OpenAI’s Potential, Google’s Speedy Model, Copilot Hits Turbulence

17:53Big Technology Podcast:Not yet. Empties the bank account.

17:54Ranjan Roy:Yeah.

17:56Big Technology Podcast:Oh, you meant all your entire balance? God damn it, Siri. All right. So we also talk about this debate on the show, model versus product. And this was also an interesting thing that I wanted to speak with Sam about because we're at this point where it seems like there's model parity in some ways, or at least the models are close enough that a lot of people can't tell the difference. And so I asked, where do you see the differentiator? Where do you see the moat here, basically? Is it better models? Is it distribution? Is it product? What is it? Here's what he said. The models will get good everywhere, but a lot of the reasons people use a product, consumer or enterprise, have much more to do than with just the model.

18:41Big Technology Podcast:We've been expecting this for a while, so we try to build the whole cohesive set of things that it takes to make sure that we are the product people most want to use. So he says the strategy is we make the best models, build the best product around it and have enough infrastructure to serve it at scale. It's an Amazon team product.

19:02Ranjan Roy:He's hedging there. He's hedging. I'm glad he's coming around to team product a bit more, but it's still a bit of a hedge. That's like you have your models, you have your product and you have enough infrastructure to serve it at scale. But I think if one thing happened this year, I think more and more folks coming over to team products that models aren't going to solve everything has been what made me very happy.

19:28Big Technology Podcast:I guess, yeah, the answer really does align with maybe my philosophy, right? That it's a little bit of each. Maybe. I don't know. I think it is a little bit of each. I don't know. If you're a company like Opening Out, you can't give up on developing the frontier models.

19:45Ranjan Roy:no i know but they the whole point was they this the story for so long was that the models will just get so good that product almost becomes irrelevant like it's it's yes that was the story that hasn't happened yeah and it's clear he is signaling the entire industry is signaling actually are there any of the ai leaders still trying to argue that like the god model will solve all problems? Or has everyone kind of moved away from that?

20:15Big Technology Podcast:I haven't heard much of that at all.

20:17Ranjan Roy:Yeah. Yeah. We've evolved this year.

20:19Big Technology Podcast:So let's talk a little bit about enterprise. We talked a little bit about it last year. One interesting point on enterprise, Sam says the same way that personalization to a user is very important to consumers. There'll be a similar concept of personalization to enterprise where a company will have a relationship with a company like ours and they will connect their data and you'll be able to use a bunch of agents from different companies, making sure that the information is handled in the right way. I think this is interesting, right? He also said that the API business grew faster this year than ChatGPT, which was surprising to me, but I guess it grew off of a much lower base.

20:58Big Technology Podcast:But just to go back to this thing, I mean, the idea that, you know, especially if memory gets better, you can sort of connect your company to an enterprise version of ChatGPT and it will be able to, you know, personalize and answer with context. Of course, there's data protections can be very important there. You don't like want to have your CEO conversations necessarily filter down to everybody else in the organization. But that seemed to me like a compelling pitch for where this is going to go with enterprise.

21:27Ranjan Roy:Yeah, I mean, I definitely agree. This is where it's going in enterprise. This is what I work in at Writer. Like this is this is going to be the big battle of 2026. I think on that point, it is clear, it's still an odd talking point to me, the API business grew faster than ChatGPT because, yeah, much lower base. And this was the breakout year for every API business for AI coding. Like, I mean, Anthropic was the biggest beneficiary of that, but the cursors of the world, all of that, like AI coding founded Stride. that drove API businesses. And I think like, it will see where that specific part of it goes.

22:07Ranjan Roy:But I think I was just thinking about like the companionship side of it. This is even more where dividing up and as you brought up data protection, like segmenting, siloing data and personalities and companions is going to have to be at the core of the product. Because just like, you don't always mix your work friends with your personal friends. Maybe at work, you don't want to tell your coworkers everything that's on your mind and just stick to work. And we all know how that goes. It's going to be reflected in how these systems work a bit. You don't want to mix these two things up and even within a company itself.

22:46Ranjan Roy:And I don't know, how your personal information flows into your work information. I think that is such a messy area that unless that becomes the singular focus of the company, I just see that being a problem.

23:02Big Technology Podcast:Let's talk about the revenue and infrastructure commitment question. So this is what Altman said about the growth curve of revenue. He says, the thing we believe is that we can stay on a very steep growth curve of revenue for quite a while. We are so compute constrained that it hits the revenue lines so hard. We see this consumer growth. We see this enterprise growth. There's a whole bunch of new kinds of businesses that we haven't even launched yet, but will. But compute is really the lifeblood that enables all of us. He says there are checkpoints along the way. And if we're a little bit wrong about our timing or math, we have some flexibility.

23:39Big Technology Podcast:I thought that was a very interesting line. But we have always been in a compute deficit. And it has always constrained what we're able to do. Basically, they're trying to free it up. So they see some correlation there between available compute and revenue. And that is the theory here behind the capital outlays. And the idea is basically that as you grow, your training costs, maybe even if it goes up, becomes a smaller percent of your overall spending compared to the inference costs, which are people using your models, which are much more directly tied to revenue. What do you think?

24:20Ranjan Roy:uh i mean as a theory or like as a kind of like overarching theory i think it's it makes sense but i guess it's it's hard to understand like have they really not launched this like pharma drug development business line sarah fryer hinted at because of compute constraints while they are updating gpt the new image model and posting sam shirtless as a fireman i think i saw that the open AI posted from their own account. And again, there's like a bunch of memes around it around like, I thought you're supposed to be solving cancer. And instead, like, everyone from OpenAI was posting. And the images were, and I started playing with it.

25:02Ranjan Roy:It's a very solid image model. I think it's like, on par with the Gemini 2.5 Flash, and we'll talk about 3.0. But like, so I think it was important that they launched it. But to me, the way the compute is being used, Even we talked about this in the past, Pulse. It's supposed to be like running compute all night to give you updates in the morning, and maybe they're going to stick ads in there. You can allocate your compute, and I think it actually kind of exemplifies that lack of focus. Because if you want to solve drug development and make that a big core part of the business, focus on that. If you want to focus on enterprise, focus on that.

25:46Ranjan Roy:The idea that it's compute that is preventing all of those businesses from exploding in growth. I don't know. I mean, maybe it is, but it's a tough one to swallow. Yeah. I mean, we did talk a little bit about like specifically if scientists had like, you know, two times more compute, what could they do?

26:08Big Technology Podcast:and um uh yeah it's you know i think the numbers that they're looking at are more like 10 times or 100 times more and we will see because it seems like they're going to get it there's talk today that they're you know in discussions to raise it a seven billion oh no 100 billion sorry yeah 100 billion i think at a 750 billion dollar valuation uh by the way one of the the the more interesting parts we just talk about it quickly was the uh discussion about ipo and i was like are you gonna ipo next year do you want to do you want to stay uh you want to stay stay private as long as you can it seemed clear that that he wants to stay private as long as he can and has like well he said interest in being a public company ceo zero which makes sense the kind of

26:53Ranjan Roy:things you have to do versus what he gets to do now are just very very different but he's got a good roster of folks right under him who would be great candidates for that as well. And kind of move over to chief product officer and get to continue to kind of lead that vision. You can see that world.

27:12Big Technology Podcast:No, it does seem feasible, although I don't think he will easily step out of the CEO chair.

27:18Ranjan Roy:I mean, I guess like you figure like a Mark Zuckerberg personality you might not have expected would be a public company CEO and would have been a long time ago, wanted to move more back to just like more of a product role. But then you see it can be done. So.

27:35Big Technology Podcast:Yeah. Device plan, it's going to be family of devices. And he said that there'll be a shift over the time in the way that people can use computers where they go from this sort of dumb reactive thing to a very small proactive thing that is understanding your whole life, your context, everything going on around you, very aware of the people around you physically or close to you via a computer that you're working with. So a family of AI devices that understand your context and who you're speaking with.

28:03Ranjan Roy:I like it.

28:04Big Technology Podcast:Is it, do you bite that? Do you bite that device? Like a bite of it?

28:08Ranjan Roy:I mean, I, yeah, like I, I, someone is going to win this and this is, I mean, already between somewhere in the mix of wearables and Ray-Ban metas and talking to my computer and like there's something there in all of this I think and someone's going to crack it so could it be Johnny Ive and Sam together we'll see yeah I mean to me the thing

28:30Big Technology Podcast:that was most interesting was that it's going to be a family so really stuff that maybe you place in the office right and then by the way speaking of knowing your context it will know your office kind place at home it will know your home context maybe it will be able to make sense of things maybe there's one that you you keep with you so when you're out on the go it could help and then give you reactive notifications. I mean, we'll see. It's clearly a ways out. But I think people at least try this device.

29:01Ranjan Roy:I think it's the right direction. We got to say I have to see something, but. Yeah.

29:08Big Technology Podcast:Okay. Then lastly, on AGI, I asked him about the Theo Vaughn interview. I said, you know, you told Theo that like the GPT-5 was going to be better than most people at most things. I'm paraphrasing here. You know, isn't that AGI? And he basically said like, I'm just going to paraphrase Sam's response. We're in this gray zone where we may or may not be at AGI. And basically like, he's like, we just need to start going towards super intelligence. And his definition of super intelligence is when a system can do a better job being president of the United States or CEO of a major company running a very large scientific lab than any person can with the assistance of AI.

29:54Big Technology Podcast:So if we're looking towards superintelligence, it's going to be a while.

29:59Ranjan Roy:Yeah, it was also interesting how he defined superintelligence with those were the three president of the United States, CEO of a major company and running a very large scientific lab, which again is interesting because it's still running under the theory that the model has to do all three of those things better than anyone versus there is like a much more specific model built for scientific progress, which I know he talked about in the interview as well around how 5.2, GTT 5.2, like really made breakthroughs on the science side. So it's clear that remains an area of focus. But I think like, I guess, in addition to everyone coming over to team product versus team model, I'm glad everyone seems to be retiring AGI and maybe even ASI's terms this year.

30:53Ranjan Roy:So we can just start 2026 with a clean slate. Yeah.

30:59Big Technology Podcast:I mean, Sam also said it about AGI. It's an underdefined term, which I think we would all agree on. All right. Before we go to break, Just quick reaction after hearing his responses and sort of, he really talked about product, the enterprise plan, the infrastructure side of things, and the IPO. Do you come away more confident about OpenAI's direction or less?

31:23Ranjan Roy:I think it seems to be like the drawing out of all from all those different topics, that idea of memory and context kind of living across all them. So if behind that they are actually truly working to kind of win at that, I think it puts them in a in a better place. But I still, again, like on that lack of focus is what worries me the most. And we've talked about this weeks on end. But within the interview, it becomes more clear that, you know, he wants to go after every one of these things. He's not saying it is absolutely critical for the business to win at every single thing. But it's still, it's like, remember when everyone wanted to be WeChat, the super app, like in the West?

32:13Ranjan Roy:Now this is an even bigger vision and ambition, but it's like we want to redefine how consumers interact with technology, how the enterprise interacts with technology, how every process that is incredibly complex takes place and do all of that as a business. It's ambitious.

32:34Big Technology Podcast:Yeah, no, there's definitely ambition. So I came away, I would say, I mean, it was good to be able to put the questions that we've been asking here directly to the CEO of OpenAI. I came away more reassured. But I also with this realization that, and we talked a little bit about this on the revenue side, that it is in his belief, also similar in Dario's belief. There is a belief that this is an exponential. and it's one of those things where it really has to continue on an exponential exponential increases in revenue exponential uh increases in capabilities uh to be able to work and and to me and we talked about this this is the great this is great unknown now they say that there is they everything they see indicates it will continue apace uh but at the end of the day it is a new category.

33:23Big Technology Podcast:That being said, you know, we marked, we started out saying 10 years since opening eye, but only three years since chat GPT. And I would say even in the past year, the difference between the chat GPT that existed, let's say in December, 2024 versus the one that exists today. It's hard not to appreciate how much better it's gotten since then. yeah i mean you have these reasoning models a year ago agreed agreed on that okay all right let's take a break and then we're going to come back with a very short segment about um this gemini 3 flash model that google has and maybe a bit about copilot all right we'll be back right after this this episode is brought to you by orchestra a couple of weeks ago i sat down with david pluff two-time obama campaign manager senior white house advisor and now a partner at orchestra for a conversation about AI democracy and the massive gap between how this industry sees itself and how the rest of the country sees it.

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35:40Big Technology Podcast:We're back here on Big Technology Podcast Friday edition. All right, Ranjan, let's lightning round through a couple of stories before we have to go. So Google has announced this Gemini 3 Flash. They say it's with pro-level performance. Following last month's launch of Gemini 3 Pro, Google announced earlier in the week that Gemini 3 Flash for consumers or developers. The tagline is it's a frontier-level intelligence built for a fraction of the cost. It retains Gemini 3's complex reasoning, multimodal vision, understanding and performance in an agentic and vibe coding tasks. But it has flash level latency, efficiency and cost.

36:18Big Technology Podcast:The Flash Model Series is Google's most popular offering. I think this is from 9to5Google, by the way. Very quickly to you, Ronjan. This to me seems like the biggest threat, right? Is that all this money goes into infrastructure and then a Google pops out an AI model. Maybe this is going to be something that will enable more AI, but ultimately all this money goes into infrastructure. And then we find out that you can process AI with similar levels of intelligence for the cost of a Google search or maybe a little bit more.

36:50Ranjan Roy:Yep. I think that's exactly right on this. And one thing that did not come up in that interview was trying to make it more cost efficient. kind of like the entire philosophy from the open ai side is bigger bigger bigger versus google is showing it's playing both work we can go bigger but we can also work on that cost side and i think that indicates like it's a mature business that understands at a certain point that is going to be more important than or as important as the type of results people are getting yeah i mean to me

37:23Big Technology Podcast:this is, again, the big question. And we're going to talk about this in our predictions episode, which we're actually about to go record. But this, to me, is the big question of what happens next year. Do these models just become so efficient? And if so, does that throw the math off? Okay. Before we leave, I think you and I have been texting about the problems that people have been having with Microsoft Copilot. And it started with this information story about how maybe Microsoft salespeople's quotas had been reduced because of this. And there's another Windows Central article that's actually quite harsh.

38:04Big Technology Podcast:And it's funny because I don't expect Windows Central to go in on Microsoft, but they certainly did. They certainly did. Windows Central says Microsoft has a problem. Nobody wants to buy or use its shoddy AI products as Google's AI growth begins to outpace co-pilot products. Here's the lead. If there's one thing that typifies Microsoft under CEO Satya Nadella's tenure, it's generally an inability to connect with customers. Microsoft has shut down its retail arm quietly over the past few years, closed up shop on mountains of consumer products while drifting haphazardly from tech fad to tech fad, from blockchain to metaverse and now to artificial intelligence.

38:42Big Technology Podcast:Satya doesn't seem to be able to prioritize effectively and the cracks are starting to shine through. I am someone who is actively using the AI features across Google, Android, and Microsoft Windows on a day-to-day basis, and the delta between the two companies is growing wider. Dare I say it, Gemini is actually helpful. Copilot 365 doesn't even have the capability to schedule a calendar event with natural language in the Outlook mobile app, or even provide something basic as clickable links in some cases. is Microsoft, I mean, this seems to be, these stories really resonated because people are having these experiences.

39:20Big Technology Podcast:Is Microsoft fumbling the bag on this one?

39:23Ranjan Roy:I think they are. I mean, I hear this all the time. And then like, to me, what it really symbolizes is just like when you have that power of lock-in of your customers that you know they're not going anywhere else, you don't have to deliver the same quality. You don't have to fight for that. And everything I've heard and read about Copilot, it kind of like feels and seems like this, that it's more it's kind of shoved into whatever existing system you have. You kind of have to use it. It doesn't do what you want it to do. And I think I actually think it's a good setup because like as we head into the next year, because Microsoft was sitting very pretty at the beginning of the year and Google was not.

40:07Ranjan Roy:and like it's such a reminder that just in this year how much things could change and also like how much that means they could change next year but i feel like already i saw that there's like reports around like further price increases for microsoft products like this that that like you have to take their ai features now whereas before there were an add-on like all of these things i I think are showing that they're just trying to kind of extract value versus have the best product and experience for their customers, which is going to be interesting to see how that plays out.

40:44Big Technology Podcast:Yeah, it's fascinating to me because I don't think anyone, at least in the early days, spoke with more clarity about the potential of AI and how to make it a good business than Satya Nadella. And here we have Microsoft as the laggard. They're performing worse than most of their peers. and they have opening eyes IP till what, 2032, but they don't seem to be making as much hay out of it as you would imagine. So yeah, that's definitely a concern for them. All right, short episode this week, but we have so much content on the feed that figured Ranjan and I could come in and out. Then we'll record this predictions episode that you'll see next week and definitely encourage you to check out if you haven't the Sam Altman interview that was just published yesterday.

41:30Big Technology Podcast:And if you really want, and if you want some more, check out my conversation with Jim Cramer, where we do all of our big tech hot takes. All right, Ranjan, thanks so much for coming on.

41:39Ranjan Roy:All right, see you next year.

41:41Big Technology Podcast:See you next year. Well, you and I, we're going to do one more episode. Well, yeah. We'll see you next week, but just to give people a view as to what's going on here, we're actually about to record it today. So it's not that we didn't change our clothes for a week. It's that we decided to take Christmas week off, but we still wanted to give you something to listen to. So we'll go record that now. All right. Thank you, Ranjan. Thanks everybody for listening and watching. And we'll see you next time on Big Technology Podcast. You can't reason with the sun.

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