Surfing the AI Tsunami w/ Peter H. Diamandis & Salim Ismail

26:20I think it's this mismatch on purpose, really. And then there's alignment inside the organization, right? And everybody knows that where our MTP is to cure cancer, then as they're working through their day-to-day projects and evaluating and making decisions, the more decentralized the organization, the more powerful and important the MTP is because it acts, as Peter said, that North Star. How does AI, how do we need to think about, someone mentioned blockchain before, How do AI and these other emerging technologies interrelate? What's the intersection? Do they stack? Do you have to get your head around expertise in one in order to build and use them all?

27:04Does it depend on the type of company you are? How are you thinking about the intersection? Salim, should we go through the five internal and five external attributes and then we can relate them back to AI? Maggie, if that works for you. Yeah, that sounds good. Yeah. Let me make a quick point before we get into that. There's a really important premise that's the starting point of all this. Peter references as the six Ds. You digitize, then you have a deceptive phase, then you dematerialize, demonetize, dematerialize products and services into a new model. Music is a classic example that's gone through cassettes and DVDs and now it's all streaming services, right?

27:40We're going to see education, healthcare, energy all follow that path. Well, in that new world where multiple technologies are intersecting to form radical opportunity spaces, then the EXO and the attributes that we've identified give you the organizing principles for operating in a highly volatile, unbelievable upside type of world. And so that's the premise and the starting point and the rationale and the starting thesis for this. So we start with the MTP, which is the massive transformative purpose. Then we found there were five externalities that many of these companies were using that allowed them to keep a very small feature footprint and then scale very quickly using some of these.

28:18So the first one is staff on demand that Uber uses where it doesn't hire its own drivers. The second one is community and crowd. Hold on. Let's just slow it down. So staff on demand, if you have a large population of drivers or a large population of Airbnb homeowners, AI is going to help you manage that. Right. So if you are turning some portion of the eight billion people out there into your community that you're using, you have a relationship with that community, not necessarily paying them. Some of them are doing stuff for free. They're helping you market, helping you promote because they love what you're doing.

28:59Or that community may become your staff on demand. That requires massive amount of AI to manage. So that's, I'm going to plug AI back into everything as promised. So that's staff on demand. And let me ask a question here. One of the issues that comes up with AI, and let's say the intersection of, say, AI and robotics, is that it's going to result in massive job losses. It's going to be very, very deflationary, and you're going to see no more lawyers, certainly no more legal assistants. And there's a lot of fear around that. And you can imagine in the political sphere that that's also going to be a rub.

29:42Do we have to change the way we think about labor? We go nuts when we hear that conversation. We hate it. The reason is that none of the data supports it. Right? Let me give you a clear example. In the 1970s, we created the ATM machines. And there was all this hand-waving and ringing going, oh, my God, what will we do with millions of bank tellers that will be out of work? And lots of consternation and thinking, should we do this? Should we preserve the jobs, et cetera? What actually happened was that the cost of running a branch dropped by 10 times. The banks ended up creating 10 times more branches.

30:13and the number of bank tellers has not changed at all. And we see the same thing with truck drivers. The most robotic automated countries in the world are Korea, Sweden, Germany. And they also happen to be the countries with the lowest unemployment rates. So it turns out when you don't automate, you don't lose jobs. You just increase capacity and you do a ton more. So yes, we may automate legal thinking. Unfortunately, we won't get rid of the lawyers. We'll just have 10 times better contracts. There is a potential to say that a number of different categories of jobs will be eliminated because algorithms or AIs will do better.

30:50And the question is, were those jobs that individuals really wanted in the first place? Two things are going to happen. There'll be a transitory period during which those individuals are partnering with AIs. Again, an AI co-pilot in every area. And then there'll be a point in which people can really pursue what they dreamed about doing versus what job was available to them to put food on the table or get insurance for their family. We're talking about staff on demand. Yeah. What else is a component? The second one is community and crowd. So TED has done an amazing job of building its brand using community and TEDx events.

31:28XPRIZE does an amazing job of incentivizing the crowd to come and solve major problems. And obviously use AI pretty heavily there to manage interactions between community members, help to optimize value creation between community members and so on. So and managing the crowd, obviously, then also becomes a fairly intensive, labor intensive and data intensive process, which then AI can help. So that's where the second one. The third one is AI and algorithms where that's embedded deeply into it. Clearly, Uber, for example, has matching algorithms to match driver and passenger based on location, similar ratings, et cetera, et cetera.

32:06The fourth one is leveraged assets. So Airbnb leveraging and tapping to other people's bedrooms. And what they've done here is information enabled those properties so that people can choose where to stay. And again, you have a matching process with AI supporting that. The classic leveraged asset is cloud computing. In fact, that's the birthplace of NEXO is when Amazon Web Services launched because you could take computing off the balance sheet and make it a truly variable cost. And so fairly heavy use of AI and algorithms there. And the final one is engagement for all these externalities. This is gamification in center prizes, Web3 crypto economics that allow you to manage and connect with your community and your user base and optimize their interaction and optimize loyalty, run promotions within that and so on.

32:53And it's all big data. It's all AI driven. And it's it's real time. Yeah. If I want my community to have this behavior, I want them taking these courses. I want them watching these videos. How do you incentivize that? Right. So when my fraternity brothers, Michael Saylor at MicroStrategies has just built a system where they're going to use Satoshi's basically, you know, a fraction of a Bitcoin. that if you are at your meeting on time, or if you take some extra coursework at night, or if you watch the proper training materials, you get some Satoshis in your wallet. And it's engaging and rewarding.

33:37So very interesting strategies. We found along all of this research, some of the kind of the stellar companies and new models that are emerging. For example, in engagement, there's a model called Octalysis, where they've taken eight major human motivations like epic meaning and fear of missing out and scarcity and social inclusion, et cetera, and mapped 150 gaming techniques and engagement techniques to those. Easter eggs, leaderboards, progress bars. So if you want to incentivize scarcity, you do these things. If you want to increase the feeling of epic meaning in your community, you do those things.

34:09So now we can create a prescriptive engagement model for our user base, right? And so there's some amazing companies doing things in staff on demand. There's a company called MBO Partners that manages all of your contractors for your onboarding, offboarding, background checks, etc. So these services are popping up to help augment your capability in all of these attributes. So those five attributes, staff on demand, community algorithms, leveraged assets, and engagement are five externalities that many of these companies use one or more of to scale quickly. Then we found five internal mechanisms that map to the acronym IDEAS.

34:45And so the first one is interfaces. Like Uber has a very customized interface in interacting with its drivers or TED with its TEDx community members or XPRIZE with all of the contestants that are operating. And that's a very, APIs, for example, are an initial form of this type of interface. The second one is dashboards. And again, just to bring it back, your APIs are all AI-enabled APIs, right? that enable anyone in the world to utilize your product or service, right? If you want to become a platform like YouTube, where people can load their videos, get all information, generate revenue, then those interfaces and APIs, AI enabled is how you do that.

35:29Apple has a great interface interfacing with its App Store developers. So when somebody submits an idea for an app, they have an AI that actually looks through it and does an initial assessment of it to see is this something we want to authorize or not. So it's a gate to go through sort of at first to help them weed through all the ideas. When you were just talking about that, does this technology help smaller or medium-sized companies compete better? Because it used to be just large companies had this ability, right? Yeah, this is fundamental. In the future, we think the future will be, you know, Peter, do you want to talk about the asteroid analogy?

36:07because I think you tell it best. So, you know, something has happened over the last 30 years that's changed the business world, right? The speed, my mom used to say the world is speeding up. I said, mom, it's not speeding up, but technology is speeding up. And so the analogy that I love is that 65 million years ago, a 20 kilometer asteroid struck the earth and it changed the environment so rapidly that the slow lumbering dinosaurs that were not agile died, went extinct. It was the furry little mammals, our ancestors, that were agile and able to adapt rapidly that dominate the planet. Well, the asteroid that struck the Earth over the last couple of decades is exponential technologies.

36:51And they're changing the business world so rapidly that unless you have the agility to utilize these technologies, you will go extinct as a company. And it used to be that one technology was enough for you to differentiate yourself. But now it's convergence. It's two, three, or four of these coming together, right? It's AI plus sensors, plus networks, plus blockchain that's transforming things. So big companies have an existential threat because if they don't adapt very fast and learn how to adapt very fast, they'll essentially go extinct. The lifespan of a Fortune 500 company or an S &P 500 company used to be something like 70 years and now it's down to about 12 to 14 years.

37:32Seriously? Just look in the last decade, all the companies that went bankrupt, right? Toys R Us and old retailers and Blockbuster, et cetera, et cetera, all gone. And so there's the metabolism change. You know, there's a concept called Coase's Law. Ronald Coase wrote this nine-page paper in the 1930s for which he won the Nobel Prize positing that the reason you have big companies is you have transaction costs are lower inside than outside, and you can achieve economies of scale. And that was great. And we, in the book, actually declare Costa's law dead because you can now achieve economies of scale outside of big company just as easily.

38:09And your decision-making speed is much faster in a smaller organization. And therefore, big companies actually serve and have an existential threat today. So is it just going to be churn now? That's going to be the lifespan and they die and form into something else? Or will there be companies that iterate and adopt fast enough to survive? They have one path, and we talk about this in the book, which is to turn into platforms and then ecosystems. So Google and Apple and Facebook have turned into platforms. Uber is trying to turn itself into a platform for delivering health care and delivering food, etc., etc.

38:45If you can get to that, then you become a coral reef and everybody builds businesses off yours like YouTube. If you stay trying to be an operating company, you won't succeed. Amazing. That's a massive change for people to get their head around. Huge. So Peter, we're talking about all of the power in this and what you can unlock when you embrace this. What are the challenges around AI? There's a lot of challenges around AI. And there are challenges that fall into two separate things. One is challenges of implementing it. And then the second is challenges in society. If we focus on the challenges on implementing it, if you're not an AI first company, it's going to be strange and difficult.

39:38Because ultimately, you're used to using your opinion. You're used to using your training. You're used to using everything other than going to ask something else. And so it really changes entire behavior of the organization. and um and so it either if you're starting from the beginning you can build this in it's like being an experimentalist company where you don't care what someone's opinion is you run the experiments you always run the experiments you listen to the data data-driven decision making um ai is going to be very similar where you're going to use you know if you're a physician i I have a number of companies in the healthcare space.

40:21You know, the physician is normally looking at all the data, making a decision, and it's going to have to flip where, no, I'm going to see what AI delivers as the differential and the recommendations. And then if I have questions about if I disagree, I'll dig a little bit further and look in further. But I'm going to get to a point where I trust the AI more than I trust my own opinion, because we are flawed in our abilities. I'll give another number, Salim mentioned. There's 7 ,000 medical journal articles per day. If you're going to a doctor, how many did your doctor read this morning? I can guarantee you the AI has the ability to consume them all.

41:08By the way, when you go to the doctor, you get the wrong diagnosis about 30 % of the time today. Right. So there's a lot of upside there to using AI. Thank you, Salim. Thank you. As we all trot off to our yearly updates. And but I think we sense that. Right. That's why we go get second opinions. And look, know what we do already today. You know, something my toes hurting. The first thing I do is look it up on Google and research all the different conditions that people may have had. I take those to my doctor who goes, what the hell is this? And doesn't even know how to look at it. And we'll start from first principles.

41:39They stop looking at what they tell you, stop looking at the Internet, because we always usually go for the ones that are, you know, we're dying usually. So when an AI empowers that, then we'll get to the right answer so much faster. Here's an example. You know, OpenAI's ChatGPT came online in November of 22. In January of 23, two months later, it had passed the U.S. medical licensing exam, right, which requires four years of medical school and two years of residence. and that's pretty spectacular. So the difficulty in implementing it is momentum. It's culture. Yeah, it's one of the most important.

42:20It's not money. So cultural meaning there's resistance to it. There's resistance. There's human. No, no, I'm the expert. I don't want to ask the stupid AI what I should be doing here. What does it know? I've been working in this field for 40 years. I'm the chief creative officer here. Well, guess what? you are going to lose that battle. And so culture is very, very much important. And then the second thing is that the field is changing so rapidly. Staying on top of it is going to be very difficult. And that's where, again, a chief AI officer informing every level of your organization is so important.

42:57What about the, when you were talking about the societal part, I guess this is where the ethics of it come in? Because already powerful technology, if it's your co-pilot, very much depends on who the pilot is. And if somebody wants to use it for nefarious means, or for deception, or for undermining, we know there's concern about elections. It's moving so fast. How are you thinking about the ethical part of it? So those are the societal, but even within a corporation, how does that fit in? And what are your thoughts around that? You know, this is like fire, right? I can use fire to heat my house and I can use it to burn down your house.

43:35And it comes down to how do we extract the promise of the technology without the peril? Now, when you look back over the last, say, 20 years or so, we were super freaked out by the internet and we may be bombarded and phished out of existence. Then we were really worried about email and we're being spammed out of existence. And we found ways of dealing with all of those. Like we don't hear about spam as a problem in email today because we've got actually AI systems that actually filter out most of the spam before it gets to us. So we think it's an arms race where people will do bad things and then we'll use AI of people doing good things to fight the people that do bad things.

44:10And it just keeps going on and on and on. It just becomes more and more automated. Yeah, Peter, I think it's been coming up. Is it an arms race or a space race? I have a feeling you're going to lean into the space race part of it. Well, no, no, it's the AI wars. And what's happening is, you know, so you have to understand, we don't actually know the answers to these questions, right? We can give opinions. I was listening to Jeffrey Hinton, who just left Google. Yes, he's been warning. Yeah, he's been in the news, right? Yeah, he recalled the fact that, you know, Google started developing these transformers and these large language models in 2017, and was basically not releasing them until they had more experience.

44:53And it was, it was OpenAI's release of ChatGPT onto the world stage that forced Google's hand, Alphabet's hand to release it, to remain relevant and competitive. it. You know, they release BARD. So that's fascinating. And, you know, so there's not going to be a slowing down of this stuff. And now the question becomes, how do you regulate it? Can you regulate it? And I don't know that you can regulate it. You know, if you make something illegal in the US, does it just go to South Korea or China or India? So, you know, when I was in medical school years ago, the restriction enzymes, gene editing first came on scene.

45:38And it was front pages of newspapers. The Time magazine was like, you know, designer babies and Hitler youth were good. It was going to it was like scare mongering tactics again. Right. That's what the media does. And there was a lot of discussion about should we regulate these genetic engineering? And what happened instead was that the genetic engineering industry got together at a place called Asilomar and held these very famous Asilomar conferences in which they created their own guidelines, ethical, moral operating guidelines, which have stood the test of time. We have not had a genetic engineering disaster in the past, you know, 40 years.

46:23So the call for these companies to get together to do this is going on right now. So we'll see. But, you know, listen, I'm a father of two 11-year-olds. Salim has an 11-year-old. Our three boys know each other. And thinking about what's their world going to look like is fascinating. Yeah. I'm glad you brought up a positive example because there are lots of the idea of industry self-policing is often met with skepticism and there are bad examples of that. So it's so it's it's nice for you to bring that up as something that is possible, because I think we forget about that. And it's a fantastic point on on the genetics.

47:09And it's a great example because biotech is so fundamentally powerful. the example maps across very clearly. Yeah, absolutely. So how can a lot of our audience, I think, would count themselves as having an exponential mindset. They're a learning tribe. How do you keep up? How do they need to think about this, whether they are leading companies, whether they are executives in the executive rank, or whether they're an employee? It's so much coming at us. How do we navigate it? How do we educate ourselves? It's tough. We wrote this book for that purpose. And the book is written, Exponential Organizations 2.0, the new playbook for 10X.

47:54Growth and impact. Growth and impact is the name. We wrote it as a book that is very consumable, like for each of these attributes. This is what the attribute is. Here's a case study of how it's being used. Here's the tools you can use. Here's the problems, the challenges, the opportunities. And so it's every one of these is meant to do that. We've also, Maggie, if you go to diamandis.com slash exo, there is a three hour workshop that we invite you to come. It's free. Come bring your employees, bring everybody who you want to think this way inside your organization. And during that three-hour masterclass, we'll give you free access to the book, to an AI that we've created where you can query the book.

48:47This is a, to quote Salim, this is a living book, and where you can query it about how to use it. So again, Diamandis, D-I-A-M-A-N-D-I-S dot com slash E-X-O will give you access to the masterclass and the free book and the AI. Salim, you want to add anything to that? Well, I think it's critically important because the way we built organizations in the 20th century were top-down, hierarchical, command-and-control, big structures designed for efficiency and predictability. And in the 21st century, you need to architect it for flexibility, agility, adaptability, and speed. And so the entire heuristics of how you build and transform your marketplace, et cetera, have changed.

49:31So now you need to be this new type of an animal, the furry animals after the asteroid is hit. And what we've been doing is laying out this playbook because we now have 10 years of data and case studies and examples of how people have applied these principles in different ways. We have some unbelievable data around the Fortune 100, for example, that's worth talking about. When we wrote the book, we actually analyzed the Fortune 100 and ranked them on this model. To what extent is Walmart purpose-driven? To what extent is GE using lean startup thinking? To what extent has IBM done decentralization of its decision-making?

50:07And we did a segment on CNBC Squawk Box talking about this, presenting this index. We just did a seven-year trailing analysis and said, okay, how did those companies do over seven years? And we looked at the top 10 that were using the attributes the most over that seven-year period and the bottom 10 that were using the attributes the least. So the most purpose-driven, scalable, flexible, adaptable org structures versus the least. And we found over seven years that the most EXO-friendly delivered three times better revenue growth than the least bottom 10. Profitability, 6.4 times higher. Return on equity, 11 times higher.

50:46But the killer was shareholder returns, compound annual growth rate. The top 10 outperformed the bottom 10 by 40 times over a seven-year period. And it was so ridiculous. We had to go and check the data like four times over to make sure we weren't missing something. But it's right there. And so it's pretty clear that you need to be organized as the world becomes more volatile. Your organization structure has to match to be able to deliver those some capabilities. So we're pretty clear in the future that every company, every nonprofit, every impact project, even any government department will be organized in this way going forward.

51:18And so the workshop is designed to say, Well, there's a lot of work to be done there, isn't there? I'm still fighting with the IRS over something related to my parents and I can't get anybody to resolve it. And it's ridiculous. So, I mean, clearly there's a lot of work to be done there. You know, I'll take the simplest example, right? With the blockchain, we can do authentication at very low cost. And almost all government functionality, something like 80 % is authenticated. Yes, you have the phishing license. Yes, you've got the building permit. Yes, you have a driver's license. So when we can kind of automate a lot of that, it'll actually make government way, way more efficient, which, you know, and smaller, which I think everybody could appreciate.

51:56Yeah, and maybe save some money, which is another thing we need to worry about. So we talked about organizations. What about the younger generation? You have 11-year-olds. I have kids who are a little bit older than that who are starting to think about college. And it strikes me as I'm listening to you that so much of the education system now is kind of still built on the old-fashioned model. You know, they're just learning to test and get past the standardized test that's already going to be outdated by the time they have to. We get questions a lot from people saying, what should my kid do in college?

52:30What should I tell my grandchildren? How can I prepare my kids for this? How do we need to think about that? I think about this a lot. So first of all, and because I speak to a large number of audiences, as does Salim, and when I mention I'm a dad, people ask. So listen, if your kid is in college and the question is, what should they study? You know, first of all, you know, I would be it would be incorrect me to say, you know, studying data science and AI will give you an incredible job studying biotech. You know, what's going on in the whole biotechnology world will give you a great job. Those are the two biggest business verticals that are happening where we'll see trillions of dollars in creation there.

53:13But that's secondary. And for if you've got younger kids, there are three things for me and has nothing to do with technology. Number one is help your kids find their passion and their purpose, whatever it would be. Not your passion, not your spouse's passion, not your teacher's passion, their passion. For me, when I was growing up, you know, it was my passion for space that drove me to do everything I've ever done in life as a result directly of that self-driven, wanting to learn passion for nothing. You know, it's Star Trek. It's, you know, Captain Kirk and Mr. Spock that got me going and Neil and Buzz landing on the moon.

53:51So that's the first thing. Get your passion. The second thing is learn to ask great questions. I give this advice to CEOs and kids. You know, the quality of your question is going to be the quality of your life and your work. And the third thing is grit, learning not to give up. I think it's those three things and they're independent of technology. Yeah, to build on that, for about 200, 300 years, when we think about education, it's always about job schooling. You went and got a degree in the thing that would be most likely to get you a job, and it's supply-side driven. You got the right skills, you became an accountant, a doctor, a lawyer, and you went to the job marketplace and you tried to sell those skills to get a good job.

54:33What we're seeing now is it's moving to the demand side, as Peter talks about, which is what is your passion? What problem do you want to solve? What makes you up in the morning that you have this burning desire to go do? And then now find the skills and technologies that will fulfill that. We note that, you know, look at the Steve Jobs and Zuckerbergs and Bill Gates and the world dropouts. Right. And they went and found their passion and then found the technologies that solve that passion. And this is where we think the major shift will be. There's some amazing data around this. Now the biggest companies in the world aren't hiring based on your college degree.

55:09In GitHub, which is a platform of software developers globally, in Silicon Valley today, your salary as a software developer now has nothing to do with your college degree or your grades or the reputation you have. It's 100 % what is your score on GitHub, which is an open peer-to-peer Yelp-style rating where people rated my code. And now everybody knows how good of a quality developer I have. So therefore, the value of a computer science degree just went to zero. And so we'll see much, much more of that as we go through, apply this to doctors or lawyers, et cetera, et cetera. And we think that will become pervasive.

55:47The simple answer is find your passion and follow it. Can all of us learn to engage with AI, have it as a co-pilot, use it in our companies, use it in our careers, or do you have to have a sort of technology mindset? Everybody can. 100%. You just need to play. What you need is the mindset you had when you were a kid. That's what you need. Go back and rekindle that six, eight, 10-year-old. So my kids, they sit in front of ChatGPT or Bard, and they're both great, right? ChatGPT is 20 bucks a month. Bard's free at this point. It's amazing. It's like, just ask anything. Go and learn a subject by asking, asking, asking.

56:34You know when that kid asks, well, dad, why is that? And why is that? And why is that? And gets annoying. Well, Bard or ChatGPT will infinitely go down that rabbit hole with you. I did this with my 11-year-old. He was listening to some hip-hop music. And I was thinking about how could I do this. So I went to ChatGPT with him and I said, rewrite Bible Genesis chapter as a rap song. And it did it. And you could see his eyes like freaking out going, oh my God, this is possible. This is the kind of thing that we'll do. And this is an important point to make around Peter's six Ds, which is, you know, you digitize, you get disrupted and deceptive and then you get disrupted.

57:09When a technology becomes disruptive, it usually is when it becomes usable. Steve Jobs made the mobile phone usable, right? Bitcoin base made Bitcoin usable and at least you could purchase it easily. I call it interface moments. Interface moments. Exactly. And AI now has its interface moment. We now have a user friendly way to interface with an AI. Up to then, only geeks could use these models. They had a very complex software and hardware running them. You had to know which software libraries to bring to bear, etc. But now with the interface, the interface moment has now happened with AI. Now anybody can interface with it.

57:45And it sounds like there's a huge amount of entrepreneurial activity going on in that interface. I don't want to say everyone's creating the killer apps for this stuff, but it sounds like there's an enormous potential for people to figure out how to get us all using it. There are at least, I would guess, 50 ,000 startups being created right now by two kids in a garage learning how to apply this to every domain possible. And many of them will fail, but there will be enough that succeed that will completely change those fields. Let me give you one example just to bring this home. There's a Chinese car company called Guazi.

58:25They sell used cars. Now, when you think about used cars, how would you make that 10x better? It's not that obvious. Maybe I have a better warranty, better delivery service. I do it on an app, something. What they do is they go to somebody who wants to sell a car, and they capture 250 data points, video, audio, images. They take an audio of the engine and run it through a machine learning algorithm. They can detect the quality of the engine just by the perturbation in the sounds. Their engine comes up with a price. This is what we think the car is worth. They show it to the seller, and they say, we'll give you 10 % less than this price in cash right now.

58:59Seller goes, hell, here, yeah. Then they go to somebody who wants to buy the car, and they said, here's the price of this car. We'll sell it to you for 10 % more. Fully transparent, there's the model. In seven years, they captured 80 % of the used car market in China. They sell 2 million cars a month, right? So you look at that, and you go, that's what's possible if you apply all these attributes collectively. We're going to see this. We're going to see radical disruption of every industry. And you think about used cars, it's not an obvious thing, right? If you can do it in used cars, why can't you do it in every other domain out there?

59:36Amazing. So what are both of you currently playing around with that's kind of blowing your mind in AI as you continue to sort of think about and help companies tap into their exponential selves? I'm actually doing a four-hour workshop tomorrow for my Abundance 360 members. And we're going to walk through a lot of the, you know, the OpenAI chat GPT and their plugins. We're going to look at, you know, some of the imaging work. We're going to look at some of the summarization work, the ability that you can feed into these AI engines a PDF and say, summarize it for me, or a YouTube video and say, summarize this video for me.

1:00:26So, the challenge is that as humans, our speed at which we consume information has not accelerated, but oh my god, the amount of acceleration in the world, info in the world, has exploded. So how do you use AI to find the information that's most relevant to you, your career or your desires, and then use AI to be able to filter it and present you the most important part of that information. So this is part of how do you make time more abundant, right? How do you use your time, right? We're all born with the same restriction of 24 hours in a a day, seven days in a week. And it's how you use time.

1:01:08A billionaire uses, saves time by flying in their private jet and skipping lines of magnetometers and socks. You can save time by using Google or BARD or ChatGPT and so forth. At the very metaphysical level, the world is a signal to noise problem, right? You hear a noise in the bushes, is it your friend or a dangerous animal? Better to run back in the old days. Today, you hear a noise in the bushes, you put a camera in there and you run and then watch the camera. With all the information out there, we now have really good AI gives us a really good signal to noise processor, right? Filter out all the stuff that I'm eating and give me the three things I should be eating right now.

1:01:49Or same thing with exercise. You've seen, here's my exercise patterns. Tell me the most optimal exercise for me. I've got 30 minutes. Go. And so I think we'll see a radical change in lifestyle, businesses, et cetera, all applying AI to do things and optimize things, give us more time, give us more space, give us more freedom. We're super excited about the future. You know, honestly, again, I want to say to everybody listening here, if you haven't had a chance to dive in, dive in and play. Just give yourself an hour. Go watch a few YouTube videos or just open up Bard or ChatGPT and just start asking question after question after question and go down the rabbit hole.

1:02:31And I think you'll be amazed at what you find. And we'll be coaching all of the attendees at this workshop on June the 6th on this exact topic, right? How do you take AI and apply to all your businesses and all your business functions to completely transform it to 10x your organization? Yeah, again, just to be clear, whenever you're listening to this, come to dmandis.com slash exo. You'll have access to a free masterclass, access to a free copy of the book, and an AI that allows you to query the book. Again, the idea of writing a book on AI or exponential technologies right now is insane because things are changing so fast.

1:03:11You can update the book constantly. So this will be a living book. And we think the best way to start on this journey is with this three-hour masterclass that allow us to teach it to you in a methodical fashion. Come in and say, I'm a shipping company. How would I use AI? And it'll tell you. Clearly, we have just scratched the surface. but it was an amazing conversation. It gave us so much to think about. And I really appreciate in all of the conversation around this, I really appreciate that both of you have this sort of mindset of abundance and optimism because I think that's what we need right now.

1:03:43So thank you both, Peter, Salim. Fantastic. Great to have been with you.

1:03:54What's up, revolutionaries? Thanks for tuning in to the Real Vision Daily Briefing. For more content like this, head over to realvision.com and get unfiltered access to the very best, brightest, and biggest names in finance.

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