Everyday AI Podcast – An AI and ChatGPT Podcast - EP 335: No, there's no AI bubble so it won't be bursting. Dispelling all the AI bubble talk

Episode Date: August 13, 2024

There's a time-saving, eye-boggling AI gem under your nose. Similar to custom GPTs from ChatGPT, Claude Projects can save you a ton of time. But what are they? And how can your company save time using them? Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on ClaudeRelated Episodes:Ep 206: There is No AI Hype – This is how the world works nowUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:1. Introduction to the AI bubble talk2. The AI Bubble Discussion 3. Economic Impact of AI 4. Impact on AI Startups and Big Tech Dominance 5. Generative AI and its Significance 6. Reorganization and Revenue Generation in AI-Investing Companies 7. Misperceptions and Missteps in AI integration Timestamps:00:00 Daily livestream podcast and newsletter for AI enthusiasts.03:37 Wuhai to rival NVIDIA in AI chip.07:53 Rapid industry growth can lead to instability.10:55 Assertive host makes confident, researched opinions weekly.14:40 Stock market recovers half lost, historical gains.17:53 AI bubble dominated by larger players, excluding Tesla.21:42 Dotcom bubble era companies were too young.22:33 Startup hype vs established company facts: logic wins.28:38 Invest in generative AI for successful returns.31:09 Triple down on training for change management.35:39 Automate data to presentation with Microsoft 365.37:40 Clear monetization path crucial for company success.40:41 Transitioning to digital platforms for business operations.46:11 AI startups face obsolescence with new models.50:02 Refer 4 friends for daily AI insights.Keywords:Jordan Wilson, AI bubble, Everyday AI show, Free Daily Newsletter, Google's Gemini model, Wuhai, NVIDIA, AI chip market, Chat GPT's GPT 4.0, dotcom bubble, generative AI companies, S and P 500 index, market swings, social media influencers, big tech companies, Intel, Dell, Microsoft, Nvidia, Apple, Amazon, Google, Meta, AI startups, generative AI, Microsoft 365 Copilot, regulation, monetization plan, large language models, ROI on AI investment.EP 335: No, there's no AI bubble so it won't be bursting. Dispelling all the AI bubble talkSend 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. If you've been paying attention in the media or on your social news feeds,

you probably think that this AI bubble is bursting. That's all you've been hearing over the last couple of weeks is, hey, this AI bubble, it's not going to last. It's not going to keep going. It's going to burst. It's too big. It's going to fail. Wrong.

All wrong. All right. So on today's show, we're going to be dispelling all of these myths that we've been seeing in the media, in studies, and on social media on everyone saying that there is an AI bubble and it's going to pop because guess what? It's not going to pop because there is no AI bubble. This is how the world works now. All right. I'm excited for today's show. But what's going on, y'all? My name's Jordan Wilson.

I'm the host of Everyday AI. And this show is for you. It is your daily live stream podcast and free daily newsletter helping us all understand AI so we can leverage it to grow our companies and to grow our careers. So if that sounds like you, then you are definitely in the right place. If you're new here, make sure if you're listening on the live stream or if you're listening on the podcast, make sure to check out our show notes. There's always more information where you can sign up for our free daily newsletter at your everyday AI.com, as well as the related episodes. And most importantly, you got to read the newsletter every single day. So, you know, keeping up with the podcasts or the live stream is one thing.

But the newsletter is how you actually put it into practice. So make sure that you go sign up for the newsletter. And also check out our thanks a million giveaway. Go refer some friends to our newsletter and be entered into a drawing for your favorite large language model of choice, a year of chat, GBT, or Claude or Gemini on us. So make sure to go check that out. All right, before we get into today's show, which I'm excited about, let's first talk about what's happening in the AI news. So, first, Google has announced some major updates to its Gemini model and some price reductions for 1.5 flash.

So Google's AI has unveiled some significant updates and cost reductions for its Gemini 1.5 flash model aimed at making advanced AI tools more accessible and efficient for developers. So Google has slashed the pricing for Gemini 1.5 Flash by more than 70%, making it more affordable for developers to utilize this powerful tool. Also, the new text tuning feature allows for improved performance in niche tasks, enabling more precise and effective use of the model. So Gemini 1.5 Flash now supports more than 100 languages, broadening its usability and appeal to a global audience. Also, Google AI Studio access has been streamlined for Google workspace accounts, simplifying the integration process for users. I'm excited about that one. We'll check that out.

Also, developers can now fine-tune the base models with their own data, huge, enhancing performance for specific tasks and application. So again, that is just on the Google AI studio side. So not for front-end Google users or Gemini users, but regardless, pretty big news from Google. Next, Chinese company Wu-Wai is set to compete with Nvidia in the AI chip market amidst U.S. sanctions. Pretty sure that's how it's pronounced, right? Wu-I. So, Wu-I is set to launch the new Ascend 910C, a new chip aimed at rivaling NVIDIA's H-100.

So yes, NVIDIA has pretty much dominated the world in creating these GPU chips for generative AI. but Wu-Wai is set to compete. So U.S. sanctions have prevented Nvidia from selling its advanced chips to Chinese customers. So the new 910C chip is currently being tested and is said to match the performance of Nvidia's H-100. Also, major Chinese firms like BightDance and Bidu are reportedly interested in the chips and expected orders have already exceeded 70,000 units or totaling around $2 billion in new revenue. Wuai aims to start shipping the AI chip by October. And this move could reshift the AI landscape in China,

offering an alternative to Nvidia's more limited options. All right, last but not least, yes, chat GPT has updated. It's GPT4O model. If you checked our newsletter yesterday, you were some of the first to know about that because we sent it out just minutes after the announcement. So Open AI has rolled out a new and improved. GPT4O model on its chat GPD platform, sparking discussions about performance and capabilities. So OpenAI announced the updates on its Twitter account, but we still have not seen any official word aside from them saying,

yo, it's new. Go check it out. It's updated. So we don't have any details yet if it's the same name, anything like that. So the new and improved GPT4O model is now available on chat GPT for both free and premium users, though free users as normal face a messaging cap. It's not going to look like a new model, but it is essentially has been changed under the hood. Users have noticed stark improvements, particularly in conversational nuances and programming tasks.

Some users have also noticed improved and more natural and human-like behavior and new multi-step reasoning functions. That's huge. Additionally, there are rumors swirling everywhere that there could either be a more formal announcement from OpenAI today, either about this new model or additional updates such as the rumored strawberry project. So, you know, check out our newsletter for that. Presumably it could be coming this morning. All right, that's a lot of AI news. So let's go ahead and jump into this concept of the AI bubble.

You know, and I'm curious. You know, if you are listening on the podcast, I always put in my, you know, email, LinkedIn, information. Reach out to me. I love hearing from you. But hey, live stream audience, what do you think? Is there an actual AI bubble right now? Is it going to pop, right?

Is this generative AI movement? Has it gotten too big, too quickly? Is it bound to fail or is it too big to fail? Would love to hear from our live stream audience what you think. So, you know, Fred tuning in and Denny tuning in. Thank you all. Raul, Brian, would love to hear Tara, Brian, Michael, everyone, Cecilia. Thank you for tuning in.

And hey, it is Hot Take Tuesday. You know, sometimes Tuesday, we'd like to spice it up a little bit. You know, a lot of times we're, you know, either doing interviews or talking about the news. So we bring a little opinions on Tuesday. So let me know, should we make this, should we be nice? Should we bring the heat or should be burned? All right, because I actually have strong opinions about this, right? And I think part of it is because these narratives on an AI bubble, right?

it gets clicks, right? It gets clicks. It gets people talking, right? Anytime there's controversy or, you know, when people are talking about this concept of a bubble, right? We think of the, the dot-com bubble of the, you know, early 2000s or, you know, late 90, I guess, 99 to 2000. And, you know, the kind of the economic turmoil that can happen from when one certain industry gets

a little too big too quickly. And the economy maybe in the economic growth maybe becomes a little bit too reliant on one certain sector. And it can get too big, right? And it can burst. And that can obviously have both short and long term adverse effects for not just the economy, but for a business. Right. And when that happens, you know, and here I'm talking about in the U.S. at least, but that impacts every aspect of our lives. All right. So, hey, Josh Cavalier, former guests, said he wants old man Wilson coming in. So we might have to get people off our AI lawn.

All right, let's do it. So let's, I mean, let's talk about this. Let's talk about this. So there's, this dominated the new cycle for like three or four days, right? This is all you saw, all these stories here. I'm sharing them, you know, for our, live stream or sorry for our podcast audience. I'm sharing them on the screen here. So, you know, Forbes article is the AI bubble about to burst. Bloomberg, Goldman's top stock

analysts is waiting for AI bubble to burst. Futurism article, the AI bubble is bursting. Experts say, uh, guess what experts? You're all wrong. All of you. This is, this is comical. This is something Gardner hype cycle wrong. These AI experts wrong. Guess what else all the experts and all the analysts said. They said in 2023, every single, go back and look at the end of 2022. The predictions for 2023, every single person, every single analyst, recession, recession, the U.S. economy is going to take. There was not a single reputable analyst that said in 2023, and I'm only talking about

2023 because that is the, you know, the last complete calendar year for businesses, right? We're, you know, nearing the fourth quarter here of 2024. So we can talk about the results and how every single expert was disastrously wrong. 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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See it today at firefly.adobie.com. Disasterously wrong. And I started every day AI. you know, about in the second quarter of 2023. And I said then, I said, no, they're all wrong. And 2023 was a great economic year here in the U.S. And so far, 2024 has been as well. However, these headlines spread like wildfire, like wild fire.

Okay. Because here's what's happening. And, you know, I'm going to be sharing about this here as we go over kind of these six common misconceptions or six trains of thoughts that I want to address, that the quote unquote experts are completely wrong about. And one of them has to do with just how lopsided the economy is right now on the top end with generative AI companies. This hasn't happened before.

And like always, y'all, you know I'm bringing receipts, all right? On hot take Tuesdays, yeah, I come in with opinions. And normally I spout off and, you know, come in with some hot takes and tell a bunch of smart people, people that are probably smarter than me. I tell them they're wrong. But guess what? Hey, on hot takes on hot take Tuesdays, I'm not saying I'm batting a thousand,

but I'm batting better than everyone else, right? I come with receipts. I come with research and, you know, I come with logic. And, you know, I've been lucky enough here at everyday AI to talk with the smartest, literally the smartest people in the world and bringing on great guests for you all to speak with.

And the experts are wrong. I'm sorry. All right. Let's start diving in. All right. So let's go over six reasons why there is no AI bubble and therefore why it cannot burst. All right. So here's what every everyone is wrong about.

So, so first and foremost, it's looking at these momentary trillion dollar losses in market swings, all right? Because that's what started. That's what started this, this wave. And it was everywhere for a couple of days. right, it was dominating. You know, you turn on the news at night. It was on the news. When you go to your social feed, this is what everyone was talking about.

It dominated the conversation. I mean, part of it, right, and I'm a former journalist. I know how news cycles work, right? One big journalist, you know, tries to hop on a trend early. They write a scathing article. Everyone else follows suit, right? The newsroom editors say, hey, did you see this by Forbes? Why didn't we have this?

Right. And then that goes to all the TV stations, the radio stations, the online publications, and everyone's writing about it, right? It's like, oh, how could you not foresee this? You know, and everyone wants to be a futurist, right? Everyone wants to be a, you know, a thought leader and try to identify trends. And, you know, so it's easy, but it's lazy work. Y'all are lazy.

Seriously. You can't look at a momentary swing and then try to run this, this narrative and push this narrative that, oh, AI is actually in a bubble and it's going to burst. No, it's not. No, it's not. Let's look. Here's what caused the chaos, y'all. All right.

So podcast audience, I have a, I'm talking about the S&P here. So, you know, one of the major indexes here in the U.S., we have the NASDA, we have the NASDA, We have the Dow, we have the S&P. I talk about the S&P 500 a lot. It's probably at least when I'm talking about the economy. I'd like to talk about the S&P, right? You pick your index and stick with it. We talk about the S&P here on everyday AI.

So this is what set everyone off, right? So about I have the past month trend here. All right. And oh, a 5% loss, right? A 5% loss over the last month. Everyone's losing. their noodles, right? Because there was a huge, there was a huge two-day slide about 10 days ago. And what happened is we had multiple days of trillion dollar losses, right?

The U.S. economy lost trillions s, trillions with an S of dollars. And everyone, like I said, everyone was in a frenzy. All right. But perspective is important. All right. Because guess what? Obviously in the last week, we've already gained back about half of what was lost. Okay. And then put it in perspective, y'all. Put it in perspective over the past year. The S&P is up 20%, right? Which when you look historically over the last 50 years, very rarely does a major index go up by 20% in a year, right? Generally, it's. It's normal to go up, you know, any, you know, aside from if you're in a recession, but for the most part, you're looking at four to eight percent, four to eight percent gains,

right? We've been spoiled as of, you know, 2021. We've seen huge gains year over year. Perspective is important. All right. So, yeah, I'm talking to you journalists. I'm talking to you social media influencer that sees these headlines and in rights in, an ill-informed post.

Y'all are looking dumb. Stop. All right? Use perspective. Don't freak out. It's so important to be educated. We have, especially with AI, we have all the tools to be educated. Yet people see these headlines and they lose their noodles.

They start selling off their 401K. Oh my gosh. The AI bubble's going to burst. The economy's going to tank. No. No, be patient. Be patient. and use perspective.

All right. Actually, before we move on to that, before we move on, I want to talk about there's always going to be big losses. We're going to go through, you know, I'm not a financial advisor, blah, blah, blah, disclaimer, disclaimer, go talk to your financial advisor, whatever, right? Because the U.S. economy is so top and heavy, we are going to see those kind of swings, right? And go back, check the archives. You know, what's a great resource to learn AI, your everyday AI.com.

We have like 330 some episodes, but guess what? We also have hundreds of hours of receipts. I've been saying for forever that in quarter four, there's going to be some tumultuous times, at least here in the U.S. economy, all right? I think that because all the big tech companies in 2024 so far have been cutting jobs, and they're seeing good returns from that, right? I talked about it on this show yesterday. Intel cut 15,000 jobs. Dell cut 12,000 jobs to focus on AI, right, in the past week. So you're seeing big tech companies and you have for 2024, cutting tens of thousands of jobs and their stock is responding accordingly. It goes up, right? Unfortunately, that's what I think is going to be happening a lot in 2024. Companies are going, you know, companies have been investing into generative AI. And we're going to be talking about this. And one of the. later points, and they're wondering where are our returns?

All right? More on that here in a second. Let's go to number two. So here's number two, and this is something that people are getting wrong, all right? When they say, oh, the AI bubble is going to burst, right? Historically, when bubbles burst, it is smaller companies. Okay? In previous tech innovations, it was always a bunch of new players or medium-sized

players that created said bubble. Guess what's happening right now in AI, in this quote unquote AI bubble, in this AI movement. It's not a bunch of startups. It's not a bunch of small and medium sized players. All right. We are talking about these, you know, we talk about Magnificent Seven a lot. I don't like, I'm going to rename it. I'm going to rename the six because I don't think Tesla should be included in this.

if I'm being honest. I think Tesla's stock is a little too volatile because of it's, you know, because of Elon Musk sometimes, you know, making some wild moves. So if we just look at the magnificent seven minus Tesla, right? So right now, these are the six, the six largest companies in the world, or sorry, not in the world, the six largest in the U.S. All right. It's Microsoft.

Nvidia, Apple, Amazon, Google, meta. Those are the six largest companies in the U.S. by market cap. These are the six most valuable companies. Did you catch anything in common there? Guess what? They're all in on AI. All of them. All of them have shifted their business focus to AI.

Guess what else? is a common trend among all these big companies that are creating what these analysts are saying is this AI bubble is getting too big, right? Guess what? None of them are newbies. Almost all of these companies have been around and fairly dominant for 15, 20, 25 years. Right? Meta, Microsoft, Google, Amazon, and Nvidia, Apple, right?

For the most part, they've all been household names. for 15, 20, 25 years. Okay? Yeah, we got receipts, y'all. Let's look at the dot-com era, right? Let's look at the last, you know, so this was 24 years ago, about a quarter century ago, and that's what everyone's comparing AI to right now. Okay?

What was that bubble comprised of? It was smaller companies, right? Companies that would be considered startups. some familiar names. Amazon, right? Amazon's on the list twice, right? But these are the companies that were creating this new dot com, right? Back in the very late 90s, it was like, you know, company and the economy was printing money. All right, but look at the companies that made up this dot com bubble. Amazon at the time. So we're talking late 99, early 2000s, okay? These companies creating this economic boom were all babies.

All right. These were the main companies. Amazon was only five years old. eBay was only five years old. Yahoo was only six years old. GeoCities. Oh, GeoCities was only six years old. Alta Vista was only six years old.

The list goes on and on. All of these companies, they essentially started in the mid-90s. The economy took off and everyone's like, oh my gosh. Dot com.com. dot com. And then the bubble burst in 99, 2000. Why? Well, I mean, there's a lot of reasons why.

This would take a four-hour podcast to uncover what happened in the dot-com era. But essentially, it's this. The companies were too young, right? Some of them obviously made it out. You know, Amazon is one of the largest companies in the world today. eBay still around kicking. The rest on the list, not so much. at least, you know, they're not prominent anymore.

But do you see the difference right now, this new boom, this generative AI wave is being driven by the six largest companies in the U.S. At the time, the companies that created the dot-com bubble, I mean, they might sound like household names, but they weren't. None of them, none of them were a top 10 U.S. company. There's a difference. when hype and speculation and dollars are going into a bunch of small, medium-sized startups versus ones that are now going into companies that have been

driving forces in the economy for decades. Huge difference. Oh, what's that? None of those articles, none of those analysts drew those conclusions. Why? Well, it's not sexy when you use logic, right? It doesn't make for a good headline when you use logic, when you use facts, when you use trends, when you use statistics. That's what we do here at everyday AI.

That's why, hey, when we come in with a hot take, we're normally not wrong or not book market. Let's go to number three here. All right. Hey, live stream audience. What do you guys think? Yeah. Fred, Fred said there was some big, uh, dot com losers when the bubble bursts. Absolutely.

Zane saying exactly all these companies are not newbies and they've been around for 20 to 25 years. Yeah. And they hold massive, uh, trillions. Yeah, trillions of dollars, uh, in, in market cap, but hundreds of billions of dollars in revenue. Absolutely. Michael, don't worry.

We're going to be getting to the GPT rappers here in a second. All right. So let's talk about number three. You know, this is another thing that. Everyone has wrong. Or you know what? Sorry, no. Let's rewind.

Sorry. I wanted to point something out. Yeah, we did research. All right. So right now, the generative AI wave. And I talked about there has been no time in history where the top five companies have been essentially competing in the same sector, in the same space. All right.

So as an example, yeah, I went back 30 plus years, checked the top five. market cap companies, all right? There's always been a diversity of companies, right? So let's look at 2010. All right, let's hit rewind. Number one, ExxonMobil. Number two, Apple. Number three, Microsoft.

Number four, Berkshire Hathaway. Number five, Walmart stores, right? Diversity there at the top, right? You have one oil, you have two tech, you have one investment holdings, and then you have Walmart, you know, merchandise retail. All right. Let's look at 1990. Yeah, I checked, I checked every, I think I checked every five years for the last 50 years.

All right. 1990. GE, General Electric. General Electric. Two, Exxon. Three, IBM. Four, Coca-Cola. Five, Philip Morris.

So, you might think that. I'm making the opposite point, right? Like, oh, Jordan, it looks like every single large company is playing in generative AI. That just proves it's a bubble. No, it doesn't. No, it doesn't. This is literally never happened. It's literally never happened.

It's never happened that the top five or six most valuable companies in the U.S. have all been investing and have been singularly focused on the same thing. That is not sign of a bubble that is about. to burst, that is a sign of mature companies. Like I said, none of these companies are startups. None of them rose to prominence over the last three years. These are the largest companies. They've all been publicly traded for decades, right?

At least, you know, 15 to 25 years. None of these companies are new. And there's a reason why they've all shifted strategies, right? Meta's a great example. Meta was, you know, oh, social media. then their web, web two, then they're, you know, web three, whatever, then they're Metaverse, AR, VR, guess what? Now they're all in on large language models.

Everything that Matt is doing is focused on AI. Because the smartest, largest companies in the world that are mature and that are driving economic growth, they understand that generative AI, large language models, AI, that is the future of work. there's a reason why all of these companies, Amazon's another great example, largest e-com retailer in the U.S., right, and one of the largest in the world. There's a reason why they're investing, right? They're investing billions of their own dollars into companies like Anthropic. They're investing billions of their own resources into cloud infrastructure for generative AI into their own models.

Every single big company, regardless these companies, right, regardless of. of what they were doing 10 years ago, they all have a generative AI focus because they understand it is not a bubble. It is the future of work. All right. Let's keep going. Sorry. Number three. Another thing people are getting wrong. Everyone's saying, well, AI investments aren't showing significant returns. Okay, yeah. Right? Especially, I mean, the largest companies in the world are seeing significant returns, but the rest of the world isn't. Guess why? You can't plant a tree last week and expect it to grow next week. It's not how it works, okay?

Generative AI large language models require a seismic shift in thinking. Proper AI implementation and to get a return on investment. I'm not lying, y'all. People think generative AI is a technical implementation hurdle to climb. it's a change management. It's a philosophical hurdle to climb. If you want to get a return on investment on generative AI, number one, you have to actually invest in it, which so few companies are doing.

Let me call you out all companies. You don't just say, oh, what's your, what's your AI go to market or what's your large language model go to market? How are you going to integrate large language models into your company? Right. So many companies, they just say, oh, well, you know, we're going to build on, you know, we're going to build on this API. and then we're going to, you know, we're going to, you know, do some rag, bring in our own data with

retrieval long meta generation. We're going to fine to find a model. And we're going to give it to all our employees. Great. Yo, I, I am not kidding. There's so many large multinational, multi-billion dollar companies right now in the U.S. that take that approach. And guess what they don't do?

They don't educate their employees. They don't train them, right? That's another. it's a catch 22 of generative AI. It moves so quickly and is so powerful. By the time companies, and companies are doing it wrong too, right? Like, they're doing like scopes of work that are like a year long. And you can't take traditional deployments with generative AI.

It has to be fast. You have to start small, start easy, start fast and measure something right away. Don't take a three quarter long approach. You're going to fail. But so many companies, all they do is they try to bring in their own data, build on top of a model, give their employees access. And then they look at their bottom line, right? They look at their profit. They look at their revenue.

Right. It's literally like dropping a seed on the carpet and then just like rubbing your hands together and being like, I can't wait till this grows into a tree. No, y'all are wrong. You have to continually invest in your people, train your people, keep up with AI advancements. Because y'all, as we see, there's literally new large models every single week. For the last four weeks, we've seen a new model every single week, a new major player releasing something every single week. So you can't just drop this large language model seed and say, I can't wait to grow.

Here we go R.O.I. Here we go revenue. Here we go profit. No, you have to triple down on training. And it is change management. I'm sorry. You have to untrain employees of working the old way that has made them successful. That's why you're not seeing return on investments because you're not training your employees.

you are not giving them a place to practice. You are not bringing in experts to help all these employees understand this seismic shift that is going on between like or beneath our very eyes. You can't work. You can't have the same work tendencies that you've had for two decades in a large language model in an AI first world. It's not how it works. We talk about this all the time on the everyday AI show when we bring on great experts who prove our point.

You have to unlearn successful habits, right? What made you successful? That knowledge in your brain, that domain expertise. Is it still important? Yes. Is it as important as it was? Absolutely not. Now you need to know how to use that knowledge, that domain expertise, that one,

two, three decades of experience that you have in your brain, now it's all about can you leverage that to get the most out of a model. It's not about you recalling that information or your department, having those old school strategies. You have to redefine how you work. That's why you're not getting a return on investment. You can just drop a seat on the carpet and say, grow, baby, grow. You have to rethink, reimagine, restructure how you work. Number four. I love this one, right? And this is go read any of the articles. These are essentially the five or six points that all of these articles, all of these people posting are making, right?

I read them all and, you know, we're debunking them one by one. So number four, everyone's saying, well, AI spending is too high without clear monetization, right? All right. I'm taking a deep breath here. I'm trying to think how mean, how mean I should be. I mean, y'all wanted the hot takes, right? So, all right, AI spending is too high without clear monetization. Guess what?

You're not spending your money in the right way. I think so many companies, their first foray into large language models are the wrong first step, the wrong first step, right? Companies, instead of taking advantage of what generated AI solutions they have under their knows or, you know, essentially out of the box models that are already primed for how they can work. Instead of doing that, I think companies are instead trying to build their own solutions, which don't get me wrong. It's gotten much easier.

It's gotten much more affordable than it was, you know, 18 months ago, right? Because 18 months ago, I said, if you're trying to build on top of a, you know, a large language model 18 months ago, I'm like, that's dumb. Unless you're like one of the largest companies in the world, unless you're, Fortune 100 company. 18 months ago, if you were trying to essentially build your own model, that was dumb. But you still have companies doing it when you don't need to. You really don't need to.

But here's where companies should start, right? If you're a company with, you know, 50 employees, 500 employees, whatever it may be. And if you still haven't implemented generative AI, don't think you need to build your own model or fine-tune a model to get started. That's wrong. That's where people are spending without a clear monetization path. They're spending too much money. Instead, start where you work.

Are you a Microsoft organization? If so, go all in on Microsoft co-pilot. Microsoft 365 copilot. Guess what? It's not a super spendy thing. $30 a month per user. You gain that back the first time someone uses copilot. You gain that back with one interkey.

$30 a month? you can literally save multiple hours in one prompt, right? One prompt, as an example, in Microsoft 365 copilot, right? When you're looking at a spreadsheet and you're like, oh, man, I got to turn this spreadsheet into a PowerPoint and I have to do a bunch of research, right? Normally, that's a very manual, laborious process, right? But if you have Microsoft 365 copilot and you have all your data connected and you have all of the access and all of the features, it's as simple as a prompt, right?

go through this Excel sheet, grab our, you know, fourth quarter trends, do some research on these websites, and turn it into a 12-page PowerPoint going over A, B, and C. Right. And you're going to get a pretty decent first output from Microsoft 365 copilot within a minute. In that process, doing it quote unquote old school, what you hang your hat on, maybe take a day or two, right? And you have a working version, you have a pretty decent version in a minute or two, right? So if you are, if you think AI is spending too high without clear monetization, you don't understand that time is money, right?

People are automatically thinking, oh, if I spend $20 on this, we're going to get this much revenue, not necessarily. one of the most easy to realize goals or benefits of generative AI is time savings, right? So like I said, this is change management and people management. When companies implement something as simple yet powerful as Microsoft 365 co-pilot or chat GPT for enterprise, right? This is something we help companies with, right? We go in there, companies pay us and we say, hey, this is how you should be working. And, you know, literally, you know, we had some comments.

We were doing a live training for, you know, pretty big multinational, multi-billion-dollar company. And the comments in the chat were, this is mind-boggling. This changes how we work. This is going to save us so many hours. It is hard to count. That's what people were literally saying, right? Number one is time savings. So if you don't have a clear monetization path, I mean, this is a much, much larger and much longer conversation.

But that's why, unfortunately, a lot of companies are cutting, jobs because they've realized these time savings. So you have to have a clear path to monetization. And oftentimes, you have to look for either new lines of revenue, new lanes of revenue, or you might look at reorganizing the organization, right? Maybe there's areas of your business that you are going to have 60% staff savings, time savings. You need to shift those people to somewhere where,

maybe you can't get those big of gains out of generative AI into maybe more revenue driving areas of your business that you have room for growth. That's the problem. It's a change management people management problem. If you don't understand the immediate time savings of generative AI, I can't do anything for you, right? We've talked about it literally over hundreds of episodes. I just gave you a very easy example, right?

You're in a Microsoft Excel spreadsheet with hundreds of thousands of lines or cells of data and you need to do some additional research and then you need to create a PowerPoint presentation, right? You can literally do that with a prompt and it's done for you. Microsoft 365 co-pilot will create it for you. Very, right, very simple, right? If you don't understand that you're paying that person, whatever, let's just say $100,000 a year and you just gave them on that one task.

Maybe that's a task that they do over and over. Maybe you just save them 70 to 80% of time. Guess what? You then need to have you then revenue driver at company X. You then need to have a monetization plan for how you capture and implement that time savings. What are you doing with that new time savings, right? You either need to be shifting people, upskilling them, re-skilling them, and putting them into a different department that's driving more revenue. or you need to be putting them in a new lane or new line of business.

That's the thing people don't realize. In theory, you should be saving so much time. So either, sorry employees, this is just the reality, right? You should either be doing double the work that you were pregenerative AI, or you need to start taking half of your people and rescaling them, upskilling them, and putting them in other departments. There you go. I know it's easier said than none, but solved your monetization problem,

Sherlock. Number five. Everyone's saying AI might just be an overhyped tech bubble. Dead wrong. Dead wrong. AI isn't a feature. All right. It's how we work.

You could even make an argument, right? Oh, the dot com tech bubble or the dot com bubble. Look what happened. It popped. I mean, did it? Sure, maybe some of the stock. popped. But that's how we work. Guess what? You are going to a dot com, right? Or a desktop app version of a dot com for everything you do, right? Technically, your email is a dot com, right? Maybe your shared

documents that you're collaborating on.com. Your CRM is a dot com, right? Your outreach for sales.com. the programs you're using for marketing.com, how you're growing your business with different advertising platforms.com, you know, business isn't a phone book and a telephone anymore. It is a dot com. So was there a dot com burst? Yes, there was, but guess what? Still how we work. The same is with generative AI.

All right. It's how we're going to work. I've been saying this since day one. This gardener is wrong. There is no hype cycle. AI isn't hype. You can't plan it on a curve and say, oh, well, here we are at the trough of disillusionment. No, this is how we're going to work.

Book market, right? Whether it's in three months, three years, doesn't matter. If you're not already using generative AI like you're using a dot com, you will be soon. Because guess what? All the dot coms are moving to generative AI. right. Oh, you're like, oh, I spend all my time in Salesforce. Salesforce will never be generative AI. Yes, it is. Look at their Einstein platform, right? Every single place where you work, every single piece of software that you use, every single CRM, ERP, SaaS, blah, blah, blah, alphabet soup. It's all going generative AI. So if you think AI is a bubble, no, it's not. And just wait until we get these more capable models, autonomous agents.

just wait. Generally of AI is everywhere. It's not a bubble. Last but not least, y'all. And hey, if you do have any questions or comments, get them in now. I'll see if. I'll say if there's any questions to answer. All right. Cecilia's spot on saying it's all about the allocation of resources. Apps of fruit and looting. All right. Dr. Harvey Castro, back in it. Good to see it. All right. Number six, AI startups, getting gobbled up. doesn't mean the bubbles bursting. All right. Yeah, here's another thing.

All these articles, all these articles, right? Oh, AI bubbles going to burst. Good job reporter that didn't do any work and that doesn't know how AI works. You know, all these articles, everyone's saying, oh, AI is going to burst. Look at these, you know, look at these, look at these AI startups. So many of them are going out of business. They're cash strapped. Right.

Guess what? it's just big tech gobbling up the market share. You know, a good example. And I had back in October, back in October of last year, you know, so I'll try to, you know, put this show in the show notes as well. I had a receipt filled episode talking about how most AI startups are going to die. And guess what? That's played out.

There's been probably tens of thousands of quote unquote AI startups, little guy. that have just died. Because guess what? Large language models, your Gemini, your Claude, your chat GPT, your,

you know, Amazon Q, sure, right, whatever you want to throw in there, your co-pilot from Microsoft, right?

All of these big tech bohemists are essentially just integrating new features and new functionalities. Right. So it's not that when these, you know, probably hundreds and thousands of AI startups are dying. That's not a sign of a bubble bursting. That's a sign of you ignoring the writing on the wall. I've been screaming it for years, well, a year at least, right? That AI startups are going

to die. Number one. Number two, that means nothing. That means nothing. All that means is as an example, Right. An easy example in November when chat GPT introduced the ability to upload PDFs in a chat, right? All of a sudden, you've literally had hundreds of small little companies that became irrelevant, right? Because all these small little companies, they were essentially like, hey, you know, chat with your PDF, right? There's literally hundreds, hundreds of them. You know, some were just small little projects. some were doing seven figures in revenue, right, at least according to reports. And most of them are gone now.

Doesn't mean the AI bubble bursted. It means those AI startups were thin, right? We talk about GPT wrappers, right? Which is essentially, you know, in a couple of hours, you can literally create an actual SaaS, an actual software as a service where you essentially just grab a feature by using the API. So you can grab a feature from the GPT, you know, from the GPT. model, you can grab a feature from Claude and, you know, wrap a nice little interface around it and say,

oh, and start charging people. Oh, $10 a month for this, you know, this AI that does this for this, right? And there's great use cases for that. But so many of these, I mean, they're just moteless AI startups. They're essentially wrappers that, hey, as soon as any of these large language models integrates this new feature, it makes these 10 companies, these 50 companies, these 500 companies, essentially obsolete because if that is all your little company was doing, if you are just a chat with your PDF company, you're going to die, right? Or at least you're going to lose the majority of your revenue, right? Because people are going to say, oh, why am I paying, you know, $10 a month or $100 a year for this when, hey, our Microsoft co-pilot does this now or, you know,

Claude does this now or whatever, right? So just because you see, see all of these startups go out of business and a lot of these startups that raised, you know, tens of millions of dollars two years ago are laying off their staff. That does not mean the AI bubble is bursting. That actually means the AI bubble is just big tech getting more powerful, right? There's a reason why the top six companies in the U.S. right now, according to Market Cap, are all in on generative AI. They figured it out, right?

Hey, another thing, another thing on that note, right? And we'll end it here. Going back to 2023, right? Oh, you think we're in a, you think we're in an AI bubble? No. 76 percent. In 2023, I'm talking about 2023 because that's the last complete year we've had. In 2023, 76 percent of the S&P's gains were from the magnificent seven.

Okay? That's wild. That's wild. Before that, the, you know, you could look at any year, and I believe it was more like 30% was the biggest year before that, that any seven single stocks in the S&P, the largest before that was 30%, 30% of the gains, right? What that tells me is right now, generative AI, and I've said this so many times, generative AI is powering the, U.S. economy. That's why we're not going to have any meaningful legislation because most smart people understand that generative AI is far too important for the U.S. economy to ever legislate it. It will be regulated. It will not be legislated. Okay. And when you have the six largest companies

in the U.S. all going all in on AI over the last five years, they've reprioritized their entire business models. We're talking trillion-dollar companies. on AI. Not because it's a bubble, because it's the future of work. Stop believing all that nonsense. There is no bubble. It won't be bursting. All right, y'all. That's it. Sorry to bring the truth. Right. So if you think the AI industry or generative AI is a bubble that's going to burst, now you know, now you know the facts. Now you have the receipts. Stop believing the nonsense that you read that, you know, some random reporter spent an hour on. They have no clue.

I do this every day. There's no AI bubble. It's not bursting. If this is helpful, y'all, let me know. Please repost this. If you're listening here on LinkedIn or Twitter or YouTube, whatever it is, repost this, share this with your friend, tag someone who needs to hear this. If you're listening on the podcast, please leave us a rating on Spotify or Apple.

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