I’ve been running an experiment to see how well ChatGPT-Generated Portfolios perform in real-time trading. In this experiment, several versions of the portfolios that are deployed are “optimized”…

An Illustrated Guide to Genetic Algorithm

Genetic algorithms are the methods of solving search-based optimization on the principles of Genetics and Natural Selection, the process that drives biological evolution. It mainly used in research, and machine learning. It finds optimal or near-optimal solutions for difficult problems which might take a lifetime to solve. Genetic algorithms are a subset of a much larger branch of computation known as Evolutionary Computation. GAs were developed by John Holland and his students and…

Creationists who don't see this sort of research as a problem, probably haven't understood it or grasped the significance of it. What they need to consider is: How can something designed by a perfect designer be improved upon? Why is a genetic algorithm such a good tool for finding novel ways to improve a system? If intelligently devising an ideal outcome and testing against that ideal produces a better design, why does what we see in nature look like something produced without a concept of…

A four-letter alphabet might seem limited, but it’s all nature needed to write the instructions for all life on the planet. News that researchers have added four letters to the genetic alphabet opens the door to new possibilities in synthetic biology, data storage, and even the search for life beyond our planet. The genetic code...

UCLA study concludes insurers should provide better coverage for cutting-edge genetic test

An introduction to genetic algorithms, optimization, and implementations with code examples in Python