Why Physical AI Is the Next Frontier | Applied Intuition

17:39Qasar Younis:And essentially, you then find data like that, or you synthetically create data like that. And then you close that loop and you see, are you performing in those same scenarios better and better? I think if you fast forward some years, that will be a completely closed loop, like with no humans intervening. Right now, you still have like, what's the fog error that we saw? We still see errors in the real world that impact self-driving. Oh, yeah. So it's like, what are the bottlenecks, right? And the bottlenecks, there's plenty of them, but whenever you're dealing with physical systems, inevitably you hit a lot of gnarly hardware problems.

18:13And it could be anything from overheating to sensor being slightly miscalibrated or a funny issue we saw yesterday was basically a fogging sensor, like fog impacting a sensor. And these are the things that you actually have to solve for this stuff to work very reliably in the real world. Yeah.

18:32Marc Andreessen:So I'm going to ask you a question and we can decide whether you guys want to engage in it or not. It might be an opportunity or you might hate the question, which is, were you surprised? So Cruise was a super high-flying Silicon Valley autonomy startup that was kind of running neck and neck with Tesla early on and so forth. And, you know, very top-end team. And then they famously got bought by General Motors.

18:50Qasar Younis:One of my first distributions personally, so I enjoyed that. There we go.

18:53Marc Andreessen:Y Combinator, Y Combinator, Y Combinator company. And, you know, top-end team. And they were, you know, by all accounts, making excellent progress. they got bought by General Motors, they became the GM autonomy program. GM got a lot of praise, at least in tech circles, for being like, okay, being the legacy automaker with the biggest

19:12Qasar Younis:investment. I called Peter before I was announced on that and I said, hey, Cruz just got bought. You know, he's also a GM family. We're both GM families. And Peter guessed it. He said, NVIDIA? I said, no. He said, I said, go fish. He said, Apple? I said, no. I said, General explicit motors. So that's surprising to people who are from GM.

19:31Marc Andreessen:That they were willing to buy. Yeah, that they did it. Okay, they did it. And then by all accounts, they were, I mean, as far as I ever heard, like they were making excellent progress. And then they had this, there was an accident. There was a, was it an injury or fatality? It wasn't a fatality,

19:45Qasar Younis:but it was a serious injury.

19:45Marc Andreessen:Somebody was dragged for 20 feet. Yeah, serious injury, bad press. And then they put a bullet, the GM CEO on board put a bullet in the cruise project. Yeah. I know that at least some of the senior cruise people were extremely upset, you know, by the aftermath of that.

19:59Qasar Younis:Was it surprising that they reacted the way that they did? So, you know, full disclosure, General Motors is a customer. And I went to the General Motors Institute, so we have a lot of love for the company. But incidentally and ironically, I'm reading a coincidental, I should say, I'm reading this very famous book, which I had actually never read before, called On a Clear Day You Can See General Motors. Right. And DeLorean's book. Have you read it?

20:20Marc Andreessen:As one does. Have you read that book? So years ago, I have. It's one of the great all-time book titles. And we should just pause and say John DeLorean was like, what, he was like the super genius of the car industry.

20:30Qasar Younis:He was going to be the next president of General Motors.

20:31Marc Andreessen:Of General Motors. And then later on, he started his own car company, which led to the car. Which was in Back to the Future. Which was in Back to the Future. And then that whole thing collapsed for a variety of reasons. But yeah, he was like a legend. He was like one of the main principal drivers of innovation in the car industry. Exactly.

20:45Qasar Younis:Lee Iacocca, Bob Lutz, this category. Yeah. And you got to remember, this is Linda's. But sorry, repeat the title of the book. On a clear day, you can see General Motors. And why was that the title of the book? Because there's a lot of bullshit.

20:58Marc Andreessen:It's very large, complex. Yeah, complex. It's like a nation state.

21:02Qasar Younis:Yeah, I mean, really. I mean, it is. I think we say that sometimes almost flippantly. But these companies are like extension. Like Hyundai is an extension of the state. Toyota is an extension of the state. Literally, Volkswagen board members are members of the government. So these are extensions of the state. And there used to be an old saying, what's good for General Motors is good for America. Right. And you cannot understate how important General Motors is the history of the American corporation. Sloan's My Years at General Motors and Adventures of White Collar Man. If you run a large engineering organization, you should read that.

21:38Qasar Younis:This thing that we talk about as a modern corporation didn't just emerge. Sloan and Kettering create, Kettering was the head of engineering, created this with levels and vice presidents and how do you do functional and matrix organizations. There really is like the source code. comes along, John, you know, comes on DeLorean, and he says, he writes, he's going to be president, and he's so fed up with the company. But what was controversial was GM was doing really well at the time. GM was like a, when we say like GM was number one, the Fortune 100, it was like number one, two, and three. It was everything.

22:16Qasar Younis:And it was seen as the best company in America. So somebody to openly criticize the company. And so he has a hope. He writes this book as he quits. out of how annoyed he was, how General Motors was being led, he writes his book, and then after he sobers up, he's like, I don't want that book published. And so he fights for years for his co-author not to publish the book. The co-author still publishes it. So it's a real true insight into a large corporation. I'm incidentally just reading it out, even though I've worked at GM 20 some years ago and I know a lot about the company. And what's shocking is it's not only by GM, most of the major manufacturers actually still operate that way.

22:53Qasar Younis:on the inside. And so the question isn't, the point I think for everyone to take away isn't that these people who run these companies are stupid. They're not stupid. It's kind of like, you know, when you're selling to the Department of War and people say, well, why are you doing that? It's like, well, the distribution defines the business. So like the distribution is, this is a consumer product. This stat might be outdated, but when I worked in safety systems 20 years ago, I remember GM used to pound into your head of the top five consumer lawsuits in American history, three are automotive we got the majority right so it's a gift to be extremely careful we had these like weird things like inside the company you couldn't it wasn't red yellow green it was like purple or like you'd always have to as decoder because you know why because when they go to lawsuits they're like you let a safety system that was marked red go to production it was like no it was marked magenta like so like can you imagine how infuriating that is every time you're like what does orange mean?

23:52Qasar Younis:I have to like, so fast forward to you're meeting that system.

23:57Marc Andreessen:Well, the Ford slogan for a very long time was quality is job one, right? Yeah, yeah, yeah. Safety is about. Yeah, yeah, exactly.

24:04Qasar Younis:And that's the one-two punch of automotive. It's quality and safety, quality and safety. And quality really because the Japanese really reset that stage because that's a whole separate automotive history. We could talk about automotive history for an hour. But the punchline is you have then a Silicon Valley company meeting this immovable object. There is a parallel universe that cruises out there right now, even as a part of General Motors. So I think you always have to take it into the context of where the company is, where union negotiations are happening literally that year. And if you're the union, you're like, you can't make a billion dollars for us, but you're funding this thing that's killing people and it's sloppy.

24:41Qasar Younis:And so I'm not saying precisely that's what happened, to be very clear, but it's a multivariate problem. My other hot take is, you know, I worked at both companies, right? Google and General Motors, those companies are way more similar than they are different. Way, way more similar than they are. Literally, people don't know this. The Google leveling system is the same as the General Motors leveling system. And I used to say, I used to say this inside of Google meetings is like, hey, actually, some of the engineers I knew at General Motors are better than the engineers here. And people would look at me like, I'm saying there's no God in church.

25:10Qasar Younis:It's like, they're like, how dare you, you metal bending monkey from Detroit. I was like, no, actually, like making a modern combustion engine is extremely complex. It's not just like, you know, it's, it's, it's not simple stuff. And so the, the, the, the, the macro point I think is it's a bunch of things. I think safety is always at the top of their, uh, top of their list. I do think, you know, we've hired lots of cruise people. I think the way they dealt with that specific issue with a government, you gotta, you gotta dance a particular way when that happens. And it just didn't dance exactly right.

25:45Qasar Younis:And that just gives government bureaucrats, more ammo to go after. And you're a big target like General Motors. You gotta, you know, it reminds me, you guys ever see that movie like Goodfellas? You know, one of the last scenes of the House of the Rising Sun, you know, all the old bosses go in the back of the courtroom and they're like, and you know, that's what happened. The board was like, what are we gonna do about Cruz?

26:09Erik Torenberg:What can we do? It's like, Kyle's a good guy. And then it's like, Cue how's the rising sun. People running through a San Francisco office. Just kidding.

26:23Qasar Younis:Don't make that an AI video. It's going to get a mean text from Kyle. So I think there is a universe that would survive, but it's tough.

26:33Marc Andreessen:So then a lot of what Applied Intuition does is kind of, as you said, like that dance. It's like how to be a great partner to these companies. Exactly. Bearing in mind their own very real issues and constraints. I think generalists also have the topic of business model, right? So you have, Cruise was going after the robotaxi concept, but GM makes its profits from personal car ownership. And those things can be a bit odd. So I think that was also a bit of the equation.

26:56Qasar Younis:Yeah, and I think it wasn't clear. I mean, by the way, you know, you, actually, all people, you spoke at YC in 2013. I was in the audience. I was a partner at the time. And you said something, which I think is, it's very like recursive here. We're feeding each other your own advice. It's the key thing in the new technology business. Actually, everyone kind of figures out the technology, though that's still hard. It's still hard sometimes to build really complex things. It's when and how you deploy them into the market. The when becomes really important. You're two years early and you're doomed.

27:29Qasar Younis:You're two years late, there's too many competitors. You have to like hit it at the right spot. And I think it's like, I mean, a controversial thing to say is like, I actually think crews, you know, they were certainly moving at a much faster pace than Waymo. They started way behind. and you're talking about neck and neck when, you know, ultimately the plug was pulled. So who knows what happens in the long term? Our hypothesis in that same equation is actually the distribution. You let the manufacturers do that. Like we run self-driving trucks right now in Japan. They carry commercial loads. They're, you know, they're safety drivers there, but they're autonomously running.

28:03Qasar Younis:And, but you won't know that because the brand is Isuzu. That's the customer. And why it's so good for us to partner with Isuzu in that case is that company's been around for almost 100 years, right? If I'm not mistaken, a pre-World War II company. And they are, you know, they know the government. They have test tracks. They know their own trucks very well. So when we go and provide them with the intelligence and the integration into their physical machinery, that's a fantastic one-two punch. I think today the world is ready to consume AI in the real world. And that's a lot because of ChatGPT and Anthropic and all these, you know, everything that's happened.

28:40Qasar Younis:And so people are no longer like, what's a self-driving car? And there's views of Waymo and Tesla. So the market is ready to consume. And I think you just have to meet the market in the way that, the best way possible. And our view of that has always been, you go through some of the people who run the economy right now, whether it's a mining operator, whether it's a department of war, whether it's the manufacturers. And we work within each vertical with the right partner. But that's a fundamentally different view than a Tesla or a Waymo, which are going to be vertical. we're really playing the horizontal and I think the way we can always think we think about our companies we're kind of like a chip maker we actually look and talk and walk a lot like a silicon company except we obviously don't make chips but we have design wins and then we have really large long term relationships and once we're in we're in it's really hard to take us out so you need deep trust our partners have really a lot of deep trust and we know their markets really really well the things that Jensen knows is he knows his customers.

29:39Qasar Younis:That's why NVIDIA does well, beyond the fact, obviously, they make a very complex technology.

29:44Erik Torenberg:So how are these legacy car companies preparing for the future? Are they making more acquisitions? Are they building and partnering with you? How are they going to compete with tech native companies?

29:56Qasar Younis:It's like saying, how are governments dealing with AI? It's such a broad topic. And each manufacturer, even like you take Honda, Nissan, Toyota, three Japanese manufacturers with long legacies, they all approach it very differently. They're roughly in a spectrum of we're going to build to we're going to buy. And both extremes, more than ever, we're going to buy is the common answer because they've been trying and we've been there the whole time. For the folks that are going to build, we provide them tools. And we talk a little bit about our new product that we're announcing here. And then on the ones that just want to buy, we sell them the actual intelligence that goes on the machines.

30:34Qasar Younis:And so we meet the customer wherever they're ready in their journey. The more nuanced version of that is, you know, the reality is like every product is a different product. And so the amount of silicon and amount of dollars you can put towards it, towards sensors, what the customer is willing to pay, all that depends on what actually gets in the long horizon. All these things will be fully autonomous. but the intermittent steps are very much what we saw in the pc where you you have this slow step up to one day that'll be like now nobody really looks at laptop specs and even maybe frankly your phone specs but that's not the case from basically 85 to 2002 2005 where finally people stop actually speccing at all and and and then they're really moving to laptops but there's a similar kind of 20-year i think uh horizon there broadly when you talk about machines and machines becoming intelligent, right?

31:30Fundamentally, a machine is a collection of these different components that are integrated, right? And whoever does that final integration is oftentimes the company that puts their badge on it, the brand name. But many, many companies are building technology that goes into that machines. And so we now have a bunch of technology components and platforms that can go into these machines. But we also sell the core technology that can be used to develop them as

31:52Qasar Younis:well. And if you look, by the way, under the hood of a dirt mover or like combine or diesel truck, They'll have Cummins engines in them. But nobody says, well, because all these guys buy Cummins, this means that they're, you know, whatever, Caterpillar is not a good company. It's like, no, that's just a component that they buy. They have a different role. So when you look in any of these verticals, it's just a complex web of folks. That's why I always say like the chip kind of analogy actually works quite effectively because none of those companies make chips, but they all buy chips. and so I think that's a good way to think about it.

32:29Marc Andreessen:So self-driving cars, so we've all been talking about self-driving cars for like I think the whole thing started like around 2005 or something with the DARPA Grand Challenge originally and so then Google engaged in the program shortly after that. Yeah, late 00s, yeah. Late 00s. So almost 20, basically around less than 20 years maybe. And there have been lots of predictions over the last 20 years of like self-driving cars that are imminent at any moment. So I guess the bad news is we're sitting here today and most cars are not self-driving. The good news is there are now self-driving cars. And so the Waymo cars are driving all over, you know, in the places they're deployed.

32:59Marc Andreessen:It's become, you know, like people in San Francisco are, I think, treated now as routine that they get into self-driving cars. And I think you can call,

33:04Qasar Younis:I think Tesla, it's kind of like the AGI thing. It's like, you know, if we're talking 20 years ago, everything we're seeing right now is like a mind-blowingly AGI. Right. The post keeps moving. The Tesla stuff's amazing. You can look at a bunch of manufacturers, Blue Cruise, Super Cruise, BMW, Volvo's Pilot. They're all quite impressive systems. They're not full self-driving. Right. But yeah.

33:23Marc Andreessen:Well, it's still self-driving ex-whatever remote monitoring is happening. The Tesla, we have a home in Los Angeles, and you guys may recall there was a large fire in Los Angeles. Yeah, yeah, yeah. And then the California power grid was buckling even before that. And so it actually turns out, among the things Cybertrucks are good at is they're very good batteries for powering your house. Yeah. And so literally we have Cybertrucks as our backup battery for the house. And as of last year or whatever, the FSD release, I forget the exact one, but there was one where at least a lot of people thought it really turned a corner.

33:53Marc Andreessen:14, yeah. And that thing drives you. I talked to somebody yesterday who has a Model Y who let the thing do the full route all the way up Highway 1 through Big Sur.

34:02Qasar Younis:Yeah, I think mean disengaged, like the mean time and miles per disengagement are really high. I think miles is like in the thousands, which is very impressive.

34:13Marc Andreessen:Yeah, for people who haven't driven the Highway 1 Big Sur, like, that's a stress-filled drive. He said it was great. Anyway, so I wouldn't have been talking to him had it not been great. Would have gone right off. Because he unbolted the steering wheel. Yeah, right off the cliff. So, and then, you know, Tesla's rolling out their robotaxi, you know, is starting to show up in the wild. So, on the one hand, those exist. On the other hand, you know, 99.99999 % of cars are still not self-driving. And then I would say maybe just one other would be the self-driving trucks. There's been this recurring kind of panic in the press of like, the trucks become self-driving and the employment, you know, all these truck drivers are going to be out of a job.

34:51Marc Andreessen:And sitting here today, I don't think, I don't know, are there any trucks on the road that are self-driving that don't have at least a safety driver in the truck? And I think the answer is probably still...

35:00Qasar Younis:Yeah, still very few. So let's split the, there's multiple points we brought up here. One is on the, let's say, personally owned vehicles. And why are they not more ubiquitous? The part of that is the manufacturers are not good at deploying technology. Part of that is they want to be safety conscious. But most of it is cost, cost, cost. What you're seeing in China, which is China's kind of a different EV ecosystem, mainly because they don't care about profits. And you're talking about business that doesn't care about profits. It changes the entire calculus of the entire industry that doesn't care.

35:35Qasar Younis:But what you're seeing is you're seeing L2++ systems. So we can simplify the entire self-driving conversation to is there a driver behind the steering wheel? So this is a driver behind the steering wheel, still there, but generally like Tesla drives everywhere. They're like sub$1 ,000. There's an aggressive, that's chip, sensors, the package, the software, everything. We anticipate that there's a very aggressive, once you get to like 500, the automotive OEMs will actually subsidize it for free. They'll just give it to you. This happened in nav systems. If you guys remember, nav systems used to be a big thing.

36:06Qasar Younis:You pay four grand, 3 ,500 to get a nav system. and then suddenly it became free and it just became default. I think that'll happen. There's a weird thing, which is like, actually getting into a subset of your cars costs X dollars, and to get into all the cars costs X plus just a small incremental amount. Because it's just a fixed cost in the way that how many vehicles and the way the assembly line comes in, the way you have homologation, all these testing regimes, all this stuff. So I think you'll have wait, wait, wait, and then a lot. Every single OEM, without exception, even the lowest dollar OEMs are working on an FSD competitor.

36:40Qasar Younis:So it'll come. But it's just like, you know, with a good analogy to think about self-driving in the personally owned ecosystem is mobile phones. We had the satellite phones, then we had the Qualcomm, you know, brick phones, then we had the Motorola Razors. And from, you know, the late 90s to the late, you know, double zeros, the review was like, when's mobile going to come? There was a huge like, and then it comes and by 07 from the iPhone launch, it's like four years when you get Uber, Instagram, WhatsApp, Snapchat. Those are the killer applications. So I think there's a very, very similar kind of wait, wait, wait, and then it's just basically ubiquitous in every vehicle.

37:21Qasar Younis:If you had to ask me for what that number is, 28 SOP, 29 startup production, 29, 30. And then by the early 30s, it'll start becoming very cheap to free. Routinely by the early 30s, you would just buy a car and you just assume it's self-driving. Exactly. Or it has the driver in-seat L2++ system being very specific.

37:40Marc Andreessen:Like Cybertruck, or the Tesla equivalent. What Tesla owners have today will be some common.

37:46Qasar Younis:Yeah, will be default. So then the question, then the other side of this is, why don't we have a bunch of Waymo's everywhere? Specifically, Waymo has a different technology. Without getting into the nuances here, but Tesla and many of the Chinese and Applied were very much in this end-to-end model architecture. This is a new way of doing self-driving. Waymo, for the lack of a better word, is not that. It doesn't mean they're not learned. It's just not one end-to-end system. It's not one monolithic model. One of the proclivities of their approach is it does depend on HD maps. Therefore, there is a geofencing concept.

38:29Qasar Younis:I think Waymo's trying hard to remove that bottleneck so they can expand geographically faster, but the reality of today isn't there. The other thing is when you have researchers, which Waymo really was, coming out of an alphabet research organization, they didn't put commercial constraints. So the sensors are bespoke and expensive. The cars and the compute that are in there, they're just not economically feasible. And they've tried a lot to get that down, but it's kind of like, it's a lot easier to go from something that's really cheap and make it more featureful than something that's overbuilt and then trying to trim and make it really, really cheap.

39:06Qasar Younis:And that's the big debate. Who's going to get there first? Tesla with full self-driving or Waymo with cost and geographic ubiquity. But you know what we're not debating about? Is it going to happen? You know what we're not debating about? Like, is there a big technical breakthrough that needs to happen? None of those things. So now we're clearly in the engineering side of self-driving, which is just this grind down to like dollar per mile efficiency. And the moment that it's cheap, guess what? All the OEMs are smart. They'll just adopt it. It's not the OEMs are resistant because they don't think consumers want it or they don't understand the technology.

39:41Qasar Younis:It's because they want a price envelope, which allows them to keep their thin, razor thin margins, and at a scale, which is deployed across 100-plus countries in V1. And so if you're just doing a small deployment, it's very different. And I think, and the last thing I would say is the buyer of a Subaru or a buyer of a Suzuki have very different brand expectations than a buyer of a Tesla. And so including the age of the consumer and what they think will happen or what won't happen. So that's also the reason. So if you're a Suzuki, you're like, my buyer is like not to want this stuff. So I'm not going to jam it into the car.

40:22Qasar Younis:It's not because they're not like technically competent. This is a different area.

40:25Marc Andreessen:When do you think of a routine? let's say the 200 biggest American cities, like, it would be routine to walk outside and you're just taking for granted that a robot taxi can come pick you up?

40:36Qasar Younis:It's 26 now. I mean, certainly by 30. All right, okay. Yeah, certainly by 30. And I would say, the big, like, variable there really is, like, because what Waymo will say is that the dollars and cents per city already work, and it's like, well, a company that has basically unlimited capital, why are they not already in 200 cities? But then you see their launch schedule is pretty aggressive. And you're like, that can get there. So maybe if I was being aggressive, I would say 28. Yeah, okay. Like two years. I would say available in 30, but routine in maybe like 32, 33.

41:11Marc Andreessen:Sure, because to scale up, there's a volume.

41:13Qasar Younis:And also if you live in LA, so like five years ago, I'd go to LA. People would be like, what's applied intuition? I don't know what self-driving cars are. In the last couple years, now they all know self-driving, and some of them even know applied intuition because they know from the other manufacturers. I think you fast-forward another two to four years, everybody knows it now. Does that mean everyone's taking Waymos exclusively? The answer is no, actually. Now, there is a huge, huge, if you look at the numbers, if you're Uber, you've got to be scared. I mean, they're just eating into ride-sharing.

41:47Qasar Younis:Yeah, but to get 100 % ubiquity, I mean, that's another, it has to be extremely cheap. And what about long-haul trucking? So that's the passenger side. The long-haul trucking, completely different economics, completely different business model. There are many companies right now, I would say probably north of five, that are running long-haul trucks with drivers carrying loads between America and China. If you had China, it's probably getting into double digits. So it's there. But the reason you don't know it and the reason it's not top of mind is it's not a consumer product. And unlike on the Waymo and Tesla side, where investors are willing to essentially give you, you know, some market cap, you know, adjustment for the potential of, they say the trucking business is like, you know, made.

42:37You buy a car with your heartstrings,

42:39Qasar Younis:you buy a truck with a calculator. Yeah, it's a calculator business. And so it's like pure dollars and cents. And so I think you as the provider of self-driving trucks, if you're doing the whole thing, like some of the companies are, which we're not, you have to show every mile, I'm going to save you this many dollars. And it's like, for sure, for sure, for sure. Because the buyer is unsophisticated. And they're just like, well, I already got a staff that can drive. And it's like, and they're just not inclined. Now, where we're playing in Japan, it's not random that we're doing trucking in Japan.

43:11Qasar Younis:There's a massive labor shortage today. And there's an imploding demographic, you know, a situation. And so there's a demand from almost every sector. and that's why we've picked that market to really grow. But I think like you can take like even more obscure, like when will all queries, you know, literally like where you're moving cement, you're moving dirt, not queries, Q-U-A-R-R-Y, queries, queries.

43:42Marc Andreessen:It's a rock stone. Rock stone, cement.

43:44Qasar Younis:When are those? I can tell you the people who own those things and run those things want it today. Right. So it's literally, then you don't have a point. We can't make this stuff fast enough. The macro point, though, that people don't talk about, I think all this stuff's going to happen. It happened pretty soon. It happened fairly soon. But the macro point that in legislation and kind of in the kind of economics, the political economy of this conversation is AI is really, you see you have this big pushback in digital AI because accountants are like, I don't know if this is going to happen to my job.

44:19Qasar Younis:and VCs, I'm sure all of your associates are very scared. But like in our universe...

44:24Marc Andreessen:They're betting whether they need us.

44:26Qasar Younis:Yeah, yeah, yeah. In our universe, it's the other way around. It's like, literally, I'll meet these operators and they're like, we'll give you everything. Like, if you can do this, we'll give you everything. So then it's just up to us to like get there as, you know, aggressively.

44:40Marc Andreessen:Well, you know, the fear for a long time has been for... Trucking for some reason triggers at least the press's imagination on like, you know, sort of apocalyptic levels of job loss. Like, will there... But it's so wrong.

44:50Qasar Younis:Go ahead. There's not enough truck drivers. And guess what? Nobody wants to freaking be a truck driver. Why is that? Explain that. Because it's a terrible job. Because? It's like, you're like, you're like.

45:00Marc Andreessen:By the way, I grew up, the main feature of the town where I grew up was a truck stop, so I know the answer. But why is truck driving not a truck driver? Yeah, it's like, you're asking me,

45:08Qasar Younis:you know what, this is like talking to my kid. He's like, well, why can't I put my hand on the stove? It's like, because it's going to burn your hand. It's like, but why? It's like after the third Y, it's like, come on, buddy, let's do this.

45:25Qasar Younis:So what's hard about - I'm kidding, just to make sure everybody knows I did not do that with my son.

45:28Marc Andreessen:Yes, yes. So what's hard about - Why is being a truck driver a difficult job, or why would kids not want to do it when they grow up?

45:33Qasar Younis:So let me use a parallel analogy, which is very clear, and then you can - True. You know, people will say, like, nobody wants to work anymore. And they say, well, you know, McDonald's has all these job openings. No, no, actually what it is is those people that used to work at McDonald's, now DoorDash and Uber. Because it's better for them. Because they can open, they can start their hours and end their hours and they don't have to, there's no boss and they don't have to like stand on their feet and they can surf their phone in between, you know, orders and they don't, like, that's the reason. It's not random.

46:03Qasar Younis:The market is efficient. And so in the truck driving example, why does somebody not want to be away from their family for four to eight days in a row doing long haul trucking, the more sharp example is in Australia. Why don't people want to go literally buy a plane to go to a mine and work on, or you go offer a offshore oil rigs. Those jobs exist. If you want a job that pays six figures, they exist. Even with such lucrative pay packages, it's not enough because people are like, you know what? I like kind of being around my family and I'm willing to take an incremental decrease in cost and how much money I make.

46:42Qasar Younis:And, and then And also, like, I think today, more than ever, things like back pain and, like, being exposed to the sun and cancer and people that care about. That's now a part of the issue. This is the thing.

46:54Marc Andreessen:Tell me if I have this right, but I believe it's because I think long-haul truck drivers have life expectancy 10 years less than their peers. And I think it's a consequence. People say it's a consequence of several things. So one is some combination of nutrition and sleep. It's, you know, it's basically, you know. Yeah. It's very difficult. It's very difficult to eat well and exercise and get sleep. What's your sleep score if you're a long-haul trucker? Let me gather.

47:15Qasar Younis:There's no eight sleep on that. Exactly.

47:17Marc Andreessen:And so, like, obesity and then heart disease, hypertension, and so forth, they're all very high. One. And then two is I think the vibration is very difficult. Stress in the body. And then the third is, you mentioned cancer, but I think it's the— I think the truck drivers have, like, a much higher rate of melanoma on their left arm. Exactly. Yeah.

47:30Qasar Younis:There's photos of, like, a truck driver who's been driving for 30 years, one half their face, the other half's face, because it's exposed to the sun. Right. A more interesting, or even more stark stat, that mining is 1 % of the labor pool globally, 8 % of work-related fatalities. Do you think people are rushing to work in mines when they hear stats like this? Most major mines have a fatality regularly, which means once, twice a year, three times a year. And if you ever visit a mine, you'll see that everything is based around safety. Because once you experience one of your coworkers dying, then you're like, what am I doing here?

48:03Qasar Younis:Like there's other jobs I can take. And so it's, I understand you're trying to enumerate for the audience, like, but these are not good jobs. And the best evidence is this is not a mining podcast. This is not a podcast about, hey, long haul trucking is so great. They're just not attractive jobs.

48:21Marc Andreessen:Yeah, and even truckers don't want their kids to become truckers. Like, it's for that reason. They want their kids to be in a, at the very least, like, safer line of work. But do the, notwithstanding all that, how long will there be, do you think there'll be safety drivers in long haul trucks that are self-driving? Or let's say other, even just somebody in the cab to deal with what happens when they arrive?

48:40Qasar Younis:We know multiple companies that have driver out goals right now. Okay. So like they're working to get drivers out right now. Yeah. You know, without going into our own details. To be honest, it's not long. It's not long. We're talking a few years. I think on the long end. Yeah, on the long end. And the thing is, there's a software technology thing, which is one part of the problem. But the other part is, it's the redundancies that you need in hardware and the validation necessary for those redundancies. And in many cases, that can actually be a long pull. It's like, oh, they're productionizing a fully redundant steering system, fully redundant braking system.

49:14That's not in high-volume production yet. And once you get that in high-volume production, I get the quality up, and then that's validated, and now you can actually do these. Need the price downs. Exactly.

49:23Marc Andreessen:Do you guys, do you like the, you know, these own delivery robots? Do you see a world where there's a billion of those running around?

49:28Qasar Younis:Yeah, I think so. I mean, the product that we're announcing, I think it's probably come out around this time, is called Dana. So you can just simplify everything that Applied Intuition does into two buckets, which is, we've been talking mostly about the models that go on the machines. Then this is, we say, onboard software or onboard AI. Then there's off-board AI. This is the tools to design and develop these same systems, the models that actually go on the machines. Our, you know, vision for that is, and the delivery robot is a great example, is like a high school kid or a middle schooler, they can make iPhone apps.

50:04Qasar Younis:They should be able to make autonomous systems. So why can't they? Just ask that very simple question. Why can't a ninth grader make a delivery robot in their home? Well, they don't have the actual environment that they would first develop the scenarios in. They would define the requirements. Hey, I want this robot to go on my high school campus around these, let's say, four buildings. Then how, okay, now that you define the requirements, then you have the scenarios get made where all the scenarios that can be made by using, let's say, a satellite image of the high school. Then now you have to train the robot.

50:40Qasar Younis:So you need some data. Where do you get that data? There's maybe enough publicly available data that can actually train a fairly rudimentary robot. Okay, now you got that data from online, maybe YouTube videos, a couple of other places. Suddenly the robot's not doing, now you need to deploy it onto the actual machine. So then you deploy it onto the machine, and then the robot runs into the wall. Okay, what happened there? The loop closes. That platform for designing and developing is what we're launching. It's called Dana, which is the street that Applied Intuition is headquartered on.

51:13Qasar Younis:And this comes from our tooling background. And if you look at how tooling has changed in the digital AI world, If you look at like what Claude did to all, we also remember like, you know, from Mixpanel to, you know, GitLab, GitHub, all these, now everything has moved into a very different, almost IDE, frankly speaking. We think the same thing's gonna happen in the physical world. And so that's, yeah, that's what we're building. That's what we built, that's what we're launching. And we already use it in-house to develop our autonomy system, which is, you know, and we're working on the most kind of scale complex systems on the planet in all these different verticals.

51:50Qasar Younis:So we're pretty confident that it's actually quite useful. And we've seen massive productivity gains. But also, you know, we think like other companies will use this to build their own systems. Because it gets to that mission, that billion intelligent machines. Fundamentally, Dana is our agentic platform for physical AI. And everything that we've built and developed over the past nearly a decade, every tool, every technique, that's available in Dana. And it's very actually easy to use with the agentic interface. And so workflows that used to maybe take days or weeks to run, you can now run those in minutes in many cases.

52:28And this just lowers the barrier to entry to building these systems.

52:31Qasar Younis:And just lowering the bar of like, you know, what it means to develop an autonomous system. Autonomy is still actually quite in the scope of software is quite exotic. It's not because of the things that we've talked about. and we've just brought that down very, very aggressively. And it's kind of like, you know, the old adage of like, how do you make a great product in software? It's like you either increase safety, convenience, or cost, and we want to try to do all three of those things with Dana. And our hope is just like you said, like, you know, kids can develop robots for their own use, and that extends to humanoids.

53:08Qasar Younis:So we're not just talking about like land-based systems or, you know, ones that are, so you can do humanoids, you can do drones. The fact that right now writing drone software and deploying it at the time, it's quite obscure and almost hobbyist. We want to just make that absolutely like, you know, maybe not child's play, but like teenager play.

53:30Marc Andreessen:So this points to a world of like just like a lot more experimentation and entrepreneurship and like agriculture.

53:35Qasar Younis:Everything.

53:35Marc Andreessen:Bots and like basically every domain, construction.

53:38Qasar Younis:Yeah.

53:39Marc Andreessen:Defense. Exactly. You just all of a sudden have a much larger number of people who are applying creativity and coming up with ideas and making things that move.

53:45Qasar Younis:Yeah, and have you seen like with Claude, it's like, it's one thing just to make the engineer more efficient or bring more people into engineering. But then when these agents really run, you're getting into, it's just like the iPhone example of, you couldn't imagine Instagram before like the iPhone. It's like, imagine 2005 on laptops, you're like, in 10 years, there's going to be this app. Yeah. And you can put photos and they're like, well, the phones don't have cameras. Like, yeah, but it's going to be like social. Like, what the hell? Like, so like Facebook, it's like, see, it's just hard to, and so we think by lowering that barrier, you're going to get way, way more creative autonomy products.

54:23Qasar Younis:Right. Yeah. I will definitely decide

54:26Marc Andreessen:whether to include this or not. So my kid is building autonomous bots in Factorio. Oh, nice. Yeah. It's one of his projects. Yes. But he's, you know, he's hand rolling because the toolkit's not available yet. So he's actually training and he's actually, He's actually training models.

54:39Qasar Younis:Yeah.

54:39Marc Andreessen:He's gathering data in the game. And actually, he has like a whole army of like bots that he's developed to go out. Yeah. So like, that's what - And then his mother is like, why are you playing that game so much? And he explains, of course, it's a purely educational process and experience. But it's interesting. You know, it's the kind of thing. It's like, yeah. It's like, you know -

54:56Qasar Younis:Like there's no reason autonomy should be this like, you know, obscure, difficult, you know, alchemistic, you know, technology. And I think not only does that have a huge impact on society, it also allows people to understand that these systems are not like, you know, magic. Like, if I can develop a Roomba for myself in my house on a weekend using Dana, then why, then it's not suddenly so scary. And I think that's important.

55:32Marc Andreessen:And it can support people in all kinds of ways that we haven't even imagined yet. Absolutely. Yeah, exactly.

55:37Qasar Younis:I mean, you think about, like, you know, folks with disabilities. You know, we always think about humanoids as, like, this very important task of folding laundry, which seems to be a lot. So we focus on, you know, the important task when you allow these tools to exist. I mean, I, you know, we started a tooling company. I mean, I feel so importantly that tools are like what separates actually advanced civilizations from, you know, less advanced civilizations. And our first mark for the company was a monkey's head. And then we got a designer who said, What is this? Like, this is stupid. I was like, I thought it was pretty good.

56:16So you were talking earlier about how when, you know, the technology got so good in mobile that there was a wave of these companies, you know, Uber, WhatsApp,

56:25Erik Torenberg:Snap, you know, Airbnb, etc. that emerged in quick succession. And so now that technology is getting there or the infrastructure for physical AI, what are some use cases or companies that you could, obviously it's hard to predict the future, but where are you most excited for? Like, what could we be talking about the equivalent here of in quick succession?

56:43Qasar Younis:I mean, I think, you know, midterm, we want Dana, if not the short term, to really, you know, make humanoids way more real. There's, I mean, how many, it's like a thousand core tasks in a home from humanoids. And these companies, it's like such, I mean, if you talk to people who work in these companies, everything is difficult. Every step of the way is difficult. Collecting data is difficult. You know, cleaning that data is difficult. Training those models or deploying the model is difficult. And the bar being, I want a high school kid to make a humanoid. So that's our path. And we think there could be a lot there.

57:16Qasar Younis:But that's like the obvious stuff. I think the true non-obvious stuff is going to be, we'll look back, will be way more interesting. And there's some core ingredients that we're bringing together in data, right? We're making it way easier to actually get imitation learning to work, way easier to make reinforcement learning work in combination with that. where we have pre-trained models that can be used as a baseline for a lot of things. World models, advanced simulation tech, all of these things come together and then you're sort of limited by your creativity. Like, well, what do I want to do?

57:48And if you think about any kind of physically high task as it's a, you are understanding the world and you're manipulating something and we can build that. That can be built now much more easily in this tool.

57:59Qasar Younis:And I think sometimes people ask, like, us being a tooling company and like you take self-driving trucks, we deploy self-driving trucks and many of the self-driving trucking companies use their tools. I think sometimes people ask, look, you know, with Dana, are you going to like enable all these competitors? That's great. That's absolutely completely fine. If you look at Google and what Google did to web applications, there was a massive internet. Google still succeeded through, you know, search and YouTube and other web apps and other folks learned and used open source products and then ultimately closed source products and ultimately venture backed products.

58:32Qasar Younis:And we think the same thing could happen here.

58:36Marc Andreessen:I was at a robotic startup a while back that you guys know well, and they were training, you know, they were doing, go through a training process, training one of their arms to do, particularly a killer app that I thought was very appealing, which was picking up dog poop. Literally, you know, training over and over again is the difference. And so, you know, I don't know, why not, right? Why not have the little, why not have the little robot follow you around when you walked it on? Yes, yes. Pick up the poop.

59:00Qasar Younis:Yeah. And I think like, I know somebody who built,

59:02Marc Andreessen:I forget who it was, but somebody built a little lawn robot that would go around and pick up individual leaves. Yeah. Because you got that problem right. You rake your yard, it's completely clean, and then like two hours later, there's like 14 leaves. And you're like...

59:15Qasar Younis:Yeah. So it's like send out

59:16Marc Andreessen:the little bot to pick up leaves.

59:17Qasar Younis:It's like if development costs are zero, then people will do that. I mean, you guys remember like the early iPhone apps that hits were like the beer one or the fart app. If you imagine that in like... Yeah, if you imagine that in 98 with, you know, with the Symbian mobile, you know, whatever, or the OS from my, who's Ericsson or somebody. That'd be impossible. You'd need a team of like 50 people to develop a beer thing for the BlackBerry. So I think there's a similar type of thing that's happening. We're, you know, we really want to be a part of that. We want to enable that. And if it like makes making, like I think it'd still be a while before like making a robo-taxi is like super, super easy.

59:55Qasar Younis:Yeah.

59:56Marc Andreessen:But that'll happen. But there's, I mean, the number of bots that could be, the number of kinds of bots that could be deployed in healthcare is almost, just healthcare alone is that most okay. home care. Yeah. And then in construction,

1:00:07Qasar Younis:you know, all the physical trades. It's like us sitting in 2007 and saying, let's, we should have an app store. Right. What type of apps? And we would come up with like a list of eight. And then they're like, there'll be a messaging one. And then there'll be a camera one. And it's like, now you look at the app store and it's like, you know, there's an app for like the hotel you go to and it's like, you know, to order you know, food off the menu. Right. Yeah.

1:00:29Marc Andreessen:It makes sense. Yeah.

1:00:30Erik Torenberg:We were talking earlier about the differences between digital AI and physical AI, we were sort of hinting at LLMs, but world models are in vogue right now. Why don't you talk about sort of the state of them as it relates to physical AI and how we should think about them? So first off, world models means about 100 different things. And we had a team at CBPR recently, and I was joking with them about just how many different ways you can define what a world model is. But when we're thinking about a world model, we're typically thinking about it in the context of a simulation, right? Something that is effectively...

1:01:01Qasar Younis:We started as a sim company. Yeah. Yeah. Something that is sufficiently able to represent the real world and is reactive in a sense where you can actually have, let's say, an autonomous agent that's acting in this world and the world model is behaving appropriately in response to that autonomous agent. Maybe, Peter, I think it's worth being super explicit here. We just go just one level lower. you know determinism in simulators kind of the sim to real gap physics based you know rendering all the way to like this generated world yeah where do we fit on it or or where you know yeah describe the landscape i think maybe yeah so this is like let's say simulation broadly right there's there's so many different ways of doing simulation and so the the more classical approaches of simulation very physics based and and you can decompose physics in all different ways and all different levels of abstraction and you can simulate with sensors or without sensors and is it is just a body simulation or are we actually simulating for example the light in the environment or the almost think about like the way cgi is done if we literally had technical artists and we have technical artists who would create assets which would go in the simulator which would mimic real like road signs and have you know reflectivity and material properties that you would see in the real world but as you guys know hollywood is going through its own fundamental change and now you've generated technology, the same thing is happening in our universe as well.

1:02:23Yeah, so that's sort of on the, that's at the far end of physics-based simulation. And then the opposite end is purely neural simulation. But within that spectrum, there's many different things you can do that are each useful in their own right. And so one of those things is a Gaussian-based simulation, right, where you have effectively a representation of the real world that has a 3D representation. And that 3D representation is consistent, meaning that if you, let's say, have some reference point, let's say a camera, and that camera moves within that 3D world, because the Gaussian is actually representing the 3D geometry of that world, you'll actually get very high quality output from that.

1:03:05There's a lot of value in that, and that's, let's say, one type of world model. But when you go further on that spectrum, really into neural simulation, then you get into these where you're actually generating the video feeds. You can think of a neural network that's actually outputting a video, what's actually coming out of the neurons of that. And that can be reactive, which gives you some very interesting problems.

1:03:30Qasar Younis:Reactive is in the ego does something in the environment and the other agents respond to the ego. Exactly. However, you're not guaranteed in that reactivity that it's accurate, right? And now it's a question of, well, how can I align this simulation, this world model, with the real world and the way that the real world would actually react? And if you have perfect alignment between the real world and the world model, I think you've just sort of solved the universe roughly, right? That's a possibly difficult problem. But as we make progress towards that, it makes training physically on models much easier because you can do more of that in simulation.

1:04:08But the hardest part, though, is we're always talking about performance, right? So I like to say the labs, they have it easy because they can make models that are trillions of parameters, and those models can be super slow, and that's fine. But we don't have that luxury in physical AI, right? We deal in real time, like the actual clock real time. And so we have so many milliseconds before we have to do something. and those performance constraints, they actually constrain the problem in a lot of ways. So we can have very large models and we do have very large models that are used in the off-board environment.

1:04:43But once you go on board, all of those constraints are very real and now we need to train a much smaller model that has these safety constraints, these determinism constraints. And that's the hard part about physical. It's also the moat, right? It is what makes our tooling and our competencies valuable because it's just really hard to meet all of these constraints in a physical system.

1:05:05Marc Andreessen:When will you, which will we get first? A perfectly simulated real-world environment for training autonomous devices or Grand Theft Auto 6?

1:05:14Qasar Younis:You know, as long as they keep putting out great trailers, I mean, I feel like I'm getting entertained without paying a dollar. I'm reintroduced to Tom Petty because of how these... Will you give us some timelines?

1:05:30Erik Torenberg:Let's run with that for a second. Yeah, go for it.

1:05:32Marc Andreessen:Well, no, look, I mean, So the whole thing with Grand Theft Auto was the big innovation was open-world sandbox gaming. So it's a simulated city, at least in theory.

1:05:42Qasar Younis:On that spectrum, we hire so many people about the video game world. On that spectrum, it's absolutely real. Tell us about that. What's the spectrum? So here, this is speculation, but I think Grand Theft Auto VI will be perhaps the last major real-world video game that's still really developed, let's say, in that legacy era of traditional computer graphics tooling. Technical artists and, yeah. I think that Grand Theft Auto 7 will much more likely be like a world model-based video game. Right. And you could imagine as AI tech evolves here, you have like this concept of this video game world model and there's like some sort of baseline, let's say, data store that represents the real world and somehow, and then you have some translation layer that's actually turning that data store into something that you can see and run around in.

1:06:30Like, it's pretty possible.

1:06:31Marc Andreessen:But it could be, the game as a consequence could be the real world, right? As we said, you could have a complete recreation of the real world in the game. This has kind of happened with flight simulators, hasn't it? Yeah. The most recent flight simulators are literally, it's the entire planet rendered accurately, is my understanding, at least from the air. Is that right?

1:06:46Qasar Younis:Yeah, yeah. And I mean, that's where our bread and butters, when we started the business, we hired so many people out of the Microsoft flight sim. I'm surprised they didn't.

1:06:56Marc Andreessen:But when you fly over, you know, whatever, New York, or when you fly over Duluth in the flight simulator now, it is the real city. Exactly.

1:07:01Qasar Younis:But there's some tricks that they play there. And a lot of that is fidelity. You know, the real world, the more you zoom in, it stays a certain level of fidelity. And so the tricks that you play there is you basically are downsampling very, very aggressively. And then as you get closer, you know, then it becomes more high fidelity, where the real world isn't like that. if you were to try to rebuild the world with this level of fidelity, it would take all the energy of the universe, right? It's quite complex. And that's probably, by the way, the best argument against us being living in a simulation is among the...

1:07:38Qasar Younis:But, of course, then you would say, well, the simulator we're in doesn't follow the laws of physics that we're...

1:07:44Marc Andreessen:How do we know that the simulator that we're in is rendering all the stuff that we can't see?

1:07:48Qasar Younis:Yeah, yeah, that's true.

1:07:50Marc Andreessen:As far as I know, everything happening outside this room doesn't even exist.

1:07:52Qasar Younis:Yeah, this is, I mean, you know, like, Buddhism believes this. It's a different type of podcast. It's like, you know, when you open your eyes, the world is rendered, and then you close your eyes, the world. That's literally religious. Exactly.

1:08:04Marc Andreessen:I don't see why. I don't see why it's necessary for it to keep rendering if I'm not there.

1:08:08Erik Torenberg:Buddhism from first principles. Yeah, exactly. That's what you should, that'll get a lot of clicks, as you call this. Yeah. Well, just to be on the timeline topic, you know, we gave us timelines on self-driving cars. What timelines do you want to give us, if any, on sort of, you know, other interesting things that were worth tracking, like perhaps when we'll get laundry folded or other, you know, things that emerge because of humanoid.

1:08:29Qasar Younis:And I think also maybe just touching a little bit on world models, where we see world models, because I think it's fundamental to what the work we do. Yeah, for sure. Yeah, yeah. So to answer the first question, so laundry folding, it's not terribly far from being solved, to be clear. And there is a lot of interesting research being solved. And then humanity can rejoice. That's in Proverbs 4, 16, I think. Well, here, I do think housekeeping is a killer use case for physical AI, right? Peter thinks, too, that he always talks about in the company, what is housekeeping and it's entertainment? Peter's long on humanoid entertainment.

1:09:07Qasar Younis:What kind of entertainment do you know?

1:09:08Marc Andreessen:I would 100 % agree with that. I think entertainment is a robotist killer app, and I don't think anybody would. Yeah, these two. What do you envision? I mean, like,

1:09:15Erik Torenberg:So these Midwest white guys are really into this.

1:09:19Marc Andreessen:I'm just saying. I think... I just want to know when they get Westworld. That's all I want to know. No, I actually have an entertaining... I have a little... A tiny little Chinese robot dog. That's like, literally, it's just like a little... It's just a little... And it just like roams around, and it just like... Yeah, would you pay to see Cirque du Soleil with robots? Like, yes. Yes. I want to see... I want to see kung fu. Trapeze swinging. Spoken by like a compilers guy.

1:09:47Marc Andreessen:I want Westworld. I want Westworld.

1:09:49Qasar Younis:I mean, the funny thing is, I was just saying, like, well, people in, like, the suburbs of Detroit, actually, that passed the test. I bet you people in Sterling Heights would actually pay to see that. It's actually true. I stand corrected. I stand corrected. But back on laundry folding for a moment, it's actually not far from being folded if you remove the time constraint. And so the trick that's played, and if you look at the latest research videos, is they'll say, like, play it at 8x real time or whatever. and that's for you to make it watchable. So the question is, when can you actually reach human parity of performance?

1:10:22That's further off.

1:10:23Qasar Younis:When you decouple models from just the hardware, the hardware can do it now. That used to be a constraint. So the hardware is very fast and accurate now, which was actually... There's still overheating issues that are still being dealt with, but it's not terribly far off. Like, these are solved. I mean, it's far off from like, you know, when I was a Mechie, that was like fantasy. Like, there's like nothing can... What's the movie that has the most realistic future vision of robots? Oh, man.

1:10:44Marc Andreessen:Bicentennial Man. Is it? Okay.

1:10:45Qasar Younis:Yeah, he's real issue.

1:10:48Marc Andreessen:Why that one?

1:10:48Qasar Younis:I actually haven't seen it. Well, I like that scene. I think it's iRobot when Will Smith jumps in the car and his, you know, whatever, his accomplice sits in the car and he's like, puts the car in manual and she's like, what are you going to drive this thing yourself? Yeah, she's like, are you crazy? What are you going to drive this thing yourself? That's applied to intuition's goal. By the way, I haven't seen this movie in a long time, probably since it came out. So my recollection of it is probably a bit incorrect. Don't worry, the internet will correct you. But I think Bicentennial Man has fully self-driving cars.

1:11:23And it also has the housekeeping robot, which is played by Robin Williams. And it's sort of like the friendly guy that will, the friendly robot that will clean up and also babysit your kids and stuff like that. And it seems like it's in the not terribly distant future.

1:11:38Qasar Younis:I got a different answer. You guys ever see that movie, Sam Rockwell Moon. Oh, yeah. Yeah, the setup. I don't want to, it's a great movie. Don't watch the trailer, just watch the movie. It's the premises, the tagline of the movie is 250 ,000 miles from home, you find who you are. And it's one guy who works on an energy harvesting base run by Platt Intuition, run by Lunar Technologies.

1:12:03Qasar Younis:I don't want to be, I don't want to be whaling you, Tani. I don't want to be, you know, that's from the Alien franchises and then Tartaral Corporation from Blade Runner. No, no. I want to be lunar technologies in the moon franchise. Not even franchise. There's one guy who works on this and the base basically runs by itself. And he's just there to kind of mind it when things kind of, some, you know, error signal. Yeah, the reason why it's, I think, so accurate is because the state of the art for AI systems is, like, these systems, they just need the occasional grounding. Exactly. They'll just go off and do something crazy.

1:12:35And then you'll say, no, no, stop doing that. L-Lons are like that, too. That's what coding bots are like.

1:12:39Qasar Younis:And the other reason I think it's quite accurate, it's maybe uncouth now, but Kevin Spacey is the AI, you know, smiley face. And he's just there to kind of placate the human to assist, but to also like, he's like, oh, you seem like you're sad, Sam. And like, you know, like that's the, but really it's the one running the base. And hopefully, I mean, I shouldn't say we want to be lunar technologies, because I don't know if they're quite a positive force of nature in that. But I think massive energy farm that's completely autonomous, that's going to be the future. And I think everyone reacts to things like that with fear.

1:13:19Qasar Younis:And it's like, guys, that's amazing. That means energy costs go way down. That's an incredible positive thing. I think the, you know, I just did this commencement speech at my undergrad. Did you get destroyed?

1:13:33Erik Torenberg:No. You know what? Unlike Eric Schmidt. Yeah, yeah, yeah. He's not getting booed?

1:13:38Qasar Younis:Listen, listen, my wife started watching and she said, I feel like you're yelling at me. I can't watch this. I basically I'm not like I don't I don't I'm not going to say which tech leaders who just basically avoid it by like punting and saying I'm not going to talk about it. I talk about this stuff. And partly it's the General Motors Institute. No one's like these these are I don't want to I don't I don't I don't want to throw judgment on, you know, the people we recruit out of out of MIT and Stanford. but let's say GMI people are a little different and they're like pragmatic people. You don't go to a place like GMI if you believe a superficial view of what corporations do.

1:14:18Qasar Younis:Corporations are just people working on projects together. And by the way, people working on projects together in government, people working on projects together in nonprofits, they all screw up. And so it's too simple to say AI corporations are terrible. That's also, you can't say the other side, which is like, it'll all be great. So you have a role to play. That's basically what, you know, what my, what my message is. And it's, that's, that's the case. I think if you feel like if, if, if the, of the, the, I think the obvious, you know, abundance that comes from self-driving trucks, self-driving cars, and the fact that people don't die, which is amazing.

1:14:51Qasar Younis:but then you also get this efficiency of cheaper energy etc if all those things don't still satisfy your your fear you you as a person it's up to your responsibility to really learn about that technology you you can't just say well i'm afraid of it and my reaction is shut it down that's not that's simple it's the uh and i don't say this just to say that we're competing with the chinese but there's a Confucian. The saying about Confucian is, no hand can block the sun. And the sun is technological progress. And if we as a society don't embrace technological progress, we will be left behind.

1:15:29Marc Andreessen:Right, and somebody else is going to do it.

1:15:30Qasar Younis:Somebody else is going to do it. And if it's not the Chinese, who knows? Maybe it's the Uzbeks, or it's another country that is recognizing, hey, my citizens are suffering, and I'm going to use this technology to remove them. It is, honestly, it's because we live in such a great society that we can have these, like, I would say stupid conversations. Like, there still are people who can't get food. And someone will immediately quip if they were debating me. They would say, well, there's plenty of food. It's the capitalist system that doesn't. No, no, no. Let's be very specific. There's plenty of food, but getting that food to those people is difficult.

1:16:05Qasar Younis:So that means we should let robots get that food to them faster. That's just how it is. And I think, like, we as, like, technologists, I think sometimes we, you know, it's, I think, an inclination just to say, leave these people behind. I think you have to bring them along. You have to explain it to them. But we also have to treat folks like adults and say, if you don't get it, after I explained it a couple of times, then you just don't get it. There's like a middle ground. It's not everyone's an idiot and we should just be, technology will just be perfect, perfect, perfect. There's a middle ground.

1:16:37Qasar Younis:Let's have that conversation to a point. And then we just move forward and make society better. And then the results show it. I mean, there's people who still shockingly believe communism is the right answer. I mean, I just want to say why, and I'm, you know, I am a capitalist. I can't not admit that. But there's 70 years of history there. Like, that's not even a debate anymore. I mean, I think it could be a debate. If we're sitting here in 1965 and having a debate, you say, okay, maybe centrally controlled systems work better. There's no debate anymore, folks. You know, systems where individuals make decisions on their own interests, actually work better for society.

1:17:13Qasar Younis:And so that doesn't mean everything is perfect and you can't extrapolate. That same thing with, you know, AI. It doesn't mean everything's going to be perfect, but net-net, it's definitely going to be better. And that's roughly what my commencement speech was without the boos. A market, these guys were booing, so they just cut it out.

1:17:31Erik Torenberg:Eric was booing and throwing stuff and they just added it out. You mentioned the Japan market earlier. Why don't you talk briefly about sort of the global ambitions and how these technologies interplay and what we're doing here.

1:17:42Qasar Younis:So I think America particularly is still the most advanced in terms of when you take account the business model. The second thing for a company like Applied Intuition, we're an extremely global company. We work with everybody, minus we don't have an office in China, but really everyone else on the globe. And we're a horizontal company. We're a technology provider. And I think more Silicon Valley companies, I think can employ a little bit of what we do, which is work very, I would say, collaboratively with the local economies. As sovereign AI becomes more of a real thing, we have to build businesses that take that into account.

1:18:20Qasar Younis:By the way, we're not the first ones to do this. If you look at the history of America, you read the history of Standard Oil, you'll see that that was the history of companies. You'd work internationally. Aramco is not a random company. You build based on the geopolitical realities of the time. And so I think, you know, we've, I think, navigated it quite well. I've lived, you know, in Japan. I lived in Germany. I lived in Dubai. So also being Pakistani by birth, I think that's also influenced our company. Peter's only lived in Michigan and here, but he is a German. But so I think innately we're more, we think about the globe more.

1:18:58Qasar Younis:And I think when I was at both at Google and at OIC, I was always surprised at how kind of almost myopic. The companies are just always looking at the market that's just like within the 30, you know, between San Jose and San Francisco. It's like, actually, the market is really big. I think physical AI, the nature of it being physical, I think we have to be a very international company. And I think we've had a lot of success being a very, you know, being international. Yeah. Cool.

1:19:22Erik Torenberg:I think it's a good place to wrap. Okay. Peter Kasser, thanks so much for coming on the podcast. Congrats on a big launch with Dana.

1:19:27Qasar Younis:Yeah. Thanks for having us. Awesome. Great to see you guys.

1:19:29Erik Torenberg:Okay, great. thanks for listening to this episode of the a16z podcast if you like this episode be sure to like comment subscribe leave us a rating or review and share it with your friends and family for more episodes go to youtube apple podcast and spotify follow us on x a16z and subscribe to our substack at a16z.substack.com thanks again for listening and i'll see you in the next episode As a reminder, the content here is for informational purposes only. Should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.

1:20:11Erik Torenberg:Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see a16z.com forward slash disclosures.

1:20:27Thank you.