2025 In Review, 2026 Predictions — With Reed Albergotti

0:00Big Technology Podcast Host:Let's look back at 2025 and anticipate what's coming in 2026. We'll do it with Semaphore Technology Editor Reed Albergotti right after this. I'm just back from ServiceNow's Knowledge 2026 in Las Vegas and the conversations I had there are ones you're going to want to hear. I sat down with their president and CPO Amit Zaveri on the platform strategy powering enterprise AI, Chief People and AI Enablement Officer Jackie Canney, and Chief Digital Information Officer Kelly Romack on what AI really means for the workforce. The technical leaders behind ServiceNow's NVIDIA partnership on shipping AI at scale and Ulta Beauty on deploying ServiceNow's technology across 1 ,300 stores.

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1:14Big Technology Podcast Host:Aboard is your partner for AI transformation. Visit Aboard.com and let's build something together. Welcome to Big Technology Podcast, a show for cool-headed and nuanced conversation of of the tech world and beyond. It's the holiday season, which means one thing. We take a look back at what happened over the past year and say, what's next? And if we can be right, you know, maybe three or four times out of like the 90 ,000 predictions we'll make, I'm sure we'll celebrate it next year. So joining us as always is, or actually joining us in key moments in history, shall we say, is Seminfo Technology editor, Reid Albergatti.

1:52Big Technology Podcast Host:Reid, great to see you. it's always good to be here. I kind of emailed you and said, let's do predictions, but I'd love to hear just your recap of 2025. I mean, is there, it's been a crazy year, so much funding, commitment, back and forth. What would you say is like sort of the defining characteristic of the past year? Yeah, I think, excuse me, I think that is one of them. I think the infrastructure, you know sort of questions and just the the sheer scale of it is has been probably like the big topic of conversation um but i also think you know we've been talking a lot about china recently right i think geopolitics has played a big role much bigger role than it did last year um i was looking back at my predictions from last year and trying to see like where did i get where would i get right and what do they get wrong?

2:43And I mean, you know, it just seems like it was such a different world a year ago, right? Before the changeover in the administration, we've seen all kinds of crazy stuff happening in the Gulf. And so, you know, I think that's another, another big one.

2:59Big Technology Podcast Host:I mean, for me, like I view this as sort of a year of scale where like, let me, I'm just going to try to go through like the various years since ChatGPT has been released, because obviously gender of AI has been the animating conversation in the tech world. I mean, 2022 was like, oh, wow, the computer can talk to you and doesn't sound like an idiot. 2023 was basically, it felt like treading water. There was a lot of like, where's this going to go? Because the capabilities weren't advanced enough. Sam Altman gets fired, reinstated. and then I think 2024 and 25 have really been the years where like the applications are starting to materialize.

3:41Big Technology Podcast Host:Maybe 24 was when the application was starting to materialize. Like you really had a sense that this stuff might work and now 2025 has been like everybody's taking all of their money and putting all of it into this project in the hopes that you know it really will continue growing the way that it has. Is that a good sort of representation of where we are? I like that. I like that. Yeah, I do think that's right. And I did write in the predictions last year about infrastructure and the fact that it was probably an obvious prediction, but that we were just going to see multiples more compute this year than we did last year.

4:19And also talked about how these data centers were going to get so big that these large frontier models are going to be trained across multiple locations, which we started to see in like the last quarter. So yeah, I mean, I totally agree with that. And I think we'll see that continue next year.

4:37Big Technology Podcast Host:So if those are the labels for 2025, what do you think the label is going to be for 26? Like if we're going to look back this time next year, where do you think we are? Yeah, I mean, I think actually we're reaching this point in AI where it is still going to be the major topic of conversation. but I think some of the novelty of it is wearing off now and I think we'll see it plateau. Then I think the products will become much more important. You mentioned the products back in 2024, but I think next year it's really going to be about the products. I don't think people are going to be getting excited about whatever new model is coming out and what are the capabilities because I think for most people, they're basically good enough.

5:28And it's really about, it's really about just adding new products rather than like the underlying model capability. So I think, I think that's what next year, at least for consumers will be about in the enterprise. It's, it's maybe a little different. Yeah.

5:42Big Technology Podcast Host:I mean, I think there's going to be some companies that will continue to push the envelope and that will be some, some pretty impressive news. But I also think the shakeout is coming in a way like to me, I think 2026 is really going to be a year of chaos. I mean, we're already starting to see some of this happen with Oracle and some of the other infrastructure builders. And the bets have become so big. And, you know, that's one of the things about gambling is not everybody wins their bets. So, yeah. Yeah. So, so, so what I'm going to do, I think that like, we have a prediction episode coming up with Ron John Roy.

6:17Big Technology Podcast Host:So instead of just going like for our wild predictions, I just kind of wanted to set the table for 2026 and sort of throw some ideas is about what the companies, you know, might be going through, what this chaos might look like, and then sort of hear your perspective about it, Reed. Does that sound good? Sure. Yeah. And I'd love to hear if you disagree, because I think this is, it's fun to argue about this stuff. Definitely. All right, let's do it. Pardon the interruption style. Meta. The question for Meta is like, what is going to happen to that super intelligence lab? I mean, that is, it's a multi-billion dollar effort.

6:50Big Technology Podcast Host:It hasn't, has it produced anything? and it is really going to be sort of deliver or chaos or crisis mode for that division next year. Yeah, I think it's going to continue to be chaos and crisis mode. I mean, you're already seeing stories coming out. I think it was in the Times about some sort of friction between the product teams and the super intelligence team. So I think that will continue. I think it's just so remarkable that Meta, you know, they were so early on AI. They tried to acquire DeepMind, you know, before Google did, and then sort of just lost focus on it. And now it's just it just seems to be all over the place.

7:30And it's going to be all about, I think, for them, like, again, it's products, right? It's like these glasses, you know, the glasses incorporating AI into those and, you know, in across its products, which has been sort of a, you know, a clunky experience. Right. I don't think that the Facebook and Instagram AI products that they put out have been necessarily that popular. So I think it'll just be more chaos as they try to figure it out.

7:55Big Technology Podcast Host:I mean, let's flesh that out a little bit. So obviously there's one question about whether Alexander Wang is going to stay. The other is, are they going to ship a leading model or at least a model that people respect? Because after, let's say, Llama 3, which was neck and neck with some of the state-of-the-art closed models, they've really fallen off a cliff. And they have all the expertise and all the GPUs they could want. and obviously this stuff takes a long time, but yet where's the cream filling? I think they've actually failed at that strategy of sort of putting out open source models and then trying to make that the standard.

8:30They're really good at open source software. I mean, they've done that many times, right, with PyTorch. But I think AI is different because it's just so expensive. And I wrote about this a bunch. Like eventually do these models get so expensive that it just makes no sense to put out a leading frontier model and make it free? And you have so much competition now from China, from France, you know, with Mistral, that it's just I think at this point, the new models are either going to just be part of their products, like almost back end technology, or they'll be, you know, they'll be closed models just like like open AI.

9:04That's my that's my guess. I mean, I think like an educated guess, I would say. I don't know if you'd agree with that.

9:10Big Technology Podcast Host:I think so. I think they're not going to their open source strategy is definitely done. The question really is, can they build a even closed model that rivals today's leaders? Well, I don't think they have to, to be honest. I think that thinking about it that way is like the way a lot of people still think about AI. It's like there's this race to superintelligence. I don't think that's the case. I think at this point, it's about products. And if people like the meta products that they put out there that are run on these foundation models, to be honest, they could probably be run on a lot of different models that are out there.

9:47I think it's partly ego. It's partly bragging rights and maybe a nod to, maybe it's really for Wall Street to kind of look like you're on the cutting edge. But I mean, I really don't think they have to. I think the models are pretty, they're good enough and they're close enough that you don't have to have some breakthrough. In fact, I think the same is true for probably open AI. I mean, we, you know, I don't know. Again, that's maybe a controversial opinion, but

10:16Big Technology Podcast Host:you know, do you agree? Well, I was going to say, so let me, let me throw this, this other thing out there, which, which is, which is basically is one answer to your question. As you're talking about meta, it does seem clear that meta can effectively fail to build super intelligence. They could fail to build, you know, the worst model and still make their products better. But then what do their products look like? There's a lot more interaction with AI in them than there were previously. You go from, you know, you friend a human to you friend your AI bot. And we've already seen that there's compelling uses for that.

10:53Big Technology Podcast Host:So maybe next year really is the moment where Facebook and I mean, we've already seen some of it with the recruiting, but Facebook and OpenAI's battle just explodes out into the open. And maybe Zuck and Sam are at odds with each other and meta might even see start to eventually see some use usage declines as people are like i don't want to look at other people's great lives on instagram i want to speak with my ai therapy bot who tells me how great i am well you know that's interesting to think about like so so um all these tech companies are always competing with each other on like every front right they all make a product in every single category and open ai has now made a social media app, right?

11:37And I think that's sort of looking like it's failed. I mean, they threw the spaghetti against the wall. I think actually it looks like Facebook is, or Meta, and Facebook and Instagram are sort of competing more with like YouTube and TikTok. And it's not so much social media anymore. It looks a lot like just media, right? And like television. I think that's in the YouTube strategy is like, if you talk to Neil Mohan, it's like, you know, the CEO of YouTube, it's like, they don't care whether it's AI generated content or human generated content, they just want to put content in front of you that you want to see and you want to watch.

12:18And I think that's ultimately what Meta is about. I mean, it's eyeball farming, right? And so, like, I don't know what the AI, what the future of social media and content is in the AI world, like we can make guesses about that. but meta will will see what it is and they're very good at copying that right so they will just mimic whatever you know wherever the eyeballs are going they'll they'll do those products and they'll probably do a you know they generally do a good job of that i think

12:47Big Technology Podcast Host:talk a little bit more about why you don't think open ai needs the best models well i mean there was an interesting story in the information today um that that said you know ai So OpenAI has realized that there's less progress on the model front and it doesn't necessarily translate into better consumer products as they increase the capabilities of the models. And that's creating some tension within the company. Of course, the company responded and said that's more or less not true. But I've been calling this now for over a year, which is that the real – the OpenAI, as soon as ChatGPT came out, completely changed from a research lab to a consumer product company.

13:30Yes, they have an enterprise business that's growing, and I think that could be a good revenue source. But really, what they have that nobody else has is ChatGPT and a lot of eyeballs. I think it was or is the fastest growing consumer product in history. If you just look at the numbers and the speed of growth. So they're just, what they need to do is keep those people engaged. That's their product. And they have to reduce costs. So I think when you talk about like open AI, building its own chips and data centers and all this stuff, that's all about like them foreseeing the future where there's so many people using these things.

14:08It's expensive to run in the data center. They're going to have to have a strategy to control the costs and sort of vertically integrate there. it's not about like can we build super intelligence i think they have to they have to keep stay on the cutting edge but that's more because they've like they still have a lot of investors who believe that you know that they've invested in this company because they're going to invent agi and it's going to tell them how to make money right and and there's a story that they they have to keep telling um and i think it's part it's important for recruiting and all that but like ultimately, I think that will just become, there will be a research lab within open AI, just like Google has, you know, had for many years, like an AI research lab.

14:52And now that's becoming much more a part of product. So that's, that's kind of how I see it. If that, if that makes sense.

14:59Big Technology Podcast Host:Yeah, that makes sense. I mean, I think my, I will go against you on this one. I do think they need the best models. I think their story and their story is important is predicated on them being out ahead of everybody else. And it was interesting how, uh, when Google released Gemini three, before the code red happened, the underappreciated comment within that company was, uh, Sam saying there are going to be some, you know, I guess like, what did he say? Bad vibes or some economic, bad, like tough economic vibes, uh, which, which I think just indicates that best model story continues. And, you know, then you can sort of build the infrastructure you need to be able to deliver the products.

15:38Big Technology Podcast Host:So I think if you fall too behind... Go ahead. Oh, good. Sorry, I cut you off. Yeah, no, I was just going to say, if you fall too behind on model development, then some of that magic evaporates. I agree with that. But I think the thing that I'd love to get your thought on is when the bad vibes, the bad economic vibes, are they, is that their customers with the products or is that more about investors and raising money and, you know, or borrowing money, that kind of thing?

16:10Big Technology Podcast Host:I think it's more about, about investors. That would be my guess. That's right. Yeah. But that money right now is so important to the company. Totally. Totally. And that's, and that's what I mean. I think they have to keep doing it because, but it's more about appearances. It's not, it's not like, you know, if, if they don't stay on the cutting edge of models, the users will go to Google or something, right? I mean, I think there is a competition for users there, but it's much more about like, what does the actual product feel? What are consumers able to do with this? Which has, I think, less and less to do with the underlying model capabilities and more to do with all the stuff they build around those models.

16:50So that's sort of my view.

16:54Big Technology Podcast Host:Okay, that'll take, that'll take. I get that, that's an important nuance and we love doing that here. All right. Oh, we have so many companies left to do. I think we've only really done one and a half. I know. Google. The Google thing is like, we're going to see next year whether or not they can maintain this momentum. And if they do, they effectively become the undisputed leader in AI, given where they started and how they've been tracking. And that is an impressive turnaround for them. But my, all right, I will go with my perspective on this first. I don't think they're going to do it. I think there's been all this buzz about Gemini being so great.

17:34Big Technology Podcast Host:You use the product. It's good. It does cool things. It has really interesting features. You can talk to videos, which I like, but it doesn't feel as developed as the others do, as Claude and as ChatGPT. If you said, run, go use an AI and you need to get something done right away. I don't go to Gemini. It just, it, it, sorry. Well, I was going to say something mean. Um, I just think I, not about you. It's about it. I'll say it. I'll say it. I'll say it. Gemini to me feels like an Axios article, right? It's like giving you the bullet points. Oh, wow. I thought you were going to say something mean about Google, but you're okay.

18:14You're going for Axios. All right.

18:16Big Technology Podcast Host:I like Axios, but you know, it just feels like, you know, Oh, here, let's just give you, you know, the bullet points. Then you go away. yeah no i i i see what you mean um i actually i like gemini too like i i use that i think it's good for like you kind of said anything visual like i used it to try to like redecorate my house which you know was like just just in mayhem and so it was really helpful for that i think it was i tried you know chat gpt so i think on the multimodal front they're they're better the way I look at it though is not that like Google you know caught up or something like that I think Google was was already ahead on AI but they just hadn't been thinking about productizing it yet they were sort of like this technology's not here yet it's not ready yet so we're gonna wait you could say that was a mistake or not but like whatever happened is they got dragged into this into this new world and they had to catch up not on AI but just on like how to turn these AI you know this ai research into products and they pretty much have caught up um but i think that they still have a big problem which is that like they're underlying you know they get 80 percent of their revenue i think from from search from the advert search advertising ecosystem um and that's totally changing right that whole industry is changing like it's i think traditional search is like is going to be just gone um even google search is to me totally different now and what does that do to revenue and i think it's just a question of like that's a very tricky balance that they have to it's a tightrope they have to walk where they can't disrupt themselves too fast but they kind of have to disrupt themselves and there's a lot of ways that you that that can go wrong so i kind of agree like the it's not like google's now in the lead and and they can just like continue getting better at AI.

20:10And, you know, this isn't really about being better at AI. But then again, I think that's also looking at Gemini as like very narrow because like in a lot of ways, like their AI is showing up in places like self-driving cars, right? The Waymo thing is, you know, all over the place. We can talk about self-driving car predictions if you want to, but you know quantum computing right where you've got a potential there for you know breakthroughs in quantum which then would feed into you know like isomorphic labs their biotech spinoff right which could be whole new sources of revenue so I think in a lot of ways like they're this giant empire that has a lot of like I think really good things going so I'd sort of like broaden it out beyond Gemini if that makes sense yeah that does make sense I mean

21:01Big Technology Podcast Host:this is like a place where, I mean, Waymo is brought up every, you know, couple episodes and there's the only thing you can do with Waymo is just be like, they're really doing it. Um, it's it Google, like between Waymo AI quantum. I mean, the fact that they acquired DeepMind, they're a smart company. It's, it's a, yeah, I think it's a very smart company. And I think Sundar, you know, he gets a lot of, he gets a lot of crap, I think, but like, I mean to be able to kind of like quickly mobilize and change and if you talk to people at google they're just like it's a totally different vibe now than it used to be it's like people it's much more of like a hey let's get going like fast-paced vibe versus kind of that was kind of a sleepy it's kind of sleepy before that was that was my vibe so yeah it was a retirement home in a way I mean I know that's yeah that's wrong but there's truth yeah in the joke yeah not for everyone right It's a huge company, but there were some people who for sure were taking it easy.

22:01And I think they're being sort of ushered out in one way or another. But it's tough to turn around that chip. So I totally agree that they have huge challenges. But it's such a bigger – I mean, we haven't even talked about their TPUs. I think so much of this AI stuff is about cost and vertical integration, and they're leading there. So, you know, it's really, I think all this data center build out, the way I think about it is it's like the training part is like interesting, but it's really about inference. It's really about serving the products to, you know, consumers and enterprise in the most efficient way possible.

22:42And like, I don't know, it's between, I mean, Amazon's doing a good job of that too. So it was Microsoft, but like Google seems to be just ahead there. I don't know how you feel about that.

22:53Big Technology Podcast Host:No, I agree with that as well. My perspective on this is the Gemini hype is going to fade a little bit, but Google the company is in really good shape. All right, I need to take a quick break. Let's come back. We'll do Amazon. We'll do Apple and we'll see what else we can get to. Netflix, I don't know. Let's do that right after this. Bitcoin has been part of the conversation for years now, but actually doing something with it has always felt more complicated than it should be. Where do you even start? If you've been curious about using Bitcoin but haven't made the jump yet, Cash App makes it easy.