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Dispelling the Hyperbole: The AI Bubble that Isn’t
In the tech world today, there is speculation about the existence of an 'AI bubble' that mirrors the dotcom bubble of the late 90s, and the imminent burst that comes with it. Businesses need to separate fact from fear, interpreting the trends that point to the lack of such a bubble.
Market Swings & The S&P Index
Perceptive understanding is pivotal. The S&P 500 index's 5% loss and subsequent recovery signify only the normal ebb and flow of the market. Overreacting to market swings based on these slight adjustments is ill advised.
Generative AI: The Bedrock of the US Economy
The economy shines when generative AI companies lead the way. The example of the US, where top behemoths like Microsoft, Nvidia, Apple, Amazon, Google, and Meta are all heavily invested in AI, illustrate this well.
Job Cuts & Generative AI
The shift in the economy towards AI isn't a sign of an impending bubble-burst but instead a marker of its dominance – especially when tech giants like Intel and Dell cut jobs to deepen their focus on AI.
Big Tech Versus Start-ups
The struggle and failure of AI start-ups, while big companies integrate new features, is less a sign of an imminent bubble and more an indication of these larger conglomerates tightening their grip on the market.
Generative AI: The Future of Work
Generative AI is predicted to undergo regulation, not eradication, due to its prominence in the current economy. Regardless of their size, companies are encouraged to implement generative AI and take advantage of existing solutions. A prime example is Microsoft 365 Copilot's significant time-saving feature that converts data into presentations.
AI's Ubiquity
AI is now an integral part of labour, not merely an optional add-on. This widespread adoption, with AI being part of various software and platforms, illustrates that the perceived AI bubble does not exist.
Money Matters: Implementing Generative AI
The need for a clear monetization plan is crucial in demonstrating the immediate time savings offered by generative AI. To reap the maximum benefit, companies must possibly reorganize their resources to areas that drive more revenue.
Investing in Generative AI: A Cautious Approach
However, many companies that venture into investing in generative AI either fail to educate their workforce appropriately or adopt a slow deployment approach, leading to minimal ROI. The solution is to unlearn and redefine traditional working habits in this AI-driven economy.
In conclusion: The AI Bubble Misnomer
Lastly, one must keep in mind that the acquisitions of AI startups are not indicative of an AI bubble. Instead, they point towards AI being the future of work – a reality that requires seismic shifts in thought and implementation for optimal returns on investment. As it turns out, the speculated AI bubble is far from bursting – it simply doesn't exist in the first place.
Topics Covered in This Episode
1. Introduction to the AI bubble talk
2. 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
Podcast Transcript
Jordan Wilson [00:00:17]:
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 gonna last. It's not gonna keep going. It's gonna burst. It's too big. It's going to fail. Wrong.
Jordan Wilson [00:00:41]:
All wrong. Alright? 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. Alright. I'm excited for today's show, but what's going on y'all?
Jordan Wilson [00:01:07]:
My name's Jordan Wilson.
Jordan Wilson [00:01:08]:
I'm the host of Everyday AI, and this show is for you. It is your daily livestream 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 livestream 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 everydayai.com, as well as see related episodes and, you know, most importantly, you gotta read the newsletter every single day. So, you you know, keeping up with the podcast 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 Chatt GBT or Claude or Gemini on us.
Jordan Wilson [00:02:08]:
So make sure to go check that out. Alright. 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 Gemini 1.5 Flash now supports more than a 100 languages, broadening its usability and appeal to a global audience.
Jordan Wilson [00:03:08]:
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 applications. 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.
Jordan Wilson [00:03:37]:
Next, Chinese company, Wuhai, is set to compete with NVIDIA in the AI chip market amidst US sanctions. Pretty sure that's how it's pronounced. Right? Wuhai. So Wuhai, is set to launch the new Ascend 910 c, 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 Wuhai is set to compete. So US sanctions have prevented NVIDIA from selling its advanced, chips to Chinese customers. So the new, 9 10 c chip is currently being tested and is said to match the performance of NVIDIA's h 100. Also major Chinese firms like ByteDance and Baidu are reportedly interested in the chips, and expected orders have already exceeded 70,000 units or totaling around $2,000,000,000 in new revenue.
Jordan Wilson [00:04:33]:
Wuhai 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. Alright. Last but not least. Yes. Chat GPT has updated its GPT 4 o 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 OpenAI has rolled out a new and improved g p t four o model on its chat GPT 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.
Jordan Wilson [00:05:17]:
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 g p t four o model is now available on chat g p t for both free and premium users. Though free users as normal face a messaging cap. So it's not gonna 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 multistep reasoning functions.
Jordan Wilson [00:05:53]:
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. Alright. That's a lot of AI news. So let's go ahead and jump into, this this concept of
Jordan Wilson [00:06:20]:
the AI bubble. You know, and I'm curious.
Jordan Wilson [00:06:23]:
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, livestream audience, what do you think? Is there a an actual AI bubble right now? Is it gonna pop? Right? Is is 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 livestream audience what you think. So, you know, Fred tuning in and and Denny tuning in. Thank you all. Raul, Brian, would love to hear. Tara, Brian, Michael, everyone, Cecilia, thank you for tuning in.
Jordan Wilson [00:06:59]:
And, hey, it is Hot Take Tuesday. You know, sometimes Tuesday, we we 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 we burn? Alright. 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.
Jordan Wilson [00:07:32]:
It gets people talking. Right? Any anytime there's controversy or, you know, when people are talking about this concept of a bubble. Right? We think of the the dotcom bubble of the, you know, early 2000 or, you know, late 90, I guess, 99 to 2000. And, you you
Jordan Wilson [00:07:48]:
know, the, kind of the economic turmoil
Jordan Wilson [00:07:53]:
that can happen from when one certain industry gets a little too big too quickly. And the economy maybe and 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 you know, and here I'm talking about in the US at least, but that impacts every aspect of our lives. Alright? So, hey, Josh Josh Cavalier, former guest, said, he wants Old man Wilson coming in. So, we might have to get people off our AI lawn.
Jordan Wilson [00:08:39]:
Alright. Let's do it. So let's I
Jordan Wilson [00:08:40]:
mean, let's talk about this. Let's talk about this.
Jordan Wilson [00:08:44]:
So there's there's this dominated the the the news cycle for, like, 3 or 4 days. Right? This is all you saw, all these stories here. I'm I'm sharing them, you know, for our livestream or 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 stack stock analyst is waiting for AI bubble to burst. Futurism article, the AI bubble is bursting, experts say, guess what, experts? You're all wrong.
Jordan Wilson [00:09:16]:
All of you. This is this is comical.
Jordan Wilson [00:09:20]:
This is something Gartner hype cycle, wrong. These AI experts, wrong. Guess what else all the, you you you know, 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. Economy the US economy is gonna tank. 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 Q4 here of 2024. So we can talk about the results and how every single expert
Jordan Wilson [00:10:04]:
was disastrously wrong. Disastrously wrong. And I started Everyday AI, you
Jordan Wilson [00:10:12]:
know, about in the Q2 of 2023, and I I said then. I said, no. They're all wrong. And 2023 was a great economic year here in the US, and so far, 2024 has been as well. However, these headlines spread like wildfire like wildfire. Okay? Because here's here's what's happening. And, you you know, I'm gonna be sharing about this here as we go over kind of these, 6 common misconceptions or, 6 trains of thoughts that I want to address that the, quote, unquote, experts are completely wrong about. Alright? And and and one of them has to do with just how lopsided the economy is right now on the top end with generative AI companies.
Jordan Wilson [00:10:55]:
This hasn't happened before. And like always y'all, you know I'm bringing receipts. Alright? On Hot Take Tuesdays, yeah, I come in with opinions and, you know, normally I I spout off and, you know, come in with some some hot takes, and tell 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 1,000, 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 smart literally the smartest people in the world and bringing on great guests for you all to to speak with, and the experts are wrong.
Jordan Wilson [00:11:35]:
I'm sorry. Alright. Let's let's start diving in. Alright. So let's go over six reasons why there is no AI bubble and therefore why it cannot burst. Alright. So here's what every everyone is is wrong about. So so first and foremost, it's looking at these momentary $1,000,000,000,000 losses in market swings.
Jordan Wilson [00:12:02]:
Alright? 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. And the I mean, part of it. Right? And I'm I'm a former journalist.
Jordan Wilson [00:12:26]:
I know how news cycles work. Right? One big journalist, you know, tries to hop on the trend early. They write a 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, then everyone's writing about it. Right? It's like, oh, how could you not foresee this? You know? And everyone 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 it's easy, but it's lazy work.
Jordan Wilson [00:13:05]:
Y'all are lazy. Seriously.
Jordan Wilson [00:13:09]:
You can't look at a momentary swing and then try to run this, 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 here's what caused the chaos, y'all. Alright? So podcast audience, I have a, I'm talking about the S and P here.
Jordan Wilson [00:13:33]:
So, you know, one of the major indexes here in the US, we have we have the Nasdaq, we have the Dow, we have the S and P. I talk about the S and P 500 a lot. It's it's probably at least when I'm talking about the economy, I'd like to talk about the S and P. Right? You pick your index and stick with it. We talk about the S and P here on everyday AI. So this is what set everyone off. Right? So, about I I I have the past month trend here. Alright? And, oh, a 5% loss.
Jordan Wilson [00:14:02]:
Right? A 5% loss over the last month. Everyone's losing their noodles. Right? Because there was a huge there was a huge 2 day slide about 10 days ago. And what happened is we had multiple days of $1,000,000,000,000 losses. Right? The US economy lost 1,000,000,000,000 s trillions with an s of dollars, and everyone, like I said, everyone was in a frenzy.
Jordan Wilson [00:14:32]:
Alright? But perspective is important. Alright? Because guess what? Obviously, in
Jordan Wilson [00:14:40]:
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 and 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 you know, aside from if you're in a recession, but for the most part, you're looking at 4 to 8%. 4 to 8% gains. Right? We've been spoiled as of, you you know, 2021. We've seen huge gains year over year.
Jordan Wilson [00:15:26]:
Perspective is important. Alright? So, yeah, I'm talking
Jordan Wilson [00:15:31]:
to you journalists. I'm talking to you social media influencer that sees these headlines and and writes in an an ill informed post. Y'all are looking dumb. Stop. Alright? Use perspective. Don't freak out. It's so important to
Jordan Wilson [00:15:49]:
be educated. We have especially with AI, we have all the tools to be educated, yet people see these these headlines and they lose their noodles. They start selling off their 401 k. Oh, my gosh. The AI bubble's gonna burst. The economy's gonna tank. No.
Jordan Wilson [00:16:04]:
No. Be patient. Be patient and use perspective. Alright? Actually, before we move on to that, before we move on,
Jordan Wilson [00:16:16]:
I I wanna talk about, there's always going to be big losses. We're going to go through, and, you you know, I'm not a financial adviser, blah blah blah. Disclaimer. Disclaimer. Go talk to your financial adviser. Whatever. Right? Because the US economy is so top end heavy, we are going to see those kind of swings. Right? And go back, check the archives.
Jordan Wilson [00:16:39]:
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 4, there's gonna be some tumultuous times, at least here in the US economy. Alright? 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.
Jordan Wilson [00:17:24]:
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 gonna be talking about this in one of the later points and they're wondering where are our returns. Alright. More on that here in a second. Let's go to number 2. So here's number 2, and this is something that thing that people are getting wrong. Alright? When they say, oh, the AI bubble is going to burst.
Jordan Wilson [00:17:53]:
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 start ups. It's not a bunch of small and and medium sized players. Alright? We are talking about these you know, we talk about magnificent 7 a lot. I don't like I'm gonna rename it. I'm gonna rename this 6 because I don't think Tesla should be included in this if I'm being honest. I think Tesla's, stock is is a little too volatile because of its, you know, because Elon Musk sometimes, you know, making some some wild moves.
Jordan Wilson [00:18:47]:
So if if we just look at the magnificent seven minus Tesla. Right? So right now, these are the 6 the 6 largest companies in the world. Or sorry, not in the world. The 6 largest in the US. Alright?
Jordan Wilson [00:19:04]:
It's Microsoft, Nvidia, Apple, Amazon, Google, Meta. Those are the 6 largest companies in the US by market cap. These are the 6 most valuable companies.
Jordan Wilson [00:19:22]:
Did you catch anything in common there? Guess what? They're all 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
Jordan Wilson [00:20:13]:
years. K? Yeah. We got receipts, y'all. Let's look
Jordan Wilson [00:20:16]:
at the dotcom era. Right? Let's look at the the the last, you know, so this is 24 years ago, about a quarter century ago, and that's what everyone's comparing AI to right now. Okay?
Jordan Wilson [00:20:28]:
What were what was that bubble comprised of? It was smaller companies.
Jordan Wilson [00:20:36]:
Right? Companies that would be considered start ups. Some familiar names. Amazon. Right? Amazon's on the list twice. Right? But these are the companies that were creating this new .com. Right? Back in the very late nineties, it was like, you know, company and the economy was was printing money. Alright? But look at the companies that made up this dotcombubble. Amazon at the time.
Jordan Wilson [00:21:02]:
So we're we're talking late 99, early 2000. Okay? These companies creating this economic boom were all babies. Alright? These were the main companies. Amazon was only 5 years old. Ebay was only 5 years old. Yahoo was only 6 years old. Geocities, oh, Geocities, was only 6 years old. AltaVista was only 6 years old.
Jordan Wilson [00:21:27]:
The list goes on and on. All of these companies, they essentially started in the mid nineties. The the economy took off, and everyone's like, oh my gosh. Dotcom.com.com. And then the bubble burst in
Jordan Wilson [00:21:39]:
992,000. Why? Well, I
Jordan Wilson [00:21:42]:
mean, there's a lot of reasons why this would take a 4 hour podcast, to to uncover what happened in the dotcom era, but, essentially, it's it's this. The companies were too young. Right? Some of them obviously made it out. You know? Amazon is is one of the largest companies in the world today. EBay still still around kicking the rest on the list, not so much, or 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 6 largest companies in the US. At the time, the companies that created the dotcom bubble, I mean, they might sound like household names, but they weren't. None of them.
Jordan Wilson [00:22:33]:
None of them were a top ten US 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 those articles, none of those analysts drew those conclusions. Why? Well, it's not 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.
Jordan Wilson [00:23:26]:
Bookmark it. Let's go to number 3, number 3 here. Alright. Hey, livestream audience. What do you guys think? Yeah. Fred Fred said there was some big, dotcom losers when the bubble burst. Absolutely. Zane saying exactly all these companies are not newbies, and they've been around for 20 to 25 years.
Jordan Wilson [00:23:45]:
Yeah. And they hold massive, 1,000,000,000,000, yeah, 1,000,000,000,000 of dollars, in in market cap, but 100 of 1,000,000,000 of dollars in revenue. Absolutely. Michael, don't worry. We're gonna be getting to the GPT rappers here in a second. Alright? So let's talk about number 3. You know, this is another thing that everyone has wrong. Or you know what? Sorry.
Jordan Wilson [00:24:09]:
No. Let's rewind. Sorry. I wanted to point something out. Yeah. We did research. Alright? So right now, the generative AI wave, and I talked about, there has been no time in history where the top 5 companies have been essentially competing in the same sector, in the same space. Alright.
Jordan Wilson [00:24:30]:
So as an example,
Jordan Wilson [00:24:31]:
yeah, I went back 30 plus years, checked the top 5 market cap companies. Alright? There's always been a diversity of companies.
Jordan Wilson [00:24:44]:
Right? So let's look at 2010. Alright? Let's let's hit rewind. Number 1, ExxonMobil. Number 2, Apple. Number 3, Microsoft. Number 4, Berkshire Hathaway. Number 5, Walmart Stores. Right? Diversity there at the top.
Jordan Wilson [00:24:59]:
Right? You have 1 oil. You have 2 tech. You have 1 investment holdings, and then you have, Walmart, you you know, merchandise retail. Alright?
Jordan Wilson [00:25:09]:
Let's look at 1990. Yeah.
Jordan Wilson [00:25:12]:
I checked I checked every I think I checked every 5 years for the last 50 years. Alright. 1990, GE, General Electric, General Electric, 2, Exxon, 3, IBM. 4, Coca Cola. 5, 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 is playing in generative AI. That just proves it's a bubble.
Jordan Wilson [00:25:44]:
No. It doesn't. No. It doesn't. This has literally never happened. It's literally never happened. It's never happened that the top 5 or 6 most valuable companies in the US have all been investing and have been singularly focused on the same thing. That is not sign, sign of a bubble that is about to burst.
Jordan Wilson [00:26:06]:
That is a sign of mature companies. Like I said, none of these companies are start ups. None of them rose to prominence over the last 3 years. These are the largest companies. They've all been publicly traded for decades. Right? At least, you you know, 15 to 25 years. None of these companies are new. And there's a reason why they've all shifted strategies.
Jordan Wilson [00:26:29]:
Right? Meta is a great example. Meta was, you know, oh, social media, then their web web 2, then their, you know, web 3, whatever, then their metaverse, AR, VR. Guess what? Now they're all in on large language models. Everything that Meta's 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 ecom retailer in the US. Right? And one of the largest in the world.
Jordan Wilson [00:27:14]:
There's a reason why they're investing. Right? They're investing 1,000,000,000 of their own dollars into companies like Anthropic. They're investing 1,000,000,000 of their own resources, into cloud infrastructure for generative AI into their own models. Every single big company regardless these companies, right, regardless 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. Alright. Let's keep going. Sorry.
Jordan Wilson [00:27:43]:
Number 3. Another thing people are getting wrong. Everyone's saying, well, AI investments aren't showing significant returns. Okay. Yeah. Right? Especially I 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
Jordan Wilson [00:28:09]:
next week. It's not how
Jordan Wilson [00:28:11]:
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 is a technical implementation,
Jordan Wilson [00:28:31]:
hurdle to climb. It's a change management. It's a philosophical hurdle to climb. If you want
Jordan Wilson [00:28:38]:
to get a return on investment on generative AI, number 1, 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 gonna integrate large language models in your company? Right? So many companies, they just say, well, you know, we're gonna build on, you know, we're gonna build on this API, and then we're gonna, you know, we're gonna, you know, do some rag, bring in our own data with Retrievalog Meta Generation. We're gonna fine tune a model, and we're gonna give it to all our employees. Great. Yo. I I I I am not kidding. There's so many large multinational, multibillion dollar companies right now in the US that take that approach.
Jordan Wilson [00:29:21]:
And guess what they don't do? They don't educate their employees. They don't train them. Right? That's another, it's it's a catch 22 of 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 of work that are, like, a year long and you can't take traditional, deployments with generative AI. It has to be fast. Okay? You have to start small, start easy, start fast, and measure something right away.
Jordan Wilson [00:30:00]:
Don't take a a 3 quarter long approach. You're gonna fail. But so many companies, all they do is they try to, you know, bring in their own data, build on top of a model, give their employees access, and then they look at they look at their their 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.
Jordan Wilson [00:30:31]:
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 4 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, can't wait to grow. Here we go ROI. Here we go revenue. Here we go profit. No.
Jordan Wilson [00:31:09]:
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 under 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 2 decades in a large language model in an AI first world.
Jordan Wilson [00:31:54]:
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 who prove our point. You have to unlearn successful habits. Right? What made you
Jordan Wilson [00:32:07]:
successful? That knowledge in your brain, that domain expertise, is it still important? Yes. Is it as important as
Jordan Wilson [00:32:18]:
it was? Absolutely not. Now you need to know how to use that knowledge, that domain expertise, that that 1, 2, 3 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, you know, 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't just drop a seat on the carpet and say, grow, baby. Grow.
Jordan Wilson [00:32:48]:
You have to rethink, reimagine, restructure how you work. Number 4. I'd love this one. Right? And this is go read any of the articles. These are essentially the the 5 or 6 points that all of these articles, all of these people posting are are are making. Right? I read them all, and, you know, we're debunking them 1 by 1. So number 4, everyone's saying, well, AI spending is too high without clear monetization. Right? Alright.
Jordan Wilson [00:33:22]:
I'm taking a deep breath here. Trying to think how how mean how mean I should be. I mean, y'all wanted the the hot takes. Right? So alright. 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.
Jordan Wilson [00:33:52]:
Right? Companies, instead of taking advantage of what generated AI solutions they have under their nose 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 a Fortune 100 company. 18 months ago, if you're trying to essentially build your own model, that was dumb. But you still have companies doing it when you don't need to.
Jordan Wilson [00:34:38]:
You really don't need to. But here's where companies should start. Right? If you're a company with, you 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 Copilot.
Jordan Wilson [00:35:13]:
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 1 enter key. $30 a month. You can literally save multiple hours in 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.
Jordan Wilson [00:35:39]:
I gotta 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, 4th 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 gonna get a pretty decent first output from Microsoft 365 Copilot within a minute. And that process, doing it, quote, unquote, old school, what you hang your hat on, would maybe take a day or 2. Right? And you have a working version, you have a pretty decent version in a minute or 2. Right? So if you are if you think AI is spending too high without clear monetization, you don't understand that time is money.
Jordan Wilson [00:36:43]:
Right? People are automatically thinking, oh, if I spend $20 on this, we're gonna 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 as simple yet powerful as Microsoft 365 Copilot 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.
Jordan Wilson [00:37:18]:
And, you know, literally, you know, we had some comments. We were doing a a live training for, you know, pretty big multinational, multi $1,000,000,000 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 1 is time savings.
Jordan Wilson [00:37:40]:
So if you don't have a clear monetization path I mean, this is there's this is a much, much larger and much longer conversation, but it's 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, 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.
Jordan Wilson [00:38:40]:
Right? We've talked about it literally over a 100 of episodes. I just gave you a very easy example. Right? You're in a Microsoft Excel spreadsheet with, 100 of 1000 of of lines or or cells of 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 Cobalt 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 a $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.
Jordan Wilson [00:39:17]:
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, reskilling them, and putting them into a a different, department that's driving more revenue, or you need to be putting them, in an air in a new line 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 pre generative AI, or you need to start taking half of your people and reskilling them, upskilling them, and putting them in other departments. There you go.
Jordan Wilson [00:40:06]:
I know it's easier said than none, but solve your monetization problem, Sherlock. Number 5. Everyone's saying AI might just be an overhyped tech bubble. Dead wrong.
Jordan Wilson [00:40:21]:
Dead wrong. AI isn't a feature. Alright? It's how we work. You could even make an argument. Right? Oh, the.comtechbubbleorthe.combubble.
Jordan Wilson [00:40:34]:
Look what happened. It popped.
Jordan Wilson [00:40:36]:
I mean, did it? Sure. Maybe some of the stocks popped,
Jordan Wilson [00:40:41]:
but that's how we work. Guess what? You are going to a dotcom, right, or a desktop app version of a dotcom for everything you do. Right? Technically, your email is a dotcom. Right? Maybe your, shared documents that you're collaborate, collaborating on, dotcom. Your CRM is a dotcom. Right? Your outreach for sales, dotcom. The programs you're using for marketing, dotcom. How you're growing your business with different advertising platforms.com.
Jordan Wilson [00:41:16]:
You know? Business isn't a phone book and a telephone anymore. It is a dotcom. So was the you you know, was there a dotcom burst? Yes. There was. But guess what? Still how we work.
Jordan Wilson [00:41:28]:
The same is with generative AI. Alright?
Jordan Wilson [00:41:33]:
It's how it's how we're going to work. I've been saying this since day 1. This Gartner is wrong. There is no hype cycle. AI isn't hype. You can't plan it on a on a curve and say, oh, well, here we are at the trough of dissolution, man. No. This is how we're gonna work.
Jordan Wilson [00:41:51]:
Bookmark it. Right? Whether it's in it's in 3 months, 3 years, doesn't matter. If you're not already using generative AI like you're using a dotcom, you will be soon, because guess what? All the dotcoms are moving to generative AI. Right? Oh, you're like, oh, I spend all my time in Sales Force. Sales Force will never be generative AI. Yes. It is. Look at their Einstein platform.
Jordan Wilson [00:42:16]:
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
Jordan Wilson [00:42:30]:
think AI is a bubble, no. It's not. And just wait till we get these more capable models, autonomous agents. Just wait. Generative AI is everywhere. It's not
Jordan Wilson [00:42:40]:
a bubble. Last but not least y'all and, hey, if you do have any, any questions or comments, get them in now. I'll see if I'll see if there's any questions to answer. Alright? Cecilia's spot on saying it's all about the allocation of resources. Absa fruit and lutely. Alright? Doctor Harvey Castro back back in it. Good to see you. Alright.
Jordan Wilson [00:43:03]:
Number 6, AI startups. Getting gobbled up doesn't mean the bubble's bursting. Alright. Yeah. Here's another thing. All these articles. All these articles. Right? Oh, AI bubble's gonna burst.
Jordan Wilson [00:43:17]:
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 gonna 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 I'll try to, you know, put this show in the show notes as well. Had a receipt filled episode talking about how most AI startups are going to die.
Jordan Wilson [00:43:58]:
And guess what? That's played out. There's been probably tens of thousands of, quote, unquote, AI startups, little guys that have just died. Because guess what? Large language models, your your your Gemini, your Claude, your ChatGPT, your, you know, Amazon q shirt. Right? Whatever you wanna throw in there. Your your your copilot, from Microsoft. Right? All of these big tech behemoths are essentially just integrating new features and new functionalities. Right? So it's not that when these, you know, probably 100 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.
Jordan Wilson [00:44:47]:
I've been screaming it for years. Well, a year at least. Right? That AI startups are going to die, number 1. Number 2, that means nothing. That means nothing. All that means is as an example. Right? An easy example. In November when, ChatGPT introduced the ability to upload PDFs in a chat.
Jordan Wilson [00:45:08]:
Right? All of a sudden, you've literally had 100 of small little companies, that became irrelevant. Right? Because all these small little companies, they were essentially like, hey. You you know, chat with your PDF. Right? There's literally 100 100 of them. You know? Some were just small little projects. Some were doing 7 figures in revenue. Right? At least according to reports. And most of them are gone now.
Jordan Wilson [00:45:35]:
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 a 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 chat 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.
Jordan Wilson [00:46:11]:
But so many of these, I mean, they're just moteless, AI startups. They're they're essentially rappers 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, that's you're gonna you're you're gonna die. Right? Or at least you're gonna lose the majority of of of your revenue. Right? Because people are gonna say, oh, why am I paying, you know, $10 a month or a $100 a year for this when, hey, our our Microsoft copilot does this now or, you know, Claude does this now or whatever. Right? So just because you see all of these startups go out of business, and a lot of these startups that raised, you know, tens of 1,000,000 of dollars 2 years ago are laying off their staff. That does not mean the AI bubble is bursting.
Jordan Wilson [00:47:09]:
That actually means the AI bubble is just big tech getting more powerful. Right? There's a reason why the top 6 companies in the US right now, according to MarketCap, are all in on generative AI. They figured it out. Right? Hey. Another thing another thing on that note. Right? And we'll we'll 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.
Jordan Wilson [00:47:39]:
76% in 2023 I'm talking about 2023 because that's the last complete year we've had. In 2023, 76%
Jordan Wilson [00:47:49]:
of the S and P's gains were from the magnificent seven. Okay?
Jordan Wilson [00:47:56]:
That's wild. That's wild. Before that, the you you know, you could look at any year, and I believe it was more like 30%. Was the biggest year before that that any 7 single stocks in the S and 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 US economy. That's why we're not gonna have any meaningful legislation because most smart people understand, that generative AI is far too important for the US economy to ever legislate it. It will be regulated. It will not be legislated.
Jordan Wilson [00:48:40]:
Okay? And when you have the 6 largest companies in the US, all going all in on AI over the last 5 years, they've reprioritized their entire business models. We're talking $1,000,000,000,000 companies
Jordan Wilson [00:48:56]:
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. Alright, y'all. That's it. Sorry to bring the truth.
Jordan Wilson [00:49:15]:
Right? So if you think the AI industry or generative AI is a bubble that's gonna 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.
Jordan Wilson [00:49:36]:
Alright. If this is helpful y'all, let me know. Please repost this, if if 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. We'd appreciate that. Make sure you go refer a friend. Go to your everyday ai.com. Also, sign up for that free daily newsletter.
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