Your Transformation Station - 101. Game Theory and Marketplaces

Episode Date: March 3, 2022

Favazza and (Noah Healy) hits on many topics, one being..breaking of glass is which change? Entropy. "Coordlink" is an innovative company, what exactly that is, is a bit complicated. Noah is a professional algorithm developer and recreational mathematician who is an expert on game theory and designing marketplaces. PODCAST INFO: Podcast website: ⁠⁠https://www.ytsthepodcast.com⁠⁠ Apple Podcasts: ⁠⁠https://www.ytsthepodcast.com/apple⁠⁠ Spotify: ⁠⁠https://www.ytsthepodcast.com/spotify⁠⁠ RSS: ⁠⁠https://www.ytsthepodcast.com/rss⁠⁠ YouTube: ⁠⁠https://www.ytsthepodcast.com/youtube⁠⁠ SUPPORT & CONNECT: - Facebook: ⁠⁠https://www.ytsthepodcast.com/facebook⁠⁠ - Instagram: ⁠⁠https://www.ytsthepodcast.com/instagram⁠⁠ - TikTok: ⁠⁠https://www.ytsthepodcast.com/tiktok⁠⁠ - Twitter: ⁠⁠https://www.ytsthepodcast.com/x⁠⁠ - Pinterest: ⁠⁠https://www.ytsthepodcast.com/pinterest⁠⁠ - Linkedin: ⁠⁠https://www.ytsthepodcast.com/linkedin⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

What about the consensus as far as with this system and what people are putting into it? It gives us real-time analytics to understand the exact, precise amount of people on the planet and everything on everything if we were to really maximize this. Well, that's, yeah, that's the, at the maximization, that's sort of the libertarian fantasy of everything. being marketplaces. The market is a super intelligence. It's a lot of human brains working together to get this information that's better than any individual can have.

How can you create a transformation in others if there's no transformation in yourself? Join your host, Greg Favaza, as your voice on the hard truths of leadership, Your transformation station connecting clarity. Connecting clarity to the cutting edge of leadership. As millennials, we can establish change, not only ourselves, but through organizational change, bringing transparency that goes beyond the organization and reflects back into ourselves.

Extracting, actionable advice, and alternative perspectives that will take you outside of yourself. All right, Noah Healy, welcome back to your transformation station. Yes. Feels like I've always been here. I still don't understand what this system is because when I think of something, I need to almost envision a physical essence in order to really pick apart this description that I'm thinking of. Yes. And that's one of the basic challenges.

that's going on, this is a lot like an arch. The, you know, architecturally, arches didn't exist for most of human history. And then sort of somebody figured out that if you just had this keystone,

you could sort of lean two columns against each other and they would hold each other up. Trade is an archer. type behavior, having a marketplace as a common point for buyers and sellers to come together, that sort of buyers and sellers can hold each other up in that trade structure. What I have found is a three-way arch, which allows separating the buyer and seller concerns in two pieces, the one of price negotiation and the second of, of physical exchange of goods.

And the keystone is a more complicated object in order to balance the needs and products available from these three sides. And so that's my basic challenge is sort of describing the structure of this much better keystone. that's a really interesting way of putting that with the arch that now like looking at the the graph that makes a lot more sense when I tried to envision that way but before we get back into that can you just give our audience a little bit about yourself a little more about your history your education and understanding that led to this creation of this the system that you've created Yeah, sure. So I've been fascinated by math basically my entire life. I started at the local college, University of Virginia, in my junior of high school because the various pilots of advanced math systems actually meant that I'd finished high school mathematics in my sophomore year. And then I sort of transitioned almost. I almost transferred from high school to college, continued my education there,

and wound up in the engineering school and didn't really have a specific life plan in mind. But like math, knew I was really good at it, and figured engineering was sort of a good fit for that talent structure. Bounced myself into the nuclear engineering program basically just because one of the deans that I knew and knew was a good teacher was teaching an introductory class, the department itself had been dissolved the year before I became a full-time student, but it was still around and some of the classes existed. And the nuclear engineering is the most comprehensive branch of engineering that exists.

It's got mechanical, electrical, civil, um, computer coding for for various pieces and then another whole bit of radiation and so on. So there's this sort of mass mortgage board of things that you get to learn about. And so that was kind of what I was doing there. And then I got out and got working in dot coms and then other tech startups around town. And got into computers. Nice. So it's like a dismaline, God, I always fucking struggle with this word.

An interdisciplinary approach in all aspects of mathematics. Yeah, yeah. And that's a thing I've always, I guess, had a facility for and also an attraction towards. one of the things, as you learn about the history of mathematics particularly, you learn is how much cross-pollination effect and how much different things are when you look at the right way, really exactly the same thing. So going back to Lake Descartes and the analytic plane where Euclidean geometry and algebra are shown to be essentially the same subject, just by using graph paper. And those sorts of insights where you can learn something and apply it effectively everywhere

is to me, and not just me, this is sort of the philosophy of science, is what math is really great for. you know, the fact that how you cut up, you know, how you cut up, say, food to serve it out like a lasagna and how you can divide up land is exactly the same set of techniques and tools, even though land and lasagna are basically unrelated things, is really important and would then also apply. in many other contexts. And so when I learn about things, I try to dive into them to that mathematical level and both to understand them more thoroughly,

but also to sort of pick up whatever gems might be there that I could then. Let's get back to this. So with your CDM and how it works, the simplest description that you defined that I'm looking at your little map here online, It's down to four individuals, which is the producers, the consumers, market, and forecasters. And there's a start to, let's see, close of trading window and then trade resolution.

That would be the market actions less than one second. Now, if we were to go into that, the first part you were going into was starting at the market. And that would be a published price of information where the consumers can get a baseline of what is a reasonable price. And then the market, which is the published price information, which is sent to the forecasters. And let me finish the initial part when I said the market price where the consumers can see it, that is published towards the producers. Is that correct? it's published so if you see there's actually sort of three arrows coming out of that part of the map so it's actually that information is published to everybody everybody gets to see that effectively at

the same time because it's stable over a long enough time frame that you know if you get it one microsecond before i get it it's still the same when i see it and it's going to stay that way for minutes or more usually hours or days. So if I get up late, I can still see the same deal that's on and decide how I feel about it. Beautiful. So we were talking about it a little bit earlier. We were touching on it. With the market and sending out this price, who is the deciding factor that this is the price it should be?

No one person can guarantee being the deciding factor. this is an integration of every forecast that is willing to put their money where their mouth is. So how would that happen? So that happens within the market space. There has to be an interface where people can basically plot out what they think they know about the future. So this could be a full curve of, you know, every day what the price of corn is going to be for the next 10 years, if you're insane. This might be somebody that thinks that they know what happens on Valentine's Day and it's just February 14th thing it, you know, for a couple of years. this could be somebody who, you know, helps out members of the Fed and thinks that they know what

inflation is going to do. And so, you know, is moving three or six months or something around. These can be essentially anybody that is willing to invest behind their beliefs about the future. And what my system does is it uses this sequence of integral equations to integrate all of those different beliefs into sort of the single, not quite median, but approximately congenial belief of the entire group. That's really interesting, but it makes me concerned because I'm, I'm thinking about this. What if I, like, is there any standard guidelines that will, that will keep people in check when they are doing this? And if there's not, would there be?

Because I feel like if I wanted to manipulate the system, I could. So you could attempt to lie to the system, yes. And, and you can attempt to lie to the systems that presently exist as well. In both cases, the penalty is similar. it's very costly to lie to the system because the system as a whole has more information than you do and is looking for the truth. And so it punishes people that are wrong whether they're lying or not. It's also completely independently of how this thing goes on. It's illegal to intentionally lie to the system.

Now, right now, that's something that can't. really be prosecuted because it's fairly difficult to detect. However, within CDM, a lie about, you know, three years from now isn't that big a deal. The world has a long time to sort of figure out that you're lying and go in and correct the record. The material lies would be both large and short term within a CDM. And those are both extremely expensive and, if successful, extremely detectable. And so intentionally lying to a CDM is not only economically ruinous, but also physically dangerous because it's against the law.

And the proof would be trivially easy because you essentially have to say, I think this thing that's obviously false. And I'm going to spend billions of dollars to make you believe me. And then have it be demonstrated to be obviously false, at which point your billions of dollars help ameliorate the costs that you imposed on everybody. And you go to jail. Okay. Let me just explain this.

The CDM, that's a coordinated discovery market. and that's based off a core disk with your business here. Now, you did touch on the very last statement there with people that were to invest money to try to, as much as they can to get people to believe in them, even though it is a lie. But, okay, now there is a, there's some backlash that would happen and he would go to jail. Now, how do we make this actually a solid system and not just actually fundamental? Well, so that's one of the things that's interesting is that the solidity comes from the participation. So this requires at least 50 people to be using it to work.

And this isn't particularly unique. The existing markets require this competitive nature of buyers and sellers to come on in order to regulate them. When they lose that liquidity, their marketplace falls apart. And in fact, there was an incident around six or seven years ago where the beef market market had. become so thin that a single traded contract actually shifted the entire marketplace by something like 10% or, I can't remember exactly what it was, but it was an incredibly large number. So, you know, imagine if somebody sold one share of Amazon and Amazon went from being a $2 trillion dollar company to a $1.8 trillion

company as a result of that single share selling, that happened to the beef market. So is there a, how do we, I'm trying to look at the integrity behind that because that's why I was trying to frame earlier and I just didn't, I couldn't get it out.

So between that and the stock market and cryptocurrency like how do we maintain that structure where we can do that? Well, so marketplaces and this again, Adam Smith, rest integrity on self-interest.

And there are both theoretical and empirical economic modeling from game theory and history to demonstrate that relying on individual self-interest is pretty rock-solid. People cannot

always know or act in their own immediate interests but by and large on average we do a pretty decent job of wanting what we want and doing what we do

in accordance with those desires and so within a CDM yes within a CDM a person who's telling the truth about what they believe and acting in their own best interests based on the information that's presented to them will have the highest rates of return that are possible within the CDM for them.

And those rates of return will be significantly higher, whether you're a producer, a consumer or a forecaster, than what you can achieve within the existing marketplace. Now, let me ask you this. Is there a second system in line that almost challenges the consumer's choice? Because I know we're, I mean, fucking our emails are collecting a shit ton of stuff on us as we speak. So I'm just, I'm looking at it as, okay, if this individual is deciding to do, to go down this route, but the data says he is not.

Would it challenge him or would it actually let the producers or the forecasters alter something within the market? So in the commodity space right now, it's very much about free choice. In my system, if anything, the choices are even freer, because existing commodity markets in order to get price discovery out of their trades essentially force people to lock in trades into the future. And I'm not even doing that. However, what you're talking about is what I call the retailization of the economy.

And that's something that I think is very clearly dangerous at the political and social level. It's obviously highly remunerative for the people doing it, which is why they're doing it. You know, Google and Facebook and even Amazon would much rather, you know, ad buys be how all material on earth is transacted. But the, so commodities are a low margin business with a lot of competition, which any business school will tell you don't get into. But the compensation for doing that is that basically no marketing budget. If you grow X, then all you have to do is hump it down to the market for X.

and they'll just buy it from you. You don't have to find, you know, who likes these little goo gauze or whatever. Whereas if you are in the retail space and you make a new kind of pot holder, you've got to fight for market share in the, you know, cutthroat world of pot holders. So the marketing people

who have sort of eaten the business world think that that's great, that everybody should have, you know, a multi-billion-dollar marketing budget to fight for market share within the whatever, but our lives are based on the ubiquitous availability of high-quality raw materials. And if the marketing people manage to change things like the oil, steel, wheat, rice, beef, fork, markets into the, you know, toy drapes, those markets, the loss of economic efficiency would be probably sufficient to end the political viability of states in their current form.

Interesting. Okay. So they're trying to do that. It's incredibly difficult and they are mostly failing. We should celebrate those failures because if they succeed, it's going to be extremely dangerous. But they are trying to do that. I'm working on a different system of trying to make the sort of high-quality raw materials system just function better. Okay.

And we'll pause that. We're going to pause that. I want to make sure we get the, this system down first and keep people. Okay. Yeah. You have a lot of great information. I love that.

All right. So now from the start phase, we already explained that. Now, this is the close of the trading window. We have a market that's sent to the forecasters. The forecasters will commit to future price updates. Then consumers will commit.

to the purchase and then producers offer to sell. So then from there, that all intersects and everybody meets at the market. Right. So people have to update the market with their own desires. This isn't some sort of predicting human behavior thing. This is a aggregating and managing human behavior thing, which is a subtle difference. So the commitments, starting with the forecasters, as you did, are basically what I'm doing about the future. What the existing system does about the future is it actually commits to trades in the future.

I have this commitment to price information about the future. Wait, so if it doesn't commit or if it doesn't predict human behavior, to me, it sounds like it does, like with, like does it collect psychographic data? So it doesn't predict human behavior, humans and other external systems predict human behavior. What it does is manages a reward package for those external persons or systems. to filter out the best of their work and put it together in a way that can be universally accessed. Like operative conditioning? So that's interesting.

It's actually something called evolutionary game theory. And what evolutionary game theory basically says is that Because operant conditioning is a real thing, in an environment where individuals can sort of take on this role-based game behavior, the entire game will equilibrate at the Nash equilibrium, the point of game optimization, because it's, in the interest of the individuals to sort of do what they do. And the ones whose actions aren't contributing towards national equilibrium of behavior, offering conditioning will kick in for those individuals and essentially train them either to leave or change their behavior in ways that caused the Nash equilibrium to become dominant. Let me ask you this. This is a really good thing you brought up.

With contextualization, do you feel or have you noticed in the population that there's a possibility that we might be lacking and understanding in contextualization? And we are not grasping the concept of these core principles within mathematics within. English, within what our school system was teaching us because the way that they were trying to make us adapt to learn this system was flawed and how they were trying to teach us. So my institutional issues are a little more fundamental than that. I think that, and this will monologue for just a couple of phrases, but computers are a bigger deal than steam engines. Steam engines ate the world.

Like, it's incredibly difficult to point to a presently existing institution that exists in the form that it did before Steam engines did. And sort of, if you don't believe me, imagine a debate between Elizabeth I first and Elizabeth the second on whether or not there had actually always been in England. because I don't think they'd be on the same side. So computer technology, the communication technology that it's enabled, the other sorts of technologies enabled,

the sorts of technologies that it could enable, to me suggest that the assumptions that are built into our institutions, whether that's cultural or political or economic or anything have been falsified. And attempting to move forward on a false premise is just a waste of time. Oh, all right. I got to stop you because this is where we, this is the best parts of all the podcast is when we go into organizational culture. And we look at that understanding on how organizational leadership is making an effective culture today or is attempting to or lacking the effective culture. And that's what they're trying to achieve.

Now, I feel like they are lacking the fundamental decision making that follows transparency, but also balance. transparency and I would say focused training where they understand that employees, everybody within an organization understands exactly what their role is, but actually can grasp it from a in-depth concept like mathematics where if they just taught their employees like employees like that, the system will flow naturally. That, so I would, I would say that's a true statement. I would say that that's so challenging that it's not a realistic goal. The thing that coordination discovery markets are based on is a thing within game theory

that I appear to have discovered that I call negotiation. games, which is that coordination games, which are a well-known idea in game theory, can be modified with essentially an extra player that can be a computer program because the extra players is wholly determinative. And the game plus that extra player will change its long-term evolutionary structure. and that's essentially how my sort of cordless company, the marketplaces that I'm talking about, that's how they function.

The market operator is essentially writing the code and playing the game of that extra thing to cause the marketplaces to function as marketplaces, but do so less expensively. These negotiation games are potentially available in many, many contexts, but the downside of this negotiation game approach is that the difficulty of solving the underlying problem

increases hyper exponentially as the number of roles being considered increases. So if you sort of wanted an idealized, perfect organization, on the scale of, you know, a transnational, some organization that has like 100,000 or even a million employees, all of whom understand their roles and are pulling in a direction that's organizationally valuable. The mathematical problem that I have identified that solution of which would allow you

to build the system that would do that thing would have two to the half trillion factors, if you will. So two to the tenth is about a thousand. So that would be a number with about 50 trillion zeros. That's totally impractical. like that we don't know what that is. I do not see a world in which we would ever solve problems like that.

And so what do you see with your system that you've came up with? Is there a way that we could look at, let's say, an organization, the hierarchy looking at a vertical level. If we were to put in dependent, independent variables where we look at the behavior, the perceptions, the influences of management and the changes within the market, could we somehow predict how the company will run based off our understanding? The win, and the win is enormous because of this hyper-exponential nature is in defining useful roles within the company. And so creating a system. So, like, within coordinated discovery markets, we've been talking about this sort of four-player game that is the marketplace. But obviously, markets are actually being used by thousands to. millions of users. It's just that there's four roles within the game that they're playing.

If you have this million-person company that has a problem that has, you know, 50 trillion zeros worth of difficulty in just figuring out how to solve a problem, that's insane. If you could reduce the scope of what you're doing down to 10 roles, that the million people are involved in, possibly at different levels. Then those 10 rolls problem would still be insanely hard. It would be on the order of 30, 40,

what? That's quintillion, quadrillion, sorry. 40-ish quadrillion. in terms of difficulty, which is still mind-boggling, but you might get lucky. Well, sometimes the problems actually have easy answers. I've got some stories about that. But in contrast to, you know, of like 40 quadrillion versus a number that has 50 trillion zeros,

you've made an enormous strides. So if you can do that, if you could define sort of 10 roles within your system that we're interacting and then provide something like that. Or if you could just define certain valuable things to learn or know about yourself. So there's a very simple negotiation games you can build to just extract single points of information.

So if scheduling or budgeting projections would be valuable to your company, which would be valuable to most companies, much simpler games could be generated to allow your employees to collectively and anonymously tell you the truth, something that you might be interested in. Yes, okay, now don't go any further here.

All right. Yes, this is a game theory and we are playing off this the CDM and that is the coordinated discovery markets. And what we're looking at is it's a formula, a malleable formula where we are going to try to integrate the context and what we're going to go into. And what I'm curious about is if I, let's say if I were to have everybody in my company fill out a 24, hour time wheel of how they would spend their day and what that time would look like. And if I could look at everybody's time wheel and see exactly, all right, this is how their time's being spent.

I can almost pull out the most like important factors that are actually causing, say, an issue in, am I hear myself echo? No. Okay. causing an issue within the system when because I really feel like with organizations, they're always, they're not utilizing their resources properly.

Well, that's, that gets to something called the theory of the firm, which basically says that the reason organizations exist is because it would be so expensive to generate markets that replicated their notions that in spite of the fact that the organization isn't actually making decisions all that well, it's if you factor in the cost of getting better information, it's making decisions well enough. Yes.

And so that's what gets into things. But yes, the difference between sort of great. teams. Things like the Walt Disney era animation or Pixar's ability to essentially just become a hit factory for, you know, in Pixar's case, decades now. Or NASA, once the Kennedys came in and they were about to get their funding hamstringed, you know, there are, or, there are, or or Los Almos and the gathering of, you know, everyone who won the Nobel Prize in physics, basically, to build the atomic bomb. There are collections of extraordinary people, and there are collections of people that sort of punch above their weight class, and there are the combinations of those two things together, and the capacities of those, of those events,

are miraculous. It's amazing what can happen. And so it's easy to say, oh, I would only like to be involved in things like that. And that choice is a hard one to make. There's a story from, I think it's Bell Labs. And there's a guy named Hilbert, who's not the famous David Hilbert of the 19th

Century Mathematics, who was there, and the lunchroom tended to be very clicking. You're monologuing. I'm sorry, but let me get the story out, because this is good. He would go around and he would talk to newcomers, and he had three questions. What is your area? Second question, what's the most exciting and important work being done in your area? third question, what's your work? And very frequently, people weren't doing the most exciting and important work in their area.

You know, like they were afraid or didn't have the resources or whatever. And it was, it's a challenge. It's like, well, if you know what the right thing to do is and you know you're not doing it, and it's put to you that boldly, why aren't you? doing the right thing. And that's, that's a, that's sort of a personal challenge of your, you know, mental toughness or spirit or whatever. And that's, for leaders, that's, that's the, that's the challenge that confronts them if they

wish to face it, which nobody's going to force you. You're a leader. Well, put on the end right there. That's really good. From what I've understood in my research and trying to finish up this remaining year in organizational leadership, my bachelor's, it's coming down to commitment and transparency and just the decision making within the system and applying a deep context and teaching your employees, actually giving them real knowledge and understanding of. concepts that will take them, that they can carry forward into their next line of work and not just at a meaningless job. Because I feel like, well, you're describing earlier, that's employee disengagement because they don't really,

it's all surface. I mean, it's like basic conversations. Okay, you just do this and this and you're fine. And nobody will notice you. You just do that. But. Well, again. It's going all the way back to sort of invisible hand.

So first off, not everybody in fact wants to be noticed. But invisible hand, the point Adam Smith's making and the point of other things is that people are being driven by their own self-interest. And so in a meaningless job, the self-interest is the paycheck. You know, I'm here because I want food and shelter. I can collect a paycheck and require food and shelter. Or experience to get into a promotion that is required. Yeah, or something, you know, whatever it is, it can be a lot of different things. And so then they are going to be disengaged.

Like the job is irrelevant to what they're receiving from it. But making jobs relevant is itself a difficult task. Yes. And I feel like it comes down on the cost. culture. I mean, we're looking at fucking with Facebook and how that shit came out and understanding that there wasn't any transparency. I mean, I feel like if they were to just told us, hey, we are controlling and manipulating the system here. That would you be okay with it? And they're opaque like from the jump. Consider how many highly successful, you know,

litigation events occurred during the financialization of Facebook, including my favorite one of all time, that the guy with the cocktail napkin. As Facebook was going public, this guy showed up with a signed contract from Mark Zuckerberg that Zuckerberg had gotten this guy to give him, I think it was $50,000 in order to build Facebook. in exchange for a very small stake in the resulting company, but which would become a controlling stake if Mark couldn't deliver by, like, January or something. And Facebook launched in March, and I can't remember the exact dates. So basically, that's what happened, you know, approximately, that Mark missed the thing. So this guy had a signed contract from, Mark Zuckerberg and said that he owned Facebook and the company was just about to go public.

And whatever happened in litigation, he went away and he went away with a very large amount of cash money. And yeah, Zuckerberg essentially must have lied to every single. person he worked with forever. Yes. He's developed that fucking popularity. Right. Because, you know, nobody would have invested in a company that was actually owned by some guy

who's, you know, got a cocktail napkin with his signature on it. Now, let's look back at here with your system. I got one more question and then we'll go into it. You mentioned a lot of great people in history that made an impact. in society. Now, with this game theory system, what if we were to able put, almost take in the context of their, of their thought process and a decision making that they would make and input it into the system?

I think it'll take a long fucking time. But if you had enough manpower to do it, do you think we could come to an understanding where society should be at versus where. we are actually at. I think the single greatest miss in terms of our potential is underutilization

of brain power. The human brain almost nobody's too dumb to see. The amount of, if you think seeing is an unsophistic process, talk to some computer vision people sometime, because it is not. And so there is an

extraordinary amount of processing power available, not just in the chips and silicon, but also between our ears. And we are using, you know, in round figures, none of it. Now, coming up with sophisticated network coordination systems is, in fact, incredibly difficult. And there's also a lot of moral and ethical and philosophical issues with so-called super-intelligences. And that is all for us to navigate. And none of the systems that we have are concerned with navigating them, which is, I think, one of the reasons why. those systems don't have much of a future. Interesting.

Okay. But the degree to which we can create systems which which allow people to improve their, pursue their goals, I think is the best way to put it. By improving the well-being of the system is the degree to which we will be able to move forward the potential of societies, companies,

communities. I like that. I really, I really like that. Now, let's go back into this here. When we initially started off, we started,

we have the producers, the consumers, the market, and the forecasters. Now, this is the four, uh, aspects that make up this

this arch that you were elaborating on the last episode now with these four variables I want to say it starts at the market the published priced information the published it's sent out to the forecaster to the consumer to the producer

and then right back to the market with the offer to sell commit to purchase and to commit to the future. Now, at that very point, it almost ricochets right back out with, let's see, we have a send to the contracts that could send out and aggregate information and collect investments. Now, what, tell me a little bit about that part. Okay.

So supply and demand, hopefully match each other. It's sort of a disaster if people want to buy things and they can't or people want to sell things and they can't. So what the system does is it batches up all supply and demand in sort of one go and then matches them all out against each other. And that's how it can maintain a stable price across all the trades that it engages in. So if you trade, you'll trade at the price that's published. And you will trade as long as you're either sort of below average or on the side, which has matches for all this demand, which if supply and demand match, everybody on all sides will be at that level. And we use this bottom-up settlement strategy where essentially we try to fill the first,

item of everybody's order and then the second item of every's order and so on. And so what that does is it minimizes the marginal cost of misses. So it's it's not the struggling farm family that can't make the one and only trade that means that their kids can't, you know, have socks to go to school. It's the, you know, factory farm that owns half of Kansas that loses one percent of their trade today and can then sell it tomorrow, which isn't ideal, but isn't as costly as the hedges that they currently have to engage in. So they're still better off. Then the second part of that is the integration.

That gets into how we take different people's beliefs about what the future is going to look like and integrate those into a common belief. And that comes down to measuring how much information is in each one of their stated prices. And doing a computation determine what the effective median of those beliefs are. It's slightly different than that, but that's the simplest way to think about it. And consequently, how much each. of those information segments contributes to that output value of the sort of common belief of common beliefs.

So would the, is the, say the news, like, I didn't want to bring it up, but could the, like, something that was just published on the news, couldn't or brought live, could that impact that system? Yes. Yes. So that, that happens right now. And it actually goes the other way around, you know, CNBC is an entire news network that is essentially dedicated to describing what the markets are doing. Marketplaces are a lot of different things, but one of the ways to think about them is that they are the world's most reliable and valuable news source.

the Austrian economists did the work on this, and they basically point out that in a functioning price discovery system, price is 100% of the information that you require to operate your business decisions. Interesting. I like that. Something like the price of oil, you know, the conflict in Ukraine, the availability of oil, transportation, and production all around the world has an enormous number of incoming factors. But basically just by looking at the price of gas, you can decide how much to drive your car.

Yes. You don't need to comprehend the entire physical universe and how it's interacting with itself. the price alone is enough to give you that information. And the price is two-sided. The price alone is also enough to give Exxon, Mobile, and Shell, and so on, enough information to determine how they should put together their strategy for transportation, extraction, refinement, and so on. So price is this sort of two-sided piece of information that enables the invisible hand

to function. Beautiful. Well, put, I like that right there. That made it so like

comprehensible right there, the way you put it. So is this like a representation of the stock market or a creation of crypto,

something. It just seems too this is an alternate way to build something like a stock market. Once again, going back to history, the price discovery mechanism that we use right now is traceable to the city-states of northern Italy, which launched the Renaissance.

And the reason they were able to do that is because they suddenly got very rich. And the reason that happened was their price discovery mechanism, the one we use right now, was so much better than the one being used everywhere else that they became the hub of Mediterranean trade. and they did this without armies. The existing hub of Mediterranean trade was located in Constantinople, where the Eastern Roman Empire was still a thing at that point. And they had radically better strategic position, radically better location. They had armies.

They had vastly deeper culture in history. but their economy didn't work as well. And so people who wanted the best prices and the best planning would hub out of places like Venice and Genoa. And when people's self-interest is aligned in a particular way, that starts tending to happen. This is an algorithmic advance on that system. This is a different way to achieve that same goal that costs less money, less time, and less effort. Okay. Now, what is your main concern with digital currency space, including this marketplace?

My primary concern with the digital currency space right now is the algorithms don't have a long-term time plan. Bitcoin, the grand mac daddy of everything, is dependent on its hashing algorithm and doesn't have a reasonable way to shift hashing algorithms in a sort of retroactive fashion. Well, hashing algorithms break. This one isn't likely to break anytime soon, but we definitely don't have a theoretical justification for believing it will never break. and sort of they all tend to break eventually. So if the hashing algorithm that underlines Bitcoin, if somebody figures out what's broken about it, then that's the ballgame.

And unless your chain is multi-hash resident at all times, which is very expensive, which is why nobody does it, then you're vulnerable to that. And what is now? What is multi-hatch? Well, so imagine if you will, multiple parallel blockchains. Okay. That were all operating on completely different tech stacks.

So that a flaw that existed in one tech stack could take out one chain, but then the rest of the chains would remain alive. So let me pause that. Let me try to relate it to our listeners. I'm looking at it as a data warehouses that are located all across the United States. If we were to have a natural disaster or a powder outage that took out maybe two or three states worth, that would be fucking horrible. But then all internet information metadata would get pushed over. to different servers in different parts of the states to allow the individuals to bring the power back up and get those data warehouses back.

And that. Yes. Yes. Yeah, yeah. So it's a foundational of reliability. The really only way to acquire reliability is through redundancy. And redundancy is expensive. Beautiful.

That's what we needed to hear. Thank you. I love that. Okay. So now we're on the trade resolution. Now, this is going into, yes. Yeah, I was just talking about how trade resolution or actually, no, I think, keep going because I was talking about contract sending. Yes, trade resolution is slightly different.

Make a delivery, confirm delivery, and make a, where is this, payment based off commission. and right, because of the end of the contract. Yeah, we covered that. Well, sort of. So the notion is that the marketplace collects commissions on the trades that it's managing. And then from that commission, because it is measured how much useful information that individual forecasters provided that integrated outcome. it can actually precisely cut up the pie of both the investment pool and this incoming commission pool. And so you get rewarded as a forecaster based on the fraction of your useful information as a percentage of the total useful information that got inputted into the system.

So to go back to last time, when you were talking about, what if I just lied to the system? Yes. Your lie is purely useless information. And so the system can essentially measure that out as of zero value providing you with zero percent of the outcome. And the useful people who either are correcting your lie, essentially will get paid by your own investment for correcting the record. I like that. Is that also bring up the, say, if we were to look at the lower population, lower class,

does that give them more of a fighting chance to actually get a return on their investment? Yeah. So the way this functions is that the ROI is based on a parameter that the operator sets and the amount of your forecast that is valuable to the final outcome. And so everyone capable of the same level of accuracy can get the same ROI within the system, which means that since, the producers and consumers themselves have some degree of knowledge about the system, it is possible for them to not make huge investments, but make small investments around their beliefs, have those beliefs aggregate together, which definitionally has all of the information required, because what the producers and the consumers collectively think the price is, is what the price actually

is. And so they can invest in this positive sum high rate of return system at a very low level and still get the price information, which is what the marketplace cares about. And the only way to sort of short-circuit that would be for a sophisticated investor to be able to anticipate before they could know what they could know what they were going to know, they would have to sort of know ahead of time and use up that useful information reservoir from the system. But if that were to occur, then the practical outcome would be marketplaces that were more accurate and more stable, which means that their primary businesses

now function better than they used to function at a lower cost. So it's for sort of the little guy in this high competition environment, it's pure win, which is exactly why it's, how it's designed to work, because the value of the commodity marketplace is its allowance of little guys to survive in low margin environments as a reliability mechanism so that when you go down to the lumber mill, they're never out. Because if the foundational product, are ever missing? Well, like in the 20th century, we saw this happen repeatedly in China

and Eastern Europe, Soviet Union, and so on. What about recently with, let's say, the housing? Yes, yes, the supply chain disasters as well. Yes. It's tremendously damaging to an economy not to be able to find its base things. Yes. Now, what are the, let's say, like a rise in current

or with the housing development, there was just not enough. What does the impacts of that have on this kind of system? So this, again, is a news system. So as these large social or biological forces move around, this thing's job is just to report what the practical reality of that is. If the practical reality is that the swiftly increase in global population means that the price of food is going to keep going up, then that's what it means. Well, wouldn't it project the price, though? Couldn't it project?

Yes. Yes, that it will. It will tell everybody that that's true and let people know that they should maybe consider getting into farming instead of getting into, you know, marketing because the price of food is going to keep going up. If, on the other hand, the increased population actually means that technical resources are going to be redeployed in ways that make the price of food go down in the future, perhaps stabilizing global population at some level, then it will determine and project that and let people know that maybe there isn't a guaranteed free ride in farming for the next century. and maybe you should just go into marketing instead. So I don't know what the future holds, but this system allows a market to explain to itself humanity's best ability to figure out what the future will hold for itself.

So I like that. And I feel like there's a lot more other things here that we are not getting into. What about the consensus as far as with this system and what people are putting into it? It gives us real-time analytics to understand the exact, precise amount of people on the planet and everything on everything if we were to really maximize this. Well, that's, yeah, that's the, at the maximization, that's sort of the libertarian fantasy of everything. everything being marketplaces. The limitation of markets and these kinds of, the market is a superintelligence.

It's a lot of human brains working together to get this information that's better than any individual can have. The limitation of markets, and this is very explicit in the case of my coordinated discovery markets, is that they operate on systems of voluntary cooperation. and voluntary cooperation is not the only way that things work. You know, some people are not so nice. And so war's happened.

Right. And even beyond that, some people are just sort of beyond the pale. Like, you know, Jeffrey Dahmer really was a cannibal serial killer. It's not just, you know, it's not just a fictional character. there's people that are actually evil and horrible and you don't want to have around. And so there's limitations to the degree to which everything can just be everybody getting along because some people don't want to play. And so markets are great. We should have better ones.

They are not a universal solution to human evil. They are a tool for creating accurate and valuable news sources. And I have an approach that allows the generation of low-cost accurate news sources for industries and companies and people that would find that, something interesting and useful. But, you know, some people are running companies in their kind of dictatorial asses, and they want to kind of show up and tell people, you know, push people around and tell them what to do.

And the people who work in those companies want to collect a paycheck and go home and play with their kids. And would we all be better off if there was like some sort of, dynamic leader that was that was inspiring people to come in and and yeah sure we would but you know that guy doesn't exist in that industry and and so we we've got what we've got mm-hmm no that that makes a lot of sense uh what other fintech news do you have that's relevant to your products today um supply chain is is increasingly getting looked at by fintech and that's that's something that has a lot of potential overlap with

improvements in in marketplaces existing marketplaces are are centralization points and that simplification is important but they're also very much based in specific locales so one of the issues with that is that something like a third of the volume on the CME group is actually sourced outside the United States. And those people actually cannot physically trade on the markets. So places in like Central Asia, although with the latest sanctions, maybe not so much anymore, essentially need to use the United States marketplaces in order to price their goods for trading with, you know, the next town. over because they need the market information.

But in order to acquire market information where you're not actually able to use that marketplace directly, you have to sort of buy into the hedge and then you have to buy back out of the hedge. And so there's sort of a double-dip cost that's associated with doing that. I feel like we gave everybody the rundown on CMD and how exactly that works. Because the final stage to this is the trade resolution, right? Yeah. Yeah, and CDM, coordinated discovery markets, not coordinated market discovery. Oh, shit.

That might be interesting as well. What companies are you working with now and what companies have reached out to you, if you don't mind sharing some of that? Well, some of us under NDA, so I can't talk about too many specifics. there is a company doing fundraising that's actually attempting to build an NFT-based marketplace that is using the NFTs as proxies for other financial instruments, which will allow essentially cross-border investment to occur without the regulatory overhead that normally be associated with that.

Wow. And their intention is to use CDM technology in the governance of their market system. So they're sort of doing at a higher level of having the system, a marketplace in commissioning costs and so on of their marketplace in order to sort of tune it to be a more sophisticated and successful. gotcha. Okay. Market. People that are really interested in this, this system you develop, maybe they are kind of in,

they're actually in the same pool and they're trying to develop their own system. What are some recommendations that you would make to, to people that are engineering something very fascinating or leadership personnel that want to step up in their game? Like, what would you tell them? Well, feel free to reach out to me. I'm happy to talk about these things. I'm also, you know, consulting services, if that's the kind of thing that you're up to.

But if you want some sort of reading on your own to do, I cannot remember the name, it's up my head, but the Rand Corporation actually put together this basically children's book level version of game theory that's actually fairly comprehensive and really helps. Other things that are pretty accessible are things like Parkinson's Law or the Peter Principle. I've mentioned Adam Smith several times. 18th century literature is a little weird to modernize,

but it's he's actually, I mean, you know, it's really well known for a reason. It's actually pretty readable. You go to the actual, you know, back to the actual texts. So to actually read that kind of literature, you've got to have that 18th century mindset. So would you actually look at, I don't know, diaries or personal journals to get an idea and then kind of read? No, read Treasure Island. Ah, yes. Treasure Island. It's a great read.

Get yourself into the set with one of the finest writers in human history. So, yeah, there's a lot of smart people in the world. There's a lot of people that are smarter than you in the world. Most of the people who have ever lived are dead. so most of the smart people who have ever lived are also dead and some of them wrote some stuff down so that's an enormous resource dig in

I like that well I do appreciate you coming on to your transformation station now Noah so I really do thank you for your time thank you all righty you take care You've been listening to Your Transformation Station, your voice on the hard truths of leadership. We hope you've enjoyed the show. We hope you've gotten some useful and practical information.

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