Impossible? Perhaps not!

Lord Kelvin

Throughout the history of science there have been proofs that something is impossible. These proofs are usually true in mathematics, such as that it is impossible to generate the number π with a ruler and compass. Despite which, many amateurs continue to assert that they have made it. I myself have had to face one of these “proofs”.

Another similar case is the proof, this time related to physical science, that it is impossible to build machines with perpetual motion, because they oppose the first or the second principle of thermodynamics. Also, in this case many amateurs insist that they have made it. In these cases, one should not waste time looking for the error, which is known to exist.

Will we be able to build conscious beings?

I use the term conscious beings, because the term conscious machines has materialistic connotations that I do not share, while artificial intelligence has been burned and abused by generalist media.

Before trying to answer this question, I want to make a few previous clarifications:

1. We are now capable of building conscious beings: our children. Four billion years of evolution have led to the appearance of a type of beings (us) endowed with self-awareness and capable of reproducing. This was a natural process, which we have not designed ourselves, but has been given to us since before we existed. However, when someone poses the question in the title of this post, it is usually interpreted thus: will we be able to build artificial conscious beings, by means other than natural, devised and developed exclusively by ourselves?

Artificial intelligence or computer algorithms?

John MacCarthy

The term artificial intelligence appears frequently in the media. It is usually used to refer to a computer application that behaves in a way that appears to be intelligent. But is it really intelligent? Or is this a case of meaning displacement, the application of a more appealing term to something not really new?

The term artificial intelligence was invented by John MacCarthy in 1956, in a seminar that took place at Dartmouth College in Hanover, U.S.A. At that time, the participants made exaggerated predictions about the imminent advances they expected in this field, some of which have not been fully performed 65 years later. Now the predictions are even more ambitious, but it is quite likely that none will come true in the short term, and that some will never come true.

Automatic Learning

By popculturegeek.com
 Originally posted to Flickr as Comic-Con 2004
Terminator statue, CC BY 2.0
https://commons.wikimedia.org

As I said in a previous article, automatic learning is one of the areas of weak artificial intelligence which has been object of research for at least 40 years. Strictly speaking, rather than a field of application, automatic learning is a methodology or technique used by other fields of application, such as neural networks, expert systems or data analysis. Automatic learning is divided into two main branches:

• Supervised automatic learning, which has been used most frequently up to now. This post is dedicated to explain it.
• Unsupervised automatic learning, related to the field usually called Data Mining. It has lately been widely advertised by the media in relation to a program (AlphaGo Zero) that, learning by itself, has reached a level comparable to the world champion of the game called Go (at the end of this post I’ll talk more about this).