GOSHtastic - Game shows, Options, Software, & Hardware!

To read Part 1 of this series, click here . The Russian Elektronika DVK-3 PDP-11 clone is a very fascinating computer to me, and I want to share it with the world.  Part of that endeavor involves allowing people to actually interact with it and play games on it remotely, not just see videos of me using it.  To get this to happen, I need to actually allow people to input into the system via the keyboard.  I could build a ridiculous robotic action to hit the keys on behalf of remote users, but this would likely introduce a great deal of latency into the system and would not be good for those critically-timed Tetris block rotations.  The best bet is to spoof the keyboard by basically building a whole new one, but instead of keys, use an Internet connection and microcontroller to generate the scan codes. The Elektronika MS7004 keyboard is based on the DEC LK201 keyboard interface , standard for PDP-11 minicomputers.  It utilizes the RS423 serial communication standard at 4800 baud.  I

Having used plenty of pre-built machine learning models using Tensorflow and GCP APIs, and having gone through the pains of setting up Tensorflow on plain vanilla Amazon EC2 AMIs (not even the pre-configured ones with all the goodies installed already) and getting it to run classifications through the GPU and on Tensorflow Serving, I thought it was high time I try coding my own machine learning model in Tensorflow. Of course, the thing most folks aspire to do with Tensorflow when starting out is to build a neural network.   I wanted to model my basic neural network based on the MNIST examples just to get my feet wet, but use a dataset different than MNIST.   There are many datasets on Kaggle to choose from that could fit the bill, but I decided to use one of my own from a while back.   It consists of skin tones found in pictures, cropped carefully and aggregated into a dozen BMP files.   Don’t question where I got these skin tone pixels from, but rest assured that a wide variety of