Sheep without Muzzle

I thought that “They Made America” would be a great book of entrepreneurship and invention. Unfortunately, it turned out to be a book of capitalism, mistakes, and prejudice.

Harold Evans hales the money-making abilities of entrepreneurs, as opposed to their inventions. When talking about Apple, Evans puts on the pedestal the salesman and marketer Steve Jobs, almost forgetting that it was Steve Wozniak’s genius that gave life to the first Apple computers. He also forgets that iPod and OS X were in development long before NeXT was bought resulting in Steve Jobs coming back to Apple. Also, Apple I was priced $666.66 because this is $500.00 with 1/3 markup. Neither Jobs nor Wozniak knew about “the number of the beast,” to which Evans eludes.

Even in 2004, when this book was published, Evans makes derogatory comments about communist states. According to the author, Thomas Watson Jr. told Khrushchev that good working conditions uphold the dignity of the workers when the head of Soviet Union was visiting an IBM manufacturing site. The author compares Microsoft to Chinese army: they throw waves of expendable soldiers at the threat until it is defeated.

This book diminishes the importance of inventors, even though it can be found in the library of an engineering school. This book bad-mouthes the enemies of the past, like kicking the opponent while he is on the ground, and is discriminative of any kind of foreigners in United States, even though it is written in the 21st century by an Englishman. No, the world has not changed in the new millennium. What a disappointment.

I used the examples from FANN to make a neural network learner with easily modifiable options for Tino’s class. The options are:

• –train <file>, -t <file> This is input file.
• –save <file>, -s <file> This is output file.
  
• –input <integer>, -i <integer> The number of input neurons.
• –output <integer>, -o <integer> The number of output neurons.
• –hidden <integer>, -h <integer> The number of hidden neurons. The default is input+output neurons.
• –connection <real>, -c <real> Connection rate for neurons between 0 and 1. The default is 1, i.e. fully connected network.
• –epochs <integer>, -e <integer> Number of iterations. The default is half a million.

As you might have guessed, this neural network creates only 3 levels of neurons: input, hidden, and output. The input file has to be in the following format:

<elements #> <input neurons #> <output neurons#>
<input value 1> <input value 2> <input value 3> . . .
<output value>
. . .

The program requires the FANN library. I was able to install it using apt-get install libfann1 libfann1-dev in Ubuntu. Compilation is as easy as ./configure && make && make install. Example use is: nn -t end-game.data.nn -s end-game.nn -i 64 -o 1. Enjoy.

I decided to cook some borsch for my friends today, so I went to P&C and got some beef, cabbage, potatoes, tomato paste, etc. Then I decided to not cook this soup. I changed my mind because I forgot to get the essential ingredient of borsch (beat) and already started cooking. I remembered that Min always says that I do not put enough salt in the soup, so I added one tablespoon. “This is too much,” I thought immediately after adding the salt. It did not taste much like the borsch I used to eat at home. When Min arrived, she joked that she will have to recook the whole thing for me. But she tried it and she liked it. Then Madhu and Tessa tried it, and they liked it too. Lucky me! My cooking accidents turned out to be better than my best masterpieces.

This is the first blog post.