Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 511: The Mad Dash To Cash in On AI. Is AI overhyped AND underhyped?

Starting point is 00:00:00 This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live in Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. It's probably a question that many of you have pondered to yourselves.

Starting point is 00:00:52 Is this AI thing overhyped? Or is it maybe underhyped? And we might not know the answer to that question for many years, but it doesn't change the harsh reality right now. Regardless of what your views on generative AI are, everyone's doing the same thing. Everyone's in this mad dash to cash in on AI. So I'm excited for today's conversation as we tackle this with a guest that's been there, right?

Starting point is 00:01:26 One who's actually written the book on this very topic. So I'm excited for today's conversation and I hope you are too. So what's going on, y'all? My name's George Wilson. I'm the host of Everyday AI. This is your daily live stream podcast and free daily newsletter. us all, not just learn what's happening in AI, but how we can actually leverage it to grow our companies and our careers. So it starts here with the podcast live stream. That's where you learn,

Starting point is 00:01:51 but you leverage everything that we learn by going to our website at your everyday AI.com. So there on the website, you can sign up for our free daily newsletter. We're going to be pulling out the best insights from today's conversation and breaking it all down for you there, as well as keeping you up to date with everything else that you need to know in the world of AI to be the smartest person in AI at your company. Also on the website, you can go listen to more than 500 episodes with some of the brightest minds in AI. All right, I'm excited for today's conversation on this mad dash to cash in on AI and talking

Starting point is 00:02:24 about if it's over hype or under hype. But before we do, let's start off as we do on most days by going over the AI news. A lot actually going on today. So first, Adobe announced that it is adding image generation AI models from Open AI and Google into its Firefly app, broadening the range of AI tools available to users and making the app accessible also on mobile devices. So Firefly users will be able to create images using OpenAI's GPT ImageGen, a lot of news on that one today, as well as Google's Imagine 3, Google's V-O2 video generator, flux 1.1 Pro, and more, and they will be adding models soon from Luma

Starting point is 00:03:11 and runway. So Adobe is aiming to serve different user needs by allowing customers to choose between its proprietary Firefly models for production level work and also third party models, whether it's for idea, ideation, experimentation, or whatever else. So pretty big news there from Adobe. All right. Next, but pretty big as well. Geez, a lot of for a random Thursday here, the middle of end of April, a lot of AI news. So Microsoft. has officially unveiled its co-pilot Wave 2 spring release for 2025, with some new updates and just some old ones as well, putting it under the Spring Wave 2 wrap.

Starting point is 00:03:54 So a couple new things. The chat interface has been redesigned to make it easier for users to find and use tools, access previously created content, revisit past conversations, and engage with favored AI agents directly from the chat. previously Microsoft has also rolled out AI agents called researcher and analyst powered by OpenAI's latest reasoning models which will soon be accessible through their frontier program also a new agent store will allow users to browse select and pin preferred AI agents for quick access and then probably the biggest one out of this is well they're going to be rolling out chat

Starting point is 00:04:33 GPT's new GPT40 image generator and also integrating that as well throughout their co-pilot platform. The co-pilot notebook feature will soon transform notes and data into actionable insights, including dynamic charts and those ever popular audio summaries narrated by two hosts. So yeah, a lot going on there on the co-pilot side. And last but not least, related actually to those last two stories, is Open AI has officially unleashed their image gen model to the API. All right.

Starting point is 00:05:11 So you might be wondering, what does that mean? Well, all those viral images that are being created in OpenAI's GPT40 image generator. Well, they've all been inside of Chad GPT, but now Open AI is opening that up to developers everywhere. So what that means is you're probably going to be seeing a lot higher quality of AI generated images where, you know, previously, especially for these companies that maybe still use open AIs Dali technology, the images weren't that great. But now we are going to see a much broader rollout across the board to probably hundreds. And major companies already, such as Canva, GoDaddy, and Airtable, are already exploring or even already have implemented the new model, which on the API side

Starting point is 00:05:57 is called GPT Image 1. Terrible name. Anyways, but this is going to, to definitely streamline creative workflows and offer image generation capabilities directly in so many more enterprise tools. All right. For more on those stories, make sure to go to your everyday AI.com. All right, let's get into the heart of today's conversation. This is one I'm stoked for bringing in a Chicago writer and reporter, right, who used to be in the Chicago scene.

Starting point is 00:06:27 So for our live stream audience, please help me welcome to the show. Gary Rivlin, the author of AI Valley. Gary, thank you so much for joining the Everyday AI show. Great to be here. Thanks, Jordan. All right. I'm excited for this one. Live stream audience. Thanks for tuning in, Kyle and Gene. And gosh, we got a couple dozen already in the house.

Starting point is 00:06:48 So if you do have any questions on today's topic, make sure to get them in. Might have time for them at the end. But let's start at the top, Gary. Give us a little bit about your background in Silicon Valley, specifically and how you've been kind of reporting and following AI since the early days. Right. So I had been a political reporter at the start of my career, but it was the mid-1990s. I was in the Bay Area, San Francisco Bay Area. And, you know, I had actually got to school as an engineering major program, but just got interested in politics. But suddenly the dot-com internet was rising. And so I kind of changed topics in the mid-1990s and wrote about the rise of the internet, the dot-com boom and bust and all. And, you know, kind of since and then kind of went on. So I was working for Wired. I went on to cover Silicon. Valley for the New York Times through the mid-2000s, you know, kind of the Google going public,

Starting point is 00:07:37 kind of revival of of Silicon Valley after kind of the 2000.com fall. And, you know, just I'd kind of moved on, but then I just got this random email at the end of 2022 from Reed Hoffman, Reid Hoffman, co-founder of LinkedIn, investor in Facebook, Airbnb, you know, kind of just a central figure in Silicon Valley. I had gotten to know him in the early 2000s right after LinkedIn when published, I wrote a feature for Wired. So I've known him since the early 2000s. And I was on his meal. He's like, dear friend, I'm like one of 2,500 friends. And you know, at a different day, I might have hit delete. But I read this thing. And like, he's like, hey, I'm having my first, I've co-founded my first startup since LinkedIn. And it's around AI. And he had this one line.

Starting point is 00:08:28 This remind me of me being a frustrated programmer earlier in my life. Like, instead of us learning the machine's language, the machine is going to speak our language. And I feel like, like, wow. And I realized, like, this is I had great time. It's right before the world kind of went crazy with chat CPP. Again, the end of 2020, it's like, huh, maybe I should move back to Silicon Valley. You know, I mean, move back to Silicon Valley as a topic. And so since the start of 2020, 23, I've been following, you know, his, Reed Hoffman's

Starting point is 00:08:58 company and other founders, other investors, looking into Google, Microsoft. How are they planning on cashing in, taking advantage of this moment? So I love that story, right? Like getting an email from, from Reid Hoffman and being like, huh, like, like really thinking about it and first being like, is this real? And then figuring out, oh, yes, it's definitely real. Right. So, you know, walk us through.

Starting point is 00:09:22 How did that initial email from Reed eventually, right, down the line, turn into the book AI VAL. Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience. Meet Firefly AI Assistant, now live in the Adobe Firefly app, the all-in-one creative AI studio. Powered by Adobe's Creative Agent, Firefly AI Assistant lets you start with your vision, just describe what you want, and shape the outcome as it takes form with the assistant.

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Starting point is 00:10:40 See it today at firefly.adobie.com. Right. So, you know, I mean, just because one person is telling you like, hey, this moment is here, you know, you don't necessarily get on an airplane and, you know, start reporting. So I just, you know, make calls. I'm like, you know, just figuring out that generative AI really, this was a breakthrough moment. And again, it helped that my timing happened to coincide with chat GPT. So the wider world was waking up to the potential of generative AI.

Starting point is 00:11:12 But just kind of re-contracting sources of mind from over the years and understanding, like, wow, all this has happened, like the transformer model out of Google, you know, GPT's 123, 3.5, you know, before this, that you're like, wait a second, you know, there have been these key moments and this is the inflection point. So, you know, early on, I just realized, like, wait a second. This is one of those before and after moments, like before chat CPT, you know, a small group of people involved in AI. But after chat CPT, this is gen of AI. This isn't a product like Google Translate behind the glass. This isn't a recommendation engine.

Starting point is 00:11:51 This is something you can talk with. You can interact with. And so, you know, I just kind of instinctually understood that this is an inflection point. and I should I should jump on this moment. You know, and we'll make sure to leave the link to the book in the newsletter today because I think it's definitely on my list of books that I need to read very soon. But, you know, walk us through maybe what are some of your main findings, right, from being able to talk with some of the leaders that are building all of the AI systems

Starting point is 00:12:27 that we're using now as well as just, you know, being a pretty, to everything, right, as a former Pulitzer Prize winning journalists, you know, privy to probably things that we didn't get to see on the surface. But walk us through maybe some of your main findings of the book in AI Valley. Well, I mean, one of the first things is, how did we get here? And, looking into the history is fascinating to me. I tell it through a couple of characters, but, you know, since the 1950s, there was this over optimism that AI is just around the next corner. So for like decades since the 50s. It's been just around the next corner. You know, there was this massive wrong turn that, you know, kind of rules-based, this idea that you have to like teach a, teach a

Starting point is 00:13:11 program line by line by line to how to react. You know, that was the main approach. People ridiculing neural networks, neural networks date back to the 1950s. But, you know, people didn't see any promise in that. And in fairness to those folks, there really wasn't much promise because computers computers weren't powerful enough until that point. We didn't have the digital data for training. That wouldn't really happen until the second half of the 90s and the rise of internet. So that was one thing, like, just kind of how did we get here and sort of, you know, just just sort of the, to understand this moment, it helps understand what it happened before it.

Starting point is 00:13:47 And, you know, I also started realizing, like, I'm in deja vu. This is, this is the mid-1990s all over again. We could talk about a couple of differences, the change is moving faster than it did in the 1990s. With that said, you know, this is idea. I learned this early on, my second interview ever in Silicon Valley. I was really smart guy, Paul Safo, a forecaster, kind of helping us understand the future, said, you know, we tend to overestimate the short-term impact of a technology, but underestimate the long-term impact. And that's the Internet.

Starting point is 00:14:23 You've asked me about the internet in 1997. I understood lots of reporters understood like, yeah, startups, you're not really going to get, this isn't going to happen fast enough for you to get, you know, fabulously wealthy overnight. And, you know, most dot coms did in fact go out of business with no return. But I also didn't quite understand in the mid-1990s how pervasive this would be. In fact, I remember talking to a venture capitalist back then, John Doer, very well-known venture capitalists.

Starting point is 00:14:52 And he just invested in this company called Amazon.com. And he says to me, like, oh, they're going to do more than books. And so to my little mind, it was like, oh, they're going to do CDs, too. You know, they're going to, you know, it's just going to do. And so, you know, I don't think we understood it was going to be the everything store. And so much of the world, business, education and your personal life would be transformed by the internet. And I think the same, you know, two years on the front lines of AI, I think the same. I think the same thing.

Starting point is 00:15:23 I use models. I use large language models every day all day. They're really useful tool. I could tell you, we could talk about the strengths and limits. But, you know, it's a powerful,

Starting point is 00:15:34 powerful tool. However, it's limits. Like people talk about 2025 is the year of the personal age. I'm like, yeah, but it doesn't really have much of a memory.

Starting point is 00:15:43 And so the whole advantage of a personal age is they know like, you know, Jordan likes aisle seats and Gary likes windows. You know, they get some new you over time. They really, I'm having a hard time remembering you from session to session. But imagine 10 or 15 years from now, and I think we'll say the same thing about AI that we've said about the internet. It's changed everything.

Starting point is 00:16:03 It's turned upside down organizations, education, personalized businesses across the board. So, you know, I'm curious. And that was some great background there in drawing these parallels to the, you know, the dot com, you know, boom or bust era of the late 90s. ultimately what that led to. But I'm wondering, you know, what other insights did you glean? And, you know, like that comparison specifically, right? I'm always thinking about it because I think, you know, companies specifically, they had, you know, three, five, sometimes 10 years to, you know, figure out their kind of

Starting point is 00:16:43 internet strategy, right? But on the AI side, I tend to think it's not really the same. Yet, I think people are really drawing that comparison, in my opinion, maybe too tightly, right? With everything on AI and kind of the dot-com era and they're like, we've been here before. So, you know, I'm curious from your findings, your reportings. Are you seeing that as well? Companies trying to follow kind of their dot-com business plan a little too tightly? Yeah.

Starting point is 00:17:13 Are you talking about potential customers? Do you talk about the creators of these? Maybe even both. Yeah, that's interesting to tackle it from both. Yeah, I mean, for the creators, you know, let's understand that when, you know, an open AI or an anthropic takes, you know, billions, tens of billions of dollars. And venture, you know, venture dollars, they really need to satisfy their investors. And so, you know, I really do think they're following a dot-com playbook of overpromising.

Starting point is 00:17:44 And I think that's really going to hurt them. I mean, I wouldn't bet against open AI. But, you know, just sort of that there's an issue that the accelerationist, the zoomers, those who say like full speed ahead, let's put no guidelines on AI. The general public is, the majority of general public is fearful of AI. Less than one third of folks in polling are excited about AI. So I do worry that a hype is going to cause a similar fall. I don't think we're going to have a dot-com like bust with AI.

Starting point is 00:18:21 We're not seeing all these AI startups go public. It'll be different. But I really do worry about kind of a boomerang. So if I was talking to a business audience, I would say, yes, you should be experimenting with this. But again, understand it's this is idea of like autonomous AI, this idea that, oh, we'll just have AI employees, digital employees, and they'll do the work. It's like, I think in the short, medium term, that's the wrong construct. To me, in fact, I love Microsoft's name for its, you know, for its chatbot, co-pilot. That's perfect.

Starting point is 00:18:55 It's like, it's going to help you. You know, we were talking before the show. Like, you can't type into a prompt, you know, make me a Martin Scorsese movie, you know, enter. Like, that's not the way it works. You are the creator. It's human-centered, you know, right now. It's a fabulously powerful tool. It's a limited tool. It makes mistakes. It's not quite where it's going to be in five or ten years, but it's a really powerful tool that can help you do whatever you want to do it. For the book, you'll laugh at this. The first thing I did when I thought of that, huh, should I write a book about AI? I went to chat TVT, like write me a 5,000 word proposal that would win me a contract on a book on AI. And, you know, I got two things from that experience. You know, one, it is far better read than I am as a far superior memory than me.

Starting point is 00:19:43 But on the other hand, the second thing is like, it can't really, it's very mediocre writing. It's very flat. And so like, however, when I say, hey, here's a paragraph, I'm not loving it. I like the ideas and it helped me improve it. That's when it's really strong. Get, I'm the creative. I'm giving the ideas. I'm giving it the approach and it could help me see that through.

Starting point is 00:20:06 It could help me with the execution. And so like, you know, I really think that's important for businesses to understand. that this is an autonomous AI. When I get rid of the human, at least not quite yet, I can't predict 10, 50 years from now. But I want everyone, students in school to business leaders

Starting point is 00:20:29 and everyone in between, use this, understand what it's good at and what it's not good at. So, Gary, you brought up an interesting fact as part of a study, saying that less than one third of people are excited about AI. Yet the six largest companies in the US by market cap are sticking every dollar they can into investing in these systems. Technically hundreds of billions of dollars in

Starting point is 00:20:58 capax and in AI spending. So how can you kind of like explain that dichotomy, right? Because people aren't necessarily thrilled about AI. Yet the biggest companies in the world are sticking hundreds of billions of dollars and kind of saying like, hey, it's coming no matter what. So I'm curious, you know, how can we make sense of that kind of dichotomy? You know, I think it's very rational for a Microsoft or meta to be putting in these tens of billions of dollars will probably be soon each company hundreds of billions of dollars. Because if they miss this, it's going to be a multi-trillion dollar miss. And so, you know, you can almost see it as a hedge against, um, uh, the,

Starting point is 00:21:39 the future, but I don't think it's a hedge of against the future. I come back to we tend to overestimate in the short run and underestimate the long run. Like these companies, I mean, you know, Microsoft's sitting on $100 billion, they can afford to do this kind of investment because they see, and I think they see correctly that five, 10, 15 years from now, they're going to get a nice return on this investment. Like, you know, right now, we're, you know, capacity on these data centers. they're predicting that, you know, by 2030, we'll have have a doubling of data centers. So I don't see that diminishing anytime soon.

Starting point is 00:22:14 I just, you know, there's an expression among the venture capital. It's like, you know, go to where the puck is going, not where it is right now. And I think that's what these companies are doing. You know, they see like, you know, we're making an investment, not for the next quarter, but for a five or 10 year time horizon. And that seems very difficult. right, right, to even like my, you know, because I think about the, you know, skate to where the puck is going, which makes sense and has historically made sense for, you know, at least dealing with tech innovations

Starting point is 00:22:48 over the past couple of decades. But at least for me, when I look at everything as someone that covers AI every single day, it's almost like, you know, we're in a new game, right? Like there's no longer a puck, right? And there's no longer skating because, you know, all these, you know, machines are starting to do these things for us. right so you know not not asking you to be a business uh consultant here but but how can the majority you know of americans and our listeners kind of uh you know kind of uh take on that that that mantra of skating where the puck is going when a high development is so freaking fast right so i i was talking about kind of the venture capitalists the founders you know the tech leaders uh um skating where the puck is going i think for people right now you know again

Starting point is 00:23:36 start using it. I'll use that. I wrote a feature article about this incredible company runway. They do text to it, excuse me, text to image to video, text to video. And you know, they're one of the leaders in, you know, video generation. I mean, they're up against Open AI, Google, et cetera. So who knows who's going to win this? It's three artists in New York City, you know, taking on, you know, de-blurting PhDs. And so far, if they're not ahead, they're right there in the competition. And so in doing that article, I said, like, it's really important that who's actually using your product? Hollywood is using their product. They, like, instead of having a, like, they want to do a 60 second scene that is on a mountain size with a thousand soldiers in the mids, you know, in the middle ages.

Starting point is 00:24:23 That's prohibitive. It would be $10 million more and they probably wouldn't do it. But now with AI, they can do it. And so, you know, what are the practical things? I talked to a global production, production company that uses. runway all the time and like you know how is this helping they said you know in the past they'd have 50 or 60 people for a film shoot you know kind of people organizing the talent the talent the production people the post production people all of that and 50 60 people now using runway they have

Starting point is 00:24:53 15 to 20 people you know the timeline instead of being you know typically 16 weeks from thinking of an idea to you know launching to releasing it it's now six weeks so 16 weeks to six weeks to six weeks And they say like the average project we're saving 50 to 80%. See, that's a very concrete way. They have figured out like, okay, we're still figuring this out as you correctly say, like, who knows in five years what a video model. What will a cutting edge video model, you know, look like? But they're figuring out how to use this thing that exists now that's a limited but powerful tool

Starting point is 00:25:27 or a tool that's very powerful in certain ways and not quite what it's going to be. And so they're figured out like how to say 50 to 80 percent. That's a big, big savings. And so, you know, across the board, you've, you know, you've got your marketing team, you know, and is the marketing team of 10? Like, I think using AI, you can have a marketing team of five that's, you know, using the AI to iterate and, you know, kind of, oh, here's my idea, do a quick illustration. Oh, no, change it, change it, change it.

Starting point is 00:25:55 You know, you'll still have an illustrator or two. You'll still have creatives, but I don't think you'll need as many. I think right now AI is a great cost savings tool rather than like, oh, we will replace our marketing team, you know, with digital labor. Yeah, I think the runway example is great. And yeah, obviously, you know, Gen 4, extremely impressive. And it is cool to hear kind of the story, right? It's artists and not, you know, people with, you know, 20 years of deep learning experience.

Starting point is 00:26:23 And, you know, yeah, they did their partnership with Lionsgate, right? Like a huge studio there. So extremely impressive. You know, so I'm wondering, you know, Gary, kind of like, going back to this concept of, you know, AI maybe being overhyped in the short run and maybe underhyped in the long run, even for you, as someone that was covering this, you know, from the front lines, so to speak, and being able to talk, you know, personally with, with some of the leaders in the AI industry, what were maybe some things that even took you back and you're like,

Starting point is 00:26:56 oh, wait, you know, wow, right? Like, I have those moments all the time, but I'm very much on the outside looking in. So from an insider's point of view, you know, what over the past, you know, year or two or a couple of months or a couple of weeks, right, is really even shocking you? Well, you know, this idea and this definitely, you know, conjured up memories from the dot com years, this idea that venture capitalers are so scared of missing out on the moment, this, the phoma, like we could have gotten early into X, but we missed this, you know, multi-billion-dollar opportunity. So they're throwing money at these half-baked ideas. I mean, Ilias Satskiver, the co-founder of Open AI, who famously initiated the coup back in 2023. He left Open AI for obvious reasons.

Starting point is 00:27:44 So he's founded as safe superintelligence, I think it's called. They don't have a product yet, but they've raised billions of venture capital and they have a paper worth of, I think, $32 billion. And so I kept on seeing this happen over and over again. There's a promising team like, two top Google machine learning specialist teaming up with someone, you know, Meta who left, another machine learning. And they create a company, they write a memo and they raise, you know, $10 million on $100 million, you know, valuation. Like, you know, I think two things, like, that's insane. And the other thing is like, I sort of get it. These are really promising people. We have no idea. We want to get it on the hot deal. We might lose our $3 million we put in towards

Starting point is 00:28:29 a 10 million, but if we don't, you know, if we, if it pays off, you know, that three million, you know, could be, you know, billions. I, example, so I was covering Silicon Valley through the New York Times in the mid-2000s, and there's this new company, the Facebook.com and Excel, Jim Breyer, famous venture capitalists, put in, I think you put in $12 million at $100 million valuation, up and down Sandhill Road, you know, all through Silicon Valley. They're all mocking, you know, Brian. What a fool for this college only app.

Starting point is 00:29:02 He's putting in all this money, $100 million. Like that $12 million became like, if you, if you kept it through going public, it was like $4 billion, something like that. And it would be held it. It would be worth, you know, tens and tens of billions of dollars. And, you know, that's the venture capital game. Most bets are wrong. I mean, they either, you know, show nothing or they show barely any return.

Starting point is 00:29:25 But, you know, it's, it's, it's a game. where that one big hit to make up for everything. So and that's that's venture capital in Silicon Valley. You know, we're just going to slap down bets and just hope that one or two of them are, are huge. So you'll ask me why to conjure it up. There's kind of this insanity that's understandable. So, you know, one thing that you mentioned earlier, right, when we were talking about,

Starting point is 00:29:51 you know, less than a third of people, you know, being excited about AI, yet all the big companies, are, you know, investing in it. You kind of talked about this boomeret effect. Could you talk a little bit more about what that means? Well, you know, so there's business and there's the personal side. Business I put in a different category. Like, okay, if your work is saying like the Shopify CEO, I want every employee to be using it. You're going to be using that.

Starting point is 00:30:24 But, you know, kind of this whole idea of personal agents, this idea, this idea, that the public is going to be, the consumer, the general consumer audience is going to be using these things. Like, we're asking, you know, these personal agents are going to have all this power. They're going to have access to your private information. And, you know, kind of in an existential sense, like humans are soon not going to be the smartest entity on the planet. It's kind of frightening for people. I mean, I blame the media song for that. I blame Hollywood, you know, for, you know, the Terminator-like movies like, oh, the robots are going to take over.

Starting point is 00:30:56 It's not Mike. my concern. But, you know, so I feel like they're going to get ahead of this. And I think it's inevitable that something bad's going to happen because AI, you know, just to make one up, like a trillion dollars is siphoned off from the global economic system before a human even understands what's happening, a deadly pathogen, you know, and AI for good, it could create, you know, vaccines and cures. There's also one that could create a deadly pathogen. So I think, I think it's inevitable that that something bad's going to happen. And I really fear that it's going to turn the general public off to AI.

Starting point is 00:31:31 So I wish those working on frontier models would be a little bit more aware of where the public is assure them that trust and safety is essential, as I'm sure your listeners know, trust and safety used to be a major concern of all these companies. But once the starter's pistol went off, once chat cheap, B2 went out there, you know, the competition cashing in became a priority and trust in safety became a secondary concern. I think that's a mistake. That is fascinating, right? And even these, you know, Frontier AI labs, their safety teams have, you know, kind of shrunken over, over the years or maybe, you know, it was front and center previously.

Starting point is 00:32:14 And now, you know, it's kind of an afterthought, right? Like the safety of models, right? Like, what are you seeing, you know, what are you maybe seeing as similar trends? right so that's that's one you know hey safety it used to be all about safety now the starter pistol went off it doesn't really matter right what are some other trends that that you've picked up through this experience of reporting uh you know in silicon valley that that maybe the rest of us haven't picked up on yet so what really scares me so i approached this book um looking at startups i felt like i wanted to find who's going to be the next google who's going to be the next facebook

Starting point is 00:32:51 meta and what I discovered after like all my reporting is like the next Google is likely going to be Google and the next meta is going to be meta. These things are so expensive. When I started, it was like they were talking about this is started 2023, tens of millions of dollars to train, fine tune and operate these large language models. By the time I was done reporting, you know, it's hundreds of millions of dollars. Now it's billions if not tens of billions of dollars and like a large venture capital outfit in Silicon Valley raises $1 billion. But if Anthropic, as Dario Amode, you know, said, they're going to need, he figures $100 billion, you know, for their next iteration, their 2027 iteration, how are they going to raise that money? So I'm scared it's going to get so

Starting point is 00:33:38 expensive that either they're going to have to sell so much of their company, they don't really own the company, you know, Anthropic, to use that example, Google's put in billions of dollars, Amazon's put in billions of dollars or probably more likely they'll end up getting bought by a Google or an Amazon. So, you know, my big fear is that big tech, which create a big mess with technology in the 2010s, that if they're going to be charged at AI, there's the trust issue. You know, AI had really bad timing, right? Came out, you know, I mean, AI has been around for decades, but, you know, generative AI coming out at the end of 2022. You know, trust in Big Tech, big tech was pretty much an all-time.

Starting point is 00:34:18 low, you know, Facebook, Amazon, Google, people really are entrusting those companies. And yet I do think AI is going to be in the hands of Google, Microsoft, maybe an open AI. And, you know, I'll point out, by the way, Open AI founded in 2015 was a counter to Google. Rather than, I know, stars of nonprofit famously, they're trying to rid themselves with their nonprofit parent. But it started as kind of this idealistic thing, rather than profit. profit-driving AI. This is too essential. This is too powerful. We want it in the hands of an entity that isn't profit-driven. But open AI is profit-driven as Google or any other company out there. So even if an open AI breaks into that Google, Apple, Microsoft, Amazon, category of trillion-dollar giants, I think they're the same as those companies. I mean, Sam Altman, it's amazing what he pulled off. He's an amazing CEO. But he's, you know, he's

Starting point is 00:35:18 He's, we've seen all the folks who have left Open AI. I mean, the anthropic team before, you know, and before Chat CPP came out. But, you know, many people since then, you know, keep on saying the same message that safety is taking a back seat to shiny toys. Again, I get it. Like, let's, let's, these are great tools. They could do amazing things for medicine, for science, for education. I see fabulous upsides into this thing.

Starting point is 00:35:46 But like, there's also. like any technology, there's goods and there's bads. And I really wish we'd be more deliberate of ensuring that AI is a net positive and not a net negative. Yeah, I think that's the one thing ultimately on everyone's mind. So Gary, we've covered a lot in today's conversation, but I'm sure something that remains on people's mind is, okay, is AI overhyped or is it underhyped? So maybe for those business leaders, you know, they've been using generative AI, they're

Starting point is 00:36:18 implementing it in their company, but they're still wondering that. Is it overhyped? Is it underhyped? What's your quick takeaway on that as we wrap up today's show? I would say individual companies are overhyping their specific products and what they're able to do. But I think AI is underhyped. I really think AI is going to transform this world. Amazing things are going to happen because of AI. Yeah, I'm going to say underhyped. Great. Great question. Great answer there in a great way to wrap up today's show. So Gary,

Starting point is 00:36:53 thank you so much for taking time out of your day to come on the Everyday AI show. We really appreciate it. My pleasure. This is great. Thanks. All right. There's a lot there, y'all.

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Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 511: The Mad Dash To Cash in On AI. Is AI overhyped AND underhyped?

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