Oliver Selridge: From Cybernetics to Neural Networks

Question 1: What are neural networks?

Answer: A neural network is a model of the way real nerves, real sensors like eyes and ears and brains, work. It tries to imitate so that it will work in the same way and do the same things.


Question 2: E' possibile costruire macchine, computer e altre apparecchiature con le reti neurali?

Answer: It is possible. We believe that our thinking works in a way like that and we want to find out how real brains work, and also to build machines to do some of the same things that our brains, our minds do.

Question 3: But these machines are not programmable. Will they learn by themselves?

Answer: One hopes so. They do learn by themselves, by their own experiences but not as much as people do. They are still very simple. The kinds of tasks that these machines can now do are low-level tasks. As science improves, as the engineers and scientists, the people at SMAU, work them and practice with them they get better, but they are still very far from real people.

Question 4: Can you compare the ability of neural networks with the ability of animals or children?

Answer: It is not an age so much. The neural network in the machine keeps trying, but an intelligent child stops trying after a while and gets bored. Our machines do not get bored yet, which is a sign that they are very elementary indeed. There are tasks which they can do for us. They will keep track of the right way to do a very easy task. But as yet they do not have much sense of purpose of their own beyond what they are given by the people who build them.

Question 5: That is interesting because they have to understand from the environment. How can they understand from the environment?

Answer: That is a very interesting point. It is not that they understand so much, it is that they work with the environment to get something done, to perceive something, to have the right effect. But they do not really understand what the environment is or how it works. So neural networks today do not make a model of the environment in the way that you and I make a model of the environment, instead they merely play with what they can do until it works.

Question 6: And can you compare the goals of cybernetics and the goals of neural networks?

Answer: The goals of neural networks are much more cybernetic than present day computers. Our computers are nearly all programmed, that is, they are told exactly what to do. Neural networks are not told exactly what to do. The study of cybernetics started out with Professor Norbert Wiener at MIT, who was my adviser, studying how gets to a particular place. The word cybernetics comes from the Greek word for the steersman on a boat, who moved the tiller or the rudder to get the boat where he wanted to go. The steersman is performing the goal, the seeking of the goal, the going where he wants to. At a very low level neural networks move their connections and rewire themselves so that the machine will do what it is programmed to want to do. In computers the programs are written so the machine will do what the designer wants them to do. So the machines in computers do not want. Neural networks are beginning to want, to care, to have purpose.