What a great eBook for learning how to solve problems in Matlab: Experiments in Matlab. It covers topics like Google Page Rank, Game of Life, Sudoko, Shallow Water Equations any many more. A perfect tutorial like introduction that shows you immediately the practical use of being able to program (in any kind of language).
Nowak, Martin A. 2006: Five Rules for the Evolution of Cooperation, Science 314: 1560–63
This paper provides a very easy to understand mathematical approach for the evolution of cooperation.
Cooperation is needed for evolution to construct new levels of organization. Genomes, cells, multicellular organisms, social insects, and human society are all based on cooperation. Cooperation means that selfish replicators forgo some of their reproductive potential to help one another. But natural selection implies competition and therefore opposes cooperation unless a specific mechanism is at work. Here I discuss five mechanisms for the evolution of cooperation: kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. For each mechanism, a simple rule is derived that specifies whether natural selection can lead to cooperation.
A nice discussion is going on in the NEAT User Group about the mechanism that lead to modular (artificial) neural networks, motivated by the recently published paper The evolutionary origin of modularity. The discussion around the questions, what modularity in a neural network actually is, how to measure it and how to setup evolutionary mechanisms to promote modularity in neural networks highlights the different views on that field that people with different backgrounds have.
Explore the new Scale of the Universe from Joe Hanson on Vimeo.
The Power of Ten is an absolute classic, maybe the first video that shows a continues zoom across all scales of the universe. Thanks to the Worm Singularity I discovered today Scale2 which seems to me the modern pendant of the Power of Ten, making use of todays techniques in depicting the various scales on which we can identify objects. A very nice application and again an impressive demonstration of the complexity and size of the world we live in.
I recently got the book Principles of Brain Evolution and can recommend it to everyone interested in evolutionary mechanisms that lead to the complexification of natural neural networks. The author writes in a subjective style that makes explicit why which topics are discussed in the book and which are just touched. Furthermore, he explains the categories in which brain evolution is studied and outlines the general limitations and problems with these categories. In this regard, the book provides a good and comprehensive introduction into the current notion of brain evolution from a cautious, distant perspective.
What a fantastic documentary. Truly inspiring vehicles created by the filmmakers.
I am still working on neural networks with heterogenous conduction delays, inspired by Izhikevich’s work about Polychronization. As I couldn’t find a Python implementation of his script file spnet.m (which is written in Matlab), I wrote it by myself, using the modules Numpy and Matplotlib. It is a more or less direct conversion of the Matlab code to Python thanks to Numpy. Maybe someone else can use this code as well.
Jorge Cham, the artist behind PhDComics gave a nice TEDx-talk at UCLA about the gap between the scientific world and its perception in the public. Enjoyed watching it:
This is maybe just the beginning but I thought I share it already because in the next couple of weeks I have no time to continue working on these scripts. I recently created a slideshow in the Video Sequence Editor (VSE) of Blender. The VSE has originally not been designed for creating slideshows (e.g. in contrast to the Windows Movie Maker) but with a few scripts, which restore the aspect ratio of images and which add pans and zooms to an image, it is pretty easy and straightforward to put a slideshow together. The scripts and a more detailed description can be found in this post at BlenderArtists.org.
Just discovered on Wikipedia the List of Dates predicted for Apocalyptic events. I guess, we can be lucky that we are still alive so far. According to this list, right before Christmas, on Dec 21, we will have “the next one”.
Several scenarios for the end of the world including galactic alignment, the Mesoamerican Long Count calendar, a geomagnetic reversal, nuclear war, collision with Nibiru or some other interplanetary object, alien invasion, and the Earth being destroyed by a giant supernova. [...]
Let’s enjoy the few days we have.