Predicting AI’s Next Advances — With Suhail Doshi

Suhail Doshi is the CEO and founder of Playground, an AI image generation and editing software company. Doshi joins Big Technology Podcast to discuss where the next generative AI breakthroughs might come from. Tune in to hear Doshi's insights on the innovation within language models, image generation, video, and 3D creation. We also cover the business opportunities the competitive landscape among tech giants like Google, Meta, and Microsoft, and the debate around AI's true capabilities in understanding physics and reasoning. Tune in for a nuanced exploration of the cutting edge of AI from one of the leaders driving it forward. ---- 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?

  A leading AI CEO and entrepreneur joins us to talk about the state of the field, the research, products, competition, and where this is all heading. All that and more 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, including the business decisions, trade offs, and lessons along the way.

• 0:43Alex 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/alex for a free consultation. That's akash.network/alex for a free consultation.

• 1:15Speaker 01

  LinkedIn Presents.

• 1:20Alex Kantrowitz?

  Welcome to Big Technology Podcast, a show for cool-headed, nuanced conversation of the tech world and beyond. Today, we have a great guest for you, someone I've been trying to bring on for months, and I'm very excited to have him here. Suhail Doshi is here. He's the CEO and founder of Playground, which is an AI image generation and editing software company, somebody that I've been following on Twitter pretty religiously to get a sense as to like where this is all heading. So I'm thrilled he's here. Suhail, welcome to the show. Yeah, thanks for having me, Alex. Thanks for being here. I always

• 1:52Alex Kantrowitz?

  End up learning about like the latest breakthroughs through your Twitter account. You're like definitely on it. You're talking with the right people. You have a sense as to where this is going. So just to start this conversation on that theme, where are we right now in terms of the curve? You know, the curve of the innovation curve. Are we the early part? Are we kind of troughing here? And I'm also curious to hear just kind of a two parter. Where do you think the business cases for this stuff are going to land? Because I think that's still a kind of an open question. I mean, you run an image generation company and editing company. So that's something I'm sure you think about because you have to figure out who you're going to sell to. So yeah, let's just start real broad to begin with.

• 2:33Speaker 02

  Yeah. In terms of where we are, gosh, I am always surprised how, you know, I used to have this tweet last year that there were AI breakthroughs every single week. And eventually I got to the point where I think like Elon Musk tweeted every single day.

• 2:53Speaker 02

  And the interesting thing is that that's, it still feels like that's happening, right? I try to follow just the right people, researchers. I troll through this place where there are all the research papers get uploaded called archive. And I just read through things that are interesting that are kind of taking off. Sometimes these things are good demos and they're nothing more than a good demo. But sometimes they are truly breakthroughs. So right now the pace continues to seem relentless. You know, I'm often surprised by what new thing happens. And, and what's interesting is sometimes a breakthrough will happen in a week. And it's only like a couple of days later that something beats that, beats that thing in terms of performance or capability or some sort of surprise.

• 3:38Speaker 02

  But if I were to take a snapshot about roughly where we are right now, it has been over a year since GPT-4 has basically been out. I, I view it as a little bit over a year because I was a lucky person and I had access around October to GPT-4. And I think it kind of came around, it came out around February.

• 3:59Speaker 02

  And so it's interesting, I think it's interesting to point at that milestone because we don't know what has been internally happening at a company like OpenAI over the last year. And they're definitely training a new model. So the question, and so I had this, this thought today that was kind of like, We don't really know how far behind everybody else is in language. Because we have no idea what OpenAI or Anthropic or some other company is training internally. We have markers for things like Gemini from Google, or we have markers from Mistral. But we really don't know how far behind they are. We only know where they are.

• 4:42Speaker 02

  They are matching compared to last year or the year before that in October. That's in language and in images. Images is interesting because it's probably a couple of years behind a GPT four true moment. Right. And now audio is starting to happen with a company called Suno. That I actually tried out this weekend. I'm a producer, so I was making songs. So I was trying that out. So I have some weird thoughts about that. And then I think the last area is the companies that are doing 3D are just starting to get started. There's a friend of mine who's a who's starting like a 3D foundation model to do like Pixar or level type of creation.

• 5:20Alex Kantrowitz?

  Wow.

• 5:21Speaker 02

  I don't know if I can name them yet, so I'll probably avoid doing that.

• 5:23Alex Kantrowitz?

  Yeah, but even the fact that that's happening is.

• 5:25Speaker 02

  But it's getting it's.

• 5:26Alex Kantrowitz?

  And there's video.

• 5:27Speaker 02

  Video. Yeah, there's video. Yeah, now we're getting like minute long sequences that are not kind of artifacty. They're they're sort of more coherent with the right character consistency. We are at the very beginning, I think.

• 5:38Alex Kantrowitz?

  So where do I mean, what is the North Star for this stuff? I'm trying to think about a chatbot like or a GPT model, right? So it's already pretty good, like it does a great job of synthesizing information and spitting stuff back. Like where does where does it end? Where are you worth like, because you mentioned, okay, they're working on a new model. Well, how's that new model going to be an improvement from what we have? And then where do we end up getting to if this keeps on getting better and better?

• 6:06Speaker 02

  I mean, Sam's Sam Alvin's response would be like AGI, right?

• 6:09Alex Kantrowitz?

  Yes, what's yours?

• 6:10Speaker 02

  I think there's another. There's like another version of of of his belief, which is like. One, I think one time when we were talking with Sam, just kind of at a dinner party, his. I think he he said this thing that he believed that everybody would just like have a thousand employees. And I think we all thought he was crazy, still do, by the way. And he may be may prove to be right. But I think chatbots are just like a very like sort of. Very basic, primitive thing that we'll end up getting. You know, my general feeling is that one of the, I was talking to someone at OpenAI who was working on the robotics team there back in the day. And I was starting to get into AI robotics a little bit. I was kind of curious where things were.

• 6:53Speaker 02

  And the general, you know, to summarize, kind of like where the field seems to be. I'm not an expert, but I've talked enough to enough people that are that, you know, broadly robotics kind of asymptotically and hit a ceiling about like three or four years ago. And the research still isn't like kind of on a trajectory that's amazing. But the reason why I'm bringing robotics is because I want to answer your question about where I think things are headed is that there was a belief, for a little while, someone at OpenAI at least had this belief, can't say that it was everybody there, that the ceiling due to robotics was in part because, because maybe the solution to solving it was actually through large language models first.

• 7:33Speaker 02

  Maybe if we could find a model that could reason to the extent of language, that maybe that could help the robots sort of navigate through some of the toughest problems that they're they're having trouble with. And so it's kind of like the sequence is sort of like first make language great. And now we're starting to see, and then the second thing we start to see is image models and graphics becoming great. And now we're, and then the next piece is now we're starting to get a sense of multimodal vision plus language plus maybe audio. Can we make a multi, a very powerful multimodal model? And if we could do that, maybe those will surface and cause many breakthroughs, one of which could be in robotics, one of which means that you'd have a robot, not a Roomba,

• 8:15Speaker 02

  like a robot that, you know, maybe embodies us like, you know, there are a lot of humanoid startups right now. And by the way, the reason why the humanoid startups are humanoids and not different looking robots is because we know that humans are already able to generalize to lots of human related things, right? We know that if we're human, look, we look like a human, then we can hit a printer button and take a box and, you know, all these different activities. So I think that. If the models get more powerful, we're probably going to see, probably going to see some kind of Westworld version of the world. We're going to go way beyond a chatbot.

• 8:50Alex Kantrowitz?

  And what about reasoning? Because OpenAI had this Q-Star thing that people were talking about. There's another company that says they've been able to reason. Is the adding reasoning into large language models, is that like another next new bound? Or is that just a way to get us to this reality that you're talking about?

• 9:08Speaker 02

  And reasoning in AI is kind of like this very really big philosophical word, I think amongst researchers. You work with a research team, you know, you talk to researchers. Reasoning is really tough for anyone to really prove whether that's actually happening or not.

• 9:24Alex Kantrowitz?

  Right. Because the big question is, is it just like spitting back the next word? Or is it really able to like work through problems on its own, which?

• 9:31Speaker 02

  I mean, how do we know your reasoning or I'm reasoning right now? How do we know we're not doing that? How do we know we're not just reacting to our surroundings and predicting the next token? We don't really know.

• 9:42Alex Kantrowitz?

  Interesting. But then why do you think that there are AI companies that are working on this problem? I mean, this is, it's not an abstract thing. Like there's actual research programs and progress that are being made on this question itself. You know, I think the Q-Star example, from what I've read, is that it basically can solve complex math problems on its own. So that requires being able to conceptualize and reason through a problem as opposed to like, take, you know, it could do novel, novel problems. So as opposed to like, take what you've seen before and spit out something that looks like an answer to a math problem.

• 10:21Speaker 02

  Yeah. I mean, just to dive into the philosophy of reasoning, just for like, just the tip of the iceberg, I think that, you know, just some, just because something is able to articulate its reason for doing, for getting to an answer, doesn't mean that it is necessarily reasoning.

• 10:36Alex Kantrowitz?

  Interesting.

• 10:37Speaker 02

  The one way that you could prove reasoning is maybe, you know, like one, one, because, because it's possible that its training data, you know, it's just really tightly fit to its training data and it kind of knows, it just happens that the next token ends up being step one, and then step two and step three. We don't really know. But I think one way that you could maybe litmus test reasoning is if you gave the model something truly out of distribution. Right? Like an example of something that's truly out of distribution that humans faced was COVID, a pandemic, a pandemic that it had not yet seen before. And then we had to reason about how we would go and deal with that kind of odd current event. The question

• 11:19Speaker 02

  would be like, could you, if you gave a model something that it was truly not trained on, you could prove that it was not trained on. And you gave it, and you asked it for a solution, could it really figure out the right solution? That might be really hard. We might find that really difficult. And humans don't necessarily do either, right?

• 11:37Alex Kantrowitz?

  Well, it's interesting because when people talk about like artificial general intelligence, it's like, well, who's your baseline? Because

• 11:43Speaker 02

  Right.

• 11:44Alex Kantrowitz?

  I don't know. We'll see. I mean, AI can definitely exceed humans in some areas and others it can't. So anyway, it'll be something that we'll all be talking about for a while.

• 11:55Alex Kantrowitz?

  Obviously, like image generation is something that requires some understanding of the world. You're doing it at a playground, right? That image will understand, like, let's say you say, you know, show me a monkey sitting on a beach ball will understand that there's some physics in the world and the monkey has to sit on top of a beach ball. So I'd love to hear your perspective on the state of image generation right now. You have an update that you're releasing or you have released by the time this this goes live. Obviously, it's an exciting time, but you're also coming up against some very big companies that are trying to do this as well. Midjourney has been been at it for a while. Dolly 3 is pretty impressive. I use it through Copilot from Microsoft. Google, of course, has tried

• 12:38Alex Kantrowitz?

  it, but they've had some some problems there. So talk a little bit about it. And also, I'd love to hear like the business case here because, you know, for LLMs, that's one thing, like you can say, all right, we'll read contracts, understand them, help us with back. But for images, you know, is it that it will replace design, that it will democratize design and make it available to everyone else? Like, I'm curious to hear your perspective on why that's a problem to work on.

• 13:02Speaker 02

  Right. Yeah. Yeah. You know, images are definitely behind in terms of overall capability and utility relative to language. You know, like, I think at the end of the day, all of these models, for the time being, Have their kind of narrow somewhat utility, right? You know, there are a lot of things posted on Twitter about how people are using language models, but the predominant use case continues to be homework. And then there's kind of this other one that's like coding. For images, it just turns out that the predominant use case is making art. And it just turns out, and it's very surprising, but it just turns out that millions of people are very excited to make art.

• 13:46Speaker 02

  And art, art can be, it's not art that you're going to necessarily always put on your wall, but it's art that could be used in marketing, like maybe you post it on your Instagram, or maybe you make an icon and you use it as an icon for your app, or maybe it's a YouTube thumbnail, or it's an image that you put in a blog post. Maybe it's just a fun meme that you send a friend. That's somewhat the state of images right now. It's really interesting imaginative art.

• 14:13Speaker 02

  But I think that it hasn't quite gotten to the utility of language. And I think there are a number of things that are probably coming for graphics. But I do think it's going to be about democratizing graphics for people. I mean, our, our company is trying to help people make graphics like a pro without being one. You shouldn't have to, you ever open up Photoshop? I mean, it's, there's a dizzying amount of menus, right? There's all these icons. You have to go to YouTube and do a really sophisticated tutorial to be good at Illustrator or Photoshop or Lightroom.

• 14:42Alex Kantrowitz?

  I had to take classes on both of those, Photoshop and Illustrator, semester long classes to be able to do that stuff.

• 14:49Speaker 02

  Right, yeah. There was a summer where I grinded just making logos and then I would upload them to SitePoint and try to win logo contests to get better at my own skills back in high school when I was a lot younger. And it doesn't have to be that way anymore, right? So I think the first thing that's going to happen is that a lot of graphics are going to be, be able to be capable on the model. Maybe, you know, if you have wedding pictures and you wish you could like color grade them somehow, maybe you'd use Lightroom or something for that. I think an image model would be very good at that.

• 15:18Alex Kantrowitz?

  I know you're about to move on, but graphic designers, do they become like a extinct profession or where do they go? Because you can not only create images within Playground, you can edit them.

• 15:29Speaker 02

  No, I mean, look, Walt Disney started as a, you know, person that drew pictures. And then he worked somewhere where he animated them. And then that just like evolved and eventually we got to 2D cartoon movies like Snow White and things like that. Right. And, uh, and then, and then, and then things like Pixar came up, came about. And we built like a 3D rendering engine. So did all the people that, um, you know, were that were people that drew the 2D cartoons, they, they, they lose their jobs. And, you know, that was the end of the, end of an era. Definitely not. People retooled. The stories that came from them were still really material to their creative process. Story matters more for a company like Disney, Pixar than the animation itself.

• 16:14Speaker 02

  So I think in this case, you know, the graphics matter, but I think that people will retool.

• 16:20Alex Kantrowitz?

  Right.

• 16:20Speaker 02

  The question is, are we giving people enough time to retool?

• 16:22Alex Kantrowitz?

  Yeah. So like if you're doing one sheets, like I used to work in marketing before I went into reporting and we used to do one sheets. And if you're doing one sheets, right, like get the headline image, you know, and passed off as a piece of marketing collateral. Like that's, that seems like you might want to try to invest in some new skills.

• 16:41Speaker 02

  Yeah. I also think that there's something, there's something beautiful about the person that is creating the thing. Like let's say you're doing a piece of writing or maybe you're a music artist and you made a song. I think there's something really beautiful about that person being able to connect their art, their graphics as closely intertwined with the other kind of art that they're making. Like if I'm a music artist, I want to be able to choose the exact album art. I don't want to have to always outsource that to somebody who may not really understand what I want.

• 17:10Alex Kantrowitz?

  Yeah, it totally resonates because like I've been using image generation for big technology. And like we, I, we're, I'm a one person shop. Like I couldn't afford to do graphic design for every single story. I mean, I was hardly making it work with like the whatever iStock photo. And every now and again, I would, um, you know, pay for the image. But like now it's like these, we get perfect, almost perfect illustrations every time for every story. Because this technology has made that possible.

• 17:37Speaker 02

  Right, you're able to marry the creative process of your podcast with the graphics and the thing you want to show people and only you, you can go through as many iterations as you want to find the perfect thing that you think is like the right mapping. So I think, though I think, like, and I have actually talked to people, like artists or people that draw, who hate this stuff. Last year, I think like a year or two ago, I basically got almost cancelled like on Reddit and Twitter and everywhere. Back when AI art was, you know, people hated the idea that you would even say AI art is art. And, and so one of the things I decided to do is be really curious. And I said, let me go talk to some of these people that, you know, basically they're sending me death threats on Twitter or something

• 18:18Speaker 02

  like that. And, you know, some of these people love drawing. It doesn't matter that you offer them a better tool. They love the idea of picking up a pencil and drawing. And so for those people, certainly, you know, that's one way of making art and some people will treasure that and enjoy that. But that's, that, that would be taking something that they enjoy. It, well, they still can do it. They can still enjoy it. It just might not mean that it kind of doesn't evolve perhaps with the time. So there will be some people, I think it does matter to think a little bit about how fast the technology is moving and how people will deal with that.

• 18:54Alex Kantrowitz?

  Right. Definitely. Okay. Sorry. I didn't mean to break your momentum.

• 18:57Speaker 02

  No, no worries. Yeah. So I, I think that, I think that those things will be possible. I think the utility of graphics are going to increase though significantly in the next year. I think that we haven't really thought through editing, for example, right? You know, a lot of this stuff is generating synthetic images, but we haven't really thought about like, what if I have an image and I want to add my dog who's not in the image for my holiday card? Could I take a dog, could I take my dog from a different image and then just like insert it? Where it gets all the lighting and the shadows and the color and all, and all the ambiance, correct? What if I want to do fantastical things? Like, what if I want to see what you would look like if you were the Incredible Hulk? Big, green, but it really had your face and you thought that face was your face.

• 19:39Alex Kantrowitz?

  Doesn't take much imagination to tell you the truth.

• 19:43Speaker 02

  Yeah, I think I think that, you know, what if I want to make a logo? Logo is really hard. I mean, I remember having to pay, I have paid people $50,000 to just generate, you know, not to make, hand make a bunch of logos that I want to use to brand my product. Sometimes you can only get five of them, though. Why can't I get 100 of them? You know, I think with graphics, it's, graphics is on this never ending cycle where we never feel like it's good enough. If you can, you can think a little bit about like, PlayStation one, and then PlayStation two, and then three, four, five, right? Grand Theft Auto, the first Grand Theft Auto to now maybe what five looks like. We can see that graphics is still improving 30 years later.

• 20:26Speaker 02

  So I think by giving people tools with where they can do incredible feats of graphics is going to be really exciting. But I think graphics is only a subfield of a bigger, of a bigger plan that at least our company has. I don't know if there are other companies that care to do this. But our company cares about creating a unified vision model. Where we can create and edit and understand anything with pixels, a single unified model. This is missing in vision, but definitely kind of exists in language. In language, we can solve hundreds or thousands of different tasks. But in graphics, but in vision, it's all separated. It's kind of like where language was back three or four years ago. Where you, you know, there'd be a model that could summarize and a model that could do sentiment analysis

• 21:11Speaker 02

  and a model that could, you know, do a little, like these different little act tasks. But there wasn't a unified, single, large language model. But there's no equivalent for vision. What is a large vision model? We don't really have a term for that. So my feeling is that vision as a field is going to significantly expand. Why, why can't a robot look at images and navigate the world like a self-driving car, right? That's one thing. Why can't we understand images or what's going on better? You know, we've seen early glimpses of that. You know, I think there's like a famous picture of Barack Obama stepping on a scale and the model goes, knows that Barack Obama is like trying to increase the scales like a joke.

• 21:51Speaker 02

  But can models like really understand what's going on in these images to a much deeper level? So there's large, there's large vision models that are starting to incorporate language and images. But vision, there's no real all encompassing multitask vision model.

• 22:07Alex Kantrowitz?

  So I have a couple of questions for you on this. First of all. Well, on the vision part, does that, does that sort of play into like, a lot of people have been talking about how, you know, one of the biggest applications of this current generation of AI is going to be an augmented reality. Right? And like the meta has those glasses where like you're not, you don't have an overlay right now. But you can talk to things to their AI bot and it will look at the world and then give you a sense as to like what you're looking at. Or you could even just ask questions about things and it will talk to you. So I'm curious like how, how, um, how seriously you take this, this new era of augmented reality that we seem to be heading in because

• 22:50Alex Kantrowitz?

  speaking of one of your tweets, you wrote, "It's going to be hard to beat a computer in your pocket. You can use inconspicuously when you need to." So it sounds like you're a believer that the phone is going to be the, the way that we're going to interact with computing for a while, but maybe there's something I'm missing.

• 23:07Speaker 02

  Yeah, I mean, I think the, the phone is a really good form factor of computing.

• 23:13Speaker 02

  You know, I've talked to lots of different friends who've tried the Vision Pro and such. You know, it seems like that's still kind of early in terms of its use cases and in its utility. So we'll see what happens over the next year or two. I tend to be like more optimistic no matter what, because you never know about these things. I think, I think one thing that Meta is doing, regardless of where VR is headed or AR is headed, is they have one of the most world-class teams for graphics and they have to because of all the stuff that they're doing in VR.

• 23:46Speaker 02

  But yeah, you know, I think it's kind of unclear what the right form factor is. Is it, is it on your face? Is it somewhere else? Is it a, you know, the thinner, you know, video screen? I'm not sure. But one thing I do feel pretty confident in is that we will care a lot about being able to use AI to manipulate graphics, regardless of the form factor. Like I'm somewhat form factor agnostic. Is it a TV? Is it a watch? Is it a, is it glasses? Is it some new thing? I don't know. Um, but it seems very likely that we're going to care, you know, like an example would be, I wish I could just go into a store, stand in front of a mirror and then just sort of swipe for like a jacket that I'm wearing. You know, I went to, I went this weekend to the, uh, the, the DeYoung.

• 24:32Speaker 02

  And it had this like sort of fashion, San Francisco fashion exhibit. And there was this, you know, powered by Snapchat thing where it would like to put on a dress. And so I was in a dress at the exhibit. But it was really cool and it's very, it's very obvious that this thing could be higher fidelity.

• 24:51Alex Kantrowitz?

  Right.

• 24:51Speaker 02

  And that was like a really cool AR experience, but why can't I have that for jeans and a jacket or anything that I want to wear without having to try it on? So I think those kinds of experiences seem inevitable regardless of the form factor.

• 25:05Alex Kantrowitz?

  Yeah. And then talking about the limitations of image generation models today. You know, it just seems like they all end up generating images that look so similar. And you know, when I said before that like I generate the perfect image for each story? Conceptually, yeah, but you can still tell that it's been generated by an AI image model and not a graphic designer. So I'm curious like why so much of these AI generated images from your perspective? Look so similar? Is it because they're using the same underlying technology, using the same training set? Is it just that they're not quality enough that people can pick them out? What do you think?

• 25:44Speaker 02

  Yeah, I mean, language models have this problem too.

• 25:46Alex Kantrowitz?

  Right.

• 25:47Speaker 02

  Like, like the way that we know this is that language models are kind of overly verbose, right?

• 25:52Alex Kantrowitz?

  They talk a lot.

• 25:54Speaker 02

  They talk a lot, right? So that's kind of the, the little tell for language models. For images, you know, the tells are a little bit different. Uh, maybe they have overly crazy bouquets or they are super lush in ways that you don't need them to be lush. Right? But I, I think with images, you know, what's happening is, is that maybe the models are a little bit too curated. It's at its infancy, but I think that the models are probably too curated and maybe overfit to be based on human preference. And human preference isn't your human preference. It's your preference. I mean, it's some kind of average of human preference.

• 26:34Speaker 02

  And so, you know, in art, there's art that we like in the modern time. And then there's kind of avant garde art.

• 26:43Speaker 02

  And maybe you prefer that, right? You want something more ostentatious. Maybe you want something more minimal and laid back. And I think what we're, what we've kind of discovered is that actually like there are just huge wide varieties of preference. And then there's the average. And so I think with image models is somewhat twofold. It's it's that we're not catering to people's personalized preferences and styles. I think that's one problem or the niches, right? And I think the other is that quality is the lowest it's ever going to be, starting today.

• 27:16Alex Kantrowitz?

  Right? Right.

• 27:16Speaker 02

  So the quality is going to get incredibly good.

• 27:19Alex Kantrowitz?

  But it's also, it's interesting because so one of I having worked at publications where we did have graphic artists. Right? Like, one of the interesting things was was you would give a prompt or that you'd write a story. And that artist would then sort of take it back and based in their own style, end up creating an image. And I love doing this because I was seeing what they came up with because I was always surprised by what they'd built. Because they would do it through their own lens and focus. But what AI does, I think, is it tends to sort of take everything into account and spit back the average. Right? Like, kind of like the average type of words or average image.

• 28:01Alex Kantrowitz?

  And that's where I sort of say, you know, sometimes I'll be surprised by what an AI image generation engine will will will create. But oftentimes it's like, yeah, that sounds right, or that's close enough. Let's put it in the top of the story.

• 28:14Speaker 02

  Right? Yeah, I mean, it's interesting. Humans, human graphics designers are also kind of overfit, right? They have their own particular style. Like anytime I've reached out to a graphics designer, sometimes they'll say, hey, why did you reach out to me? Like, what did you like that I did? Or an interior designer or whoever, right? So they all have their style. They're the kind of like less these human graphics designers are somewhat like less robust designers in some sense. Like they are very skewed to something and then you pick them. And that's cool because then it can lead to brandable things. The models, if you prompt them simply, then they will, they will be an average style, an average style that represents something. You will probably get at this point, you will get something that is beautiful. But it may not be, it might not be like stretched.

• 28:58Speaker 02

  It might not be headed in a stylistic direction because everybody uses it. Then it feels kind of fatigued. It's like a, you know what I call it? Internally, I call this pop. It's like pop art. Yeah, just pop music, top 40 music. And then you like like

• 29:12Alex Kantrowitz?

  Great way to think about it.

• 29:13Speaker 02

  Like growls and noises and sounds, right? But then there's pop music. There's like Justin Bieber, that kind of thing. What you're getting from the image models is pop. And people love pop. We know that. Love top 40. But it's hard to market pop all the time because it gets tiring. So yeah, in this case, you know, it is definitely the models are capable. It's just you have to have like this perfect alchemy of figuring out the right prompts, prompting engineering.

• 29:40Alex Kantrowitz?

  But then that's where it gets interesting then, because then let's say, okay, you know, I like, like art in the style of a specific graphic, contemporary graphic designer. And let's say the model's trained on that art. And I say, all right, you know, create an image of like a robot playing tennis in the style of, you know, person Y.

• 30:03Speaker 02

  Sure.

• 30:03Alex Kantrowitz?

  But then you get into some really tricky questions because we have to figure out a way to either compensate these people because it's like, it really becomes like some sort of intellectual property theft. So I'm curious, like you're running a company that does image generation. So how do you think about this?

• 30:23Speaker 02

  Oh, yeah. Super, super interesting issue and really complex. You know, these days, we don't really, we're not really seeing customers, you know, wholesale be like, I wanted this person's, this one person's name, you know, which is good. I think it's a good thing. You know, Greg Rukowski is someone that I think about in this case, because a lot of people add that person's name. He makes really amazing fantasy art that on DVNR and maybe he's helped out some video game studios and stuff. I'm not sure. But,

• 30:57Speaker 02

  but his name is kind of quintessential in this debate. And, you know, what the reason why people, it's important to understand the reason why people are doing it. People aren't doing it because they're trying to copy Greg Rukowski. They're doing it as a shortcut to get somewhere. Because if you take an image from Greg Rukowski, it's not easy to articulate. In fact, there's a reason why there's a phrase called, you know, picture speaks a thousand words. It's very hard to describe his art completely. We can come up with some words, but it's a vibe, it's a style. And so people are using it as a shortcut. And there's other people like H R Geiger, who does like kind of more eerie, you know, worst type stuff. There I've learned about a lot of artists because of how

• 31:40Alex Kantrowitz?

  I can imagine, yeah.

• 31:42Speaker 02

  There's a lot and and there's no, no easy way around this. But I think that this thing is going to go away in the next year, this year. I mean, we're working on something. I can't talk about it exactly right now. But I think this idea is, is that users are doing this because it's a shortcut to get to a very difficult to describe style. And what they really want is to say, I like this, like, I want to reference this, I want to reference, actually, I want to reference five of these different things. And get to this, get to an image, because actually with graphics and a lot of, a lot of images and art, what's happening is like, it's like remixing a lot of things, like even I, because I make music, I can kind of relate to it because it's sort of like,

• 32:24Speaker 02

  you know, if your inspiration is Kanye West, and then your other inspiration is, you know, Dr. Dre, and then your other inspiration is, you know, Six, who produces music for Logic, and you want to combine like the drum rhythms of this person and the instrumentals of this person and the lyrics of this person, did you copy them? I mean, all of these people were inspired by people. And so I think in this case, people are just feeling inspired, but they're using a shortcut. So the question is, how do we get them away from just copying actual record? Because that's definitely the wrong thing. We definitely don't want that in the world. Nobody should be copying Kanye, you know, wholesale. That's bad, too.

• 33:01Alex Kantrowitz?

  Right. But you just kind of, it's difficult to eliminate the prompts completely. Like, let's say you did have audio generation, you know, and you could say, write me a song about, you know, I don't know, my girlfriend in the, you know, style of Kanye West.

• 33:14Speaker 02

  Yeah.

• 33:15Alex Kantrowitz?

  I don't know why you'd want to do that, but you could. And, you know, you sort of get into those issues.

• 33:21Speaker 02

  You do. Yeah, you definitely do. But I don't think, I don't think that's people's true intent.

• 33:25Alex Kantrowitz?

  Let me ask you this. Do you think that the artists that are, whose work is being trained on should be compensated?

• 33:31Speaker 02

  I think we need to find some solution for them. Yeah, you know, we do. We do a small, you know, it's not clear like, you know, every time you generate an image, they get like, you know, some Spotify streaming payment, you know, one hundred, one thousand to a penny. I don't think anyone's going to be happy in that circumstance.

• 33:45Alex Kantrowitz?

  Right.

• 33:46Speaker 02

  But, you know, we try to do something small, small. We don't, we don't think this is the solution. We don't think this is enough of a remedy per se, by any means, is a stretch of imagination. But one thing we do that nobody seems to else to do is we actually look back to a lot of these artists.

• 34:02Alex Kantrowitz?

  Yeah.

• 34:02Speaker 02

  When an image gets generated, we say additional credit, Greg Rukowski, and it links directly back to his DV and art page so that people can find him, learn about him, pay him, donate to him, whatever they want, right? We even, we even link back to like Wikipedia artists that, you know, no longer are artists that are on Wikipedia that are not living, just so people understand what they're doing.

• 34:24Alex Kantrowitz?

  Right.

• 34:25Speaker 02

  Yeah.

• 34:26Alex Kantrowitz?

  I think that's a good start. Okay, so let me, let me ask you this. You're like, you're, you're doing, you're doing an image generation startup. You're very focused, like you'll tweet often about how it's so, it's so important to stay focused. And I do think there's something to be said for that because there's so many other companies that are just kind of going all over the place. Do you regret not doing video, though? Because what we've seen out of OpenAI, Sora and others is just kind of, you know, jaw dropping. It's pretty amazing. So is that something that now you think you should have done?

• 35:01Speaker 02

  I mean, it's too soon to tell. You have to ask me in a year to find out if I regret it, right? Right now, you know, I don't have any regret. I, it's, it's funny. Where we are with video is kind of where we were with images. And I don't know if people remember, but about two years ago, Dolly came out, Dolly two came out in April, and the world was amazed, totally amazed. But if anyone goes, looks at a Dolly two image today.

• 35:31Alex Kantrowitz?

  Those images are awful.

• 35:33Speaker 02

  Horrendous images, you would laugh.

• 35:35Alex Kantrowitz?

  Right.

• 35:36Speaker 02

  Right? So when we see something like Sora come out, you know, I have this belief, I've been having this personal reaction or a moment with all of this stuff, which is that my baseline for quality instantly resets. Like 15 minutes after the technology comes out, I'm just kind of like, anything worse than this is unacceptable. And my feeling is that we're only at the very beginning of video. And the truth is, if you could probably go talk to real video people, they'll be like, this is not good enough. This is definitely, I can't use this. People are going to have a lot of fun doing it. But the utility is probably not there yet. It's probably, we're really just at the beginning, I think, for video. So I think, my feeling is, my bet to people, you know, sort of listening is

• 36:21Speaker 02

  that in a year, we will think, you know, we'll think something like Sora was not even close.

• 36:29Alex Kantrowitz?

  Right. Yeah, it is amazing. I mean, that transition, you talked about from Dolly 2 to Dolly 3. I mean, even going from Dolly 2 to Mid Journey, I was just like, I'll never type the word Dolly in a Google search ever again. I don't want to get anywhere close to it. And it is, it's amazing. I think you've pointed this out, how fast that we're moving, that these jaw dropping breakthroughs become obsolete, or like, kind of looked at as unimpressive a few months later. That's the speed that this stuff is moving at.

• 36:57Speaker 02

  Totally. And I think with, so that's videos. I don't have any worries about video because I think video is still early. Like, there's still maybe a moment where we can do videos. There's nothing, there's nothing.

• 37:06Alex Kantrowitz?

  Right. Seems like you'd be able to somewhat easily take into what you've learned with images and go to, go to video. Easy might be or underrating it, but.

• 37:15Speaker 02

  Yeah, I think, I think, you know, without saying too much, I feel like probably where we're headed with images is not going to be like, it's not going to be like a completely, we throw every, we had to restart and throw everything away to go do video, you know, to put it simply. I mean, we were trying, we were trying to work to a unified vision model that incorporate 3D, Nvidia, and everything related to pixels into a single model that's capable of everything. But I think for now, we're just, we're trying to start with something that's narrow and sharp that we think is deeply under invested in.

• 37:44Alex Kantrowitz?

  Right.

• 37:44Speaker 02

  I still think that images have a ways to go. Yeah.

• 37:49Alex Kantrowitz?

  Let me ask you something about video before we go to break there. Cause there's a debate that I've been trying to wrap my head around, which is kind of this debate between Yann LeCun, who built this thing called Vjeppa, right? Which will black out a portion of a video. And then the model with its understanding of the world will basically fill in what it should have been. So, you know, you have a guitar and someone seems to be playing it, blackout the hand and the model will create the hand and the strings, showing that it has a understanding of the real world. They say that that's not generative, that that's actual real world understanding. And then on the other side, you have OpenAI that's created Sora. And it's, uh, it's this pretty amazing thing where like clearly this model understands

• 38:34Alex Kantrowitz?

  the physics of what's happening because the pirate ships are, you know, sloshing around in a cup of coffee ocean. And it's like, oh, they understand that the ships belong in the ocean and this is the way the ocean moves. And this is the way the ships should interact with the water. It's so impressive and it seems like it also understands the world. But you ask the meta folks and they would say that actually, uh, that process of generating these videos is actually limited and doesn't achieve what the AI research community is trying to achieve. What do you think?

• 39:11Speaker 02

  Yeah, I think that, you know, I haven't studied, um, Yann's Vjeppa thing too deeply. But I get the gist of it.

• 39:22Speaker 02

  I mean, I would posit this to you. Are you sure it understands physics?

• 39:26Alex Kantrowitz?

  No.

• 39:27Speaker 02

  Right.

• 39:27Alex Kantrowitz?

  Because, actually, because let me stand on the side of, of that it does. And then you can sort of take, take this argument down. I mean, come on, like boats in the water, the water's coffee, you know?

• 39:38Speaker 02

  Right.

• 39:38Alex Kantrowitz?

  All right. That's my argument. What do you have to say?

• 39:41Speaker 02

  Well, I mean, there is, that, that is, it's not too difficult to refute in part because like, just, just imagine that there's, um, video and the video represents, uh, the physics of a different world, like Mars, right? And even though there are natural physics to Mars, they don't necessarily represent the physics of Earth. They represent some physics. It just happens to not be Earth. And so I would say you could just pull that thread a little bit longer and just say, actually, what it's really doing is it's representing the physics it understands in the videos it's being trained on, which could be.

• 40:17Speaker 02

  Incorrect physics. It's really what it understands what it's being trained on is kind of my main thrust of my point in that to a human, to us, it looks like physics. It's imitating physics and it's not, but it's not necessarily imitating correct physics.

• 40:32Alex Kantrowitz?

  Right.

• 40:33Speaker 02

  So it's really mimicking an understanding of its training data and likely, and if there's any training data that's like cool CG or like, you know, the matrix or Neo's like, you know, on his back, that's not real physics of our world. But it models its training data and I think that that's totally fine though. For a tool that's meant for creativity, that's acceptable. But can we really say that it has learned physics? I can't say that I don't think we can, not yet. You know, maybe lighting, but even the videos that have lighting could have incorrect lighting.

• 41:06Alex Kantrowitz?

  Right.

• 41:07Speaker 02

  Yeah.

• 41:07Alex Kantrowitz?

  It is interesting. Yeah, I think that, that the folks that I speak with in the AI community are really divided on this. Like we had Brian Kandazera from Nvidia a little bit back. He runs applied machine learning there and he's like implying some metaphysical capabilities in these large language models where, whereas like others would say that it's just predicting the next word. And this could be the same thing where like, we still, we're still so early on and still trying to figure out like what's happening in these advances that it's still an open question. Or maybe I'm just giving the people who disagree with you too much credit.

• 41:40Speaker 02

  I just, but I, I take like a very different argument than these like two different factions.

• 41:45Alex Kantrowitz?

  Yeah, okay.

• 41:46Speaker 02

  I posit, I take the argument that it doesn't, I just like, I don't think it matters.

• 41:51Alex Kantrowitz?

  Right.

• 41:51Speaker 02

  Like at the end of the day, we are making, we are making, these models could do it or could not, but either way, what matters is what utility it brings to humanity. And if what it brings is this amazing, you know, creative tool to create super slow motion action shots for the next matrix movie, that's fine. And if it can truly model physics in the real world, because we want to simulate what might happen with self-driving cars at a faster speed than actually having the cars be out in the world, so be it. To me, it doesn't matter. It's kind of irrelevant. What may, what matters more is its value to us as humans. And I think we're a little like too deep on a philosophical level about whether it's this or that.

• 42:34Alex Kantrowitz?

  The reason why I ask the philosophy questions is that they matter from my perspective in terms of like what you can do next. Like if it does understand physics, then you can imagine or anticipate that it will be able to do more than if it doesn't. But it's definitely interesting.

• 42:48Speaker 02

  I guess I'm trying to say that it can do both.

• 42:50Alex Kantrowitz?

  Right, no, no.

• 42:50Speaker 02

  So anything is really like the options are kind of wide open.

• 42:54Alex Kantrowitz?

  Definitely. Okay, let's take a break. I want to, when we come back, I want to do a quick lightning round through the tech giants and also talk a little bit about, well, one of the tech giants, the state of Google. So why don't we do that when we come back right after this? This episode is brought to you by App Point. 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 App Point does. For 25 years, they've been the trusted layer beneath the world's most demanding data, now extended

• 43:34Alex Kantrowitz?

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• 44:17Alex Kantrowitz?

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• 44:59Alex Kantrowitz?

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

• 45:14Alex Kantrowitz?

  And we're back here on Big Technology Podcast. We're here with Sohail Doshi. He's the CEO and founder of Playground. We talked a little bit about image generation in the beginning. In the time we have left, let's go rather quickly through the tech giants. I'll start with Google because Google's been sort of like the punching bag of the AI community for a while. Sohail, you even had a tweet that says, "Google's lost its way. It's the best company to compete with. Even investors have stopped asking, what if Google does it?" I mean, Google did just start doing image generation. They had to shut it down. What is happening there?

• 45:52Speaker 02

  Oh, man, I wish, you know, obviously, I only have a slight preview into what's going on at Google. But, you know, my guess as to what feels like is happening is they are in a significant race where either investors or customers believe that by losing this race, it's an existential issue. Time will tell, however. And Google's rushing to be a strong leader in that race. And they have to contend with a significant, complex bureaucracy that is not really well attuned for the velocity that AI is running at right now.

• 46:35Alex Kantrowitz?

  So it's organizational. I've wondered how much of it is because... Google sees a threat to search over time if it pushes the status quo forward too quickly. And right before we were talking, I was on CNBC talking about the state of Google. And I was absolutely floored by one of the numbers that Deidre Brosa, who's an anchor there, brought up, which is that I think Gartner believes that by 2026, we will be doing 26% less searches than we are today. Our search engines will have 26% less traffic. I know you've, you're connected with perplexity in some way. We just said, are of in Cerny Voss. I'm kind of floored by that number. I don't believe it.

• 47:17Alex Kantrowitz?

  I think that search is going to be, continue to be a way that we use web navigation. And AI search like perplexity will be more to satisfy curiosity and engage with different topics. What do you think about the stat? And what do you think about that, that argument that I'm making?

• 47:36Speaker 02

  I mean, I think there's a very high probability it is greater than that number in a shorter span of time.

• 47:43Alex Kantrowitz?

  Whoa, for real? That will be doing even fewer, that, that search engines will have even less traffic than, or even, an even greater decline than 25%?

• 47:52Speaker 02

  That's right.

• 47:52Alex Kantrowitz?

  And that will happen before 2026. Okay.

• 47:55Speaker 02

  Yeah, that's right. Exactly. Because let's think about the model jump so far, right? We've got, you had Dolly two in April, two years ago. Look at the difference between that and any cutting edge model. We can look at GPT three, which was four years ago. And now we have GPT four, GPT five is probably slated imminently this year. The jump from four to three was incredible. And I don't, and I think the key, the reason why I believe this, this perhaps this like very surprising thing is because

• 48:27Speaker 02

  I don't think people quite internalize how many more, how big of a jump can be had still. Like, we're still so, at the beginning, the early phases of this thing, that it is, it is moving faster than Moore's law.

• 48:43Speaker 02

  By a lot. And the biggest people right now are putting in huge quantities of money. I think I already find it annoying to have to go to Google and like run through a few links and then click and then back and then click and then back and then, oh, there's an ad here. Okay, let me scroll down. You know, it's already, it's, I think humanity already can tell it's frustrating. So if you were to, if you were to go, hmm, this thing is already kind of inefficient, somewhat frustrating. In fact, like, I just want the answer. I don't want to have to find the answer. Right? I think that's the problem these things are solving. And you look at the model jumps, right? Over the last three, four years, it doesn't seem, it doesn't seem surprising that like

• 49:27Speaker 02

  almost all the traffic would shift to something that is, I mean, Google has very low switching costs. I mean, right now, it happens to be integrated well in the browser. Right? It, it happens to be, um, uh, but actually, the funny thing about Google is like, it has slightly less lock-in and ease on mobile. In most consumer traffic, desktop is shrinking for consumer while mobile's dramatically increasing.

• 49:52Alex Kantrowitz?

  They do have Android.

• 49:53Speaker 02

  Many times.

• 49:54Alex Kantrowitz?

  Yeah.

• 49:54Speaker 02

  We do have Android. We do have Android. But, but we're talking about, you know, whether Google's search matters. Like, Google could make a model that matters and is relevant, but it still might, it might still might spell the end of its search business. So in my, my general feeling about this is that the UX of like something like Perplexity, we've already figured out is like a nice UX. And you combine that with another model jump like GPT five or six, it doesn't seem that crazy to me that we end this desire of going to Google and then scrolling through blue links and clicking on each of them.

• 50:27Alex Kantrowitz?

  Is your default search engine Google or something else?

• 50:31Speaker 02

  Oh, certainly it's Google, but I've already, but, but I've already shifted so much. It, it's not my first go-to.

• 50:38Alex Kantrowitz?

  Right.

• 50:38Speaker 02

  Right? Unless I want to go to a very specific site. I mean, people going to their address bar inside of a browser or phone to search a website that they're trying to go to is just, they're not really using Google's value. They're just, you know.

• 50:50Alex Kantrowitz?

  Right.

• 50:51Speaker 02

  It's like my, you know, my dad used to type in CNN.com into Google and you could just type it in the address bar. It's not a real search.

• 50:57Alex Kantrowitz?

  Yeah.

• 50:58Speaker 02

  Right? Um, I, I don't, I already think it's not really a, a great go-to.

• 51:02Alex Kantrowitz?

  Interesting. Okay. Another thing that you said, let's go to Meta. You said, uh, the only thing scarier than Satya is Mark Zuckerberg taking AI seriously. Unpack that.

• 51:12Speaker 02

  Well, I feel like Mark has been very focused on VR because he's trying to do something that I think, regardless of your view of whether VR is going to succeed or not, it's ambitious if he succeeds. And I think he's like a very relentless entrepreneur and founder. So, and he's one of the few entrepreneurs and founders that are like running a trillion dollar plus company. Not that many left. So I feel, you know, I somewhat feel like-

• 51:39Alex Kantrowitz?

  It's him and Jensen, I think.

• 51:41Speaker 02

  Yeah. And he's, and he's, he's very young still. So I think that, you know, for him to take AI, and the thing about Meta is it is super set up to succeed at this. They have the world's, they're like the first, second biggest research lab. They are, they have an immense quantity of compute that's only growing. I mean, I think he talked about having 350,000 H100s by the end of the year or something like that.

• 52:03Alex Kantrowitz?

  Yeah. And they're going to have total 650,000 GPU like equivalents by, I think, the end of the year, which is crazy.

• 52:13Speaker 02

  He, he's got an extremely ambitious AI research leader.

• 52:17Alex Kantrowitz?

  I mean, that's a lot of GPUs.

• 52:19Speaker 02

  It's a lot.

• 52:21Alex Kantrowitz?

  How many do you guys have?

• 52:23Speaker 02

  Uh, no, not anywhere close to that.

• 52:26Alex Kantrowitz?

  I mean, more than a thousand?

• 52:27Speaker 02

  Not more than a thousand.

• 52:28Alex Kantrowitz?

  Right. So it's just the crazy, I mean, speaking with ServiceNow also, which is their 150 billion, 160 billion public company, like they wouldn't say that they have in the thousands in an interview that I did with them. So to have 600,000 is, it's crazy.

• 52:44Speaker 02

  Yeah. I just, I just think that, you know, you combine founder with relentless ambition, with compute, with the best talent, you know, to me, it's a recipe that is hard to, I mean, and then you compare that with Google, you know, it feels a little like, you know, to me, it feels like they're a force to be reckoned with in the next few years.

• 53:08Alex Kantrowitz?

  Okay. Let's talk about Nvidia. Speaking of Jensen, I want to test an assumption here. I recently have found out that they, the basically are, the software that they, that they sell along with their chips is core to training AI models. And that makes switching away a lot more difficult. Is that something that you're finding in your business? That you're using the chips and the software to train models and you'd have a hard time switching to like an AMD?

• 53:34Speaker 02

  Yeah, the software is called CUDA and it's like their platform for doing all kinds of the, it's their way of interfacing with their GPUs. And so, you know, it has lock-in in the sense that there's like a huge developer community around it, just like x86 or something like that. You know, maybe there's, you know, software that's really tuned and optimized for x86. So that's what causes people to kind of stay on it. With CUDA, you know, it's not CUDA that's keeping, I think, keeping a lot of us. It's actually that there is nothing really dramatically better than Nvidia's GPUs. And so if there's nothing dramatically better than, I mean, the reality is the cost for

• 54:13Speaker 02

  training and inference are so high at companies at scale that CUDA is not, is not like a big reason why you're going to stay there. It's going to, it's going to come down to compute costs. And so if there were somebody that were really driving the costs down for the rest of us, we would all flip because we'd be worth it. So to me, it's not really, it's not just a function of CUDA. You know, I think that does, that is true to some extent. But I think for the big companies or anyone spending a lot of money, you know, we're just, we are, we all want there to be someone that can compete with Nvidia because one of the problems with Nvidia was that they released their H100, but they didn't really reduce its cost. You know, it is, it's two, it's, you know, 1.9x faster, but 2x costlier.

• 54:59Speaker 02

  And it technically reduces your costs because you're getting more GPU compute per node. Like you have a server, server costs finite amount. Well, now you can put more of the GPU dense compute per node, so your costs go down. But they didn't really price their GPUs lower. So that's somewhat disappointing because it would have been nice if it were the same price but double the compute, obviously. So Nvidia knows what they have.

• 55:24Alex Kantrowitz?

  Right. And so what about a company like Amazon? They're obviously developing their own chip. They're making models available off the shelf. People are using AWS compute, I imagine, to run models. What's your perspective on Amazon's place here? I mean, they also have Alexa, which is like, you know, a sleeping giant.

• 55:45Speaker 02

  Yeah, I mean, I think I think AWS has significantly missed the mark actually on this.

• 55:50Alex Kantrowitz?

  Okay.

• 55:51Speaker 02

  I think that Azure and GCP are doing Azure better than GCP better than AWS. AWS is interesting and we were looking for compute last year and AWS wanted to charge us five times more for the same GPU than 10 different providers all around them.

• 56:13Alex Kantrowitz?

  Wow.

• 56:14Speaker 02

  Would you stop at a gas station that was that costs you five times more than the one that's right next to it?

• 56:18Alex Kantrowitz?

  I would speed buy it, throw an egg.

• 56:21Speaker 02

  Right, and that's kind of what, and you know, I think what's happening there is that this is my insights, so I hope it's helpful for someone, but my guess is that they have a scarce stockpile of GPUs and they know that they can price those GPUs internally. They can price them to their internal customers at that price and the customers will buy it because the customers can't go anywhere else. Maybe maybe because they're allowed to in their company, so then they can charge five times more and that's what the sales reps are doing. But if you are a new customer, you have choices.

• 56:54Alex Kantrowitz?

  You're not doing that.

• 56:55Speaker 02

  You're not going to do that, but the sales reps will do it because it helps them reach quota.

• 56:59Alex Kantrowitz?

  That's crazy.

• 57:00Speaker 02

  So it's a, so I think there's a short term, there's a sort of short, it kind of feels like ever since Andy Jassy became CEO, AWS has turned very short term minded about how it's going to earn revenue. And this is obviously bad because anyone that knows anything about startups knows that the the biggest companies are yet to be built, but they're definitely going to not be running on AWS if their compute is five times more expensive.

• 57:27Alex Kantrowitz?

  Wow, that's crazy. And I wonder what that means for startups like Anthropic that are, you know, have billions of funding from Amazon and are going there.

• 57:34Speaker 02

  Well, that might be priced at 3.5X.

• 57:37Alex Kantrowitz?

  Exactly. Let's talk Apple real quick. I wonder what they're going to do with AI. I mean, they're hinting that they're going to do something at WWDC is like they're going to make a supercharged Siri or, you know, take the search bar away from Google and then give up on all that money they're getting.

• 57:55Alex Kantrowitz?

  They have some incumbency advantage, disadvantage, don't they? Because if they really push, push hard on AI to, you know, take up more room in the operating system, then they can crowd out some of the advantages that they have today.

• 58:09Speaker 02

  Yeah, I think Apple is in a really good position because their culture is already seemingly like one where they wait and see. And their advantages are not easily eroded because they own the hardware platform and all the network effects that are associated with that. So, Apple seems like they're in a really healthy position to wait and see and build the best things, not just build kind of like aimlessly. And Google feels like it's just trying to build everything. They're building ImageGen and Gemini and the coding and they're building an IDE and you know, they're and then they're like, ask all the PMs clearly to like integrate it this week into like every imaginable product. I opened Gmail, I opened Docs, I opened so many different random Google things and they're all trying to convince me to use AI.

• 58:54Speaker 02

  And I think Apple is super well positioned to just like let Google do all those experiments. And then just pluck the ones that are the best ones and use its massive install base and distribution power to deliver an amazing experience, not a rushed, rushed one. So, I think Apple is behind, but I think that they are often okay being behind and they execute very well, kind of from behind because they find ways to leap.

• 59:26Alex Kantrowitz?

  Yeah. Yeah. All right, let's talk lastly about Microsoft and OpenAI. You know, you gave a pretty strong statement about Amazon. I'm curious what you would think, what you think about the current offering from those companies. I mean, obviously, you're competing with them on the ImageGen front. And also just like, from your sense, do you think that the OpenAI situation is stable right now or is, are there going to be more fireworks on the governance side there?

• 59:53Speaker 02

  Hmm. You know, I think that, I think that the folks at OpenAI really only care about one thing. They, and I think people don't fully internalize this because it seems, it seems a little too crazy. It seems like sometimes when you read a company's mission, you're like, whatever. But I think that they, I think that Sam is genuinely focused on AGI and attaining that. And I think he does not care about Graphics and video necessarily, I think, I think he, those are stepping stones and that helps research, you know, get to the next point. But I think he is very focused on that.

• 1:00:34Speaker 02

  And so I think broadly, we don't tend to worry about that because we're pouring all of our energy into graphics. I can't, I can't say much about Microsoft, but I can just say that I genuinely believe that OpenAI is trying to pursue that effort. I can't tell whether that'll be three years from now or 30 years from now, though.

• 1:00:57Alex Kantrowitz?

  Yeah.

• 1:00:58Speaker 02

  In terms of what Microsoft's doing, yeah, I don't know. I'm not sure. But brilliant play by Satya either way.

• 1:01:03Alex Kantrowitz?

  Seriously. Yeah.

• 1:01:05Speaker 02

  Yeah.

• 1:01:06Alex Kantrowitz?

  I mean, to be the most valuable company in the world. But they seem like they're the tech giant that's in the best position right now, which is wild, given where they were like seven years ago, eight years ago.

• 1:01:17Speaker 02

  And also, and also just very surprising because it's like if they had not done that, they would have been maybe in the worst position.

• 1:01:23Alex Kantrowitz?

  Totally. I mean, being aggressive sometimes it matters. They've learned their lesson, right? They sat by and tried to ride Windows for as long as they could. And then people were like, yeah, we don't want to use desktop operating systems anymore. And they're like, oh, that's interesting. Okay.

• 1:01:40Speaker 02

  Right.

• 1:01:41Alex Kantrowitz?

  And the person that led that shift from, you know, one era of computing to another was Satya in the server and tools division. So here he goes again.

• 1:01:48Speaker 02

  Yeah, you know, he, he has, he is doing something that I find as even like slightly even more brilliant, which is not just the OpenAI deal, but if you observe very carefully, he is actually partnering with everybody. He is bringing all the models into Azure.

• 1:02:05Alex Kantrowitz?

  Right.

• 1:02:07Speaker 02

  And he's doing it very methodically. And I think that he is really setting up Azure to be, to leap, to leap and be a lot more competitive. So I just, I actually think that he's doing a really good job, kind of. Playing every field.

• 1:02:26Alex Kantrowitz?

  Yeah.

• 1:02:26Speaker 02

  And positioning himself kind of in the mid, positioning Microsoft, sorry, kind of in the middle of all that. So, you know, game recognize game to Satya.

• 1:02:37Alex Kantrowitz?

  Totally. All right. Just to end, I want to say that I actually reached out to you initially when you had a tweet advising founders to that, you know, if you're going to speak with a journalist, speak with someone who's independent, and I certainly am independent, and I DM'd you and I was like, so, and you lived up to your words. So I appreciate that. And I'd also say that like, these conversations are super valuable. And I think that, that speaking with journalists inside, we're probably not going to agree on this one. So it could be a different, different conversation. But speaking with journalists inside some of the corporate media, I don't think they're all out to get tech founders, especially

• 1:03:18Alex Kantrowitz?

  off the record conversations, sort of like if there's a divide between founders and reporters, then the misunderstandings will just grow. But anyway, that's just my piece. So I appreciate you being here, though. But go ahead.

• 1:03:31Speaker 02

  Yeah, I, yeah, I think that's sort of the, the real issue is not that, you know, the individual reporter is a bad person. I think they're all like well meaning, well intentioned. So when you, if we have conversations with them, right, if you have a conversation over drinks or dinner, whatever, they're obviously good people, good, good, well meaning people working hard. That's not so much the issue that a lot of us, that you, that basically think that you should largely stop talking to the institutional media have. It's not that we think they're bad. It's that we think that their institutions are bad. And their institutions create incentives that create bad situations. You know, where, where like

• 1:04:15Speaker 02

  they, you know, like, what is the cause? You know, we should, I think we should also be a little bit curious. Like, what is the cause that causes a reporter to write a story? And then email you and say, do you have a comment? And then publish the story one hour later. What is the cause for that? You know, is that person a bad person? Probably not. A person is under some kind of deadline or incentive or pressure that is causing this thing. And this particular, I pick on this instance because it's a very obvious one that everybody knows is bad. Is not well, you know, that has really bad implications. They're not giving founders to respond to something. It's happened to a lot of my friends, a lot of other people talk about this. So, you know, I think that's the real issue.

• 1:05:00Speaker 02

  And that's why, you know, you could just as well work at, you know, any of these media institutions. But the fact that you're independent causes your incentives and your desires of what you want to write and what you want to do to be totally different. And the reporters that used to work at some of these institutions that have struck it out on their own, like you,

• 1:05:20Speaker 02

  you can see it all get cleaned up. Right? They completely change what they write, what their beats are and how they work and interact with other people in the world. So I think it's a lot better, more factual, more interesting reporting.

• 1:05:37Alex Kantrowitz?

  Yeah, it's interesting. I mean, I obviously am competing against like the broader media ecosystem. So I do hear you on that front. Anyway, it's something that we could talk about forever. It is good to hear your perspective on it. And once again, I appreciate that you you put something out there in the world. And then when I was like, all right, let's talk, you said yes. So I hope this isn't the last time. I hope to have you back. And so thrilled that you were able to come on and join and talk about all the new stuff that you're working on in the broader industry. It's like, it's cool to be able to speak with someone who like you read their stuff on Twitter. And then like you have a conversation like this goes more longer than an hour and it could easily go to or more. So the substance is there and I appreciate you being here. Thanks again.

• 1:06:19Speaker 02

  Thank you. Thank you for having me.

• 1:06:21Alex Kantrowitz?

  All right, everybody. Thank you for listening. We'll be back on Friday to break down the news as we do every week. And we'll see you next time on Big Technology Podcast.

• 1:06:38Speaker 03

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