We have a little Maltipoo puppy. We named her Pixie Woo. I think she imprinted on me. When we were at the breeders to pick out a dog, she stood up on her hid legs and and begged me to pick her up. I did. She rode home on my lap and by the time we got home, I was her human.
My wife tells me that Pixie cries for half an hour every morning after I leave for work. When I get home in the evening, she barks with glee and dances around on her hind legs until I pick her up and give her a hug.
And the affection goes both ways. I have never had a pet that I loved like her. She is such a smart girl. She has a large vocabulary and it’s growing all the time. She knows steak, chicken, and fish. She knows carrot and greenie. She loves carrots and greenies.
My wife plays a game with her where she gets her nose while saying “Boop!” She decided to be the “booper” and jumps up and tags our nose when we are playing the game.
When I call my wife to make plans for dinner, she asks our dogs what they want to eat. She goes through a list of possibilities. When she says something that they want, they high-five her.
I have spent a good part of my life studying computer science with the goal of creating artificial intelligence. Part of the challenge is coming up with a test for determining whether a program is exhibiting intelligence behavior or is just doing what it has been programmed to do. By all criteria I can think of both my dogs are extremely intelligent. But Pixie more so than Belle our older Maltipoo. One thing is for sure, I am lucky to be the human of such an intelligent, affectionate little dog.
Sweet dreams, don’t forget to tell the ones you love that you love them, and most important of all, be kind.
I approach programming as an exploratory process. I can’t seem to bring myself to sit down and plan a program out in minute detail beforehand. The truth is, any program that I understand well enough to plan out in minute detail beforehand, doesn’t interest me in the slightest. I want my programs to teach me something I didn’t know when I started writing them.
Consequently, I usually start out with some vague idea for a program. I write the shortest little bit that might work and compile and run it. Even better, I use an interpreted language like Lisp or scheme or ruby so that I can skip the compile part. I love dynamic languages!
At first, I find myself exploring the boundary between the language and the environment. For example, I have spent hours exploring the
Dir module in ruby. I have spent similar amounts of time exploring similar functionality in Common Lisp. Knowing how to traverse the file system in a given language is an important detail.
Another facility that I often dwell on is the reflective capability of a language, that is the ability of a language to know or discover details of its structure. For example, most symbols in ruby have a method
methods that returns an array of methods that the object implements.
methods is a reflective method. It allows the programmer to discover details about the programming environment dynamically at run time. Reflection is also called introspection.
Java implements reflection, demonstrating that languages not typically considered dynamic can be introspective too. The clever trick to Java reflection is that Java doesn’t create data structures to describe itself until you actually need them. This adheres to one of my favorite principles that states “you shouldn’t have to pay for features that you don’t use.” I’ve heard this principle called parsimony.
The underlying theme to these language features is that they all help make a language more adaptive. One of the key characteristics of human intelligence is our ability to distance ourself from a situation and analyze it with detachment. This is an important part of our ability to adapt to rapid changes in our environment. The ability of someone to reason about their relationship to their environment is essential to intelligent behavior.
Now I’ve really tipped my hand. The romantic notion that has captured my imagination is the quest for emergent intelligent behavior or Artificial Intelligence as it is commonly called. I try to avoid the term Artificial Intelligence because I find that neither the word Artificial nor the word Intelligence lend themselves to unambiguous definition, much less objective measurement. In fact, many of the great debates in the field revolve around this shortcoming.
To be continued.