Born in 1927, Marvin Minsky is one of the pioneers of the field of Artificial Intelligence, founding the MIT AI lab in 1970. He has also made many contributions to the fields of mathematics, cognitive psychology, robotics, optics and computational linguistics. Since the 1950s, he has attempted to define and explain human cognition, the ideas of which can be found in his two books, The Emotion Machine and The Society of Mind. His many inventions include the first confocal scanning microscope, the first neural network simulator (SNARC) and the first LOGO 'turtle'.
The perceptrons did some things that were quite useful and remarkable. And then, there were some things that seemed remarkable, but turned out to be accidents. Like I had a friend in Italy who had a perceptron that looked at a visual... it had visual inputs. So, he… he had scores of music written by Bach of chorales and he had scores of chorales written by music students at the local conservatory. And he had a perceptron – a big machine – that looked at these and those and tried to distinguish between them. And he was able to train it to distinguish between the masterpieces by Bach and the pretty good chorales by the conservatory students. Well, so, he showed us this data and I was looking through it and what I discovered was that in the lower left hand corner of each page, one of the sets of data had single whole notes. And I think the ones by the students usually had four quarter notes. So that, in fact, it was possible to distinguish between these two classes of... of pieces of music just by looking at the lower left… lower right hand corner of the page. So, I told this to the… to our scientist friend and he went through the data and he said: 'You guessed right. That’s… that's how it happened to make that distinction.' We thought it was very funny. A similar thing happened here in the United States at one of our research institutions. Where a perceptron had been trained to distinguish between – this was for military purposes – It could… it was looking at a scene of a forest in which there were camouflaged tanks in one picture and no camouflaged tanks in the other. And the perceptron – after a little training – got… made a 100% correct distinction between these two different sets of photographs. Then they were embarrassed a few hours later to discover that the two rolls of film had been developed differently. And so these pictures were just a little darker than all of these pictures and the perceptron was just measuring the total amount of light in the scene. But it was very clever of the perceptron to find some way of making the distinction.
Title: Embarrassing mistakes in perceptron research