
55:45
But they would do anything to be an to be able to have free access to America, to be able to set up shop here, to be able to build their business here.
55:53
>> Um to be able to uh >> to be the king in the castle >> to be to be not even the king but a popper.
56:00
>> Just someone just someone in the castle >> in the castle at all.
56:03
>> Uh and so yeah, and I haven't uh yeah, just >> we got to go.
56:10
It's very >> clear very clear.
56:12
got to go or at least send Tyler. >> I would go. It looks fun.
56:18
>> Pack your bags, buddy.
56:18
[laughter] See you in 30 hours when you land. Uh, absolutely wild.
56:22
Let me tell you about CrowdStrike. Your business is AI.
56:24
Their business is securing it.
56:26
Crowd Strike secures AI and stops breaches.
56:28
Uh, Mark Zuckerberg uh was answering questions about his AI strategy on the latest Meta earnings call.
56:37
and Ben Thompson wrote about uh about uh what Meta's position is in AI, how they're grappling with a few things.
56:47
There was a bunch of interesting points in this strategy update.
56:49
Uh one I wanted to call out was um uh what Ben Thompson thought the best moment on the call was when an analyst asked him why the company can't just use other models.
56:58
Like why can't you just do the Apple thing? Do nothing, win.
57:00
Like partner with one of the labs, do some license agreement.
57:05
If you need an image model, you get an image model.
57:06
If you need a text model, you get a text model.
57:10
If you need to speed up your programmers or your your your engineers, hire the best coding agent and negotiate with them, right?
57:18
Um, and here's how Mark Zuckerberg answered it.
57:20
He said, I can take the open source question. Let's see.
57:24
So, basically the question is, do we think that because there are some openweight models that we can just rely on those?
57:30
Uh, I mean, right now the open source models are not as strong as the frontier models. Good point.
57:34
Uh so no is the basic answer.
57:37
Meta needs to be on the frontier with their intelligence that they use.
57:42
So they have to be there according to him.
57:44
He says and then there's also just the there's always there's there's also just always the perpetual both policy debate and and question around other companies actions and whether that's a thing a company like Meta can rely on.
57:57
So if you're using Chinese open source and there's some regulatory risk.
58:01
It seems like that's sort of what he's getting at is these things might not rely they might not be available all all the time and then also some of these companies they might be open source for a few years and then go close source and then start charging you an arm and a leg.
58:12
So you don't want to be in a place where you become super dependent and then all of a sudden get uh get you know hurt once you're you know uh super dependent on a particular product.
58:23
So he says and I think that's very tricky.
58:25
So on both fronts, we believe we're going to be able to do better work and we think that there's some risk in that reliance.
58:31
I don't believe that's the right thing to do.
58:35
So uh that felt like not a great answer to me uh in the sense that the the Apple approach seems to be working so well.
58:45
We'll talk to John Gruber about that in a few minutes.
58:47
Um but uh then he goes on to explain some of the history of Meta and it's very very interesting.
58:53
He says, "I think that we're a company that if you look at meta from, take a step back on this.
58:57
A lot of people view the service layer as of we build some social media apps and we have an ad business.
59:03
We are really a full stack technology company.
59:05
We we build our own data centers, our own infrastructure, our own chips, our own low-level software.
59:10
When we get when we got started, he says, "My background in engineering, I wrote a lot of the systems code.
59:16
A lot of the reason why Facebook worked was because it actually it just worked, which is a crazy thing to say based on the history, but he but he makes a really good point.
59:27
He says like it literally worked when other social networks did not work fast and efficiently.
59:33
And I think we just have the ability to build things that can be more personalized, more optimized, more efficient.
59:39
Some qualitative experiences are just not even possible for others to build because we go all the way down the stack.
59:46
And it just seems to me pretty clear that having kind of sovereignty over building your own models is going to be an important part of that stack going forward, which is why it's important for meta.
59:55
And so that that was very interesting that that was a differentiator in the early days that uh certain other competitor sites would just be slower.
1:00:03
They wouldn't be able to launch new features quickly.
1:00:04
And by vertically integrating all up and down the tech stack, they were able to do things very aggressively.
1:00:10
This is the uh the reals uh thing.
1:00:13
the reals uh thing. They built uh they built like two extra data centers to be able to do the reels algorithm uh because if they didn't have that compute capacity they could not have launched a competitor to Tik Tok on any normal time frame because it was actually a compute intensive project not just a design people see oh they just put a new button
1:00:36
there and there's some videos but it's like behind those videos is a massive recommener system that is very computationally intensive and stores a lot data and you can't just spin that up for three billion users or however many billions of users they have uh on a on a dime if you don't have the infrastructure if you're not actually vertically integrated. So there's a
1:00:52
So there's a whole bunch of other things where in terms of personalization understanding the user de like delivering a really firstass experience they sort of do need to bring it inhouse but investors are very upset about this.
1:01:08
>> [laughter] >> They're not very happy because um they they uh the uh he Ben Thompson call calls it the financial tail wagging the dog and uh says that they have to sort of double spend right now.
1:01:19
He makes a good point about this.
1:01:21
They're double paying the company right now is basically double paying for infrastructure without a clear path to monetization.
1:01:27
Uh and to make matters worse, it's improving monetization story lost a bit of its luster.
1:01:31
So they're both renting AI compute, paying a bunch of money for new researchers, and then also spending all the capex for the next data center.
1:01:41
So all of that needs to come together uh in this uh in this moment to actually deliver and the investors are starting to ask all these questions about what the what the strategy is, but Zuck's sticking with it.
1:01:52
He's not he's not backing down, but we will see.
1:01:55
Yeah, tough position to be in when uh capital markets don't have a ton of faith and you just see that in in uh the stock price uh the the company broadly, right?
1:02:07
There's a lot of infighting, frustration around uh just how MSL is treated versus the rest of the company which is paying for MSL.
1:02:14
Uh so Zuck is uh is at war with uh fighting a war with multiple fronts. >> It is. It's a big war.
1:02:23
Well, >> he'll get through it though.
1:02:25
>> We'll dig into it more.
1:02:25
Uh, I still think this this Pier Richelson tweet is so funny. Shower thought.
1:02:30
Why is no one doing Outbound for pizza?
1:02:31
Hey, this is Gigi from Gigi's Pizza calling you ordered last week.
1:02:36
We have a pepperoni pizza ready and could deliver it in 10 minutes. You hungry? Uh, hilarious concept.
1:02:42
Uh, would be extremely annoying to have every possible low tier uh, you know, business that you do that you've bought anything from with spamming you.
1:02:53
I mean, they basically do this with uh, you know, email awareness, like, "Hey, there's a Super Bowl coming.
1:02:56
Like, do you want to place an order?"
1:02:59
>> What if we made a law that said that restaurants could only call between 5:30 >> and 6:00 p. m. >> when you're hungry?
1:03:08
>> And so, you knew you'd be getting calls coming in and you could kind of play them off each other. You get a pizza offer.
1:03:12
You're like, "Look, >> I'm kind of interested in pizza, but I'm I have an open conversation with the Takaria and I need to wait to understand like what they can offer tonight, and I'll let you know." Yeah. >> Takaria calls you.
1:03:23
They go four steak tacos, >> side of rice, >> you in. >> Yeah.
1:03:29
>> And and then you you you get a price, you get a bid, you go back to the pizza, you kind of play them off of each other a little bit, and then you go with, you know, with what you're really feeling at the end of the day.
1:03:38
>> Do you know what it's called on Wall Street when uh you have multiple parties negotiating to sell a block of stock or debt or something like that and you want to bring them all in really quickly?
1:03:48
Uh, like let's say you're negotiating with Tyler and I have extra information.
1:03:53
I might have a buyer and I want to jump in.
1:03:56
Do you know what that's called? >> Barging your line.
1:04:01
>> Say like, "Oh yeah, I'm going to barge his line.
1:04:02
Jump in there and then we'll be on like a three-way call basically."
1:04:07
And and you can do that when your phone system's set up with multiple lines.
1:04:08
So, you could potentially have, okay, you got Domino's on on line one and then you got Pizza Hut on line two, and you could be like, okay, I'm just going to put you as, you know, all in one call. Let's debate.
1:04:22
Let's get to the bottom price.
1:04:23
Because that's basically what you're doing.
1:04:24
You're saying, "We're just going to hold an auction right here."
1:04:26
>> Yeah, >> this might be the solution. >> Uh, I like this post.
1:04:28
Explaining to my wife, explaining to my ape wife that I have to spend nights and weekends learning the bone so we don't end up in the permanent underclass.
1:04:41
[laughter] Is this from uh 2001 Space Odyssey? >> Yeah. >> It's a good movie.
1:04:45
Jordy, have you seen 2001's Space Odyssey? >> Yes. >> You have? >> Yeah. >> No way.
1:04:50
>> Yeah, I remember that scene. >> What? How? How did that happen? That's wild.
1:04:55
>> I think I was forced to watch it. Hm.
1:04:57
[clears throat] Um, oh yes, this this old this old uh Leopold lore is coming back up.
1:05:01
The author of this New York Times article, definitely doesn't realize Leopold was being literal about the stars and galaxies, asked in a 2004 podcast interview with Darkesh Patel what his goals were.
1:05:13
He answered, eventually you are going to go to the stars.
1:05:15
You are going to go to the galaxies.
1:05:17
He added, done right, there's a lot of money to be made.
1:05:20
That was true for a while at least.
1:05:22
While the fund was the center of the hottest trade on the planet, the fund made a return of more than 2,200% after fees uh as anything tied to AI shot higher.
1:05:31
One investor said, "Yes, there was a funny line uh where uh where Leopold's talking about buying galaxies."
1:05:37
And some investors like, "Oh, like the particular brand of private jet that's referred to as a galaxy, like the Galaxy 750 is the one that you'd want."
1:05:47
And and Liupold was like, "No, no, no.
1:05:49
I'm going to buy an actual galaxy."
1:05:49
Tay Kim says, "Who will play Leo and Ken in the movie? We know it's coming. The story is too juicy." Okay.
1:05:54
Will it be like >> We got to play We got We got to play this clip of uh of Ken Griffin because uh this came up on my uh my for you page and uh it's a it's a wild story of when Ken Griffin had his darkest moment basically and lost a whopping 4% of the fund. Something like that. Play this clip.
1:06:15
You >> know, 1994, I was in Switzerland.
1:06:15
We'd had a rough year in '94.
1:06:17
We lost about 4% of our capital in 94.
1:06:20
It was one of our only losing years in the history of the firm. And I'm in Switzerland.
1:06:23
I mean, it was a rough day.
1:06:26
My lunch, my lunch, I sat down at lunch. This person sits down.
1:06:33
Oh, you're not John Griffin. No, I'm I'm Ken Griffin.
1:06:36
He goes, "Oh, I thought you were John Griffin from uh Fen Church, another firm."
1:06:39
He goes, "I I got to go." [music] Like, great.
1:06:42
I flew all the way to Switzerland for my lunch date to get up and leave the table.
1:06:46
And then around 3:00 or 4 in the afternoon, I was with uh another Swiss banker and when his office's office was [music] like almost the square footage of the stage, beautiful furniture.
1:07:00
Goes, "Do you mind if I smoke?"
1:07:00
Takes out a [music] big cigar. He's smoking this cigar.
1:07:02
And we're talking for about 45 minutes.
1:07:04
[snorts] Such a pity [music] that such a bright young man so picked the wrong career.
1:07:13
[laughter] like, well, that's the most graceful no I've gotten [music] today.
1:07:19
But but you just have to tolerate.
1:07:21
You're going to hear no a lot, [music] but you need to become accustomed to >> Leophold's stat. >> Yeah.
1:07:27
[laughter] >> You represent what you stand for.
1:07:31
>> Again, whether it's the people that you want to have work for you or people are trying to give you capital or customer, you need [music] to get comfortable with the art of selling. >> Ah, great clip.
1:07:40
It's so funny that someone was like, "Ken Griffin, like you're just in the wrong job. You should be >> Yeah. >> I don't know.
1:07:47
>> This is This is not for you."
1:07:49
>> I wonder what that banker would have preferred Ken Griffin do.
1:07:51
Like, did he have a prescription?
1:07:53
Was he like, "You should be >> seller, [laughter] hustler, I don't know, skier or something."
1:08:00
Uh, anyway, fun little trip down memory lane.
1:08:02
We have John Gruber from Daring Fireball in the waiting room.
1:08:07
Let's bring him in to the TVP and Ultra Dome for the second time.
1:08:10
Welcome back to the show, John. How are you doing? >> Good. How are you guys? We >> Great to see you. >> Good.
1:08:16
>> Uh, >> how's your summer been? >> Yeah, >> hot. >> Hot.
1:08:22
>> Has the [laughter] Has has the tech news been overwhelming or underwhelming this summer compared to previous summers?
1:08:32
>> Oh, I'd say much busier.
1:08:32
Say overwhelming, but but definitely busier.
1:08:36
It feels like the I don't know I mean at least the the there's like the traditional news which is like a company does a thing there's a process something launches that felt that has felt very light recently but then there is like the meta drama of like situational awareness blowing up and that stuff has
1:08:55
been really really crazy like the the hugging face hack and like mythos and all these different stories that are sort of like not planned in the same way of like there's a release cycle we all got to talk about the thing that's like goes through the PR turn, you know. >> Yes. I don't think that there was a >> Yes.
1:09:09
I don't think that there was a marketing schedule for when we're when they're going to have a hey, our um AI broke out of a sandbox and attacked a major partner of ours during a testing run.
1:09:28
>> Well, it just depends if you believe in like the Truman Show thesis.
1:09:30
So the simulation theory was like now have the hedge fund explode.
1:09:34
That will be the entertaining thing.
1:09:37
>> Well, the funny thing is there was there there actually was people that were making the allegation that uh the the hack was just mark was just marketing. >> Yeah.
1:09:46
I I think they they don't mind, right?
1:09:50
Like I don't think it's so I don't think there's a conspiracy and that it was fake or deliberate, but I do think there's a strong sense of oh no, you mean that the news cycle for the next 24 hours is going to be about how scarily effective and intelligent our model is?
1:10:08
[laughter] Uh, you know, I do think that there is a laughing all the way to the bank aspect of it even though it wasn't deliberate. >> Sure. >> Yeah.
1:10:18
or like a parent watching their kid and like the, you know, plays sports and like the kid runs up like, you know, a bunch of points on the other team and the and the coach has to talk to the parent and say like, "Hey, look, like your son is [laughter] very good, but like he's got to pass the ball a bit more and like it's not really that sportsmanlike to, you know, run up the score that crazy.
1:10:37
He should focus on, you know, >> teamwork." >> Yeah. Yeah.
1:10:42
Um I heard I while we're on conspiracy theories, I heard a funny one that uh the person that's the most happy about uh situational awareness uh blowing up is potentially Apple because they've been under all this pressure from memory.
1:10:58
Situational awareness was of course very long memory.
1:11:00
There's a flywheel there where the stock goes up, the memory gets more expensive.
1:11:04
Now, I I feel like that the the the real take here is that in fact pumping up memory stocks is the best way to lower the price of memory because they will all fund capex and that will ultimately make uh Apple devices cheaper.
1:11:19
But how do you think about the the pressure that Apple's been under around component pricing, supply chain pricing getting caught flat-footed versus just reacting to what's happening in the world?
1:11:36
It is extraordinary and I really do think that it to go the other way.
1:11:38
I think you know Tim Cook's public remarks on it as being a once in a hundred year flood situation and that he's been looking at this market his entire career and there's there is no comparison point.
1:11:52
>> You know that the and Ram in particular has always gone through these boom and bust cycles.
1:11:57
Um, and this is just a boom with a capex expenditure fueling it that is just such an extraordinary amount of money that it's like nothing else.
1:12:16
And so I don't know that even though that Apple was caught flatfooted, it's like you it's like the sort of situation you just can't prepare for, right?
1:12:22
There's if you live on a flood plane, you take precautions and you build levies and you know, you take out you pay insurance that's based on that.
1:12:34
If you don't live anywhere where there's ever been a flood before, you don't pay exorbitant amounts of money for flood insurance. You don't build levies.
1:12:42
And if something happens where you still experience a flood, well, then it's a catastrophe.
1:12:47
Um, >> and I wouldn't even I catastrophe is a strong word, but Apple having to go through, you know, I guess it was just a month ago, but it feels like just speaking to how the summer is going, it feels like a while ago.
1:13:02
But for them to come out and say we're going to have to raise prices and then a week later raise prices um midcycle just Apple just does not do that.
1:13:12
And for Apple, that's like a minor catastrophe.
1:13:14
Um, but I don't know what else they could do.
1:13:17
I don't think there's any point where you could look back 18 months ago and say, "Oh, well, Apple should have really foreseen this and somehow done something different."
1:13:26
What could they have done?
1:13:29
>> How how much do you see the the leasing program as a direct response to higher prices?
1:13:34
Is this do do you think the leasing program is something that was rolled out because the prices were raised so abruptly, or is this something that they've always been sort of moving towards?
1:13:46
This program was probably in the works three years ago and Apple works on a long time cycle and so this is just the natural arc of things because they've had a they've had a refresh program where you could effectively subscribe for pre-memory price spike, right? >> Yeah. Yeah.
1:14:02
They had the old iPhone upgrade program. >> Yeah.
1:14:07
[clears throat] >> Which was just for iPhones.
1:14:10
>> And I think they've seen it as a success.
1:14:15
Um, and so I think this was sort of a natural 2.
1:14:18
0 way of of the, you know, and it's no, no, I mean, they're the ones who discontinued the old iPhone upgrade program the day that the new Apple upgrade program for all of their major products come out.
1:14:31
Are I mean, you can even get like uh I think you can even get like AirPods on Apple Upgrade.
1:14:39
It's not just for >> I don't know. I think so.
1:14:41
Um, but certainly like all the Macs, all the iPads.
1:14:45
So, I think this was in the works and I do think that they've been I mean the whole consumer market is moving towards there's a lot of competition in paying over time.
1:14:59
>> It's you know and for a while I think that it was sort of at the consumer level just locked into credit cards.
1:15:05
You get a credit card, you buy something and you pay the credit card company over time.
1:15:11
And I think a lot of people just looked at that and thought, "We're leaving money on the table because they're buying our products.
1:15:17
It's not just Apple, but everybody is looking at that >> and thinking, well, this is crazy.
1:15:23
They're charging these consumers 13 or 14% APR."
1:15:25
Uh, >> well, how do we get involved in that?
1:15:30
And you know, Apple specifically, they now they have the Apple Card, which is, I don't know, seven, eight, nine years old.
1:15:37
I mean, it's been a while.
1:15:37
and they've had a program through that where if you buy an iPhone you get 24 months of zero interest.
1:15:42
Um I think the big change though it it's all clearly about the fact that for so many people it you know I don't even want to pass judgment on them but I think for some of them they are mathematically disincclined >> to be able to extrapolate a monthly payment by the terms they're agreeing to and realize this is what you're going to pay over time. >> Sure. Sure.
1:16:10
um that they just look at the monthly payment and they say, "I can cover I can pay that."
1:16:14
And they look at the lumpsum payment of $1,200 for the iPhone they want.
1:16:19
They say, "I can't pay that." Yeah.
1:16:21
>> But if I agree to this, I can get a new iPhone.
1:16:23
I can walk out of the store with an iPhone 15 minutes from now.
1:16:25
Um and so I think Apple just looked at that and thought, well, how can we offer something that's attractive? and the lease.
1:16:33
I think the big difference with the lease is clearly that the monthly payment is even lower, you know, than the buy overtime of the old iPhone upgrade program.
1:16:42
But in either case, it is good for the consumer.
1:16:45
And I know some really smart people who are like, I'm doing this, you know, because it is there's there's no interest on it.
1:16:52
And if you do get a new iPhone every year, it is just an easy way to you don't really lose anything.
1:16:59
you're not paying any interest penalty and you just have like an easy system and they mail you the box to send the old one back in every year.
1:17:06
So, I think it's just a way for Apple to sort of kneecap the number of people who were buying their iPhones with credit cards and paying interest penalties over time.
1:17:16
So, I think it's better for everybody.
1:17:19
>> It feels like I could bundle the leasing program, the MacBook Neo into a Apple is going down market strategy.
1:17:25
Do you think there are other plays that they will make to sort of calcify that strategy or really deliver on it or is this sort of like you think it's a pretty mature strategy that they have?
1:17:42
>> I think it is incremental let's say like there's it's these are not major moves.
1:17:47
Even the MacBook Neo I mean I think the MacBook Neo is one of the certainly the most interesting Mac product since the Apple silicon in 2020. >> Mhm.
1:17:56
Um, and it is that that there were a couple of times where MacBook Airs dropped to like $8.
1:18:02
99 or something like that, but that $9.
1:18:04
99 starting point had been the the starting point for a base MacBook Air for I don't know at least 15 years.
1:18:14
And so, you know, when you consider inflation, the price has been coming down, but not down in the way that like what's the entry model for an HP laptop or something like that, which is like $400.
1:18:27
>> Um, so to drop the entry price not just by like $100 or $200, but all the way down to $599. I guess it's up to $6.
1:18:32
99 now with the price increases, but still that is significantly lower.
1:18:37
Um, and I think they've been doing the same thing.
1:18:42
I think on the iPhone side, the switch from selling SE models, iPhone SE that only get updated every 3 or 4 years to an annual schedule of having whatever the current number is, they stick an E at the end, 16E, 17E, there will be an 18e next year.
1:19:00
Um, those are really low prices uh for a brand new iPhone that has the latest silicon.
1:19:07
I mean, it doesn't have the greatest camera, but so many people do not care about the camera.
1:19:10
And that camera on the ephones, it is fine.
1:19:13
It's one camera on the back.
1:19:16
It's a 1x camera that you can get 2x optical with the the fancy sensor that system that they have.
1:19:24
>> It takes great photos.
1:19:24
I mean, but it's the same sort of thinking where we're not going to they're not going to sell years old products >> as their Okay, fine.
1:19:32
Here's our affordable stuff.
1:19:35
It's here's brand new stuff.
1:19:38
It's just less technically advanced silicon-wise, but it is brand new, right?
1:19:43
The Neo is months old and it's at a record price.
1:19:45
So, they're incrementally moving it down market, but I think only in so far as they think that there's people with money to spend. >> Yeah.
1:19:56
Jordan, >> what percentage of the employees, the team over at Apple do you think are excited, truly excited about AI and think that it can make the Apple ecosystem significantly better over time?
1:20:15
It feels like to me they're like very It feels like to me that the whole company is like >> ah like why is this happening to us [laughter] instead of like instead of saying like hey this is this like you know useful set of tools that can make our software better that can make our devices more magical to use.
1:20:31
Uh >> I that's a good question.
1:20:35
And the last thing I would say is like there's I don't know anyone who's excited about AI that's saying like I got to go work at Apple because they have the best devices in the world.
1:20:46
They have billions of users. >> Biggest opportunity.
1:20:49
>> This is such an amazing opportunity.
1:20:51
Like if I want to work on consumer AI, I have to go work there.
1:20:54
Like that's just I don't know anyone like that.
1:20:58
>> Yeah, I think that's true. I don't either.
1:20:59
Um but I don't know that it's a problem.
1:21:02
And I do think clearly AI is where Apple was caught flatfooted.
1:21:05
I don't see how else you could describe that, right?
1:21:09
And I think as time goes on, looking back at the WWDC from 2 years ago, 2024, when they first announced Apple Intelligence and then announced the stuff that 8 months later was supposed to be rolling out and they were like, you know what, we're going to have to postpone this by a year.
1:21:28
And really when they postponed it and said it'll be coming in the coming year, this is the coming year, right?
1:21:35
And it still isn't really out.
1:21:37
It's in the public betas this summer.
1:21:39
It's coming out this fall.
1:21:41
So they were they announced something that they were saying was going to come out to consumers, be in people's hands in the first half of 2025, and it's coming out at the end of 2026.
1:21:53
Um >> and in in this market in the AM AI market that is a big miss time wise.
1:21:59
Now 10 years from now will people look back at this and say wow that was a huge gap of time probably not.
1:22:05
Um, and when people look at the new Siri AI that's in the the OS 27 betas right now, is anybody who really is juiced into the whole AI system saying, "Wow, they've really taken the lead here in any way." No, absolutely not. Right?
1:22:23
This is very basic stuff, but it all does work.
1:22:26
It is and it's going to be the intro to LLMbased generative AI for hundreds of millions of Apple customers.
1:22:38
Hundreds of millions of them have never used any of the stuff.
1:22:43
However popular ChatGpt and Claude remain in the app store.
1:22:46
There are hundreds of millions of Apple users who've never used this.
1:22:50
And you know I've been using ChatGpt in particular for you know years.
1:22:54
Um, I I'm definitely not among amongst my peers in the tech media.
1:23:01
I use it less than most, but I'm pretty familiar with it, but I have to say testing it this summer, ever since WWDC for all of the basic questions, the Syria AI is great and just being able to squeeze the side of the phone is a great way to do it.
1:23:16
And I honestly think it's like what triggered OpenAI to have the fiasco of a launch of the new desktop app for chat GPT.
1:23:30
Clearly the biggest driver of that is their fear of missing out with Claude and Anthropic taking taking the lead.
1:23:40
As if you just pulled everybody who watches TBPN, who's who's in the lead right now? I think it's very clear.
1:23:47
I mean, you'd be I think you'd be kind of nuts not to say anthropic. >> Yeah.
1:23:51
It's verifiable based on >> revenue run rate. Yeah.
1:23:54
So, shouldn't >> just the state of things, right?
1:23:57
You just put lick your finger, put it in the air, and who's got the momentum, right?
1:24:02
>> I think and and that's put open AI they they seem to have and still I think are panicking over that.
1:24:09
They really seem to have formed a sense of self which was that they had already won.
1:24:14
I think you know like somewhere around 18 months ago or so that whole company had the we've won this already.
1:24:23
It's we're just mopping up the chessboard at this point and now they found out that they're in a long-term race and they're not.
1:24:30
So that's clearly the biggest driver is that they they looked at the way Anthropic has bundled up Claude and Claude code and said we need to do something more like that.
1:24:39
something more like that. But I do think I absolutely think part of it is that the Siri AI app that Apple is rolling out it which visually you just look at it looks like chat GPT right it's black and gray and it at a glance if I showed it to you >> in May before WWDC and I just quick showed you a screenshot of it you'd say
1:25:03
oh yeah that's chat GPT no it's Siri AI and I think that there you know in the Apple world we call Sherlocking because there was the Sherlock thing 20 years ago where there was a Apple had an app called Sherlock and some third party developers made a much better version called Watson and then the new version of Sherlock came out. Sherlock was
1:25:22
Sherlock was Apple's first.
1:25:25
>> Oh, >> then there was a a third party thing the other way.
1:25:28
>> I always get it flipped. Yeah. Thank you. This is helpful. >> No.
1:25:32
And the third party one was called Watson and it was way cooler.
1:25:34
And then the next version of Sherlock was like Watson.
1:25:40
And it was sort of, you know, it's like tough luck to the outsider, but it's like everybody looked at Watson and was like, "Oh, this is the way Sherlock should be.
1:25:50
This should," you know, and Apple looked at it and thought this is the way Sherlock should be.
1:25:53
And you know, Apple had this stance that was they they quite outspoken about it.
1:25:57
like Craig Federigi, I think it was with Joanna Stern last year, >> you know, said that Apple did not see chat bots as a good interface to AI, right? You know. >> Yeah. >> Yeah.
1:26:09
And they're just like, you know what, it is a great interface to AI, so why don't we make one, too?
1:26:12
And I sort of think like ChatGpt sees that for >> nonadvanced usage, nobody's going to go to these third party ones when Siri can can answer that. So, no.
1:26:23
Is it exciting and is it where the people who want to work at the frontier want to work?
1:26:28
Do they want to work at Apple? No.
1:26:30
I mean, why would you at this, you know, they don't really have a product that's even aiming for that?
1:26:35
But Siri AI isn't aiming for that.
1:26:38
It's just aiming for, you know, the type of trivia questions that people just ask like a oneoff twooff chat session.
1:26:46
Um, and it does a fantastic job.
1:26:49
And it has these integrations with stuff like your if you use Apple Mail, if you use iMessage, it finds stuff in your iMessage just like they promised. It really does work.
1:26:59
All of the stuff that's in my Apple Notes, I ask questions about it.
1:27:03
Uh, and it just finds the answer to it.
1:27:05
It's really, really useful.
1:27:07
Is this impressive to people who've been following AI for the last 3 four years? Not at all.
1:27:15
But this is the Apple way is take something that is super exciting, super cutting edge and boil it down to its basic core and put it in a way a a usable interface that people will be a normal people will be able to understand and give it to everybody.
1:27:33
>> Okay, let's um >> let's play it out a bit further because I'm curious where you where you imagine Siri AI goes.
1:27:39
I've always felt similar to you in that uh there's so many questions that you don't need, you know, incredible advanced intelligence.
1:27:48
You just need a simple answer to something.
1:27:53
Um and I can see a lot of that flowing through uh flowing through Siri.
1:27:55
Uh but where does this product go over time?
1:27:59
where does this product go over time? Is this something because if you play it out far enough and the product gets enough traction then at what point is Apple competing not just with other LLM providers but competing with Google itself and then they say like oh we're the private you know we're for privacy
1:28:17
and all these things but then at what point do they say hey we're this is costing us a lot of money to run we got to we got to start running ads and then at that point like do we do targeted ads or non-targeted ads or do they try to take the moral high ground and say we're better than ads, even though they run ads in in maps and they run ads in the app store and all these things. So, play So, play it out for me. How does this go?
1:28:37
Let's assume that let's assume that it's a it's a success to the degree that they keep investing in it for many many years to come.
1:28:52
Uh the ad question is interesting because obviously Apple never had to or never decided to make a search engine for Safari and they just sat on you know what we'll just have Google is the default and Google will pay us for the traffic acquisition and we all know from various court cases that how you know
1:29:11
however much they'd like to keep it under the radar it's like 25 billion a year now and it had been in that range you know it's been a lot of money for a lot of time and For a while in the early era of Tim Cook's services narrative, even though it was a lower number 10 years ago, it was a huge percentage of Apple's quote unquote services. So
1:29:30
So Apple's, you know, Tim Cook said to Wall Street, our our growth area is services and their services number kept going up, but it was really for a long while just the Google traffic stuff.
1:29:43
Well, why would Google keep paying this much money?
1:29:47
Because when people would search, you see the Google results and what does Google show them? Ads, right?
1:29:51
And you you know there's a very simple, oh, this is kind of you see how this works for everybody.
1:29:58
There's a sort of flywheel.
1:30:00
Google gets all this traffic from the terrific audience, the demographically attractive Apple user audience and is obviously very profitable at showing ads and search results.
1:30:11
They pay a significant portion of that to Apple to have it as the default in Safari and everybody just keeps searching in Google and everybody can kind of about the ads that have gone into the search results but people still use Google.
1:30:29
What happens with Siri where there are no ads?
1:30:30
Why, you know, how does that financial relationship work with Apple and Google for the back end?
1:30:35
Like who's paying for it? I that's a real mystery.
1:30:41
I and I they've they very and I I every it's one of those questions where when the like Apple just reported results at the end of last week every time I I I never listen cuz I find those calls in they they're like 45 minutes long and they feel like 45 hours to me.
1:30:56
they feel like 45 hours to me. So, I skimmed the the transcript and I'm like, I would love if somebody could ask and I don't think that they would answer, but >> if there's any clue about how that >> it's so it's so interesting to me
1:31:09
because Google is help is like we're going to help Apple because we want to try to commoditize the LLM space because we're behind and we're and our business is threatened for the first time because a billion people are using effectively another search engine, an answer engine, right? They're using chat GBT, they're
1:31:24
They're using chat GBT, they're using some Gemini, they're using some claude, but like obviously by and large that usage is going >> uh going somewhere else besides Google.
1:31:35
And so Google makes the call to support Apple and Apple's effort to try to commoditize the sort of assistant category.
1:31:44
But then through that they if you assume that partnership is going to be successful then what happens to their existing Apple partnership and then what happens to search over time and then even with a demographic even with a group of like customers like iPhone customers
1:32:03
if you there's a lot of people that are not going to sign up and say oh I'll spend another 20 bucks a month on on AI with Apple right >> um people already complain about the like, you know, twice a month you see a charge from Apple and it's like what's that charge, you know? Um and and so
1:32:19
Um and and so there's the big question to me is like Apple right now to me is like positioning the entire company around being against ads and and you know really pushing privacy.
1:32:34
really pushing privacy. I see random out of home ads for like Safari and it's like finally private browsing that is like already counterpositioned against Google who is now their partner and then eventually I just think if you want to
1:32:48
serve this product to the entire Apple user base they're probably going to it will probably make sense to do ads then at that point do they dance with Google again and and use like the Google ads network but it's so hard to see where
1:33:05
this goes >> they are but Apple is dipping its toes into ads right that the app store is ground zero for this where when you search in the app store they have a big ad in the top spot now and sometimes >> if you're searching for let's say signal and I like signal is a
1:33:26
good is the example I always go to because they don't pay they don't seem to pay but if signal the signal group or whatever the the organization is bounced signal pays for an ad on the keyword signal. You can buy your own name as the
1:33:38
You can buy your own name as the top result and then you get an ad and then you get the second spot too because that's where you naturally show up.
1:33:47
>> But there's, you know, or or you search for Roblox, you know, or something that kids play and there's like sometimes there's like gambling apps that show up in number one. It's crazy.
1:33:56
>> Um, and now they've added a second spot in the third spot.
1:33:58
So when for most things you search for in the app store, the top spot is a paid ad, often paid for by the app you're searching for, but they're still paying.
1:34:06
Now they're like double dipping because Apple's taking the commission from the app store transactions and making you pay to get the top spot.
1:34:14
>> The second spot is the top natural search result and the third spot is another paid ad.
1:34:18
Now >> um and I think that's off-brand for Apple. I really do.
1:34:22
I think it is, you know, like I always go back to HBO, which it just was when I was a kid, it just seemed too good to be true that you could watch movies and there were no commercials >> and it's like the only what's the catch where you're you got to get your parents to spend, >> you know, whatever 10 bucks at the time in the 80s, like 10 bucks a month extra on the cable bill.
1:34:44
>> Um, but it seemed like such an amazingly good bill, >> good deal.
1:34:48
And that's, you know, always been sort of the Apple thing.
1:34:50
It's like, oh well, MacBooks cost more than other laptops and iPhones cost more than other iPhones. What do you get?
1:34:57
Well, part of the experience is you don't get inundated with ads.
1:35:00
Um, and I go back to the Safari thing with Google search like it has been such a good deal for Apple.
1:35:09
It is 20 to2 billion in cash that just comes in. It is almost no margin.
1:35:13
comes in. It is almost no margin. You know, you can say that you could subtract 100% margin keeping almost right at this I mean what's the salaries of the team that makes salary Safari and WebKit compared to $25 billion a year right it is it's as close to 100% margin as anybody could reasonably get
1:35:34
>> it is year after year and it doesn't look like Apple is serving you the ads so you're just Joemo Apple customer you use Safari on your iPhone because it's the default browser you search you see ads It looks like Google's Google is showing you the ads, but it's like Apple gets all this money and their hands are free. That that really can't happen with
1:35:55
That that really can't happen with Siri, right?
1:35:57
They could partner with Google >> to have [clears throat] Google sell the ads, but it's coming through the s it would be in theory in the future.
1:36:04
It would be coming through the Siri interface.
1:36:08
I don't think they'll ever do it.
1:36:09
I don't think they'll ever put ads in Siri.
1:36:11
And I think if anything, >> they'll put like a cap on the number of queries you can do that need the server.
1:36:20
But then the question is Apple. >> Yeah.
1:36:22
>> The question is you just play it out. Play it out. Play it out.
1:36:24
And how much of a threat like is Google creating an even bigger monster than the one they were trying to, you know, keep down in chatbt, right?
1:36:34
>> Like if you make if you help make Siri a massive success and there's no ads.
1:36:40
>> And I have gone a year ago I didn't use Chad GBT for really any like product based searches.
1:36:46
Like I just still thought that Google was just like objectively better if I wanted if I was like looking up a car or a piece of clothing or anything like that.
1:36:55
And more and more and more of that of those kind of searches I've just ended up in chat because they have better images now and I can be like, "Hey, I'm looking for this exact type of product. Just go find it for me.
1:37:06
Find me the the cheapest, you know, version of it."
1:37:09
And so you would expect that Apple Apple's like maybe like two yearsish behind or maybe 18 months behind in terms of AI capabilities, but I could imagine 18 months from now Apple becomes pretty good at finding you a product that you want and you have Apple Pay built in.
1:37:24
they have and so you just fully cut out a necessarily that becomes a cost center for and sort of cannibalizes like Google's search revenue but doesn't even necessarily get Apple that much out of it itself.
1:37:44
Uh, and then and then like you were saying with like on the app store like it does you're right in that like searching for an app and then being flooded with a bunch of like what feels like spam on an Apple surface area the Apple the company that's meant to be dedicated to just giving you the most magical product experiences.
1:38:03
It doesn't feel Apple at all searching on the app store anymore because Apple knows exactly the app I'm looking for and yet they're serving me junk, right?
1:38:10
And it's usually like >> and and and the Apple monetization for the app store should just be the commission they charge on all the transactions through the app store, right?
1:38:18
And that's controversial enough and has been a source of antirust and >> you know all sorts of complaints.
1:38:22
But at least in terms of well how do you how do you fund how do you profit from the app store?
1:38:29
The story was very simple.
1:38:29
store? The story was very simple. they take 30 to 15% of every transaction and that should be good enough right because you're paying and if you know at some level as a consumer you have to assume that you're paying at least a little bit more for everything you buy through the app store because Apple is taking that commission and to double dip and show it
1:38:47
would be like HBO you pay extra money and in the middle of the movie they have one commercial interruption right and it's like with the World Cup where oh they still don't have commercial breaks but they have hydration breaks And [laughter] >> it's like that's sort of what it feels like with the app store showing you these ads when you search and it's like I'm just trying to find a freaking thing. How about you
1:39:11
How about you just fix search and their search still kind of sucks.
1:39:15
So I Jordy, I think your big question is what's in it for Google, right?
1:39:19
Why is Google helping Apple here?
1:39:21
And I think it is from Google's persp and I don't think anybody knows.
1:39:24
I really don't think anybody knows where any of this is going to be 4 years from now, right? It's so fastm moving.
1:39:33
But I think Google would rather dance with Apple who they know and they know what Apple culturally wants to do like and I don't think there's any kind of [snorts] I mean Apple is doing AI research.
1:39:47
They have AI teams and you know and I think Apple would obviously love to handle as much of this on their own as they could.
1:39:53
But is Google seriously is anybody seriously afraid that four years from now Apple is going to be the producer of the leading edge models, the frontier models? Nobody.
1:40:04
>> And I don't think anybody really thinks there's even like that they're that they've got a path to that or that they're even trying for it.
1:40:09
So I think Google is comfortable working with them where well in a way that they would just prefer to kneecap open AI and anthropic and if there is if Apple was fishing around for a partner like we need somebody who knows their to give us an LLM backend so that Siri is actually useful. >> Yeah.
1:40:33
And I think Google was willing to cut them a sweetheart deal to say, "Let's do this."
1:40:39
And and if it makes if it entrenches Siri for a decade to come as something that a billion iPhone users around the world are relying on, >> we can handle that, right? We know Apple. We're not worried.
1:40:51
That's that's not going to We'll figure out We'll still figure out a way that we'll make money.
1:40:56
We'll still have everybody who's not using Apple products, but a world where like that twoyear ago deal with Open AI, which now makes [clears throat] you laugh with [laughter] with the >> with the deterioration to say the least between Apple and Open AI at a corporate level.
1:41:15
level. But if that had continued and it was OpenAI who was partnering with Apple to do this in a way and and again the original deal two years ago had chat GPT branding in the answers and it was like a >> you know >> yeah the whole thing is so funny because
1:41:33
you have Google being like okay we need to help Apple because like we need to help Apple attack Chachib because Chacht is threatening us but if we if we if Apple's really successful then they'll end up threatening ing our core >> business and Apple's like, well, I we
1:41:49
also want to take we also want to try to kneecap Chad GBT because they're now building devices, but then it >> Google and Apple's relationship is just like headed on a pretty interesting path and I and I can't imagine I I think they both companies will look back and be
1:42:06
like, man, you remember those days where I could just give you tens of billions of dollars and we could just be [clears throat] friends and then, you know, you play it all out and and uh it doesn't it doesn't seem as as friendly. >> Yeah. And I think basically it comes >> Yeah.
1:42:18
And I think basically it comes down to Google is very comfortable playing in a world where the technology is commodity level and that they can at because of their scale they can not just succeed but thrive in a commodity world, right?
1:42:33
Like is the actual computer science behind Google search significantly better than what Microsoft has with Bing? No, not really.
1:42:44
It's just that the scale is there on Google's side and so it's perpetuating.
1:42:50
>> And I think that if AI works out that way, you know, there was somebody at Google years ago who, you know, Google invented all of this technology that we now consider AI, the all the LLM stuff.
1:43:00
But there was a paper that came out of Google where they were they the the one of the scientists argued that there is no moat around this technology, right?
1:43:08
No one company is really going to own this.
1:43:12
And I I think it's an open question whether that's true or not, right?
1:43:16
Like the super intelligence hypothesis is that if somebody gets to the breakthrough of super intelligence first, >> then they will that super intelligence will accelerate their AI at a pace that nobody else can keep up with and no one will ever be able to catch.
1:43:33
will ever be able to catch. I don't think that's where it's going and I don't really, you know, and it just goes back to what we were talking about half an hour ago with the hugging face thing and chat GPT and it's like, oh,
1:43:44
coincident, you know, and this is what makes people roll their eyes and think it's a marketing stunt is then, you know, 3 or 4 days later, Anthropic came out with, well, we went back and looked at our logs and we found Claude broke into somebody four months ago. We didn't
1:43:55
We didn't even know it, you know, and it's, you know, they're they're even Steven and I think I I >> I just think ultimately Google looks at this of let's just shut those guys up.
1:44:07
Let's let this bubble burst. We'll still be here.
1:44:10
They won't >> and Apple will certainly still be here.
1:44:14
>> Um, you know, Apple's the one big company with no exposure in this bubble. Um, >> that's true.
1:44:21
>> Uh, and I think Apple's bet is back to there is no moat here.
1:44:24
And if they don't own this technology that it doesn't it's fine this and I I kind of think it's shaking out that way at least for Apple's business. >> Yeah.
1:44:36
>> Uh last question uh and you can answer in 30 seconds.
1:44:39
Do you think do you think Apple will make an acquisition of an AI company could be an aqua hire or product but I'm thinking more aqua hire north of $10 billion.
1:44:52
>> 10 [laughter] million. No, I think 100 million. Yeah. One.
1:44:57
>> Okay, then let's bring it down 1 billion because there's just not that many there's not that many great teams to be honest that you could get for less than >> I mean they bought Siri.
1:45:05
That was a 100% >> and I was kind of expecting them to try to pick up Poke >> which Cognition just bought.
1:45:11
Poke was like a a really nicely designed assistant >> that worked in iMessage and that felt like a no-brainer for them to just bring in some talent that is excited about AI that's already working in the Apple ecosystem.
1:45:25
Yeah, >> I I would look at it on the silicon side and I think because I think that as this gets commodified, I think that >> you know something like the PA semi acquisition that led to Apple Silicon that that's who Apple I suspect is hunting for is somebody >> who has like a breakthrough spitball idea.
1:45:47
And again, at this point $1 billion probably isn't that much.
1:45:50
So something in that range, but like I would think hardware, something that Apple can do for silicon. >> Yeah.
1:45:57
If you have really optimized silicon serving, you know, lagging models that are a year or two old, like the inference cost can actually be pretty low and then that changes all the calculations about ads that you were talking about.
1:46:08
So, uh, thank you so much.
1:46:10
>> And ultimately, I think it's why Apple's I ultimately I think it's why Apple's staying out of the capex race to keep building out these data centers.
1:46:15
the idea of why are we going to spend all this incredible sums of money, all of our free cash flow to build data centers that are going to be completely technically outdated 5 years from now. >> Yeah.
1:46:28
Well, I want to have you back to have a great debate about Electron versus native apps.
1:46:32
We got to go through all this, get to the bottom of what's going on with these AI labs.
1:46:35
They have such powerful coding agents and yet they can't ship native code apparently.
1:46:39
Uh we'll get to the bottom of that next time you're on the show, but thank you so much for taking the time to come chat with us.
1:46:45
Have a great rest of your summer and >> you cool out there. >> Thanks so much. We'll talk to you soon. Goodbye. >> Cheers.
1:46:52
>> Let me tell you about Figma >> agents. Meet the canvas.
1:46:53
Your AI agents can now create and modify your Figma files with design system context.
1:46:57
And up next we have Sean McGuire and Isaiah Taylor.
1:47:02
Isaiah >> dynamic duo >> two guests.
1:47:05
Third, fourth time on the show. How's it going? What's up, guys? >> Tell us the news. >> Look at you. Nuclear reactor.
1:47:12
We got to get the eagle scream every time.
1:47:14
This is like This is our intro at this point. Exactly. >> There we go. >> What happened, guys? What happened? >> $1 billion series B.
1:47:30
>> Back, baby, >> with the wind up.
1:47:33
>> Crazy, crazy, crazy moment.
1:47:33
Um, where should we start, Isaiah? You want to kick it off? >> Yeah.
1:47:39
I mean, I'm right here in the reactor hall right now with the hardware.
1:47:42
This is where I like to spend my time.
1:47:44
And one thing that was just amazing about Sean's partnership in uh in getting to know this company is he just wanted to know about the hardware.
1:47:52
>> That's really my favorite type of investor, like show me the stuff, like are you actually building things?
1:47:54
I think that's what's special about this company is that we just build and we build fast.
1:47:59
And uh yeah, it's been really great to to meet the Sequoia team and and get to know everybody.
1:48:05
>> And this facility th you're no longer purely in the Gundo. You've expanded.
1:48:09
Where is this facility now?
1:48:11
So, this is our Orangeville, Utah site.
1:48:14
It's our first uh first nuclear site. Y >> Okay.
1:48:16
And what are the short, medium, long-term goals with this site and beyond?
1:48:21
Uh is this still an R&D site or is this going to be generating power?
1:48:25
Uh and when do you start building the factory that build the machine that builds the machine? >> Yeah.
1:48:32
So, we've already made a tiny bit of nuclear power here.
1:48:34
We became the first startup in history to make nuclear power about a month ago.
1:48:37
and uh but it's still a test unit and what we're building toward is something that we call a giga site.
1:48:42
These are massive campuses of reactors and we think they'll make the cheapest energy on earth and so that's what we're working toward here and it starts right here in Utah for sure.
1:48:51
This is a great place to serve data centers, AI factories, then eventually all of the industrial stack that has been falling behind in the United States that depends on energy.
1:48:58
uh aluminum, electrolysis, steel, you know, all of the the different input metals to to making everything in the physical world uh starts on our our gigasites.
1:49:08
So, that's what's coming next and that's really what this raise is uh is going to help support. >> Massive.
1:49:12
Sean, uh I have to assume you've met every nuclear startup.
1:49:18
There's a lot of them, but you've got enough time in the day to to meet them all. Uh I don't know.
1:49:22
I I I doubt I there's so many different applications of the technology, you know, it's not it's not only Valor, but there's only one Isaiah, that's for sure. >> Yeah. Yeah. So, talk about Yeah. Talk about Yeah.
1:49:35
What drew you to the company?
1:49:37
And this is like, you know, this is not a this is not a series A check.
1:49:40
This is a billion dollar. >> No, it's a big check.
1:49:42
This is a big boy check here.
1:49:43
This is a ultra high conviction investment.
1:49:45
Um, look, I'm a former physicist. I have a PhD in physics.
1:49:49
I've loved nuclear since I was a little kid.
1:49:51
I was hoping that, you know, I read Richard Rhodess's Manhattan Project book when I was like 17.
1:49:55
Um, and I've kind of been waiting for there to be an opportunity in nuclear.
1:50:02
Cainly, I didn't think it was going to happen.
1:50:04
I thought we were just going to go like solar battery or solar plus some other storage mechanism future just given how regulated nuclear was.
1:50:13
It just didn't seem like it' be possible to get to scale.
1:50:17
Um, and then two things happened.
1:50:20
one, like power became important in the West again, which is like pretty amazing.
1:50:26
Second, this administration, but I got to say this, I think a very bipartisan thing.
1:50:31
Both the Democrats and Republicans, this power became a bottleneck, have been pushing for more favorable, you know, nuclear regulation and it's starting to happen.
1:50:39
So, even three years ago, I just the regulatory side was too scary for me.
1:50:46
So we've had kind of regulatory breakthroughs with this next generation of founders that are, you know, really trying to bring in this nuclear future.
1:50:56
But for me with Isaiah, there were a few things.
1:50:57
One, just like when you get to know this guy, the level of intensity is psychopathic.
1:51:03
And I mean this in the best of sense, but like the the day he went critical in this reactor he's in, um, first of all, like he thought he was going to go critical the day before, it ended up being the next day.
1:51:16
So, he was up kind of all night, two nights in a row.
1:51:19
Then that night that he went critical, they didn't go critical on like 9:00 p. m. or something.
1:51:23
There was a candidate he wanted to close whose partner was in San Francisco.
1:51:27
So the day he went critical after not seeing for two days, he got on an airplane that night to fly to San Francisco to have drinks with, you know, a candidate and the the guy's wife.
1:51:38
I don't know what time he went to sleep.
1:51:41
And then the next day he's back in, you know, I think it was Utah, maybe Los Angeles, but like getting to know Isaia, the level of intensity is just absolutely incredible.
1:51:50
And kind of the only person I I just I don't know many people that have this level of intensity.
1:51:54
And then just one more thing, um, something that I learned, like a lesson, a mistake I made in the space industry was, you know, Elon started off trying to build the Falcon 1, which was a pretty simple rocket relative to, you know, what NASA could do in the, you know, 80s, 90s.
1:52:12
It was like a 1960s rocket or maybe even earlier.
1:52:14
Um, and there were all these other companies that were telling these like advanced science stories.
1:52:20
we're gonna use carbon fiber, you know, vehicle frames to have, you know, less mass or we're gonna 3D print the rocket.
1:52:28
So, other people were like trying to do this >> very advanced technology to have better mass ratios, etc.
1:52:35
And Elon was like, I'm going to do the simplest thing possible.
1:52:40
Put up one satellite, you know, get that revenue and then go from there to something that's, you know, Falcon 9, pretty damn hard, but still not state-of-the-art compared to what NASA had done in say the '9s, and then from there go to what's truly state-of-the-art, reusability, and then from there go to Starship, which is just completely pushing the limit.
1:52:57
And Isaiah understands this.
1:52:59
He's the only He's one of the only founders I've ever met ever in any industry that like really understands the power of starting with the simplest unit where you can actually scale and and like win and then climbing from there.
1:53:12
So anyways, Isaiah should do the rest of the talking. >> That was great.
1:53:17
Yeah, I I think that's one thing that Sean and I just connected on very early is like lots of investors trying to understand the nuclear space want to know what's special about this technology, what's really unique about this technology.
1:53:29
They they want to find this sort of like IP technical edge where you're doing some special sauce that that nobody else is doing.
1:53:34
And my approach is like no, like we want this reactor to be as simple as we possibly can.
1:53:41
like if we could just staple this thing together from IKEA, then this would be a trillion dollar company much faster.
1:53:47
>> And so there's like two two philosophies that we use in in building the reactor is we try to buy things that are completely off the shelf, like 100% commodity or we make it ourselves and there's very few things in between, right?
1:53:59
There's very few places where we have a supply chain that's dependent upon the existing nuclear industry because if you think about it, we're trying to go 100 times faster than the nuclear industry's ever gone before.
1:54:08
And so if we're plugging too deeply into the existing network, it's not going to work that well.
1:54:13
So we want to use standard off-the-shelf things and and make things ourselves where we can't buy something off the off the shelf.
1:54:19
And by necessity, that means the design the design is extremely extremely simple.
1:54:23
The more complexity you add to it, the harder it is to do one of those two options and the harder it is to scale.
1:54:29
So you know, I think especially in nuclear, this is a difficult thing because it's it's full of very smart people.
1:54:34
It's full of uh physics people and PhDs and people who have spent their life doing complex analysis and they actually want something that is a little bit complicated.
1:54:44
It's like it's an ego thing to to design something that is like complicated and looks very sophisticated and um we have just really rooted that out of our our minds at Valor.
1:54:52
Like we work extremely hard to root that mentality out.
1:54:56
Like it's it's our preference that this thing is so simple that somebody with nuclear PhD looks at like that's like a toy.
1:55:02
And uh it's like great because people make toys in like the millions, right?
1:55:06
They just like stamp them out.
1:55:07
Um and that's exactly what we want to do.
1:55:09
And then the other aspect that's super unique here is just the safety of the overall architecture lends itself to this approach.
1:55:16
If you build a really really safe reactor, you're also by necessity building a really safe reactor because most of the engineering complexity in nuclear comes from safety engineering.
1:55:26
If you look at a a modern pressurized water reactor plant, they're very complicated and 90% of the complexity comes from trying to make it safe.
1:55:35
So the approach that we've taken instead is design it to be safe from the physics and you can actually just delete a huge amount of the bill of materials.
1:55:43
Just like completely remove it.
1:55:44
It doesn't even exist in our in our bomb.
1:55:46
Um, so those are the the philosophies we've we've taken here.
1:55:48
And um, yeah, like listen, I can't give enough credit to Sean in particular and also the >> No, no, this is all Isaiah.
1:55:55
This is this guy's building nuclear reactors. I'm wiring money. Like, get out of here.
1:55:59
I got to give a couple shout outs though.
1:56:03
I got to shout out Palmer Lucky who gave me the hat tip that this is a special company. Thank you, Palmer.
1:56:07
Hats up to Liam Corrian, you know, newest investor at Sequoa, who was my wingman here, >> physics guy, road scholar, Olympic gold medalist, rower, 65 Chad. >> Chad, total Chad.
1:56:22
>> Total Chad and Max Ukropina, who's on the team at Valor, who uh is someone I've known since I was a kid, who for years was trying to get me to come meet this company.
1:56:33
I was like, "Ah, dude, nuclear is too hard.
1:56:34
Regulator is not favorable." one.
1:56:36
Anyways, Max, I look stupid. Good job.
1:56:39
>> Uh, how Isaiah, how have the Have there been talent wars in in nuclear?
1:56:42
You know, you're flying on on such an important day to go to go meet someone, uh, which many founders will have done, but that's felt like maybe urgent.
1:56:51
Uh, how intense has the competition for talent been?
1:56:56
This round, I imagine, will give you a lot of advantages just having um, yeah, more firepower to to continue compounding a great team.
1:57:04
But walk us through the last maybe two years in the category.
1:57:09
>> Yeah, look, I I view my job essentially as trying to get the most talented people in the world to come and build this mission with me.
1:57:16
Um there there are no blockers in in front of us.
1:57:18
Like we have a regulatory environment that's ready to move.
1:57:22
We have an enormous demand signal.
1:57:24
We have customers that want to buy.
1:57:25
We have an architecture that's very simple and very scalable.
1:57:29
And now we have a lot of capital in the bank.
1:57:30
And the blocker on us becoming the, you know, 10 50 hundred trillion dollar company that makes most of the world's energy is the smartest people in the world coming and and joining us in this mission.
1:57:40
So I spend an enormous amount of time of my time doing that.
1:57:41
I actually would say that our our primary talent competition is in other places where you can move the needle on a global scale that need incredibly talented engineers.
1:57:53
Um I I don't I don't see it as sort of like okay other nuclear companies.
1:57:57
It's it's more like, you know, what are the other companies that are genuinely going to change the course of humanity in the next 50 years?
1:58:04
And like those are the people that that I'm fighting for. >> Mhm.
1:58:07
Yeah, that makes a lot of sense.
1:58:08
>> Lessons from Yo, sorry.
1:58:10
>> Well, if I can say one thing on that, something I've seen from Isaiah that is very rare.
1:58:13
He is looking for just ultra talented generalists and he tests people like crazy and it's and like real world tests, you know, like, hey, I'm going to be in someone says like, hey, I want to interview.
1:58:25
And he says, okay, I'm in Texas.
1:58:26
It's like meet me here tomorrow and if they get to Texas then they have a shot and if they don't make it to Texas then they're weeded out.
1:58:32
It's just not having that level of like commitment.
1:58:35
And anyways there not many people that understand you have to kind of design the hiring process to find the people that select into a crazy mission >> high agency. Yeah. >> Yeah.
1:58:49
>> You're revealing the secrets here.
1:58:49
Sean, yeah, this [laughter] now now the next three are going to show up to the meeting and I'll have to figure out some some other way to weed them out.
1:58:56
But yeah, that was it's very true.
1:58:59
>> Uh >> if they show up, it's still a good it's true. It's true. Still a great set.
1:59:03
>> Uh lessons from SpaceX.
1:59:03
One of the interesting >> Yeah, I can imagine. >> Yeah, sorry.
1:59:07
I got a dentist appointment in Utah all places. I got to get out there.
1:59:12
It's like this, you know, people being like, "Yeah, I got a dentist appointment.
1:59:15
I have to take three [laughter] commercial flights, you know, and drive 3 hours to get my to my dentist appointment. >> Yeah.
1:59:21
[laughter] >> Uh, one of the interesting SpaceX stories is residual capability.
1:59:25
They build all this launch capacity, they have maybe too much launch capacity, you get Starlink, amazing business, becomes a telecom company.
1:59:33
Not probably not in the first pitch deck. Uh, Sean, you'd know.
1:59:38
But is there a world where there's a residual capability from what you're building here where you're using the electrons that you're generating?
1:59:43
uh yourself or do you see there's just like so much demand that just that that's something that's uh like is very very unlikely to happen?
1:59:54
>> Yeah, I mean look you you know and you and I have talked about this before like I think Valor actually started I look I grew up watching Elon, right?
1:59:59
I I watched I read everything that I could about the Falcon 1 and the Falcon 9 and saw this very simple path that you just they call it flight rate.
2:00:08
I think at SpaceX we call it tick rate.
2:00:09
Tick tock is basically how quickly can you go from cores turning on, you know, each one.
2:00:15
It's it's like a look back average metric of the time between new cores turning on and it is predictive of who's going to win and who's going to have the lowest cost and the highest capacity and all these different things.
2:00:25
And we actually started with the idea of that excess capacity and being able to make the world's commodities, right?
2:00:31
And I think that the AI thing happening as quickly as it did and power prices changing so dramatically where people will send a $200 PPA is like okay obvious that we should sell electrons. >> Yeah.
2:00:44
>> But no question is our long-term vision to actually have the cheapest energy on earth and to use it for our own things.
2:00:50
I mean we see a a vision of the world where steel is just way cheaper than is today.
2:00:55
Aluminum is way cheaper than it is today.
2:00:56
the manipulation of matter is a lot cheaper because you have robotics hooked up to AI that's doing matter manipulation and vision and all these things just take energy.
2:01:04
Um, and so it'll be interesting to see like where we decide to play in the stack.
2:01:07
I think like we want to be in the in the business of turning on thousands of reactors primarily, but there will be a couple of like massive massive markets that we attach to that uh that we can just make at a competitive price that no one else in the world can cut.
2:01:20
And also uh like the nature of the AI boom is that you need a lot of energy in a single place which is perfectly suited for you as opposed to if we were in some boom where we need everyone in their pocket needs twice as much energy you would have to maybe transform into another source of energy or do something else in the supply chain.
2:01:38
Uh Sean >> did you have something?
2:01:42
>> I no I agree I violent agreement. >> Fantastic.
2:01:45
[laughter] >> Well thank you so much. >> Yeah.
2:01:47
I was just going to say that's the the AI the AI thing like perfectly matches gigasites, right?
2:01:52
Like the the idea is nuclear is a thing that benefits from extreme scale.
2:01:57
Like if you could build a thousand nuclear reactors right next to each other, you should like you will get the cheapest energy anywhere in the universe if you do that.
2:02:05
And so AI is like the the perfect thing to do with that first.
2:02:09
But we will do many many interesting things with it over the next century.
2:02:13
>> Well, congratulations.
2:02:15
Excited for you guys to partner up.
2:02:17
Dynamic >> duo tag teams are fun. Peace. >> Goodbye. >> Cheers.
2:02:21
>> Let me tell you about MongoDB.
2:02:21
What's the only thing faster than the AI market?
2:02:24
Your business on MongoDB. Don't just build AI.
2:02:26
Own the data platform that powers it.
2:02:27
We're going backto back energy round with another backto back billion dollar round.
2:02:34
We have Justin Lopez from Bass Power Company. Justin, how you doing? Good. >> How you doing? Good to see you. >> Give us the news. What happened today?
2:02:46
raised raised a bunch of money and not just a capital raise though. Uh break it down.
2:02:54
But but first for anyone that's been living under a factory, reintroduce base power, what you're working on, why it's important, and then I want to talk about the news under the headline from today. >> Yeah.
2:03:08
So, welcome to Factory 1. Good to see you guys. Thanks for having me on.
2:03:12
Uh today we're announcing three different things.
2:03:14
Number one, launch of the factory that I'm sitting in right now, it's behind me, that builds batteries.
2:03:19
Number two is uh $1 billion raise at $13 billion post money valuation.
2:03:25
And the third thing is base core is our custom fully custom designed, engineered, installed, manufactured here in Texas.
2:03:33
Uh what we do is we design batteries.
2:03:33
We manufacture them here.
2:03:35
We them on homes and then we own and operate them as a distributed fleet, distributed power plant.
2:03:41
Uh that's the business today. >> Uh incredible.
2:03:44
Talk about the decision to not announce the factory or talk about the factory very much until it was actually producing uh product. >> Yeah.
2:03:55
You know, it's like uh I I I put this on X, but you know, a lot of factories get announced with a bunch of people in suits and hard hats shoveling like an ounce of dirt. And that's cool. It's groundbreaking.
2:04:04
exciting and all that, but like factories are meant to make stuff and yeah, we wanted to make stuff beforehand.
2:04:10
So, uh we're we're doing that today.
2:04:12
We're just getting the line ramped up.
2:04:13
The the station behind me is starting to build some modules.
2:04:17
You'll see some come through uh as we talk here.
2:04:19
But, um yeah, look, you want to have you want to have the real deal ready before you talk about it. >> That's right.
2:04:24
And when did you when did you guys actually break ground on this site because I imagine >> So, the site Yeah, the site was already here.
2:04:32
So this is actually the old printing press of the Austin American Statesman building.
2:04:34
We started building the equipment behind me about 5 months ago.
2:04:39
So it hasn't been a super long time.
2:04:41
And we started warehousing here about 8 months ago.
2:04:42
Uh previously we had a smaller facility just north of here in Austin.
2:04:46
But um yeah, we're uh we're we're we're live and running now. >> Very very cool.
2:04:50
Talk about talk about the state of the business overall.
2:04:56
you know, how the how the market in Texas is evolving, what what people can expect uh from base over over, you know, the next couple years in terms of new markets and things like that. >> Yeah.
2:05:07
So, as I mentioned, look, we install batteries on homes.
2:05:08
Turns out there's a lot of homes, not just in Texas.
2:05:11
Uh so, we recently launched our Chicago market.
2:05:13
Uh and we've also launched uh I think it's six or seven utility partnerships now uh here throughout the state of Texas.
2:05:19
Uh you'll see us announce a few new states and a few new new utility partners hopefully by the end of this year as things get signed and and under contract.
2:05:27
Um and that allows us to go into more states here in Texas.
2:05:32
Texas has got a partially deregulated market which means that we can go to market without having a direct relationship with the utility.
2:05:38
In other states like California where I'm originally from in Michigan those are regulated states so they require uh deals with utilities.
2:05:45
So we have two go to market motions regulated and deregulated.
2:05:49
both work in various different states uh in the country.
2:05:51
And uh look, the goal is to have a battery on on on every home in the US and eventually internationally.
2:05:57
Uh we've started here in Texas.
2:05:58
We're in all the major markets now, also in Chicago, but we'll be launching new ones here pretty soon. >> All right.
2:06:05
As a if somebody's a a homeowner in Chicago or Austin or Texas, broadly, give us the the elevator pitch for why they should install uh >> Yeah.
2:06:17
Look, so we we make your power more affordable, more reliable.
2:06:19
So if you're in a place like Houston or Dallas where you can choose your power provider, you sign up with us, we sell you electricity every month at a very affordable rate.
2:06:28
We also put a battery on your home that is only typically a few hundred depending on exactly where you live.
2:06:33
That provides you backup protection if the grid goes out uh and also supports the grid when the grid's up and running.
2:06:39
That's how we monetize and how we make money is that grid support function.
2:06:42
Uh and so it's affordable, reliable power. That's the simple pitch.
2:06:45
Is there an element of uh price savings from drawing power from the grid at low rates, storing it and then uh reusing it in the house when rates would be higher and just sort of load balancing at the house level. >> That's exactly right.
2:07:04
That's basically how it works. Okay.
2:07:05
So, we charge uh the battery when energy is abundant and available when there's not a lot of uh stress on the grid and then we discharge it into the home and sometimes if we decide to spin the meter backwards, push back onto the grid, there's when there's uh some stress on the grid or when there's uh peak demand times that typically happens, you know, in the dead of winter and in the height of summers. >> Okay.
2:07:27
Uh what about throughout the day, throughout the week?
2:07:29
Like when are typical peak load times?
2:07:31
Because during the day it's hot, people are running air conditioning, but at the same time that might be when solar panels are collecting energy.
2:07:39
So like what what is the actual reality of like a typical grid, the Austin grid?
2:07:44
Does this vary grid to grid?
2:07:47
H like what what is the uh the differences and the nuances of load balancing? >> Yeah.
2:07:54
So you're you're exactly right.
2:07:56
Basically, what you care about is the difference between available capacity or supply and the amount of Yeah. Yeah.
2:07:59
And so here in Texas and in many places, especially in the south where it's quite hot in the summer, uh you typically have these peak times in the summer at least in the in the early evening.
2:08:09
So kind of like, you know, 4 to 6:00 p. m. 5:00 p. m. to 7:00 p. m.
2:08:13
where the sun is setting, so supply is coming offline, but people's people are coming home, plugging in their EVs, turning on their uh air conditioners, etc. Got it.
2:08:22
And so that's really the where the where the supply and demand meets.
2:08:26
Then in the winter here in Texas and in many places in the north, you have these early morning peaks.
2:08:31
Basically, people are waking up using more electricity.
2:08:32
Your heaters, your electric heaters are coming on. Yeah.
2:08:36
Uh they're on throughout the night.
2:08:37
Um but the sun hasn't risen yet.
2:08:39
And so batteries help fill those gaps.
2:08:41
That's at the macro level.
2:08:43
And then at the at the more micro level, they're also able to shave peaks off of the lines on the grid.
2:08:47
So you might have enough capacity in aggregate in bulk, but one part of Houston or Dallas or Chicago may need support.
2:08:54
And so because we've got tens of thousands of these systems out there, we can say, "Look, in this neighborhood, we need some support.
2:09:01
We're going to discharge just in that neighborhood."
2:09:03
And that's the beauty of having a high volume of systems.
2:09:08
>> Uh I see a lot of robots of different types moving around in the background.
2:09:13
Where are you guys getting the most leverage from robotics?
2:09:17
I can imagine as you started the facility it can make sense to to do to figure out the sort of process using a lot of your your uh human talent but um where are you guys getting the most leverage and and how how automated can this become over time?
2:09:34
Can it become you know fully lights out factory?
2:09:36
Is that even something to aim for?
2:09:38
But what's your view on all that?
2:09:42
>> Yeah, you know robotics is a great is a great place but it doesn't have a place for everything.
2:09:45
There are certain tasks that do not make sense to automate or at least not as a starting point.
2:09:49
And then there are other tasks that do.
2:09:50
So like what you see exactly behind me, you've got the robots that are driving through the tunnel and that tunnel is placing these stacks of battery cells that are created also by robots outside of the frame here.
2:10:01
That is a great thing to automate because it's relatively heavy, relatively repetitive and requires a lot of fine precision.
2:10:07
Then there are other tasks, loading in certain components, testing certain things that require a little bit more finesse, a little bit more dexterity that are pretty hard to not impossible but harder.
2:10:17
And so we've said, look, we're not going to automate those as a starting point.
2:10:22
>> We're going to focus on the things that are, you know, either either dangerous or hard to do repeatably or are quality concerns and then we'll automate more and more over time.
2:10:29
So it's just it's a I'd say it's a it's a it's a phase in approach.
2:10:33
We're starting with what makes sense to automate and we'll likely trend towards more automation.
2:10:36
But the fundamental thing is trying to, you know, not do tasks that you don't need to do in the first place.
2:10:41
You delete the task, then you optimize [clears throat] it, and then you automate it.
2:10:46
>> What's the state of blackouts, brownouts, blackout uh prevention that feels like a huge selling point?
2:10:52
Uh you're selling a sense of security, a sense of uh comfort during a winter blackout or summer.
2:11:01
Uh but at the same time uh I how often are they actually happening?
2:11:08
It seems like a known problem.
2:11:09
Grids and energy providers have been working on this at a at a you know higher level than you.
2:11:13
Uh so is the problem still broad?
2:11:16
How big is the problem of just losing power outright?
2:11:21
And how big of a factor is that for you in the sales process?
2:11:25
>> So it's huge in the sales process, right?
2:11:27
People want to have more affordable, more reliable power. Yeah.
2:11:30
the reliability is different from from place to place.
2:11:32
So typically coastal regions, so if we think of the Texas coast, Florida, the east coast, etc.
2:11:38
where you have a lot of hurricanes, you typically have more power outages. Okay?
2:11:42
>> Also, in more rural areas, so if you're at the end of a line, basically any break in that line all the way up to the substation is is going to cause you to have an outage.
2:11:49
And so if you have more line in front of you, basically you have typically lower reliability.
2:11:54
>> Yeah, >> it totally varies though.
2:11:55
So, uh, very very very rarely is there an outage because there's not enough power.
2:11:59
Most outages occur because of a weather event, because, you know, uh, a tree falls onto a onto a power line, etc. because of a storm.
2:12:08
>> Um, but but outages are arising generally across the country.
2:12:10
There are places where they are getting better. >> Okay?
2:12:14
>> It's a factor in the sales process, but if I'm honest with you, the way we think about this is more about portability first, reliability as a as a benefit of having this system on the grid.
2:12:22
Uh and it reli it adds reliability to the whole system, right? It's not just your home.
2:12:28
Obviously, it'll back up your home if and when the grid goes out, but it's more about adding reliability, capacity to the whole system, so you can have more load and uh you know, more EVs, more homes, more data centers, etc. on the grid. >> Got it. Got it. >> Absolutely crushing.
2:12:44
>> My my last question is what what does it actually take to expand to a new market?
2:12:48
I mean, I want one of these in California.
2:12:49
Um, but uh it seems like you're I mean you're growing the business and the factory and like there's there's immense scale billion dollars raised, $2.
2:12:57
5 billion raised and yet geographically it feels like a little small. It feels tight.
2:13:01
Sometimes you have companies that are Yeah.
2:13:03
We're available in every market all over the globe.
2:13:07
We'll ship our thing everywhere and we're a tiny company.
2:13:09
You're sort of the opposite. Very focused.
2:13:10
What does it take to bring a new state, new city online?
2:13:14
Why the measured approach to actual go to market? Yeah.
2:13:20
So, I'll start with the latter point, which is the sort of measured approach.
2:13:22
I'll remind you that Texas is larger than most. [laughter] >> Yeah.
2:13:27
Got more more homes and more electricity load than than than many large company countries that you've heard of in Europe and [laughter] so so Texas is a big place.
2:13:36
But regardless, um I'd say the uh the geographical tightness is a feature, not a bug. >> Okay.
2:13:41
>> And the reason for that, >> the reason for that is like not only do we have a factory behind me that produces these things, but more importantly, we have a factory in the field.
2:13:48
They've got hundreds of people out in the field installing these things. Okay.
2:13:51
And we've got trucks and crews and tooling and all this other stuff.
2:13:54
And so having geographic density is very helpful from an efficiency.
2:13:59
>> Now to answer your question though on how do you expand new markets, >> there are oversimplifying here, but there's basically two types of markets.
2:14:06
There's ones like Texas where you can choose your power provider.
2:14:08
Y >> uh places in Texas, not all of Texas.
2:14:11
And then there are there are markets like you have in California where for the most part especially in residences you cannot choose your power provider.
2:14:18
If you live in Northern California, PG& is the only game in town.
2:14:20
If you live in Southern California, self Galison or LWD or or other utilities.
2:14:24
Um and so in the deregulated markets, we can essentially go there and start the business and and there's nothing really stopping us except for a bunch of regulatory uh hoop jumping to do and setting up of a warehouse and hiring people and all in which is its own challenge.
2:14:38
In the regulated market, it's basically getting a deal with the utility.
2:14:41
It's a B2B sales motion where we go to utility and say, "Hey, we offer megawatts as a service.
2:14:47
We'll go install these batteries that we've that we've built behind me.
2:14:50
We'll put them on homes in your service territory.
2:14:51
You can control them, operate them, and use them to add flexible capacity to the grid."
2:14:55
And so, that's a matter of, you know, B2B sales, long sales cycles, and and working with both the regulators and the utilities in that state uh to go into those states.
2:15:06
I'll say we'll we'll launch a few new regulated uh utility opportunities over the next next few months here.
2:15:10
Um and then and the deregulated part will also launch a few new states, but as I said like it wouldn't be surprising to me if we're only in you know 10 15 20 states over the next few years just because again the geographical density is so helpful for us. >> Yeah. Yeah.
2:15:23
And of course like you you only have so much manufacturing capacity.
2:15:27
You have to load balance your own business across your sales people, your installers, your manufacturing capacity, your supply chain, all of this stuff.
2:15:34
That makes a ton of sense.
2:15:34
Uh congratulations on the progress and thank you so much for coming on and sharing it with us.
2:15:40
>> Love seeing you guys cook. >> Yeah, amazing work.
2:15:42
>> And thanks for the thanks for effective the factory demo.
2:15:45
>> Yeah, that is remarkable. >> I know.
2:15:47
We'll we'll come by next time we're in town.
2:15:49
>> Yeah, that'd be awesome. We'll talk to you soon. >> See you. >> Goodbye.
2:15:52
Let me tell you about the New York Stock Exchange.
2:15:55
Want to change the world?
2:15:56
Raise capital at the New York Stock Exchange. our next folks.
2:16:00
I think we have to issue uh sort of like a a warning to the viewer.
2:16:07
The next guest is building something truly horrific.
2:16:09
Uh so avert your eyes if you are a scaredy-cat because uh our next guest has built something terrifying.
2:16:20
Bo Gaston, welcome to the show. How are you doing? >> Great. How about you guys? >> We're doing well.
2:16:25
Uh talk talk to us about what you're building.
2:16:28
Tell us about the journey, the goal.
2:16:29
uh the mission I want to get into the aesthetics everything uh but also the applications. >> Yeah. Yeah.
2:16:36
So uh the full timeline uh a very high level um we'll start about six years ago a paper comes out of MIT where a guy Ben Pat made this quasi direct drive actuator >> quite cheap.
2:16:52
I think it's about 700 bucks.
2:16:54
the these are kind of like the building block of these humanoid robots and a large reason that you're starting to see a lot of these pop up that uh he he open sourced the design as well.
2:17:02
So I'd seen back then it kind of looked like it was going to become possible to build humanoids a few years in the future that are not like only affordable to to a huge lab. Right?
2:17:14
So around 2022 I start to take on this design that you see in the background.
2:17:22
Uh what I wanted to do with it was really make a robot first for myself.
2:17:26
And uh what what what I would like to do with the robot is uh you know not do the dishes or fold my laundry.
2:17:36
>> You want this thing to do the dishes. >> No.
2:17:39
He's saying he doesn't care about a robot that WILL DO THE >> OH, OKAY. >> YEAH.
2:17:43
Seems like software update.
2:17:43
Uh I wouldn't try that quite yet.
2:17:46
Yeah, >> my kind of thesis is it's going to be more useful to have something that's stronger than you at first and maybe >> you could sacrifice some precision [clears throat] precision and intelligence, right? >> Sure.
2:18:00
>> And uh yeah, running a chainsaw uh I get that people have thought like, wow, this is crazy to give a robot a chainsaw.
2:18:08
It's you know uh a bit scary, but I mean what's really scary is operating a chainsaw as a human.
2:18:13
So I kind of looked at that uh you know which is something I'm well familiar with living out here in the woods.
2:18:20
So >> uh my kind of thought is this is a good tool to start with.
2:18:23
I mean running a saw is the most dangerous job in the US.
2:18:28
It's it's 130 per 100,000 >> uh workers per year.
2:18:31
It's 30 times more dangerous than the next most dangerous job. >> Wow.
2:18:36
And uh yeah, I mean you could imagine not only is a chainsaw dangerous as a tool, but what trees are you cutting down, ones that are damaged near power lines, ones that are uh next to a fire bake in a wildfire.
2:18:49
So it's just a preposterous kind of situation.
2:18:52
So looking at what >> Yeah, the form the the use case makes total sense.
2:18:58
Um I'm curious to get into a couple questions.
2:19:01
Uh we should start with I think what everyone's wondering is why make it look like you know uh >> uh a demon from from Hades.
2:19:09
[laughter] Uh >> especially for some of these like disaster use cases.
2:19:15
You know, I was thinking uh I've been in situations where I've never been like really really really close to a to a to a wildfire, but I've been close enough where the sun is gets a little bit, you know, blocked and it's dark and a little hazy and and if I saw one of these things, you know, kind of walking out of the smoke, I'd be I'd be a little freaked out.
2:19:39
Um and I think a lot of people might feel that way.
2:19:43
Um but uh but yeah so so talk through the decision- making on making it look uh demonic and then and then I really want to understand like the actual uh functionality of the form which we can get to. >> Yeah, sure.
2:19:58
So um I will say yeah the the rescue stuff also was kind of propagated by the the virality a little bit.
2:20:07
That's definitely I was not uh aiming to pick you up out of a burning building, you know, like a hero in a movie.
2:20:13
Though I would point out if that did happen, like, you know, if someone's saving you, I'm not going to probably be too picky.
2:20:19
And if it's centaur in the mouth, >> Yeah. Yeah. Exactly. You just don't do it. >> Yeah.
2:20:26
But uh you know it's interesting with the anthropomorphic stuff on humanoid robots like I think it's actually really disarming and people kind of aren't understanding what's really going on under the skin which you can see a little bit here but I don't know like have you guys ever used a drill press? >> Yeah. >> Okay.
2:20:43
So you kind of know they're dangerous and you know the workpiece could fly out of it and they got a lot of torque.
2:20:49
So imagine if someone hooked 20 drill presses up series par parallel all together and then used basically some arcane knowledge uh of machine learning to make it balance and walk.
2:21:02
This is pretty much what a humanoid robot actually is, right?
2:21:04
That that's around the same power that you're seeing on on leg actuators on >> uh most humanoids today. Okay.
2:21:10
So where crazy >> where Yeah.
2:21:13
where you're going is basically like a humanoid itself looks tame, but in reality it's potentially incredibly dangerous to be around.
2:21:22
>> So, it's better to let people know.
2:21:24
You're putting like caution tape on it effectively.
2:21:26
You're telling the user, "Hey, this thing is a chainsaw.
2:21:28
It's going to be doing work in a dangerous environment."
2:21:31
You should be triggered to say, "Hey, I got to step back because this is serious business." >> Exactly.
2:21:38
Like I don't know if you guys have ever been on a big uh work site or in a factory and first time you go in there maybe you're kind of putting your back to the wall and like you're a little overwhelmed and that's kind of the right attitude to take when you're around something that can knock your head off.
2:21:50
So >> from my perspective uh I made one in gray as well and you could kind of imagine it actually kind of looks like you know a little bit like a gray goat.
2:22:01
You know you might want to go feted. >> Yeah.
2:22:03
Um, this is >> So, do you do you think that do you think you'll end up redesigning it?
2:22:08
Because if you want to just show that uh at least like the head uh cuz if you want to just show that it's dangerous, you could just have it uh you know, maybe a speaker or a light that says like, you know, [laughter] stay >> caution tape or, you know, >> a lot of way to do it besides besides the horns, even though clearly [laughter] clearly it sounds like you just wanted to make this.
2:22:26
Sounds like you live in the woods.
2:22:28
Sounds like you want a few of these patrolling around your house. Yeah. >> Yeah.
2:22:33
I mean, I think the other thing about humanoid robots, like you we all kind of know that they're not purely like a perfect productivity maximizer device, right?
2:22:41
Like they have they have to be emotive and cool and we've wanted them for 80 years or something and been dreaming of this stuff.
2:22:48
Um, and I'd say kind of like a car.
2:22:50
Like, uh, no one buys a car because it's the perfect like mobility blob with no personality that, you know, is exactly as safe as you want.
2:23:01
Yeah, maybe a few people do, but, you know, humanoid robots, like cars, the ones that people really like, have to have their own personality a little bit.
2:23:09
So, I think trying to redesign it to be like, uh, okay, maybe the optimal safety would be you have to have a giant yellow siren on the top.
2:23:16
Um, but uh, yeah, it's just not as exciting.
2:23:20
So, we got to keep it interesting, right? >> Yeah, I get it.
2:23:24
And I'm sure there's I'm sure there's people out there that want to cut down some trees that genuinely would prefer this form factor than uh, something more tame.
2:23:34
Talk about uh, for the types of environments that you're imagining uh, the robot in, why four legs is better than one?
2:23:42
I can imagine just weight.
2:23:44
>> One leg, >> sorry, two, two, [laughter] two. One leg is really tough.
2:23:47
>> One leg, but but imagine a human one leg.
2:23:50
[laughter] >> The pirate robot is leg four legs versus two legs.
2:23:55
I imagine if you want to be able to actually um manipulate like something like a saw, you want to be able to having the stability, but also the terrain.
2:24:05
>> Yeah, you want to be on wheels.
2:24:05
And I think there's been enough videos now of the robot dogs kind of running around crazier terrain that show that yeah, four legs is superior than two to to two.
2:24:16
And >> I'm I'm all in on centaurs. Let's hear it though. >> All right. Yeah.
2:24:19
I mean, bipeds are tough.
2:24:21
You have to move the center of gravity up for the whole bot, right?
2:24:24
Because you're putting the pack up in the human chest or I have it in the horse body.
2:24:29
>> Um you're getting actuators closer to the ground because their ankles are actuated.
2:24:33
So, if you think about walking around in the forest, you're putting electronics really close to the ground.
2:24:39
And, you know, if you have a linear uh actuator, then a moving shaft like right on the ground, whereas this thing uh you know, the closest actuator is is nearly three 3 ft off the ground.
2:24:48
Um the way I'm driving the knee, um it's easier.
2:24:53
You know, I'm not a This is not a huge project.
2:24:55
project. that I think another kind of misconception from the uh viral explosions like we're some huge stealth startup that's popping up and these things are going to go knocking door to door but uh no this this is more of a passion project so doing a biped today
2:25:10
is is really tough um you're not going to see all but you know the best people doing uh and even then I'll point out there's of course a lot of curation for what you see with pipets [laughter] from from anyone I think everyone kind of knows that They're pretty tough to to get stable. And I think another question is why not
2:25:28
And I think another question is why not do tracks or wheels?
2:25:32
>> That's pretty tough in robotics, too, because if you're trying to keep all four wheels on the ground, like not like these, uh, the ones you see out of China that are wheels and a dog, but just wheels, you know, then you're going to have to have some suspension, uh, which is kind of the enemy of robotics is having these unknown spring forces and stuff like that.
2:25:49
And tracks [clears throat] are just really heavy and really actually not all that stable for uh the size that they are.
2:25:55
If you think about a little tracked square driving around the forest if you're on hard pack ground, it's actually could still be a little tippy.
2:26:03
So, uh yeah, four legs works pretty well. >> Yeah.
2:26:06
>> Have you gotten any death threats since the viral moment?
2:26:11
>> Seems like a long personal threat.
2:26:13
>> He's got a robot army at his disposal.
2:26:15
Well, I imagine some people might might think now is the right moment before you have, you know, a hundred of these on your property.
2:26:23
>> The real >> um I guess though the few people that were offended by the design are Christian, so that you know peaceful people.
2:26:30
So, uh, you know, fortunately, I've had, you know, people, uh, say I should stop or, uh, you know, that it's, uh, someone sent me an email today that said, "My company is now owned by God, >> uh, who will save me and stuff like that."
2:26:47
But, no, nothing too crazy.
2:26:47
Um, >> the [clears throat] more surprising reachouts have been police departments.
2:26:54
Oh, >> that is what I wouldn't have thought would have happened, but >> reaching out to partner with you or arrest you. >> Yeah.
2:27:01
To ask if it, [laughter] you know, could use for for public safety. So, >> Okay. Yeah. Yeah. >> No, I do that.
2:27:07
>> If you've ever been in at an event where a bunch of police uh calvary and then there's just like >> people just dissipate. Yeah.
2:27:15
There's something about being around a large horse where like it just doesn't >> I was going to say the humanities that that gets >> I hadn't even thought about that. >> Yeah.
2:27:26
>> I I just think for for riot control the the the horse is just like it won't quite it's not like you're going to get hit by a car but there's a natural human reaction to sort of just moving out of the way.
2:27:34
>> The chat wants to know about the pogo humanoid uh a pogo stick. >> There is one. >> There is one. >> Yeah. Yeah. There's at least one.
2:27:41
Um look yeah if you search potentially even a scarier format where the robot can [laughter] jump 30 feet in the air and it's just >> pogo stick.
2:27:52
It's a psycho clown on it.
2:27:54
Uh talk to me about controlling this thing.
2:27:57
Uh I imagine you're not doing full autonomous control heavy tea operation, but what am I because you have multiple cameras.
2:28:06
So, are you looking at a a screen with multiple camera feeds and then controlling with like an Xbox controller? Uh, what is the process?
2:28:16
And then I imagine that as you go forward towards controlling a chainsaw that's a little bit harder to control with a Xbox controller.
2:28:23
So, will you have gloves VR?
2:28:25
How are you thinking about that?
2:28:28
>> I got a solution for that. >> Okay. Um, let's see it.
2:28:30
>> We'll see if we could see.
2:28:30
No one's seen this chainsaw, so I guess you guys could uh >> There we go. >> Yeah.
2:28:35
>> Do it on your show, but There we go.
2:28:35
So, this chainsaw is >> to a degree of freedom.
2:28:41
Uh, you know, kind of like a Let's see if I can line it up a little better.
2:28:45
You can kind of see what's going on.
2:28:46
Yeah, [clears throat] I got to go this way.
2:28:48
I have my things mirrored. >> Yeah.
2:28:50
>> Um, but yeah, it's something I thought about.
2:28:52
So, uh, yeah, it's think about like this like you have you can split robotics into moving around and doing something with the endector.
2:29:01
And the good thing about a quadriped is, you know, you could kind of park it and then the hips have enough mobility where you could kind of control it almost like it's an excavator if you ever been to one of those.
2:29:13
So, it's a little bit more intuitive >> to do than trying to do something like dynamically like you see uh you know people with VR goggles and >> uh gloves to control a humanoid that has hands or a biped and all that.
2:29:27
Uh, that's again like way way outside what I'm able to accomplish.
2:29:32
So, you could think about it more like you're driving a big >> car that keeps his hips square to the ground and then the top half kind of acts more like it's an excavator. >> Yeah.
2:29:44
>> Um, where you're kind of controlling the two plane.
2:29:47
>> Do you think there's more of a consumer market for robotic horses?
2:29:52
because there's a lot of lot of people out there that uh love horses, but >> horses are quite expensive to maintain and uh I imagine if you made a robotic horse that you could control with an Xbox controller and sit on it, there would be some some consumer market for it, >> like a riding one.
2:30:10
There was a demo that came out of Japan, I think.
2:30:12
Maybe we shouldn't be surprised that they're on the the cutting edge of making that sort of thing.
2:30:18
Uh but yeah, I don't know. Would you buy one? >> I think I would.
2:30:24
I think I would potentially get one for uh for my daughter. Yeah.
2:30:28
>> Oh, not to like commute in.
2:30:30
>> Uh the the robo horse commuter galloping to work if you could get it up to like 40 miles an hour would be would be quite appealing to me, but um maybe maybe more just for fun use case early on.
2:30:42
So something to consider.
2:30:44
You need to make the head a lot a lot prettier though.
2:30:45
I think really [laughter] catch up.
2:30:49
>> Like a angler fish head, >> you're thinking?
2:30:51
>> I'm thinking more like a normal horse. [laughter] >> Oh, okay.
2:30:54
I haven't thought about that.
2:30:58
>> Well, thank you so much for coming on the show and breaking it down for us.
2:31:01
Uh, good luck with wherever this project goes.
2:31:03
Would love to stay in Keep us going.
2:31:06
I will say when when John showed me the website, I said, "This is clearly somebody just messing around that vibe coded a site."
2:31:14
I love that it's a real thing. Amazing. >> Yeah. Yeah.
2:31:19
It's it's going to be amazing to see where this goes.
2:31:22
Congratulations and thank you so much. We'll talk to you soon. >> Have a good one. >> Have a good one.
2:31:26
>> Uh up next we have Ron Ireel from Intology.
2:31:28
He's the co-founder and we're talking about RSI, recursive self-improvement. Is it here? It might be. We'll get his take. Ron, how are you doing? >> Really well.
2:31:41
Thanks for having me on, guys.
2:31:42
>> Thanks for hopping on.
2:31:42
Uh first time on the show.
2:31:44
Why don't you introduce yourself and the company a little bit? >> Yeah, of course. So, my name is Ron.
2:31:47
I'm the co-founder of Intology.
2:31:49
Uh, at Inttology, our mission is to automate scientific discovery and we're starting with AI R&D.
2:31:55
>> Um, so today we have some pretty exciting results to talk about regarding automated post training of other language models and lots more to discuss. So, glad to be on. >> Yeah.
2:32:03
How would you characterize the uh the the progress the announcement?
2:32:08
Because people can get sort of lost in benchmarks.
2:32:11
Are you 20% on this thing, 99% on that thing?
2:32:12
like like qualitatively where do you see the technology today? >> Yeah, absolutely.
2:32:17
So, uh fundamentally we believe that automating discovery is a domain agnostic problem.
2:32:22
a domain agnostic problem. Uh what that means is that the structure of discovery problems is pretty similar across domains in the sense of you know no matter what problem you're looking at like you know drug discovery or materials discovery even like improving
2:32:35
language models there's always going to be some sort of process of proposing an experiment getting feedback from that experiment learning from that experiment and then using that information to propose the next set and continuing until you you know make the discovery. So um it's a you know great question
2:32:47
So um it's a you know great question because you know we think about the problem on that axis of how do we build and scale systems to these problems in which the evaluations and experiments become more expensive, more difficult, harder to access and postraining for example represents a problem space where experiments are pretty expensive.
2:33:05
um they can be quite noisy and they take a long time, right?
2:33:09
So it like if you're trying to build an automated research system that, you know, um develops the next state-of-the-art, you know, 70 trillion parameter model or whatever, uh you know, you can't really imagine a system training 15,000 models until it discovers the the the best one because training is expensive.
2:33:26
So you know, you have to think about how do you run efficient experiments?
2:33:29
How do you gain know gain information from those experiments better?
2:33:33
And I think that you know today we're showing kind of a closer step in that direction because you know in the past we were doing things like kernel optimization you know like MLE bench style problems and now post training where you know obviously it's more expensive and takes longer.
2:33:48
>> On the cost side this does sound expensive uh if you want to hammer a bunch of different experiments.
2:33:52
Uh what has been your approach just uh sort of suck it up and use venture capital dollars or partner with companies and labs that have big compute allocations?
2:34:03
they have the resources have them sort of uh you know front the cost or uh is there another way to solve it because scale seems very important here and yet uh your whole job feels like uh burning compute.
2:34:16
>> Yeah, so definitely a little bit of both.
2:34:18
Um I would say at the beginning it was a lot of burning venture capital money and now we have partners and systems in place to run experiments that you know don't just burn money for no reason.
2:34:26
you know, we have our own cluster, we have our own infrastructure that efficiently utilizes those resources.
2:34:32
Um, so we're at a place where we're not just like throwing money at the wall for no reason.
2:34:35
Um, so we're well, I mean, obviously it's an unsolved problem.
2:34:39
We will always continue to work on making our system better at this, but I would say it's a mixture of having some great comput partners, you know, spending a lot of time on our infrastructure even before we start running experiments.
2:34:47
And now we're at a place where, you know, I feel comfortable throwing, you know, hundreds of thousands of dollars at the wall if we feel like the system can actually make progress.
2:34:53
Gary Marcus, he says that doesn't count if it's not a pure LLM, that uh AI is only making progress in verifiable domains.
2:35:02
You need a lean uh output that's fully verifiable.
2:35:06
Uh how optimistic are you?
2:35:09
optimistic are you? And I'm somewhat sympathetic to it because it does actually seem like uh we are moving much faster in verifiable domains like math than unverifi unverifiable domains like I don't know coming up with the script
2:35:24
for the next great movie or uh joke writing a comedy writing or even even some of the bio stuff that's maybe verifiable but over uh you know a multi-year process of going through FDA applications and testing in vitro testing in mice and in monkeys. in
2:35:39
in humans like like there's just things that the verification loop isn't just run some lean really quickly and and see if it checks out, right?
2:35:48
Um so how how what what do you see the future of transferring all the amazing learnings and ability for AI to make discoveries in ML, computer science, and math to anything that's a little bit less verifiable? >> Yeah, for sure.
2:36:05
>> Yeah, for sure. So I think that it really just comes down to I mean so we focus on verifiable domains but I think it really just comes down to you know how much you can actually query the evaluator right so back to that example of you know post- training the next large state-of-the-art model um you
2:36:21
could argue that you know that system could in theory train the whole model get the ground truth feedback see how it did but that's not fully realistic for every run right so it would have to do some sort of experimentation with either its own rewards or you know not full ground truth rewards before making that progress. I think it's my my take is I
2:36:38
I think it's my my take is I really think it's just about building systems that almost like wean off the requirement of the evaluator.
2:36:44
So for example, you know, if you if you're building these kinds of system for training small models, no problem.
2:36:49
You train an infinite amount of models and you find the best one.
2:36:52
But yeah, like it's almost like as you scale on this access of difficulty, it's almost like as a forcing function of compute availability or cost, you start having to think like, okay, well now I can't actually have my system train the whole model every time or I can't run an entire clinical trial every time I want to test a drug.
2:37:10
It it's almost like a nature of the research direction.
2:37:12
And so I guess that I I don't really think it's that different of a problem.
2:37:17
I think it's more that if we continue on this path, like for example, with our system, if we continue on this path where it doesn't need to, you know, query the full evaluator every time, eventually it'll get to the point where it might not even need the evaluator or it'll only needed at the end when sending a drug to clinical trial or or, you know, a material in the fabricator.
2:37:32
So, I think it's really just I think I guess we and collectively the AI for science community, I think we're heading in the right direction.
2:37:40
I I don't think I view it as like black and white as we are only doing verifiable and then we're going to go to unfair viable domains and like figure it out. >> Interesting.
2:37:47
Uh, I have one more question.
2:37:49
Jordan, do you have anything? >> Yeah.
2:37:50
I was just going to ask, what do you what do you think your business looks like two years from now?
2:37:53
I won't say five or 10, but like, uh, where where where is this work going? >> Yeah, for sure.
2:38:01
So, you know, we, um, I guess we really believe in not building co-pilots.
2:38:05
Um, you know, what we are really trying to do here is build fully autonomous systems that are deployed in R&D environments and just run the entire loop, you know, autonomously perpetually.
2:38:14
perpetually. Obviously we're you know we're quite far away from that right now you know we have to deploy the system we have to monitor it we have to see it work make sure it's succeeding but I think at the end of the day definitely two years from now we want to be at the point where you know our system can basically be deployed as infrastructure in any computational R&D problem and then you know it gets access to the data
2:38:33
on the problem it gets access to the ability to run experiments on the problem and then it gets deployed in an environment in which it's like you know hard to hack and you're getting good signal out of the experiments and then
2:38:43
boom you know it runs autonomously it's it's cranking out discoveries, it's shipping them and you know humans can be there to take a look and make sure it's not messing up but eventually we want it to you know be running end to end. >> Last question. >> Last question.
2:38:54
>> Tell us a little bit about the company. Where are you based? How big is the team? Who are you hiring?
2:38:58
>> What you were doing before this shape of the company? >> Yeah, for sure.
2:39:01
So, we're based in San Francisco.
2:39:02
We just moved into our new office.
2:39:03
That's why my background's uh pretty boring right now.
2:39:05
Uh we're, you know, we're growing pretty quickly and been really proud of the team we've been putting together.
2:39:10
I mean we have researchers uh you know coming from deep mind anthropic factory AI um both in I guess industry and in academia.
2:39:16
I think this is like a really you know fundamental problem that needs to be worked on and it's not just a research problem.
2:39:23
It's not just an infrastructure problem.
2:39:24
It's you know it's the whole stack and we've been putting a pretty incredible team together to do so.
2:39:27
And I guess before this u my co-founder and I ran a pretty large nonprofit research group.
2:39:33
Um we were primarily funded by the National Science Foundation.
2:39:35
Um obviously very different from running a you know a company nowadays.
2:39:38
But we did a lot of fundamental research in like coding language capabilities.
2:39:41
Uh published some of the first work in test time scaling uh with language models and it kind of felt like a natural progression because you know we were really curious about how do we model agentic behavior in this kind of search process.
2:39:54
Um and it kind of just made sense that you know this is the time this is the place let's make it happen.
2:39:59
And that's what we're doing at Intellig. >> Yeah.
2:40:01
Well thank you so much for coming on the show.
2:40:03
>> I'm sure you'll be back on soon.
2:40:03
Have a great rest of your day. >> Very cool update. Good to meet you. >> Goodbye. >> Cheers, Ron.
2:40:08
>> Let's go to this Paul Graham post.
2:40:08
He had such a wild experience as he bought a book. It was awful.
2:40:15
Didn't want it on my shelves, but I couldn't throw it away.
2:40:20
So, it sat on a table near the door.
2:40:23
>> I know someone that will rip it apart, feed it to a machine, [laughter] and burn it. I know someone.
2:40:31
I don't know them personally, but I know they they would love they would love to to take this off your hands.
2:40:40
>> Rushing to an appointment this morning, I grabbed it to read it.
2:40:42
First mistake, then went to breakfast and had nothing else.
2:40:46
So, I spent the morning reading the worst book I own.
2:40:51
It's such a funny such a funny like [laughter] just like I don't know.
2:40:54
It feels like a curb your enthusiasm episode or something like that.
2:40:58
Anyway, thank you so much for tuning in to TBPN today.
2:41:01
We'll see you tomorrow at 11:00 a. m. Pacific.
2:41:04
>> Leave us five stars on Apple Podcast and Spotify. >> It's been an honor.
2:41:07
>> Sign up for our newsletter tb. com. Goodbye.