New ROI Questions For AI, Microsoft’s Empire Plans, Jassy’s Amazon Comeback

Tom Dotan from the Wall Street Journal joins us for our weekly discussion of the latest tech news. We cover 1) What slow growing GenAI consumer usage says about the field 2) OpenAI's five levels of AI sophistication 3) Why enterprise rollouts of AI technology are moving slow 4) Is AI a startup game or scaled player only discipline 5) How small models fit in 6) Bing's failed run after Google 7) Sequoia's $600 billion question on AI 8) Can we use leftover GPUs to break out of the simulation 9) Microsoft plan to build an AI empire 10) Amazon's comeback under Jassy after a rough start --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. For weekly updates on the show, sign up for the pod newsletter on LinkedIn: https://www.linkedin.com/newsletters/6901970121829801984/ Want a discount for Big Technology on Substack? Here’s 40% off for the first year: https://tinyurl.com/bigtechnology Questions? Feedback? Write to: [email protected] Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Alex Kantrowitz?

  Tough questions about the AI business are starting to be aired loudly. Microsoft Satya Nadella is seeking to build an AI empire beyond OpenAI, and Andy Jassy's Amazon is thriving after a bumpy start. All that and more is coming up right after this. This episode is brought to you by Genesis. What does it actually take to put a Gentic AI to work across an entire enterprise? I recently spoke with Genesis chairman and CEO Tony Bates about why orchestration is emerging as a competitive advantage in customer experience and what companies need to get right in the AI era. Then I sat down with Adam Mitchell, head of enterprise business solutions at Voya Financial, to go inside a large-scale Agentic CX transformation,

• 0:43Alex Kantrowitz?

  including the business decisions, trade-offs, and lessons along the way. You can watch both conversations now on my YouTube channel today. It's never been more challenging to get frontier compute. How do you know where to look, who to trust, or how much to pay? Akash is an open cloud that provides easy access, flexibility, and peace of mind. That's how companies like Razer were able to cut their inference cost by 15 times. Visit akash.network/alex for a free consultation. That's akash.network/alex for a free consultation.

• 1:19Alex Kantrowitz?

  Welcome to Big Technology Podcast Friday Edition, where we break down the news in our traditional cool-headed and nuanced format. We have a great guest for you today. Helping me anchor the show is Tom Dotan. He's a reporter for The Wall Street Journal covering Microsoft and all things AI. Tom, great to see you. Welcome back to the show.

• 1:36Speaker 01

  Thanks. It's a, it's a big honor. I'm feeling cool-headed.

• 1:40Alex Kantrowitz?

  All right. Well, let's, let's see if we can maintain it through the course of this episode. One of the things that has my head a little bit in a place where I'm scratching it is this disconnect between the actual fruits of the AI moment and the promise. And I spoke about it with Matt Wood from AWS on Wednesday, and it just so happens that many posts are starting to show up with these similar themes. So Bendick Evans, the analyst, also a friend of the show, has just put out this post called AI Summer, making the point pretty well that like we've been promised a lot, but is it adding up? So

• 2:22Alex Kantrowitz?

  He said about ChatGPT for consumers, ChatGPT is just a website or an app and it could ride all the infrastructure built over the last 25 years. So a huge number of people went off to try it last year. The problem is that most haven't been back. If you ask what they used, what they used it for, it turns out that most people played with it once or twice, only to go back every couple of weeks. And here's his bottom line. If this is the amazing magical thing that will change everything, why do most people say in effect, very clever, but not for me and wander off with a shrug? And why hasn't there been much growth in the active users as opposed to the vaguely curious in the last nine to 12 months? I think it's a really good

• 3:05Alex Kantrowitz?

  point. I think he really nails sort of the big question about this moment in the AI quote unquote boom. And I'm curious what you think.

• 3:14Speaker 01

  Does he say in this post what the latest active user numbers are? I have not kept up with it. And I know that last year they were talking about 100 million and they kept changing 100 million what? Like it was 100 million weekly active users. Initially, it was daily active users. I haven't seen a new figure. Does Benedict have a new one there?

• 3:32Alex Kantrowitz?

  He doesn't have a new one in the post. The most recent number for ChatGPT from OpenAI is still 100 million users.

• 3:39Speaker 01

  Yeah.

• 3:40Alex Kantrowitz?

  So people say like they're whispering, at least what I've heard in sort of the backroom says it's sort of up to 200 million now, or maybe a little bit more. But we haven't seen the sort of exponential growth that you might expect. If it is, is like Benedict is saying, this like unbelievable invention that's about to like mirror human reasoning.

• 4:01Speaker 01

  If it's 200 million, they should have put it out by now because this 100 million figure has been it for a while. And I remember last year, they had a developer day conference where I think a lot of people were expecting, a few days after that, Sam Altman got fired, by the way.

• 4:15Alex Kantrowitz?

  Maybe it's because he didn't have that 200 million number.

• 4:17Speaker 01

  Yeah. If only it were that clear. If only that's what it were about. I would have, that would have saved my Thanksgiving. If it were that simple.

• 4:24Alex Kantrowitz?

  I apologize to you, man. That was a rough one, right?

• 4:26Speaker 01

  Yeah. Real low point personally for me, let alone Sam. I don't care. But for me, it sucked.

• 4:33Speaker 01

  Yeah, there hasn't been a new number in a while. And I think that to a degree is a red flag because if this is supposed to be, and this was initially touted as the fastest growing consumer app of all time and the fastest to get to 100 million, which It means something, but if the gap between 100 million and 200 million is starting to get longer and longer, and we're not seeing the same sort of growth we saw at first, I think it's reasonable to temper expectations and say, you can't just map it alongside every other consumer app like Facebook or Uber or something like that, where you saw this exponential growth that continued past 100 million and say like, oh, it's going to be the next that. Like, if it really has reached a ceiling, doesn't mean it's a disappointment, but it's certainly not the thing that people initially thought it was going to be.

• 5:18Alex Kantrowitz?

  Right. And maybe it's just because the models need to get a little bit better. I don't know if you saw this, but Bloomberg had this report that OpenAI had a bunch of different levels on the stages of artificial intelligence as we make our way towards superintelligence. So I shared this and a lot of people got mad at me because they were like, oh, you're just sharing OpenAI propaganda. First of all, I'm just putting it out there, not like, you know, saying that this is to be believed or, you know, sort of standing by what OpenAI is saying. But I think we should talk about the different levels. So for them, they say level one is chatbots, AI with conversational language. Level two is reasoners, human level problem solving. Three is agents, systems that can take action. Level four is innovators,

• 6:00Alex Kantrowitz?

  AI that can aid in invention. And level five is organizations, AI that can do the work of an organization. And they say that we are past level one, approaching level two, at least that's what they say internally at OpenAI. Is this a matter of like, we're not using these chatbots as much because they're just not useful to the point where like, when they, maybe when they get to level two as reasoners or level three as agents, those daily, those, you know, active user numbers will go through the roof?

• 6:30Speaker 01

  Yeah, I guess it's all a matter of utility, right? The other things that they're trying to achieve here are more difficult, but also more useful to people. So I actually kind of question their strategy in releasing this kind of scale publicly because

• 6:46Speaker 01

  If you are not able to actually hit these new levels over the next year or few, because the technology hasn't grown in sophistication, I mean, it's all very arbitrary, right? So like, there's an argument to be made that like, they can claim they've hit level three, level four, whatever that means, because they've decided they've hit these levels. But if the technology that underpins all this stuff isn't going to get more powerful and sophisticated over the next couple of years, then you've basically just told the world, "Yeah, we don't really have it. Like, there is promise with this technology, but we're not going to be able to deliver on it because we can't, you know, the scaffolding that needs to exist in order for this to get there is not achievable yet."

• 7:28Speaker 01

  So I actually, I mean, I imagine they put it out because they think they will, but if they don't, they kind of dug a hole for themselves.

• 7:35Alex Kantrowitz?

  Doesn't it remind you a little bit of like, the five stages of self-driving cars?

• 7:40Speaker 01

  Self-driving cars.

• 7:41Alex Kantrowitz?

  Yeah, I agree maybe that too, but like, but really, like, we've been waiting to get to sort of like, level five autonomy and just kind of stuck on level two forever.

• 7:49Speaker 01

  What did that mean again? What did level five autonomy mean? I know what you're talking about, but I can never remember what that meant.

• 7:54Alex Kantrowitz?

  I'm just going to give you directionally what it is. Like, level one is driving a car with a steering wheel, and level five is like, fully autonomous vehicles.

• 8:01Speaker 01

  Right. Well, what's interesting with that is, I remember covering tech back when people were talking about that. That was like, 2015, 16, and Uber, or, well, Uber was very big into it, and Google, and self-driving cars seemed like it was kind of a, kind of a mistake, it was just kind of a dud. They never really were able to get it on the streets, and you know, now in San Francisco, the Waymos are everywhere, and I gotta say, it's pretty great.

• 8:29Alex Kantrowitz?

  They're amazing.

• 8:30Speaker 01

  Yeah, it's a, it's a very good experience. I'm embarrassed to say how much I like them.

• 8:35Alex Kantrowitz?

  Oh yeah, I'm with you on that. It's the one, I mean, it's, I think it's the coolest tech I've tried in recent, in the past few years, without a doubt.

• 8:43Speaker 01

  Yeah, and so, I mean, there's probably still many levels to go for it to be what the promise was, you know, a decade ago or so, but like, they've really achieved it. It's at least more than I thought they were going to. But yeah, there is definitely a parallel between the two, and You know, I guess if you want to give OpenAI or AI in general, the benefit of the doubt, like self-driving, it got there, or it got there more than a lot of skeptics thought it was going to. And so, you know, maybe just give them more time is the smartest way to think about it. I don't know.

• 9:12Alex Kantrowitz?

  Right. And then the question is, okay, is this just a patience game, right? Because the first group of entities that are going to start deploying this stuff is going to be the consultants, really, or the B to B partners of these companies that are trying to put it into play in an enterprise situation. And I spoke with a bunch of Amazon folks this week, and Bendick highlights this in his post, that it really is sort of a moment where the rubber is meeting the road for AI, and it's going to take longer than a lot of people thought. So here's just a couple of stats that I'm pulling out from his post about the consultants. So he said Bain tried to split pilots, experiments, and trials. And he said everyone had a bunch of tests as far as AI goes,

• 9:56Alex Kantrowitz?

  but far fewer people are trusting something in their business to this yet. Accenture, he said, proudly announced that it had already done 300 million of generative AI work for clients, and that it had done 300 products. And he says, even an LLM can divide 300 by 300. That's a lot of pilots, not deployment. And I just published this in Big Technology Today, citing from a Gartner poll of organizations interested in artificial intelligence. And the Gartner poll had more than 1,000 organizations responded. Only 21 of the companies surveyed by Gartner said they had gen AI in production, that's this year, and the rest were either piloting or exploring the technology.

• 10:40Alex Kantrowitz?

  And this is what Bendick says about this. What happens when the utopian dreams of AI maximalism meet the messy reality of consumer behavior and enterprise IT budgets? It takes longer than you think, and it's complicated.

• 10:55Speaker 01

  Yeah. Yeah, I think that's I think that's spot on. And it's something I've been thinking about a lot, reporting on the space, because I cover enterprise software companies for the Journal, and that's ground zero, right, for adoption of this stuff. Like, these are the guys with the big budgets. You know, Microsoft is pushing their copilot, their agents, as hard as they can to all their customers. And, you know, I don't have data yet on how well that's doing on its own, but I can tell you on the startup level, there have been a lot of companies that were building enterprise software, AI enterprise software, that are in a tough spot right now, because they're just not, there's not a lot of business, and a lot of revenue yet, people aren't buying it yet.

• 11:34Speaker 01

  And I feel confident enough saying that there was a miscalculation by a lot of investors in AI, that there was going to be quicker adoption to this. I really think they saw the rise of ChatGPT, and the fact that it reached this hundred million user level within a record amount of time, and just assumed that everything was gonna follow in that footstep, in those footsteps. And it was gonna be, you know, not only they're gonna fall in those footsteps, but the revenue is gonna, that spigot's gonna turn on crazily fast. And I think we've seen there's so much hesitancy and slowness, and just frankly, lack of capability in the technology, that has stopped a lot of big enterprises from throwing huge hundred million dollar type budget buys at this stuff.

• 12:18Speaker 01

  And the repercussions of that slowness are playing out right now. It's that simple. Like, there are companies that had made projections on startups, I mean, like, projections on what revenue would look like, based on uptake of the software, and it didn't, it didn't happen. And like, in a sense, I think it was arrogance and hubris on the part of investors to just assume that it was going to happen, because, I mean, this is always the issue with Silicon Valley, right? It's like, oh, they're early adopters here, so they just assume everything's gonna be like that. And This tech takes a long time. New, new, if you really believe this is the revolution that you know, you're claiming it is, it's just going to take longer than than you initially thought.

• 12:58Speaker 01

  And you need to be able to, as an investor or like Silicon Valley denizen, or just a general like advocate of technology, like swallow that pill and be honest about it, that like this is slower than it was expected.

• 13:12Alex Kantrowitz?

  Right, and I definitely want to get into the numbers because that's another post that came out of Sequoia this week. But before we do, I think one of the last questions that Ben Dick posed is that's quite interesting is sort of what this technology is. Is it a product? Is it a technology? So here's what he says. Stepping back, the very speed of which ChatGPT went from a science project to 100 million users might have been a trap, which is basically what you're saying. A little like natural language processing was for Alexa. Large language models look like they work and they look generalized and they look like a product. A science of them delivers a chatbot and a chatbot looks like a product. You type something in and you get magic back. But the magic might not be useful in that form and it might be wrong.

• 13:57Alex Kantrowitz?

  It looks like a product, but it isn't. And then he basically says there's two options that were the two different paths that we might be on. He says, you could also suggest that these startups are a collective Silicon Valley bet, that L L Ms are a technology, not a product, and that we need to go through the conventional process of customer discovery towards product market fit. Or the other thing is, and this is, he says, it's the thing that really drives a bubble, is the idea that history is over and L L Ms will be able to do everything. And that in that case, we wouldn't need any of these companies. So I'm curious what you think. I mean, it seems really like we're, we are gonna be in one, the option one,

• 14:38Alex Kantrowitz?

  which is that this is a process, it's going to take a long time to find product market fit. And that's why people like Matt Wood at Amazon Web Services this week is telling me the name of the game is incremental and patience as opposed to like what people within the, you know, sort of sphere of influence back in 2022 were talking about sea change, revolution. Even the Google, for instance, is, I mean, Google's fine. Bing has with AI hasn't just taken it over, right?

• 15:04Speaker 01

  No.

• 15:04Alex Kantrowitz?

  And hasn't really made a dent. So I'm curious what you think.

• 15:09Speaker 01

  I think it's always funny to have big tech executives like Matt Wood say the name of the game is incremental and slow because they can afford to be incremental and slow because they have giant profitable businesses to allow them the time and space to see something play out over a number of years, like a decade, whereas a startup can't do that, right? Like you can't go into Andreessen Horowitz, Benedict's former employer, or Sequoia, or any of these guys and be like, we got a business plan and that business plan is incremental and slow.

• 15:38Alex Kantrowitz?

  Right.

• 15:39Speaker 01

  Like, that's not the way the tech industry works. And so I think a lot of the hype around this technology was driven by the financial needs of investors to see fairly fast returns and uptake on this, on this technology. And like, we've all sort of been a victim to that in a certain sense.

• 15:56Alex Kantrowitz?

  But can I make a counterpoint here? Because hasn't this also like largely been a scale game? It's been a moment dominated by the Microsofts, which have invested in OpenAI, and the Googles, which have their own, you know, AI research houses, and Amazons with their investment in Anthropic, and Nvidia, which can make the chips. And you throw in, okay, so who's the upstart? Is it Meta, which has like, you know, sort of come from nowhere to make its own open source model? Like, it does seem more than most moments in technology that this has been a moment that favors scale and the big guys.

• 16:29Speaker 01

  Oh, yeah. No, it's been a huge benefit to the entrenched tech giants. They have gotten, I mean, Microsoft has gained more than a trillion in market cap. Nvidia is now one of the largest companies in the world. You know, Oracle, which is a company that you didn't think much about in the cloud game, has like benefited tremendously all of a sudden because of this. So the spoils have like absolutely gone to the incumbents, which is again, kind of funny in, you know, this industry that's supposedly driven by disruption and, you know, a changing of the guard every couple of years because new technology comes out. You know, we also should be fair that like OpenAI is a real, they may not

• 17:11Speaker 01

  be profitable probably, but they have real revenue. They're in the billions because they do run like the most popular, you know, ChatGPT and GPT-4, and Anthropic is doing pretty well. Like, there is real money that is going into a lot of these companies. Like, I don't want to overlook that. But I think the sort of

• 17:33Speaker 01

  Ecosystem wide disruption that the startup and venture capital community sort of expects when there's a technological shift has been pretty slow and tricky. And I think in the next couple of months, we're going to see, we've already seen some flameouts of these startups, like Inflection had this bizarre aqua hires type situation over at Microsoft. But it's straight up a situation of a company that didn't work out. Adept, which is, was an enterprise software AI agent company. They sold to Amazon in a very similar way. And I think we're going to see more of that in the next couple of months. So as like a

• 18:16Speaker 01

  kind of startup ecosystem, it's, it's not, it's not the healthiest.

• 18:21Alex Kantrowitz?

  So there's something else here, which is sort of gets to this second half of what Benedict was suggesting, and I'd love to hear your thoughts on it. This idea that like L L Ms will inevitably scoop up whatever is built on top of them. We've talked a lot about like how it's like a chat G P T. Is everything just a chat G P T wrapper? Right? And so like the other side of this, you know, are we just waiting for product market fit? Is like, do startups inevitably end up just being eaten by the big models as they get bigger? And is that another advantage towards scale?

• 18:51Speaker 01

  Well, that's, I guess, something I've been writing about recently. I mean, this idea of scale and, and then that's like just size of model, you know, like these, these giant models like G P T four, or when Anthropic is built, or Gemini, which is Google's large language model. These are very powerful, large technologies. They have to run in like, you know, massive cloud infrastructures, but they also do a lot more than what individual businesses really need. Like if you're trying to build like a chatbot to give financial advice or something, you don't need G P T four to, at the same time, give financial advice and also give you like a recipe for flan or something.

• 19:31Alex Kantrowitz?

  Okay. But, and I brought this up with wood, like, okay, Bloomberg spent all this money to train Bloomberg G P T with, I think they used Amazon technology to do it. And then G P T four ended up giving just as good financial answers as the custom Bloomberg bot, once it came out. That's the best. This is sort of the balance here.

• 19:52Speaker 01

  Well, yeah, I mean, I think, I mean, to go like into like the specifics of these small models and large models, no one is should reasonably say a small model is better. That's not true. What a small model can do is just be tuned specifically to the needs of its user. And so if you have like the small model plus trained on specific data sets, it'll be effective and like more cheap to run. It's really just like a an efficiency play. But you could also train a large model on or tune a large model on specific data and it'll be just as good. I don't I don't know this Bloomberg example, the Bloomberg GPT.

• 20:29Alex Kantrowitz?

  It's like a chatbot where you can talk with Bloomberg data, basically.

• 20:31Speaker 01

  Okay.

• 20:32Alex Kantrowitz?

  Financial data.

• 20:33Speaker 01

  That's fun.

• 20:34Alex Kantrowitz?

  Yeah.

• 20:35Speaker 01

  Yeah, I I think like the large model is, in one sense, a very cool demo technology and it can do lots of stuff and, you know, all the things that Benedict Evans points out in terms of its capabilities and shortcomings, like it's all it's all true in there. The one thing it is also is incredibly expensive to run and kind of a loss leader for for these companies, like just the the cost to build is in the hundreds of millions of dollars. You know, each, some of these companies, like each inference, each time that you put a request into the API for them loses money for the company because it costs more to like in process, you know, cloud computing costs than

• 21:16Speaker 01

  it is, you know, than than they charge customers to be able to do it. And so there's a real desire, I think, on a lot of businesses to find a way to do this more cheaply. And so that's why they kind of have been focusing on these smaller and dumber models that are good enough to to pull off the task, but are also efficient and and and not going to lose you a bunch of money.

• 21:40Alex Kantrowitz?

  So is the idea that they can sort of outflank the bigger models by doing the same things cheaper? Or is there also, is that what it is?

• 21:47Speaker 01

  Yeah, I mean, like the analogy that I used in a in the story that that we published a couple of weeks ago was like, you don't need to drive a tank to go pick up groceries at the store. And there's like a million

• 21:58Alex Kantrowitz?

  In some counties in the US, that's sort of the

• 22:01Speaker 01

  Yeah, maybe it's recommended. I don't know. I guess like that Humvee era, people were doing that pretty actively in the suburbs. You definitely didn't need to do that.

• 22:10Alex Kantrowitz?

  No.

• 22:10Speaker 01

  Though, but whatever. You don't need a Lamborghini to get the mail. I mean, you can, you can think of a million different analogies, but the point is like the cost of running these things when what you need, the output from it is so hyper-specific and doesn't need a huge model is leading people toward using these smaller models and it, it's a funny moment to me because it also runs in the face of like AGI and this desire for these companies to build, you know, a replication of human level intelligence. Cause if you think about it as like a researcher and you got into generative AI, a lot of people were like, like, let's go dude, let's go like replicate human level intelligence. Let's build the biggest possible model we can. We'll run it on supercomputers, the likes of which have never been seen before.

• 22:56Speaker 01

  And we're gonna like, we're gonna do it. We're really gonna make like a robot brain. We're gonna make her. And that's fine. They haven't done it yet clearly, but the business imperatives are also saying, yeah, but why don't you build a not human level intelligence? Why don't you build a small dumb thing relatively that can, you know, be, give Bloomberg financial advice? And, and that is just not that inspiring to those people, I imagine. Like they kind of, they didn't get into this game because they were gonna build like capable, competent chatbots. They really thought they were, they were building something, you know, transformative here.

• 23:32Alex Kantrowitz?

  Yeah. And it's always the economics. That's what points the direction of the technology. Like as much as people would like to say it's not about business or whatever. Businesses is what drives the development of this tech.

• 23:43Speaker 01

  I think so.

• 23:44Alex Kantrowitz?

  I mean, if you can build AGI, it would probably be good for business, but in the short term, you're right. Like it's a lot of these change management incremental, get it in the workflow type of thing. That's not exactly as inspiring to somebody as, you know, building a human brain might be.

• 24:00Speaker 01

  Right. And it's also probably harder to make those arguments to enterprises, to like IT directors, to CIOs and all those people to make, you know, huge investments when we're talking about is incremental productivity.

• 24:13Alex Kantrowitz?

  Right.

• 24:13Speaker 01

  Incremental capabilities.

• 24:15Alex Kantrowitz?

  But do you think there's going to come a point where this technology is going to get good enough where like you won't have to like, for instance, spend all that time standardizing the data where it just sort of is good enough that it can sort of work much more easily than it does today?

• 24:30Speaker 01

  Uh, yeah, I do, honestly. I don't, I don't, I'm not stupid enough to give a timeline for it.

• 24:37Alex Kantrowitz?

  Right.

• 24:37Speaker 01

  But I like, and I guess that would be my, my slight pushback to Benedict Evans. I know he was just raising the question, not really taking a side, but chat GPT is pretty good at a lot of stuff. Like I forget this from time to time because I don't use it all that much, but when you ask it to do certain types of things, very specific at times, like, um, as I was writing a story, I wanted like a, a quick summarization of what EC2 is, this like AWS technology that is elastic computing thing, just like extremely inside baseball, almost esoteric thing. Um, you know, I Googled it and it was not finding a great, like one or two sentence summarization of what this product was. And I put it into

• 25:21Speaker 01

  chat GPT, it gave me a pretty good thing and I fact checked it because I'm, you know, I'm not that stupid. Like I, I, I think we all should do that. But when it does things like that, you do sort of see a bit of the magic that got people excited. Um, coding, of course, is maybe a whole other category, category where it's shown capabilities. So I like, I, I get kind of annoyed at times with the maximalists on the other side who just say like, this is a dead end. This didn't prove, this didn't do anything. Um, this was a huge boondoggle waste of money on the part of Microsoft and everyone else going into large language models. I don't think that's true either. I think there's something really there. Um, but the timeline, like we've been saying, is maybe going to be a lot longer

• 26:06Speaker 01

  than we initially thought.

• 26:08Alex Kantrowitz?

  Yep. And on the Bing front, I mean, you cover Microsoft. We brought up the Bing challenge to Google. Uh, what do you think's happened there that it hasn't been able to? Be successful.

• 26:18Speaker 01

  I mean, it's it didn't work like it did not change the way people search online. I should say it's obviously caused effects, you know, it completely messed up Google. Like the Bing Chatbot, like the chaos that the initial release of Bing Chat caused within Google was tremendous. And all the reorgs and internal pressure and code reds and stuff that they've had to do because Microsoft has, you know, jumped ahead in this world has been real, but the market share did not shift. I'm sorry, you can show me any number of different third party studies and claim that they're like, these things are noisy. But bottom line, this was not like a huge reordering of the guard in terms of search.

• 27:01Speaker 01

  And I think that was a surprise to Satya. I really think, you know, I was there in January, February of 2023, when they rolled out Bing Chat or Bing with Chat and Sam was there. And I think this was really positioned as like an iPhone level moment where we would all look back at this and think, oh, my God, how did we ever live before Bing Chat existed? And it just didn't happen. And I think it's totally reasonable to call out Microsoft and Satya, who I know is like, and I've written about him like, you know, considered one of the most effective CEOs of the current era and, you know, gets a lot of credit for turning Microsoft around and stuff. But like this should absolutely, for the time being, be categorized as not the win that he thought it was going to be.

• 27:46Alex Kantrowitz?

  Totally.

• 27:47Speaker 01

  Yeah, and like, we'll see what happens. There's this new team in there that's supposed to be, you know, rebuilding it all and reskinning it and seeing if there's going to finally get some consumer traction. But it's just, we should be honest about that and say that this didn't work out.

• 28:06Alex Kantrowitz?

  Right.

• 28:07Speaker 01

  Can I actually ask you a quick question?

• 28:09Alex Kantrowitz?

  Yeah.

• 28:09Speaker 01

  On your usage of this stuff? I mean, you know, you put together this run of show thing beforehand, whose listeners can get a little behind the scenes where you kind of listed out the different topics you wanted to cover. I mean, that's easily the kind of thing that you could have put into ChatGPT, right? Or at least any of these these large language models and spit out like, hey, summarize Benedict Evans's post and talk about the other things we're going to do. Like you could have gotten this thing to spit out a summarization of this outline of the of the episode. Didn't look like you did. I mean, do you ever consider using this stuff? Like, is this, is this something that could change your workflow at all?

• 28:46Alex Kantrowitz?

  No, for my workflow, like, I need to be reading the stuff. Like, I need to be in the documents and picking out the points. I mean, I'll do things like upload lots of interviews to Claude and then ask it like, you know, what am I missing? Or, you know, this week I took a bunch of interviews, uploaded it to Claude, and then I uploaded my story and I said, what did my story leave out? And like, you know, it's much more effective after the fact versus proactive because like, I just think that the human touch is still more important. And honestly, I think I can do a much better job than the AIs of like picking out what we should be discussing versus what we shouldn't.

• 29:24Speaker 01

  So you don't mind, because it would obviously be faster. You don't mind spending the extra 20, 30 minutes putting the outline together?

• 29:31Alex Kantrowitz?

  Oh, I spend longer than that. And I also think that like, that's what makes, that's without that work ahead of the time, like, the show wouldn't be as good as it is. Or the show would be worse, let me put it that way, you know?

• 29:44Speaker 01

  Yeah. Well, that's such a, that's interesting because that's sometimes the argument from these guys is like, well, it's not as good as a human, but it's only, you know, it's only, it's 98% or it's 90%. And if we're willing to like, deal with that, then you actually get increased efficiency and only a slight degradation in quality, which I think is kind of cynical.

• 30:04Speaker 01

  If you think about the march of human progress.

• 30:06Alex Kantrowitz?

  Like with podcasts, it is zero sum. Like, if you have a choice of listening to a show that's like 100% of what it is or 90% of what it is, and there's another show that comes in and it's 95%, like what you've just given up in efficiency, you've lost your entire audience because people will go to the show that's 95% as good versus 90. So it's basically like, the job is just to make it the best quality show possible and sort of.

• 30:34Speaker 01

  Yeah, and that's why like the branding for this tech like Microsoft has always been like it's a co-pilot, like it's something to sit alongside you. It's not autonomous, which is again ironic because the different levels of what OpenAI is going for is not just a co-pilot, it's a pilot. Like they really want this stuff to be able to handle all tasks on their own. And so, I mean, the technology doesn't allow for that yet, but we'll see. Like, at this current moment, it's a co-pilot that people aren't all that excited about at a grand scale. And there's an acknowledgement that there's also like a quality gap there.

• 31:09Alex Kantrowitz?

  Yep, definitely.

• 31:10Speaker 01

  It's a hard sell.

• 31:12Alex Kantrowitz?

  It is a hard sell. And so it sort of is a great lead into our last segment of this half, which is talking about this doc, this post that David Kahn from Sequoia came out with, AI is 600 billion dollar question. And he basically said effectively that AI is going to have to generate, you know, 500 billion dollars more in return to make up for the massive amount of investment that's going into it. And he cites some risks there here for the lack of pricing power. Basically, like if this is all going to be commoditized, you won't be able to make a lot of money off of the models that your investment incinerates,

• 31:53Alex Kantrowitz?

  maybe because of training, or because the people will lose money in speculation, depreciation, the models get worse over time, and then the winners and losers. Like if you're not a winner, you're in, you're in rough shape. And here's what he says. He says speculative frenzies are part of technology, and so they should, they are not something to be afraid of. Those who remain level headed through this moment have a chance to build extremely important companies. But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. The delusion says that we're all going to get rich quick because AGI is coming tomorrow. And so we need to stockpile the only valuable resource, which is GPUs. In reality, the road ahead is going to be a long one. It will have ups and downs, but almost certainly

• 32:38Alex Kantrowitz?

  it will be worthwhile. I think that's sort of like the most like, cool headed take on this entire moment that I've read so far.

• 32:45Speaker 01

  Yeah, well, that's the theme of the podcast.

• 32:47Alex Kantrowitz?

  Indeed.

• 32:48Speaker 01

  I, I guess that is, it's also the optimist take on it. And it does still rely on an assumption or a null hypothesis that the technology will improve at some sort of a rate. And you know, that goes against what the real critics of it like Gary Marcus will say, which is like, deep learning, large language models are going to hit a ceiling. And you can't just throw more data and more scale, more GPUs at this to, you know, reach the level of breakthroughs that need to occur for it to be as valuable as that extra, what was the number, like 500 billion?

• 33:22Alex Kantrowitz?

  500 billion.

• 33:23Speaker 01

  500 billion revenue, yeah. That's meaningful, though.

• 33:26Alex Kantrowitz?

  It's a lot of money.

• 33:27Speaker 01

  Yeah, that's a lot. I can't think of that many 500 billion dollar businesses that just sort of were created in any period of time. Yeah. So that's like a, that's, that's, that should be intimidating and daunting.

• 33:41Alex Kantrowitz?

  Indeed. Yeah. I mean, if you think about the level of investment that's gone in, gone on, you're going to need massive returns. And I think like, right now, like, people are starting to say, okay, where's the revenue? And that question, I think, so we're just seeing the beginning of it this week. I mean, it's been building, but we're really starting to see the beginning of it now. And I do think, maybe not the end of this year, but next year, that question is just going to get louder and louder and louder.

• 34:08Speaker 01

  Yeah. You know, it's been interesting for me to watch, given what I cover is, which is, which is cloud computing, is the buildup of cloud computing and data centers around the country, around the world, in order to meet the demands for, you know, compute, for AI compute. We're sort of, now, I wouldn't say quietly, but not enough people, I think, pay attention to the fact that we're in the midst of one of the largest infrastructure build outs in history, right now. If you think about just dollars spent to build these kinds of things, right? I mean, the AI revolution turned Nvidia into a $3 trillion plus company because they're selling GPUs, for the most part, to, to large cloud computing companies, which are then putting these things into data centers all over the country.

• 34:50Speaker 01

  And this is all in advance of consumer demand, right? Like, what is the signals and data points that these guys are using in order to invest this, this heavily into this stuff? There's not a lot. And what I think about a lot at times is what happens a year or two from now if, I'm not even saying the whole thing flames out, but it levels off. And the infrastructure was built in excess of that. What do we do with these things? Like, what happens to all of these data centers that are full of GPUs that are basically lying dormant now? Because there's not as much demand from consumers and businesses to use this stuff.

• 35:31Alex Kantrowitz?

  Well, here's my question to you. I mean, do you think that the tech industry is going to find a good use for them even if, let's say, LLMs level off? Like, weren't a lot of these GPUs starting out as gaming chips? And then they were able to like, you know, kind of pivot into crypto and then pivot into AI.

• 35:47Speaker 01

  Yeah.

• 35:47Alex Kantrowitz?

  Does the GPU eventually find a very impactful use in the tech world? I mean, they're also being used to train the algorithms for recommendation algorithms for things like Reels. So I would bet that there's going to be a use that, you know, even if LLMs sort of level off, that will be productive. But like, the question is, is it going to be as valuable of a use? That's another question. I don't know.

• 36:12Speaker 01

  Yeah, yeah. And these things cost a lot of money and it's a depreciating asset. But the crypto thing is interesting because, and this happened a lot with Ethereum mining. I wrote a story about this with my colleague Berber Jin at the Wall Street Journal last year. But Ethereum mining required GPUs. And there was a change in the nature of Ethereum mining that I don't really want to explain right now. But basically, it obviated the need for GPUs. And so there were these mining rigs that were sitting dormant all over the world because they didn't need them anymore to create new Ethereum coins. And

• 36:48Alex Kantrowitz?

  That was a good investment then, that they could sell those.

• 36:51Speaker 01

  Yeah, well, they've tried to retrofit these machines to be able to do AI inferencing. And, you know, I don't think they're really capable of doing that. I'm sure people that listen to the show will think, there are some that will think differently. But my sense is that they can't. But I don't know with, you know, these top of the line Nvidia GPUs, if there's immediately going to be another use case for them that's valuable. It actually, to me, and I've not thought through this enough, this is a good sci fi premise, and I don't know what it is, but like, America over invested by the tens of billions of dollars levels in GPUs, and there are now like in excess of these hyper capable chips sitting in warehouses all over the country that have tapped into the nation's power grid, which is also being like

• 37:33Speaker 01

  actively retrofitted to be able to power these things, and yet they're not being used right now. Could there not be some sort of entity or life form or like self perpetuating technology that somehow takes advantage of this dormant technology for its own uses and devices? Is that not a decent premise? I haven't thought through it yet.

• 37:53Alex Kantrowitz?

  I love that premise. I mean, or, yeah, I don't know, there's so many interesting things you can do. I mean, I like really geek out over this, like, well, can you take this technology and then use it, like, can you, what if you hooked all those up to a Neuralink, right? And just like combined it with the human brain or gave human brain access to it? Or, I mean, I have a conversation, I teased this on Twitter, but I'll talk about it now that that's coming up in a couple of weeks with Nick Bostrom, where we talk at the end of the conversation about basically like, can we use more advanced AI to, if we're living in a simulation, sort of rip apart the wall in the simulation and go out and meet the people that are running it?

• 38:32Speaker 01

  Oh, because we've developed this technology that's so powerful, that like we can, it's like a counter.

• 38:37Alex Kantrowitz?

  Peel back.

• 38:39Speaker 01

  We can counteract the existing simulation. So we've like quietly been building, like, we've been quietly been building the

• 38:45Alex Kantrowitz?

  The escape route.

• 38:46Speaker 01

  The Matrix team that is able to exist inside the Nebuchadnezzar ship.

• 38:52Alex Kantrowitz?

  Now, I'm not saying, yeah. I'm not saying I believe in this, but I'm saying it's fun to think about.

• 38:56Speaker 01

  Yeah, yeah, I think it's all, it's all possible and we should consider it seriously. And I frankly think in the following presidential debates that we have, both Biden and Trump or whoever the Democratic nominee should be asked these questions.

• 39:09Alex Kantrowitz?

  I agree. I agree. That is what truly what America needs right now is a consideration from the top level of government about simulation theory. Why don't we do some more conversation about the state of Microsoft and then the state of Amazon and its comeback? So we'll do that after the break, back right after this. This episode is brought to you by AVPoint. Everyone's racing to roll out AI right now. Co-pilots, chatbots, agents doing real work. But here's the part nobody loves talking about. All that AI runs on your data. And most teams have no single way to see it, secure it, and prove it's under control. That's exactly what AVPoint does. For 25 years, they've been the trusted layer beneath the world's most demanding data,

• 39:54Alex Kantrowitz?

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• 40:36Alex Kantrowitz?

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• 41:20Alex Kantrowitz?

  Learn how to stop online threats before they become real-world attacks. The link's in the show notes.

• 41:29Alex Kantrowitz?

  And we're back here on Big Technology Podcast with Tom Dotan. He's a reporter at The Wall Street Journal, covers Microsoft, Salesforce, AI, business technology. Great to have you here, Tom. You just wrote recently about Satya Nadella's, now that we're off the topic of the simulation, although I imagine we might end up getting back there before the end of the show.

• 41:48Speaker 01

  Hopefully.

• 41:49Alex Kantrowitz?

  Yeah, but you wrote about Satya's attempt to build an AI empire that doesn't necessarily rely entirely on OpenAI. That's a very interesting subplot that's sort of opening up in this broader Microsoft story is like, people used to think it was just Microsoft and OpenAI, but clearly, Microsoft is high trying to hedge with other outside investments and its own models internally that could sort of do what OpenAI does. You want to take us inside that story?

• 42:20Speaker 01

  Yeah, basically, I mean, if we go far enough back, Microsoft makes this bet in 2015 on OpenAI, which was this upstart AI company that hadn't really built anything of consequence yet, but Microsoft uses them as a kind of banner customer for Azure, so they can build up their own supercomputers. Eventually, OpenAI builds these very effective large language models that Microsoft ends up investing even more money in, and then it ends up being the foundation to a whole new set of technology that Microsoft puts out there under these co-pilots and chatbots and things like that. And they, both these companies, their success rides in tandem. Microsoft gets this huge benefit of the AI revolution and their stock price goes up tremendously.

• 43:05Speaker 01

  OpenAI keeps raising more money and all that stuff. But the co-dependence that these companies have on each other is problematic, mostly because they're led by headstrong people that have their own desires to be successful in their own right and not be dependent on the other. And the

• 43:23Speaker 01

  clearest case of that was the Sam Altman board debacle, Tom's Thanksgiving ruining event of 2023. And it it ends up kind of being a very brutal wake up call to Satya that they are entirely reliance technologically speaking on a company that they do not control. And in the years that they had been investing more in OpenAI, they basically neglected their internal AI efforts. And a lot of people at Microsoft left the company in the last few years because they weren't getting any resources. All the resources were being spent on OpenAI. And, you know, one argument on what what's happened to Microsoft in the

• 44:06Speaker 01

  last seven months or so is that after the Sam Altman debacle, Satya realized that he needed to build more stuff internally. They couldn't be reliant on just one company. And so earlier this year, they had this very interesting acquisition, which I kind of mentioned earlier, of this company called Inflection, which is a, I would argue, failed AI startup that's led by Mustafa Suleyman, who

• 44:30Alex Kantrowitz?

  One of the DeepMind co-founders.

• 44:31Speaker 01

  DeepMind co-founders.

• 44:32Alex Kantrowitz?

  So do you think that bringing Inflection in and Mustafa in was a direct reaction to the OpenAI board situation?

• 44:39Speaker 01

  Yes, I do. The board situation, maybe not directly, but I do think the desire to

• 44:47Alex Kantrowitz?

  Realizing.

• 44:48Speaker 01

  hire this team, and that's what they got. And, you know, immediately, one of the things that they start getting to work on is their own large language model that is hoping to be at the same capability level of of OpenAI is is that they could one day have it as a backup plan, as a plan B, as a hedge, should they, for whatever reason, need to do that. I think they, even though they emerged successfully from that whole Sam Altman fight, the risk of exposure was made very evident for them. And one of the things that Satya is very good about, and I wrote about in my piece, is Shifting strategy when it needs to be shifted and not not being too reliant on one

• 45:33Speaker 01

  idea, one baked in belief of how the company should be run. And even though he had so successfully ridden the OpenAI relationship to the place that the company is at right now, that should be rethought when circumstances change. And circumstances, I don't think they really changed. I think they were just made more evident.

• 45:54Alex Kantrowitz?

  Right.

• 45:55Speaker 01

  Yeah. And so that's been an interesting thing to watch play out. Now, I don't want to get too dramatic about it and say like the OpenAI-Microsoft relationship is on the verge of collapse, or they're not going to work with each other anymore. But Microsoft is in a slightly better position now than they would have been had they not done any of these things.

• 46:13Alex Kantrowitz?

  How is Mustafa doing within the company? I mean, he comes in and he takes over effectively consumer AI within Microsoft. What's his performance been like?

• 46:23Speaker 01

  I say it's been OK. I think there's a lot of people who are rankled by the foreign bodies that have come into Microsoft's and they, as we wrote in the story, kind of exist semi-autonomously from the rest of Microsoft. They don't even use Teams, they use Slack to communicate. And there was a lot of internal tussling.

• 46:47Alex Kantrowitz?

  That's a heresy.

• 46:48Speaker 01

  Yeah. I have no dog in that fight. I don't really like either Teams or Slack, so it's hard for me to get wrapped up in that fight. But it mattered to people there. I think there was a lot of, you know, political infighting that happened, which isn't surprising in large companies. I will say, there are a lot of people who are Mustafa skeptics out there. There are people who think that he has gotten a lot of credit for the work that other people at DeepMind did. I'm not taking a side here, I want to be very clear about that. I'm just speaking, you know, or verbalizing the points of view from people that I've talked to.

• 47:28Speaker 01

  But I think there is a lot that people are hoping to see from that team to justify, not the amount of money that they spent, but like to really justify this as like a legitimate effort within Microsoft and that they really do, that they really are on the verge of building something that is competitive with OpenAI to be the hedge that Satya, I think, wants it to be.

• 47:55Alex Kantrowitz?

  Yeah. And then on the outside, Satya is also investing in other companies. He put 1.5 billion into an Abu Dhabi-based AI startup. He also invested some millions in Mistral. What's that all about? And is that going to change the relationship with OpenAI?

• 48:14Speaker 01

  The Mistral thing was interesting. That is this open sourced French AI startup that it was a very small investment. I would argue that one was probably more about just having more options on Azure for developers. So when developers want to build AI tools and they go to Azure, they want more than just OpenAI. And investing in Mistral, having them be listed there, that was, I think that was more the play there. The Abu Dhabi-based company, that's called G42, they're fascinating. I think Microsoft may have bit off a little bit more than they could chew with that one.

• 48:48Alex Kantrowitz?

  What's the story there?

• 48:49Speaker 01

  It's a good question. I mean, basically, they got themselves ensnared in a kind of cross-border geopolitical fight with them because there is some concerns that G42 is a little bit too close to China. And the US government has been kind of all over them in terms of making them throw out, you know, pieces of hardware that were made by Chinese component makers for fear that it could be spyware or somehow cause some sort of vulnerabilities. And, you know, Microsoft's investment stands and they'll defend it and it'll move forward. But there are hearings going on yesterday and even today as we record this, where a lot of US lawmakers are kind of investigating Microsoft's involvement in this company that has some, you know, direct and indirect ties to China. So I'm very interested to see that one play out.

• 49:34Speaker 01

  But, you know, from what you and I are talking about, this was also just a broadening of bets. And, you know, Microsoft putting their money in technology that could one day be competitive with OpenAI's.

• 49:45Alex Kantrowitz?

  Yeah. So the empire building thing, it's an interesting question. So your headline was Microsoft's Nidella is building an AI empire. OpenAI was just the first step. Do you think he's going to be successful in building that empire?

• 50:02Speaker 01

  I think that goes back to like the earlier segment about whether this technology is going to pan out.

• 50:07Alex Kantrowitz?

  Yeah.

• 50:07Speaker 01

  Yeah. I would say if it pans out, Microsoft is in a better position than anyone. Because it's enterprise technology. Microsoft is the enterprise company. You know, they've got the relationship with the most successful builder of this technology in OpenAI. Although that in and of itself is getting kind of interesting because of Apple. And it's like, you know, relationship with OpenAI, which we can talk about if you want.

• 50:34Alex Kantrowitz?

  But I thought you were going to say Anthropic, but that will be for our next segment.

• 50:38Speaker 01

  Sure, sure. We can, we can do Anthropic later. I think if this turns out to be a real thing and a real business, yeah, I think Microsoft is in a really good spot. And Satya's maneuvering around that has looked very intelligent and prescient. But, you know, it's still pretty early and there's not a lot of revenue. And so it would be, I think, kind of foolhardy to call a winner at this point when like, there's just not a lot of money there.

• 51:05Alex Kantrowitz?

  Yep. Lot of data left to collect and either it'll be, it'll be like a wild buildup or a bunch of spectacular collapses.

• 51:14Speaker 01

  Yeah, yeah.

• 51:16Alex Kantrowitz?

  It's hard to see it really being something in the middle.

• 51:18Speaker 01

  Not at that level, not at that level of investment, I would think.

• 51:21Alex Kantrowitz?

  Right.

• 51:22Speaker 01

  Yeah.

• 51:23Alex Kantrowitz?

  So, all right, you know, focusing lastly on Amazon and Anthropic, right? They're big partners. Matt Wood this week talked about how Amazon completed its $4 billion investment in Anthropic, speaking of money and needing to see it return. And it's kind of this interesting story of with Amazon, which is that basically Jeff Bezos leaves Amazon mid pandemic after spending pretty, I don't know if you'd say recklessly, but wildly trying to build up infrastructure mid pandemic. He leaves in 2021 and effectively goes to Andy Jassy, his longtime top deputy and says, "All right, you're the CEO of Amazon now. Congratulations. Also, clean it up."

• 52:06Alex Kantrowitz?

  And if you remember those first few quarters that Jassy took over, maybe even the first year plus, it was, it was not steady. It was bumpy and the company's, you know, infrastructure spending didn't seem like it was about to be justified. It built for a pandemic level era of online shopping when people went back to shopping in person. And then just, there was a hangover and they had to cut a lot of costs. I mean, they, and geez, they cut a lot, a lot of jobs. I mean, they slashed almost 27,000 jobs and rolling layoffs that I believe are still going on. They had divisions like

• 52:45Alex Kantrowitz?

  one medical being forced to cut dramatically. They, they were going to lose a hundred million, they, they asked them to cut their losses by a hundred million dollars, which is massive. Prime Video, they've gone from like looking for blockbusters to just looking for profitability. And then Amazon, all of a sudden turns it around. Operating income in the last quarter was 15.3 billion, which is the largest quarterly profit in the company's history. This is all coming from a Business Insider article about the turnaround. And next thing you know, they hit all time highs. Amazon reaches $2 trillion for the first time. And it looks like everything

• 53:27Alex Kantrowitz?

  is hunky dory inside Jassy's Amazon. But now I'm gonna, I'll, I'll add the but, and then I'm going to turn it over to you because there's always a but. And in this case, there's a serious one, which is that, and, and we'll have more on this on In Big Technology coming soon. So hopefully, well, anyway, I'll just share it. But like, the mentality might shift because that mentality of we're not going to make a lot of profit with an Amazon, we're going to fund these moon shots, we are going to look to, for those blockbusters in Prime Video and look for the moon shots is starting to dissipate as this cost cutting, market friendly Amazon takes its place. And there is this part of the story that talks about

• 54:08Alex Kantrowitz?

  Jassy's downsides. And it says, Jassy's new approach may have some downsides. Amazon employees used to leave a meeting with Bezos feeling inspired and more ambitious about their projects. Some of the people said, this is according to people talking to Business Insider, in meetings with Jassy, there's a much greater emphasis on mundane topics such as bottom line. Of course, Amazon disputes this, but. It seems undeniable that there is that growth, right? Which is a lever I think Bezos always could have pressed. And then there's the risk, which is why he didn't press it. So I'm curious what you think hearing about, hearing all this stuff.

• 54:44Speaker 01

  You know, it's funny hearing you describe all this stuff and like the, you know, on background gripes from Amazon employees. It reminds me a lot of, for a brief period while I was actually at Business Insider, I covered Uber. And this was in the post Travis Kalanick era Uber, run by Dara Khosrowshahi, he's still the CEO. And I wrote a bunch of stories about this, which I stand behind. But, you know, it wasn't hard to find people from a different era, the Travis era complaining about the Dara era, saying, "It's not inspiring. We're not reaching for the stars anymore. We're not talking about self-driving cars or, you know, owning the entire taxi industry or whatever crazy ideas that were being discussed while the company was on their way up.

• 55:27Speaker 01

  And instead, it's all about incremental changes and bottom line stuff. And, you know, people just don't want to work there anymore. They'd rather work for, at the time, it was like a crypto, you know, "Oh, I'd rather work at OpenSea than I'd rather work at, you know, Uber. That's where the real future is, you know, NFTs." And, you know, I, hold on, let's see, what is Uber's market cap today?

• 55:51Speaker 01

  151 billion. Yeah, okay. They were like at like 60 billion not that long ago when I was covering them. And that was when all these gripes were coming out. And like Dara has proved himself to be the absolute right CEO, doing the right strategy at the time. Obviously, there were a lot of bump, there was bumpiness there. But like, yeah, he had to do cost cutting. He had to like reduce the ambition that was irrational, some would argue, to making the company like a real big boy company. And it's funny to hear this playing out with, at Amazon, which is obviously at a massively different scale than Uber. But these are the kinds of things that people will complain about at a company, you know, from one, from one day to the next, one CEO to the next is like, "Oh, we used to leave these meetings inspired about changing the world.

• 56:35Speaker 01

  And now we're just talking about the bottom line." It's like, well, you know what? You also run a business. You also have stock, you have shareholders. You're also past the initial growth of e-commerce being a novel concept. And now it's just about, you know, making sure that you hit your quarterly numbers and have defendable new initiatives. And I just. I don't want to give all the credit to Andy Jassy, mostly because I just don't know. I don't cover Amazon, but like sometimes those adults in the room type CEOs that are not the most inspiring ones are the ones that actually know how to run the business the best. And maybe Tim Cook, to a degree, is a version of this at Apple.

• 57:16Speaker 01

  You know, after Steve Jobs, yeah, they haven't really released revolutionary products since Steve Jobs died, but like they know how to make that shit work. You know, they know how to make the assembly lines and supply chains like operate in tandem. And that's meaningful. And so it sounds to me like the same thing is happening at Amazon. There was also like you were mentioning, like just a right size and they needed to happen after the pandemic, that there was this overbuild out of fulfillment centers and, and you know, there was a dip in how much people were buying stuff online. And so that was like a painful episode that Jassy, I guess, had to bear the brunt of. But I don't know, Amazon's still a monopoly.

• 58:01Speaker 01

  They still basically own all of online, you know, most of online e-commerce or, you know, I mean, online commerce, and they still have the largest cloud computing business out there by a wide margin. So it's, uh, it's, it's gonna look good once like, you know, the fundamentals of the American economy return.

• 58:19Alex Kantrowitz?

  For sure. And I'm just looking at Uber stock. So July 2022, it was at $21 a share. Today, $72 a share, so more than 300 times. I mean, of course, that was at the bottom, but it is sort of crazy where they are now compared to where they were and when those questions were coming up.

• 58:37Speaker 01

  Yeah, and they're a boring company. I'll straight up say it. Anyone from Uber, call me if you, if you disagree. But like, they're, they're boring. It's the same, it's the same service it's been for the last 10 years. It's, it's, it's an app, it's a ride hailing service.

• 58:50Alex Kantrowitz?

  But Amazon is not boring. That's the thing. Like, Amazon has gotten to the place where it is by like having this day one mentality and always being willing to like, you know, not, not just rely on the bread and butter. Like, the reason why they are the cloud services company they are today is because they've had this willingness to reinvent. And that's sort of where the question is.

• 59:09Speaker 01

  Yeah, sure. And, and I mean, you could argue that not having the day one mentality makes you vulnerable to a disruption and innovator's dilemma and all that stuff. And, you know, if AI does turn out to be a massive business, it's possible that Amazon will not, you know, kind of enjoy the fruits of that as much as Microsoft did, maybe because of their conservative, less inspiring, whatever. So yeah, there are risks to that for sure, but that's still based on a hypothetical.

• 59:39Alex Kantrowitz?

  Right.

• 59:40Speaker 01

  Amazon still has like their self-driving car unit, right? Zooks?

• 59:45Alex Kantrowitz?

  I'm embarrassed and I don't know.

• 59:48Speaker 01

  Yeah, they do. I can tell you they do. So they're still doing stuff like that. Are they do, are they still doing that drone shit? Are they doing like drone deliveries?

• 59:57Alex Kantrowitz?

  I mean, they're, oh, they're doing drone delivery. They're also doing, I think it's either them or Bezos that's doing a Starlink competitor.

• 1:00:04Speaker 01

  Okay, okay. I mean, that's, that's a great business for SpaceX, for Elon. So if they're in that, like that's, it's not terrible. Yeah, I mean, I, I'm sure there is still pockets of Amazon that still do, you know, some of the more out there stuff that gets people inspired and day one mentality and stuff like that, but I don't know. I, it's hard for me, and I say this as a reporter, like it's hard for me sometimes to disentangle like the gripes of overcompensated white collar employees that just don't feel inspired by their jobs with the fact that they're like working for a company now that's like firing on the cylinders that they need to be firing on in order to work.

• 1:00:43Alex Kantrowitz?

  Yeah. No, I, I look, I guess like what I would say is

• 1:00:49Alex Kantrowitz?

  there is wisdom to these employees, but you have to be able to pull it out from the discontent.

• 1:00:54Speaker 01

  Right.

• 1:00:55Alex Kantrowitz?

  That's the thing.

• 1:00:56Speaker 01

  And just point to specific examples to me, like what is the specific thing that someone else capitalized on or invested in at a different company that Amazon chose not to because they, they lack this killer instinct?

• 1:01:08Alex Kantrowitz?

  No, I mean, I don't think Amazon's had a long period of time where they lack killer instinct. And I wouldn't even argue that they've lacked killer instinct necessarily right now. Like I just think that these things, sometimes these changes take place over decades. Like, and they're correctable also, like Microsoft, for instance, you know, their desire to sit out like cloud computing and whatever it was and mobile, like they've sort of rebounded from that quite well. It just took. You know, a lot of money and change in leadership.

• 1:01:38Speaker 01

  Yeah.

• 1:01:38Alex Kantrowitz?

  It's doable.

• 1:01:39Speaker 01

  That's, yeah, and there are examples throughout business history of companies that like absolutely lost their fire and are, you know, in the dustbin of history.

• 1:01:50Alex Kantrowitz?

  Totally.

• 1:01:50Speaker 01

  Sun Microsystems or I don't know.

• 1:01:53Alex Kantrowitz?

  Xerox.

• 1:01:54Speaker 01

  IBM. Companies that once were the most powerful that just are, you know, totally, totally got overtaken by upstarts or faster moving competitors. So there's always risk there.

• 1:02:05Alex Kantrowitz?

  Yeah.

• 1:02:06Speaker 01

  But there's also, I don't know, you tell me how you feel, but like, I think the entrenchedness of big tech companies now is greater than it's ever been.

• 1:02:16Alex Kantrowitz?

  Oh, definitely.

• 1:02:17Speaker 01

  The, like, the, you know, what do they always call it? Like regulatory, what is it called? Where like regulation kind of empowers the incumbents?

• 1:02:24Alex Kantrowitz?

  Capture.

• 1:02:25Speaker 01

  Regulatory capture.

• 1:02:26Alex Kantrowitz?

  Yeah.

• 1:02:27Speaker 01

  That's only increased over, you know, the last decade or two. And the ability for these companies to turn it around is just easier than it was because like there's just fewer competitors.

• 1:02:40Alex Kantrowitz?

  Yeah.

• 1:02:40Speaker 01

  And you own more channels.

• 1:02:42Alex Kantrowitz?

  Invest. Well, there's also like VCs want to invest in companies that are in their lane because they probably won't be able to be acquired. Acquisitions are with big tech are much more heavily scrutinized.

• 1:02:55Speaker 01

  Yeah.

• 1:02:56Alex Kantrowitz?

  So.

• 1:02:56Speaker 01

  But I think there's something to be said. I mean, I guess it's sort of the theme of your show, looking at like big technology, but like, is disruption as we know it, where like a major company could be completely destroyed by a shift in technology, is that antiquated? Are we not going to see that happening a lot in the next decade or two?

• 1:03:17Alex Kantrowitz?

  No, I wouldn't say so. I think that there's always a chance. Like, I feel like the incumbents today have this advantage because of scale and scale makes a huge difference, but you really never know, like where the next thing is going to come from. And very easily you could be behind the eight ball. Like it didn't work right now in terms of like AI search. And so Google's still sitting pretty, but like it could have, it could have just been that was the user preference. And then, you know, there goes a good chunk of, it didn't. No, but I'm saying, you know, you don't know, like, and, and sometimes it will feel super innocuous to you. Like I'm reading the Steve Jobs book now and Jobs, the Walter Isaacson book.

• 1:03:57Speaker 01

  Okay.

• 1:03:57Alex Kantrowitz?

  And Jobs goes to Xerox and effectively convinces them to give him the graphical user interface. And they're like, all right, sure. And they hand over sort of like the key, the key differentiator for Apple in its early years.

• 1:04:11Speaker 01

  Yeah.

• 1:04:11Alex Kantrowitz?

  So you can say, okay, that was just like a nice deal that they made, but people will come out on top and, and I don't think that anything is guaranteed to last, especially now.

• 1:04:21Speaker 01

  Yeah. But again, you're pulling from an example from the 1970s.

• 1:04:25Alex Kantrowitz?

  Right.

• 1:04:25Speaker 01

  I just like, what's the last company that's come up through the Silicon Valley ecosystem? That's been truly disruptive and absolutely, you know, just bodied an incumbent to a point where it's irrelevant now.

• 1:04:38Alex Kantrowitz?

  You're right. It hasn't happened. And it's, and sort of gets me back to what you were, one of the companies you were talking about earlier, where like even Oracle seems to be getting a second life because it was big enough and was able to invest and sort of build, leaned on relationships to grow. But maybe Nvidia is that, is that company?

• 1:04:57Speaker 01

  Fair. And that's fair. And you could look at something like an AMD or an Intel, maybe is a better example of a company that was once a giant that is now struggling.

• 1:05:07Alex Kantrowitz?

  Yeah, Intel for sure.

• 1:05:09Speaker 01

  Yeah. Okay.

• 1:05:10Alex Kantrowitz?

  And Nvidia, I mean, you think about like, okay, so in the Nvidia case is fascinating because you're like, well, wouldn't like all the big tech companies just be able to build their own chips? Like how difficult it is, is it to build an accelerator that does AI training and inference? Actually, it's quite hard. And they haven't been.

• 1:05:27Speaker 01

  Well, they are all building them.

• 1:05:28Alex Kantrowitz?

  They're building them, but it's coming. They're, they're all just spending so much money with Nvidia still.

• 1:05:32Speaker 01

  Yeah. Right. I mean, that's a fascinating dynamic, maybe for a different episode.

• 1:05:36Alex Kantrowitz?

  Definitely.

• 1:05:37Speaker 01

  Yeah. But yeah, I don't know. I think about this a lot because we're sort of also in the midst of a presidential election and.

• 1:05:43Alex Kantrowitz?

  Oh, that's happening.

• 1:05:45Speaker 01

  It's what?

• 1:05:46Alex Kantrowitz?

  That's happening?

• 1:05:47Speaker 01

  On the peripheries.

• 1:05:51Alex Kantrowitz?

  Yeah. Yeah. I'm still trying to figure out like, all right, how do we put that in the show?

• 1:05:55Speaker 01

  The presidential election?

• 1:05:56Alex Kantrowitz?

  Yeah. I don't want to, you know, sort of let politics dominate the show, but also can't ignore it. So we'll find some way.

• 1:06:04Speaker 01

  It's worked for all in.

• 1:06:06Alex Kantrowitz?

  Yeah, they're doing okay.

• 1:06:07Speaker 01

  Yeah.

• 1:06:08Alex Kantrowitz?

  But like, I don't know. There's gotta be some people that don't want to listen to all in and hopefully they're here.

• 1:06:14Speaker 01

  I mean, there are more people that don't want to listen to all in than, than do. So yeah, there's, there's a large market, if that's your differentiator.

• 1:06:21Alex Kantrowitz?

  I hope so.

• 1:06:21Speaker 01

  Anyway.

• 1:06:23Alex Kantrowitz?

  Tom, great to see you. Thanks for coming on. It's such a good show.

• 1:06:25Speaker 01

  Yeah, thanks, Alex.

• 1:06:26Alex Kantrowitz?

  Awesome having you on. All right, everybody. Tom Dotan from the Wall Street Journal. Where can people find your work?

• 1:06:31Speaker 01

  I work at the Wall Street Journal. So if you go to WSJ.com or use the WSJ app and you read stories about Microsoft or enterprise software, it's probably written by me. So that's a good place to start.

• 1:06:44Alex Kantrowitz?

  Awesome. Well, I know that I do it. I'm there daily on the Wall Street Journal app and then on the website. Your team is just doing great work and it's been great reading your stuff. So thanks for coming on, Tom.

• 1:06:56Speaker 01

  Thanks, man.

• 1:06:57Alex Kantrowitz?

  All right, everybody. Thank you so much for listening. On Wednesday, we have a one-on-one interview with myself and Klarna CEO Sebastian Shimiankowski. We're talking about whether they actually replace 700 customer service reps with large language models. Don't miss it. It's a real fun conversation. All right, that'll do it for us here. We'll see you next time on Big Technology Podcast.

• 1:07:20Speaker 02

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