ScreamingBox Technology & Business Rundown

Dave Erickson 0:00
AI is coming. AI is coming. Run, hide, panic or maybe embrace it. What does the AI future look like, and what are you going to do about it? On this ScreamingBox Podcast we're going to worry about how AI will play into our futures, and please like our podcast and subscribe to our channel to get notified when the next podcast is released.

Dave Erickson 0:45
Everyone is either loving AI or worrying if it'll take their job and livelihood. But what are the possible impacts of AI and how can we learn to live with it? Welcome to the Screamingbox technology and business rundown podcast. In this podcast I, Dave Erickson and my real and live co host Botond Seres, are going to worry about how AI will play into your future. In part two of our podcast with our guest, Ari block, Techstar, alumni and author, please listen to last month's podcast with Ari on how to pivot a business. If you like this podcast, the link will be below in the description. Ari is a dynamic entrepreneur and a global technology leader whose career bridges military intelligence, forensics, technology and the startup world. His passion for innovation began early. At just eight years old. He founded his first company repairing computers for a local business. By age 15, he had built and successfully exited a b2b sales platform startup. This early trajectory led the foundation for a career defined by ingenuity, resilience and the relentless drive to create impact through technology. Ari went on to serve in military intelligence before joining Cellebrite, a global leader in digital forensics. There, he played a key role in developing advanced forensic tools that are used worldwide by law enforcement, military and intelligence agencies to extract and analyze digital evidence. Beyond forensics, Ari has founded and mentored startups through TechStars, guiding founders on product development, fundraising and go to market strategies. Ari, welcome to the podcast.

Ari Block 2:21
Thank you so much for having me, gentlemen.

Dave Erickson 2:24
To begin with, how did you go from digital forensics to startup mentoring at TechStars? .

Ari Block 2:33
Oh, wow, It would be unfair to say that, you know, I started my entrepreneurial journey with TechStars, but it was definitely a nice, you know, brand name to add. I didn't even know that TechStars existed. I think it was a friend who said, Hey, why didn't you apply to them? And I was like, what is that? I had heard of Y Combinator TechStars wasn't on my radar. But then, you know, my friend said, you know, you know, not only are they one of the top in the world, they're also in your backyard, they're up in Boulder in Colorado. So you have to look into it. I applied for the program and basically didn't get in. So this is like the night before the program starts, and the Managing Director, Lila, she calls me up, and she's like, Ari, you're like, this close to getting into the program. Basically, it was you were the next in, and that's why you didn't get in. But one of the companies dropped out. So you're in. Are you interested? So basically, I was out, and then I was in, and then I was screaming. My wife was like, what happened? What happened? It was like we got into TechStars. And for those in the audience who don't know what TechStars is, it's really like Harvard for companies, right? So it's easier to get into Harvard than it is to get into TechStars. So it's quite an accolade, and it's quite the program, and we can talk about mentor madness and that stuff. But I mean, Y Combinator is an amazing program too, and there's many others. So, you know, I, even though I am an alumni, that's not necessarily the only way to go.

Dave Erickson 4:14
Yeah. I mean, it's a challenge companies are having now. You know, companies that had built a business are finding that AI is coming in and offering an alternative that they can't compete with, right big time, and a bunch of companies don't even know that, right? No. (a bunch? most), most, those of us who are in AI and doing AI, you just see it all day, this company is, you know, AI is going to do this. And, you know, how are they going to start pivoting their business? Sometimes, I guess a pivot is not just a business change in business direction of what you're selling or making, but it could. Be how you do business, right? And I think a lot of companies now are going to have to pivot how they do business.

Ari Block 5:08
I would go further than that. I would say every single one, every single one, there's not a company in the world that's not going to be impacted by this. In fact, there's probably not a person in the world that's not going to be impacted by AI and I, there's the doomsday analysis, which it's going to be really bad for a while, and I don't know how long, but I believe that after it's really bad for a while, it's going to get really good. Because what's going to happen, we're going to have a second renaissance, and we're seeing both the good and the bad signals happening right now. We're seeing computer science engineers finishing university and going to work as baggers in Walmart because they just can't find a job. That's the bad. But then we're seeing the good as well. And the good is that, you know, I just gave a free education, and this person who got my free education showed me that he did the work of 10 people. He was an entrepreneur. He did the work of 10 people in one day that would have taken three months. Now, this person is an entrepreneur who needs to get his business going in order to feed his, you know, his children. He's got a, he's got a daughter. He's got a wife. That knowledge that I gave him for free in one of my trainings, you know, changed his life. Now he can compete with other companies that are bigger, stronger, not faster anymore. He's faster now, right? So, so this is, this is, I think, you know, if you look at the history, right? If you look at the beginning of time, the things that have created the transition of wealth more than anything else was not social advocates. I mean, I love all our social advocates. Good job. You've got to tell the story. But the one thing that changed equity, the biggest thing in the world, bigger than anything else, by a magnitude, by several magnitudes, is technology. It's the wheel, it's the printing press, it's the internet. It's going to be AI now it's, it's all these things are, the only thing that have created equity in our world. It's definitely not politicians, yeah, no,

Dave Erickson 7:19
Although politicians seem to get a lot of equity, but that's for a, do they get the equity?

Ari Block 7:22
They don't redistribute the equity. Yeah. Look, it doesn't matter what side of the political, you know game you're on. Politicians are corrupt, and

Dave Erickson 7:32
I think that's the basic definition of politician. They have to be, because they're basically trying to work both sides of the aisle no matter what. But I think now companies now need to kind of start looking at it like companies in general, because they're made of many different people with many different opinions and many different eyeballs are seeing the landscape very differently, and they interpret these signals differently, right? But at some point the person, the person, or people at the top, they need to kind of get a pulse. And I think one of the reasons that businesses fail many times, not all the time, but many times, is that the people at the top get lazy. They're not plugged into their business, their market, they're not thinking about where things are going. They're just living the good life, or they're living the routine. And I think when you start smelling some change, that's when founders really need to change their track. What do you think about that, and are you seeing that trend that founders are getting more engaged? Or what do you think?

Ari Block 8:45
First of all, you nailed it. I mean that that, you know, the gravy train is great as long as it lasts, but I think if you're on a gravy train, you need to understand that it's going to finish sometime, and you should be a little paranoid about when that's going to happen, and you should always assume that it's sooner than you think. So. So everybody should have that mindset of, when is the gravy train going to finish? And if you're on a gravy chain, good job, you know, good job to you like, Okay, you may, you have, you know, you've clearly done something right, but it's going to end at some stage. So, so the question is, how do you create a almost like an early alert system. So think about this as almost like an alarm system that wakes you up if something you know goes off. So understanding the, the key, like operations of your business, and what are the drivers that drive your business, that's really important, because then all you do is you put a KPI on each of them, and you're like, as long as everything's okay, the alarm doesn't go off, right? So, you know, I teach founders to set up these alarm systems, and what's happened now is that these alarm systems are going off, left, right and center, every single one of them. Why? Because AI is changing the fundamental ways that businesses operate, from a perspective of unit economics. So think about it his way. Right now, a lot of engineers will tell you that I'm full of shit about what I'm about to say, but that's just because I'll only be right in about six months to a year. But right now, they say, oh, AI doesn't work. Don't worry about it. I'm worrying. I'm really worrying. So, so here's the thing. Engineers look at AI. They try and do something super complicated. It doesn't work. They're like, Ah, this doesn't work. They move along. I look at AI, and I'm doing some deep, cutting edge research with AIs, and I can talk through a little bit of the research. Basically, I'm trying to eliminate hallucinations, and I'm getting really good success. So basically, I've created these AI basically networks. So think of this of a swarm of agents that work together, collaborative agents that are sharing data, that is basically eliminating hallucinations. Now, when we say hallucinations, what that means is that the mistakes that AI makes, I can make them go away. That's what I'm achieving. And the problem is that this technology is going to be out in the world in six months to a year to two years. I'm doing it in a small scope of my problem sets, but the generic solution is going to be out there soon. So if the generic solution to basically write code for any application is around the corner without hallucinations, what does that do to the business environment? That's, That's terrifying. (Yeah.) Why? Basically, software, when we think about it, the IP, the intellectual property in the software, it's a barrier to entry. Now if that barrier to entry, and when we quantify barriers to entry, we quantify them in months, so it will take, let's say, 10, 12, 30, 60, months to recreate the software. That's your barrier to entry. What if that barrier to entry just went down to zero? So to zero, the fundamental economics of the world changes overnight. This is horrifying. What companies are going to do is just scary. I don't know what's going to happen when this actually works, but it's not going to be good for a while. I don't know how long.

Botond Seres 12:00
I understand what you're saying about AI not being good yet, and I absolutely agree. I just want to step in a tiny bit and say that the hallucinations are not really the concern with AI, at least from my point of view and from the point of view of some of my colleagues, the bigger concern for for many of us, is the lack of logical reasoning skills of LLMs, which they are not built for, therefore they don't.

Ari Block 12:37
Well, Potato, potato, tomato, tomato, I think we're saying the same thing. You're saying LLMs can't logically reason. I'm saying LLMs hallucinate when they try to logically reason. Is that a different thing? No, it's probably the same. But what I'm saying is that there are architectures, right? The one I'm working on, one said architecture that eliminates the inability for LLMs to logically reason, whether you call it a hallucination or an inability for them to logically reason doesn't matter. And what you need again, I'm not going to scare off your listeners by talking about math, but you probably can't see it. But let me. Let me move my camera for a second. You see those equations on the board in the back? Okay? So what those equations are, they're statistical equations. They're the first step that I'm working on, and it's basically the statistical equations to eliminate the inability to think logically or rationally. And those equations then get trans, why does this even happen? It's because of how these models actually work. So there's no such thing as AI, it's neural networks. And what generative neural networks are, what they really are, is, is, think about it as a lot of trigonometry with a bunch of linear algebra because of the matrix math, plus a whole bunch of derivative math. So you basically create a non deterministic function. That's what a neural network is. And what a general neural network is really, as simply as possible, is really two of these neural networks competing for efficiency. Once they basically compete and they get to efficient state of these two natural networks, you have one. this is Gan, right? Gan, basically you have a classifier. You have a creator. Once the classifier and the creator basically agree, they get become Pareto efficient. At that stage, you have a generative neural network, which, in essence, is what generative is. That's what we call AI, okay, so the behavior of these mathematical models, in essence, they're a function, right? So statistical, non deterministic function. They behave in funky ways because they're non determinative. In fact, if you understand the math, then the following sentence that I say would completely be clear to you, you would and the sentence would be, you can run the same function three times with the exact same input, you'll get three different outputs because they're non determinative, right? Like, duh, obviously So, but, but the beauty is that you can apply algebraic structures and then statistical structures on top of the algebraic structures, which can, can create a determinative network from a non determinant network. Now, if you understand anything about math, what I just said is, is, is the key to solving hallucinations or non logical thinking in LLMs.

Botond Seres 15:23
So are you saying that by structuring these non deterministic networks, we can get them to become deterministic?

Ari Block 15:31
Absolutely, yes. That's, that's the research I'm doing. Yes. So, so I'm creating deterministic networks out of swarms of agents which are working collaboratively to eliminate look, you have to have the non deterministic behavior. It's a core part of why they can solve the problem, right? If you had it, to, if you had to look. We tried to do this in the 70s with fuzzy networks. We're trying to create non deterministic behavior with fuzzy networks which had deterministic languages like obviously that's not going to work, right? So we try to add randomness, right? Because that, we try to add the non deterministic but it never really worked. So what we've done today with LLMs, we've created the non deterministic fuzzy network, and now we're figuring out the non deterministic fuzzy networks. They have issues. Like, of course they do. That's why we created them. But they're still brilliant. So now we're trying to figure out how to create deterministic behavior from a non deterministic network, right? So this is the evolution of the LLMs. And as I said, this research, I think, is going to change the world. I've already identified other people are doing similar research. We all seem to be thinking on the same lines. So one of us is going to figure it out, and I think sooner than later. And the big companies, like they always do, they're going to figure they're going to steal this, and they're going to figure out how to do it at scale. Because we're doing it in this small scale, the big companies are going to rip us off and do it on the big scale, and that's okay. That's how the world works. Hopefully one of us will make a million dollars on the way.

Botond Seres 17:01
Yeah, it is what it is. (It is what it is. That's right.) I mean, personally, I much look forward to the biological alternative, much more organelles, if, if you're into that kind of thing,

Ari Block 17:16
I'm starting to get scared that there's not a big difference between the biological alternative and the dry networks, and I'll tell you why. In my research, I've been starting to see that even the dry brain, meaning, you know, our neural networks, they're exhibiting a lot of behaviors which are almost identical to what we would call psychological biases. So I'm starting to see the emergence of basically, if you're familiar with the research of Daniel kohneman and Amos Tversky, so all of these psychological biases, they're emerging inside neural networks. Now that scares the shit out of me, because if neural networks at scale are exhibiting the same mistakes as humans at higher level reasoning, at the beginning, I thought, Oh, this is just biases in the training. But I'm starting to think it's not. I'm starting to think that, because if you remember the history, neural networks were modeled off the brain, that's what they're designed to do, right? I'm starting to get scared that actually, the neural networks that we have today are not that far off how the brain works, and with a little bit more power and these advanced, kind of higher level functionings, which I'm designing, I have a feeling that because we're in the right direction, we're starting to see the same problems that human have in terms of psychology. I'm seeing psychology happen with machines, and then the reason that that scares me is because I'm thinking, well, if I'm seeing the same problems with humans as I am with machines, how do I know that humans are any different?

Dave Erickson 18:50
They're probably different because of the biological component or a dry machine. But right? But whether that makes much of a difference in certain types of behavior. I think the time to get scared is when they can get machines to be able to judge correctly whether something is good or bad, then I think you're going to have,

Ari Block 19:14
Can humans do that, huh? Can humans do that?

Dave Erickson 19:18
Not very well, not very well, right? We have the capability to do it, if you were, if a person was, slow down and study and get enough data right? Most people don't do that.

Ari Block 19:29
Not really because we have different cultures. We have value systems, so we're not really going to agree on the difference between right and wrong, yes, because of our cultures and value systems. And it gets much worse. Of course, there's disinformation right now, so you start to see these scary parallels now. The reason why this is scary is because I was in the camp for many, many years. We don't need to be afraid of AI until true AI comes around. And true AI is what we call general artificial intelligence.

Dave Erickson 20:00
Or conscious general art intelligence,

Ari Block 20:04
exactly, artificial AGT, right? So, the general artificial intelligence, or the artificial general intelligence, right? So, AGI, so I've been in the camp of like, AI is not scary. It's just a statistical network, like, who cares? AGI, but is scary, though? Well, here's my point. This is why I'm saying I'm scared. I don't think there is such a thing as AGI. I think what we have now is AGI, and that scared the shit out of me.

Botond Seres 20:30
And to be honest, I, I'm inclined to agree with one. There's a lot of people might be incredibly wrong.

Ari Block 20:38
We could, we could both be incredibly wrong. I can tell you, there's a lot of researchers around the world that are telling me that I'm wrong, but I completely disagreed with myself years ago.

Botond Seres 20:49
Just allow me to make this point, as I don't think the efficiency is there with hardware, the same efficiency that we have with wetware right now in labs.

Ari Block 21:00
Yeah. So there's a researcher that was basically saying that, Oh, we need to have 3D basically inputs in order to I don't think I agree.

Dave Erickson 21:09
It's really funny, but I saw this episode of South Park, and part of that episode was with chat GPT, and the one of the characters was, you know, having a conversation with chat GPT, and it reminded me, look, the the Turing test is really important, and a lot of people can't tell if they were on a blind test that they were not talking to a human being or chatting with a human being. Now, you know, the way that they get that conversation is through an LLM, that's, you know, looking at all the different conversations that have occurred and randomly or logically or through a logic map, picking the responses. You know, I tell people that a lot of the answers you're getting out of chat GPT, they're not an answer. What they are is they're what chat GPT thinks you want to hear as an answer.

Ari Block 22:02
Yes. That's brilliant. That is right.

Dave Erickson 22:05
But humans, in general, some of them, are having a hard time determining whether the thing on the other side is intelligent or not. They think it's intelligent, right?

Ari Block 22:16
Which, by the way, is how many humans work. Yep. Humans tell you what you want to hear, yeah,

Botond Seres 22:21
I was gonna say. And we have a name for that condition. It is a psychological condition when someone says only the things you want to hear.

Ari Block 22:28
yeah, yeah. So, so, so, here's my point, if, if, in fact, the dry brain, right? What we have, what we're calling AI today, is actually not that far behind the wet brain, and it's the and it can reach there in certain amounts of time, which is not 10s of, you know, not 10, 20, 30 years, but less than 10 years. Then what that means is we actually do have an early version of AGI. Now, if we have an early version of AGI, we should all be scared. Now, why is that? If, if Alan Turing, right, helped us, you know, win a World War, we should all be very grateful for the brilliance of that man. If Alan Turing said that this is the test for, for, for, basically, you know, the Turing test, which is basically, you know, is this? Is this, I don't know what did he call it? Is this intelligence? Is this? (He was saying more consciousness, consciousness) Well, I think consciousness is still a little aggressive, but let's call it. Is this intelligence? So oh yeah, it passes the Turing test. Now, when it passed the Turing test, we were like, ah, Alan Turing was wrong. So for since, you know, World War, we've been like, Alan Turing Alan, Turing Alan, Turing Alan's and then one night, it happens, and we're like, Ah, he's an idiot. What? Yeah, no, Alan Turing is not an idiot. No, we should all be scared right now. So, you know, I'm not trying to shock everybody to being afraid. I'm just trying to say, let's open our eyes. Let's figure out where we are. Let's understand that there's a short lead time to AGI because it's already here, and we need to start thinking about what the world looks like tomorrow, and the answer has become very clear when you start thinking, but if you just ignore the fact that AGI is here today, then you're just putting your head in the sand.

Dave Erickson 24:31
Right and that goes back to kind of a full circle on the comment that you know, business leaders and founders are a little disconnected from what's happening on the ground, but it's critical. So for those business founders who are listening to this and saying, Yeah, I think there is something coming up in the future that's going to be an issue, how should they start thinking about how AGI and the integration of AI deeper into society? In business, will force them to pivot their businesses?

Ari Block 25:03
Yeah, there's probably no answer to that, because we don't know what the future looks like. And the future is no longer 10, 20, 30, 40, years out, it's six months out, right? So what's going to happen is that the large companies, right? So these are the anthropics of the world, the open AI of the world, the GPTs of the world. They're basically going to come out with a version which is going to change everything. It's just going to work, suddenly, overnight, it's going to work. And when I say work, that means it's not going to have the issues of logical thinking. It will give you the answers that you want to hear and that you don't want to hear, and it will explain to you why each of them is correct. It's going to be superhuman, basically, because even humans can't give you the right answer, because there's no such thing as the right answer. But AI will be able to say, look, there's three answers to this, and here's why. There is no right answer, but here's the three that different people would expect. So you know, something's going to happen overnight, that's going to happen. So when a CEO, or anybody a firefighter, because the training that I'm giving in a week or so is for firefighters and, and police officers. So I started a company. It's a nonprofit, which I've invested into. This nonprofit has one objective. It's teaching public safety individuals how to use AI. Now here's my point. I don't know what the future is going to look like, but the better educated you are, the better off you will be. So when I think about the devastation of communities that's going to happen around the United States, the communities that are more educated and are using those tools today will create a resilience to this future economic devastation. So my point has been, education, education, education, education.

Dave Erickson 26:57
We've done it here. I have some developers I'm working with now where, six months ago, they coded everything by hand, and I told them, Look, exploring new business, we need to be able to be much more productive. You need to start learning some of the AI coding tools and integrating them in and they did, and it's increased productivity significantly and allowed us to approach jobs at cost levels that we couldn't even dream of, you know, a year ago or two years ago. That part of it, while exciting to me, is also very scary, because I can see that at a low level that AI is currently at, the productivity gains are phenomenal, right? But that brings us to the social side, which is, you know, productivity comes at the expense of the amount of work needed. So if you are 10 Xing productivity, you're 10 Xing a decrease in the amount of people needed to do work. right. And the at some point a line is going to be crossed where there are many

Ari Block 28:12
going to be cascading. What, what you're describing is going to cascade?

Dave Erickson 28:16
Yeah, that many people, as much as they want a job, aren't going to be able to get a job because they just don't need the people, because AI is fulfilling that versus an AI taking away a job, right? Most people talk about it like AI is going to do something, then my job will be redundant. I don't, that's a different thing. But those people who can harness AI to use it to become productive, will survive and benefit. But, you know, there can only be one of those, and there's 10 others who, whether they learn it or not, are not going to have the work because of the productivity gains. And I think the first, the first job of AI, of real, see, you know, conscious kind of AI is, well, how are you going to solve this problem? What are we going to do with all the people who don't do that work? How is society going to deal with all these people who can't get a job, even if they want one?

Ari Block 29:10
Yes, well, in essence, that's the problem I'm trying to solve because I am deeply concerned about my communities. I can't worry about everything, but I'm deeply concerned about my communities, and I think that you need to think about governments as an operating system. So if you think of government as an operating system, there are different subsections or subsystems in the operating system, right, for example, Department of Education. So for example, you know, the economic departments that are basically planning out how much is the dollar worth, and is the dollar worth too much or too little? Is the interest rate too high or too low? Do we need to buy or sell? Right? This is what you know, the government does, amongst other things, like, you know, build weapons and research and stuff like that. And also shelter services, like, you know, feeding people that are hungry. So there's a lot of functions inside of the government. Now, what you've described is basically a meltdown of government services. Why? Because if there is supply and demand in terms of the labor market, and you know, labor is one of the government functions assuring alignment of future labor, if there's a breakdown in that function, what's that going to do? Well, what that's going to do is there's going to be huge, huge, huge, huge, huge, huge supply. There's going to be very little demand. Now, why is that going to happen initially? Because companies are very selfish, and initially, when there's an excess of, you know, basically supply, they, what they do is they become more efficient. They give more money back to the shareholders. So initially companies basically take a bath, right? They basically say, Oh, we're so much more profitable that can last for a couple years or more. So we don't know how long the devastation brought on by AI is going to be. We don't know how fast the cascading effect will come. It's going to happen in one industry, but then it's going to cascade onto multiple industries simultaneously. So there's going to be a period of devastation where excess supply will plummet pricing. So you know, we have supply, we have demand. Well, what happens if, you know, supply increases significantly up the price went really low suddenly, right? So, so and what price is, in this case, it's basically the cost of a human being working, meaning it's your salary. So if your salary plummets because supply increases significantly, that's a really, really, really, really, really bad crash, market crash, right? So, so if we understand we're before a market crash, we need to start preparing for that. What does that look like? What does that preparation look like? So I think the best way to understand what preparing for the market crash looks like is by actually painting out what the market will look like after the crash is done. Yeah. Mm, hmm, that's the most important thing government can ask themselves, right now. And I think we're going to have a renaissance 2.0 so we're going to have a new renaissance. The question is, will this market crash last for 10, 20, 30, 100 years? We don't really know, because that depends how governments will prepare for it.

Dave Erickson 32:21
Right? And you kind of have, in a sense, two halves of an economy. So you have a half of an economy, which I would call white collar, where the product is more ethereal, and then you have the physical side of the economy, where it's a physical doing. You know, there's not going to be really many AI that can fight fires the way a human crew fires. People are good at farming. AI and machines, not as good at farming, right? There's always going to be so there's kind of two economies. And I think you're definitely going to see a shift in the physical economy having more value, in a sense, because AI is going to devalue the work of the, the white collar jobs significant or people AI may or may not become good at managing people and working with people. That's still an unknown. (Yeah, we don't know). So there may always be a kind of a person who needs to manage people versus AI. So there's got to be areas of the economy that are going to be, quote, safe or okay, but for a while, for a while, but there's just the amount of what isn't safe. It's large. It's law. And I don't think governments are even thinking it right now. I don't even know.

Ari Block 33:37
They're not. Governments are notorious for coming late to the game. I don't think we have the, the pleasure of coming late to this game. Yeah, we don't. So if there's one thing that I want to shout on top of my soapbox is we need to start getting prepared, because if we come late to this game, we're going to be devoured.

Dave Erickson 34:00
Yeah, companies are really going to have to think about how they're going to pivot and change their business with this, right? Because not all pivots are based on the market. Some of it's going to be productivity. Your competitor all of a sudden becomes 10 times more productive than you. Rght.

Ari Block 34:17
Well, that, in some ways, that's good news, because what we're what we are probably going to see is that, you know, if you think about Clay Christensen and the innovator's dilemma, I feel like this is going to be the biggest vindication Clay Christensen has ever had in the history of everything, and we're going to see that paradigm of The Innovator's Dilemma play out. And what's going to happen is that the big companies are going to be slow to adopt. They're going to be concerned about cannibalism, meaning commercial cannibalism, and then they're going to basically not going to adopt. So what's going to happen is that the smaller companies who are adopting all of them, right? Because all the small companies are using AI right now, when I say small companies, I'm talking about one, two, three people, entrepreneurs that are in TechStars now, they're in YC now, but eight months later, they're worth a billion dollars. This is happening. Companies are becoming unicorns in less than a year. So these companies are going to start coming up like mushrooms. The big companies are going to be like whoops. So, so, I think there's going to be one of the biggest redistributions of equity that have ever happened. That's a good thing. We're going to see all these companies, these big companies, basically shrivel up, you know, they're going to be, quote, unquote, right sized. It's going to be incredibly painful, because a lot of our, you know, a lot of our savings for retirement are tied up in these big companies. That's a scary thought.

Dave Erickson 35:44
Yeah, all the pension funds, 401Ks, all that stuff. Yeah.

Ari Block 35:48
So, so, you know, we're going to be all of us are going to be hit with our pension funds. We're all going to be hit with our market values. But on the other hand, you know, this is going to be one of the most massive redistributions of equity that we've ever seen, since the printing press, since the wheel, since the internet, since the.net since everything.

Dave Erickson 36:08
Yeah, you can look at it as a bright future ahead of us, or you can look at it as darkness and but it, changes on the way, and people don't like change, but change is on the way, and we're all going to have to figure out how to survive and, and prosper. So hopefully we will be able to do that, and hopefully businesses will be able to figure out how to pivot with all these changes. And some will and some will not.

Ari Block 36:38
This is true, but there is light at the end of the tunnel. And you know each of us citizens and kind of muggles, you know people not in power, call your Senator, yeah, ask them what the world is going to look like in 10 years or 5 years, and ask them, How do we prepare for that?

Botond Seres 36:58
Usually, I would ask, what is the future of AI? But I think we have discussed that to great lengths already. So circling back to the beginning, we were talking about pivots. So what do you think the future of pivots is?

Ari Block 37:14
The problem is that the fundamental economics of the world is changing. So there's this idea that we talked about of the barrier to entry is fundamentally changing. There is no barrier to entry in software, at least, there won't be in a couple of years. So if we've changed the way that economics works, I just don't have the equations. I don't have the math to calculate how to operate. So what we need to do is we need to take our existing equations, and we need to remove software as a factor. So if we think about software no longer existing as a factor, then we're left with stuff like eyeballs, branding. We're left with stuff like markets. And then we also like, Wait, hold on. But if anybody can build software, then, won't they? Well, I think some of them will. So now we have every b2c non platform company in the world building their own platform. So hold on. Do we not need b2b platform companies anymore? Well, some of them will stay around, but many of them won't. So the fundamentals of the world are shifting in a way that I just can't, I just can't, I just don't even know what's going to happen. And it's happening so fast that even if I say something tomorrow, you know, the day after, I'm like, Holy shit, I was wrong. So, I mean, you want to set me up for failure, man. Like, that's the question to ask me. But I think the question is important because the answer doesn't matter. And I think if we all ask ourselves that incredibly important question that you actually asked that is such a more valuable thing than trying to answer it.

Dave Erickson 38:53
Well, Ari, thank you for working with us and having this conversation. What are you currently doing, and what are some of the things that you're working on?

Ari Block 39:05
Well, I am incredibly concerned about my communities, so I have created a nonprofit which is entire objective is to teach people AI for free, and what I'm hoping is, if we can get enough of the community actively understanding AI, understanding its pitfalls, understand how it's growing and will continue to grow, then we can create a resilience in our community. So, you know, I'm really, really invested in this, you know, emotionally and financially, and our first training, free training of AI, is going out pretty soon. And if you're in some way, if you're in some way, supporting your community, that means if you are a firefighter, a police officer, or even if you work for a church. If in any way you support your community, even if you're a rotary chapter, right, anything, if in any way you are supporting your community, you are welcome to come to one of my free trainings, and, you know, money back guarantee if we don't blow your mind. Unfortunately, it's free, so there's not much money to get back, but nonetheless, money back guarantee, if we don't blow your mind, blowing your mind is guaranteed.

Dave Erickson 40:28
And how do people find this?

Ari Block 40:31
Yes, so you know, we created for the purpose of the heroes that put their life on the line to save us, the firefighters I have named this company smoke eaters. Smoke eaters, yep, so you can go to smoke eaters.com, sorry.ai, or you can go to my LinkedIn. Either way, you'll find it. And then there is a current event that's going to be coming up pretty soon. I'm going to double check the date real quick, but basically, you can join the first smoke eaters training, and you can basically be part of the revolution.

Dave Erickson 41:17
I look forward to it, and I have, I'm a mountain bike team coach, and most of the other coaches happen to be firefighters, so I will let them know. And I think that's a great venture to try to do. It'll help the community a lot.

Ari Block 41:35
I think that's all we can do is right? We can help each other to get through what's about to come. And you know, if all we do is make ourselves of service to others, I will guarantee you will be happy in your own life.

Dave Erickson 41:50
Great. I think that's very good wisdom.

Botond Seres 41:53
I'm really looking forward to hearing more about your experiments on getting determinism out of non deterministic systems, or, well, clusters of non deterministic systems.

Ari Block 42:04
Absolutely, we have a, we have a group of people that are on the, the name of the group is kind of ready, is not one, I would like to say online, because it's very hubristic. What we what's not me, but what we've called ourselves is kind of very flattering, so I'm not going to say it online, but this group that comes together are all working on this project basically, and all working individually, but sharing the research results. I am on the verge of creating a very small example of this working. So basically, what I'm working on is, you know, the equations that you saw behind me is going to create a deterministic data analysis tool. So basically, I'm very close to having a deterministic data analysis tool. That means you shove data into it, it gives you a right answer, full stop. So that's the project I'm working on weekends, because I actually do have a day job. But then other people are working on the craziest stuff. One of the people has actually uploaded his stuff online. The rest of the group told him not to do that because he's crazy, because he's created something incredible. But he's actually uploaded online, including the source code. And what he, what he is working on is, actually, is actually AI agents that morph. It's incredibly intelligent, like this guy is, is off the charts intelligent. And the way he's thinking about morphing AI is, is, is just something that is amazing. So, you know, I'm pretty sure that if it's not our group, it's one of these, you know, one of many other groups are going to figure this out and bring it to the world pretty soon. The problem with AI is that it accelerates itself. That's the problem. So, so we can't predict timelines around a system that is self accelerating in a pace that we don't understand what the current acceleration is. So, all I will never again make a time prediction around AI. I'll never say it's, it's foolish to do that at this stage. It really is. I've made so many mistakes saying, Oh, this won't happen for a year, happened next month, Foolish.

Dave Erickson 44:24
Well, Botond and to the listeners, if you wish to follow the developments of this, you can find Ari's LinkedIn late link in the description of this podcast and connect with him. And I'm sure Ari, you're going to be putting stuff on your LinkedIn that will allow people to follow this Ari, thank you so much for being on our podcast and discussing AI and its possible future.

Botond Seres 44:49
We are at the end of the episode today, but before we go, we want you to think about this important question.

Dave Erickson 44:54
How are you going to use AI to grow your business?

Botond Seres 44:58
for our listeners? Please subscribe and. Notifications to join us for our next ScreamingBox technology and business rundown podcast, and until then, think about how you might be able to build a business.

Dave Erickson 45:10
Thank you very much for taking this journey with us. Join us for our next exciting exploration of technology and business in the first week of every month. Please help us by subscribing, liking and following us on whichever platform you're listening to or watching us on. We hope you enjoyed this podcast, and please let us know any subjects or topics you would like us to discuss in our next podcast by leaving a message for us in the comment sections or sending us a Twitter DM till next month. Please stay happy and healthy.