Reminds me of Donna and Dennis meadows expansion of complex systems combined with entropy and scaled to c and von Neumann utility theory and game theory of sorts combined into evolutionary behavior biology. It’s my dream to visit and talk to others there someday! 😅
The whole really is the sum of the parts. I have seen a little parameter in a equation within massive amounts of code and systems of equations create huge exponentially scaling problems. We really have to preserve the sum of computations at the small scale is what is predicting the whole, to accurately predict the large scale behavior. A analogue to this is, If biological cells do not have the ability to send signals and action through connection, you don't get the large scale complex behavior. It's about the small scale complex features coming together the make the complex whole. In the market, there is a bunch of players running data analytics, therefore you could be making a error, and another person (a little component) detects it and says to the whole (hey there is a problem here we need to correct for), meaning you might be making errors and others are eating the cost. And we know this is occurring, because there is a exponential decrease in biodiversity, from many small errors building up in our system, biodiversity eats the cost. You know what I mean? How do you know you are accurately power scaling, especially in changing conditions? You would first have to sum the small scale factors, find the average, then make that average your based for power scaling (it's also about the modes that are symbiotic with the average, there is many analytical directions). Because at the end of the day (for every action, there is a equal and opposite reaction, therefore summing over a distribution is the first thing you do, then you find the average, then you find the modes that have high fitness with the average as you progressively calculate the average of parameters, from multiple progression directions to triangulate [to get granularities, and better and better description]). For instance, we need to understand electron behaviors at smaller and smaller time scales, to better understand protein behavior and it's shape in different conditions. I'm not a very smart person myself, but I also know we have to be honest and precise.
We can simplify our political-economic system by focusing on basic precepts. If we value Truth as a primary value, we need to account for externalities, so prices will honestly represent costs. We can do this efficiently and fairly by charging fees to industries proportional to emissions, resource extraction or habitat destruction. Random surveys can show where fees should be raised (where most people say that particular kinds of impact on the environmennt should be further reduced). A system of fees can replace other, bureaucratic methods of control.
Very interesting, thanks. I predict a third way will emerge, so first the John with dark hair's modeling method as revealing information, now John with light hair way of modeling revealing knowledge and the third way will get at initial conditions for profound understanding.
Great talk! Also, please format the description better to avoid text wall, and don't use envious emotionally immature colleagues as hosts. Complexity ftw!
Some say "we" is the original psychological operation.
We think it's fascinating.
Reminds me of Donna and Dennis meadows expansion of complex systems combined with entropy and scaled to c and von Neumann utility theory and game theory of sorts combined into evolutionary behavior biology. It’s my dream to visit and talk to others there someday! 😅
The whole really is the sum of the parts. I have seen a little parameter in a equation within massive amounts of code and systems of equations create huge exponentially scaling problems. We really have to preserve the sum of computations at the small scale is what is predicting the whole, to accurately predict the large scale behavior. A analogue to this is, If biological cells do not have the ability to send signals and action through connection, you don't get the large scale complex behavior. It's about the small scale complex features coming together the make the complex whole. In the market, there is a bunch of players running data analytics, therefore you could be making a error, and another person (a little component) detects it and says to the whole (hey there is a problem here we need to correct for), meaning you might be making errors and others are eating the cost. And we know this is occurring, because there is a exponential decrease in biodiversity, from many small errors building up in our system, biodiversity eats the cost. You know what I mean? How do you know you are accurately power scaling, especially in changing conditions? You would first have to sum the small scale factors, find the average, then make that average your based for power scaling (it's also about the modes that are symbiotic with the average, there is many analytical directions). Because at the end of the day (for every action, there is a equal and opposite reaction, therefore summing over a distribution is the first thing you do, then you find the average, then you find the modes that have high fitness with the average as you progressively calculate the average of parameters, from multiple progression directions to triangulate [to get granularities, and better and better description]). For instance, we need to understand electron behaviors at smaller and smaller time scales, to better understand protein behavior and it's shape in different conditions. I'm not a very smart person myself, but I also know we have to be honest and precise.
We can simplify our political-economic system by focusing on basic precepts. If we value Truth as a primary value, we need to account for externalities, so prices will honestly represent costs. We can do this efficiently and fairly by charging fees to industries proportional to emissions, resource extraction or habitat destruction. Random surveys can show where fees should be raised (where most people say that particular kinds of impact on the environmennt should be further reduced). A system of fees can replace other, bureaucratic methods of control.
Very interesting, thanks. I predict a third way will emerge, so first the John with dark hair's modeling method as revealing information, now John with light hair way of modeling revealing knowledge and the third way will get at initial conditions for profound understanding.
Look forward to reading your book. Thank you!
Great talk! Also, please format the description better to avoid text wall, and don't use envious emotionally immature colleagues as hosts. Complexity ftw!
nonsense