It took the genius of Charles Darwin to break with the common belief that species were constant and unchanging.  His voyage on the Beagle was essential in forming these ideas as he encountered fossils of extinct forms and the effects of dramatic earthquakes in the Andes, and was led to realize that the Earth changes and that species change.  This idea of long-term change is hard to come by.  It even evaded Albert Einstein when he derived the expansion of the universe from his theory of general relativity and decided to introduce a correction term in the mathematics to ensure that the universe was constant as he knew it to be.  Einstein called this his biggest blunder.  Yet it was exactly this belief of constancy that Charles Darwin was able to shed.

What few people realize is that Western capitalism has embraced Darwinism and use the arguments of survival of the fittest to defend deregulation in the market.  This competition does work well… as long as you actually have competition.

In the area of data analysis and machine learning, which are my areas of expertise, we rely heavily on computer algorithms that search vast high dimensional spaces for solutions to problems.  The best algorithms employ techniques that are central to evolution.  These methods are called Markov chain Monte Carlo (MCMC)  techniques, and in some specific cases these algorithms have direct relation to genetic evolution and are called genetic algorithms.  What makes these algorithms work is precisely what makes evolution work.

These algorithms rely on a fitness function that enables us to measure the fitness of a hypothesized solution to a problem (we call this a sample).  We often start with many samples scattered throughout the space and let them explore via mutations.  In some algorithms, we take good samples and duplicate them and let them explore further, or we may even combine characteristics of a pair of samples to create a new one (as in genetic algorithms).  After hundreds of thousands of iterations, the algorithms are able to find the solutions to the problem.  These solutions would be impossible to find via brute force search or guessing.

The analogy that holds here is that of organism as sample.  Anyone who has actually done these simulations can understand that you can obtain solutions worthy of creation simply by iterating hundreds of thousands of times under the force of a selection pressure.

Happy Birthday Charles Darwin, and thank you for the insights that have advanced machine learning in the last two decades.

Kevin Knuth
Albany NY

Alex Wild, a biologist at the University of Arizona, has a blog on insects, photography and life.  He has an excellent article on tricks and tips for keeping ants relatively still while photographing them in their natural surroundings and while performing natural behaviors. 

Kevin Knuth
Albany NY

Here it is:

You can put it on your iGoogle page by clicking here…

I am going to write a few other versions that will complement my BirdPlanner.com site. The first will be a modification of the above where the user can enter their latitude and longitude to get birds that are present in that locale. That way people can prepare for their birdwatching trips.

I will also try writing one which is a Bird Identification Quiz. It will be a multiple choice quiz. I can vary the difficulty by sampling from birds of the same genus, from the same family, or from the whole set of birds.

This is a fun way for me to become familiar with the computational technology. The google gadget is just an XML file. The tag <Module> identifies it as a Google Gadget.

The remaining XML has three parts:

1. <ModulePrefs>, which encodes the properties of the gadget.
2. <UserPref>, which encodes the user information.
3. <Content>, which encodes the content.

My gadget is pretty straightforward.  There are no User Preferences, so I just have the first and last sections. 

You can look at the xml code here.  You will see that the workhorse of the content section is a php file that emits an html file.  In this case the gadget simply holds a simple web page.

In the future, I will write more details about how all of this works.

Kevin Knuth
Albany NY

These ants farm fungus gardens and have built a ventilation system to release the large amounts of carbon dioxide generated by the garden and bring in fresh oxygenated air.

There are only two creatures on Earth that farm: humans and ants!

PS: It appears that this video is/will be available in its entirety at these two URLs:
http://video.google.com/videoplay?docid=-8115023696779132025
http://www.stage6.com/Ants/video/2090460/Ants-Natures-Secret-Power

Kevin Knuth
Albany NY

The NASA Astrobiology Institute (NAI) announces, through the release of this Cooperative Agreement Notice (CAN), an opportunity for the submission of team-based proposals for membership in the Institute. Proposals should clearly articulate an innovative, interdisciplinary, astrobiology research program, together with plans to advance the full scope of NAI objectives as defined in the Institute’s Mission Statement.The Cooperative Agreement Notice can be accessed at: http://nspires.nasaprs.com

CAN Release Date: January 8, 2008
Notices of Intent Due: February 22, 2008
Proposals Due: April 11, 2008