Everyday AI Podcast – An AI and ChatGPT Podcast - EP 206: There is No AI Hype - This is how the world works now

Episode Date: February 13, 2024

Can we stop talking about the "AI hype?" We're two years past the AI wave and AI is more prevalent than ever. There is no more AI hype. AI is just a part of the way we work now. Here's why.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode pageJoin the discussion: Ask Jordan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTimestamps:03:15 Daily AI news08:42 Generative AI's accessibility drives recent rapid growth.10:49 Gartner hype cycle tracks technology evolution.14:48 Comparison of technological innovation over three decades.19:40 Tech giants invest billions in generative AI.20:34 Apple invests billions in AI development and acquisitions.26:57 Generative AI revolutionizes technology, compared to historical innovations.29:01 Language models making groundbreaking scientific discoveries.31:56 New technology offers high potential for writers.37:41 AI enables career growth.Topics Covered in This Episode:1. Comparisons between Generative AI and the Internet era2. The importance of understanding and keeping up with AI3. The shift in powerful industries4. The Current Economy's AI Focus5. Generative AI Hype CycleKeywords:Generative AI, Artificial Intelligence, AI development, Gartner hype cycle, Peak of inflated expectations, dot-com era, economic impact of AI, Jordan Wilson, AI misconceptions, AI skepticism, AI in business, big tech investment in AI, US tech companies, cloud computing, Microsoft, Google, Meta, NVIDIA, business process transformation, AGI, AI engineering, autonomous systems, paradigm shift, industrial revolution, AI knowledge and expertise, AI iteration, Everyday AI podcast, AI threatening jobs, language model improvement, GTC conferenceSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

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. Can we stop talking about the hype around artificial intelligence?

Can we stop that now? Are we past that point? Here we are two plus years into the generative AI wave. And guess what? The waves are still crashing. All right. We're going to talk about that today and more on everyday AI. Welcome and thank you for joining us.

My name's Jordan Wilson and everyday AI is for you. So this is a daily live stream podcast and free daily newsletter, helping everyday people like me, like you, not just learn generative AI, but how we can all actually leverage it to grow our companies and to grow our careers. That's what it's all about, right? You can read about it, you can think about it, you can talk about it, but until you use it to grow your company and grow your career,

generative AI is not working. So we're going to talk today a little bit about that there is no hype around AI. And I'm going to talk to you a little bit about what that means in so many countless conversations that I've had. And that this is just how we work now, all right? Gen. AI is how we work. All right?

So if you're joining us live, thank you as always. If you're joining us on the podcast, make sure to check out your show. show notes. So look in the episode description. We always have additional information related episodes, links. You can email us. You can connect with me on LinkedIn. Make sure to do that. And as a reminder, this is the live show. People don't know. Yeah, this isn't edited. You know, we don't have a team of six people that waits three weeks to put out an episode. We go live at 7.30 a.m. Central Standard Time here in Chicago. And the podcast goes out like two minutes after. This is the realest thing in artificial intelligence. All right. Hey, Megan, thank you for

joining us, our live streamed audience. I love it. Jay, thank you, Dr. Harvey Castro. Hey, Juan, joining us from Chicago. All right. We're holding it down for Chicago. Rolando, joining us from South Florida, Brian from Minnesota, Daniel from Buffalo. Thank you all for joining us, but I want to hear from you as well. What do you think? Is AI all hype? Is there substance? Is this just how we work now? I want to hear from you all. All right. As a reminder, please go to Your EverydayAI.com. Sign up for the free daily newsletter. We're going to be Recapping Today Show, and we do it for literally every single show. I tell people, it is like a free generative AI university on our website.

You can go in, and we've had probably now more than 140 guests over 200 plus shows. So you can go read old newsletters with so much information, or maybe if you care about, you know, sales, or if you care about marketing, or if you care about entrepreneurship, whatever it is, we have all of those categorized on our websites. You can just go learn from the experts about anything in the world of generative AI all for free at your everyday AI.com. All right. So let's talk real quick about the AI news for today, February 13th. All right.

So AI is threatening white-collar jobs according to a recent report in the Wall Street Journal. So the article in the Wall Street Journal shows that it's not just blue-collar jobs at risk to AI in automation. So this new report details how companies like UPS, Duolingo, Google and Google and Netflix, others have laid off the white-collar workers in parts due to AI. And so while the direct impact of generative AI on job loss is currently low, the trend is growing. And we've been talking about that since day one here. All right, our next piece of news. Well, how do you make AI better? More agents, right? I think of the skit from Will Ferrell, more Caldell. All right. So a recent study by Tennyson researchers found that language model performance can be improved by adding multiple agents

without the need for complex prompted designs or collaboration frameworks. So researchers here looked at the sample in voting method, which uses multiple language model agents in majority voting. And this was proven to be effective in improving performance. So performance gains were seen when adding more agents, but there is a threshold beyond which further improvements are not seen. We're going to be hearing a lot more about agents as we talked about on the show yesterday. All right.

Our last piece of AI news for today, Invidia has leapfrogged Amazon and Google and is now the third most valuable company in the U.S. According to market cap behind only Microsoft and Apple. So Microsoft has surpassed the market value of Amazon and Google parent alphabets reaching $1.83 trillion in its market cap. as its stock has quadrupled in 15 months due to its position as a leader in AI. So, Nvidia's stock, get this over the past 10 years, has grown 17,000 percent increase in 10 years, making it the best performing stock on the S&P 500 during that time. So its strong earnings and success in the AI industry have attracted investors and analysts with further growth expected.

So like we said, Nvidia's market cap just topped out yesterday. 1.83 trillion while Alphabet sits at 1.82 and Amazon at 1.8. So it could change, you know, by the time markets open here any second. But at least yesterday, NVIDIA passed to everyone to be the third most, the third highest company. And you know what? If only someone would have told you, you know, like 10 months ago that NVIDIA is the most important company in the United States. Oh, wait, that was me, right? Yeah. Oh, yeah. I told you all how invidia was the most important company in the world 10 months ago no one believed me no one no one understood but here we are here we are today with with proof hey speaking of invidia i'll be at the

gtc uh their conference it's back in live uh in march later march in san jose california so hey let me know let me know here in the live stream if you're going to be there you're out in the san francisco san jose area or if you're going to uh if you're listening to the podcast you're going to be there let me know All right. Let's talk about this. Let's talk about the AI hype cycle and just around this concept of AI hype. All right. Let's start with first a very quick history lesson. AI is not new. Artificial intelligence has been around, has been used widely in various sectors for decades, many decades, right? We're talking about the financial sector. It's been used in fraud detection for multiple decades. when you talk about health care, you know, artificial intelligence is not new.

Let's start there, right? But we need to differentiate. We need to differentiate between what I like to call traditional artificial intelligence. So that is your, you know, your deep learning, machine learning, you know, these high entry pieces, you know, for traditional AI, right? When you need tens of thousands or hundreds of thousands of data points, you need probably a data scientist or a machine learning specialist, right? That's how artificial intelligence has worked for many decades. So again, AI is not new.

Also, generative AI is technically not new either, right? That's what we talk about here at everyday AI. We talk about generative AI. And so what's the difference? Well, I tell people, think of generative AI like three boxes stacked on top of each other, right? Right. The top box is see-through. The bottom box is see-through. And the middle box is a black box. Right. And on the top, you have your inputs, you know, and these are essentially your prompts. And they flow downward into the black box. All right. And then the black box with these simple prompts, right, these text prompts or maybe image prompts or whatever it may be, create something magical, right? It generates something that you wouldn't think possible just by simple prompts. And then the output, that third box on the bottom is the output, right?

So small, simple prompts go in the top box. The middle box is generative AI. It does a bunch of magic in there. And then it spits out on the bottom, something 10, 100 times greater than the prompt that came in. So our definition of generative AI has changed a little bit, right? As these generative AI systems become more approachable as the barrier for entry is now at about zero, right? Because let's be honest, this is why generative AI has blown up over the last year and a half. It's because traditional AI, like I said, you legit had to be a computer scientist,

right? You legit have to like play with decision trees in the sandbox as a kid, right? Artificial intelligence, you know, traditionally when we talk about the 70s, the 80s, the 90s, the early 2000s, it was sparsely used in the business community because it was hard. So now what happened in that little generative AI black box that I just talked about, the smartest people in the world have been working for more than a decade to bring artificial intelligence, to bring that deep learning, machine learning, these neural networks, and to make them applicable for our day-to-day business use cases, to make them powerful for everyday people like you and me,

to make them easy to bring down the barrier of entry to about zero. Y'all, if you can type on a computer, you don't even need to type, right? If you can hit a button on your computer and speak to it, you now have the abilities and power that 10 years ago used to take the smartest people in the world, and it's greater now, right? We can generate things with generative AI so quickly that are so powerful. All right. So now with that, we got a little history lesson on generative AI.

Let's take a look, right? Let's take a look at this. So if you're joining us on the podcast, I'm going to do my best to explain this. But so much of what we talk about around hype, just the word hype. A lot of it actually traces back to the Gartner hype cycle. Okay. Every single technology, you know, and let me put. this out there. Gardner is a great research organization, some of the smartest minds in the world.

All right. So with a lot of different technologies throughout the course of human history, especially recently, you know, they plot these different technologies and they say, hey, you know, I'm simplifying here. But they essentially say, hey, all technologies follow a certain path or a certain cycle, you know, both when they're first announced, you know, when they start to get implemented, you know, when people really start to. start to use it, and then it, you know, kind of dies off, right? So one of the most common statements that I get from people or questions is, hey, what do you think about the hype around AI?

And y'all, it's gotten to the point where I'm actually so tired of answering that question. That's why I'm like, okay, today on hot take Tuesday, which, by the way, I didn't ask you all, how hot should today show me? Throw some emojis, let me know. I'm feeling not super spicy, so we'll see. But traditionally, every single technology is, you know, kind of charted. Okay? So as we look at this, as we look at this, you have your innovation trigger.

All right. And then you have your peak of inflated expectations. And then you have your trough of disillusionment, your slope of enlightenment, and your plateau of productivity, right? So these different kind of technologies, depending on where they at, Gartner, plots them, right? And according to Gartner, we are right now at the peak of inflated expectations

or generated AI. It is at the top, the very top of that roller coaster, the very top of that curve, right? We are the peakest of the peaks. for inflated expectations. So according to the smart researchers from Gartner, according to everyone else that follows this as well, right? People actually follow this and make business decisions based on this.

I've heard of this, right? I've heard companies now say, ah, well, we're going to wait. You know, we're going to wait on this generative AI thing. We know it's at its peak. We know the hype is at its peak. People use this Gartner hype cycle terminology in day-to-day business conversations. All right. Well, because Brian went like 20 emojis here with a lot of flames, I'll say this.

This is all wrong. Literally all of it. You cannot chart generative AI on a hype cycle. wrong. You literally cannot do it. All right. But like literally, let's let's look at some other things on on the hype cycle here. All right. So I'm having to manually zoom in with with my eyes here. So we have things like knowledge graphs, edge AI, computer vision, right? So all of these related technologies, AI engineering, et cetera. So, you know, here's the thing. You cannot chart. generative AI.

All right. Let's talk about why this is wrong, and let's take a quick history lesson, shall we? So I want to look because one of the most common comparisons that we get is comparing generative AI to either computers or the Internet, right? That seems like, all right, when we look at the past, you know, three decades of technological innovation, it seems like, oh, that's an apples to apples comparison. Right? Generative AI, let's chart it or let's put it on this graph similarly to the internet. All right, so let's talk about the internet era. So in the early days of web development, large companies

had less capital to allocate towards internet focus, research, and development compared to their overall portfolios. It was an unproven space. All right. So what we're doing here is we're looking at these different eras and how the business world reflected across these different areas. All right. So in the early internet era, so we're talking 30, you know, about 30 years ago, right? Mid-90s, late 90s. 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-enobes. 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. The assistant orchestrates multi-step workflows, drawing on 60 plus pro grade tools across Adobe Creative Cloud apps, including Photoshop, Illustrator, Premiere, Lightroom Express, and more to help bring your ideas to life. You can also get started with creative skills, a growing library of

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or take over at any time. You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at firefly. Adobe.com. I would say the dot com,

you know, the dot com gold rush, You could say is very similar to what we're feeling with generative AI today. People that have, you know, been in business and have been working since those days often draw and make that comparison. They say, yeah, we've been here before. Oh, yeah, the dot com. You know, yeah, the economy went soaring. And that's what we're seeing now, right?

Our economy hits all-time high, all-time records almost, you know, like almost like every other week, right? breaking all-time records for our major indexes here in the U.S. Same thing. I think we hit an all-time high yesterday in the doubt. Or maybe it was last week. So people are making that comparison to the Internet era. However, in the Internet era, companies didn't have hundreds of billions of dollars to invest like they do now. There was no trillion dollar market cap companies.

in the dot-com area, right? It is play money now, right? These trillion-dollar tech companies have play money, which they did not have. Companies didn't have that, right? You know, back in the 90s, there was, you know, your big companies were a lot of energy companies or oil companies, right?

It wasn't tech companies. Now, you look at the most powerful companies in the world, in the U.S., all. top six. So, you know, we often talk about the magnificent seven here. But they're all, they're all tech, they're all AI, right? All of the biggest companies in the world right now, especially here in the U.S., are all AI heavy, are all AI focused. It wasn't like that 30 years ago. Another reason you can't equate today's quote unquote hype with what happened 30 years ago. and try to chart it accordingly.

That is not an apples to bananas comparison. That is not even an apple to fruit comparison. It's an apples to baseball comparison. Two different things. Let's keep going. Let's look at cloud computing. That's the next, you know, kind of the next, I'd say, comparison that a lot of people like to make, right?

So a slow transition in the early 2000s and 2010s in the 10th. Is that what we say, the tens, right? So in the mid-2000s for about a decade or so, we had the cloud era. So let's talk about how companies invested then. So their investments increased, but it followed a longer adoption curve as businesses transition from on-premise IT. And then you had major players like Amazon with AWS led the way and others cautiously observed. Okay? cautiously, you had a period where about 10 years, where you had one or two leaders in cloud

computing, such as Amazon, make heavy investments. And those heavy investments gradually made early adopters into cloud computing, some of the most profitable and some of the most valuable companies in the world. But this happened over the period of a decade or more. Right? And it was really the cloud computing era that gave us our valuable tech companies up to date. But it was a long period. It did not happen seemingly overnight. So let's look at Gen AI today. And again, how things are different. So now you have giants like Microsoft, Google, and meta that are allocating massive budgets. Nvidia as well, massive budgets with generative AI becoming central to their strategic thinking.

Billions of dollars are flowing in, dwarfing even early cloud investment levels. That's the thing. I don't think the average person, maybe even most people listening, understand what tech titans have become today. They become venture arms. It wasn't like this 15 years ago, right? You literally have all of these tech trillionaire companies, your Amazon's, your Googles, your invidias, your metas, Apple, et cetera. They are all investing billions with a beat, billions of dollars into outside generative AI companies.

So yes, they are making acquisitions to bring companies in their own house, right, or under their own room. They're investing their own money, right? Apple reportedly is investing more than a million dollars a day in development of its next generative AI product, right, which very should be announced here in June. So they are spending billions of dollars internally or on pace to spend billions of dollars internally. They're spending billions of dollars on acquisitions and they are investing billions of dollars into third party companies that at least for now, they have no thoughts of acquiring, right?

You have companies like Anthropic, right, that have raised billions of dollars for multiple outside tech titans. The business world is changing. And all of the money is flowing in generative AI. Again, do you understand what's happening here? This is not hype. This is, at least for now, in what I see as the foreseeable future, this is literally how business is now getting done.

All right. Gen AI isn't a hype cycle. It's not a phase. It's not a fad. It is now how the world works. You can't make that argument. Never in the history. Y'all, go check the facts.

You know I bring receipts. Never in the history since, you know, we've had our stock market. Has this high percentage of the U.S. economy of the U.S. capital all been invested in a single technology. Is it a big risk? Sure. Right? You can make the argument, oh, you know, one big slip up in the Gen. AI space and, you know, it impacts the entire U.S. economy. Y'all, this is also why I've been saying for a year that there won't be any meaningful

legislation here in the USA because generative AI is too important. We are not going to see any, anything like the EU AI Act, right? We might see an executive order, but we're not. going to see legislation. We are not going to see meaningful laws that get passed through both bodies of Congress and become an enforceable law. That is not going to happen. Because generative AI right now, smartest people in the room know this, but most people don't. It is not a hype. This is our economy, right? This is how business is done. All right.

So I'm going to go through here. I'm going to read a little background. All right. Now we're going back. We're going backwards now. So I want to explain the thought process behind the hype cycle that I showed you, right? Then I'm going to draw some comparisons. I'm not going to go bullet points here and disprove every single thing.

But, you know, I always like to tell both sides of the story. Former journalist in me, right? I was a journalist for, I don't know, seven years. You got to tell both sides of the story. I obviously have a strong opinion here. But I want to tell a little bit more about why and how this concept of AI hype has been born, how it's been adopted, and how I think business leaders are getting it wrong by trying to graph something like generative AI on a hype cycle. Anyways. So let's let's think and let's look at this hype cycle, right?

where we are at the peak, right? We are at the very peak of the hype cycle. According to the hype cycle, things will never, things will never get better. Guess what? That was from 2023. So guess what? Were we at the peak in 2023,

the absolute peak of inflated expectations when this gardener study came out as of July, 23, seven months ago, absolutely not. We have gone even higher, which is why I tell people, stop paying attention to this supposed hype cycle. It's wrong. All right, but let's explain it. Let's explain it. And then I'll tell you why it's wrong. All right. So generative AI, according to the, you know, Gardner study. And again, I'm not picking on Gardner here. There's been plenty of studies that have come out in the last year, too, where people have said, oh, yes, you know, Gen AI is a phase. It's at its peak, right?

But I think Gardner's is one of the, like I said, they do great work. They're one of the most respected, you know, group of researchers. And this is one of the most commonly referred to, you know, studies or points of reference. So more about the Gardner study. So it says generative AI is at its peak of expectations, transforming business processes, Critical technologies include AGI, artificial general intelligence, AI engineering, autonomic systems, and more. They said innovations fueled by generative AI impact, content creation, automation, and experiences.

Also saying advancements in generative AI are driven by technologies like AI simulation, knowledge graphs, and responsible AI. Also, Garner hype cycle showing that organizations are aggressively experimenting with generative A. I leading to significant competitive advantages. All right. So now let's talk about why that's wrong. Well, first of all, that was from July 2023.

And clearly, clearly that was not the peak. If I'm saying anything, that's not even the midway point where we were. When they said we were at the peak of hype, right? We were at the peak of those expectations, right? the peak of inflated expectations. Not a chance. All right. So generative AI is not a spot on the hype cycle.

It is a paradigm shift. We are literally on a new graph that we've never been to before. We cannot say, oh, here we are in the hype cycle. This is literally brand new territory. You cannot draw a comparison, right? One thing I like to tell people, especially when they're like, oh, we've been here before, you know, the Internet, cloud. computing computers. No. You know what? I can I can tell if I'm personally judging how

knowledgeable someone is in generative AI, what they compare it to. I'd say the smartest people who know about generative AI and are using it to grow their companies and to grow their careers are saying something like, we haven't seen anything like this since the industrial revolution. And I'm like, yep, that's fair. Right. Then you have. have Google CEOs, Sundar Puchai, saying, generative AI is more impactful than fire and electricity. Also true, right? People don't understand.

The internet, cloud computing, computers, etc. That changed how we shared intelligence. Generative AI is changing how we create intelligence. This has never happened before. What happens in that little black box of generated AI? It is, we are harnessing the history of human knowledge, human expertise, and skill sets. And we're giving it to everyone literally has never been done in the history of humankind. It has not been possible.

All right. And everything else plotted on hype cycles. has been easily quantifiable. Generative AI is not. You know, we talked about previous technologies are just how we interact with intelligence. But AI changes how we create intelligence. It is literally creating intelligence.

People don't understand that. They think, you know, oh, that's overblown, Jordan. No, it's not. No, it's not. Generative AI in large language models, people think, oh, they're just autocomplete. Kind of true, but also kind of not. You've had literally large language models make discoveries.

We've talked about it here on the show before. Literally make discoveries that humans have been working on for decades. It has solved math problems that the smartest humans in the world have failed for decades to solve. It is finding new discoveries, new DNA patterns, new medicines that hundreds or thousands of humans have spent decades trying to do. Large language models, generative AI, is creating new intelligence, creating new discoveries, creating new rules.

Do you understand that, y'all? Do you understand? Generative AI isn't a chat box, right? Generative AI isn't a little thing that makes you, you know, cool art. Generative AI is changing how we do business, right? And I think it's important for business leaders to realize this.

Because I think it's also difficult. It can be difficult as a human being, right? I'll take myself as an example. I've been getting paid to write for 20 years, right? I was a journalist. I wrote for big brands like Nike and Jordan. I've written commercial scripts. I won national writing awards.

All right. So you could say pre-gen AI. I was a subject matter expert, you know, in MARTAC and communications, right, but specifically in writing, right? And so I think business leaders have this fight against generative AI technology. They look at it as a threat because they say, you know, I had this thought, you know, originally when I was first using GPT3, the first time we used it in 2020. I had this feeling. I said, wow, this technology is taking like the best writing in the world and it can be better than me.

That's the thing. I think humans, business leaders, we used to have so much pride in being like a subject matter expert, being, you know, oh, I'm one of the smartest people in the world in subject A. I am a business leader in topic B. Guess what? Generative AI is better than you now. Period. It's a better writer than me.

I won national writing awards. Chad GPT can write circles around me. Most people don't figure out how to use generative AI correctly. They just put a copy and paste prompt in. They get something bad out. And they're like, oh, yeah, generative AI isn't good. Let's put it on a hype cycle and say it's dying. It's not how it works.

People aren't bothering to understand how to properly use Gen AI. All right. So like we talked about, it's not following a hype cycle. And this is the lowest barrier of entry with the highest upside potential of any technology ever. And it's not even close. Like what I just said, someone with zero writing skills, right? Maybe someone's always dreamed of being a good writer and they've just never been

able to. Now guess what? You can use a large language model if you're doing it correctly, right? If you're using our prime prompt polish PPP method, you can go in there and you can literally write content. That is better than 99.9% of writers. if you know what you're doing, right? Gen AI is one of the only technologies in the world.

This is important that is iterative at its core. All right? Let's talk about that. That means that literally generative AI is building itself to be better at gen. It is constantly learning from the hundreds of millions of people that are using it. That's what people don't understand. right? When you're, oh, you know, people don't understand what it means, you know, that our data goes back to these big companies. Well, that's why, as an example, you had something like AI images. Two years ago, they were laughable.

Guess what? Gen. AI is building itself to be better at generative AI. It is constantly learning to be better. Generative AI is building better versions of itself. Now, those same images that are laughable two years ago look more realistic than human photos. I'm not going to turn this into one of those one hour episodes, y'all. I wanted to keep this short because here is the short and simple truth about generative AI. We haven't seen it before. We haven't seen it before. and it is more impactful, it is more powerful than something that you can just put on a chart. All right.

So hear me out. I'm not saying ignore studies from Gartner. I'm not saying ignore hype cycles. I'm not saying that. All I'm saying is so many people are wrong when they're talking about AI. Because somewhere along the way, someone who is a, a novice or doesn't understand AI or maybe they are a skeptic. You always hear the word hype.

They say, oh, it's not going to live up to the hype. Or they say, oh, it's overhyped. AI is overhyped. Generative AI is bound to, you know, go away. You know, Chad GPT can't stick around forever or, you know, Google Gemini, you know, whatever. No. I'm telling you right now, if, leaders in your organization feel that way.

If they say, oh, we're at the height of the curve, let's wait this out. We don't need to get on board. You will get squashed, right? If you're in your career right now and you say, ah, man, my company's encouraging us to use Gen AI, these large language models, not really for me. These things are just hyped up tools. your career will stall. If you're a business owner,

trying to figure out if it's worth it for you to implement generative AI, and you say, ah, you know what, I think if we just, you know, kind of let our employees use chat GPT, kind of like the internet, that'll be good enough, right? We'll get back some productivity gains here and there.

Wrong. You have to, y'all, even when we talked about the internet, when we talked about cloud computing, we talked about decades, right? That's why we bring receipts, right? The amount of investment from big tech companies right now has, in the past two years,

has surpassed investments over the last two decades, and it is not even close. These tech companies are literally printing money, right? They can't invest the money fast enough. There has never been, this much money, this much resources, this much eyes on any technology, not even during the dot-com bubble, the dot-com boom. It is not even close.

You didn't have the seven biggest companies in the dot-com era, all investing in a single technology. This has never happened. Generative AI is unlike anything we've seen. You need to understand that AI. is not a hype. Gen AI is not on a hype cycle. If you understand that, and if you show up every day to keep practicing

and to keep learning generative AI, y'all will outsmart the future together. All right, thank you for joining us. Make sure to join us tomorrow. I'm excited about this one, y'all. This one's going to be fun. So we're going to talk about how AI will allow us all to make music we enjoy.

This is going to be a good one. have to listen into that one. So I hope today's episode was helpful, y'all. Don't believe a random dot on a chart and go to your everyday AI.com. Sign up for the free daily newsletter. We're going to be recapping today's episode and a whole lot more, keeping you up to date with what's going on in the world of AI, how you can use it to get ahead to grow your company, grow your careers. That's it, y'all. Appreciate you. We'll see you back tomorrow and every day for more everyday AI. Thanks, y'all. Meet Firefly AI assistant. Live in Adobe Firefly, the Allman One Creative AI Studio.

Just describe what you want to create in your own words and the assistant handles the rest, orchestrating multi-step workflows across Adobe Creative Cloud apps, including Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome while the assistant accelerates execution. Stand control with the ability to step in and refine at any time. See it today at firefly.adobie.com. And that's a wrap for today's edition of Everyday. A.I. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep

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