“The sciences do not try to explain, they hardly even try to interpret, they mainly make models. The justification of such models is solely and precisely that they are expected to work.”
- John von Neumann
Coming Up
Building Models That Actually Work
DIY Stock Trading Bot
Fracticality of Natural Systems
Information over Time
Scoping a Solution Space
Simultaneity Doesn’t Exist
Exploring Time Data
Event Occlusion and Sample Resolution
Working with Time
Core
What is Prediction?
A Modelers Glossary
Models as Compression
Brain Time
Fractally-Nested Clocks
Meta-Lamarckism
Conditions For Prediction
In most cases, predicting the future is impossible. However, there are certain criteria and areas of reduced dynamics where it can be predicted up to a certain time horizon. After this horizon, the dynamics exponentially make it harder to predict an outcome to a point of equivalence to infinitely impossible. Sometimes longer-term windows open up, but they’re open so briefly it’s almost impossible to catch them.
In college and industry, differential equations was by far my best class. It was the only class where I never took notes or did homework assignments and only learned by means of my professor’s barely discernable spoken English. I didn’t need anything else. I got 100%’s on almost all my exams, and a 4.0 in the class, while my friends were completely baffled after struggling to keep up even with hours of study and exercise. I just got it. It’s purpose, modeling change, was so intuitive and natural for me.
In these writings about predictions, I will attempt to shed light on my prodigious change-modeling abilities and hope readers become better at thinking about time, prediction horizon, identity abstractions, and complex-system simulations.
Concepts
Time is the dimension from which meaning is derived. A causal-metric space for information interpolation. A space which is stretched in different ways to allow for composition of forms into new forms. It is the canvas of Creation itself.
- TM Bird