Herself’s Artificial Intelligence

Stanford is offering free online classes in Machine Learning and Introduction to Artificial Intelligence

I’ve taken their iPhone programming class and it was fantastic. I’m going to take the AI class to brush up on things and the Machine Learning to learn some new things.

Classes begin Oct 10 and run through mid Dec 2011.

It’s getting to where you can learn everything you need to know on any subject online and that’s a wonderful thing. Now with portable pdf and ebook readers you can take that information any where with you.

E-Books Directory
Sciyo – Free science books and journals
National Academies Press

I’ll add to this list as I run across new sites.

Electric Sheep is a collaborative abstract artwork founded by Scott Draves. It’s run by thousands of people all over the world, and can be installed on any ordinary PC or Mac. When these computers “sleep”, the Electric Sheep comes on and the computers communicate with each other by the internet to share the work of creating morphing abstract animations known as “sheep”. The result is a collective “android dream”, an homage to Philip K. Dick’s novel Do Androids Dream of Electric Sheep.

Anyone watching one of these computers may vote for their favorite animations using the keyboard. The more popular sheep live longer and reproduce according to a genetic algorithm with mutation and cross-over. Hence the flock evolves to please its global audience. You can also design your own sheep and submit them to the gene pool.

Electric Sheep

More information:
The Electric Sheep Screen-Saver: A Case Study in Aesthetic Evolution (pdf)
Source code at Source Forge
Electric Sheep Wiki
Artificial Evolution for Computer Graphics, Karl Sims
BodyLab Researching the evolution of the human body shape

Pyevolve was developed to be a complete genetic algorithm framework written in pure python, the main objectives of Pyevolve is:

* written in pure python, to maximize the cross-platform issue;
* easy to use API, the API must be easy for end-user;
* see the evolution, the user can and must see and interact with the evolution statistics, graphs and etc;
* extensible, the API must be extensible, the user can create new representations, genetic operators like crossover, mutation and etc;
* fast, the design must be optimized for performance;
* common features, the framework must implement the most common features: selectors like roulette wheel, tournament, ranking, uniform. Scaling schemes like linear scaling, etc;
* default parameters, we must have default operators, settings, etc in all options;
* open-source, the source is for everyone, not for only one.

More information:
Blog for Pyevolve
Documentation and downloads
GA Based Sorting using Pyevolve
MIT OpenCourseWare – Intro to Computer Science with Python

Google’s Research Blog posted an article this week on its use of quantum computing algorithms

More information:
Training a Large Scale Classifier with the Quantum Adiabatic Algorithm
Qubuit.org, Center for Quantum Computing
Introduction to Quantum Computing
The Quantum Computer
Quantum Computing and Shor’s Algorithm
Quantum Computing Day 1, Google Tech Talk on YouTube
Quantum Computing Day 2, Google Tech Talk on YouTube
Quantum Computing Day 3, Google Tech Talk on YouTube