WIRED Roundup: The Five Tech and Politics Trends That Shaped 2025

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0:47Welcome to Wired's Uncanny Valley. I'm Zoe Schiffer, Wired's Director of Business and Industry. Today on the show, we're wrapping up our news episode series by reflecting on the trends and stories that shaped 2025. And who better to do that with than Brian Barrett, our executive editor who works tirelessly in the shadows. Zoe, thank you. Thank you for having me. Happy to emerge from my shadowy lair. From the dark, dark cave. Thank you. What a year it's been, and I'm so excited for it to be almost over. Oh my gosh, me too. Okay, because it's been quite a year news-wise, safe to say, especially in tech and politics.

1:31Honestly, it was a little bit tricky to pick which trends we should discuss today, but we settled on five stories that kind of encapsulate this year pretty well and I think give us clues as to what is going to be unfolding in 2026. The first one that I want to talk about is dear to my heart, and it's about AI data centers. So we all know that the investment, the amount of money being spent on data centers is absolutely staggering, with companies like Meta, Google, and Microsoft tripling down on AI infrastructure spending this year. But it's not just about the money that's being spent. It's also about how that money is being invested and the domino effect that it's already having on the rest of the tech industry.

2:13and honestly, our entire economy. I'm glad you're talking about data centers because they sound boring. They should be boring. In a just world, they would be. But they're at the center of so much that is going on right now. They are sort of single-handedly propping up the economy in a lot of ways. They are responsible for so much environmental upsetment. They are driving up energy prices for people. And they are powering AI experiences that are sometimes really great and sometimes really not, depending on who's using them and how. If you had said five years ago that the biggest story in tech would be data centers, I don't think anybody would have believed it.

2:52I mean, if you had told me that we were going to have multiple reporters whose, like, beat was directly related to data centers, I would have said, absolutely boring, skip, next. But, you know, we're always looking for points of agreement with Peter Thiel, and I think this is one of them. Peter Thiel says, he says that the U.S. really doesn't have another big moonshot project. We don't have a Manhattan project right now. All we have is artificial intelligence. And I think when he's talking about this, he's saying it as like a bad thing. Like we should have other big initiatives that we're doing.

3:24But I think even more specifically within AI, it's like it's AI data centers. And we're hearing a lot of people in this industry, Sam Altman, other kind of executives, talk about the fact that it really looks like there's an AI bubble that is forming and expanding possibly. And the data centers are right at the center of that. I think that a lot of these financial deals are being set up through special purpose vehicles. So like the money that is being spent isn't directly on these companies' balance sheets. It's also true that 60 % of the cost of building a data center is basically just on the GPUs, and you need to replace those GPUs every three years.

4:09So I think a lot of people are looking at this and getting pretty worried, saying the math doesn't look like it's going to work out. Yeah, so Michael Burry, who made a name for himself around the housing crisis, right? He was the center of the big short. he has made a decently big bet exactly that, that the accounting here is kind of funky, that it is a bubble, as you said, and it's going to burst. Now, he's made bets before that have not panned out. I was going to say. He is not infallible, but his argument is indicative of the argument that you see, and he is someone who has, like, caught a bubble before.

4:42Is 2026, though, the year that this kind of comes to a head? Even Sam Altman says, like, it's probably a bubble. There's going to be winners and losers. He's obviously betting that he's going to be to the AI bubble what Google was to the internet bubble. It made it through. It survived. It grew. It dominated the market for years. Do you think that's where it had in 26? Or do we have a little bit more time than that? I actually think we have another good year. Good, depending on who you are in this space. But I would guess, and this is based mostly on Vibes, so take it with a giant grain of salt, but that we have until like 2027 until this really starts to come to a head.

5:18And one thing that I'm going to be looking at specifically is, you know, I've visited some of these data centers. I've talked to politicians who are really supportive of having data centers in their city. And right now, it looks like there's not a lot of cost, politically speaking, in a lot of places. Like, obviously, there is a lot of local pushback. But in a lot of places, like, these data centers are being built in very red states. There's not a lot of job opportunity. And so they're being heralded as kind of like, look, this economic boon that's coming. It's going to be really great for the local economy.

5:52There's going to be all these jobs. But the truth is that, well, one, you need thousands of people to build a data center, but you need far fewer to maintain a data center. So once it's already up and running, those jobs, a lot of them will evaporate. Two, they are very, very resource intensive. It takes a lot of water to cool a data center. It obviously uses up an absolute ton of energy. And so I think we're going to see a switch. I mean, this is just a prediction, but where it's going to be politically untenable to support a data center. And we're going to have an offshoring push in the next three years.

6:24And even the people who those thousands of jobs of people who build the data center aren't always local, right? Because a lot of these are specialized people come in. I live in a red state and there is pushback. They're trying to build a data center near me. It's not enough to actually do anything. It's going to the thing's going to get built. But yeah, I do think as people start to put the piece together of, oh, my energy bill's higher now. Oh, the jobs aren't here that I thought we're going to be. I agree. I think we're going to see pushback. And that's when we're going to build data centers in space.

6:53I was literally just going to say on Mars. We don't have a data center in Santa Barbara where I currently live, but we do live very close to a SpaceX rocket launch site. and for a really politically unengaged community. Wow, do people rally against those rocket launchers because it freaks out their dogs and horses and such. And so I would just love to see what happens if they try and build a data center here. Amazing. Okay, so I feel like we would be remiss not to talk about what these data centers are being built for because it's chatbots, it's ChatGPT. They're being built for inference, meaning not just to train the models, but actually to support millions and millions of people asking chatbots questions and wanting to get a result.

7:39One trend that I feel like we really saw pretty acutely this year was the rise of chatbot companions and AI relationships. I'm curious kind of like how you feel about that now and how has that feeling, I guess, changed since the start of the year? It's interesting. I think on the one hand, you've got so many individual incidents where things have gone really wrong, with chatbot companions. You've got interactions allegedly leading to suicide or contributing to suicide. You've got some seemingly pretty unhealthy relationships, but at the same time, you also have cases where, you know, people seem genuinely happier.

8:17They seem like they are filling a void. I don't know. I personally, it's one of those things where I have been sort of reflexively like, oh no, let's not do that. But I recognize that I need to come around to like, Like, well, it's not for me, but that doesn't mean it's not a place. I think really, most of all, it's still so early in all of this. And I think there needs to be so much more work done to figure out what these relationships are doing to people for good or bad or neither. And I wish that some of that work had been done on the front end by AI companies themselves before just sort of saying, go have fun.

8:52Go have fun with a new AI boyfriend or girlfriend without really understanding what the consequences are because no one really knows yet. It's too early. So I'm glad to see there are more safeguards in place on a lot of levels from a lot of these places. But it does seem too much too fast. Let's figure out what's going on. So this is something I've been thinking about with mania or what's being called kind of like AI psychosis, because I think a lot of the time, at least in my experience as a tech reporter, it's like the issue at hand, whether it was misinformation or what have you, there was a technical cause to that.

9:27But it felt like it needed a multi-pronged solution. And we were really just looking at tech companies to like fix this entire issue that was impacting our democracy. And with AI psychosis or AI mania, I don't know, that really does feel like a tech issue. If the chatbot is telling you that you've discovered some like new frontier of physics or whatever, or if it's validating you again and again and you believe it, that seems like a problem with the chatbot. But with AI relationships, I wonder if the issue, when it is an issue, is more complex. If there's something else that's going on kind of at a societal level and that chatbot relationships are a symptom of that rather than a cause.

10:12I do think we need more safeguards in place. Like, absolutely. I think also a lot of other things need to be done at the societal level so that we have more connections with people. It's easier to make those connections. There are more things pushing us to be in community with one another. Zoe, we're going to bring back bowling leagues. We're going to bring back bowling leagues. What could be better? So another trend that we followed really closely this year at Wired is the global competition in making frontier AI models. So we will get into stories and trends that are not centered on AI, I promise.

10:47But it would be disingenuous to pretend that AI hasn't been the defining story of our industry this year. And one of the moments in which that became really clear happened pretty early on. If you remember back in January, when the Chinese AI research lab DeepSeq released the R1 open model. And it felt like all hell broke loose. Yeah, it really came out of, I want to say it came out of nowhere, but it didn't. It came out of China, and we shouldn't be surprised that China's doing really great work like this. And there was an actual market impact, right? Investors got kind of freaked out. Yeah, especially, I mean, NVIDIA is really the bellwether for the AI industry at this point.

11:25After DeepSea came out, it lost nearly$600 billion in market cap on January 27. It is the largest single-day loss for a single stock in history. And that was the end of NVIDIA. Yeah, and no one ever heard from them again. No, they recovered just fine. They're doing great. No, but it is. That is, A, tells you, I think, how, I don't want to say inflated, but like how much room there is for these sky-high stocks to sort of vacillate from here, but be the impact of just a model release. Like the fact that one model release, you know, there are dozens of models out there. The fact that one from China can have that big of an impact really tells you how big a deal everyone thought this was.

12:06And they're right, it is. The big thing about DeepSeq R1 to me was the openness of it. It's an open-way model. Anyone can use it. Like really only US only meta had really been pursuing that strategy on a pretty big scale. Now, all of a sudden, you've got a model that I think was competitive with Lama. Lama also kind of fell by the wayside. So now you're in a world where China is really leading on these open way models that anyone can use, which is going to be a pretty big deal. Because like if you have a choice between paying for something or it being free, a lot of people are going to go for the free version.

12:39And these models are going to really inform a lot of how people are using AI in the next two, three, five, ten years. I think we're going to see a lot of influence from Chinese models doing that. Yeah. And we should say before we get into this more that open weight means that like the weights of the model are published. So anyone can download the model on a personal device and they can modify it. Like you can't really do that with ChatGPT, but you could do it with DeepSeek. You could get an understanding of how it works and you could tailor it to your liking. The reason that this is attractive to AI firms is that instead of just having your, let's say, 300 researchers and developers working on the model, you release an open weight model.

13:18And all of a sudden, everyone in the world who's tinkering with that model could be making improvements that you can then take co-opt and improve the model yourself. So you get access, theoretically, to a research community that's much, much bigger than the one that you have. And this is a huge advantage for China because they're really going hard on open source AI, open weight AI, and it's allowing them to advance really, really rapidly. Whereas in the U.S., we've really become more closed source. Even Meta, like you said, one of the first firms to build advanced open source AI has signaled that their next series of models will likely be proprietary.

13:57And so among other things, people feel like it's a strategic disadvantage. Also, we're repeating the same training runs, like we're using all of this energy and resources and research and compute to essentially do the exact same thing. Each lab is having to repeat the exact same process versus building on the insights and innovations of another lab. So what do you think about DeepSeek being built in China? Sometimes Chinese models are subject to certain censorship situations. I think DeepSync has run into that as of other Chinese models. Does that limit its potential upside or are people just kind of, you know, not going to care so much about that?

14:36I suspect the latter, but. You know, I would be curious what Will Knight, one of our really amazing AI reporters at Wired, would say about this. But so far in my conversations with him, the sense that I get is that people don't care. And even U.S. firms that have been kind of championing the U.S. race against China behind closed doors appear to be using DeepSeek. If for no other reason, then it's obviously just a lot cheaper to do. And it's really advanced and its capabilities are good. I also think there's this interesting dynamic where this debate has been playing out in politics around how to handle export controls.

15:11Do we cut off China's access to advanced GPUs and chips and so try and slow their progress? or do we give them access to these GPUs and then hopefully make them dependent on U.S. chips? And I think when DeepSeq came out, it felt like almost a signal that cutting them off was not a good move because look, it was spurring them to like advance in all of these other ways because DeepSeq was trained in a really cheap and efficient way. Now we've seen the Trump administration say, okay, wait, they can get access to like certain cutting edge chips. And actually China is coming in and saying, Well, you know, if you're a company operating in this country, we don't want you to be using those American chips like they're trying to tie Chinese AI more closely to Chinese hardware.

16:05Do you ever feel like you blinked your eyes and then woke up in some kind of sci-fi movie? Suddenly it seems like the very existence of AI is changing everything, including our relationships. I would like to think that I could not fall in love with an AI companion, but I really think that anybody could. I'm Oz Velocian. And I'm Cara Price. We break down the tech news you really need to know. Listen to Tech Stuff in the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

16:38Moving on from AI. So the next trend that really defined the magazine this year was the creation and the workings of the so-called Department of Government Efficiency, or DOGE. Where to even begin, Brent? Yeah. This is the story that kept on giving, and for good reason. We recently learned that members of the group are still working, largely, we believe, unsupervised across the federal government. So I feel like it's as good a time as any to take stock as to why DOGE remained so important this year. I just this week was looking back at some of our earliest DOGE reporting and reminded of what a crazy couple of months that was.

17:22So just as a reminder for folks who were slumbering through the first half of the year, A, I'm jealous. I respect that. I was just going to say, good for you. Department of Government Efficiency came about when Elon Musk and Donald Trump got together and basically Trump gave Elon Musk kind of free reign to do whatever he wanted, and I'm not really exaggerating here, within the federal government. So Musk allies took over various government agencies, including the Office of Personnel Management, which is sort of the human resources for the whole government, the General Services Administration, which is its tech IT department, basically.

17:57and from there kind of fanned out across agencies and were responsible for a lot of the chaos that we saw in this early administration. Massive job cuts, massive cuts to USAID, regulations being slashed, not always for good, having everyone in the federal government having to write an email with five points of what they did that week and sending it to never be read. Doge didn't end up doing what it set out to do. The idea was to cut a trillion dollars from the budget, which you literally can't do unless you cut into entitlement programs, which A, Doge had no control over, and B, politically would be untenable.

18:35So, Zoe, what did they do? Yeah, I think the goal ostensibly was to root out fraud and waste, to root out inefficiency. And abuse. Fraud, waste, and abuse, I think. Fraud, waste, and abuse. I was going to say it, and I was like, I don't even know exactly what that means. They didn't either. It's fine. It sounded good on the surface, but it also, I think, very quickly felt like a political project for Elon Musk. And I think he said as much. It was interesting. I remember this moment when the executive order codifying and naming Doge first came out. And the way that they had been talking about it previously, it felt like it was going to be this big, enormous thing.

19:13And then the language in the EO was kind of like, improve the government IT and like modernize it. I don't remember. It was very like, okay. But then when Elon talked about it subsequently and when Doge affiliates talked about it subsequently, the language they used was something akin to like, it is our job to enforce the will of the president. And when that's how you conceive of your job, it really does feel like there's nothing you can't do. You know, I think the impact hit federal workers first, and we documented that pretty meticulously. Now I think we're kind of seeing the trickle-down effects.

19:50Like a quarter of the CDC is gone at this point. I think around 300 ,000 federal workers are no longer in the government. USAID shutting down has led to an estimated hundreds of thousands of deaths reportedly. So I think we're going to keep seeing the ripple effect. it does bring me to a slightly lighter note, which was Elon Musk talking about Doge on Katie Miller's podcast recently. Stephen Miller, who's quite high up in the Trump administration, obviously Katie Miller has worked for Elon and his companies as well as in government. And she kind of operated as like the Doge comms person when she was working in government.

20:27She now has a podcast. She sat down with Elon recently and she asked him, would you do it all again? And do do you think it was successful? And he kind of like hems and haws, but ultimately what I got from it was Elon saying, I would have worked at my companies. In some ways, like I should have just focused on my companies. It felt like a tacit admission that Doge was not successful, which I think feels fairly obvious. But I also think it's not as simple as that. Like, of course they didn't cut anywhere close to what they wanted to, but I do think they changed the federal government pretty profoundly.

21:06Yeah, well, and not only that, I mean, Elon Musk's personal brand, I think, took a pretty big hit. If you sell EVs, whose market is presumably people who lean a little bit more left and care more about the environment, and you become this sort of demagogical agent of destruction to the federal government, there's a dissonance there. Tesla sales have plummeted in Europe. They're holding out okay in the U.S., but he's even switched over to robo-taxis and humanoid robots as the future. And I think, to your point, Doge changed the government. And the effects are, I think today, most acutely being felt in another big, unfortunately, big theme of 2025, which is immigration and the immigration crackdown.

21:50A big doze project that has been going on since at least the summer is to combine different pockets of data from throughout the U.S. government, whether that's Social Security data, tax data, Homeland Security data, cross-reference it, pool it, when it has always historically been kept separate, and use all of that sort of combined information to surveil and track down immigrants. Right. Yeah. Like explicitly, that's the purpose and has really transformed, I think, A, how everyone's data is held in the U.S. government because everybody's data is now intermingled in ways that it was never supposed to be.

22:26And B, has really given ICE an incredible wealth of data that, again, they should not have, historically would not have had, and has given them tools to really fuel their mission here. So I think that is a consequence that we're going to be feeling indefinitely. Once you commingle all that, you can't separate it out again. So that's the world we're in now. Thank you, Doge. Yeah, that was another executive order that came out. I think it was literally titled something around like eliminating data silos. Another thing that on its surface sounds good, data silos inefficient, sounds bad, but there's a really good reason to keep a lot of this information separate.

23:03separate. You don't necessarily want the federal government to be able to knit all of that together to track you across any platform to know your financial data, your health data, your whereabouts, all of that. Yeah. I mean, the Trump administration now wants to vet, what is it, five years of social media if you're coming into the country just to see what you've been saying. And also they're looking to strip more foreign-born Americans of citizenship. They're moving towards denaturalization. The predictions for 2026 and immigration aren't great. It's that it's going to get worse and more. Or let's say, if you were an engineer born in a different country and you had an option of going to the U.S.

23:43or Canada or China or somewhere else in Europe, it's a lot harder question to answer now than it was before all this happened, I think. Yeah, no, I think that that's exactly right. And we're going to have, I think, some really good reporting on that. in 2026. So we're nearing the end of our 2025 recap, and we would be remiss not to mention the Jeffrey Epstein saga. So this is a story that has had so many lives across many, many years, but it felt like it really came to a boiling point this year, politically speaking. So Brian, I guess, can you just refresh our memory on what even happened this year?

24:22I get the easy job. Without going into the whole Jeffrey Epstein everything for so many reasons, obviously he's a disgraced financier, convicted sex offender, also the locus of so many conspiracy theories from QAnon up to the White House and its supporters. what we saw this year was a real movement towards releasing the so-called Epstein files, which the White House Donald Trump basically ran on. He said, look, if I get in that office, I'm going to release the Epstein files. You're going to have them right as soon as I get there. And then we got to that point and he got there and he said, you know what?

25:00Never mind. And there was people saying there are no Epstein files. Actually, the Epstein files are a hoax. Actually, no, they are here. It has been a mess. the upshot of all this, maybe by the time this podcast airs, the Epstein files will be released. Or maybe sometime after, there's a deadline for Friday, December 19th that has been set by Congress. So we'll see what happens what's actually in there. Personally, I think it's just going to add more fuel to various conspiratorial fires. I think the people who are fans of Donald Trump are going to find ways to decide that, oh no, he was actually an FBI I inform it the whole time.