Meta's New AI Model, AppleGPT's Potential, Is ChatGPT Getting Dumber — With Aaron Levie

Aaron Levie is the CEO of Box. He joins us for a special Friday episode to break down a major week of AI news. We cover: 1) Meta's incentives to open source its Llama 2 AI model. 2) Whether people actually want to interact with chatbots, no matter how well they perform. 3) Why enterprise might be the clearest use case for Ai. 4) Why Apple is developing LLMs and where the project might go. 5) Whether AI companies can actually build moats around their products. 6) Is ChatGPT getting dumber? 7) Levie's view on AI and jobs 8) AI's influence on creativity. --- 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/ 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?

  The CEO of Box joins us to break down a wild week of AI news and the state of technology with Meta, Apple and Microsoft all making waves. You're going to want to hear about that and more, all coming up after the break. 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, including the business decisions, trade offs and lessons along the way.

• 0:46Alex Kantrowitz?

  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 Razor were able to cut their inference cost by 15 times. Visit akash.network slash Alex for a free consultation. That's akash.network slash Alex for a free consultation.

• 1:17Speaker 01

  LinkedIn presents.

• 1:23Alex Kantrowitz?

  Welcome to Big Technology Podcast, a show for cool headed, nuanced conversation of the tech world and beyond. Joining us today is Aaron Levie. He's the CEO of Box. He is a friend of the show. I think it's your fourth appearance, Aaron, and every time you're here, it's always just huge news going on. So this week is no different. Welcome to the show.

• 1:41Speaker 02

  I think you certainly chose a good time for a for a technology podcast, given everything going on in the world. So there's probably every week is pretty crazy.

• 1:49Alex Kantrowitz?

  Absolutely. It's funny because we spoke last time we spoke was like the week that chat GPT came out or pretty, pretty close after it was launched. And now we have like AI news every day. Something big is happening and all the big tech companies are jumping in and really making some waves. So why don't we just start with the big news of the week, which is that, well, there's multiple stories, but this is the one that really caught my eye, which is that Meta is open sourcing its Llama two model. Now I think that like, You know, some people have, everyone's like looking for an ulterior motive right here. Like everyone's like, this is like a, you know, Mark Zuckerberg really sticking it to the competition? I don't fully understand how that's happening, but maybe you have a better idea of what's going on.

• 2:31Speaker 02

  Um, well, so I'll, I'll give you the, um, uh, the consensus theory about the, maybe sticking it to the competition. And then, and then a more, you know, uh, just maybe philanthropic interpretation with, with some self-interest. So, so the, the, maybe the, maybe in reverse order, um, you know, uh, Facebook formerly Meta now. I think actually has consistently released, um, open source technology and frameworks, uh, for the industry, uh, to, to leverage, um, in their, in their history. We use a bunch of technology that, uh, that came out of Facebook. I think it's been a core philosophy of that organization, um, to always kind of contribute software back or, you know, data center design, infrastructure design.

• 3:12Speaker 02

  You know, back to the community and, uh, the, the tech industry, I think, has always benefited from, from their open source approach. Now, um, you know, that, that both is great for all technology companies. It's also great for them because, um, you tend to see a sort of a flywheel where the best talent wants to work. And the companies where you can do leading research, you can open source your technology, AI, uh, in particular. You know, you can tend to attract the best AI talent if there's a, an element toward, uh, toward a more research oriented, open oriented approach. And so I think that's super attractive. They can get great talent. They can also, you know, make sure that they're, uh, that they're, you know, sort of, you know, providing more, uh, more, more kind of technology, uh, you know, shared practices across the industry. So that's all, that's all great.

• 3:56Speaker 02

  Now on the, on the more pure competitive dynamics, um, you know, I think there's an element which is, um, uh, which is on the margin. If, if you can sort of reduce the proprietary nature of your competition's, uh, technology stack. And, um, and this idea of sort of commoditizing, uh, that for the market, um, then on, on the margin, again, you, you might be able to reduce, you know, you know, some of the value proposition or some of that, that competitiveness, um, that, uh, that, that your competition might have. And I think it's probably a little bit of a stretch in AI right now for Meta like there's like to your exact point. They're not going to be monetizing the AI directly. They just want, you know, ultimately probably more usage

• 4:38Speaker 02

  of their platforms and AI, you know, can be a contributor to that. So, um, so I think that's probably the the one take which is well, if they can commoditize something that Google otherwise is going to make proprietary or charge for. There's some kind of game theory in that, but I think for the most part, it's probably way more of the you know, Facebook and Meta ethos of, of open source technology. And, uh, and then, you know, if you, I think if you look at like Yon as an example, you know, they've always been at the forefront of AI research. And so I think it's more consistent with just their, their kind of research and open source orientation as an organization. So that's sort of my, my best take. It, it, you know, brings in great talent. It puts Meta at the top of the, the food chain in terms of leading technology companies.

• 5:19Speaker 02

  It has everybody sort of, you know, studying their technology, their models. They become more of a standards bearer for the industry. I think that that all generally accrues good, good things to the companies that, that do that.

• 5:30Alex Kantrowitz?

  Right. So if you're Google, for instance, this, let's just talk about quickly the bad thing or the, the dark use of this. So if you're Google, you're trying to sell your, your version of Bard or whatever to people. And if Meta releases it open source, there goes a business line.

• 5:44Speaker 02

  Yeah, I think if you, I, I, like, I, I would guess that they've spent less than like an hour even thinking through that at, at Meta just because their, their, the high order bit is, is the, is the talent. And, and just being a leading AI company, but, but if you sort of draw it out and you say, okay, you know, Google makes their money on advertising. Facebook makes their money on advertising. You know, you, you, you're competing for ad dollars and attention, you know, on YouTube and Google search and whatnot. If Google's AI technology is, is superior or, uh, you know, delivers better, better results for the market, they'll make more money. If you, if you kind of, you know, find a way to sort of make that be an open technology, you know, you on like, you can kind of maybe bring down their competitiveness

• 6:27Speaker 02

  just marginally. But again, I, I really, I'm, I'm not convinced that this is, this is really an affront to, to any other major tech company. I think it's just net positive for, for Meta as an organization.

• 6:38Alex Kantrowitz?

  So yes, let's think a little bit more about the constructive uses. I mean, is it that Meta releases this and people will then, I don't know, build a chatbot onto Messenger? I mean, I know that's like the most rudimentary way of thinking about it. But what value accrues to Meta's products in particular? If like, everybody's all of a sudden building on their large language model?

• 6:58Speaker 02

  Yeah, well, I think, so if you roll back the clock, it was six or seven years ago, where, you know, David Marcus, Zuck, you know, these, these folks were on stage saying Messenger was the

• 7:11Alex Kantrowitz?

  Oh, yes.

• 7:12Speaker 02

  the future, the, the future of how you interact with, with businesses and commerce. And you would, you would say, hey, I want flowers delivered to me, you know, from this shop. And you would, you would do that through a chat session. And it really didn't take off if, if, if we're, you know, if we're being honest in terms of actual usage. But they were, they were really early to this idea of, you know, messaging platforms being a, a way that you would interact with, with, with vendors and potentially people. And so I think this, this wave of large language models probably gives them another chance to get back into that side of the business. You know, I think right now the conversation is probably on chatbots and, and, you know, sort of AI friends, as, as it were.

• 7:52Speaker 02

  I, I mean, I couldn't, couldn't guess possibly what, what, what, you know, how much Meta would, would care or do that. But, but certainly in interacting with businesses and becoming a, a leading interface for interacting with, with AI models, you know, WhatsApp, Facebook Messenger, Instagram, I think, you know, seem like natural platforms where, where, where one might do that. If this is a modality that continues to persist in terms of how we communicate with these agents.

• 8:20Alex Kantrowitz?

  Right, yeah. And it could be a crucial way. I mean, they still don't, they still have WhatsApp highly under monetized because they don't really do ads there. So it could potentially, I mean, I remember being at their F8 developer conference. I was a reporter for BuzzFeed and I saw them talking about messaging as the new platform. And I really believed in it and I wrote about it for BuzzFeed. And now I kind of feel a little snake bitten because. Wow, like, you know, it turned out that it wasn't just the technology that held people back. Like, you can full and well, like, book a flight on the kayak bot, but just people hated the mode of interaction. They'd much rather, like, tap a few things on kayak's app and then be good with it. So even if these bots get so much better,

• 9:04Alex Kantrowitz?

  like, what leads you to believe that this could possibly be different this time?

• 9:09Speaker 02

  Yeah, well, on the snake bitten, to be fair, I mean, I think it was probably not a malicious snake bite.

• 9:16Alex Kantrowitz?

  No, no, I don't think it was malicious, but they sold the vision. And I, like, told readers, like, hey, this is gonna happen. And also, I had access, I think you must have also, to Facebook M, like, their messenger assistant that, like, actually had contractors in the WhatsApp building, actually, on the other end of it. And that was so mind blowing. It was people, but it was assistive and very cool.

• 9:38Speaker 02

  So unfortunately, I'm like the worst person to ask on this because I have always been convinced that chatbots are just one iteration away from happening. In 2003 or 2004, I started developing chatbots for AOL Instant Messenger. And so there was this wave of chatbots. One was called Smarter Child.

• 10:08Alex Kantrowitz?

  Oh, yes.

• 10:09Speaker 02

  You remember that? And then you would ask it questions, you'd get, like, movie theater times and whatnot. So I've, like, always been, you know, sort of, you know, red-pilled on chatbots. And but to your exact point, the challenge is you're always competing with the powerful, you know, with a powerful graphic, you know, graphical user interface, where we're just in two clicks without any, you know, verbose typing, you can get exactly that same answer. And so I do actually, I think the jury's out, to be totally honest, on what... You know what the form factor ultimately will be for a lot of these AI interactions. And, and you know, you do see some examples where you'll see a viral video of, of somebody

• 10:52Speaker 02

  interacting with some software via a chatbot and you're like, holy crap, that's the most amazing thing ever. But then you kind of like, you know, you kind of, you know, you flip it and you sort of say, well, actually like, how many clicks would that have been on just a normal website? And it's like, okay, that could have just been two, two clicks. And, and you could have done the same thing. And so, you know, I think the one, the one challenge we're going to run into on the chatbot craze is often this element of you don't know what the, the AI bot is able to do. And that makes it, you know, sometimes a complicated paradigm because at least with a graphical interview, user interface, that it's really the responsibility of the software provider to say sort of, here are all your options that that are available. Here are all the buttons you can click. Here are all the, the things in the menu. Those are the functions that we can provide you. And a chatbot, you can't really, you don't

• 11:37Speaker 02

  really know in advance, what are all the, the sort of functions that that service offers you. And so, so you can have a lot of dead ends or a lot of incomplete experiences. And I think that will be the fatigue that consumers end up having in some cases is when they, when they go and try and interact with one of these bots and it doesn't produce the thing that they wanted to do. Are you willing to go back to it again and again, if you know that there's a lot of these kind of dead ends? So, so that, that tends to be the problem with, with these chatbot assistants. I think that's probably what Messenger and WhatsApp and, you know, Facebook has sort of run into in the past. Large language models, I think, you know, open up the, the surface area of what they can ultimately solve. But it's, I would say we're just in the very, very starting, you know, kind of period of this.

• 12:19Speaker 02

  I think it's been fun to watch like Pi and Inflection as, as a, as at least, you know, one potential outcome of this. And, you know, I think, you know, if you listen to Mustafa talk, right, there's, there's this vision of you just be able to, you know, book a, book a flight and, and this sort of assistant would know exactly, you know, how to do that for you and, and what to do. And I, I, I think that's an incredibly exciting, audacious, ambitious vision that would be amazing for that to happen. Of course, there's going to be some questions, which is, well, a lot of people have these very idiosyncratic preferences or, or Things where you're gonna have to go back and forth with the bot enough times that that you know another you know again a just a classic user interface might be a better way to do that. But I'm excited to see all the exploration. I think it's great that we're we're trying a bunch of we're we're kind of pushing the boundaries.

• 13:04Speaker 02

  Um, of software and um, and user experience. And I think it's only a net positive for all of us that. That there's going to be innovation going in lots of directions. Maybe we look back in five years and we say, okay, you know, we still don't really like doing chat for most of our interaction. But but nevertheless, you know, uh, these large language models uh, are solving a lot of problems behind the scenes. Because of their kind of reasoning skills and and logic that they have in them. And that's another kind of outcome that this technology could lead to.

• 13:31Alex Kantrowitz?

  Yeah, it could be that it just kind of hangs in the background and then you're like going to a certain page and it pops out with like a English language suggestion.

• 13:39Speaker 02

  Right.

• 13:39Alex Kantrowitz?

  Or natural language suggestion. And then all of a sudden that makes it's a kind of interesting. I feel like. We're both and and I think many people watching this are in the same place where it's like, oh, wow, like this is like. Unbelievable technology and like now the question it's gonna do something and the question is like, what's it gonna do?

• 13:55Speaker 02

  Yeah, well, there's and I think there's a continuum. So on the enterprise side, uh, we we sort of already have a very strong sense of what it can do that we could never have done previously. So like where where in the in a lot of the enterprise use cases, you're not competing with a with a graphical user interface. You're you're solving a problem that that quite literally could not be solved previously. Like you, you literally could not go to in our in our business, you could not go to. A data set of information that was made up by, let's say, documents. And ask that data set a question and have an AI model and then have any way to a actually answer that question from a large set of documents. It just was not possible. This was not something that search could even do.

• 14:33Speaker 02

  And now these large language models with with, you know, combined with with um, uh, with with this idea of a vector database, uh, you can now solve that problem. And so, and so in that case, there's, there's, you know, unlike the, you know, kayak inside of Facebook Messenger where you had an alternative, you could just go to kayak.com and do that same experience. There's literally no alternative to many of these enterprise applications with AI. And that, that, you know, we're a hundred percent confident is a breakthrough in, in terms of these, the, you know, what we can now do with software. On the consumer side, obviously, if, if, if you're really just replacing how, was something you already would be doing today, but now just via a chat interface. That has a lot of other elements that have to kind of go right around sociology and human computer interaction and all of that.

• 15:17Speaker 02

  But, but, and so, you know, that, that one will, will certainly remain to be seen.

• 15:21Alex Kantrowitz?

  So let's just talk quickly about Lama. I keep wanting to call it Lambda, but that's clearly not the one. So Lama, what do you, have you heard anything like, are you, is your, are your developers interested in using it? Have they used it? What do you think it can, like, okay, it's a big, large language model. It's open source, not really open source. We're going to get to that in a second, but it's open source to a large extent, right? And so what are companies going to do with this thing?

• 15:48Speaker 02

  Yeah, so, so first of all, I, I think it's incredibly exciting that we are at this moment in technology where you have so many different at scale, highly capitalized, very, very, you know, kind of intelligent organizations and individuals in these organizations that are all, all advancing the state of the art of AI.

• 16:09Speaker 02

  You know, I, I think, I think nine months ago, you know, the common comparison, and I use this comparison as well, because, because I, I lived through it was, you know, like ChatGPT was sort of this iPhone moment in techno, of AI, because it finally made interacting with an AI model, this sort of consumer at scale value proposition. The thing I missed at the time that now is, is very clear is like, it's like an iPhone moment, but like, but, you know, on steroids. Because, because not only do you have iPhone and Android, but it's, you have 10 other operating systems and 10 other, you know, phone manufacturers all vying and all competing for, you know, the, whatever the state of the art is, and on a daily and weekly basis.

• 16:50Speaker 02

  So, so we are, we're seeing a, a level of, of scale of innovation that in a, in a platform shift that I've never, I've never seen. That doesn't even compare to, you know, cloud computing or the early web. This is a different kind of scale now. The impact obviously still has to, we have to kind of see how this plays out. But the fact that you've got Meta, Google, Amazon, Microsoft, IBM, Anthropic, OpenAI, you know, just, just an incredible amount of organizations all building, you know, break, you know, breakthrough, either large language models or diffusion models, I think is a, is a pretty incredible, you know, moment. And, and with Llama, I've only played with it for like five minutes.

• 17:31Speaker 02

  So, so I'm not, I'm not fully up to speed on, you know, how it would benchmark across, across GPT 3.5 or four, but it, it feels fast. It, it is the quality of answers that I've at least seen in my very rudimentary tests have been pretty, pretty, you know, you know, high, high quality. And I think the play and the value proposition of a, of a sort of a commercially used open source, large language model is that I as a developer could go take it. I could change the weights of it. I can fine tune it in the way that I want for my particular set of use cases. And I can kind of run it on my own infrastructure. That's a, that's a pretty, you know, substantial value proposition for, you know, a large number of developers and a large number of use cases.

• 18:14Speaker 02

  And, but, but, but pretty akin to, pretty akin to how we always think about kind of open source, which is, which is if you have the prerogative and the, the skillset and the, and the need, open source gives you some really great benefits. And then there's a lot of people that say, you know what, actually don't need that level of, of, of, you know, customization. I don't really need to own my own hardware. And so I'm fine with a commercial approach. And so then, you know, I could just stay on, on what I'm doing with OpenAI or another commercial vendor, Anthropic, et cetera. And so I think, I think it's just great to have choice in this market and it's going to push the industry forward because you're going to see this sort of constant leapfrogging, you know, between providers. And it's just going to, again, dramatically advance the state of the art very quickly.

• 18:57Alex Kantrowitz?

  So it's got, it's going to have companies building their own applications on top of this stuff. But it's interesting because the way that you describe it, it seems like if you're smaller, you, it might have less appeal. You'll just go with like something off the shelf. If you're bigger, then all of a sudden it becomes interesting. But this is where things become kind of complicated because this is from Insider. It talks about how it's not exactly so open source, right? So the story says in Meta's terms and conditions for those requesting access to Llama 2, the company states that larger users won't be granted access to the model in the same way smaller companies, individual developers will. Any company hoping to use Llama 2 with a user base of 700 million active users a month or more is required to request use of the model.

• 19:40Alex Kantrowitz?

  I guess that's just protecting like the direct competitors from using it. You're smiling. What do you think about that?

• 19:46Speaker 02

  I mean, I mean, yeah, that that filters out four companies on the planet. So I'm not, I think, I think that that is a, that's basically just a nod to saying, hey, Google, please call us. Just give us a ring if you're going to use the the language model. But, but I don't, I don't think that's a, I don't think that's going to be a, an issue for, you know, 99.99999% of the world.

• 20:09Alex Kantrowitz?

  Apple is in the game also. This is coming from Bloomberg. Apple Inc. is quietly working on artificial intelligence tools that could challenge those of OpenAI, Alphabet, Inc., Google and others. But the company has yet to devise a clear strategy for releasing the technology to consumers. It's built its own framework to create large language models. And some people inside the company are already calling it Apple GPT. It's so strange because Apple, you know, it doesn't have any like really successful consumer products. I mean, of course it has calendar and maps and whatever, but like, and it has messages. Okay, now maybe I'm talking my, my argument away, but like, it just doesn't feel like

• 20:50Alex Kantrowitz?

  it has any like real consumery products, like a social network or chatbots or anything like that. And I don't, can't really imagine it like, building these models and then licensing them like an OpenAI would. What do you think is happening inside Apple right now?

• 21:06Speaker 02

  Um, yeah, well, so I, I, I would probably counter on, on the core, the core, you know, supposition, um, the, uh, I mean, I, uh,

• 21:14Alex Kantrowitz?

  I basically rebutted myself as I was asking the question.

• 21:16Speaker 02

  I mean, I mean, between, between Maps and, uh, and, and Apple TV and, and iMessage and photos and camera, I probably use, I probably use their software more as a consumer than anything else at the moment, but, um,

• 21:30Alex Kantrowitz?

  But you know what I mean? It's the, the tie, this type of app they don't do.

• 21:33Speaker 02

  Hundred percent.

• 21:34Alex Kantrowitz?

  Utilities, yes.

• 21:35Speaker 02

  Yes. Well, well, that's actually, so that's an interesting question. So is this a utility? Or is there, you know, like, I would actually argue that, that the, you know, their play here should, should be pure utilitarian and, and, you know, it shouldn't be a social thing. And to your exact point, what there may be less, you know, apt to go and pursue. And so, um, so I, you know, to, to me, you kind of just like step back and you say, okay, should you be able to grab your phone and just say, hey, can you order me a pizza? And then, and then a little dialogue comes up and it sort of says, hey, you know, here's where we're going to order the pizza from, click yes, uh, if you want it. Like that, that seems like the most obvious thing on the planet, uh, that, that Apple should just do as a, as a phone. Uh, or, you know, hey, please write down a note for me to go do

• 22:20Speaker 02

  this thing and remind me later. And it just like gets it right every single time. Um, and obviously, you know, that's just like Siri plus plus. Um, but I think Apple has both the device, the, the software prowess for it. Um, and, um, and maybe they were kind of like late to large language models in this current ilk, um, by nine months or something. But, but, you know, the good news is that everybody's still buying their phones. And I think people would switch overnight if there was an integrated application, you know, right on the device that, um, that could solve that kind of use case. So, so I think if they, if they put their mind to it and the use case was a smart assistant on your phone that could kind of do everything, um, I would be very optimistic about their, their hit rate and their success and, um, and driving a strategy like that.

• 23:03Alex Kantrowitz?

  I went right to Hacker News after the news broke and it was amazing to see the conversation. I mean, it's kind of what you expected. Like half of the engineers are like dreaming up these amazing products that Apple can build and the other half is like, how about fixing Siri? I mean, they, they really have, it's, it is embarrassing how, you know, what they've done in terms of like the assistant. They were first. It seems like we're still using Siri 1.0, maybe 2.0. And so like the question is like, yeah, are they even capable of doing this?

• 23:31Speaker 02

  I think they, well, definitely they are. And, and I think that, I think this is just one of those things, you know, Apple, Apple is willing to take their time and, and study a market and decide when is the right time to enter a market. And I actually would say if in, I think if in, you know, three months or six months or nine months or whatever, when they launch, you know, Siri 2.0 based on an all new large language model or whatnot, I, I think, I think within, you know, a month of that happening, we will have forgotten, you know, whether we thought Apple was late or not to that. It just won't have mattered like Apple will just like, like they, they, they, they take the time to get the thing right. And I think we are in such an avalanche of, of innovation and change right now that in

• 24:17Speaker 02

  a weird way, you know, there's a premium in, to kind of leaning in, understanding the market early. So you understand kind of all the different fractal, you know, ways that this is going to kind of take off. But there's not like a huge premium in, in sort of like just being right out there with a product, no matter what that product is like, it's actually the premium is, is making the right decision on the right architecture, on the right user experience. And Apple is not one necessarily to do iteration and beta testing in public. And so I think by the time that we see a product from them, it'll be, it'll be one that has now learned a lot of the lessons that we're already talking about, about where these things kind of get, get it wrong. I don't think, you know, if you, if you even just take things like hallucinations, right? You know, it's not really on brand for Apple to give you a product that's just going to like hallucinate a ton.

• 25:01Speaker 02

  And so they probably want to figure out like, what is the right kind of, of, you know, approach that we should take where it's not just making up answers all the time for all of your questions. Um, and, and so what, what is that, what, what is that, you know, architecture? How should it plug into, into search? Those kinds of things I think, I think makes sense that they're taking their time to, to get right.

• 25:20Alex Kantrowitz?

  One of the things that was really interesting in the story is they talked, it talked about how Apple views this, it's getting into this because it doesn't want to miss a potential platform change. And I think that just kind of says so much about where this is heading. I still don't think it's necessarily like, we have to see this happen, right? Like there are still open questions again, like we talked about. In the beginning about like whether people want to use the like the chat function to begin with. I mean, I think they'll probably gravitate towards that, but it's just kind of interesting to see how how seriously Apple views this. And my hunch is what's going on in Cupertino right now is they're looking around. They got some vision pros lying on their desks and they're like, goddamn, we just spent five or seven years

• 26:01Alex Kantrowitz?

  trying to build for the next computing platform, which was the metaverse or whatever ARVR. And this chat thing just surprised us like a lot of people, right? Maybe met it the same way. And now they're saying, all right, let's let's get the, you know, get it going on that front.

• 26:15Speaker 02

  Yeah, yeah, I think, um, I, I, I, uh, I, you know, the good news about Apple is, is, uh, again, they, they, while they take the time to, to get things right. When they then decide to turn on the engine, uh, they, they see it through and, and then will commit to it. And I'm, I'm pretty confident that they've got the right kind of prowess to, to do that if they, um, if they decide they want to.

• 26:38Alex Kantrowitz?

  But they haven't really been able to like, show that they can really excel in a paradigm shift of technology. I mean, well, I'll just take the voice computing thing, which is most recent, right? Like, so you had Amazon and Googled, they did, I mean, obviously it didn't turn out to be, you know, what a lot of people thought it was going to be. But Amazon and Google took the lead. They come out with the HomePod, um, and flops. So I don't know if they're going to really be able to navigate this change. It's a, it, it seems like they're very good. And maybe this is an archaic argument, but it seems they're very good at refining the iPhone and less about like thinking about brand new areas of computing, although the Vision Pro was impressive. I, I still don't feel like they can do it.

• 27:19Speaker 02

  Well, I, I would say this is, I mean, this, this sort of benefits from a lot of the iPhones. This, this actually dramatically benefits from a lot of the iPhones kind of innate characteristics. So, so, so I wouldn't, I wouldn't actually think about it as sort of like out of left field or orthogonal to, to the iPhone. I, I think it builds on, um, uh, you know, like, again, literally, if you just, I mean, voice might even be the right way to interact with this for a lot of, for a lot of the use cases, you know, versus like an actual chat interface. And so if you think about just what they are built for, we again are all, you know, you know, a second away from being able to talk to our phones and ask our phone a question

• 28:03Speaker 02

  and get an answer back. And so, and, and, you know, at this point, you know, does, you know, building an actual large language model is extremely well understood. One of the interesting lines that I didn't actually fully realize or understand like a year ago, but now I, I like, I'm a lot more steeped in from one of my kind of top AI friends is there's no secrets in AI.

• 28:23Alex Kantrowitz?

  Yeah.

• 28:24Speaker 02

  And, and it's because there, everything is such a research forward, research first kind of approach in this space. And so if you have a space that, that really there's no secrets and, and actually right now, the skillset that seems to be required is capital and then, you know, you know, 10, 20, 50 AI engineers, but not a thousand. That's something that I think Apple is extremely capable of putting together and then designing an incredible user interface around. So I'm going to take the other side on this one and I, I would be, I'd be bullish on, on their approach, whatever they decide to do here.

• 28:56Alex Kantrowitz?

  We're going to go to one of my favorite segments when we have you on the show, which is Reed Aaron's tweets or Reed's threads, because this is applicable. So this is talking about moats. You, you say, I've probably spent more time debating where AI moats will be created than perhaps any other tech trend to date. There's something quite fascinating about AI where the deeper you are in the stack, like training models, you have risk that there's a technical breakthrough and that, and that leapfrogs your approach. And the higher up in the stack, like thin wrappers, you're at the mercy of platforms not competing with you. There will be trillions in value generated, but it's too early to tell where. It's very interesting. I mean, we have all, I mean, you basically have all, all these big tech companies and small, you know, smaller startups are all like what we've talked about up until this point. We talked about Facebook model, we talked about Apple model, we talked about

• 29:41Alex Kantrowitz?

  Googles. The question is like, really like where the points of differentiation are. So you've had these debates about where the modes are, who's going to really come up on top and, and profit from it. What are your, what are you leaning towards now? I mean, I know we don't know yet, but.

• 29:57Speaker 02

  Well, so I'll give you the two obvious ones, and I hate to bring them up because they're so obvious. So, and so the first one's really quick. So, you know, at the Nvidia level, an obvious winner. Because at the end of the day, you know, all this stuff has to run on, on, you know, at least today GPUs. And there's a very small number of relevant players there. So, so you kind of know the infrastructure winners just automatically. On the opposite end, you have, you have the existing software that already has data. It already has users, it already has workflows. And AI becomes this kind of booster into the software that makes that software more useful, more valuable, more intelligent, more functional.

• 30:40Speaker 02

  And, and, you know, for all intents and purposes, I mean, I'm, I'm sort of, you know, I'm talking my book, but it's, it's going to be, you know, SaaS product probably in, in, in the enterprise space. It's going to be the ServiceNows of the world, the Lassians of the world, you know, We Believe Box and, and other players. Because we can plug in AI into our software and just make that, that a much better experience, be able to solve problems for customers that they couldn't solve before. So, so those ones are, are pretty obvious. The, the reason for the, the thread was, was on one hand, and this is actually, I mean, again, like, it's funny how fast these things age. Like, this was before Lama, Lama 2, that, that I wrote that. You know, imagine you're going down a particular architecture paradigm and you're an AI model trainer.

• 31:24Speaker 02

  So you're at, you're at that level of the stack. Lama 2 comes out, the entire world, all of a sudden, puts all of their energy, maybe temporary, but, but they put all their energy on Lama 2. And they're like, oh, this is now, you know, God's gift to open source, you know, AI models. Very quickly, if you were training an inferior, you know, open source, you know, LLM, you're, you might already be on the wrong architecture. And now you have to kind of move over to Lama as the, as the new, you know, sort of, as the new, you know, model that, that you, that we're all going to kind of be building on.

• 31:58Speaker 02

  And so the speed at which that happens in this industry, I've never seen before in terms of, of how quickly everybody will kind of just shift their, their, their lens on the, on the underlying technology. Conversely, all the way up the stack. I think we've already seen examples where a company that maybe was building a very lightweight interface on top of the L M of like, okay, we're going to give you an interface to produce text for some use case. We're already seeing that unfortunately, the actual, you know, underlying product providers are kind of incorporating many of those features into their into their products, whether that's chat G P T or Bing or whatnot. And so then then it's very, very hard again to survive as as kind of one of these kind of quote unquote thin wrappers. So so I think that that was sort of the the reason I wrote that out is like, I, you know,

• 32:42Speaker 02

  it's it seems pretty tough to be an A I model trainer unless you are meta, Google, Microsoft, OpenAI, Anthropic, and and you definitely don't want to be one of these just pure thin interfaces on top. You've got to really establish a a high degree of of of value and and probably workflow and and kind of data mode associated with your product.

• 33:04Alex Kantrowitz?

  Yeah, and that that thin wrapper thing, I mean, it's really unbelievably competitive. And the thin wrappers, I mean, when when OpenAI came out with chat G P T plugins, it was just obvious that like, you're gonna have companies that will build and maybe they'll have some proprietary like relationships that they'll be able to build into the A I. Like if you're like, for instance, I don't even know, like a kayak potentially, like you have the relationship with the airlines. So you could have this one bot, but even that just like seems like it might be subsumed by A I. But the things that really seem like in jeopardy are like the character A I's where like you can, you know, chat with George Washington or whoever, whatever historical figure like you can really just go into chat G P T and say, you're George Washington. And next thing you know, you might have something

• 33:44Alex Kantrowitz?

  on par. Or like you're a Jasper, which allows people to like, write better with A I and you could just go to chat G P T and say, help my writing.

• 33:54Speaker 02

  Yeah, so so, you know, I might separate those those two slightly. I think I think on the character. Oh, actually, actually, I'd say both of them have a path to differentiation. But but I'm not close enough to either to understand where that value would be. But but, you know, in the character AI thing, you know, I think there's probably to the user of character AI, there's probably something psychologically different about going to chat GPT and saying, pretend that you're this person and then interacting versus, you know, sort of the the modality of character AI is sort of you're you're jumping right into that. And there's a little bit of a a community or network effect around those characters. But I'm not I'm not close enough, so so I'm I'm kind of freelancing on that answer. But I and on the Jasper thing, that that was sort of one of the one of the, you know,

• 34:37Speaker 02

  obviously, you know, current case studies of of, you know, all like they they had this kind of, you know, lock on a market, let's say, a year ago, which is I want to write an SEO blog post, you know, on some topic and and they built like the best workflow interface for doing that. OpenAI comes out and or chat GPT comes out and and it's basically completely free. You just don't have the workflow on top of it. And and so how do you, you know, kind of provide enough differentiation? And so I think there's going to be some some really interesting kind of competitive game theory, you know, lessons that that these companies will have to figure out as as we witness the the the dynamics in this market.

• 35:13Alex Kantrowitz?

  Aaron Levy is here with us. He's the CEO of Box. We're talking AI. We've touched on Apple and Meta. To begin with, on the other side of this break, Microsoft, Google, and then plenty more. We really have a lot to talk about. Let's talk about jobs on the other side of this 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,

• 35:55Alex Kantrowitz?

  now extended across your entire AI estate. Your data, your cloud, and the agents acting on your behalf. It's how more than 28,000 organizations deploy AI with confidence. So innovation scales without scaling risk. Avpoint, the unifying trust layer for AI. Head to avpoint.com to see how enterprises deploy AI with confidence. Learn more at avpt.co/bigtechnologypodcast. That's avpt.co/bigtechnologypodcast.

• 36:30Alex Kantrowitz?

  Violent threats against executives are growing at an alarming rate. When a company experiences backlash, executives are the first people blamed. When their address and other personal details are sitting online, this backlash can lead right to their front door. The team at Ironwell knows this better than anyone. They've protected some of the most targeted executives and individuals on the planet for almost two decades. As a wide glove enterprise security service, they protect your people with continuous personal data removal, proactive prevention tools and human-led emergency support. So when someone goes looking for your executives, Ironwell ensures they hit a dead end. So here's what to do. Go to ironwall.com/bigtechnology, fill in the quick form and request your free risk assessment. Their team will show you just how exposed your executives are

• 37:15Alex Kantrowitz?

  and how to lock it down before a threat reaches their front door. That's ironwall.com/bigtechnology. Learn how to stop online threats before they become real world attacks. The link's in the show notes.

• 37:35Alex Kantrowitz?

  And we're back here on Big Technology Podcast with Aaron Levy. He's the CEO of Box. Let's do some more news, shall we? So Microsoft this week, shares rose 5.8% on Tuesday, just in a day. This is from CNBC. After the company announced new artificial intelligence subscription services for Microsoft 365, the company will charge users an additional $30 per month to use generative AI tools in Teams, Excel, Word and other places in their product suite. I don't know. First of all, I think there's, there's levels of insanity all the way down on this one. The stock market sending Microsoft stock 5.8% to the north. I mean, it just seems like you say AI and this, I'm actually kind of curious how you feel about this as a public company CEO.

• 38:20Alex Kantrowitz?

  You've got to be careful, right? You got to keep the market's expectations like, you know, now Satya Nadella is like, dang it, like we did this one product now at my company and I have to justify a 6% more in expectation. So that to me is, is bananas. And then the other side of it is $30 a month to do this. I mean, you can go over to the Google Office suite and I'm part of a test group now where in labs you can just hit like, write it for me and Google Docs and Gmail will give them a prompt and there, there's your email or there's your document. So it's like, wait a second, that's a lot of money for something. Again, going back to our themes, you know, no moat. What do you think?

• 38:58Speaker 02

  Well, so I would separate the pieces out. So on the market's reaction, I'm, you know, if everything goes as according to plan for Microsoft, actually, the market's reaction weirdly makes, I mean, it just mathematically makes sense. So let's say they added, I'm gonna just make this up, you know, they added $100 billion of market cap or something, whatever the number is, you know, from that, or 150 billion in market cap.

• 39:24Alex Kantrowitz?

  No big deal.

• 39:25Speaker 02

  Yeah, no, no, no big deal. But if you just kind of multiply sort of the expected, you know, revenue generation from, from that uplift in price on their Microsoft 365 subscriptions, you kind of have a certain expected profit margin, you multiply that profit margin by what they're trading at in a P/E ratio, and like weirdly, it actually probably just like checks out that like that is sort of what they actually did add in terms of market cap. If they can, if they can actually generate the revenue and profit that's tied to this increase. So, so that aside for a second, in terms of, you know, will the market bear that price? That is like, you know, we'll find out pretty quickly in the next, you know, you know, six or 12 months as customers start to, to go through these upgrade cycles.

• 40:08Speaker 02

  I think it's a pretty steep price, but also Microsoft is, is, you know, a, a company that has a very strong, you know, command on, on the customer base. And, and we'll see, you know, sort of what, what ends up happening. I think right now there is a moment where, where IT leaders, CIOs have to continue to show that they're, they're solving AI problems. That's, that's sort of why Copilot, I think, has, has gotten a lot of support from the market. You know, this is why certainly our number one conversation with customers right now is on AI and customers trying to figure out, okay, how can I use AI on my content in a secure and safe and privacy oriented way? And I think Microsoft will benefit from a similar set of conversations across the productivity stack.

• 40:49Speaker 02

  But yeah, I mean, they are, they are certainly taking advantage of, of this moment in the market.

• 40:54Alex Kantrowitz?

  Yeah. And what about the fact that you could go across the street to Google and get those similar services for free?

• 40:59Speaker 02

  Yeah, you know, in reality, any midsize enterprise or on up or will not make the the switch on the basis of AI pricing. So if you're a, if you're a, you know, a 5,000 person company and you're already on exchange and you're already on office and you're already on Teams, AI will not be the determining factor as to, you know, kind of switching out your entire, your entire infrastructure. So I, and I think Microsoft knows that and they're in a good position to, to kind of benefit from that, that effective, you know, kind of stickiness of the, of the platform.

• 41:29Alex Kantrowitz?

  There's another story that I wanted to lead with that kind of, I had to push down because we, I mean, every big tech company is making news on this this week, but let's talk about it now, which is the, it seems like people are saying that ChatGPT or the GPT models are starting to degrade. I mean, this is from Insider. It's very interesting because there are so many different ways to read this story. I'm very curious what you think. So it says, "In recent weeks, users of OpenAI's GPT-4 have been complaining about degraded performance, with some calling the model lazier and dumber compared with its previous reasoning capabilities and other output." It's so interesting. Like, I, I have this theory that these chatbots have spent, you know, they were spending their time talking to OpenAI engineers and they were freaking smart and they learned from

• 42:13Alex Kantrowitz?

  the people they speak with and then they got released to the general public and yeah, they're dumber. So that's one possibility. The other side is that maybe they don't seem as amazing to us the more that we chat with them. What do you think?

• 42:26Speaker 02

  Well, I don't remember where I saw this. I'm pretty sure it was, I'm pretty sure it was from an OpenAI employee tweet, but if I'm wrong on that, then, then, then, then obviously don't, don't go off this. But I'm pretty sure an OpenAI employee claimed the, the, the second explanation, which is, you know, we're now used to this. And so, you know, if you kind of imagine, if you imagine like going from no ChatGPT to ChatGPT, like, it's like that level of jump. And now, and then, and so now this is our new baseline and we're kind of watching it over time and our, our brains are not having that same instant kind of reaction of like, holy crap, this is the craziest thing of all time. We're now in this sort of expectation mode of like, yeah, you're gonna, you're gonna produce text for me with my question.

• 43:10Speaker 02

  And I, so I think now we are a lot more, we're a lot more critical of now the information we're getting back because the core novelty is now over. And now it's actually, we're like fundamentally in the, you know, are you telling me very useful, how reliable information? And so I think our, our level of criticality has just gone up because there's no kind of novelty factor that's sort of overweighting or outweighing the critical, you know, kind of, you know, maybe component that we wouldn't have had nine months ago as the technology was new. So that's, I'm actually more probably in the camp of the latter, but you know, who knows, maybe they did some kind of training update or, or model weights update that, that made it dumber. But, but it seems like it might just be our

• 43:52Speaker 02

  expectation level is now, is now off relative to, to, you know, where these models are.

• 43:57Alex Kantrowitz?

  Yeah. And there has been like a decline of interest that you see in Google search trends. And there's been a decline in use, at least according, or the slowing of growth according to some third party reports. We have a professor from Wharton coming on, on Wednesday, Ethan Mollick, who is going to talk about the impact of this on education. Just going to plug that. But it is, there have been some people saying it's just, oh, it's the kids. They're, they're not using it to cheat anymore. I'm curious what you think, what you think we should make of these reports? And what has your personal use been like? Have you been using these bots less in the past few months? I know I have.

• 44:30Speaker 02

  Yeah. I mean, so I'm probably, I, my, my usage pattern's actually been pretty constant, other than the first week where I was just testing everything. I was just typing in the dumbest stuff. I mean, I, I would say I am a regular user for business, like some category of like business brainstorming. So if it's like 10:30 at night and there's nobody, you know, in the company that I can kind of quickly run an idea off of or ask a question, I might go. To chat GPT and, you know, brainstorm a product category or a name or, or, um, uh, you know, help, help me to kind of synthesize some of my thoughts. Um, and, uh, and so I,

• 45:12Speaker 02

  I've been pretty much commonly using that for, for the entire existence of the product. Um, uh, we had a, uh, we had like a goat, we, we had what we thought was a gopher problem, um, in our yard, um, uh, like, uh, like two months ago and I was, I went down like a gopher rabbit hole.

• 45:28Alex Kantrowitz?

  Oh, my God. Was it, you thought it was a gopher problem? It wasn't, it was like a hedgehog problem instead?

• 45:33Speaker 02

  Well, we, we never validated actually what it was, but, but I learned a lot about gopher holes, um, uh, from GPT. So I, I really hope it was not hallucinating.

• 45:41Alex Kantrowitz?

  You went down a, a gopher hole, rabbit hole. No, I'm sorry.

• 45:44Speaker 02

  Exactly, exactly. Um, so, um, so I think, I, I think it, it, you know, what, what's interesting is it very clearly is it's, it's different than search, right? And so, and so like, I don't know that we even, I, I still, you know, in July of, of 2023, I still don't know that we've got a perfect term for what category these things are in. It's, it really is this new emergent, you know, kind of, you know, technology use case where you have this intelligent, you know, thing that you can go and, and ask questions of and, um, and help you kind of work through, work through your own thoughts or, or help you sort of figure out what, what things you want to then go and dive into. I've done a lot of

• 46:26Speaker 02

  things where I'll go to chat GPT, ask a set of questions, learn about a set of things and then go to Google to then go dive really deep into the research on whatever that topic is. And I, and so it clearly is not a, a one-to-one replacement as much as a new complement to sort of working through information. And I think what, what we're probably finding is actually like, like, you know, that is not, um, that's not a use case. Maybe you do five times a day in the same way that you're Googling, like, what time is this restaurant open till? Um, uh, and like, and so that, that's just like a different behavior that, that we don't, you know, we don't do these like broad information, you know, sort of understanding type, type scenarios, you know, you know, five times a day, um, in our, in our personal lives at least.

• 47:09Alex Kantrowitz?

  There are a lot of companies that I think are trying to pull a fast one on everyone in terms of saying, you know, we're in a moment of, of, you know, companies trimming down and doing layoffs. And they're, and, and obviously another moment where if you say AI, the market will reward you and they'll reward. They have been rewarding companies for layoffs also. And some companies are trying to like blend the two into one. I mean, you had IBM, for instance, that said like, oh, they're not going to hire anymore because they're going to give these tasks over to AI. And I had people from IBM or who had been in IBM saying LOL, like that's not going to happen. This company is not able to pull that off. And even one of your competitors, Dropbox, right? They had to do a layoff and they said that they're going to pivot to AI. And this is from Drew Houston, the CEO there.

• 47:55Alex Kantrowitz?

  Our next stage of growth requires different mix of skillsets, particularly in AI and early stage product development. So, okay, it's people building AI, but you know, there's been this meme chat GPT is going to take your job. It hasn't really yet. Why not?

• 48:09Speaker 02

  Yeah, I'm, I'm, I'm firmly, until proven otherwise by some breakthrough I haven't seen yet. I'm firmly in the camp of this is all net positive to jobs. I think that, you know, first of all, we are so early on, on any form of kind of like multi-operation, tasked string together with any level of efficacy to be able to replace even, even like 10 minutes of what a real person does in their job. So right now, I mean, you, you really got to think about these things as they can take, they can do like one discrete information oriented task.

• 48:50Speaker 02

  Basically at a time before they need a human to kind of review what they've done and then move to the next thing. And, and again, I don't, I don't really see an architecture paradigm that would change that anytime soon. And so, and so basically they can do, they can do tasks where they take some information. They they go and look across other information, they can produce something and that that thing that they produce can go somewhere certainly automatically. But but usually you very quickly need a human in the loop to to to review or kind of help streamline whatever that was. And so that's just not that many jobs are are relegated to only that kind of thing. Even even in the even in the scenarios where we've kind of like tried to say, okay, well, the paralegal job.

• 49:35Speaker 02

  You know, could could be automated or whatnot. It's just it's just simply not true. There's just too many things that that these job functions. Are pulling together across across email and a communicate and another communication tool and a manager. And going into some other system and then reviewing something and then writing something. And and the AI is just not, we're just nowhere close for the AI successfully to wrap all those those scenarios together. And I'm just not seeing anything on the horizon that would change that because the cost of an error is so high. That that that no one is willing to put that, you know, the liability on the line. Would be required. I mean, look at just even that one example of the lawyer that, you know, used. Chat GPT had hallucinated cases.

• 50:19Speaker 02

  And and now they're like, you know, they've been sanctioned or whatever the the, you know, consequence was. You know, you can't have paralegals running around everywhere, being replaced by AI, just producing, you know, all this stuff that doesn't get reviewed. And then we just put it into the legal system. It just simply won't happen. So so I'm I'm not convinced that I've so so so that's like the that's why the the doomer scenario I just don't buy right now. And now actually you flip it to the optimistic scenario. And I actually think more more of our economy is constrained by either talent. Or the cost of of of that talent, not by the demand for for the for the talent. And so I think in most areas for the of the economy, if you could make something 20% cheaper or or conversely 20% faster.

• 51:04Speaker 02

  You would probably use more of that type of resource or service than than you would than than instead of kind of capturing the savings. And and that that is, you know, there's there's sort of, you know, two, you know, there's there's sort of two complementary economic, you know, rules or fallacies or principles that are at play. You've probably, you know, written or talked about both. You have you have this idea of lump of labor fallacy and you have this Jevons paradox fallacy, which is which is both of them basically amount to. We tend to think that if we made something more efficient, jobs will go away. And actually, by making that thing more efficient, demand rises because we've been able to actually get more output out of that thing.

• 51:49Speaker 02

  And actually, the cost of that thing was was the main reason why we didn't use it previously. So so, you know, even in the example of like an engineer, let's say, if I can, if I could ship 20 or 30% more code, then we're not going to have 20 or 30% fewer engineers. We'd probably hire more engineers. Because because our main rate limiter right now is how fast we can ship software to generate more revenue to hire more engineers.

• 52:15Alex Kantrowitz?

  Right.

• 52:15Speaker 02

  So like, this is where we got it all backwards, which is most areas of our businesses. We would actually accelerate growth. We'd accelerate our business if we could make the underlying thing that we do faster and more efficient. And so I'm I'm much more in the optimistic camp. I basically think the pessimistic scenario I'm not seeing. And I'm I'm and I just I don't think it's going to happen within this architecture paradigm 20 years from now. Sure, let's do a podcast and find out where we ended up. But but right now, this is not something that that I feel we have to worry about.

• 52:45Alex Kantrowitz?

  Okay, I'm just gonna ask you two questions to wrap up. These are two I definitely wanted to get to, so I appreciate you taking them. The first is about where Amazon sits in all this. They've been very quiet on the consumer front. They have they're actually building GPOs, which no one talks about. And their their sort of position is that they want to make this something where they can work with their customers to help them build like those custom off the shelf models. So I'm curious, I'm just gonna ask you both of them and then then we can get to them. I'm curious what you think there. Second thing is you had this thread that said, if Sarah Silverman ends AI, that's going to be absolutely wild. She's sued for the use of her content and I hadn't I'm working with an editor. And he said that I should ask you, aren't AI companies just vampires sucking

• 53:27Alex Kantrowitz?

  value out of human creativity, putting people out of work and returning very little in terms of value to humanity? Why should we tolerate that and who will benefit from it? So it goes back to, I think, like the intellectual property thing. Okay, that was a lot. And feel free to answer as succinctly as you can. I want to make sure to be respectful of your time.

• 53:45Speaker 02

  Sure. Well, on the Amazon piece, I would say I probably can't fully

• 53:52Speaker 02

  describe where they want their role to be. I can describe where the role is now, which is that they're clearly going to be one of the at scale, you know, hyperscale or infrastructure providers hosting models from a variety of vendors and providers. And I think that's a great, great spot to be in. They could host Llama. They can host Anthropic. They can help customers fine tune Llama. You know, there will certainly be, you know, a thousand times more AI models that could run on Amazon that are open source than than sort of ones that are commercial and proprietary to one particular vendor. And so, so their strategy is just to say, hey, you know, bring on all of the AI innovation in the world, let a thousand flowers bloom. We'll host all of that. And that's, I think, a very, a very practical, you know, strategic

• 54:37Speaker 02

  move. You know, do they go deeper in their own AI models? Do they help customers train models with additional services? You know, probably. But, but, but I don't know beyond kind of them as an infrastructure player where they want to sit. But even in that, even in that position, I think they're really good at that. And, and I think they'll, they'll, they'll continue to kind of profit and, and build a very large business on just that role alone.

• 55:01Alex Kantrowitz?

  Great point. Sarah Silverman.

• 55:03Speaker 02

  Sarah Silverman. Well, so, so I guess a couple of things. One, you know, most people that are at least on the commercial AI side, I think are at least contemplating or trying to figure out a way for the Sarah Silvermans of the world or the content producers to get paid something. At least that, that's the high level commentary. I don't quite know technically how anybody accomplishes that. But I think that, that they're, you know, I don't think the intent is to be a vampire, as it were. Now, now, I think, I think the other, the other thing is, is, you know, it's, it's unfortunately just a repeat of the, the prior conversation. I just don't think they take the job of the

• 55:43Speaker 02

  screenwriter, or the, the joke writer, or the animator. I think they act as a, a way to, you know, boost or amplify or accelerate the work that, that one of those, those individuals are doing. You know, I was, I was chatting with someone in the AI space, doing kind of video AI. And, and, you know, why, you, you are, you're, you're a director or a cinematographer, and you have to go kind of figure out what's the shot you want to go do for some film. And, you know, you spend X amount of time thinking that through, and, and, you know, maybe, you know, storyboarding it. This, this, you know, the, the, the capability you now have is you could look at the simulations of that, and you can look at a thousand of

• 56:27Speaker 02

  them, or a hundred of them, and then pick out exactly the kind of shot you want to go with. And now your creativity, combined with the automation benefit of, of seeing lots of options and testing different scenarios, we will actually just get better content from that amazing cinematographer or director. Not because of AI, because AI made them more efficient in, in something that would have taken, you know, months or quarters or whatever of time, now is, is, is sort of shrunk into a much shorter period. So, I think we, we sort of imagine AI is going to go replace those, those types of jobs. And it, it won't. It will be another tool in their arsenal, just as, just as, as every new technology kind of breakthrough has become another tool for the Jon Favreau's and the Steven Spielberg's. This just becomes yet another way for them to continue to make better art and better

• 57:12Speaker 02

  content than, than they did previously. So, I'm pretty optimistic on, on all of the, the kind of creative flourishing that we're going to go see from, you know, from all of this. Not to mention just- I think we'll be, we'll see this as a multiplier of content. And anybody who argues that it's, you know, that it wouldn't be good that just have more people be able to produce good content, then, then you're kind of just gatekeeping. And, and you're, you're sort of just trying to constrain who should be able to make a film, who should be able to be creative, uh, which obviously doesn't, I don't, I don't think is, is, is practical or reasonable.

• 57:45Alex Kantrowitz?

  Aaron, every time we talk, it seems there's just this avalanche of interesting AI news. So let's keep it up. I mean, great speaking with you as always. Thank you for being here.

• 57:53Speaker 02

  Good to see you. Appreciate it.

• 57:54Alex Kantrowitz?

  Awesome. Thank you, Aaron. Thanks, everybody for listening. We'll be back on Wednesday with my conversation with Ethan Malik, professor at Wharton, Wharton College, University of Pennsylvania. Thanks again for listening and we'll see you next time on Big Technology Podcast.

• 58:14Speaker 03

  Now more than ever, we need someone on our side, but Rob Whitman? Whitman's votes drove up costs, cut Medicaid and risked 350,000 Virginians healthcare to pay for tax breaks for himself and his donors. He's not on our side. Shannon Taylor will fight corruption, cut taxes and bring down costs. This November, vote for Shannon Taylor. She's for us. Paid for by HMP, the House Majority PAC dot com, not authorized by any candidate or candidate's committee.

• 58:44Speaker 01

  In this life, you can't win.

• 58:46Speaker 04

  When the world gets you down.

• 58:47Speaker 01

  No!

• 58:48Speaker 04

  Escape to Pluto TV.

• 58:49Speaker 01

  This is objectively fantastic.

• 58:51Speaker 04

  Relax into the movies and shows you already know and love, all for free.

• 58:55Speaker 01

  Schwing!

• 58:55Speaker 04

  Even our news is uplifting.

• 58:57Speaker 02

  You stay classy, San Diego.

• 58:59Speaker 04

  Watch School of Rock, Crazy Ex Girlfriend, Anchorman: The Legend of Ron Burgundy, The X-Files, Wayne's World and so much more.

• 59:04Alex Kantrowitz?

  We're not worthy!

• 59:06Speaker 04

  The best things on TV really are free.

• 59:08Speaker 01

  You just have to know where to look.

• 59:10Speaker 04

  Escape to Pluto TV. Stream now, pay never.