Protgens can be real?

Furry Theories; Part 2: Protogens can be real? Part 1! Like some of our patrons have said "yeah, I thought of that. and their bio/mech ratio is 40/60, so that means easier to create since all that is really needed is a nervous system and a digestive system(stomach, pisser, pooper) but, unique to their species is the nanites(what their visor is made of) and that has like separate thing and is unrealistic for our current time. because we don't have anything that can replicate a brain and move mechanical objects the way a brain does. if that makes sense."; I feel like there could be a way to make them real... The problem this fellow furry has said was a brain! now, I am not very well with coding, but, I do know a program to help out with this... Python! I know very little about this program, so, I did some research, I will explain that at a later date... But, to make an "Artificial brain" we need something that will probably kill us all... Artificial Intelligence! or AI! In basic terms, the goal of using AI is to make computers think as humans do. This may seem like something new, but the field was born in the 1950s. Imagine that you need to write a Python program that uses AI to solve a sudoku problem. A way to accomplish that is to write conditional statements and check the constraints to see if you can place a number in each position. Well, this Python script is already an application of AI because you programmed a computer to solve a problem! Machine learning (ML) and deep learning (DL) are also approaches to solving problems. The difference between these techniques and a Python script is that ML and DL use training data instead of hard-coded rules, but all of them can be used to solve problems using AI. In the next sections, you’ll learn more about what differentiates these two techniques. Machine learning is a technique in which you train the system to solve a problem instead of explicitly programming the rules. Getting back to the sudoku example in the previous section, to solve the problem using machine learning, you would gather data from solved sudoku games and train a statistical model. Statistical models are mathematically formalized ways to approximate the behavior of a phenomenon. A common machine learning task is supervised learning, in which you have a dataset with inputs and known outputs. The task is to use this dataset to train a model that predicts the correct outputs based on the inputs. The image below presents the workflow to train a model using supervised learning:; This is already getting too long, so I'll just give a link to the website I'm citing... https://realpython.com/python-ai-neural-network/; I'll need Mark Rober for this sh*t...