Ep 511: The Mad Dash To Cash in On AI. Is AI overhyped AND underhyped?
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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. It's probably a question that many of you have pondered to yourselves. 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? 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 is Jordan Wilson. I'm the host of Everyday AI. This is your daily live stream podcast and free daily newsletter helping 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 but you leverage everything that we learn by going to our website at youreverydayai.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 about if it's overhyped or underhyped. 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 OpenAI 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 image gen. A lot of news on that one today. As well as Google's Imagine 3, Google's VO2 video generator, Flux 1.1 Pro, and Microsoft's

more and they will be adding models soon from luma and runway so adobe is aiming to serve different user needs by 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 uh from adobe

All right, next, but pretty big as well. Geez, a lot of for a random Thursday here in the middle of the 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.

So a couple of 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 ChatGPT's new GPT-4.0 image generator and also integrating that at

as well throughout their Copilot platform. The Copilot 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 OpenAI has officially unleashed their image gen model to the API. All right, so you might be wondering, what does that mean? Well, all those viral images that are being created in OpenAI's GPT-4.0

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 ai's dolly 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 is called GPT-Image 1. Terrible name. Anyways, but

This is going 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 youreverydayai.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 at the Chicago scene. 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. Livestream audience, thanks for tuning in. Kyle and Gene and gosh, we got a couple dozen already in the house. 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'd actually gone to school as an engineering major. I had programmed, 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 a

working for Wired. I went on to cover Silicon Valley for the New York Times through the mid-2000s, Google going public, revival of Silicon Valley after the 2000.com fall. I'd moved on, but then I just got this random email at the end of 2022 from Reid Hoffman, founder of

co-founder of LinkedIn, investor in Facebook, Airbnb, kind of just an essential figure in Silicon Valley. I had gotten to know him in the early 2000s right after LinkedIn went public, excuse me, launched.

I wrote a feature for Wired. So I've known him since the early 2000s. And I was on his media. He's like, dear friend, I'm like one of 2,500 friends. And, you know, on a different day, I might have hit delete. But I read this thing. 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.

This reminded me of me being a frustrated programmer earlier in my life. Instead of us learning the machine's language, the machine is going to speak our language. And I feel like, well, like,

Like, wow. And I realized like this, I had great time is right before the world kind of went crazy with ChatGPT. Again, the end of 2022, 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 2023, I've been following, you know, his, Reid Hoffman's 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 Reid Hoffman and being like, huh, 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 how did that initial email from Reid eventually, right, down the line, turn into the book AI Values?

Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Gen AI. Hey, this is Jordan Wilson, host of this very podcast.

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Right. So, you know, I mean, just because one person is telling you like, hey, this moment is here, you don't necessarily get on an airplane and, you know, start reporting. So I just, you know, make calls and like, you know, just figuring out that, you

generative AI really, this was a breakthrough moment. Again, it helped that my timing happened to coincide with ChatGPT. So the wider world was waking up to the potential of generative AI, but just kind of recontacting sources of mine from over the years and understanding like, wow, all this has happened, like the transformer model out of Google, GPT's 1, 2, 3, 3.5, before this, that you're like,

wait a second, there have been these key moments and this is the inflection point. So early on, I just realized, wait a second, this is one of those before and after moments, like before ChatGPT, a small group of people were involved in AI. But after ChatGPT, this is gen of AI. This isn't a product like Google Translate behind the glass. This isn't a recommendation engine. 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 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 that we're using now, as well as just being privy to everything, right? As a former Pulitzer Prize winning journalist, 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 Values.

Well, I mean, one of the first things is how did we get here? And, you know, looking into the history was 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

is just around the next corner. So for like decades, since the 50s, it's been just around the next corner. There was this massive wrong turn that rules-based, this idea that you have to teach a program line by line by line how to react. That was the main approach. People ridiculing neural networks. Neural networks date back to the 1950s, but people

didn't see any promise in that. And in fairness to those folks, there really wasn't much promise because 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 sort of to understand this moment, it helps understand what had happened before it. And, you know, I also started realizing like,

I'm in deja vu. 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, this idea, I learned this early on, my second interview ever in Silicon Valley. This really smart guy, Paul Safo, a forecaster, kind of helping us understand the future, said, we tend to overestimate the short-term impact

of a technology, but underestimate the long-term impact. And that's the internet. 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 fabulously wealthy overnight. And most dot-coms did, in fact, go out of business with no return. But I

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 Doerr, a very well-known venture capitalist, and he had 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 you know they're just going to do and so you know i i don't think we understood it was going to be the everything store and so much of the world business education in your personal life would be transformed by the internet i think the same you know two years on the front lines of um ai

I think the same thing. I use models. I use large language models.

every day, all day. They're a really useful tool. I could tell you, we could talk about, you know, the strengths and limits, but you know, it's a powerful, powerful tool. However, it's limits. Like people talk about 2025 is the year of the personal agent. Like, yeah, but it doesn't really have much of a memory. And so the whole advantage of a personal agent is they know like, you know, Jordan likes aisle seats and Gary likes windows. You know, they get to know you over time. They really are 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. 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 and ultimately what that led to. But, you know, 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, it's

sometimes 10 years to figure out their kind of 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.

Yeah. Are you talking about kind of potential customers? Are you talking about the creators of these products?

Maybe even both. Yeah, that's interesting to tackle it from both. Yeah, I mean, for the creators, let's understand that when an open AI or an anthropic takes billions, tens of billions of dollars in venture dollars, they really need to satisfy their investors. And so I really do think they're following that dot-com playbook of over-promising, and I think that's really going to

hurt them. I mean, I wouldn't bet against open AI, but just sort of there's an issue that the accelerationists, 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 the

hype is going to cause a similar fall. I don't think we're going to have a dot-com bust with AI. We're not seeing all these AI startups go public. It'll be different. But I really do worry about 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 the idea of autonomous AI, this idea that, "Oh, we'll just have AI employees, digital employees, and they'll do the work." I think in the short and medium term, that's the wrong construct. To me, in fact, I love Microsoft's name for its chatbot, Copilot. That's perfect. It's going to help you. We were talking before the show, you can't type into a prompt, "Make me a Martin Scorsese movie," enter.

That's not the way it works. You are the creator. It's human-centered 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 10 years, but it's a really powerful tool that can help you do whatever you want to do. 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 to EBT, write me a 5,000 word proposal that would win me a contract on a book on AI. And I got two things from that experience. One, it is far better read than I am as a

far superior memory than me. 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. It could help me with the execution. And so I really think that's important for businesses to understand that this is an autonomous AI. We're not getting rid of the human, at least not quite yet. I can't predict 10, 50 years from now.

I want everyone, students in school to business leaders 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, you know, saying that less than one third of people are excited about AI. Yet the six largest companies in the U.S. by market cap are sticking every dollar they can into investing in these systems, technically hundreds of billions of dollars in CapEx and in AI spending. Right. So how how can you kind of like explain that difference?

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, you know, 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 mess. And so, you know, you can almost see it as a hedge against the future, but I don't think it's a hedge 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 5, 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. There's an expression among the venture capitals, go to where the puck is going, not where it is right now. And I think that's what these companies are doing. They see we're making an investment, not for the next quarter, but for a five or 10 year time horizon.

And that, and that seems very difficult, right? Right. To, to even like my, you know, cause I think about the, you know, skate to where the puck is going, which, which makes sense and has historically made sense for, you know, at least dealing with tech innovations over the past couple of decades. But at least for me, when I look at everything as, as someone that covers AI every single day, it's almost like, you know, we're in a new game, right? Like the,

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 consultant here, but, but how can the majority, you know, of Americans and our listeners kind of, you know, kind of, you know,

take on that mantra of skating where the puck is going when AI development is so freaking fast. Right. So I was talking about kind of the venture capitalists, the founders, the tech leaders skating where the puck is going. I think for people right now, you know, again, start using it. I'll use, I wrote a feature article about this incredible company Runway. They do text to Susie

excuse me, text to image to video, text to video. And they're one of the leaders in video generation. I mean, they're up against OpenAI, Google, et cetera. So who knows who's going to win this? It's three artists in New York City taking on deep learning PhDs. And so far, if they're not ahead, they're right there in the competition. And so in doing that article, I said, it's really important that who's actually using your product?

Hollywood is using their product. They want to do a 60-second scene that is on a mountainside with a thousand soldiers in the Middle Ages. That's prohibitively expensive. It'd be $10 million more, and they probably wouldn't do it. But now with AI, they can do it. And so what are the practical things? I talked to a global 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 15 to 20 people.

The timeline, instead of being typically 16 weeks from thinking of an idea to launching to releasing it, it's now six weeks. So 16 weeks to six weeks. And they say the average project, we're saving 50% to 80%. See, that's a very concrete way. They have figured out, 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 look like? But they're figuring out how to use this thing that exists now that's a limited but powerful tool or a tool that's very powerful in certain ways and not quite what it's going to be. And so they're figuring out how to save 50% to 80%. That's a big, big savings. And so across the board, you've got your marketing team. When is the marketing team of 10 like,

I think using AI, you can have a marketing team of five that's using the AI to iterate and kind of, oh, here's my idea, do a quick illustration. Oh, no, change it, change it, change it. 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 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. And, you know, yeah, they did their partnership with...

Lionsgate, right? Like a huge studio there. So extremely impressive. So I'm wondering, Gary, kind of like going back to this concept of AI maybe being overhyped in the short run and maybe underhyped in the long run, even for you as someone that was covering this from the front lines, so to speak, and being able to talk personally with some of the leaders in the AI industry,

What were maybe some things that even took you back and you're like, 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 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 conjured up memories from the dot com years, this idea that.

Venture capitalists are so scared of missing out

on the moment, the FOMO. We could have gotten early into X, but we missed this multi-billion dollar opportunity. So they're throwing money at these half-baked ideas. I mean, Ilya Setskiver, the co-founder of OpenAI, who famously initiated the coup back in 2023, he left OpenAI for obvious reasons. So he's founded what was 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, oh, two top

Google machine learning specialist teaming up with someone at Meta who left, another machine learner. And they create a company, they write a memo and they raise $10 million on $100 million valuation. I think two things, that's insane. And the other thing is, I sort of get it. These are really promising people. We have no idea. We want to get in on the hot deal. We might lose our $3 million we put in towards the 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 is so I was covering Silicon Valley through the New York Times in the mid 2000s. And there's this new company, the Facebook dot com.

And Excel, Jim Breyer, famous venture capitalist, put in, I think he put in $12 million with a $100 million valuation up and down Sand Hill Road, all through Silicon Valley. They're all mocking Breyer. What a fool for this college-only app. He's putting in all this money, $100 million. Like,

That 12 million became like, if you kept it going public, it was like 4 billion, something like that. And if you held it, it'd be worth tens and tens of billions of dollars. And that's the venture capital game. Most bets

I mean, they either show nothing or they show barely any return. But it's a game where that one big hit can make up for everything. And that's venture capital in Silicon Valley. We're just going to slap down bets and just hope that one or two of them are huge. So you asked 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 are talking about, 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 boomerang 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. But kind of this whole idea of personal agents, 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 some for that. I blame Hollywood, you know, for, you know, the Terminator like movies, like, Oh, the robots are going to take over. That's not my, 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 globe.

global economic system before a human even understands what's happening. A deadly pathogen, you know, at AI for good, it could create, you know, vaccines and cures. There's also one that could create a deadly pathogen. So I think it's inevitable that something bad is going to happen. And I really fear that's going to turn the general public off to AI. So I wish those working on frontier models would be a little bit more aware

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 ChatGP2 went out,

went out there, you know, the competition cashing in became a priority and trust and 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 the years or maybe, you know, it was front and center previously 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 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 you've picked up through this experience of reporting, you know, in Silicon Valley that maybe the rest of us haven't picked up on yet?

So what really scares me, so I approached this book 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 meta. And what I discovered after all my reporting is 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 the start of 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 one billion dollars.

But if Anthropic, as Dario Amode said, they're going to need, he figures, $100 billion 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 expensive that either they're going to have to sell so much of their company that they don't really own the company. 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 they're going to be in charge of AI. There's the trust issue. AI had really bad timing. It came out, I mean, AI has been around for decades, but generative AI coming out at the end of 2022, trust in big tech was at pretty much an all-time low. Facebook, Amazon, Google, people really aren't trusting those companies. And yet I do think AI is going to be in the hands of Google,

Microsoft, maybe in OpenAI. And I'll point out, by the way, OpenAI founded in 2015 was a counter to Google. Rather than start as a nonprofit, famously, they're trying to rid themselves of their nonprofit parent. But it started as kind of this

idealistic thing, rather than 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 OpenAI is as profit-driven as Google or any other company out there. So even if an OpenAI 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 you know, he's, he's, we've seen all the folks who have left open AI. I mean, the anthropic team before, you know, and before chat GPT came out, but you know, many people since then, you know, keep on saying the same message that safety is taking a backseat 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 these things. But there's also, like any technology, there's goods and there's bads. And I really...

I 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, they've been using generative AI, they're 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 and a great way to wrap up today's show. So Gary, 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 was great. Thanks. All right. There's a lot there, y'all, and there's going to be a lot more. If you missed something that Gary talked about, or if you want to dig in more, that's where it's going to happen in our newsletter. So if you haven't already, please go to youreverydayai.com, sign up for the

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