The Amazon  machine learning AMI  (link may change in the future) is set up for CUDA/GPU support and preinstalled: TensorFlow, Keras, MXNet, Caffe, Caffe2, PyTorch, Theano, CNTK, and Torch. I chose the least expensive  g2.2xlarge  EC2 instance type with a GPU and used the One Click Launch option (you will need to specify a key file pem file for the AWS region where you are starting the instance). to have an instance running and available in about a minute. This GPU instance costs $0.65/hour so remember to either stop it (if you want to reuse it later and don't mind paying a small cost of persistent local storage) or terminate it if you don't want to be charged for the 60GB of SSD storage space associated with the EC2. I am very comfortable working in SSH shells using Emacs, screen, etc. When an instance boots up, the Actions -> Connect menu shows you the temporary public address which you can use to SSH in: ssh -i "~/.ssh/key-pair.pem" ec2-user@ec2-54-201

I am very busy with my new machine learning job but I always like to try to split off some of my own free time for occasional side projects that I think will help me learn new technologies. My latest side interest is in blockchain technologies  and specifically I am interested in blockchain as a platform and environment for AI agents. I liked  Tim O’Reilley’s call for action for corporations and people to take a longer term view of working for things of long term value to society in his recent keynote speech: Our Skynet Moment  While I consider myself to be a talented practitioner for building machine learning and general AI applications since 1982, I don't feel like I work at the level of creating any groundbreaking technologies myself. So, as far as 'giving something back' to society, it seems like my best bet is in putting some energy into distributed systems that push back against centralized control by corporations and governments, things that enpower people. Alt