When it recognises a face, it actually visualises that face.The simple engineering trick that one does is to interconnect the neurons, the cells to one another, so that they recognise what each other is doing, and the whole consensus of these neurons working together comes up as a known image; that gives Magnus its power.BM: You refer to neurons - exactly the word we would use if we were talking about brain cells - but in this case those neurons are what, simple processors?IA: If built in hardware, they are very simple processors. Wizard would take in an image of a face, say, and someone would say to Wizard by typing it in, "This face's name is Fred" and Wizard would take in the image and produce Fred as its output and it would do this for cups and saucers and anything you cared to show it. One of my students heard me say that and one of the first things he did was try to get it to recognise faces, and it did, so we recognised we could do things which were difficult with conventional computers.BM: So it could do what it could do because, unlike the other computer technology, it didn't work in a direct-line logic, it was more intuitive, it was pulling things together from different directions, as the brain does?IA: It was learning, rather than relying on a programmer to work out everything ahead of time. How do you recognise a face? You measure the distance between the eyes, then you measure the distance between one eye and the nose and so on, and that would take for ever on a computer and it wouldn't work, even with a lot of computer power.BM: But now, if we move on to the next major development, a machine called Magnus, is that son of Wizard, or is it a different breed?IA: It's a completely different breed. But in those days you had to keep quiet about that, because neural networks were seen as a lunatic fringe activity So we called it an "adaptive pattern recogniser" Its application was difficult pattern-recognition tasks.

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I was once asked by a BBC journalist, "Will this thing do things like recognise faces?" I said no, never. But, again, I could see that fairly classical design of computers wasn't all that exciting, so I started looking around for other forms of computing and that's where the neural network came in.Wizard was a hardware neural network which was based on quite a lot of computer technology that was known at that time [late Seventies, early Eighties] and it was probably one of the first pattern-recognisers that used neural net techniques. So that created a tension - what is it that goes on in the brain that makes it so competent, which we haven't quite as engineers got around to in our engineering?BM: But what, in the first instance, turned you on to engineering, then?IA: It was the creative aspect of engineering that I really found exciting. Engineering seemed to be something where you had to make something out of nothing, and it's through that process that I realised that by making things you really understand how things work, and then the brain became a target for a complex organism which might be understood by trying to create something out of engineering materials, or out of engineering skills which would emulate it ...Computers hadn't been invented when I was a student, but while I was working in industry computer design became a very important thing and I actually did my PhD in that area. It captures things out of experience and avoids a programmer having to work everything out ahead of time. So that's what turns me on. BM: How and when were you first turned on to this idea of neural networks?IA: Very early on in my study of engineering I was fascinated by the brain, and by the fact that it seemed to be such a competent and wonderful piece of equipment that keeps us going for the rest of our lives, and, looking around at the electronics that I was learning about, it all seemed to be far less competent.

We have 10 billion little cells in our brains, which is all that our brains are. Now, artificial neural networks are computing devices which are very different from conventional computers. A conventional computer is just a large filing cabinet in which you store your information, you do a few operations, and a programmer decides everything that's got to be decided A neural network learns a bit like the brain does. He has spent a lifetime designing computers with names such as Wizard and Magnus, which have surprisingly complex capabilities. All this work is based on the concept of neural networks, but what are neural networks? Igor Aleksander: It's artificial neural networks that we're talking about.