You can listen to the Grok 4 Wows, The Bitter Lesson, Elon’s Third Party, AI Browsers, SCOTUS backs POTUS on RIFs using Speak’s shareable media player:
Grok 4 Wows, The Bitter Lesson, Elon’s Third Party, AI Browsers, SCOTUS backs POTUS on RIFs Podcast Episode Description
(0:00) The Besties welcome Travis Kalanick and Keith Rabois!
(3:02) Travis on Pony.ai / Uber rumors and the state of Cloud Kitchens
(18:51) xAI launches Grok 4, learning “The Bitter Lesson” in AI
(40:36) How Grok can catch ChatGPT in usage, OpenAI’s product excellence
(46:27) Perplexity and OpenAI building AI-native browsers and taking on Chrome
(58:01) Elon’s “America Party”: is now the right time for a third party, and could he make an impact in 2026?
(1:13:12) SCOTUS backs Trump over federal government RIF plans
Follow the Keith:
https://x.com/rabois
Follow the Travis:
https://x.com/travisk
Get The Besties All-In Tequila:
https://tequila.allin.com
Join us at the All-In Summit:
https://allin.com/summit
Summit scholarship application:
http://bit.ly/4kyZqFJ
Follow the besties:
https://x.com/chamath
https://x.com/Jason
https://x.com/DavidSacks
https://x.com/friedberg
Follow on X:
https://x.com/theallinpod
Follow on Instagram:
https://www.instagram.com/theallinpod
Follow on TikTok:
@theallinpod
Follow on LinkedIn:
https://www.linkedin.com/company/allinpod
Intro Music Credit:
https://rb.gy/tppkzl
https://x.com/yung_spielburg
Intro Video Credit:
https://x.com/TheZachEffect
Referenced in the show:
https://www.nytimes.com/2025/06/26/technology/uber-travis-kalanick-self-driving-car-deal.html
https://grok.com
https://x.com/ArtificialAnlys/status/1943166841150644622
https://x.com/elonmusk/status/1943192643439337753
http://www.incompleteideas.net/IncIdeas/BitterLesson.html
https://x.com/chamath/status/1943177837956968499
https://x.com/perplexity_ai/status/1942969263305671143
https://x.com/elonmusk/status/1941584569523732930
https://polymarket.com/event/will-elon-register-the-america-party-by
https://ropercenter.cornell.edu/presidential-approval/highslows
https://news.gallup.com/poll/651278/support-third-political-party-dips.aspx
https://www.whitehouse.gov/presidential-actions/2025/02/implementing-the-presidents-department-of-government-efficiency-workforce-optimization-initiative
https://www.afge.org/article/summary-of-afge-lawsuits-against-trump–how-litigation-works
https://cei.org/publication/10kc-2025-numbers-of-rules
https://www.netflix.com/tudum/articles/american-manhunt-osama-bin-laden-release-date-news
This interactive media player was created automatically by Speak. Want to generate intelligent media players yourself? Sign up for Speak!
Continue reading the full guide (click to expand)
Grok 4 Wows, The Bitter Lesson, Elon’s Third Party, AI Browsers, SCOTUS backs POTUS on RIFs Podcast Episode Top Keywords
Grok 4 Wows, The Bitter Lesson, Elon’s Third Party, AI Browsers, SCOTUS backs POTUS on RIFs Podcast Episode Summary
Podcast Episode Summary
Key Points & Major Topics:
– The episode features a roundtable discussion with hosts Jason, Chamath, and guests Keith Rabois and Travis Kalanick (Uber/CloudKitchens founder). David Sacks and David Friedberg are absent.
– The conversation opens with light banter and travel stories, then shifts to technology, automation, AI, and politics.
– Travis Kalanick discusses CloudKitchens’ automation efforts, including robotic food assembly and delivery, and the broader implications for labor, real estate, and the future of food service.
– The panel analyzes the rapid progress of AI, focusing on Elon Musk’s Grok 4 model, its technical achievements, and the “Bitter Lesson” (Rich Sutton’s thesis that scalable computation outperforms human-labeled data in AI).
– They debate the future of AI training, the shift from human-labeled to synthetic data, and the potential for AI to drive scientific breakthroughs.
– The group explores the rise of agentic browsers (e.g., Perplexity’s Comet), the impact on consumer software, and the potential obsolescence of traditional browsers in favor of agent-driven interfaces.
– Political discussion centers on Elon Musk’s idea of forming a third political party, the feasibility of winning congressional seats, and the impact of recent Supreme Court rulings on federal workforce reductions.
Important Guests/Speakers:
– Travis Kalanick: Shares insights on automation in food delivery and robotics.
– Keith Rabois: Offers perspectives on AI, investment, and political strategy.
Actionable Insights & Advice:
– Automation in food and delivery can drastically reduce costs and errors, but requires end-to-end integration.
– For AI startups/investors: The value of human-labeled data is diminishing; focus on scalable computation and scientific breakthroughs.
– In consumer tech, prepare for a paradigm shift as agentic interfaces replace traditional apps and browsers.
– Political entrepreneurs should consider leveraging new FEC rules and focus on high-profile, charismatic candidates to disrupt the status quo.
Recurring Themes & Overall Messages:
– The relentless advance of automation and AI is transforming industries, from food service to scientific research.
– Scalable, computation-driven approaches are outpacing human-guided methods in AI.
– The intersection of technology, politics, and society is creating new opportunities and challenges, especially as influential figures like Elon Musk enter the political arena.
– Adaptability and willingness to embrace new paradigms—whether in business, technology, or politics—are crucial for future success.
Want to run this on your own file?
Upload audio, video, or text and get a transcript, summary, and insights in minutes.
Free trial includes 30 minutes (60 with a work email)
Word Count: ~300
This summary was created automatically by Speak. Want to transcribe, analyze and summarize yourself? Sign up for Speak!
Grok 4 Wows, The Bitter Lesson, Elon’s Third Party, AI Browsers, SCOTUS backs POTUS on RIFs Podcast Episode Transcript (Unedited)
Speaker: 0
00:00
Ai have a very funny story to tell you, Jason.
Speaker: 1
00:02
Where have you been? I’ve been trying to text you. You’ve been offline. What’s going on? Where have you been?
Speaker: 0
00:06
I’ve been working feverishly, but yesterday I had to go to prepare for some meetings that I have on Sunday, which I can’t tell you about. But
Speaker: 1
00:16
Can’t tell you about it. Matt and
Speaker: 0
00:17
I ai to Passalacqua, which is in Lake Como, which is an I mean, it’s stunning. The the grounds are stunning. The hotel is stunning.
Speaker: 1
00:27
If you
Speaker: 0
00:27
have a chance to go to Lake Como. Anyways, this is us at Passalacqua.
Speaker: 1
00:32
Who’s the beautiful woman there? Is that the woman who owns it or something? Is that the queen?
Speaker: 0
00:36
That’s not. But the best part is we had such a good time. You know how they have like a registry book to leave a message? Sure. So I left a message.
Speaker: 1
00:46
Here we go. What a truly magnificent place above and beyond any expectation we had.
Speaker: 0
00:53
Go below, go below that slot for me.
Speaker: 1
00:55
Thank you. We took everything to free. We took everything to free merch.
Speaker: 0
01:02
Great. Awesome. Jason, the hangers. Okay. The eggs. The laundry bags.
Speaker: 1
01:07
Did you
Speaker: 0
01:07
get your robes? The robes, the slippers. The robes.
Speaker: 1
01:09
Everything. Absolutely fantastic. Listen. You’re gonna have
Speaker: 0
01:11
to send a bill with
Speaker: 1
01:12
a free bird that’s Absolutely. Alright. Listen. We’ve got a great panel this week. It’s the summer. Things are slow. Some people are busy. I think, our prince of panic attacks, our dear sultan of science is, he’s at the beep. Sachs is busy. Couldn’t make it this week. In his place, another brilliant PayPal alumni and, dare I say, GOP supporter, Heath Rabois. How are you, sir?
Speaker: 2
01:56
Pleasure to be with you again.
Speaker: 1
01:58
Nice to see you. And I’m assuming you’re in gorgeous Florida or somewhere in Italy. Yeah?
Speaker: 2
02:03
I’m actually in New York.
Speaker: 1
02:04
Oh, my hometown. Is it safe? Is it okay? Mom Dommy, chasing you down the street?
Speaker: 2
02:10
Not yet, but it’s safe.
Speaker: 0
02:12
Did you see your
Speaker: 2
02:12
It’s safe.
Speaker: 1
02:13
Your assets?
Speaker: 2
02:14
It’s safe. Yeah. It’s safe right now. We’ll see you on November 4. You know, as you probably heard, on July 4 was the first time in recorded history that there were no shootings or no murders in New York on that day. So right now, things are in pretty good shape, but we maybe we maybe leaving New York quickly.
Speaker: 1
02:30
Yeah. You’re gonna probably wanna sell that place if you got one there because Mondami is, gonna seize it and turn it into a drugstore for you. Yes. It’s gonna be the Mondami drugstore. Travis Kalanick is back with us. How are you doing, bestie?
Speaker: 3
02:43
Pretty good. Pretty good.
Speaker: 1
02:45
Yeah. Second appearance here on the round table. And, third time on the show. Of course, you spoke at the summit. You’ve been busy with Cloud Kitchens. Yeah? Lots of exciting things going on?
Speaker: 3
02:54
Oh, lots of stuff. Lots of stuff. The robots the robots are taking over. We’re we’re rolling out we’re rolling out robots.
Speaker: 0
03:00
Yeah. TK, can you tell us what you’re doing with this saloni Ai or not? That’s speculation.
Speaker: 3
03:06
Look. You know, obviously, is autonomy as we you know, in The US, we have, of course Wait.
Speaker: 0
03:14
Do you wanna just frame for people that don’t that may not be up to speed what was announced or at least Why
Speaker: 3
03:18
don’t you frame it?
Speaker: 1
03:19
Why don’t you frame it?
Speaker: 3
03:19
So Why don’t
Speaker: 1
03:20
you frame it? Ai is, an autonomous company doing self driving. It’s one of the few, players that actually have cars on the road. They’re based in China. They’ve got a lot of operations in The Middle East. They’ve got a deal with, a delivery company called Uber, which you might be familiar with.
Speaker: 3
03:39
Okay. Sai,
Speaker: 0
03:41
look. Well, the deal was basically that you could partner with Uber, license in the pony technology, and essentially start a competitor, I guess, to Waymo and Tesla.
Speaker: 3
03:53
Let me work on this one. Okay. So so in The US, we have Waymo. We see the Waymos in San Francisco, Los Angeles, Austin, coming soon to Miami, coming soon to Atlanta, coming soon to DC. They’re even talking about New York. Tesla is sorta like the you know, they’re doing it the hard way. You know? Classic Elon ai. Like, let’s let’s do this sort of in a fundamental holy shah.
Speaker: 3
04:22
Let’s go all the way kinda kinda approach. And it’s unclear when it gets over the line. Of course, he he launched sort of a a semi semi pilot of sorts in Austin recently, but there’s no other alternatives. So what happens is is some of the folks who are interested in making sure their alternatives have reached out.
Speaker: 3
04:45
They they’ve reached out to meh, and there are different discussions they get going because they’re like, Travis, you did autonomy way back in the day. Got the Uber autonomous stuff going in 02/2014. Maybe there’s something to do here to create optionality. Maybe, like, I’m, of course, very interested on the food side.
Speaker: 3
05:06
I talk about autonomous burritos being a big deal because if you can automate the kitchen, the production of food, and then you can automate the sort of, logistics around food, you take huge amount of costs out of the food out of what’s going on in food, and that’s, of course, near and dear to my heart.
Speaker: 3
05:24
There’s folks, of course, that want to see autonomy and mobility. That’s a real thing. It it meh be that or I would say if you get the autonomy problem right, you can use it to apply to both problems. So there’s a lot of folks interested in moving things, moving food, moving people.
Speaker: 3
05:47
And if there is some kind of autonomous technology that maybe I get involved in, it might apply to a bunch of different things. And so I’ve got some inbound. Let’s just put it that way. There’s no there’s no real deal right now, but there is definitely some inbound. And I think there is some news about some of that inbound that may or may not be occurring. That’s probably the best way to put it.
Speaker: 3
06:10
That is long winded. I’ll try to tighten that up next time.
Speaker: 1
06:12
No. No. I think it’s great to get the overview here first sana, all in. Thank you for sharing it with us. And everybody knows you have been doing a bowl builder Yeah. Lab 37, I think it’s called. You can throw it up on the screen. Not sure what the status of it is, and then I’ll let you go, Jamoth, with your follow-up question.
Speaker: 1
06:29
But Ai I think there’s a pretty interesting concept here of the ball getting built and then put into a self driving car.
Speaker: 3
06:36
Yeah. That machine looks huge, but it’s actually 60 square feet. That picture makes it look monstrous. It’s a 60 square foot machine. Like, imagine running, like, a speak green like brand or a Chipotle like ram. I’m just making it so it comes to life for people who who, you know, are like, hey. What is this thing?
Speaker: 3
06:54
Imagine you just order online exactly the kind of bowl you want. And actually, this machine could run, like, many brands at the same time and and does. You build the bowl you want, whatever ingredients, it sort of if you look at that bottom, you see those little white bricks at the bottom?
Speaker: 3
07:11
That’s what carries the bowl underneath dispensers. It fills up. The machine puts, it sauces the the bowl, then it puts a lid on it. It takes the bowl, puts it in a bag, puts utensils in the bag, seals the bag, and then the bag goes down a conveyor belt where then another machine, what we would call an AGB, takes the bowl to the front of house.
Speaker: 3
07:35
The bowl gets put into a locker. The courier, via DoorDash, who bryden courier, will wave their app in front of the camera, and it will open up the locker that has the food that they’re supposed to pick up. So it just it takes out a lot of what we would call the the cost of assembly, which is And reduces mistakes. Right?
Speaker: 1
07:55
It reduces hard for making mistake. Yeah.
Speaker: 3
07:57
We know exactly how many grams of every ingredient are put in. That’s exactly what you’re supposed to get. Mhmm. And sai you get a higher quality product. It takes a lot of the cost out. You imagine ultimately that’s going to be there are sana be couriers with that as well.
Speaker: 3
08:13
That, you know, I like to say autonomous burritos. Like, is a Waymo sana carry a burrito? Or is Tesla gonna have a a machine that carries food? Or, you know, is there another another company that ends up doing, you know, sort of the the the things, the the the the autonomous delivery of things?
Speaker: 3
08:30
And the point is is, well, where we are right now is we’ve got customers. And so those customers are starting to deploy this quarter, and it’s pretty interesting. I mean, you can see that the in our delivery kitchens, the cost of labor is about 30% of revenue. That’s what the successful ai, let’s say 30%, 35% of revenue. In a in a brick and mortar in a brick and mortar restaurants, it’s even higher. K?
Speaker: 3
08:59
When they’re running our machine, it’s between 710% of revenue.
Speaker: 1
09:05
Ai. Then you take out the cost of the delivery, you know, and now it’s becoming everybody can have a private chef, which was your original vision for Uber was Yeah. People don’t know the original tagline, but it was your your pri everybody has a private driver.
Speaker: 3
09:16
Everyone’s private driver was the original for Uber. The basically, the infrastructure was already there. And I said this on, you know, one of your recent I I think it was at the all in summit, Jason. But, like, in the mobility cars, you know, Ai transport, space, the roads were already there. The cars were already built. People weren’t using their cars 98% of the day.
Speaker: 3
09:42
So the infrastructure is already there to get people around, to do this as a service and do it very efficiently and conveniently. With food, the infrastructure is not there. Like, yes, restaurants have excess capacity. That’s what Uber Eats utilizes. But to go and say, like, let’s make 30% of all meals in a in a city, sort of prepared and delivered by a service.
Speaker: 3
10:07
The infrastructure is not there, so you have to build it. So our company, the the mission is, infrastructure for better food. So that’s real estate, that’s software and robotics for the production and delivery of food in a super efficient way.
Speaker: 1
10:24
Ai. Keith, what are your thoughts? Any questions for
Speaker: 2
10:27
well, he’s not here, but isn’t this what David Freeberg tried to do a few years ago?
Speaker: 3
10:31
Yeah. This came up on the last all in. Yeah. They’re the last one I was at. Yeah.
Speaker: 1
10:35
Yeah. Vatsal. Itza. The problem was I told Freeberg, people don’t wanna eat quinoa. You gotta put a ai little steak in there, maybe a piece of salmon. But he was kinda I think eventually he relented and let people have a little bit of protein. But, yeah, sai it’s such a great vision.
Speaker: 0
10:51
Wait. He he died as a vegan martyr?
Speaker: 2
10:54
I think
Speaker: 1
10:55
the business died as a martyr.
Speaker: 3
10:57
Well, yeah, that That was the
Speaker: 1
10:58
hell he was he was led to There’s a lot of
Speaker: 3
11:00
people that ai on that hill. But the bottom line is if you’re gonna get into automation, you have to it has to be end to end automation. What I mean by that is, like, there are pizza there are pizza companies that have come and gone, automated pizza companies, where it’s like, we have a pizza machine, and everybody’s like, yeah.
Speaker: 3
11:17
This is amazing. And you have a guy you have a million dollar pizza machine. And then on the left, you have a guy feeding ingredients into the pizza machine. And on the right, you have a guy taking the pizza out and then putting it in a box and doing all this. So instead of one guy making pizzas, I have a million dollar machine and two guys making pizza.
Speaker: 3
11:36
And so when you look at these, ai, robotic food production machines or food assembly machines, you have to look at the full stack and say, does it work with the ecosystem that exists in a restaurant? And does it go full stack ram, you know, like like, we have this thing where that machine we saw earlier.
Speaker: 3
11:59
The staff preps the food, they put the food in the machine, and then they leave. They’re gone. This restaurant runs itself for many hours without anybody there.
Speaker: 0
12:11
But this could be McDonald’s, Burger King, and Taco Bell. Nobody would know.
Speaker: 3
12:17
That right there, that machine is a it’s an assembly machine. Right? The food is prepped by humans and then assembled by this machine. For a Chipotle or a speak green, this is ai a a majority of their labor. Right? You go up to a Chipotle, there’s like 10 guys at lunch, and you’re still in line. That machine right there does 300 bowls an hour. Right?
Speaker: 3
12:38
And so you go, okay, that’s the this is what’s called, like the assembly line. It’s just that front line where you basically assemble things. I I think sometimes I will call it the make line. What will happen over time is you’ll have perpendicular lines going into it where you’re producing food. Ai?
Speaker: 3
12:58
So you’ll have a production or make line going into an assembly line here, and then you go, oh, wow. So you have it something that dispenses burgers on buns. That’s the dispenser. That’s the assembly.
Speaker: 0
13:13
Right. But It’s like Factorio on steroids, basically.
Speaker: 3
13:16
And then it’s ai, how do you cook that burger? That’s what I call that’s what we call state change. So state change is the is the cooking of the food. Assembly is the, like, how do I put it together and plate it?
Speaker: 0
13:29
Doesn’t this collapse, like, for example, if you have a yield of 300 per hour, you sai, out of that one machine
Speaker: 3
13:36
Yes.
Speaker: 0
13:36
Very quickly, you can impute the value of having a smaller footprint store with five of these things in a faceless warehouse Yeah. With drone delivery or cars. You don’t need the physical infrastructure. So then don’t you create a wasteland of real estate
Speaker: 1
13:52
or how do you repurpose
Speaker: 0
13:52
all the real estate?
Speaker: 3
13:54
Well, the way to think about it is, like, 90%, well, it’s probably a little lower than that or not. Let’s say 85% of all meals in The US are at home. They just are.
Speaker: 0
14:04
Mhmm.
Speaker: 3
14:05
And a vast majority of those meals are cooked at home. So, you know, like Uber Eats and DoorDash, they represent, like, 1.8% or two percent of all meals right now. It’s very tiny. Right? So what you’re doing is you’re using real estate to and infrastructure to prepare and deliver meals to people at their homes. And so it’s not restaurants still exist.
Speaker: 3
14:33
We’re still gonna wanna go to restaurants. We’re still gonna wanna go outside. We learned that during COVID. We knew it before. We definitely know it after.
Speaker: 3
14:40
And so I don’t it’s not really ai a decimating real estate situation. It’s taking a thing we used to do for ourselves and creating a service that does it higher quality.
Speaker: 1
14:52
Meh.
Speaker: 3
14:52
Sort of Ai like to say you don’t have to be wealthy to be healthy and just infrastructure to get that cost down. And so you’re doing something as a service that we used to do at home. I think in the super long run, you’re like, what where’s the story on grocery stores? If you go to like, in in twenty years, I think everybody agrees you you will have machines making very high quality, very personalized meals for everybody.
Speaker: 1
15:22
This would be good for Keith because he measures stuff down to, like, five calories based on his Keithogram.
Speaker: 0
15:28
Ram, I’m like What’s your what’s your body fat? Ai, 7%, 8%?
Speaker: 2
15:33
It’s ai 10.
Speaker: 1
15:33
Just open his Instagram. He posted for Oh my god. Because I talked to you
Speaker: 0
15:37
today about your body fat. He’s, like, so disgusted with himself at 10%.
Speaker: 2
15:40
It’s, like, out of 10. But, I actually think the vision of this actually, the natural implication and maybe the home run version of this is everybody has a private chef in their house. Robot in their house actually does this personalized because people do want to cook at home, but they don’t have the time.
Speaker: 1
15:59
Yeah. Or space, and infrastructure. But, man, these delivery services are charging rich people do this all the time. Right? They do these crazy meal delivery services for $200 a day, And this is just gonna abstract it down to everybody. And, man, people get creative when there’s that empty space to your point, Shmoph, about what happens to all this space.
Speaker: 1
16:18
When I lived in New York in the eighties and nineties, it was common to in Ai, in West Chelsea, where I lived, to take storefronts, put your little architect’s office in the front and live in the back. And many people were hacking real estate. We still need five, ten million homes in this country and they’re already doing this with malls.
Speaker: 1
16:35
I keep seeing malls being turned into colleges and creative spaces. One of them in Boston, they turned, like, the Second And Third Floor into studio apartments for artists. So, you know, where there’s a will, there’s a way. We could use the speak. Sai ai You
Speaker: 3
16:50
know, where this goes with Ai saying and where the real estate goes is we call it the Internet food court, where, you know, you’re on Amazon. Right? It’s the everything store. Now imagine that for food. And then imagine you have an 8,000 square foot facility where basically anything can be made.
Speaker: 0
17:07
Anything can be made.
Speaker: 3
17:08
Yeah. Because if you have, that machine you saw has 18 sort of dispensers for food, 10 different sauces. You get the idea. Now what what about when it’s 50 or a 100 dispensers for food? What if you have multiple machines with a 100 dispensers for food?
Speaker: 0
17:24
That’s crazy.
Speaker: 3
17:24
You can the combinatorial math in terms of what’s possible, what could be made sort of, you know, goes exponential. And so the Internet food court is sort of the vision for where this all goes.
Speaker: 0
17:38
Another example of the bitter lesson.
Speaker: 1
17:41
The bitter yeah. Well, when we get to that, I guess, today. In a very full docket, before we get to that, just a little bit of housekeeping here. September in Los Angeles, the All In Summit again, allin.com slash yada yada yada. Ai is stacked, and we’re gonna start announcing the speakers.
Speaker: 1
18:01
People have been begging us to announce the speakers. I don’t know. Maybe You gotta
Speaker: 0
18:05
you gotta hold some back. Careful, dear.
Speaker: 1
18:07
Hold a couple back, but we got some really nice speakers lined up. It is gonna be a shredder.
Speaker: 0
18:13
It is the best one yet. Sai mean Well done.
Speaker: 1
18:16
Every year We have this.
Speaker: 0
18:17
Well done.
Speaker: 1
18:18
Yeah. Yeah. Every year, we have this little bit of panic, like, you know, we’re gonna get great speak. And, man, they arya flowing in this week. It’s gonna be extraordinary almost as extraordinary as this delicious tequila behind my head here. Get the online tequila at tequila.olin.com. Deliveries begin late summer.
Speaker: 3
18:34
Oh, he’s moving to the side. You can’t even tell us tequila.
Speaker: 0
18:37
Oh, that’s right
Speaker: 1
18:39
there. All ai. Listen.
Speaker: 0
18:40
Oh, wow.
Speaker: 1
18:41
Lots to discuss this week. Obviously, AI is continuing to be the big story in our industry and for good reason. Our bestie, Elon released Grok four Wednesday night. Two versions, base model and a heavy model, $30 a month for the base, dollars 300 a month for this heavy model, which has a very unique feature.
Speaker: 1
19:05
You can have a multi agent feature. I got to see this actually when I visited XAI a couple of weeks ago, where multiple agents work on the same problem, then they and they do that simultaneously, obviously, and then compare each other’s work. And it gives you, kind of like a study group, the best answer, by consensus. Really interesting.
Speaker: 1
19:22
According to artificial analysis benchmarks, you can pull that up, Nick, ROX4 based model has surpassed OpenAI’s ai three Pro, Google Gemini’s 2.5 Pro as the most intelligent model. This includes, like, seven different industry standard evaluation tests. You can look it up, but reasoning, math, coding, all that kind of stuff.
Speaker: 1
19:44
This is, you know, book smarts, not necessarily street smarts, so it doesn’t mean that these things can reason. And obviously, there was a little, there was a little kerfuffle on, X, formerly known as Twitter, where XAI got a little frisky and was saying all kinds of crazy stuff and needed to, maybe be red teamed a little bit more decisively.
Speaker: 1
20:06
Many of you know Grok four was trained on Colossus. That’s that giant data center that Elon’s been building. And we showed the chart here, Chamath. You sent us a link to the Bitter Lesson ai, Rich Sutton in the group chat. That’s the 2019 blog post.
Speaker: 1
20:22
We’ll pull it up here for people to take a look at and put it in the show notes. Maybe just generally Yeah. Your reaction to both how quickly Elon has and that chart showed how quickly Elon has caught up. And I don’t think people expected him to take the lead, but here we are.
Speaker: 0
20:39
Before we start, Nick, can you please show Elon’s tweet about how they did on the AGI benchmark? It’s absolutely incredible. Two things. One is how quickly starting in March of twenty twenty three. So we’re talking about less than two and a half years, what this team has accomplished and how far ahead they are of everybody else as demonstrated by this.
Speaker: 0
21:10
But the second is a fundamental architectural decision that Elon made, which I think we didn’t fully appreciate until now. And it maps to an architectural decision he made at Tesla as well. And for all we know, we’ll figure out that he made an equivalent decision at SpaceX.
Speaker: 0
21:29
And that decision is really well encapsulated by this essay, The Bitter Lesson by Rich Sutton. And Nick, if you can just throw this up here, but just to summarize what this says, it basically says in a nutshell that you’re always better off when you’re trying to solve an AI problem, taking a general learning approach that can scale with computation because it ultimately proves to be the most effective.
Speaker: 0
21:56
And the alternative would be something that’s much more human labored and human involved that requires human knowledge. And so the first method, what it essentially allows you to do is view any problem as an endless scalable search or learning task. And as it’s turned out, whether it’s chess or go or speech recognition or computer vision, whenever there was two competing approaches, one that used general computation and one that used human knowledge, the general computation problem always won.
Speaker: 0
22:34
And so it creates this bitter lesson for humans that want to think that we are at the center of all of this critical learning and all of these leaps. In more AI specific language, what it means is that a lot of these systems create these embeddings that are just not understandable by humans at all, but it yields incredible results.
Speaker: 0
22:53
So why is this crazy? Well, he made this huge bet on this 100,000 GPU cluster. People thought, wow, that’s a lot. Is it gonna bear fruit? Then he said, no, actually I’m scaling it up to 250,000. Then he said, it’s gonna scale up to a million.
Speaker: 0
23:08
And what these results show is a general computational approach that doesn’t require as much human labeling can actually get to the answer and better answers faster. That has huge implications because if you think about all these other companies, what has Llama been doing? They just spent 15,000,000,000 to buy 49% of scale AI.
Speaker: 0
23:31
That’s exactly a bet on human knowledge. What is Gemini doing? What is OpenAI doing? What is Anthropic doing? So all these things come into question.
Speaker: 0
23:39
And then the last thing I’ll say is if you look back, he made this bet once before, which was Tesla FSD versus Waymo. And Tesla FSD only had cameras, it didn’t have ai, but the bet was Ai just collect billions and billions of driving miles before anybody else does and apply general compute and it’ll get to autonomy faster than the other more laborious and very expensive approach.
Speaker: 0
24:08
So I just think it’s an incredible moment in technology where we see so many examples. Travis is another one, what he’s just talked about. You know, the bitter lesson is you could believe that, you know, food is this immutable thing that’s made meticulously by hand by these individuals, or you can take this general purpose computer approach, which is what he took, waited for these cost curves to come into play, and now you can scale food to every human on earth.
Speaker: 0
24:34
I I just think it’s a it’s so profoundly important.
Speaker: 3
24:38
One thing I’ll throw out there, Shemoff, is the Tesla approach for autonomy is taking human knowledge. In fact, the whole idea is to approximate human human driving. Right? That is the whole damn thing. Now depending on your approach and the technology, you can do, like, what’s called an end to end approach, or you can look at, okay, perception, prediction, planning, and control, which are ai these four modules that sort of you you you sort of engineer, if that makes sense.
Speaker: 3
25:10
But it’s approximating human driving to do it. The difference is that, you know, I I think Elon’s taken a a almost a more human approach, which is ai, I’ve got two eyes. Why can’t my car? Why can’t my car do it like a human? Like, I don’t have any lidar spinning around on my head as a human. Why can’t my car?
Speaker: 3
25:33
So it’s kinda interesting. He’s sort of taking what you’re saying, Chamath, on the computation side because hardware five is coming out on Tesla probably next year, which is gonna make a big difference in what FSD can do. That’s the compute side you’re talking about, but then he is approximating human.
Speaker: 0
25:51
Yeah. I just speak that you know, other than the first versions of FSD, which I think Andre talked about Andre Karpathy talked about. You know, they’re not really so reliant anymore on human labeling per se. Right? So that Respect. Yeah. That Yeah. That interference.
Speaker: 0
26:07
And then
Speaker: 3
26:07
Yeah.
Speaker: 0
26:08
The other crazy thing that he said, subsequent versions of Grok are not gonna be trained on any traditional dataset that exists in the wild.
Speaker: 4
26:18
The cumulative sum of human knowledge has been exhausted in AI training. That happened basically last last year. And so the only way to then is with synthetic data where the AI creates it’ll sort of ai an essay or come up with with a thesis, and then it will grade itself, and and and and sort of go through this process of self learning with synthetic data.
Speaker: 0
26:39
He said that he’s gonna have agents creating synthetic data from scratch that then drive all the training, which I just think is it’s crazy.
Speaker: 1
26:48
Just explain this concept one more time in the better lesson. Hand coding heuristics into the computer and saying, Hey, here’s specific openings in chess
Speaker: 0
26:56
and teams. Yeah, use chess, right? Like you’re
Speaker: 1
26:59
doing your same. Yeah, so you’re hand coding specific examples of openings in there, end games, etcetera, versus just saying, Play every possible game and here’s every game we have.
Speaker: 0
27:07
And you, Yeah. Yeah. So the two approaches would be, let’s say like Travis and I were building competing versions of a chess solver and Travis’s approach would say, I’m just gonna define the chess board. I’m gonna give the players certain boundaries in which they can move, right?
Speaker: 0
27:25
So the bishop can only move diagonally and there’s a couple of boundary conditions, and I’m gonna create a reward function and I’m just gonna let the thing self learn and self play. That’s his version. And then what happens is when you map out every single permutation, when you go and play Keith, who’s the best chess player in the world, what you’re doing at that point is saying, okay, Keith made this move.
Speaker: 0
27:52
So you search for what Keith’s move is and you have a distribution of the best moves that you could make in response or vice versa. That was the cutting edge approach. The different approach, which is more, you know, what people would think is more quote unquote elegant and less brute force would be Jason for you and I to sit there and say, okay, if Keith moves here, we should do this.
Speaker: 0
28:15
We should do this specific variation of the Sicilian defense and it’s too much human knowledge. And I think what it turned out was there was a psychological need for humans to believe we were part of the answer. But what this is showing is because of Moore’s law and because of general computation, it’s just not necessary. You just have to let go, give up control.
Speaker: 0
28:35
And that’s very hard for some people and for others also very hard
Speaker: 1
28:39
in some circumstances where a car is driving down the road and it’s learning in that process, which is why he needed a safety driver and and I think Elon made the right decision to put one in there.
Speaker: 2
28:48
Keith, your thoughts. Yeah. A couple points. It’s not quite that binary, Chamath. I generally agree with your arc. But, like, if you think about LLMs being the most important unlock in AI, LLMs are all trained on human writing. So someone wrote every piece of data that every LLM used a human wrote at some point in history.
Speaker: 2
29:07
So, yes, it’s true that they’ve shocked everybody, including OpenAI’s, you know, original team on the implications, the broad implications, the general applicability to almost every problem. But it’s not like there was, some tablets floating in space that weren’t drafted by humans that we’ve trained on.
Speaker: 2
29:25
As you get in non LLM based, models, you may be totally right, but almost no one’s really using non LLM based models at scale. On driving, specifically, Travis is totally right, that humans are actually really good drivers except when they get distracted. They get distracted by drugs or alcohol.
Speaker: 2
29:42
They get distracted by being tired. They get distracted by turning the radio. They get distracted by chatting with their passenger. So training against human behaviors actually turned out to be a great decision because what for whatever sort of Darwinistic reasons, humans are pretty ideal drivers.
Speaker: 2
29:56
And so you don’t have to reason from first principles. This is a much better path. And I think, again, there may be a a bryden, sort of lesson there. The most important thing, I think, as a VC that you said, is we’ve been debating for years. Should we invest in companies like Scale or Merkore or any of these surge? The truth is, I think there’s a very short half life on human label data.
Speaker: 2
30:20
And so everybody who’s investing, in these companies, they’re just looking at revenue traction, really didn’t understand that there may be a year, two years, three years max when anybody uses human labeled data for maybe anything.
Speaker: 1
30:36
Because we hit the end of human knowledge, or just the collection of it.
Speaker: 3
30:41
Or is
Speaker: 1
30:42
99% done.
Speaker: 3
30:43
Or you train on you train on it so well that you don’t need to label anymore. Like, the the machines know how to label as good or better than a human. And so, like, we’re seeing this in the self driving space is labeling was huge. Right? You would have a three-dimensional sort of scene that’s created by video plus lidar, let’s say. Okay. I have to label all of these, essentially, what become boxes.
Speaker: 3
31:10
Like, I’ve identified objects. You’re you’re some of the players in the in the autonomous software space, autonomous vehicle software speak, are no longer doing any labeling because the machines are doing it all, just broadly.
Speaker: 1
31:24
It’ll just be built into the chip set that this is a stop sign. Like, it’s like we know what a stop sign is. We don’t need the millionth time
Speaker: 0
31:31
for someone to
Speaker: 1
31:32
be able
Speaker: 3
31:32
to CAPTCHAs. Like, you’re like, find the stop sign or what’s the traffic ai, and eventually, the machines are just way better than humans at identifying these things.
Speaker: 2
31:41
For you to be very practical, when you see a stop sign, you don’t have to identify that it’s a stop sign. You just see that every human, when they encounter a stop sign, 99.9% of the time, they hit a speak. And they never act they so nobody actually knows it’s a stop sign. It’s just that hit a break when you see something that looks like the subject.
Speaker: 3
31:59
It’s just a vibe. Yep. It’s a vibe.
Speaker: 0
32:03
I I would just say that that’s, like, intuitive knowledge versus, like, the expressly labeled human knowledge. The question for me is, if everybody was so reliant on human labeling initially, if you’re an investor now, when you see these GROC four results, how do you make an investment decision that’s not purely levered to just computation?
Speaker: 0
32:25
So if you look at these results, does it mean that, you know, there’s 300 to a thousand basis points of lag between just letting the computers vibe itself to the answer versus interjecting ourselves. If interjecting ourselves slows us down by 300 to a thousand basis points per successive iteration, then over two or three iterations, you’ve totally lost.
Speaker: 0
32:52
So what does it mean for everybody that’s not grok when they wake up today and they have to decide how do I change my strategy or double down?
Speaker: 3
33:01
I think look. I’m I’m not in the investment game, but if I were, it would be all about scientific breakthrough. So I sometimes get in this place where I’m looking I’m going down a path. Ai you know, I’ll be up at four or five in the morning. My day hasn’t quite started, but I’m not sleeping anymore.
Speaker: 3
33:20
And I’ll start go like, I’ll be on Quora and see some cool quantum physics question or something else I’m looking into, and I’ll go down this thread with GPT or GROC. And I’ll start to get to the edge of what’s known in quantum physics, And then I’m doing the equivalent of ai coding, except it’s vibe physics.
Speaker: 3
33:44
And we’re approaching what’s known, and I’m trying to poke and see if there’s breakthroughs to be had. And I’ve gotten pretty damn close to some interesting breakthroughs just doing that.
Speaker: 1
33:55
And
Speaker: 3
33:56
I, you know, I pinged, I pinged you on at some point. I’m just like, dude, if I’m if I’m doing this and I’m super amateur hour physics enthusiast, like, what about all those PhD students and postdocs that are super legit using this tool? And this is pre GROC four. Now with GROC four, like like, there’s a lot of mistakes I was seeing Grok make that then I would correct, and we would talk about it.
Speaker: 3
34:24
Grok four could be this place where breakthroughs are actually happening, new breakthroughs. So if I’m investing in this space, I would be like, who’s got the edge on scientific breakthroughs? And and the application layer on top of these foundational models that orients that direction.
Speaker: 1
34:43
Is your perception that the LLMs are actually starting to get to the reasoning level that they’ll come up with a novel concept theory and have that breakthrough? Or that we’re kinda reading into it and it’s just trying random stuffs at the at the arya?
Speaker: 3
34:59
It’s,
Speaker: 1
35:00
Or maybe it doesn’t happen.
Speaker: 3
35:01
No. No. No. So what Ai what I’ve seen and, again, I haven’t used grok four. I tried to use it early this morning, but for some reason, I couldn’t do it on my on my app. But so let’s say we’re talking grok three and existing chat GPT as it is. No. It cannot come up with the new idea.
Speaker: 3
35:17
These things are so wedded to what is known.
Speaker: 1
35:21
Mhmm.
Speaker: 3
35:21
And they’re so like, even when I come up with a new idea, I have to really it’s like pulling a donkey sort of you you see you’re pulling it because it doesn’t want to break conventional wisdom. It’s ai really adhering to conventional wisdom. You’re pulling it out, and then eventually goes, oh, shit. You got something.
Speaker: 3
35:41
But then when it says that when it says that, then you you have to you have to go, okay. It said that, but I’m not sure. Like, you have to double and triple check to make sure that you really got something.
Speaker: 0
35:52
To your point, when these models are fully divorced from having to learn on the known world and instead can just learn synthetically Yeah. Then everything gets flipped upside down to what is the best hypothesis you have or what is the best question. You could just give it some problem and it would just figure it out.
Speaker: 3
36:11
So where I go on this one, guys, is it’s all about scientific method. Right? If you get if you have an LM or foundational model of some kind that is the best in the world with the scientific method, gain the f over. You basically you just light up more GPUs and you just got, like, a thousand more PhD students working for
Speaker: 0
36:35
you. Mhmm.
Speaker: 1
36:36
Keith, you’re, nodding your head here.
Speaker: 2
36:38
Sai Ai agree. I I agree with that. I think that’s fantastic because the scientific method also the faster it is, the more you when you have a hypothesis, the faster you get a response, you’re more likely to dive in and dive in and dive in recursively and recursively. And every lag, every millisecond lag causes you to, like, lose your train of thought sort of sai to speak.
Speaker: 2
36:57
So you get the benefits that Travis is leading to plus speed, and you go places you never really got. This happens all the time when you run a company and you’re doing, like, ai, and you have a tool that allows you to constantly query quickly, quickly, quickly, double click, triple click.
Speaker: 2
37:10
You get to answers that you never get to if there’s even a second or two second or three second bullet, let alone sending it to a human. Secondly, where you actually see this today, it’s already happening. If you look at foundational models that just apply to science, there’s lots of things about the human body, let’s sai, health biology that we humans don’t actually understand all the connections.
Speaker: 2
37:28
Like, why do we do x? Why do some people get cancer? Why do other people not get cancer? Why does the brain work this way? Models trained solely on science tend to expose connections that no human has ever had before.
Speaker: 2
37:41
And that’s because, like, the raw material’s there, and we only have a conscious awareness of all 110%. But when you apply it to other human domains where you’re training on human sort of data, human produced data, human produced output, they’re limited to that output. So I think you just take the science and apply it writ large, and you you’re gonna wind up finding things that no human has ever thought before.
Speaker: 3
38:04
And it’s the the thing about ai, though, is that it’s the hypothesis that you then have to test in the physical world. So the you’re like, okay. If you’ve got this hive mind, this, like, you know, this computation engine, this brain of sorts.
Speaker: 1
38:23
You wanted to say consciousness, but you stopped yourself. Yeah.
Speaker: 3
38:26
And Ai was like, how do I describe this? The big c word, consciousness. Yeah. But but you need to be able to test in the physical world. So you could imagine a a physical lab connected to one of these systems Mhmm. Where then you could say, okay. Like, if it’s a chemistry experiment, you could do chemistry experiments or physics. You you get the idea.
Speaker: 1
38:48
What could go wrong?
Speaker: 3
38:49
It would it it would be it’s yeah. No big deal. It’s gonna be fine. Okay. So but but this is where it goes because if you have a scientific method machine, you still have to be able to test your hypothesis. You have to go through the ai
Speaker: 0
39:01
method. Yeah.
Speaker: 1
39:04
Wow. It’s ai mind blowing. Reminds me of
Speaker: 0
39:06
the It’s really mind blowing.
Speaker: 1
39:07
If you meh I don’t know if you guys remember dark matter and, like, the discovery of it and everything. And as explained to me by Lisa Randall, you know, the the discovery was made not by knowing there was dark matter there and observing it, but observing there was something, you know, gravitational forces around this other matter.
Speaker: 1
39:25
And then they said, but wait, what’s causing that? And that’s why they found dark matter. So these ai, you know, the idea that an LLM could actually do that, come up with something so novel is it doesn’t it feels like we might be right there. Right? Like, we’re kind of on the cusp of it.
Speaker: 0
39:39
One of the seven most difficult problems in math or the most important problems in math is proving a general solution to this thing called Navier Stokes, which is basically like viscous fluid dynamics and conservation of mass. We use it every day in the design of everything. You know what? It hasn’t been proved.
Speaker: 0
39:54
Isn’t that the craziest thing where you’re just like, how is this even possible? We use it to design airplanes, to ai planes, to design everything, it hasn’t been proved. And so you could just point a computer at this thing and you would unlock all these incredible mysteries of the universe and we would probably find completely different propulsion systems.
Speaker: 0
40:12
We could probably do things that we didn’t think were possible, teleportation. I mean, who knows what’s possible.
Speaker: 3
40:18
But remember remember, you know, how Elon talks about Brock and and about AI generally is about why are we here? What is the purpose?
Speaker: 1
40:29
Meaning of the universe. Speak.
Speaker: 3
40:30
What is the meaning of the universe? How does it work? And a sort of fierce truth seeking mechanism there.
Speaker: 0
40:36
Let me ask you a question, Keith, Travis, Jason. If you guys were running GROC four?
Speaker: 3
40:43
That’d be so much fun.
Speaker: 0
40:46
How do you judo flip OpenAI? Because they are marching steadfastly towards a billion Meh, then a billion DAU. It’s a juggernaut. So how do you use the better product in a moment to judo flip the less better product?
Speaker: 3
41:09
Look. Yeah. I mean, here’s the thing. Right? So you do the Elon way. So you you get a bunch of missionary, like, full on missionary engineers that work twice as hard, and you have a culture that is ultra fierce truth seeking. And you don’t you don’t get caught up in politics, bureaucracy, BS, and you just you go for it. And and I think, you know, that’s where you know?
Speaker: 3
41:40
And then you go, wow. Scientific breakthrough, scientific method. Like, you start winning on truth, and that will start, I believe, that will start to give the product awesomeness of OpenAI a run for its money.
Speaker: 1
41:56
Mhmm.
Speaker: 3
41:56
But, like, the product of OpenAI, the product department, those guys are rushing.
Speaker: 1
42:01
They’re class.
Speaker: 3
42:02
They’re really good. They’re not only ahead of the game, but they feel like it just they’re just leading in a lot of different ways. But if you are better at truth, you will eventually you’ll eventually have an AI product manager.
Speaker: 1
42:14
Yeah. And on a tactical basis too, people forget how good Elon is at factories and physical real world things. What he did standing up Colossus made, ai, Jensen Huang was like, how is this possible that you did this? Right? So pressing that, his ability to build factories, and he said many times, like, the factory is the product to Tesla.
Speaker: 1
42:36
It’s not the cars that come out of the factory or the batteries. It’s the factory itself. So if he can keep solving the energy problem with solar on one side and batteries and standing up, you know, Colossus two, three, four, fives, he’s gonna have a massive advantage there on top of Travis, you know, the missionary individuals, which, by the way, was what he backed before Sam Altman corrupted the original missionary basis of opening.
Speaker: 1
43:03
I made it closed Ai in a you know, there’s nothing derogatory towards him, but he did hoodwink and stab Elon in the back. It’s not nothing personal. I mean, he just screwed him over and
Speaker: 0
43:13
Would you say he bamboozled him?
Speaker: 1
43:15
Bamboozled him, screwed him, hoodwinked him, you know. But you pick your term here, but, he did it he did it dirty. The original mission was to be a visionary, open source all this content. That’s the other piece Ai think is a wild card, and I’ll and then I’ll I’m interested in Keith’s position, but open sourcing some of this could have profound ramifications.
Speaker: 1
43:37
I think open sourcing the self driving data could have a really profound impact. Elon wanted to do something really disruptive, like he open sources patents for, you know, charging. If he open sourced the dataset and self driving, does anybody have the ability to produce robo taxis at the scale he can do it? I don’t think so.
Speaker: 0
43:56
Paul Sweeney’s hypothesis is true, then, yeah, everybody will.
Speaker: 3
44:00
Well, ai will what? Sorry. Everybody will what, Chamath?
Speaker: 0
44:03
If you have access to the money that buys the compute, everyone could solve that problem.
Speaker: 1
44:08
What’s the hardware piece? I’m trying to
Speaker: 3
44:09
Which problem?
Speaker: 0
44:10
He said he said if he if he published all the FSD data, could somebody build an autonomous vehicle?
Speaker: 1
44:16
Well, yes. But could somebody produce a 100,000,000 robotaxis from a factory with batteries in them? Okay.
Speaker: 0
44:23
No. That’s a diff that’s a different question. I’m saying.
Speaker: 2
44:25
And not really because there’s last time I was a guest on, you know, all and we talked about vertical integration. Products really require vertical integration. So, ultimately, you have a self driving something that is custom built for knowing it’s going to be self ai. And it interacts differently. The cost structure is different.
Speaker: 2
44:45
The controls are different. The seating is different. Everything you build a product taking advantage of where in the stock you have the most competitive advantage, but then you leverage that and it reinforces. It’s still why, like, Apple, despite missing the AI wave, still a pretty good company from any empirical standpoint.
Speaker: 2
44:59
I mean, like, their performance is absolutely miserable on the most important technology breakthrough over the last seventy years. But the company is still alive and still worth trillions of dollars because it’s vertically integrated. OpenAI, ai per your point, they do have a good product team, and they need to stay ahead of the product level because they can’t compete on the factory level.
Speaker: 2
45:20
The way to stay ahead of the product level is shipping a device. They gotta ship the device. It’s gotta be good. It’s gotta be right. It’s gotta be the right form factor. It’s gotta do things for humans that are unexpected. But then if they do that, they’re like Apple plus AI.
Speaker: 3
45:32
Chamath, what’s the paper you’re talking about before? What was the name of it then?
Speaker: 0
45:36
The Bitter Lesson.
Speaker: 3
45:37
That that, yeah, could apply to autonomous driving is right now, it’s still like, hey. How do I drive like a human? We talked about that. But the leapfrog moment here could be like, hey. Drive a car. Make sure it’s efficient. Don’t hit anybody. And just simulate that, quadrillion times, and it’s all good. Right?
Speaker: 3
45:57
But right now, we’re still trying to drive like humans because we don’t have enough data and, therefore, can’t do enough compute.
Speaker: 2
46:04
That’s the global lesson, by the way. TrueAuth, you’re totally right. Conceptual you know, the blog post is right, but that’s only true when you have enough data. And depending on the use case, the level of data you need may not be possible for years, decades, and you may need to hack your way there through human interactions.
Speaker: 3
46:20
Physical world AI is lacking in data, and so you just try to approximate humans.
Speaker: 1
46:27
I I don’t know if you guys have seen this. In related news, OpenAI and, Perplexity are going after the browser. Perplexity launched Comet for their $200 a month tier. I actually downloaded it. I’ll show it to you in a second. But this is, a really interesting category. It’s something developers can do already, and they do it all the ai, you know. But having your browser, connected to agents lets you do really interesting things.
Speaker: 1
46:54
I’ll show you an example here that I I just fired off while we’re talking. So I just asked it, hey. Give me the best flights from, United Airlines and, business class from New York City San Francisco to New York City. It does some searches. But what you see here is it’s popped up a browser window, and it’s actually doing that work. And you can see the steps it’s using.
Speaker: 1
47:14
And then I can actually open that browser window and watch it do that. This is just a screenshot of it. And it will open multiple of these. So you could I was doing a search the other day saying, like, hey. Tell me all the autobiographies I haven’t bought on Sana.
Speaker: 1
47:26
Put them into my, you know, shopping cart and summarize each of them because I like biographies and I ai, doing it here. And when it did this last time, it put my flight into, ai, and I was logged in under my account, and it basically put it into my account in the checkout.
Speaker: 1
47:45
So again, this isn’t like if you’re a developer, you do this all day long, but this really seems to be a new product category. I’m curious if you guys have played with it yet and then what your thoughts are on having an agentic browser like this available to you to be doing these tasks in real time.
Speaker: 1
48:06
You can also connect, obviously, your Gmail, your calendar to it. So I did a a search. Tell me every restaurant I’ve been to and then put it by city. And then I was gonna open my open table and then pull that data as well. What’s interesting about this, Keith, and I know you’re a product guy ai you’ve done a lot of product work.
Speaker: 1
48:25
I’m curious your thoughts on it, is you don’t have to do this in the cloud. You’re authenticated already into a lot of your accounts, nor do you have to worry about being blocked by these services because it doesn’t look like a scraper or a bot. It just it’s your browser doing the work. Your thoughts on this? Have you played with it at all?
Speaker: 2
48:43
Yep. I think it’s a great hail Meh attempt by perplexity. I think, obviously, something like this, perplexity is toast. Like, for the stat about ChatGbt is going to a billion users, like, it’s becoming the verb, you know, the the way you ai using AI for a normal consumer. There’s nothing left in perplexity if they can’t pull this off.
Speaker: 2
49:02
So it’s a great idea because, like, the history of, like, consumer technology companies is whoever’s up has uphill ground, like, in a military sense. Whoever’s first has a lot of control. This is actually what Google should be doing, truthfully. Like, I think Google is also Google search cross search is toast.
Speaker: 2
49:18
And since they have Chrome and they theoretically have a a quality team in Gemini, they should be putting these two things together and hoping to compete with Chattopty. They are gonna lose the search game. Like, the assets that are best at Google right now have nothing to do with search.
Speaker: 2
49:33
It’s every other product is the only thing that’s gonna save that company if they can figure out how to use them.
Speaker: 1
49:40
Travis, your thoughts on this category? Anything come to mind for you in terms of, you know, feature sets that would be extraordinary here? Ai know you you like to think about products and the consumer experience.
Speaker: 3
49:54
Lee, it’s really interesting. So, you know, I’ve been spending yeah. As you guys know, I’ve been spending my time on real estate and construction and robotics, and so Ai I’ve been out of the this kind of consumer software game for a long time. But super interesting over the last six months, there have been a a number of consumer software CEOs.
Speaker: 3
50:15
Like, when I hang out with them or whatever, they’re like, yo, how are we gonna how are we gonna keep doing what we do when the agents take over?
Speaker: 1
50:24
Yeah. The paradigm shift is so profound that the idea that you would visit a web page goes away and you’re just in a chat dialogue?
Speaker: 2
50:31
You have an agent who’s
Speaker: 3
50:32
just taking care of your flights for you. Sai I I kinda I I think there’s a leapfrog of over that. I think it’s just ai you tell something, yo, I wanna go to New York. Can you you know, I’m sort of looking at this time range. Can you just go find something I’m probably gonna like and give me a couple options? Yeah.
Speaker: 3
50:52
And it’s just a whole you have an interface and then, you know, is Perplex is this thing that you just showed him Perplexed, is that the interface? Or do I just have an agent that just goes and does everything for me? And is this the start of that? You know, I just haven’t spent enough time.
Speaker: 3
51:10
I I do know that every consumer software CEO that has an app in the App Store is tripping. They’re tripping right now. And I need big boys. I need guys with real stuff. And sometimes Sai I’m doing, like, almost like therapy sessions with them. I’m like, it’s gonna be fine. You actually you actually have stuff.
Speaker: 3
51:32
You have a moat. You have real stuff that’s of value. They can’t replace it with an agent. And they’re like, okay.
Speaker: 1
51:37
Ai them. You’re doing hospice care and you’re telling them everything’s gonna be okay, but the patient stops because you got a
Speaker: 0
51:43
lot of options on Robinhood while he’s like, yeah. Yeah. Tell me more. Tell me more.
Speaker: 3
51:46
I just want you guys
Speaker: 2
51:47
these things. There’s
Speaker: 3
51:48
certain things that are protected and there’s certain things that aren’t. That’s all. What’s your problem?
Speaker: 1
51:52
Let’s talk about that because the you and I are old enough to remember, General Magic. This vision was out there a long time ago with personal digital assistants, and you would just talk to an agent. It would go do this for you. This feels like a step to that where it does all the work for you, presents you the final moment, and says approve.
Speaker: 1
52:12
Sai it looks like a concierge or a butler. Yeah.
Speaker: 0
52:15
I think what you’re describing is what we sana, but I think more specifically for today, Keith and Travis totally nail it. Look, I think building a browser is an absolutely stupid capital allocation decision. Just totally stupid and unjustifiable in 2025. Specifically for perplexity, I think their path to building a legacy business is to replace Bloomberg.
Speaker: 0
52:40
Everything that they’ve done in financial information and financial data in going beyond the model has been excellent. As somebody who’s paid $25,000 to Bloomberg for many years, the terminal is atrocious, it’s terrible, it’s not very good, it’s very limited And anybody that could build a better product would take over a $100,000,000,000 enterprise because I think it’s there for the taking.
Speaker: 0
53:11
I wish that perplexity would double and triple down on that. And so when you see this kind of random sprawl
Speaker: 3
53:17
Let’s do it. Let’s do it, Jamoth. Let’s just go do it.
Speaker: 0
53:20
When you do the random sprawl, I think
Speaker: 1
53:21
it doesn’t work.
Speaker: 0
53:22
Ai I just wanna say like a browser is like the dumbest thing to build in 2025 because in a world of agents, what is a browser? It’s a glorified markup reader. It’s like handling HTML. It’s handling CSS and JavaScript. It’s doing some networking. It’s doing some security.
Speaker: 0
53:39
It’s doing some rendering, but it’s like, this is all under the water type stuff. I get it that we had to deal with all that nonsense in 1998 to try Lycos or Google for the first ai. But in ai, there’s something that you just speak to and eventually there’s probably something that’s in your brain which you just think and it just doesn’t.
Speaker: 0
54:04
You’re thinking, I need a flight to JFK Or at the maximum today in a very elegant, beautiful search bar, you type in, get me a ai. And it already knows what to do.
Speaker: 1
54:16
Keith, in some ways, this is a step towards that ultimate vision. So you’d think it’s worth it to, you know, sort of perplexity to make this waypoint, perhaps, if you look at it as a waypoint between the Ultimate Vision, which is a command line, and Earpiece how
Speaker: 0
54:31
do you get distribution, Jason, for the nineteenth web browser in 2025?
Speaker: 1
54:35
Well, yeah. That is a challenge and I think most people are speculating Apple, which has a lot of users, might buy perplexity or do a deal with perplexity and give them that distribution because of the justice department case against Google. So there has been a lot of speculation about that. But, Keith, what do you think?
Speaker: 2
54:53
Sai don’t think they’d buy anything worth it. Like, what do you what is Apple gonna get? And if you continue this failed strategy of Apple
Speaker: 1
54:59
Right.
Speaker: 2
55:00
Apple has missed every possible window on AI and continues to miss it. And it has cultural I think the CEO has challenges. I think culturally, they have challenges. They have infrastructure challenges. So it’s it’s not an easy fix, but buying perplexity is not gonna help. Like, to my strategy, he’s actually pretty coherent one for perplexity, quad perplexity. So I think that not a bad idea.
Speaker: 1
55:20
Ai vertical and own a strategy. Not meh
Speaker: 2
55:23
a not a bad idea, especially because you need unique data sources. Some of those data sources may or may not license their data to OpenAI. So you can do some clever things there, but, I don’t think there’s any residual value that Apple would get out of perplexity, except there’s some product taste.
Speaker: 2
55:39
But what are you gonna speak? Like, a billion dollars for product taste? I mean, Mark’s spending hundreds of millions of dollar hundreds of billions of dollars or whatever he’s spending these days. And, you know, Grok, if anything, Grok four shows that Mark really just he just speak money to build a whole new team because everything they’ve done in AI has also missed the boat.
Speaker: 1
55:56
Ai, I mean, Keith, the way you phrased it there almost makes it worth it for Apple to throw a Hail Mary, have a team with some taste, because that’s how they tend to do things is something that is elegant. And why not just throw your search to it, throw 10,000,000,000 at What’s elegant would be if there’s
Speaker: 0
56:10
a bunch of
Speaker: 1
56:11
see what happens.
Speaker: 0
56:12
What’s elegant would be if there’s a bunch of agents in just a chat box. Seeing a bunch of visual diarrhea is not elegant. It’s lazy.
Speaker: 3
56:20
Ai on our on our little Bloomberg saloni. I’ll give you naming rights. So you can call it
Speaker: 0
56:25
that You ai? You like it?
Speaker: 3
56:26
Polyhappetia. So, hey. Can somebody can somebody, bring up the poly hapatea?
Speaker: 0
56:32
You you know what’s so funny?
Speaker: 3
56:33
The social rules right off your tongue.
Speaker: 0
56:36
TK, listen. We were trying to do a screen of companies, and it maxes out at five companies on a specific type of screen where you’re like you’re trying to compare stock price to EBITDA and you’re like, ai, I can only choose five, I guess. So which five should
Speaker: 1
56:51
I choose? That happens when Lafont was on, right? Like two episodes ago, he was like, I can’t pull this up. It’s limited to six companies.
Speaker: 0
56:57
Dude, you it’s, so what do people use Bloomberg for? They ai it for the messaging. Now, like my team has traded huge positions via text message on Bloomberg. So there is something very valuable there, but the core usability and the core UI of that company has not evolved.
Speaker: 1
57:13
I have my contribution. And perplexity
Speaker: 0
57:16
is very good at that, by
Speaker: 1
57:17
the way.
Speaker: 0
57:17
It it they they do a very good job.
Speaker: 1
57:19
I got a new domain name, Travis. Let this one just sink in here. This is my way to weasel my way into the deal. Begin.com.
Speaker: 0
57:26
Begin.com. You own
Speaker: 1
57:28
that, don’t you? I do. I’m just a little I sniped some good ones once in a while. I got begin.com and I got annotated.com. Those are my two little domains. You’re like
Speaker: 0
57:36
you’re like one of these old people that show up at those Oh, like the
Speaker: 1
57:39
roadshow, and then Yeah. They all of a sudden and I’m
Speaker: 0
57:41
a team at the roadshow. And you’re like, oh, I have this thing that I bought 1845.
Speaker: 3
57:46
Guys, Jason Jason is Jason is the daddy in GoDaddy. Okay?
Speaker: 1
57:50
I am. I’m your dad. I’m your dad.
Speaker: 3
57:52
That’s what it is.
Speaker: 1
57:52
Who’s your daddy? Hey. Speaking of daddy, let’s go to our next story. Elon. Oh, is now the right time for a third party? Elon seems to think so. Last week, he announced that Axie would be creating a a new political party. I’ll let you decide who daddy is in this one. He said, quote, when it comes to bankrupting our country with waste and graft, we live in a one party system, not a democracy.
Speaker: 1
58:20
He’s not yet outlined a, a platform for the American party. We talked about it here last week. I listed four core values, which seemed to get a good reaction on x. Fiscal responsibility shah Doge, sustainable energy and dominance in that. Manufacturing in The US, which Elon has done, single handedly here. Pronatalism, which I think is a passion project for him.
Speaker: 1
58:43
And Shabazz, you punched it up with the fifth, technological excellence according to Polymarket. 55% chance that Elon registers the American party by the end of the year. And, you know, one thing I was trying to figure out is just how unpopular are these candidates and, these political parties.
Speaker: 1
59:02
This is a very interesting chart that I think we can have a great conversation around. It turns out we used to love our presidents. If you look here from Kennedy, at 83%, his highest approval rating, his lowest was 56%. That was his lowest approval rating. So he operated in a very high band.
Speaker: 1
59:19
Look at Bush too during, after ai, 92% was his peak. His lowest was ’19, right, ai president. But then you get to Trump one, Ai, and Trump two, historically low ai approval. Their high watermark, 49 for Trump one, sixty three for Biden, one of one, and then 47 for Trump two. And their lowest, twenty nine thirty one forty.
Speaker: 1
59:45
So maybe it is time for a third party candidate. Let’s discuss it, boys.
Speaker: 3
59:51
I have no idea how to read this graph. Zero This is
Speaker: 0
59:55
the worst.
Speaker: 3
59:56
I’m like, what is happening here?
Speaker: 1
59:58
This is the worst formatted chart. This is a confusing chart. But, well, the the reason I’m putting it up is for debate. So you should be saying thank you
Speaker: 0
01:00:05
for for debating
Speaker: 1
01:00:06
that it’s trading great debate.
Speaker: 0
01:00:08
Why did you put it up?
Speaker: 1
01:00:09
Here’s another one. Gallup poll Meh desire for a viable third party, 63% in 2023. So it’s it’s it’s bumping along an all time high.
Speaker: 3
01:00:17
K. I’m really concentrating on this one.
Speaker: 1
01:00:19
Okay. Anyway, I’m gonna stop there. What’s the gray? Okay. I’m gonna let you
Speaker: 0
01:00:24
Oh, okay. Okay. Got it.
Speaker: 1
01:00:25
I got it.
Speaker: 0
01:00:26
In a
Speaker: 1
01:00:26
different sense
Speaker: 0
01:00:27
I got that.
Speaker: 1
01:00:28
During that time period and how popular the party is. What I got. Let’s stop here. This is a good this is a good place to stop.
Speaker: 3
01:00:33
I just blew it off here.
Speaker: 2
01:00:34
Yeah. Look. A couple points. Yes. The idea of Saloni creating a third party is for any other human being, like, absolutely absurd and ridiculous. Elon has obviously done incredible things, so dismissing anything he’s touching is a bad idea. However, I think the best metaphor I’ve seen is it’s a little bit like Michael Jordan tried to play baseball.
Speaker: 2
01:00:52
He became a replacement level baseball player, which is actually really hard to do, by the way. Elon is probably a replacement level politician. He’s Michael Jordan for entrepreneurial stuff, but the third party stuff is not going to work. First of all, there that chart is misleading. It’s a flaw of average.
Speaker: 2
01:01:11
It sai badly designed, and it’s a flaw of average. Right. Is incredibly popular among Republicans. He actually has the highest approval rate of any Republican ever measured in recorded history. It’s 95%. Reagan was peaked out at 93%.
Speaker: 2
01:01:24
It’s just Democrats don’t like him, which is perfectly fine. Being polarizing is is an ingredient to being successful, including with people on the show. Like, the point of accomplishing things in the world is you don’t really care what half the world thinks. You need to make sure that there’s a lot of people who ai you and really approve and are enthusiastic about what you do.
Speaker: 2
01:01:42
And Trump is about as popular with his party as anybody’s ever been ever, period. No exceptions. Secondly, there’s MAGA has kind of already, changed the Republican Party. Trump is sort of ai a third party takeover of the Republican Party. And so it’s kind of already happened, and maybe you can do this every twenty years or thirty years.
Speaker: 2
01:02:05
I don’t think you can have, like, this kind of transformation on one party within a two compressed period of time for a lot of reasons. Third is, really smart parties absorb the lesson of political science. Unfortunately, I studied political science. I wasted kind of my college years.
Speaker: 2
01:02:20
And instead of saying CS and, you know, maybe then I’d be coding stuff and doing physics like Travis. But one thing I did learn is smart parties absorb the best ideas of third parties. So the oxygen is usually not there because they’re a Darwinistic evolution. If you could get traction on an idea, it’s really easy to conscript some of those ideas and take away the momentum.
Speaker: 2
01:02:44
No third party candidate that’s a true, like, third party has won a senate seat since 1970.
Speaker: 1
01:02:50
Mhmm.
Speaker: 2
01:02:50
And that’s, actually, Bill Buckley’s brother, and sai he has some name Ai need. The other thing Elon, I think, is missing and the proponents of what he’s doing is people vote not just for ideas, they vote for people. It’s a combination. The product is what do you what do you believe and who are you? And you can’t divorce the two.
Speaker: 2
01:03:09
Trump is a person, and that generates a lot of enthusiasm. And it’s one of the reasons why he has challenges in midterms because he’s not on the ballot. His ideas may be on the ballot, but he is not specifically on the ballot. So unless because Elon can’t be the figurehead of the party, he literally can’t constitutionally, there you need a face that’s a person, Obama, a Clinton.
Speaker: 2
01:03:29
Like, there’s reasons why people resonate Reagan without that personality. Specific ideas just are not gonna galvanize the American people.
Speaker: 1
01:03:40
Okay. So the counter to that and what people believe he’s gonna try to do is win a couple of seats in the house, Ram. Win maybe one or two senate seats. If you were to do that, those things are pretty affordable to back couple of million dollars for a house race. Senate, maybe 25,000,000.
Speaker: 1
01:04:00
If Elon puts, I don’t know, 250,000,000 to work every two years, which he, I think, put 280,000,000 to work on the last one, he could kinda create the Joe Manchin moment and, he could build a caucus, a platform, Grover Norquist kinda pledge saloni these lines. So what do you think of that?
Speaker: 1
01:04:21
If he’s not gonna create a viable third party presidential candidate, could he, Travis, pick off a couple of senate seats, pick off a couple of congressional seats?
Speaker: 3
01:04:30
Okay. So first, I have this axiom that I’m making up right now.
Speaker: 1
01:04:34
Okay.
Speaker: 3
01:04:35
Okay? It’s called Elon is almost always right. Okay. Okay? Ai.
Speaker: 1
01:04:39
And Elon is right about everything.
Speaker: 3
01:04:41
Okay. Seriously. Let’s just be real. And, like, honestly, the things he’s upset about and that he’s riled up about, especially when you look at the deficit, like, man, I am right on board that train. Part one. Part two, we’ve never had somebody with this kind of capital that can be a, quote, unquote, party boss outside of the system. Right?
Speaker: 3
01:05:08
And there’s a lot of people that agree with the types of things he’s saying, and he knows how to draw you know, he Elon in his own right kinda has a populist vibe. Like, he does his thing, and he’s turned x into what it is, and he’s he’s a big part of x. And so I think it’s the I think it’s great.
Speaker: 3
01:05:33
And, honestly, there’s there’s the moves you can make on senate and house and just having a few folks and then being you being levers then to get the things you want done. That’s part one. And then part two of that is the threat of that happening can make good things happen separately even if it doesn’t go all the way.
Speaker: 3
01:05:51
I just love it. I’m Ai on the email train.
Speaker: 1
01:05:54
Yeah. I’m I’m I’m in love with this role for Elon more than picking a party because he’s picking a very specific platform that I think resonates with folks, which is just balance the budget, don’t put us in so much debt, and let’s have some sustainable energy, You know, job done.
Speaker: 1
01:06:09
Create jobs in America.
Speaker: 2
01:06:10
The problem with that is, like, he’s actually wrong about the reason why we have a deficit or debt. It’s not because we’re under taxed. It’s we’re massively overspending. If we just
Speaker: 1
01:06:21
No. I think he believes we’re overspending.
Speaker: 2
01:06:23
They should’ve been supporting the last, you know, beautiful bill. Because if you just held federal spending to 2019 levels so 2019 is not like, you know, decades ago. Literally, with our current tax revenues, we would be in a surplus.
Speaker: 3
01:06:38
500,000,000,000.
Speaker: 2
01:06:40
Yeah. Sai there the all we need to do is cut spending. Now I admit that there’s
Speaker: 1
01:06:44
that happen with the big, beautiful bell?
Speaker: 2
01:06:46
So this is where details do matter. I think there is a willingness and a, you know, discipline problem on both parties, and I think may maybe he can help fix that. The second thing is that we have these arcane rules, particularly in the senate, and you need 60 votes in many ways to cut things except through very hacky meh.
Speaker: 2
01:07:04
And that’s a reality. So the best thing, truthfully, you could do is help get a Republican Party to 60 votes, and then and then, in theory, he could be absolutely furious if you didn’t cut back to 2,019 levels. But it it’s very tricky, or you can just overrule. Like, this the filibuster is an artifact of history.
Speaker: 2
01:07:24
And at some point, some majority leader is just gonna say we’re done with the filibuster and just steamroll through all the cuts at 50 or 51 votes, which you can do. There’s no constitutional right to a filibuster. It is an artifact of centuries of American history, and at some point, it’s gonna go away. So maybe the time is now.
Speaker: 2
01:07:42
Maybe we should just fix everything now.
Speaker: 0
01:07:43
I think you’re exactly right. I think that the filibuster, it’s just a matter of time. I think it’s on borrowed time. And I think in a world where it is on borrowed time, Jason, I think your path is probably the one that gives the American party if it does come into existence the most leverage, which is if you control three to five independent candidates, you gain substantial leverage.
Speaker: 0
01:08:06
I just sana take a step back and just note something. I don’t know if you guys know this, but the only reason we’re even having this conversation or this is even possible is because in 2023, the Meh, Federal Elections Commission, they actually released guidance and they changed a bunch of rules and the big change that they made then was it allowed Super PACs to do a lot more than just run ads.
Speaker: 0
01:08:33
Up until that point, all you could do if you were a Super PAC is just basically run advertising, television and radio, I guess online as well. But what they were allowed to do starting in ’23 was they were allowed to fund ground operations. They were allowed to do things like door knocking, phone banking, you know, get out the vote.
Speaker: 0
01:08:53
So in other words, what happened was a super PAC became more like a full campaign machine and Trump showed the blueprint of using a super Speak, specifically his, to win the presidential election. So he was able to fund this massive ground game. He built infrastructure across the swing states.
Speaker: 0
01:09:14
He was obviously incredibly effective and now that playbook can actually be used by other folks. And so to the extent that Elon decides to use those changed FEC rules, Jason, I think what you said is the only path, but but I just, I thought I just wanted to double click on Keith’s point because it’s so important.
Speaker: 0
01:09:32
I do think the filibuster is gonna go away and it is because the the arcaneness of these rules, having to do a reconciliation build and, you know, needing a super majority, a veto proof super majority in the other case, it just means that nothing gets done. And I think somebody will eventually get impatient and just steamroll this thing.
Speaker: 1
01:09:51
We’ve never had so many people say they feel politically homeless as we did the last two ai, and that includes many people on this podcast, people in our friend circle. And I think just the idea that Elon could create a platform that people could opt into and support, just the existence of that would make the other two parties get their act together.
Speaker: 0
01:10:13
By the way, the other thing
Speaker: 1
01:10:14
that need is a little bit of a stick there and a carrot.
Speaker: 0
01:10:16
Yeah.
Speaker: 1
01:10:16
Hey. If you don’t control spending, there’s this third option. And if Travis and I are in it, and, Keith, I know you’ll never leave the Republican party, but, Shmoph, you know, you’re probably set where you’re where you wanna be ai now. But I can tell you, we go to our top meh, twenty friend list. Out of those, 50% will join Nuance party.
Speaker: 0
01:10:35
Well, the other the other thing, Jason, that that Keith said, which I think is is really important is if he were to run people, I think they have to transcend politics and policy. And I think they need to be straight up bosses, people that have enormous name recognition. So that effectively what you’re voting is a name and not an agenda.
Speaker: 0
01:10:58
Equivalent to Ai think what happened to Schwarzenegger when he ram. He ran on an enormous amount of name recognition in the Great Davis recall. He didn’t run on the platform. I don’t think any of us could mention.
Speaker: 1
01:11:10
Which JD Vance had this great book, Captured People’s Imagination. He’s an incredible speaker. He pisses off a third or two thirds of the country, depending on where you are in the country, but you can’t ignore him. I think Elon can find 10 JD Vance type characters and back them fairly easily. He is a magnet for talent. People will line up.
Speaker: 1
01:11:30
I have been contacted by high profile people at Amazon.
Speaker: 0
01:11:33
Sai was actually thinking
Speaker: 1
01:11:34
of running. Can you put me in touch with Elon?
Speaker: 0
01:11:36
Ai high profile people.
Speaker: 1
01:11:37
I am
Speaker: 0
01:11:37
thinking more like actors and sports stars, meaning where they just come with their own inbuilt distribute. Like Sai think you almost have to rank x followers and Instagram followers and do a join and say, okay. These are do you know what I mean? Like, I think it’s, like, totally different ai
Speaker: 3
01:11:53
this. Ai, it’s painful. Like, let’s not get more celebrities as politicians. Like, let’s get, like, people who’ve led large large efforts, large initiatives, complex things.
Speaker: 1
01:12:05
You know? Ideally, but they still have to communicate. Right, Keith? They have to be able to communicate on a podcast. That’s the new platform. If they can’t spend two hours, three hours chopping it up on a podcast like this Of course. Or Joe Rogan, you know, that’s Kamala’s the reason she couldn’t even contend was because she couldn’t hang for two hours in an intellectual discussion.
Speaker: 1
01:12:24
If you can’t hang, you’re out in today’s political arena.
Speaker: 2
01:12:28
You know? Interesting to see if he can tune his algorithm for talent, which is epic, to tune for politics because it’s a slightly different audience. But if you can tune the algorithm and quality, that might work. I think you can win a few house races. I think that’s doable.
Speaker: 2
01:12:43
I don’t think you can win a senate race.
Speaker: 1
01:12:46
Well, there it is, Elon. Keith doesn’t think you can win a senate race, but he thinks you win a couple of congressional ones. Thanks for giving him the motivation, Keith. I appreciate it.
Speaker: 2
01:12:53
I’m sure he’s gonna win back.
Speaker: 1
01:12:54
He’s the biggest mistake you’ve ever made. He’s now gonna win too. People in the Republican party right now are going, oh, no. Don’t poke the tiger. Listen. Speak the That’s how
Speaker: 2
01:13:03
Trump got into politics, so I don’t wanna be Obama here.
Speaker: 1
01:13:05
Can I You just Obama? Ai. Right. Yeah. Congratulations. Ai, listen. SCOTUS made a big decision here. This is a really important, decision. They’ve sided with Trump for plans for federal workforce rifts, reductions in workforce for those of you who don’t know. As you know, Elon, Trump, they wanted to, you know, downsize the 3,000,000 people who are federal employees. This is just federal employees we’re talking about.
Speaker: 1
01:13:37
We’re not talking about military, and we’re not talking about state and city. That’s tens of millions of additional people. If you remember, Trump issued this executive order back in February when we got in office implementing the president’s DOGE workforce optimization initiative.
Speaker: 1
01:13:50
And he asked all the federal agencies, hey. Just prepare a RIF for their departments consistent with applicable laws, was part of this EO. Okay. In April, the American Federation of Government Employees, AFGE, sued the Trump administration saying the president must consult Congress on large scale workforce changes.
Speaker: 1
01:14:09
This is a key debate because the Congress, as you know, has power of the purse. They set up the money. But the president and the executive branch, they have to execute on that, and that’s what the key is here. So they accuse Trump of violating the separation of powers under the Constitution Act. AFGE has 820,000 members.
Speaker: 1
01:14:28
In May, a San Francisco based federal judge sided with the unions blocking the executive order. The judge, who was appointed by Clinton, said any reduction in the federal workforce must be authorized by Congress. This is a key issue. And the White House submitted an emergency appeal, yada yada. Eight of nine Supreme Court justices sided with the White House in overturning this bloc.
Speaker: 1
01:14:50
And so the reasoning, it’s very likely the White House will win the argument of the executive order. They have the right to prepare a rift. The question is, can they actually execute on that rift and who has that power, Chamath? Does the power reside with the president to make large scale or, you know, riffs? Or do they have to consult Congress first? Your thoughts on this issue.
Speaker: 0
01:15:11
It’s an incredibly important ruling. Incredibly right. I think President Trump should have absolute leeway to decide how the people that report to him act and do their job. If you take a step back, Jason, there are more than 2,000 federal agencies, Employees plus contractors, I think number almost 3,000,000 people If you put 3,000,000 people into 2,000 agencies and then you give them very poor and outdated technology, which unfortunately most of the government operates on, what are you sana get?
Speaker: 0
01:15:53
You’re gonna get incredibly slow processes. You’re going to get a lot of checking and double checking and you’re going to ultimately just get a lot of regulations because they’re trying to do what they think is the right job. So since 1993, what have we seen? Regulations have gotten out of control. It’s like a 100,000 new rules per some number of months. Like it’s just crazy.
Speaker: 0
01:16:20
So eventually we all succumb to an infinite number of rules that we all end up violating and not even know it. Sai if the CEO of The United States, president Ram, isn’t allowed to fire people then all of that stuff just compounds. So I think that this is a really important thing that just happened. It allows us to now level set how big should the government be.
Speaker: 0
01:16:46
But more importantly, the number of people in the government are also the ones that then direct downstream spend that make net new rules. And if you can slow the growth of that down, you’re actually doing a lot. In many ways, I wish Elon had come in and created Doge now. Ai, could you imagine if Doge was created the day after this Supreme Court ruling? It would’ve been a totally different outcome, I think.
Speaker: 0
01:17:15
Because with that supreme court ruling in hand, these guys probably would have been like a hot knife through butter. Travis So I I think it’s a big deal.
Speaker: 3
01:17:24
Except that ruling doesn’t happen without Doge. That Doge caused that ruling to occur.
Speaker: 0
01:17:29
True. Well, the EO did. You could have passed the
Speaker: 3
01:17:31
ai Meh pushed the ball off. That was all Doge style, though. You you know what I’m saying.
Speaker: 1
01:17:34
It was If they if they wasn’t firing people, yeah, they probably wouldn’t felt the need, to your point, Travis, to actually file this. But, Travis, if you are living in the age of AI efficiency right now, operations of companies is changing dramatically, can you imagine telling somebody you you can be CEO, but you can’t change personnel?
Speaker: 1
01:17:53
That’s the job. You get to be CEO, but you just can’t change the players on the team. You can buy the Knicks, but you can’t change the coach. Well, I’m sure
Speaker: 0
01:18:01
you can grow ai. You just can’t shrink it.
Speaker: 1
01:18:03
Yeah. It’s like a
Speaker: 2
01:18:03
union it’s like running a unionized company, which actually does exist, are a large unionized company, is where you can’t do any of these things.
Speaker: 1
01:18:10
Right. Do they do they still exist, or are they all gone? I think they just quickly.
Speaker: 2
01:18:14
Yeah. Probably. I think
Speaker: 3
01:18:16
this just gets back to what what is actually congress authorizing when a bill occurs. And there’s certain things that are specific and certain things that aren’t, and I don’t I’m not sure that in a in a lot of these bills, it’s not very specific about exactly how many people must be hired.
Speaker: 3
01:18:34
And so if it’s Ai just doing the common man’s sort of approach to this, which is ai, if if the law says you have to hire x number of people, then that is what it is. If the law says you here’s some money to spend, here are the ways in which to spend it, but it’s not specific about how many people you hire, then that is different.
Speaker: 1
01:18:55
Yeah. It should be outcome based. Hey. Here’s the goal. Here’s the the key objectives. Right?
Speaker: 2
01:19:00
But Travis Ai is totally right. Like, there are there’s a variety of different laws, some with the incredible specificity, some with very bryden that age. The constitution clearly says that all executive power resides in the president of The United States, period. There’s no exceptions there.
Speaker: 2
01:19:13
However, Congress does appropriate money, and post Watergate, many people think Congress has the power to force the president to spend the money, and you can debate that. You can debate it on a per statute basis. And that will be more nuanced, and that’s gonna get litigated whether the president can refuse to spend money that congress explicitly instructed him to spend, sometimes called empowerment.
Speaker: 2
01:19:37
That’s a very interesting intellectual debate. This one’s a little bit easier. It’ll get more complicated again. Like, this EO is only approved to allow for the planning. I think the vote might be closer.
Speaker: 2
01:19:50
I think there’s still a majority on the Supreme Court for the actual implementation, but it may not be eight one when there’s a specific plan that has to navigate its way through the courts again.
Speaker: 1
01:20:00
Yeah. It’s super fascinating. Yeah. I wonder if they’re gonna get to the point where they’re gonna say in every bill, you need to hire this number of people
Speaker: 0
01:20:08
to hit ai bill.
Speaker: 2
01:20:09
I don’t know if they can. Like, that’s where it gets borderline unconstitutional, like, where you actually prescribe that the president in the exercise of his constitutional duties, has to hire certain number of people
Speaker: 1
01:20:21
Mhmm.
Speaker: 2
01:20:22
That feels pretty precarious.
Speaker: 3
01:20:24
Well, I I I’m not sure, Keith. It’s just ai they prescribe a whole bunch of other things. Ai, you must you must appropriate money for to this specific institution to do this specific work.
Speaker: 2
01:20:38
I mean not an executive function. Like, if you said, like, the secretary of state has to have x number of employees employees doing something. The secretary of state is your personal representative to conduct foreign affairs on behalf of the president of The United States. It gets a little bit more messy as you translate it to people, that the president should I mean, yes, Congress does set, you know, which people are subject to sana a confirmation, what their salaries and compensation bans are.
Speaker: 2
01:21:07
So it’s it’s never gonna be fully binary where the president can do whatever he wants, and it’s never gonna I don’t think it’ll be constitutional for congress to mandate and put all kinds of handcuffs on the president.
Speaker: 1
01:21:17
Well, then you you also have performance that comes in here. What if you look at the Department of Education and say scores have gone down. We’ve spent this money. We’re not getting the results. Therefore, these people are incompetent. Therefore, I’m firing them for cause, and I’m going to hire new people.
Speaker: 1
01:21:32
How are you gonna stop the executive from doing that?
Speaker: 2
01:21:35
There’s been a bunch of litigation, you know, in parallel to this litigation about the president’s ability to fire people. And for the most part, the supreme court’s basically, with maybe the exception of the federal reserve chair, said that the president can fire pretty much anybody he wants.
Speaker: 1
01:21:51
I mean, that’s the way to go is, like I mean, I hate to be cut throat
Speaker: 2
01:21:54
out, but if
Speaker: 1
01:21:55
the results aren’t there
Speaker: 2
01:21:57
I think if they’re presidential yeah. If they’re a presidential appointee, the president should be able to fire you at will. Just like if you were a VP at one of our companies, the CEO should be able to fire you at will.
Speaker: 1
01:22:07
But what about, Keith, if the whole department sucks? Hey. You guys were responsible for early education. You had to put together a plan. The plan failed. Everybody’s fired. We’re starting over. Like, you should be allowed to do that. How would we have the official government?
Speaker: 2
01:22:20
Some of these departments were created by congressional statute, like the Department of Education in 1979. And you’re right. Every single educational stat has got worse in The United States since the department was created. But there is a law on the books that says there shall be a Department of Education, so you may have to repeal that.
Speaker: 1
01:22:40
Alright. Listen. We’re at an hour and a half, gentlemen. Do you wanna do the FICO story, or should we just ram, Jamal? And we got plenty of show here. It’s a great episode. Anything else you wanna add?
Speaker: 0
01:22:50
I don’t really have much to say on the FICO story. I thought these other topics were really good, though.
Speaker: 1
01:22:54
We did great today. This is a great panel. I’m so excited you guys are here. Let me just ask you guys, any off duty stuff that you can share with us, with the audience? Any recommendations, restaurants, hotels, trips, movies you watch, books you read? Keith, I know that you are an active guy. What what what’s on your agenda this summer?
Speaker: 1
01:23:14
Anything interesting you can share with the audience that you’re consuming, conspicuous or otherwise?
Speaker: 2
01:23:19
Well, I don’t wanna share any good restaurants or hotels because Oh,
Speaker: 1
01:23:22
you’re gatekeeping.
Speaker: 2
01:23:23
You’re gatekeeping?
Speaker: 1
01:23:25
Come on, man. Tip us some.
Speaker: 2
01:23:26
Tip us your baby. Baby. It’s like if you had a babysitter, you’re not gonna tell her maybe you’re babysitter.
Speaker: 1
01:23:32
Yes. Can I get your nanny’s name out?
Speaker: 2
01:23:35
Okay. But there are there are things that arya, what do you call it, no marginal cost consumption ai Netflix. So for example, you know, this documentary on Osama bin Laden is phenomenal. Like, I don’t know if any of you have seen it. I haven’t seen it. And, you know, I I I’m a student of this stuff, and I I thought, you know, I knew the whole story and etcetera. Watch episode one.
Speaker: 2
01:23:56
Just start with episode one, and it just blew me away with new information, new footage, just absolutely incredible stuff. So ai, highly recommend it.
Speaker: 1
01:24:04
What, what was the big takeaway for you so far?
Speaker: 2
01:24:06
I don’t know if there’s any, like, specific takeaway, but just, like, so many parts of the story are misunderstood and not really understood and how the various confluences of somewhat random things lead to a very catastrophic result. But it it it’s it’s, like, as, dramatic as the best movie, but it’s a full meh, and you will learn things and absorb things.
Speaker: 2
01:24:28
I I just I’ve had friends ai I’ve been recommending it to friends. And for a story you think you know, it’s incredible incredibly revealing.
Speaker: 1
01:24:37
Okay. Travis, anything you got on your plate there that you’re enjoying the restaurant, a dish?
Speaker: 3
01:24:42
I mean, look, you know I mean, JC, you know Ai go to Austin a lot.
Speaker: 1
01:24:47
Yes.
Speaker: 3
01:24:48
Like, basically, from March till October, I do about 15 weekends in Hello?
Speaker: 0
01:24:55
Austin and
Speaker: 3
01:24:55
I have a lake house. Jason’s hung out a couple times. So I I love water skiing. That’s my whole thing. That’s my, like, that’s I just love it. It’s just my thing since
Speaker: 1
01:25:06
I was here. Very zen.
Speaker: 0
01:25:07
Very zen.
Speaker: 3
01:25:07
And, man, it’s lake it’s I call it lake life. So
Speaker: 1
01:25:10
Lake life.
Speaker: 3
01:25:10
That’s a thing. And then I recently this little bit of, like, a side quest. Ai recently purchased the preeminent backgammon engine.
Speaker: 1
01:25:22
XG?
Speaker: 3
01:25:23
XG. That’s right. This, acronym is it it’s Extreme Gammon.
Speaker: 1
01:25:29
And
Speaker: 3
01:25:29
so the preeminent engine, so all the pros rate themselves based on this. It was done it was built by this amazing entrepreneur, this guy Xavier, who is just a full on sort of ultra ultra I mean, just what’s the word I’m looking for? It’s not, Saloni? Like sai Sana, essentially. But hasn’t worked on it for many years, so I’m getting back into it.
Speaker: 3
01:25:56
And
Speaker: 1
01:25:56
Love it.
Speaker: 3
01:25:57
And making it like, taking modern machine learning sort of deep learning techniques and, like, big compute and saying, can we push the game of backgammon forward? So super exciting. And ultra training apps to get people up to speed quickly. I played in my first backgammon tournament in cached. Sai that was pretty cool.
Speaker: 1
01:26:19
No. Wait. Yeah. Okay.
Speaker: 2
01:26:21
Yeah.
Speaker: 1
01:26:22
All due respect, you ai Uber. You’re very high profile. You go to this back end. Is this, like, held at the Motel eight in, like, a a conference room in the back? I’m I take
Speaker: 3
01:26:31
it to the spot. Ai they it was at the it was, like, a month ago or so. There’s, like, a big tournament, and it was, so the the United States Back End Federation had this big turn. It was, I guess, it was at the Los Angeles LAX at the LAX Hilton. And it was in the Yes. It was in the basement of the Hilton.
Speaker: 1
01:26:53
Great.
Speaker: 3
01:26:53
And it was ai
Speaker: 1
01:26:55
next to the Dungeons and Dragons convention. Right?
Speaker: 3
01:26:58
It it had those kinds of legit vibes. I love it. People would so so I went in super low pro, just did my thing, but eventually was ai. But I was not recognized as the founder of Uber. I was recognized as the owner of XG.
Speaker: 1
01:27:14
Oh, the owner of XG.
Speaker: 3
01:27:15
And then there was ai a full on melee that basically occurred. They’re like, oh, the owner XG, Travis is here.
Speaker: 1
01:27:22
Chamath, I feel like we’ve got a window here to do the all in backgammon high end tournament. We gotta lock this down now. We gotta lock down the all in backgammon set.
Speaker: 3
01:27:33
I get the co branding rights on this. Okay? Absolutely. X g
Speaker: 1
01:27:37
x Yeah. Well, no. The all in x g. Oh. You know, like, because I love a great back end set. If we could make, like, a $10,000 one, Chamath, we could kill turtles or white rhinos, all the animals that, you know, Freiburg is trying to protect. We could murder them and then make
Speaker: 0
01:27:52
That would be so great.
Speaker: 1
01:27:54
Meh. Like, maybe the white could be, you know, rhinos and then you could take something else, elephant skin, something, you know, just really tragic and then eat the meat and make the the the backgammon set for you.
Speaker: 0
01:28:06
I love back end. And honestly, like, if I wasn’t attempting to be, like, expert poker player, that is the game. I mean, if you’re talking about a Pandora’s box where once you open it, oh ai god, you can go down the rabbit. Let’s not rush
Speaker: 3
01:28:19
them off. Let’s go. Let’s do that.
Speaker: 0
01:28:22
Back end is a beautiful, beautiful, beautiful game.
Speaker: 1
01:28:25
I love the vibes of sitting. Travis and I sai. I got some cigars out. You know, we pour a little of the all in tequila, tequila.allin.com. We get that going. A couple of, the oil in cigars, and then we have the oil in back. It’s a wonderful hang.
Speaker: 3
01:28:41
Yeah.
Speaker: 1
01:28:41
Keith, would you consider giving us some of your money playing back out, Keith?
Speaker: 2
01:28:44
Absolutely. Absolutely.
Speaker: 1
01:28:46
We gotta we gotta get some of that cheap money on the table because you don’t
Speaker: 2
01:28:50
play poker
Speaker: 1
01:28:50
with us.
Speaker: 2
01:28:51
I don’t play poker, but backgammon yeah. That sounds great. And I’ll bring I’ll bring better tequila. Ai have better tequila. We’ll, like, we’re gonna upgrade it.
Speaker: 0
01:28:57
We’ll do
Speaker: 1
01:28:58
a little taste off. Yeah. Sai you’ve insulted now Elon with the senate seats and facts with his, chigula?
Speaker: 2
01:29:03
My chigula is much better. Trust me. Wait.
Speaker: 1
01:29:05
My okay. Who who was
Speaker: 0
01:29:06
left in the PayPal mafia you’d like to insult before this episode is like?
Speaker: 1
01:29:10
Reid Hoffman. Or Peter. Anything about Peter?
Speaker: 2
01:29:14
Reid could join Elon’s party. He’s collected a bunch of misfits sai meh might as well take read to.
Speaker: 1
01:29:19
Alright. Listen. This has been another amazing episode of the number one podcast in the world, the all in podcast for your sultan of science who couldn’t make it today. He’s at the beep conference, so we don’t meh. And, David Sachs, who is out, making America safe in AI and crypto. Chamath Palihapitiya, world’s greatest moderator. Pravas.
Speaker: 0
01:29:43
Keith, thank you for coming. Thanks for patiently.
Speaker: 1
01:29:45
You guys were great today. What a pal. A pal. See you all next time.
Speaker: 0
01:29:49
Bye bye.
Speaker: 1
01:29:51
We’ll let your winners ride. Ram meh David Cyrus. And it said we open source And it said, we open sourced it to the fans, and they’ve just gone crazy with it. Bobby West. Queen of Kim Wa. Besties are gone. That is my dog taking a noise in your driveway We should all just get a room and just have one big, huge door because they’re all just useless.
Speaker: 1
01:30:25
It’s like this, like, sexual tension that we just need to release them out. Let your Beep beep. Let your feet be. Where are your feet? What?
Speaker: 1
01:30:34
Where did you get Mercies Arman ai?