Weaving Wolfram Rule 90

 

I’ve been interested for a while in cellular automata, pattern generating mathematical formulae such as Rule 90

There are many of these rules, each generating different behaviour. Each rule generates the content of cells in a column based on the cells in the preceding column, and are each based upon given starting conditions. 

These are the rules for Rule 90:

current pattern

111

110

101

100

011

010

001

000

new state for center cell

0

1

0

1

1

0

1

0

 

Start 2014 with a Edinburgh Hacklab Workshop

We are repeating the very popular Soldering and Arduino workshops in the new year. Ideal as Christmas presents, especially for those often hard-to-buy-for geeks in your family. No previous knowledge of soldering, electronics or programming is required, we start with the basics and help you to learn at your own pace. Soldering Workshop Saturday 11th[…]

The main trick in Machine Learning

I have been irritated that many recent introductions to machine learning/neural networks/whatever that fail to emphasise the most import trick in machine learning. Many internet resources don’t mention it, and even good textbooks often don’t drill it in to the reader the absolute criticality to success the trick is. In a machine learning context, we wish a learning system to generalise. That is, make good predictions on data it has never encounter before, based on what it learnt during from a training set. There is no easy formula to predict the ability of a learning system to generalise, but you can estimate it using held out data. That held out data is labelled but it is not used in training. It is called the validation set.

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Make a game month results!

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Ahhh, #makgammon, make-a-game-month, is over. I have semi-recovered from the development exhaustion. The single transferable votes have been counted. I have the results!

Before that I would like to say #makgammon was really amazing this year. We had 6 entries, all of which represented a significant contribution in different ways. The spread of games was broad, so there was something for everyone. This was represented in the votes! We asked people to order the games by personal preference (of the games they played). Those orderings were pretty random, indicating that at least someone really liked *every* game. So it just goes to show, you can’t please everyone (so you should never try)! If a game dev did not win a prize, don’t feel bad, because someone in our judging audience did like the concept.

That said, the games that did win did appear higher on average in most people’s score sheet. So congrats to those for winning the mainstream appeal awards. Our prizes were kindly donated by Scirra who make the game development software “Construct 2”. I used that software to build Universal Machine, and I was blown away by how productive I was in 4 weeks. I think its fair to say that even if Universal Machine did not “win”, it was the most complex game, indicating how useful Construct 2 is as a productivity tool. So without further “ado”, the results…
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