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What is Intelligence: Evolution of Intelligence

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EVOLUTION OF INTELLIGENCE

Imagine a large laboratory where billions of beakers are holding different mixtures of elements and molecules prepared by some invisible agent or process. Some beakers explode some evaporate away, while some become sweet smelling some become very toxic, etc. now imagine that the agent/process just adds new elements and molecules to different beakers sometimes takes the content of one beaker and mixes it within another beaker or bunch of beakers.

What is Intelligence: Limitations of current neural networks

Limitations of current neural networks

The biggest limitation of current neural networks is that they need enormous amounts of input data to properly generalize the data. To properly generalize data like images of dogs, cats or whatever we need millions to billions of instances of these data classes to train the network to be able to identify species of dogs or species of cats. It is clear that the human being requires very little input data to enable it to identify what is a dog and what is a cat, this is because it uses its imagination to generate all kinds of variations of the input data internally so it doesn't need so much input.

Announcing the FREE Wolfram Language Engine

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The power of a programming language lies in the size and quality of the libraries available for it. When learning computer programming the student is exposed first of all to the syntax of the language which takes a great amount of time to come grips with for the newbie but can easily be grasped in a shorter period of time by the veteran.

Learn Wolfram Mathematica in the cloud part 5

List FU is the art of doing Kung Fu with Wolfram language lists! The more you practice on the different ways to deal with data in lists the better you get when doing a lot of data-oriented tasks.

What is intelligence: Search! The Algorithm of intelligence

Search! The Algorithm of intelligence

I have previously talked about the network being the best representation for all kinds of problems and thus equivalent to what we can call general intelligence. My argument is that if we can find the most general representation of any problem whatsoever then we have discovered general intelligence because then it will be only a matter of manipulating the structure of this representation to solve any problem.

What is Intelligence: Human Brain vs. Artificial Neural Network Representation

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Human Brain vs. Artificial Neural Network Representation

In regular programming, we usually write code in text form, but this code eventually gets transformed through several layers to a representation that the computer hardware can deal with, which are numbers. Basically just 1 and 0. But in reality, the computer doesn’t know what a number is and it is the humans who interpret the discrete states of the computer hardware as 1 and 0. There is no symbol 1 and 0 imprinted anywhere on the computer circuit, the computer circuit performs its operation on several circuit components that can be in any of the binary states of high or low voltages, it is the human who interprets these states as 1 and 0 thus ascribing a symbol to the lumped matter abstraction of computer circuitry.