Where is machine intelligence going? What do super intelligences really want?


Let’s face it, humans are pretty intelligent. Most people would not argue with this. We spend a large majority of our lives trying to become MORE intelligent. Some of us spend nearly three decades of our lives in school, learning about the world. We also strive to work together in groups, as nations, and as a species, to better tackle the problems that face us.

Fairly recently in the history of man, we have developed tools, industrial machines, and lately computer systems to help us in our pursuit of this goal. Some particular humans (specifically some transhumanists) believe that their purpose in life is to try and become better than human. In practice this usually means striving to live longer, to become more intelligent, healthier, more aware and more connected with others. The use of technology plays a key role in this ideology.

A second track of transhumanism is to facilitate and support improvement of machines in parallel to improvements in human quality of life. Many people argue that we have also already built complex computer programs which show a glimmer of autonomous intelligence, and that in the future we will be able to create computer programs that are equal to, or have a much greater level of intelligence than humans. Such an intelligent system will be able to self-improve, just as we humans identify gaps in our knowledge and try to fill them by going to school and by learning all we can from others. Our computer programs will soon be able to read Wikipedia and Google Books to learn, just like their creators.

She is also the cofounder of carboncopies.org – and organization that works on connectome mapping of the brain and downloading memories.

Even in our deepest theories of machine intelligence, the idea of reward comes up. There is a theoretical model of intelligence called AIXI, developed by Marcus Hutter [3], which is basically a mathematical model which describes a very general, theoretical way in which an intelligent piece of code can work. This model is highly abstract, and allows, for example, all possible combinations of computer program code snippets to be considered in the construction of an intelligent system. Because of this, it hasn’t actually ever been implemented in a real computer. But, also because of this, the model is very general, and captures a description of the most intelligentprogram that could possibly exist. Note that in order to try and build something that even approximates this model is way beyond our computing capability at the moment, but we are talking now about computer systems that may in the future may be much more powerful. Anyway, the interesting thing about this model is that one of the parameters is a term describing… you guessed it… REWARD.

Changing your own code

We, as humans, are clever enough to look at this model, to understand it, and see that there is a reward term in there. And if we can see it, then any computer system that is based on this highly intelligent model will certainly be able to understand this model, and see the reward term too. But – and here’s the catch – the computer system that we build based on this model has the ability to change its own code! In fact it had to in order to become more intelligent than us in the first place, once it realized we were such lousy programmers and took over programming itself!

So imagine a simple example – our case from earlier – where a computer gets an additional ’1′ added to a numerical value for each good thing it does, and it tries to maximize the total by doing more good things. But if the computer program is clever enough, why can’t it just rewrite it’s own code and replace that piece of code that says ‘add 1′ with an ‘add 2′? Now the program gets twice the reward for every good thing that it does! And why stop at 2? Why not 3, or 4? Soon, the program will spend so much time thinking about adjusting its reward number that it will ignore the good task it was doing in the first place!

https://www.youtube.com/watch?v=r8x_ohZJLx0

Source: physicsandcake.wordpress.com

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