The grid(lock) slowing AI down

0:00All right, Reid, we never do endorsements, but for those of you who are watching on YouTube, you may notice that I'm wearing a Patagonia and there's a picture of a mountain behind me, which can only mean one thing, that I'm at the Grand Canyon. So I'm just going to give a shout out to anyone. A lot of people have heard of the Grand Canyon, but it's really amazing. And you should go and you should hike down it. And if anyone has kids, make their kids go on the hike. So that is my endorsement for the day before we get into lots of AI news. I think an endorsement of a national treasure is a good way to begin.

0:34People have heard of it. All right. So recently, Samsung's co-CEO, TM Rowe, announced at CES 2026 that the company wants Google's Gemini AI running on 800 million devices by the end of this year, which would be double the 400 million that it reached in 2025. Samsung is adding these features to TVs, home appliances. I feel like you do get some consumers that are a little annoyed by that, saying we don't want smart TVs or we don't want smart fridges. So it'll be interesting to see what sort of the integration of AI into those smart appliances also means. But also consumer awareness of Samsung's Galaxy AI brand has skyrocketed from 30 to 80 percent in just one year.

1:14And consumers are using AI a ton on their phones to search for generative AI photo editing, real-time translation. Actually, just yesterday, my husband gave me a photo of the Grand Canyon. I was like, that looks amazing. He's like, oh, yeah, AI edited out all the people. So people are using this in real time as it becomes accessible on their devices. Last week, OpenAI also became the first major AI company to launch a dedicated voice-based conversational app on Apple CarPlay, Evermix. And they're rolling out ChatGPT as a hands-free voice assistant for drivers. So CarPlay 2.0 supports ChatGPT, Google Gemini, and Claude.

1:51it is very clear that AI is coming to hardware. So my question for you is how important is this AI integration at the hardware layer? And does that mean that whoever owns the hardware actually ends up owning the majority of the value the AI creates as opposed to the software layer? Well, I'll start with the simple, which is I don't think the hardware ownership will dictate the greatest value in the AI layer. It doesn't mean that there isn't a significant impact from it because when people buy a piece of hardware, that hardware is their access for that, whether it's a car for the inside of the kind of car operating or AV, whether it's a phone, whether it's a TV, all of these things, that's the AI that they then get with that device.

2:49And people, these tend to be big purchases. And the TV tends to be the central thing for the family. The car or two is the transportation, et cetera. So there is a significant kind of exposure, value creation, value capture, generation moment there. And so I think it is important for that. On the other hand, when you think about, for example, part of what I think kind of AI should be looked at is, what's the number of minutes, hours of AI being used to create value? And, you know, to some degree, when it's creating value for me, is that value kind of more substantive? And I think that's one of the reasons why, you know, value that's, you know, for example, comes through your chat GBT app on your phone or, you know, through your, you know, kind of co-pilot, you know, Claude, et cetera, app on your computer.

3:56those things, I think, hours and hours and hours of interaction and things that you're creating. And so they're on the more general platforms for this. And what's more, because the value of that, and it's one of the reasons why, of course, Samsung is using Gemini and why OpenAI is, you know, integrated, you know, along with, you know, substantive ones like Gemini and Claude into the hands-free voice assistant for CarPlay, the iteration of these things into becoming more value comes out of the hours of interaction versus the driver of it's a commodity that I just happen to slot into a hardware.

4:37And so that's the reason why it's kind of like, it's not like, well, it's the hardware runaway story. Now, that being said, obviously, it's part of what is becoming a much more mainstream adoption of when it's just there. Now, I think people are still a little bit slow to what are they doing when they're talking to their TV, they're familiar with their remote, et cetera. The AI is just, okay, play Netflix. Find Wednesday on Netflix. It's like, okay, that's fine. And by the way, much better than the kind of remote experience, And, you know, especially when you get to like Apple TV remote, which is like this, you know, simple and simply useless, you know, kind of interface point.

5:25But on the other hand, the thing that makes, you know, AI valuable is not its translation moments of, oh, I can now hear you say Netflix. And, you know, of course, it's better than Siri and it's better than Alexa and all that. But it's like, that's not the thing. It's actually kind of a much more substantive set of things that is in what you're creating and what you're doing. And the iterative cycle of that is within the frontier models themselves. And that will drive towards, you know, kind of upgradable, updatable, flexible hardware patterns, because there simply will be a huge amount of demand for, I want the one that really works here.

6:06And even if that demand is slow, because I don't realize that I can say, hey, you know, Netflix, I like these 15 of these seven shows recently. What are another five shows that you'd show me that would be interesting? And that's obviously when it begins to get, you know, kind of the beginning of much more interesting. And, you know, even when you're integrated into, you know, hundreds of millions of Samsung TVs, that's still something that we're building towards. We're enabling the user adoption of, even if the functionality is all essentially there right now. Right. We're such at the beginning of this.

6:44And so as you think, like you've spent your career thinking around network effects, especially from a software perspective. But from a hardware perspective, does this mean that like the model that is on 800 million devices, like of course your phone, you can use whatever app you want. But again, there is probably going to be some preferential models that people use. There's going to be deals that are struck between different companies. Does that mean that it's sort of game over for whatever model is on those 800 million devices because people will be locked in? You know, at this point, there's many more devices than there are people in the world, in a sense.

7:16And just because you have one device, like a Samsung device, doesn't mean you don't have other devices. And this gets, you know, there's different ways of kind of understanding network effects. And just because you're on a network doesn't mean you have a network effect. There's strong and weak network effects. Strong network effects are because I'm on this network, I'm not on other networks. Weak network effects are I'm on this network and I can adopt other networks like instant messengers. People might be using Signal, but also WhatsApp and also iMessage and Telegram, et cetera, and using the whole set.

7:50And so those are weak network effects because I have a reason to stay on it when I do it, but my ability to adopt new networks is just the cost of that. And then there's like you're on a network and being on a network doesn't necessarily matter or anything. And that's part of the reason my answer to the earlier one was, look, there's more subtle networks, like what is the reinforcement of how is the model getting better, which gets driven through, you know, depth and engagement of use, which in the cases of TVs is likely to be low for an overtime, even if you're on hundreds of millions of TVs or devices, you know, in this case.

8:30speed. No, I think it will be more on phones. And so the Samsung phones, which, you know, I have a couple of the, you know, the very nice Samsung phones, those will create, there's a form of network effect there in terms of the learning and adoption. Like it's one of the things that being in the search engine business is knowing what the query stream is, is a way of doing it. The same thing in terms of like, how do you, how do you make an AI thing more magical? Also, how's it learning? I mean, this is part of how, you know, the kind of question of figuring out good sets of queries and good sets of answers is part of how AIs are trained, it's part of how search engines are improved, you know, et cetera.

9:11And so I think that engagement pattern really matters. Now, that being said, none of this is to underplay that it's a distinct advantage to be on a number of things, especially if like it's kind of the equivalent of, hey, I'm using this thing and I see how great it is. And that's part of why everyone who actually uses other models other than Grok realizes how bad Grok is because Grok trained to the benchmarks, but is actually just not as useful on almost any vector other than maybe creation of questionable pornography, you know, than, than any of the, the primary models. And, and so you get exposure to that.

10:02So say, for example, you're, you're getting exposure to chat GPT through CarPlay and you go, Ooh, this is really good. And that's useful to have that, that exposition. And, and, and, you know, then, then, you know, if someone is trying to say, Hey, I use this other model and said, and it's like, I was like, ah, I want to stay with this. plus I'll get familiar with it a little bit in various ways. And then of course, the subtle thing that might begin to get, it's not a network effect, but a sticky effect is like, well, it starts having memory and it remembers you. So like I've been driving for two years with CarPlay and it knows what kinds of things I like.

10:40And it knows that when I say play the police, it isn't look out for the police around me. It's take this band that many young people don't know what it is and kind of play it. It knows your favorite smoothie store. It knows what songs you like. It knows that in the evening you want to pick me up. And so, yeah, that's super valuable. Yeah. So those things, I think, kind of contribute, but they're kind of not exactly network effects. Moving to the question that is on a lot of people's minds, everyone is talking about data centers. Alphabet, Amazon, Meta, and Microsoft are expected to spend more than$650 billion in 2026, just this year alone, to expand AI capacity.

11:18And analysts estimate, though, that somewhere between 30 % and 50 % of these AI data centers that are planned for deployment in the U.S. will be delayed or canceled. And the reason is electrical components. That is the bottleneck. Batteries, transformers, and circuit breakers, which make up less than 10 % of the cost to build a data center, but without which it's impossible to build one at all. And so lead times for high-power transformers used to be around 24 to 30 months before 2020. But now that timeline has stretched out, in some cases, to five years. So these construction projects, even if we get them on the ground right now, they won't be able to help us for years to come.

12:00And so across 140 construction projects, data centers representing at least 16 gigawatts of capacity, they're slated to come online, but only around five gigawatts are currently under construction. And at the same token, U.S. utilities imported more than 8 ,000 high-power transformers from China in 2025. And that's up from fewer than 1 ,500 in 2022. So needless to say, we are importing some of the most critical components of our data center capacity from China. And obviously, last week, we talked about the geopolitics of it all. What does it mean for China to be supplying some of the most important things for our AI?

12:40So if we're spending$650 billion to win the future of AI, but it is fundamentally dependent on a geopolitical rival, what does that say for what we're doing? And is this a problem as we try to stay on top of AI in a geopolitical sense? There's various ways in which we have dependencies in the AI value chain, which is one of the reasons why I think, you know, kind of call it a national policy of being less terrifable or other kinds of, you know, kind of puns on terrible. and it's not just the transformers. It's kind of chip supply, which obviously is hugely TSMC, Taiwan dependent. It's adoption, which has other dependencies.

13:31Like if you go all the way to the, you know, kind of construction of the components of which, you know, like the transformers are a kind of surprise thing to kind of chips. And then people frequently underwrite the networking infrastructure. You know, then you get kind of like data centers, There's the composition of data centers. Then you've got the kind of build out of the compute infrastructure. Then you've got the models and the train and engagement. So you've got this whole thing all the way to people actually using it. So I think there's a lot of different dependencies. And a dependency on a geopolitical rival is certainly worth paying attention to.

14:08But it's a little bit of the reason why, for example, NVIDIA kind of wants to have its cake and eat it too, e.g. sell a huge amount of chips at very high margins. but also be the builder and provider of, you know, AI models and so forth. And so it's kind of doing both. But their challenge is, you know, since they've got massive demand for the chips, all the ones they hold on to to do any kind of internal project, then, you know, hit their bottom line in terms of undercutting current sales, you know, kind of booked in margin. Well, what that means, and it's one of the reasons why, like, NVIDIA has been in a strong position because everyone says, well, look, the thing that most matters is that I can continue to build out AI in strong ways.

14:49So if you get China, you go, well, I suspect the price of high-powered transformers are going to go up, but then they're going to be selling them broadly and probably to whoever meets the price, which it can include the US, you know, kind of as a way of doing this. And this is actually one of the orientations by which the investment of capital is one of the other things that keeps the US in a substantive lead. Because if you think about, you go to the$650 billion of investment in a set of things which have partial demonstrated revenue, but a whole bunch of uncertainties, you go, well, which countries in the world can do that?

15:31And the answer is one, right? The US. None of the other countries, including China. I mean, the government has that potential capability, but the companies don't operate that way. They have much lower revenue streams. They have much lower capability to invest in this. It's one of the reasons why a lot of the AI innovations that are coming out of China relative to software tend to be efficiency and tend to be using distillation of various models as a way of doing it because it's like, actually, we have a massive amount of talent, we have a massive amount of data, and we have some compute, but we also have a lot less pure capital to just burn with an uncertain turn into revenue.

16:09So I think that the, you know, I would say it's worth paying attention to. It could turn into a sudden, you know, terrible vulnerability. It's one of the things that is, of the many kind of nuttinesses around, you know, piss off our friends and allies as much as we possibly can, you know, is kind of the strangeness of this. I think it's one factor among many, not a five alarm fire. No, fair enough. Something certainly that we need to watch. And I think another thing when it comes to AI, people are talking about trust. AI has come along at a time when trust in government, in institutions, in companies seems to be at an all-time low.

16:57And so we've been talking about AI at the national level. And I want to take a moment to talk about our government institutions. Longtime listeners will know that you launched a challenge last year with Lever for Change called the Trust in American Institutions Challenge. It was a$10 million open call, and we were asking organizations to submit and tell us what they were doing to rebuild trust in institutions in the United States, whether this is the criminal justice system, the education system, our national media, our local media, all of these things are critically important. And we're not going to have a functioning society if our citizenry doesn't trust these institutions, but also these institutions aren't responsible back to citizens.

17:42And so months ago, we announced the five finalists for the Trust in American Institutions Challenge, and it was a$10 million, again, open call for these bold ideas to rebuild and scale public trust. And the five finalists were the American Journalism Project, CalMatters, Recidiviz, Results for America, and Transcend. The great news is that yesterday, Lever for Change announced a winner, CalMatters. CalMatters is a nonprofit, nonpartisan news organization, and it's focused on transparency in government. And right now, they're focused on California politics and public policy with an eye towards expansion all around the United States.

18:21So I loved hearing about what CalMatters did and especially what they are planning to do with the integration of AI. I think when we look at government right now, AI is actually super, AI is something that can really help it analyze the enormous troves of data that we have. We have building codes with 10 ,000 pages of things that people need to do. We have congressional votes over years and years and years. Everything we have around government, around data, like AI can be enormous force multiplier in terms of understanding what's really going on and actually providing solutions for our citizens.

19:03And so, Reid, I would ask you, you were a part of this process. You were really excited about all of the organizations that submitted and the five finalists. What excites you about CalMatters and as well as the role of sort of this challenge in helping rebuild and scale public trust, especially with AI? Starting from the very top, one of the things that's interesting about this is I've been helping the Lever for Change from its very beginning and spin out of MacArthur because they have a really interesting model of using networks to create highly validated and leveraged philanthropic dollars. And so, you know, having, you know, their 100 and Change, which is the thing they launched, and then creating a new platform and spinning out, and Cecilia Conrad doing an amazing job of this and, you know, having some folks doing that.

19:51And so, as you know, we've been talking to them for years about what kinds of projects to do. And the reason why we started with, you know, kind of trust in institutions is because, you know, the thing that probably is most scary and disheartening about our current moment in many Western democracies and maybe other places, is a tendency to say, burn all the institutions down. They're not working for me, so burn them down. And when you look at history, the burn them down leads to just terrible outcomes, whether it's the French Revolution, whether it's the Cultural Revolution in China, like each of these things, and there's just dozens and dozens of them lead to enormous suffering, setbacks in society, et cetera, because the intelligent thing is to say, look, we really depend on institutions functioning to have society function.

20:44And by the way, we need informational institutions to function, to function as a democracy. And they've been tended to be highly politicized and say, well, everything is political. Now, my personal point of view is something like The Economist that says, hey, this is our, we have an informed point of view. Here are some of our principles. And let us tell you what on the thing on the informed point of view, as opposed to slogans of fair and balanced, which means slanderous and unbalanced, kind of equivalent. And so it's like that trust in these kind of information things really matters. And so that's why we said this is what we will do in terms of trust and information.

21:29And to be clear, we actually wasn't focused on only journalism. Like it was like libraries and a bunch of other things because, you know, rebuilding institutions is the thing that we most need in society. Now, what works really well in the lever for change is that they go out and get a whole bunch of different institutions aware, you know, nonprofits and organizations aware of the challenge, you know, even inventive individuals. People can submit widely divergent proposals, something that's far beyond the vast majority of philanthropists, philanthropists capabilities, including my own. And then they bring in networks of experts and networks of people through it in order to evaluate and say, you know, what's the probability of this?

22:14Now, one of my delights at kind of, you know, kind of watching at arm's length from all this, because part of it is to have it as an independently driven organization and doing all that, was that it was all of the finalists were amazing. And CalMatters happens to be one of the finalists that I'd actually already been a donor to over time. And so when I came back with, oh, this is what we think is the top pick, was like, well, that was kind of cool because I had paid attention to them. Because I always tend to have this point of view of having some responsibility to the communities that have enabled me, the communities that I participated in.

22:59So, for example, not just Silicon Valley with Second Art of a Food Bank, but also California. Cal Matters was part of that because, you know, one of my big frustrations is people go build important things in California and they go, wow, I've got this frustration in California. And by the way, you might have a very legitimate frustration in California. There's all kinds of nuttiness with a prop tax, you know, proposition, wealth tax and everything else that's kind of going on. and that's genuine, but like this is also the place that enabled you to do these amazingly scale magical things. And so you have, you should also have some sense of participation, give back, loyalty, reinvesting the kind of the seed corn that allowed the flourishing of the own crops that you made and so forth.

23:46And so the fact that CalMatters was part of this was awesome. And of course, part of the thing that's really important to having a functioning democracy is to have access to good information, like good information about how well is the legislator working? What are the policies that are working? What are the things that really matter for citizens? Is the budget stuff actually working out? Is this lying or truth? You know, has there been, you know, the results that are claimed? Is it working or not for the people the right way? And CalMatters basically says, we're going to do it as kind of the equivalent of a, like, our only real point of view is understanding, you know, what are the things that actually are working and not working programs?

24:36What are, you know, kind of like, you know, when various politicians are making claims about things, which of those things are accurate, when propositions are making claims of things, which of those things are accurate, and to facilitate so that people say, okay, this is a sort of thing where you're just trying to make sure I have the information as a California citizen, as a California resident, to inform what I'm doing. And of course, try to create that as a basis to be an incentive system for politicians to operate the right way, for journalists to be able to understand truth and write stories that help with that the right way, that then kind of citizens can go, okay, that's a perspective that is trustworthy, not because there aren't just as anything in life sometimes makes, because they did a lot of real work to try to make it accurate to what they're representing.

25:31And so it's a delight that they're the selected honoree. And, you know, I couldn't be more happy for them. And all the finalists were amazing. Awesome. Reid, thank you so much. I will give one final pitch to our listeners. If you are looking for a not-for-profit to get involved in, to donate to, these organizations have been vetted, as Reid said, by, we brought in, you know, hundreds of experts to look at all these organizations. So once again, if you are excited to give back, if you care about trust in American institutions, the American Journalism Project, CalMatters, Recidiviz, Results for America, and Transcend are all incredible, amazing organizations that are doing great work.

26:10Reid, thank you so much for being here. A pleasure. Possible is produced by Pallet Media. It's hosted by Ari Finger and me, Reid Hoffman. Our showrunner is Sean Young. Possible is produced by Tanasi Delos, Katie Sanders, Spencer Strasmoor, Imozu, Trent Barbosa, and Tafadzwa Niemorundwe. Special thanks to Surya Yalamanchili, Sayida Sapieva, Ian Alice, Greg Beato, Parth Patil, and Ben Rallis.