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My name is Mark Rubin, and I'm a dream weaver. I hope these widgets help you weave your dreams into reality.
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This is a story about visualizing dynamic systems that I've always called energy and information systems. I'm going to use some examples of this, as it relates to a marble, rolling down a ramp, and data flowing through a gigantic mainframe system. And then also through the ideas of business visualization. And it all works the same way. So I'll start this by describing what I imagined. When I imagined systems. I learned this from watching things move around me, and taking snapshots of the things that are moving in different positions and comparing them to each other. And noting rates of proportional change, how quickly things are moving. And our also listened to things and listen to a different sounds they made in different positions. And as it related to the rates of change of velocity, disability, there's modeling ability was useful, because I could see these relationships in visual spatial models that were color coded at snapshots in time. And I'm going to describe the models because what it is, is a model of cognition, or at least my cognition, which is a model of a way to visualize in a proportional way, the relationships between everything in a system at a snapshot in time, and then stringing those snapshots together to create a dynamic model of the system. And that's an energy and information system. So if you imagine a marble at the top of a ramp, at marble has a diameter, size. And let's call that the visual weight as the visual weight of the marble. And if you had a marble that had a diameter that was twice as big, the visual weight would be two times the visual weight of the original marble. And that's a way to know things in relative proportional ways. Without measuring them, like on a scale. One of the reasons I standardized on a particular size marble is it always did the same thing. And I had three different size marbles at one point. But I learned this to use one, because it always did the same thing. And if I mixed them up, they did different things, it would knock over a different number of dominoes from the same height. And I wanted to control the variables, so that I could build the models in my mind in a way that was not random. So I will control the variables by using a marble with the same visual weight
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in every experiment. And I will put the marble at the top of the ramp. At the bottom of this ramp was a Hot Wheels track for cars, I would lay down dominoes, and I would see how many dominoes gotten knocked over from different heights on this ramp. And I use the yardstick to keep the room flat. And I would put it in my drawer of my dresser to get the heights. So it's always the same was always the first drawer the second or the third drawer. And it was always the same way. point of it is at some point I systematize the thing and standardize on this experiment that I was doing. And so now I put imagine a marble at the top of this ramp. And I could see that there, let's say there were 10 dominoes at the end of the ramp that hadn't been knocked over yet. And I will let the marble go. And in my mind, I would be taking snapshots of it and position one which was at the top of the ramp. And maybe a 10th of a second later and a 10th of a second later and a 10th of a second later. And maybe not like maybe I just made that up and think that that's what it was. But I could interpolate okay between these things. So even if it was one second later, I could go backwards to see where it would have been before and then increments in between and fill them in quickly, and have these snapshots as it went down the ramp on the length of the ramp that I had, I might have 10 snapshots in my mind by the time
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they hit the dominoes. And the reason I started using ramps is because I couldn't do it fast enough when I dropped something and also wasn't repeatable. So I could slow
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down the motion of the marble. I put it on our ramp with different a different inclination different height and take these snapshots. I would also listen to the sound of the marble in the different positions. And I could see the intensity, the volume of the sound and a spatial model, like a circle that's getting bigger and bigger. The
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rate that that sort of goal gets bigger in my mind is proportional to the velocity. So it was a way to watch the Marvel accelerate, but also hear it accelerate and compare the sound that I was hearing, getting louder and changing pitch to the velocity, and see what those things were related. And I knew that the sound that I was hearing was related in some way to the marble losing energy. So what I was hearing and seeing was that was the energy loss due to friction in a scale model, because I know that a marble on a flat surface that isn't rolling, doesn't make any sound. And the faster it's going, the louder it gets, at least in the increments that I had in this experiment, I did these experiments. And so I what I would see is a visual representation of the visual weight of a marble, the map of the velocity as it related to the sound that was getting accelerating.
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And I would note, I will count the number of dominoes that got knocked over at the end of the ramp, as a function of these things. So the size of the marble was constant, the circle that represented the velocity, which I could hear and see, was getting bigger. And they also used crayons that I laid out on the floor in a specific order. So I knew which crayon the marble was at, as a function of the visual representation
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of the velocity and the sound that I was hearing at these snapshots in time. So I could keep track. And what this is a model of going back to cognition is six things. The first thing is what am I looking at? And that's a marble. And the second thing is, how many are there? And there's only one. But another component of that is how much is it, which was the visual weight of it, it's a marvel of a certain size. So that's, that's a two, two, for one thing, it's a marvel, and it has a size. So that's a an object and the value of the object. The next one is where is it. And based on where it was in relationship to these crayons, I knew where it was at a snapshot in time. And when is it and I said in the earlier video, I used to practice with time with a stopwatch. And I can keep track of time very accurately the passage of time how long things took, and as accurate as 300 seconds plus or minus two seconds. I was good at time. So I knew when it was. So at this point, I knew what it was, how much of it there was, which is maths, where it was when it was how every how question can be answered with a flowchart. And the flowchart of this was the ramp. That's how and if the curvature of the ramp changed, then the house was different. So the ramp could be curvy, a wavy, and that's a different house, because the flowchart would go here, and then there and then there and there and then there. But I made it as straight as I could. But I knew that that was how, and why? Why questions can always be answered in a multivariable plot. And there's an infinite number of y's for everything. You can always ask another why always, always. But what I learned about y questions is to rank the variables. So if there's a y question, and there's 10 Possible reasons why that you can come up with if you rank them one to 10. In terms of importance, what's important to you what you think is the most important, and you plot the top two Next, on a graph next to each other, then what you end up with is a plot where in the upper right hand corner is the most important reason why I didn't really know why. Back then about maths and gravity interacting to create a situation where a marble rolls downhill. I didn't know why. But I knew it was missing. And I could see this in these in these visual models, not in the words I'm describing them with now, but in a model of this all related at different snapshots in time, color coded. And this way of knowing something that's moving is comprehensive, because there's nothing else to know about the thing. Now that is that is cognition. That's not wisdom, that's knowing a thing completely at an instant in time. And then sampling that thing at the instant, over many snapshots to build up an intuitive sense of what's going to happen next. Because if you string the snapshots together, you create a dynamic model and energy and information system. Based on that you can pretty much know where the marbles going to be later. The system is made up of energy, which is the thing that is moving the mass of the thing that is moving information Which are things that you measure about it? And rules, which are the things that convert it from energy into information. And in this case, the energy is a marble of a certain size, the information is basically everything. Is it a snapshot in time, which has aware and aware and where is it and when is it and the information in this case could be the sound of the marble at that snapshot in time a visual representation of what is happening, the what. And the rules are why, which is the mass gravity interaction at that snapshot in time. And these things can be viewed together. This way of conceptualizing the conversion of energy to information through rules is the basis for business visualization. And also a couple other optimizations I did in my life in terms of money. And also in terms of it architectures, moving data around quickly, optimizing, understanding how the data flows through this way. And those things are advantageous. And so the ability to conceptualize dynamic systems, nonlinear systems that are related in visual spatial models that are proportional to scale, and sequence, then time has been useful. And when I was a kid, I wanted to explain this and use this idea to launch a global eco project to do something good. Something good from nature. It's taken me a lifetime, to be able to translate this and explain it in those words. Because I see it in a place in my mind as completely disconnected from language. And it's taken me since I was
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10. So I don't know 42 years now almost 43 years to translate this idea to these words, and create models and prove it in real life. And I'm happy about the part where I can share it
