Well I went back to the APU, worked there, Applied Psychology Unit, and I did experiments actually on measuring neural noise, that is the randomness of the spikes of activity in the nervous system, coding information, and I related this to ageing and I measured the noise level using psycho physical methods and then tried this out to see whether as you got older the noise level went up so that as your memory gets wonky when you get older and your vision gets worse and so on, my question was, was this due to masking by internal noise in the nervous system or was it loss of signal? I also applied this to hearing. Now I’m 82, I absolutely know that we were on the right track, my golly. One is living in a load of random activity going on in one’s nervous system and, indeed, one’s vision gets worse, one’s decision-making gets worse, you slow down. You slow down partly to compensate the noise. If you take longer to make a decision, the signal increases linearly but the noise to the square root so actually get an increase in the signal to noise ratio and you become more affected so old people slowing down is actually a very, very sensible thing to do to avoid the degeneration of signals through noise in the nervous system. And these were tricks, of course, I had learned from radar. I knew about noise, you see, any instrument, any detecting instrument, is subject to random noise, integration and so on, is very familiar to me from radar. Then I found the nervous system was carrying out these procedures that we use in electronics, in radar detection, which is really quite exciting. And then, of course, I mean electronic equipment gets a bit groggy when it gets older and the noise increases, the transistor, this is before transistors, but the valves, etc, all get more noisy and exactly the same thing in us. So this sort of connection between principles of electronics, particularly detecting systems, and storage of information, through memory, and the nervous system was powerfully important to me from the war and a lot of my early work, if I can call it that, was really drawing analogies from what I’d learned from radar, etc, into how the brain might be working and my assistant at that time, Jean Wallace, who was my research assistant, and Violet Cane, who was absolutely brilliant, a mathematical statistician, she was fantastic, she was, by the way, the first woman professor in Manchester and there was a marvellous headline in the paper, what was is it, 101, I think it was, there were 100 male professors and she, no, 99 male professors and she was the only female professor in Manchester. She left in the end to go to Manchester, anyway, she was of that calibre, she was top notch mathematician, and we developed theories of signal to noise ratio for threshold, that is for the discrimination of brightnesses and shapes and colours and so on in the perceptual system using signal to noise ratio ideas. We actually won a senior prize for it, which was really nice. Actually, there was some money in it, which was amazing because I was incredibly poor, we all were. So that was actually great fun. But I think it illustrates actually how doing one thing, particularly a technical thing, like radar or submarines or anything like that, is not irrelevant, it’s very relevant, it seems to me, when you’re thinking about theories, about how nature works, how physics works, or how the brain works. I think there are processes and principles, you know, which absolutely link technology, physics and physiology and psychology. Many, many principles which operate. A good example, of course, is feedback in server systems, control systems, which were only just invented at that time and it was a wartime idea of gun ranging and guns aiming automatically and this sort of thing. You then looked at human beings in tracking things and thinking of things and aiming at things and perceiving things, and blow me down, the same principles very much apply, which got me interested in artificial intelligence.