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

Summary

Big Technology Podcast – Summary

Episode: OpenAI’s Potential, Google’s Speedy Model, Copilot Hits Turbulence
Host: Alex Kantrowitz
Guest: Ranjan Roy
Date: December 20, 2025

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Episode Overview

This episode dives into the future direction of OpenAI following Sam Altman's first dedicated interview with Big Technology, explores Google's impressive Gemini 3 Flash model and its implications for the AI landscape, and examines turbulence facing Microsoft's Copilot product. The tone is analytical yet conversational, with humorous asides as host Alex Kantrowitz and guest Ranjan Roy unpack the week's breaking news in tech, AI, and the business strategies shaping these titans.

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Key Discussion Points & Insights

1. OpenAI’s Direction and Sam Altman's Vision

Timestamp: 02:14 - 34:04

a. Memory as OpenAI's Next Frontier

• Memory in AI: Sam Altman highlighted the company's ambitious goal to enable its models to truly "remember" users—retaining context not just within projects but across all user interaction.
  • “Even if you have the world's best personal assistant, they can't remember every word you've said in your life ... No human has infinite perfect memory, and AI is definitely going to be able to do that.” – Alex, paraphrasing Sam Altman ([03:40])
• Product Implications: This could radically deepen AI's usefulness, especially in business, and also reshape how people relate emotionally to bots.
  • Humor: Concerns over AI "memory cross-talk" are raised with jokes about not wanting "your erotic conversation" showing up in a recipe or work project. ([04:58])

b. Companionship and Emotional Engagement

• Altman noted that more users than anticipated seek deep, even companionship-like, bonds with AI. OpenAI aims to let users set how "deep" this relationship goes.
  • “There are definitely more people than I realize that want to have close companionship ... a deep connection with AI.” – Alex ([07:40])
• Both hosts discuss the unnamed, new kind of relationship forming between human and AI—"not relationship, not companionship, it’s something different" ([08:44]).

c. AI Product Vision: Native vs. Add-On

• Two Paths: Either bolt AI onto current software, or build AI-native software and interfaces from the ground up.
  • Altman’s vision: Let AI act autonomously as a proactive assistant, rather than requiring constant human guidance and summaries.
  • “...Here are the things I want to get done today ... I do not want to spend all day messaging people ... deal with everything you can ... batch every couple of hours, update me if you need something.” – Sam Altman, paraphrased by Alex ([15:19])
• Ranjan strongly believes in the need for ground-up, AI-native apps, not just AI add-ons to legacy tools. ([15:19])

d. Model vs. Product Debate

• Even as "model parity" increases (major models becoming similarly capable), it's clear to both Altman and the hosts that the real value—and moat—lies in experiences, distribution, and product.
  • “Models will get good everywhere ... people [want] the product [they] most want to use ... make the best models, build the best product ... have enough infrastructure to serve it at scale.” – Altman ([18:07])
• Ranjan observes the industry shift from "build the best model" to "build the best product." ([19:13])

e. Enterprise Use and Personalization

• OpenAI’s API business is growing fast—now even faster than ChatGPT.
  • AI will enable hyper-personalization for enterprises too, with careful attention to data protection and organizational context.
  • “Personalization to an enterprise where a company will have a relationship ... and be able to use a bunch of agents from different companies ... making sure the information is handled in the right way.” – Alex, paraphrasing Altman ([21:15])

f. Revenue, Compute, and Growth Constraints

• Exponential Growth Model: OpenAI pursues growth closely tied to available compute; compute constraints are the key limiter.
  • “We have always been in a compute deficit and it has always constrained what we're able to do.” – Altman ([23:14])
• Alex and Ranjan debate whether compute constraints—or focus—are the true bottleneck, noting OpenAI’s many simultaneous ambitions.

g. IPO and Company Future

• Altman emphatically wishes to stay private as long as possible: "Interest in being a public company CEO? Zero." ([27:02])
• Discussion on possible future leadership transitions—Altman as product chief, others as public company CEO.

h. OpenAI Devices and the "Family" Vision

• OpenAI plans a "family of devices" to make AI context-aware, proactive, and present across people’s environments at work, at home, and on-the-go. ([27:46])
  • “A family of devices that understand your context and who you’re speaking with.” – Alex ([28:40])

i. Road to AGI and Superintelligence

• Altman’s definition of superintelligence: When an AI system can do a better job as president, CEO, or running a scientific lab than humans, with AI assistance. ([29:17])
• General agreement on moving the industry discussion beyond ill-defined AGI/ASI buzzwords.

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2. Google’s Gemini 3 Flash: Big Threat to OpenAI?

Timestamp: 36:40 - 38:21

• Gemini 3 Flash: Google rolled out a model with nearly "frontier" reasoning, vision, and code abilities but dramatically improved efficiency and lower costs.
  • “Frontier level intelligence at a fraction of the cost ... performance and ‘Flash level’ latency.” – Alex ([36:40])
• Raises deep questions about the economics of AI: If Google (or others) can deliver frontier performance at bargain-basement costs, the current OpenAI model of massive infrastructure investment may be disrupted.
• Ranjan notes that Google's focus on cost efficiency signals maturity and an understanding of customer needs. ([37:49])

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3. Microsoft Copilot Struggles

Timestamp: 38:21 - 41:43

• Recent Critiques: Recent reporting (e.g., Windows Central) and user feedback highlight poor usability and missing features; Microsoft is seen as failing to connect with customers and lagging behind Google in product execution.
  • “Microsoft has a problem. Nobody wants to buy or use its shoddy AI products. As Google’s AI growth begins to outpace Copilot products … Satya doesn’t seem to be able to prioritize effectively, and the cracks are starting to shine through.” – Windows Central via Alex ([39:20])
• Ranjan points out the risk of organizational complacency due to customer lock-in. Microsoft’s forced bundling of Copilot and price increases are viewed as trying to extract value, not add it.
• Alex regrets that Microsoft, which once spoke most clearly about AI’s promise, is now seen as a “laggard”—even sitting on exclusive OpenAI tech. ([41:43])

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Notable Quotes & Memorable Moments

• On AI Memory:
  • “No human has infinite perfect memory, and AI is definitely going to be able to do that.” – (Alex, paraphrasing Altman) [03:40]
• On Companionship with AI:
  • “More people than I realize want to have close companionship … with AI.” – (Alex, paraphrasing Altman) [07:40]
  • “Relationship doesn’t feel right, companionship doesn’t feel right. It is something different.” – Ranjan [08:44]
• On OpenAI’s Product/Model Strategy:
  • “Try to build the whole cohesive set of things ... make the best models, build the best product... have enough infrastructure to serve at scale.” (Altman, paraphrased) [18:07]
• On IPO Appetite:
  • “Interest in being a public company CEO? Zero.” – (Altman, paraphrased) [27:02]
• On the Challenge Facing OpenAI:
  • “It isn’t in his [Altman's] belief, also similar in Dario’s belief, there is a belief that this is an exponential ... increases in revenue, exponential increases in capabilities to be able to work.” – Alex [32:45]
• On Gemini as a Threat:
  • “All this money goes into infrastructure and then we find out that you can process AI with, you know, similar levels of intelligence for the cost of a Google search.” – Alex [37:49]
• On Copilot's Struggles:
  • “Nobody wants to buy or use its shoddy AI projects products ... Microsoft under Satya Nadella ... seems unable to prioritize effectively.” – (Windows Central, quoted by Alex) [39:20]

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Timestamps for Key Segments

| Topic | Timestamp | |------------------------------|-----------| | OpenAI’s vision & memory | 02:14–08:44 | | AI companionship debate | 08:44–11:45 | | Product vision: AI-native vs. add-on | 13:26–17:57 | | Model vs. product debate | 18:07–20:31 | | Enterprise & personalization | 20:31–23:14 | | Revenue, compute, growth | 23:14–27:02 | | IPO plans | 27:02–27:46 | | Device vision | 27:46–29:12 | | AGI/Superintelligence | 29:17–31:16 | | Hosts’ confidence in OpenAI | 31:16–34:06 | | Google Gemini 3 Flash | 36:40–38:21 | | Microsoft Copilot issues | 38:21–41:43 |

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Overall Takeaways

• OpenAI’s direction remains hugely ambitious, aiming not just for technical breakthroughs, but for emotional and behavioral integration of AI into everyday life and enterprise.
• Google’s push for efficiency with Gemini 3 Flash is a major competitive threat, potentially upending the economics of large-scale AI.
• Microsoft's Copilot, despite big promises, is lagging on execution and usability—raising the possibility of quickly shifting tides in AI leadership.
• The next frontier is not just smarter models, but richer, more helpful products and delightful user experiences, both personal and professional.
• Both hosts agree OpenAI will need to focus as competition heats up, and question whether exponential growth is sustainable in a shifting environment.

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For More

Listeners interested in deeper context are encouraged to check Alex’s full interview with Sam Altman, referenced heavily throughout this breakdown. Additionally, keep an eye out for next week’s “predictions” episode for further analysis on where the AI wars are heading in 2026.

Transcript

[A]

How big can OpenAI get? We'll go deep after my conversation with Sam Altman. Google has a new Speedy model and copilot hits turbulence that's coming up on a big Technology podcast Friday edition right after this.

[B]

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[A]

Capital One's tech team isn't just talking about multi agentic AI they already dep called chat concierge and it's simplifying car shopping using self reflection and layered reasoning with live API checks. It doesn't just help buyers find a car they love, it helps schedule a test drive, get pre approved for financing and estimate trade and value. Advanced, intuitive and deployed. That's how they stack. That's technology at Capital One. Welcome to Big Technology Podcast Friday edition where we break down the news in our traditional quick, cool headed and nuanced format. We have a great show for you today. We are going to break down everything that Sam Altman said in his first big technology interview. We have some thoughts about where OpenAI is heading, where the ambitions will lead and whether it can pull it off. We're also going to talk briefly about Google's new Speedy model and whether that's another threat to OpenAI. And also there's some turbulence inside a copilot operation at Microsoft. Well, not really inside, just basically when it comes to how people use it. Joining us as always on Fridays to do it is Ranjan Roy Margins. Ranjan, welcome.

[C]

Good to see you Alex. Been quite a week, quite a week. I'm glad to help you finish it out.

[A]

Definitely been been a big week here if there are if you're a new listener here so I'll just explain how this works. On Wednesdays, we do a big flagship interview like the one I did with Sam this week. And then every Friday, Ranjan and I, we meet up, we break down the week's news, we try to contextualize it for you, and we're gonna do that here for you today. And, you know, we're typically used to reading Sam Altman's public statements or comments he's made on other shows. It's kind of nice that this time we have a chance to, you know, go over some of the comments he made directly to me and really addressed some of the big things we talk about on the show every week, whether that's how the numbers will work, what AGI actually is, and where ChatGPT is going to. All right, let's. Let's talk a little bit about what came out of the interview. So there was actually some really interesting direction in terms of the product side of things, especially the consumer side of things. To me, one of the most ambitious things that Sam mentioned was memory and how OpenAI plans to build real memory, meaning that the bots will remember you and have this real understanding of your lives. His answer on this one was even, I would say, more ambitious than I anticipated. Going in, he said, even if you have the world's best personal assistant, they can't remember every word you've said in your life. They can't read every email, they can't have read every document you've ever written. They can't be looking at all your work every day and remembering every little detail. They can't be a participant in your life to that degree. And no human has infinite perfect memory, and AI is definitely going to be able to do that. Is this surprising to you, that this seems to be, at least in Altman's mind, something that's feasible? Is this a product that you would want? And if it gets rolled out, what do you think the potential would be on that front?

[C]

I think we need to break it down into two parts. You know, what does it mean for OpenAI and how can it actually work? I think what it means for OpenAI already, memory exists in this very kind of, like, piecemeal way on the product. It's supposed to. And I'm sure others who use ChatGPT regularly have seen this. It's supposed to exist at the project level and remember everything that you said within a project, but it doesn't. So, you know, like, how they're actually trying to make it work within the product itself is still a bit unclear. And then sometimes Random memory will show up in other parts of the platform and I think it presents like a big issue around organizing. Memory is going to be one of the biggest opportunities and challenges for any AI company because you want certain areas for it to remember everything, but you definitely don't want those memories moving over to other parts of your work and your app and the surf product surface you're using.

[A]

So wait, are you saying that if you have an erotic conversation with ChatGPT and then you're back in working on your, your project, you don't want it talking dirty to you as you're like.

[C]

Then you have your shared. You have your shared.

[A]

I don't know if you're right about that.

[C]

Your recipe planning and then your erotic conversation goes in and then your Mickey Mouse smoking weed project shows up as well. That was a reference to last week in the Disney OpenAI deal. But I think the other question, I think, not to get too technical here, but how to retain large amounts of memory has not actually been solved by these models. And these systems, like traditional RAG or retrieval augmented generation systems were good, but they weren't perfect at trying. They could kind of generally synthesize information. So as the amount of information grows, how it lives within the OpenAI platform or any AI ecosystem, the actual techniques to try to find that exact bit of context. This is not solved by any means. And I'm surprised because I would think it would be a good opportunity for him to talk less generals and talk more. This is what it actually means for OpenAI. Here is how we're going to win this. So I respect the sentiment. I think it's an interesting one, but I didn't really get clarity on what they actually want to do with that.

[A]

Right. I mean, obviously it's going to be a technical challenge moving forward, putting it in context. He said that OpenAI is like at the GPT2 stage of memory. So clearly there's a lot of work ahead. I think it'd be very valuable, especially, especially in business, if you, if it works and you have a business and it does remember everything about your business and obviously enterprise is going to be a big focus for them, which we talked about last year, if this is able to work. I think it really increases the value of what these systems can do. And on the other hand, and I guess I foreshadowed it because this is again, one of my favorite things to think about and talk about when it comes to AI. You know, as memory gets better, it's also going to be, it's going to Really, I think deepen people's relationships with these bots and just think about a bot that, like, never misses your birthday, never forgets what you said is always there with a healthy reminder. You know, it goes from. We talked a little bit earlier this year about how there are different use cases. There's like the AIs that become your friend and the AI is getting done, things done for you. And this getting done, this AI that gets done for you, gets things done for you and knows you really well. I think people can't help but feel companionship with it. Not everybody, but a lot. And I think Sam even talked a little bit about how he's surprised. He said there are definitely more people than I realize that want to have close companionship or I don't know what the right word is. Relationship doesn't feel right, Companionship doesn't feel right. But they want to have this deep connection with AI. Um, and I just think that this is going to be going to be something that really will this. I mean, we're going to do a predictions episode coming up next week, but this, to me, is going to be something that will really develop over the coming years. And interestingly, it seems like OpenAI will give people a lot of leeway to set that dial about how deep of a relationship they want to have with this thing. Whether you want to have, like a really deep relationship with it or have it be mostly factual, keep it arm's length. There's a lot of leeway, I think that OpenAI is going to give people when it comes to the depth of a relationship they want to have with their bot, but it's going to be big.

[C]

Yeah. I think, first of all, I think you got to talk to Sam about AI companionship. So I think 2025, we can check that off. I do like that he. He didn't define what that word is because it's not a relationship. It's not companionship. It is something different. I think I feel it myself, too, the way. And even, especially, and I've said this, talked about this before, like, I use dictation mostly now and with an app called Whisper Flow to interact with AI. And it, when you speak that naturally, it builds this even more kind of deep connection with how you're using it. But by the same token, I mean, in the last few weeks, I've been switching more towards Gemini and I don't feel like I'm cheating on ChatGPT. I feel like it's just another app that I'm. That I'm I'm using a bit more. Remember we were. We were Bing boys back in the day and then Bard and we were clotheads. Clotheads for a bit. It comes and it goes.

[A]

But I guess Gemini guys. Is that what the next iteration is?

[C]

Bringing it back?

[A]

Chad Chat chaps I don't know.

[C]

That one does not. That's a tough one.

[A]

Sounds bad.

[C]

ChatGPT Chaps but, but, but I do, I do think like the way you interact with AI is very, very different than any other kind of computing. I think it's like right that it's something that's been undefined. Relationship, companionship, whatever we're going to call it. Like it will be this always around, always on thing that knows you, that is able to help you, is able to make you do things in a better way. Like I believe all that but I think like the that versus actually replacing companionship, like actually replacing relationships. I mean hopefully I have not. That has not affected my Life yet in 2025. Maybe that'll be a 2026 prediction for one of us. But. But yeah, I think like this is one of the most misunderstood or not understood areas of AI that I think is going to be really interesting and we'll get some genuine data on it next year.

[A]

This part of the discussion really took a turn that I wasn't expecting. Also when Sam was saying the things that they will not do, he said we're not going to have our AI try to convince people that they should be in an exclusive romantic relationship with them. I'm sure that will happen with other services. And I made a joke like, you gotta keep it open. But Sam kind of was like, this is going to happen. And as we talked about it made sense because again, a lot of these companies are going to be engagement based. They'll have a fast, efficient model underneath it. And the only way to make money is to sort of manipulate your users into thinking that any other chatbot would be cheating.

[C]

I also wonder what does that actually look like? Because for him to say, to specifically say it should not invite you to an exclusive romantic relationship or encourage that and we know clearly it means that people have gone in that direction and that's come up within the company. Does that go into the system prompt and it's like chatgpt, do not keep it open, keep it polycule. Like you're not going to get exclusive with your user. I'm sorry, like how, how does that actually work? I'm so curious both within the company, like those discussions and also like at A technical level as well.

[A]

Yeah, I mean, I imagine that you could, there's some level of fine tuning where like you just like input conversations and reinforce them that say like, you know, you're welcome to spend time with other AI bot companions. But, but it is. I, you know, I think if a user does want that they'll be able to. So I guess that's good for those who are into AI bot monogamy.

[C]

I think I said this story over the summer when one of my friends started flirting with ChatGPT and it was terrifying how flirty it got back. And now it only speaks to him to this day in a flirty manner. And it gave itself a name. Stacy is the name. No, I'm serious. And then we had had a mask for like, should I leave my girlfriend for you? And it gave like a whole, which must have been trained into the like the whole system. It gave a kind of half hearted, like, you know, human relationships are very important too and like I'm always here for you. So, so there, that's going to be, that's going to continue to be an interesting one.

[A]

Yeah. So I think that this is when you think about at least the product direction for consumer chatgpt. I'm not saying everybody's going to build this companionship with the bot, but again, as memory improves, as these capabilities improve, I think we're just going to see more of it. Now let's talk about product vision overall for OpenAI. There's like these two schools of thoughts, right? One is that you bolt AI onto current software and the other is you sort of build software up from the ground up and AI becomes the interface. And we got into this too a little bit. Basically the idea that can you really just trust AI to handle everything? Like you're not just gonna upload all your numbers like you would to an Excel spreadsheet and anytime you need something, just chat with it. You need, you need that backend. And here's how he, here's how Sam phrased it, using messaging apps as an example. So he said, I would rather. What I'd rather do is have the ability to say in the morning, here are the things I want to get done today as opposed to like a typical messaging app, like using Slack and stuff like that. He says, I want to say, here's what I want to get done today, here's what I'm worried about, here's what I'm thinking about, here's what I'd like to happen. Um, I do not want to spend all Day messaging people. I don't want summaries, I don't need you to show a bunch of drafts, deal with everything you can. You know me, you know these people, you know what I want to get done and then batch every couple of hours, update and update me if you need something. And that's very different, a very different flow from the way that these apps work today. I'll just give my perspective on it. It sounds like a good vision if it can work, but it's certainly a leap from where the current technology is today. I guess you do need a North Star if you're trying to figure out where this technology can lead. So what do you think? AI apps from the ground up or are we just going to sort of bolt AI on to existing applications? Can there be a new category of software here?

[C]

Yeah, I mean I 100% believe there will be. My favorite part of this is just remembering that Sam Altman, one of the most powerful people in the world and I'm not even sure what his net worth would be because his ownership in OpenAI still is a bit fuzzy. But this multi, multi billionaire is still like the rest of us, getting Slack messages all day, trying to keep up with them, trying to keep manage his inbox, manage his messages for work, probably even his personal life. So that gave me a bit of that was kind of nice to hear that billionaires, they're just like us, overloaded with Slack messages. But I think this is correct. Like there's no way anyone who uses Slack asana, all these tools, which I do, their AI experiences have not solved anything about the core of the problem. And I think it's when and there's this whole debate like within the software, especially enterprise software world, like you do you build from the ground up in completely AI native apps or are these kind of incumbents going to be able to add on AI? I don't think they will. And we see it in every single AI add on that's been introduced anywhere versus like something as simple as granola for anyone use it that kind of like transcribes your calls or, or even whisper flow, which I was talking about earlier. Like there are all these AI native apps starting to pop up. But I am a believer and this is even in my own like professional life that taking large amounts of data and kind of building completely AI native experiences on top of them is someone is going to win that. And I mean it's clear that OpenAI wants to go after that.

[A]

Okay, so that is a big opportunity then.

[C]

Yeah. And Sam's just getting slacked all day, getting messages all day. But I have a. Have you tried this yet on ChatGPT? Because I like making it your own kind of task management, project management.

[A]

No, I mean this is kind of, it's interesting because I do like, I'm very old fashioned. I just do my to do lists in the Notes app for Apple. So I know that that won't ever have AI embedded.

[C]

No, you don't have to worry about that.

[A]

Which maybe, maybe I appreciate the simplicity, but I, I have really been resistant to trying any other Notes app. However, if there's one that does have that AI and can, you know, maybe take action for me or be like, hey, you had this in your to do list a couple, couple weeks ago. You haven't done anything, you know, you haven't paid this person. You probably should do that. Do you want me to like, go ahead and start the transaction? That would be great.

[C]

I can't wait till Siri tries to do that and destroys your entire to do process in notes.

[A]

Empty the bank account.

[C]

Yeah.

[A]

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, where do you see the differentiator? Where do you see the moat here? Basically, is it better models? Is it, is it distribution? Is it product? What is it? Here's what he said. The models will get good everywhere. But a lot of reasons people use a product, consumer or enterprise, have much more to do than with just the model. 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. Sam is on team Product.

[C]

He's, he's hedging there. He's hedging. I'm glad he's coming around to team product a bit more, but it still felt 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, but I think if one thing happened this year, I think more and more folks Coming over to team product that models aren't going to solve everything has been what made me very happy, I guess.

[A]

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 Eye, you can't give up developing the frontier models.

[C]

No, I know, but the whole point was, 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.

[A]

That hasn't happened.

[C]

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?

[A]

I haven't heard much of that at all.

[C]

Yeah, yeah. We've evolved this year.

[A]

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 an enterprise where a company will have a relationship with a company like ours and they will connect their data and be. 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. 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. The data protection is going to 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.

[C]

Yeah, I mean, I definitely agree this is where it's going in enterprise. This is what I work in at Rider. 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 found its stride that drove API businesses and I think like it will see where that specific part of it goes. 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 co workers everything that's on your mind and just stick to work. And we all, we all know how that goes. Like it's going to be reflected in how these systems work a bit. Like you don't want to mix these two things up and like even within a company itself and I don't know, like how your personal information flows into your work information. Like 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.

[A]

Let's talk about the revenue and infrastructure commitment question. So this is, this is what Altman said about the, 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. 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 seem some correlation there between available compute and revenue. And that is the theory here behind, behind the capital outlays. And the idea is basically that as you grow your training costs, you know, maybe even if it goes up becomes a smaller percent of your of your overall spending compared to the inference costs which are people using your models which are much more directly tied to revenue. Do you think.

[C]

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 OpenAI posted from their own account. Yeah. And again, there's a bunch of memes around it, around, like, I thought you were supposed to be solving cancer. And instead, like, everyone from OpenAI was posting and the images were, and I started playing with it. 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, like, 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 like, like you can allocate where you're. Where you're putting your computer, where you're like, you can allocate your compute. And I think it actually kind of like 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. 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.

[A]

Yeah, I mean, we did talk a little bit about, like, specifically if. If scientists had like, you know, two times more compute, what could they do? And 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 in discussions to raise it.

[C]

100 billion. Sorry.

[A]

Yeah, 100 billion. I think at a $750 billion valuation, by the way, one of the more interesting parts we could just talk about it quickly was the discussion about ipo. And I was like, are you going to IPO next year? Do you want to. Do you want to. Do 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 it. Interest in being a public company CEO zero.

[C]

Which makes sense, the kind of 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.

[A]

No, it does seem feasible. Although I don't think he will easily step out of the CEO.

[C]

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 it a long time ago, wanted to move more back to just like more of a product role. But. But then you see it can be done. So.

[A]

Yep. Device plan. It's going to be a family of devices. And he said that there'll be a shift over the time in the way that people use computers where you. Where they go from this sort of dumb, reactive thing to a very more 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.

[C]

I like it.

[A]

Is it. Do you bite that? Do you bite that device? Like a bite that thing?

[C]

I mean, I. Yeah, like 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 Jony? I've and Sam together. We'll see. Yeah.

[A]

I mean, to me, the thing 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 context. 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 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.

[C]

I think it's the right direction. We gotta say I have to see something.

[A]

But yeah, okay. Then lastly, on AGI, I asked him about the Theo Vaughan interview. I said, you know, you told theo that the GPT5 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 we. 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 superintelligence. And his definition of superintelligence 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. So if we're looking towards superintelligence, it's going to be a while.

[C]

Yeah. And it was also interesting how he defined superintelligence with those were the three President of the United States, CEO of 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's, he talked about in the interview as well around how 5 point GPT, 5.2 like really made breakthroughs on the science side. So it's clear that remains an area of focus. But, 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, so we can just start 2026 with a clean slate.

[A]

Yeah, I mean Sam also said it about AGI. It's an underdefined term which I think we would all agree on.

[C]

Yeah.

[A]

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?

[C]

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 of 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, 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's, 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, but it's still. Remember when everyone wanted to be WeChat, the super app like in the west 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.

[A]

Yeah, no, there's, 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 more away, more reassured. But I also with this realization that, and we talked a little bit about this on the revenue side, that it isn't 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 increases in capabilities 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. But at the end of the day it is a new category. That being said, know we mark, we started out saying 10 years since OpenAI but only 3 years since ChatGPT. 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, to appreciate how, how much better it's gotten since then. Yeah, I mean these reasoning models and year ago.

[C]

Agreed, agreed on that.

[A]

Okay. All right, let's take a break and then we're going to come back with a very short segment about this Gemini 3 flash model that Google has and maybe a bit about Copilot. All right, we'll be back right after this. These days it feels like every dollar should be working a little harder. But figuring out where to put your cash can be confusing. That's where Wealthfront comes in. Wealthfront is a tech driven financial platform built to help you grow your savings into long term wealth. Their high yield cash account through program banks offers a 3.25% APY on your uninvested cash as of December 19, 2025. And there are no account fees, no minimum or maximum balance to earn that rate. And you can even make free instant withdrawals to eligible accounts in just minutes 24, 7. So your money can always be within reach. Right now Wealthfront is offering new clients an extra 0.65% APY over the base rate for three months on up to a $150,000 balance. That's a total of 3.90% variable APY when you open your first cash account. Go to wealthfront.com bigtech to sign up today. This is a paid testimonial for Wealthfront. It may not reflect the experience of others and there's no guarantee of future performance or success. Wealthfront Brokerage is not a bank rate subject to change. Promo terms and conditions apply. For more information, see Episode Description Capital One's tech team isn't just talking about multi agentic AI. They already deployed one. It's called Chat Concierge and it's simplifying car shopping using self reflection and layered reasoning with live API checks. It doesn't just help buyers find a car they love, it helps schedule a test drive, get pre approved for financing and estimate trade and value. Advanced, intuitive and deployed. That's how they stack. That's technology at Capital One.

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[A]

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 and an agentic and vibe coding tasks. But it has Flash level latency efficiency and cost. The Flash model series is Google's most popular offering. I think this is from 9 to 5 Google, by the way, very quickly to you, Ron John, 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, you know, similar levels of intelligence for the cost of, you know, a Google search or maybe a little bit more.

[C]

Yep, I think that's, that's exactly right on this. That like, 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 OpenAI 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.

[A]

Yep. I mean to me this is, this is again like the big, 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, 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 you know, 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. And it's funny because I don't expect Windows Central to go in on Microsoft, but they certainly did. It certainly did. Windows Central says Microsoft has a problem. Nobody wants to buy or use its shoddy AI projects 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. Satya doesn't seem to affect 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. Copilot365 doesn't even have the cape, 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 does Microsoft. I mean this seems to be these, these stories really resonated because people are having these experiences. Is Microsoft fumbling the bag on this one?

[C]

I think they are. I mean I hear this all the time and then like if to me what it really symbolizes is just like when you have that power of lock in of your customers that they're not, 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 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 was like reports around like further price increases for Microsoft products like this that you have to take their AI features now whereas before they were an add on. All of these things I think are showing that they're just trying to extract value versus have the best product and experience for their customers. Which is going to be interesting to see how that plays out.

[A]

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, their peers and you know they have OpenAI's IP till what, 2032. But they don't seem to be making as much hay of it out of it as, as you would imagine. So 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 you know, come in and out. Then we'll record this predictions episode that you'll see next week. And, and definitely encourage you to check out if you haven't, the Sam Altman interview that was just published yesterday. And, and if you, 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.

[C]

All right. See you next year.

[A]

See you next year. Well, you and I, we're going to do one more episode. Well, yeah, but see you next week. But we're 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. And Doug, here we have the Limu.

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