Biology seems to be a science in its own right, or set of sciences having common aims, and so it should have its own language and explanatory concepts; yet when any specifically biological concept is suggested and used as an explanatory concept it seems to be unsatisfactory and even mystical. There are many biological concepts of this kind: Purpose, Drive, elan vital, Entelechy, Gestalten.* Physicists and engineers seem, on the other hand, to have clearly defined concepts having great power within biology.

If ability to perform complex calculations were a sufficient criterion, then even a conventional digital computor could lay claim to more intelligence than any of usand perhaps we had better let it make away with the word and be done with it.

We are here today,I take it, to appraise what has been done, and to discern the future, if we may. I notice that a man's worth these times is in the words he speaks and writes. The understanding that may lead to a publishable paper is much to be preferred to the understanding that leads to a useful machine. "But I say unto you, that every idle word that men shall speak, they shall give account thereof in the day of judgment. For by thy words thou shalt be justified, and by thy words thou shalt be condemned." Can we say anything true and useful in generalization about Pattern Recognition? Are there any broad statements that have any chance of being helpful to someone building a better machine?

S MAN RUSHES to build his replacements, he communication. In the meantime at least, Though such abstraction is difficult, we already have computers must be able to, but cannot, understand the given some of our machines limited ability to read printing writing and talking of men. We are protected from technological in certain type faces [1], [2]. But reading scratchpad unemployment so long as we are buffered by handwriting or transcribing conversational speech punched cards, magnetic tapes, and on-line or off-line by machine is far beyond our ken. Also, it seems clear printers. But the day will come!

By this we mean the extraction of E CONSIDER the process we call Pattern clearly one of the most primitive sources of patterns.

Papers read at a Symposium on'Information Theory' held at the Royal Institution, London, September 12th to 16th 1955 Published by BUTTERWORTHS SCIENTIFIC PUBLICATIONS 88 KINGSWAY, LONDON, W.C.2 MANY psychologists studying learning have assumed that the subject--rat, dog, or graduate student--invariably knows what the stimulus is. They have not concerned themselves with how a dog knows that it is the bell ringing which is the stimulus to jump over a fence. A bell ringing never gives the same set of nervous impulses into the brain twice (of course the argument would still apply even if it did); why then should the dog classify all cases of bell ringing into one category--'stimulus'? There is then the further question of how this category is more or less quickly'associated' with a response: the point is that the stimulus is not a priori considered a significant entity by the subject. In designing programmes for computers to imitate conditioned reflexes, for instance, we have found that the real problem was to identify the stimulus.

A. YONEZAWA and C. HEWITT 41 REPRESENTATIONS FOR ABSTRACT REASONING 4 A maximal method for set variables in automatic theorem-proving W. W. BLEDSOE

J. Do RAN 433 22 Chromosome classification and segmentation as exercises in knowing what to expect.

B.RANDELL 3 PROGRAM PROOF AND MANIPULATION 2 Some techniques for proving correctness of programs which alter data structures.

We describe how to design simple contentaddressable memories, functioning in parallel, which can do this and which, in some sense, can generalise about the stored data. Secondly, we consider how certain graphical representations of data may be suitable for use in efficient serial search strategies. We indicate how such structures can be used in diagnosis when the availability or cost of tests to be applied cannot be determined in advance. The type of parallel system to be considered is to store descriptions of a set of patterns, and is then to be used to supplement an incomplete description of a newly presented pattern by matching it against those in store. If this partial description matches one or more of the stored patterns then we would like the memory to provide us with the partial description that these patterns share. If the new pattern does not match any in store then we expect that the information supplied will be according to the relationships between the pattern presented and those in store. The information that we require our memory to provide when given an incomplete description as an address is therefore more than just the response'yes' or'no'. In this respect our type of system differs from content-addressable parallel memories used in computer technology, and for the same reason its capabilities exceed that of a switching network which is designed to respond positively when the states of its input channels attain one of a number of combinations of binary values (Richards 1971, Renwick and Cole 1971). This paper generalises the work of Willshaw (1972) to ensembles which conform to few or no logical constraints.