Intelligence is Everywhere: Why the AI 'Race' is Already Over

0:00 I am shocked by how much of a barrier that sense of willingness is. Like I talked to a lot of folks in the business in enterprises and they're like I don't like my engineers care about codecs. That's fine. Good for them. I'm not going to make everyone a coder in my company. >> I have other things to do with my business. When you look at the next 10 years or so, paint me, I guess maybe paint me two paths, right? Paint me the happy path where you're like, "Okay, we're going to get to a society that's more functioning." And then maybe paint me a darker path.

0:29 >> Yeah. I mean, nobody won the electricity race, right? >> We all got electricity. >> Yes. And but that to me is scary because if your stuff is that good, why the heck do you need, you know, >> that much lobbying? No, it's already here. >> Sounds like the AI that we're creating. Essentially, we don't need to depend on the kindness of an alien species. We are creating our only alien species. >> We are. I've got something really special for today's video. I've been trying to find someone who can talk about US, China, AI without picking a side, and I found it. Alvin Grlin has been in AI all the way back to 1990 on both sides of the Pacific. He has perspective I haven't seen anywhere else. He tells me the arms race isn't real. That's right. So stay tuned. This is going to be a fun one.

1:15 >> So Alvin, this is the first time that you're on the podcast here. Maybe start off by just telling us who you are, how you got into AI, kind of where you're at right now. >> sure. Yeah. Thanks for inviting me. And so I've been you know in tech since 1980 >> and you know been coding since then. I started doing AI in 1990 911. I was doing neural networks controlling creating my own bread boards and doing natural language processing and have essentially worked through the entire AI stack everything from data centers to chip design to to devices to apps models. so I I've seen a few things happen and you know in fact I worked on when I was at Intel I worked on the chip that was the first single instruction multi-data SIMD which is what GPUs are based on. It was called MMX at the time. So >> MMX we worked on both both sides of the Pacific. I studied at University Washington also I did my computer science at MIT and my MBA at MIT recently and now I've essentially moved from industry to more academia. I'm doing research at at Stanford the at the HAI human center AI institute and then also at I'm teaching here at UDub and I I'll be starting in the winter but in AI and technology policy and then I >> work at a think tank in DC advising our governments on making some better policy decisions around AI and technology. So >> in that world, what do you think is the biggest misconception that people have around AI that you spend a lot of time and a lot of breath sort of trying to diffuse or change perspectives on? I I think the the biggest problem in fact probably the core problem that is driving a lot of bad decisions right now is this misperception of this AI arms race >> u and the the expectation that there's a finish line that there is a single winner the winner takes all and that the world is zero sum and none of that is true >> right and I think when people wake up and finally understand these none of those are true then everything that we've been doing whether from an industry perspective or from a national security perspective is really misallocation of resources. The competitive nature also is preventing us from making these products and these technologies more safe >> and it positions AI sort of inevitably as a weapon as opposed to positioning it as a technology.

3:44 >> Yeah. I mean nobody won the electricity race, right? We all got electricity >> and and I in a lot of ways this is what this what you know you can't keep keep people from having electricity and you can't keep people from having AI. It's just it's software and software wants to be free. Software wants to be everywhere. Software is is you know impossible to to prevent it from being distributed especially when we start having now you know open source or openweight software that >> that's right >> it's completely open source. It's tiny.

4:13 It has a a new architecture that is actually now can you know run on a Mac studio >> whereas these other closed source devices or closed source models are running on multiple racks right and each rack is millions of dollars >> so this commoditizes high quality intelligence and you know I don't think that's a bad thing no >> right except maybe for a couple companies who are relying on high profit margins from this everybody else it's good for >> that's right. I I believe in a future where intelligence is ambient >> everywhere >> essentially free >> and now it's able to run on a you know PC essentially a Mac studio and another few months somebody's going to quantize it and then it's going to run on a laptop a laptop and then another three four six months from there it's going to run on our phones and the level of intelligence we have in these systems is already amazing. It's more than most people can use most of the time.

5:12 >> That's right. And so that's the case. It will be ambient. It will be everywhere. And you know it cannot be hoarded or monopolized which you know a few companies want to do but it's it's kind of against the macro forces of nature. >> That's and then the question is going to become you have the intelligence what do you do with it? >> Yes. >> And that's really the question all of us are going to face to a different degree.

5:34 >> And this goes back to what you said earlier is do we use it to as a weapon or do we use it as something that creates betterment of society? Do we allow it to help us find new materials, you know, new new ways to be conserving energy? you know, better ways to educate our children or or diagnose, you know, just diseases, right? And and you know, I I was just in China a couple months ago and talking to one of the the leading drug discovery companies and they said, "Yeah, we're we're using AI all the time, but we're not using the 10 trillion parameter model. we're using a 10 billion parameter model specialized for whatever disease that we're working on. And so this this is where I think a lot the other mistake that people have or misconception is that they think you know the race is to make the biggest model the most super AI model that's the one that can you know cure cancer and the reality is that the one that's going to cure cancer is going to be a 10 million or 20 billion parameter model specialized in a particular disease train on that data and we'll run on a laptop >> right or can we make use of the efficiencies that are coming out every day to make better use of what we already have and then take some of the money that we're putting into data centers and put it into, you know, better hospitals and better better roads and better power plants and all these things that we we need as a society. And that feels like it's a overconentration and over reliance in in one particular area. And if it does happen to not be realized in terms of profitability of what people are expecting, then how do you pay back these these investments?

7:11 And in fact, I think it was maybe a couple weeks ago, Wall Street Journal came out with an article that showed somewhere around $3 trillion of offthebook debts and obligations of just the top hyperscalers in America. During the the height of the subprime bubble, there was $1.6 6 trillion of subprime debt, right? I feel like we're really shooting ourselves in the foot a little bit and making the economy super fragile. This this is what scares me today >> and this is what I tried to >> talk to policy makers about to help them understand. Not to mention the potential displacement issues and you know I don't know if we completely agree on kind of how quickly that happens and where it will happen and how quickly it gets resolved and there's essentially no safety social safety net in America. You know there there's a little bit of unemployment but it runs out pretty quickly and it's not enough to to help you live. and that you know the we're already seeing that today in fact with young people based on a a Stanford study that's you know been came out last year they refreshed it and the trend continues. It's something around a 19% difference for 20 to 25 year olds in terms of their you know payroll numbers versus what they should be compared to other age groups. And so it feels like for for you know AI exposed industries young people is the first to see the potential damage percent. So whereas you know the the senior people continue to to to ramp as the original rates. So it feels like it's the >> senior people are just cutting young people like or or they're just not hiring. That's the other thing. They either don't hire or they lay off the young people because they feel like you know we don't really need them because AI can do a lot of what they used to do.

8:59 So, I'm curious if we put that data together because I've seen that study as well. I've certainly talked with a lot of folks who are Gen Z and who are really feeling the pinch. >> how do you put that next to the data we get from companies like Stripe that are showing this skyrocketing rate of business creation? Entrepreneurship is on the rise. >> Yes. >> What is what does that picture look like as a composite to you? I think if you go and look at what happened in 98 to 2000 in terms of job increases, >> right? remember when when HTML coders who had a oneweek training course could get a six-f figureure salary.

9:39 >> Oh yeah. >> Right. But you know if you look at what happened in 2001 to 2005, most of those jobs went away. >> Right. So it's not that it's not that that there isn't a need. there is a need because you know right now something only about 20% of companies have actually adopted AI and probably only 5% have done it well. >> Mhm. >> You know so so there is room for people to take AI and integrate it into society. So into into their their business workflow so a lot of them haven't been able to u to extract the value yet and so they haven't done the the the layoffs but then the companies who are helping enable it you know they're the picks and shovels guys. So of course they're the ones that are going to see the first boom is actually in fact if you look at the the stock market value versus net net payrolls overall actually the net pay payrolls have been coming down consistently since 2023.

10:35 >> So total payroll in America has been going like this. >> The stock market has been going like this. This is the first time ever where this the payroll and stock markets do not move together. >> Yeah. And I think that that's actually a bigger sign of of of a real issue is that you know and and labor participation has continued to go down. >> Yeah. Yeah. That's pre AAI that >> that's preI but this continues essentially. It's just it's just a sign of automation right automation happening across all areas whether in manufacturing or in in in in the white collar work.

11:08 >> So with that context in mind what do you tell young people when you talk with them? You're teaching students like these are genzers now in college. >> Yeah. Look, it it's tough cuz cuz honestly, even at schools like MIT and and Stanford and Udub, which are all really good schools, kids are having tough times. They're having tough times just even finding and what I generally tell them is don't focus on the job that you think you're going to get. Try to get as broad a experience set as you can. create a a Tbased experience set >> as in know a lot of things and then one thing really well where you've actually built something >> right not not where you just you know get to a certain thin level because when you've actually gone through the process of designing building deploying and then maybe even you know taking end of life something you know how things are done in the real world whether it doesn't matter what industry you're in >> you know go through that entire process and and even if you have to work for free. Go go go give them your volunteered time for the summer or whatever time after school to to learn that process of actually going through entire life cycles. and then go, you know, read history and philosophy and and psychology and sociology and management and all these other things that are needed for you to actually have a breath of understanding so that you can connect connect points together. And I think that's something that unfortunately our education system has kind of taken away in the sense of we we've been asked to specialize. And right now if you specialize then you really add very little value over what AIs can can provide. And you know even if you get an answer back from the there's no way for you to really judge it and and critique it. So you just accept it. And if that's the case why are you even there? There's no >> you're the rapper over the AI.

13:03 >> Yeah. you're the you're the rapper over it. And in fact, some people say then you become actually a negative value to the company cuz they're just paying you to then just rubber stamp something that the AI did and eventually people will figure that out >> and and you're not there anymore. >> That's right. No, that lines up a lot with what I have both seen practically in companies and also talk with young folks about. It's that you need you need the ability to both rapidly coalesce and pattern form across a really wide body of experience. So that's that wide reading you talked about, but then you also need to have a fairly deep understanding of how to build something set it live, optimize it, and then to your point, sunset it and turn over and take those learnings somewhere now.

13:52 and and the the work that we're seeing that is a trend that persists sort of regardless of how smart the models get is work in that space. It's that very highdimensional high connection kind of work. I think that the street smarts experience tends to add more value. sort of like the joke that you want to get to your second startup as fast as you can because you're going to mess up your first startup real bad and that's the learning startup >> or or your first startup go learn with somebody who've actually done it instead of making all the same mistakes yourself. That's I I prefer that because not everybody needs to be a CEO.

14:24 >> No, not it's not everybody should is qualified or should be a CEO. >> That's right. >> Yeah. >> No, it's it's I often say that like if if you aspire to that then you're Yes. There's all of these leadership qualities people talk about, but the capacity to just eat glass for a long period of time needs to be off the charts. >> Yeah. And this is I think one of the things that young people particularly in America is missing is that they've been so pampered I think by and I I do the same for my kids. I I you know I am at the same fault. But I feel like, you know, they they grew up in such a nice time, >> such a peaceful time when everything just kept growing and they had everything they wanted >> and they never suffered. You know, I come from kind of the Asian Yeah.

15:07 >> culture and and that is actually one of the sayings is it's trulu is eating bitter is a sign of of growth is that you have to learn how to eat better. >> So So I feel like kids these days it, you know, especially ones that haven't traveled internationally, they don't know how the rest of the world lives. I I no it it really rings true for me because I remember back in the 90s I was in Indonesia and Indonesia was going through that Asian economic growth miracle phase. and I saw how >> people were sacrificing to put their kids into school. People were sacrificing to get to Jakarta to get a job.

15:42 >> People were overtime the households were going from on average they don't have a TV. On average they don't have a motorcycle. On average they can't have chicken more than maybe once a week. And now all of a sudden all those things are starting to come through because the economy as a whole is starting to respond to the efforts of all of these individuals to better themselves. >> Yeah. Yeah. And you know humans are very resilient animals. We we've done amazing things if we work together. Right.

16:07 That's right. And we're not having wars that that helps. >> Yeah. >> You know so there is a peace dividend and it feels like we're we're kind of going backwards in the last few years. And I think that that sense of resilience is part of what makes me, you know, I don't know what the future holds, but it makes me hopeful because as a species, we have shown over and over again that we have an ability to look at a new challenge, look at the tools that we have and say, well, how do we respond to this differently?

16:32 >> I I on a on the long term, I'm fully in agreement with you. I feel like in the short term, humans don't change unless they see a crisis. >> Yeah. My my only question is how big of a crisis do we need for people to wake up and change their ways? >> What are some like if we go below the level of okay, let's suppose that we should wave our magic wands and now we're going to cooperate. What are some of the things that you think are really important to get agreement on internationally that go to that next second or third level in the AI space?

17:03 I mean you know I think when we talk about this this is really right now a USChina race right that's happening and what's already happening in terms of discussion is the the AI side which you know I I was lucky to have participated in part of that kind of early prep for that and >> I I think that's probably the the place to start >> and and because that is a shared risk >> and we have a shared interest you know even in in the the height of the cold war the US and the USSR got together and said Hey, you know what? Maybe we shouldn't be building that many new ballistic missiles anymore. Having 70 80,000 is probably enough to blow up the world a few dozen times.

17:41 >> Yeah. >> let's actually start to reduce that. >> Yeah. >> And you know, and that's with a weapon that was only a weapon. That a technology that was only a weapon, we have even more incentive to keep it safe so that the civilian benefits can actually then acrue to our society. So, so if we can agree on, you know, safety standards, if we can agree on communication of of protocol for when incidents happen, when bad things happen and and have that kind of, you know, red phone >> red phone hotline. I mean, no, no, it worked cuz there was a few times where it's like, was that a missile or is that a satellite coming?

18:17 >> Make a call here and that will be a big deal. It saves the world to make a call. >> It's a lot cheaper to make a call than to send a missile and then try to explain it after. >> That's right. >> Right. So I mean these are the kind of things that feels like hey you know what we should just do these things because we've learned from the past. Yeah. >> and the the real threat is really not state-to-state. I think this is something that we need to just just let people understand.

18:40 >> The reason nobody has you know used nuclear arms for 80 years is because we understand that when you do you escalate this into essentially global destruction. There there is a natural balance that has existed for 80 years and AI you're not even if you got to ASI what what are you going to do you're going to say oh I'm going to go unleash it to turn off all the power data centers and and all of the power grid and all the banking system of China then they're just going to sit there and let that happen no >> for why why would you do it >> no right and they're they're not going to do it so so is that the threat that's not the threat is bad actors >> non-state actors non-state actors There's rogue actors who already every day is planning to do things everywhere in the world because it somehow achieves whatever their purpose is whether it's for self gain or for some ideology, right? We know that exists and given what we said earlier, these models are getting small enough it runs on your laptop. You >> that's not a state power, that's an individual power.

19:42 >> If it's an individual power, then it requires communication across the board. just I think we need to do the same thing soon with this technology because the ability for small groups of people to do big amounts of harm that can destabilize their society is either here or soon will be so this is already happening but it's going to go up and that's just on cyber >> not to mention you know bio and chemical you know because you can have right I think I don't I think I sent you the paper on that I did on called bigger models are not not the biggest threats right >> yes you did Right. And you know, essentially we're showing millions of parameter chemical models can make chemical weapons in hours on a laptop.

20:23 >> That's right. >> How do you stop that? How do you And these are things that are already in public open source that people can either download or buy for nothing. >> So then the question is how do you make sure that the precursors are maintained and there's there's a good, you know, know your customer protocol so that you can find people when you see that they're doing bad things. And we've done that with you know making bombs and you know fertilizers and other things >> oxycottton yeah pharmaceuticals >> pharmaceuticals right so and and the same for for bio is that we have this you know global consortium synthesis consortium that allows DNA sequencers to look at potentially harmful virus sequences flag them and not produce them.

21:06 >> Yeah. >> Right. And and that protocol has been around but now if we say oh you know our our machines are not going to talk to your machines. So if China finds a virus pattern, they're not going to share it with America. And if America finds one, they won't share with China >> and no one wins. >> Not not only no one wins, everybody everybody loses, right? Because you know, this is when you need to talk more. And I think you don't want to create a bifurcation of systems because that just creates more dark spaces for bad actors to hide.

21:32 >> Yeah. >> And and >> they hide in the cracks. >> They Yeah. And the cracks are getting bigger every day, right? Let's start there because there there is no scenario in the world where not working together makes more sense than working together. >> That's right. >> No, I think that's really true and I think there's a ton of misunderstanding about there there's this sort of assumed narrative of conflict that is self-propelling and self-reinforcing. >> I I but I I think it's not as natural as it seems. And essentially the current playbook that the AI industry is using is the military-industrial complex playbook that has worked for the last 607 years ever since >> Eisenhower.

22:13 >> Right? Is find an enemy, >> make them big and big, big and scary. Make them big and scary and then make yourself the solution to that problem. And when you do, everybody aligns and works with you, supports you, gets rid of your your regulatory constraints and allows you to make a lot of money. And this is essentially what's happened in the last four or five years with the AI industry. If your stuff is that good, why the heck do you need, you know, >> that much lobbying?

22:44 >> That that much lobbying, right? Yeah, I mean essentially there's hundreds of millions of dollars right now that are in, you know, in the lobbying and the packs to try to get their their policies approved. Who who has a lot of lobbyists? It's like the the insurance industry and the tobacco industry and the petroleum industry and the defense industry because they have reasons to try to move you off of something that you weren't going to do.

23:06 >> Yeah. >> Yeah. That's a really interesting take. okay. Let's switch gears a little bit. You've talked a lot about the idea and we've talked about the idea that intelligence is ambient, that we think there's a lot of long-term good to society, but we've also talked about this idea that there's some short-term pain around jobs and we have challenges for individuals. >> When you look at the next 10 years or so, paint me, I guess maybe paint me two paths, right? Paint me the happy path where you're like, "Okay, we're going to get to a society that's more functioning." And then maybe paint me a darker path.

23:35 >> Yeah. which one do you want to go first? >> Either one. Your choice. >> Yeah. Let's do the dark path first because usually want to start with the pain. >> Start with the pain, end on the happy. >> I mean, if you read most of the forecasts out there, they paint the dark path. Yeah. Right. And the dark path is either you know, some some country gets close to AGI. that AGI either runs away and then you know starts wars or or or takes and turns us into batteries >> or the the countries then fight against each other and we destroy each other. or a few companies become super powerful and essentially takes over the world and you have a few private companies running the world, right? And I think probably the more likely one is that we get to there probably will be some wars because if you have large amounts of displacement, the best and fastest way to employ them is to put them in an army.

24:28 >> Put them into army that gets rid of some of them >> and that also employs them for some period of time. and it also dis it distracts people's attention away from their daily suffering and it unites them against some common enemy. I mean, this this playbook has been used a few >> 2,000 years. 2,000 years. It's not. >> So, >> but I I would like us to to not be apathetic that one of these has to happen. I I I think right now on the path that we are on, we will probably head towards that that middle path, >> right? because I I don't think that the the econ economics makes sense for a AI lab to actually be the one who captures all the value. I actually believe that if AI does what we think it will is that the the value actually distributes in non-monetary ways to society >> and then takes away the value of these giant trillion dollar investments because now I can get it for free and I can just run it on my laptop which I didn't cost me anything. that so so that actually I I think so but the war part the the the the economic collapse the the bubble collapsing I think those are highly likely now >> that may not be a bad thing because it goes back to the question you asked earlier >> which was what does it take for us to to make to change our minds and start to do the right things is that we need a crisis and I think the smallest crisis I can think of that is reversible >> and recoverable in a reasonable amount of time is a economic crisis because an economic crisis we've seen is you know some cases it takes less than a year in some cases it takes a decade >> but it's recoverable and people don't die well not from directly anyways right but it wakes people up and it changes people's minds and it it shows there are maybe other ways to to do things and I think if you know if you look at the current stock market 45% of the S&P today is AI stocks 5%.

26:30 >> All right. The the Buffett index which is percentage of stock market versus the GDP. what he recommends is 100% is a good balance where you know the the total stock market value is about the stock about the same as the GP of the country. guess how what we are on on the Buffet in about the indicator today. >> Oh, we're way over that. >> We're 240%. >> I was going to guess in the 200. So, so we we know there is a bubble. The question is when does it pop and and and the internet companies dropped like some cases Amazon dropped 90 something%.

27:04 >> Yeah. They almost went out of business. >> Yeah. Right. And Cisco went down by 86%. It they just came back to what they were in 2000. >> I know. >> So, >> 26 years later. >> 26 years later. So, so this is the issue is that I think these type of of changes in in economy and changes in people's perception of wealth will make them rethink whether or not we're doing the right thing. Then the other thing is it's that the first question you asked is what is the biggest misperception? When you start thinking about survival of yourself, you stop thinking about trying to fight somebody else. You're trying to save yourself. And I think that that will actually be the the catalyst that initiates some level of cooperation between US and China. And I think those two countries, if they put their minds to it, these two are the two most powerful, richest and technological countries in the world. And they have an ability to help write that ship, >> right? In fact, if you look at, you know, World War II, US and China were actually allies. They were >> against, you know, the Japanese. In fact, my my grandmother went to China in 1937 from from Berkeley to report on the war, right? And she was, you know, kind of I guess trying to to to connect these countries. I'm I guess I'm trying to do what she didn't complete, you know, many decades later.

28:29 If you look at what happened in 2008 with the great financial crisis, >> China kept buying US bonds. >> Yep. Even when we >> which was much needed >> which was much if they didn't it could have you know completely raised the price of of of the the debt >> and created a real solveny problem for the country. Yeah. >> Right. So they came and helped us out. I think in some ways >> because China is actually less exposed to this AI bubble because they're spending about 80 billion dollars a year. we're spending over a trillion dollars a year in in capex. So their their exposure is much less, their debt is much less. So >> I think that that will actually be a positive in terms of let's stop this race. Let's redirect our our our spending to the right places. Let's actually take care of our people versus fighting. And that will also then get us to the next thing which is maybe we don't need to be, you know, making as much data centers. all the costs actually starts to come down. The the the the memory shortage we have starts to become more u manageable >> because everybody's buying the same things at the same time, >> you know. So, so we need to get it back down to normal. We we we we get it back in balance with with the supply chain with nature. And then we start to think about, okay, how can we now that we have all this extra capacity of making chips, who else can we sell to? And it's actually the global south.

29:55 >> Yeah. And so now we do what we did in 1946, which was the Marshall Plan. >> The Marshall Plan allow it was I think $18 billion over four years, rebuilt a lot of Europe and and created essentially a you know 70 80year marketplace for American goods. >> Yeah. >> Right. And I think that's what we need to do. And that will then allow all this extra capacity that we've built to then have a place to go. Allow those countries to to to catch up from a technology-wise so they're not left behind. If they grow, they then become customers for American technology, American devices and chips. and same for China. So they're they're they're both aligned. They want to be able to do this, >> you know, and and then >> we're helping uplift the global south. we we're helping ourselves. We we create a lot more peace dividend because now we're not spending as much on fighting because we we're saying, "Hey, maybe we don't need to spend $1 and a half trillion dollars on weapons this year, >> right? Because who are who are you going to fight against when everybody's fighting for survival?

30:59 >> Making more weapons doesn't really help you. >> You know, if you look at >> humans are are social animals." Yeah. You know, we we we have kind of disconnected from ourselves over the last few decades and also specifically since 2020 with COVID where we lock ourselves up and we don't talk to our neighbors, you know, and and even with our kids. Our kids, you know, lock themselves in the room and go online. They don't talk to their friends. They don't talk to their parents and they come out and get food once in a while, right? This is not a a healthy way for us to live. If we can start to leverage the the laborsaving benefits of productivity gains from AI, allow people to spend more time at home instead of, you know, time trying to compete to to to win things, >> we then have more time to actually spend face to face, >> whether with our neighbors, with our children, with our families, with our churches, whatever, and and become more human again. And I think AI will actually allow us to be more human.

31:59 that that's kind of the the final that's the happy path. That's the that's the the the happy path. >> I think one of the things that has really stood out to me is that this is a pivotal moment in history. And yes, you know, there are people who have unusual influence. There are leaders of companies, they're leaders of governments, >> but we collectively also shape our future. >> And I think if you look at it and you say, okay, there's there's a lot of investment in data centers. Maybe we're too heavy there.

32:25 What if, especially as we've been talking about these quantized models, these models coming down, >> what if the opportunity is really in something that's closer to the mini duck that hugging face released, like these little small robotic experiences, these places where compute is just available in the home and adds value in discrete ways. And sure, are there businesses there? Absolutely. But also, there's just a lot of value that will probably be hard to quantify from a GDP perspective, but that we will feel in our homes and communities.

32:56 >> Oh, absolutely. I think robotics is actually going to be increasingly important and you can see over the last few years that the progress has happened and and actually from a a US China perspective, I think actually China's way ahead right now on on manu anything manufacturing. Yeah. >> Because they had the whole supply chain. They have all of the talent there. I went to the unit tree factory just two months ago and it was a bunch of little ladies wrapping coils around magnets and they're still doing that. I mean all manual >> all manual but they did say hey you know we're working on these machines they were showing me these automated machines but you know it just the the pace of change in in that space is going to be just like the the software side has been the last few years when we look at the next few years.

33:36 >> So so so more and more devices will be coming into our homes. you know, I think starting with with little kind of fun things like what you're describing. I actually advise one of these companies that does robotics training and, >> you know, training for something as simple as folding your sheets >> takes a while. >> It's it's difficult because sheets are, you know, it's different in every home. >> Every bed's different, every cloth is different, every color is different, the lighting is different versus, you know, to make somebody, you know, have a fight on a flat mat with a a a a a standardized shape. That's actually pretty easy for for AI and robots to do.

34:10 >> Yeah. >> So, >> yeah, I think that's a really good point. I think there's a lot of you reality is surprisingly detailed. There's a lot of detail that robotics has to master to really get into the home. but we're on a path there. >> Yeah. But robotics in in factories will just it's going to happen. It's going to happen faster. And it doesn't have to be a humanoid. >> No, that that that was >> that's an assumption everyone makes. I don't know why.

34:33 >> No. And in fact, I when I was talking to the the Yinutri CEO, he was saying that they're selling more halfbody humanoids than they are the full body humanoids. you know, because it's just the batteries last longer. They're more stable. They don't fall over. They there just a lot of benefits of not having legs. and you can if you're working in in a factory, it's it's flat. You don't need to walk. Walking is actually >> you just stay there and you do your thing.

34:57 >> Yeah. It's it's an inefficient thing. And you know, you're spending all your energy keeping stable so you don't fall over. And these things are still relatively fragile. >> that's right. >> Yeah. >> Yeah. You know, one of the things I like to do when I'm tracking technical changes, I look at the rate at which an idea goes from someone made something on X to I see an ad for it in Tik Tok. >> Mhm. >> and now it's a product. Yeah.

35:23 >> And that has gotten shorter and shorter and shorter. And so like I was looking at an exop open-source project two months ago and the idea was you take this little screen, you stick it up against your wall and if you're an airplane nerd, you can see the airplanes that are flying overhead because it uses flight data and it like shows you the airplanes. Very fun little project, very open source. Not even 60 days later, exactly that product on Tik Tok. Yeah.

35:47 >> For the airplane nerd in your life. >> Yeah. >> I mean this that's sent in speed, right? Essentially anything you can think of. You've got an idea. You you go find a ODM in in Senzen and within weeks you have a working demo or working prototype and within another month or two you could actually get that on assembly line. >> Yeah. >> So in terms of of of hardware prototyping and you know time to market it's it's crazy what's possible.

36:15 >> Yeah. >> No, it really is. And I saw it firsthand. I I don't know that we've talked about my background but I used to do hardware manufacturing. but I was in the coffee space. >> Okay. >> So, I invented a sort of stainless steel filter contraption for coffee makers. >> I did my prototyping with jewelry welders. I still have scars on my hands from all of that. >> and then we tried to make it in the States and we ended up finding a factory in Pennsylvania. It was a ton of work this and that.

36:42 >> And I saw firsthand how fast once we made it, >> it just spread as an idea. Like ideas want to be free. like all of a sudden like there was this just this flood of very similar looking devices and I could see them getting better at welding because I could like buy the product and oh you're getting better you're getting better you're getting better and it was like >> technical innovation is something that >> ultimately I it was discouraging for me as an entrepreneur at the time but ultimately it's good for everybody.

37:11 >> Yeah. I mean that that's the biggest winner I think of of the this AI race is that the the consumer the end user the businesses that will utilize it and and one thing you said earlier about it doesn't show in the GDP. >> Yeah. >> And I think that that's something that we need to think about is to to redefine value >> because today everything is about how much you produce and what you can sell it for.

37:34 >> And >> in a lot of ways technology >> deflates the price of goods. Mhm. >> Right. I think if you there was a chart that went you know kind of viral the last few years which was you know all the services things kept going up significantly education and and housing and you know your TV your computer your phone it's like this diverging curve that's happening and AI makes essentially anything automatable. Yeah. whether it's it's cognitive services, white collar services >> or physical goods because these things will then be tied to machines to automate design, automate testing, automate manufacturing. So all of those prices will come down and if you look at raw GDP, >> you may actually have a reduction in price because you're going to have, you know, companies who can make what used to cost thousand dollars into $100 and $100 would be tens of dollars, >> right? and services. You know, we don't even need to talk about because I have friends who are in McKenzie and the various banks and they're saying we used to, you know, do a a perspectives for an IPO would take us weeks and teams of tens of people. Now we can do it over a weekend with a couple people, right? So, and if you're and McKenzie is the same, right? Millions of dollars per per >> and it affects your pricing power if >> Yeah. And how do you price for that?

38:51 Yeah. >> Right. And so, so that that's something that I think that the GDP won't account for, but it's actually extra value just like, you know, now everybody can have a high quality lawyer at their fingertip. I I >> How do you measure the value? >> Yeah. I mean, I used to not want to call my lawyer because I know every time I called them, it would be, you know, at least a 15 minutes times $1,000. Y >> just to have a a a fivem minute call.

39:14 So, and if it's a if it's a contract, it's it'll be hundreds, you know, hours and thousands of dollars for something that now you just send it to the AI and say, "Look at this as my lawyer. What am I missing? What what requirements do what changes should I be asking for?" >> Right? That's that's value, but it is not GDP value. >> Yeah. I it's really hard to measure the impact of a general purpose technology.

39:37 It just sort of permeates like >> we we're we're now all have a team of experts at our fingertips >> for experts for anything, right? sports injury, medicine, law, like you name it. >> Exactly. I mean, and how much and these that was not even available to the richest people in the world. No, >> just a few years ago. >> That's right. And now we just have it and don't even think about it. And I think that's, you know, that's what makes me really curious. Like I think you're absolutely right that we have this opportunity for in real life connection coming up that we haven't had but in a while. Yeah.

40:08 >> And that we really need to take advantage of. And when I think about that and I put that together with the with where sort of AI is going, miniaturaturization of AI, it just feels like we're headed more and more toward a world where we'll have the technology. The technology will be there when we want it. >> But we will have the chance to build better connections with each other. >> Because humans remain interested in each other. We remain curious about each other. That's not going to go away. And you know, you know, last week I I spent a whole week in the desert in the play and that was my biggest kind of conclusion >> was that humans are social animals. When you go, you know, to Burning Man, you spend a week in the desert and >> everything you you you bring in is all you have.

40:51 >> Yeah. >> You start to realize that first of all, you don't need a lot. You just need some water, some food, and some companionship. And you h you you can be very happy >> and everybody's there working. Nobody's being paid to do anything. But everybody's working so hard to to cook for each other, to take care of each other, to to build amazing art, to play music for each other. >> And that it made you so happy even though there was no exchange of money.

41:17 >> In fact, there was a reverse status, right? If you were a billionaire that flew in on a jet and people made your tent for you or or or you had this, you know, service staff, people look down on you. >> You're lower status. >> Yeah. No, they're like, "Dude, that that guy's not a burner." >> Yeah. Right. And so I I feel like we're we're going to need new status instruments going forward. Right now in the what they call you know the burners call the default world which is what we live right now.

41:45 >> It's all about money and power. >> Yeah. >> And on the playa it's it's all about creativity, >> service and community. >> And those are things that you cannot monopolize. Right. So it actually creates a lot more equality and that equity allows people to to bond more >> and and that that was something that I in fact I'm I'm doing a research paper >> as for for Stanford specifically on this issue and looking at does the gifting economy and the the principles of operation of that culture is that a precursor to a post scarcity post labor postetary society because in in some ways You go in there, you spend a whole year. You know, some people save up for a whole year so they can spend that week in a place where there's no money.

42:33 >> But if if AI and robots do all the labor and essentially do that 51 weeks a year, can we live our life not necessarily in the desert, but live our life in in the the the the world that we are in, but with a lot less of that financial pressure and a lot more focus on community and creativity and and and and service. I think that's part of what has made the imagined future of Star Trek so enduringly interesting.

42:59 >> Yes. >> Like Pequard doesn't think about getting more money. >> Yeah. That was his thinks about exploring the universe. >> Well, he also says we work for the betterment of our species. >> That's right. Right. >> And that's what motivates him and motivates the whole team. >> Yeah. And so I I and Oh, actually a little trivia on Star Trek. Do you know what happens in 2026 in Star Trek? >> No, I don't. What happens?

43:19 >> World War II. >> Oh, no. No, but but World War II was also what then you got people to wake up, got people to come together. It took them a few decades to to recover and then they created a warp drive. And then who came? >> The Vulcans came. Vulcans, advanced alien species, >> brought advanced technologies, gave us the resources to be abundant and stopped fighting. Yeah. >> And then we started to, you know, get together and started to discover the universe or the galaxy at least. What does that sound like?

43:52 >> Sounds a lot like the world we're living in. >> Sounds like the AI that we're creating. Essentially, we don't need to depend on the kindness of an alien species. We are creating our own alien species. >> We are >> right. And if we can do >> with AI what that the federation did or at least the humans before the federation did with AI in terms of using it for >> creating shared common good. Mhm. >> We actually can create a pseudo proto utopian world where people care a lot more about service to each other and betterment of of humanity than they do about enriching themselves.

44:28 >> Well, and to bring this all the way back around to Gen Z and the young folks we talked about earlier. That motivation is something I hear proactively from them a ton. Like that's what they're interested in. >> So, so this actually I have a theory for this. the chimps and the and the bonobos separated from each other and north of the conger the the chimps lived and it was a relatively kind of seasonal and aerid space. So sometimes there was a lot of food, sometimes there wasn't. And so being strong and and and you know alpha male driven >> might mix, right?

45:02 >> It gives you access to resources so you live better. South of the Congo River is where the Bonobos lived >> and there was always food. It was like a very >> resource abundant >> resource abundant world. And so in that world, actually having the cohesiveness of a matriarchal, female-led nonviolent you know, actually sexdriven conflict resolution model actually works better because if you have everything, why are we fighting? Let's just let's just get along. It is the one side is the scarcity driven reaction to their environment and the other one is the abundance driven reaction. And remember what we talked earlier about about young people >> is that they lived in such a sheltered life that they've always had abundance.

45:45 >> Yeah. >> And so they don't feel that the the hunger of competition and fighting and they need to fight to survive. Whereas you know like I I I was born on a re-education farm during the cultural revolution. We we were given little tickets of you this is how many ounces of sugar you have for this week for your family and >> good luck. That's all you got. >> Yes. And so you always felt scarcity, right? And and you know, so so but that's where a lot of kind of our generation maybe even before they came from a world where where you had to fight and compete for your for your what you had. Whereas that generation now have they're the the bonobos of the world and and I'm I'm hoping that we are now going to create a generation after them the the al the gen alphas or whatever will be even more and more benovo more and more peaceloving >> and having more ability to to to find ways to cooperate and collaborate versus conflict. You know, I I love that focus because that is one of the things that has emerged to me that I have sort of reflected back at talking with my community that I've sort of built on YouTube and other places, Substack, over the last year or two. The thing that has stood out over and over again, seeing like the hundreds and thousands of stories of people who have changed their lives with AI, none of them are doing so at the expense of one another.

47:03 >> The future is an abundant future. >> Yes. And so if we start to sort of buy that and think about that seriously, I think it changes absolutely everything. >> Absolutely. So this this is why I gave you that pin, the abundant pin. So because I want you to to I I know you already have that mindset, but I I think the the world needs to think more about this to realize we in fact we already live in an abundant world, particularly in America.

47:28 >> Astonishing abundance. >> Yes. >> But but but it's just not evenly distributed. And most people don't realize what they already have. And this is why going to the desert helps you realize how abundant a life we already have. >> The abundance is already here. It's just not evenly distributed. >> We're we're Gibson again. >> There you go. There you go. well, thank you. Thank you for coming and chatting. >> No, no, this this is we need to do it again sometime. This this is fun. I I I think we have a lot in common.

47:56 >> Yeah. >> Yeah. And it's just good to get that perspective. I think one of the things that I've been looking forward to about this conversation is I feel like because you have that cross-pacific perspective, it's a needed voice in a moment when most of the voices are stuck on one coast or another. >> Yeah. Just more good can come from from peace than from war. So, very much so. All right. Well, thank you, Alvin. Thank you. Hey, thanks, Nate. Yeah.