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fundamental technique in AI today. The difficulty Turing confronted in designing the bombe
was that the Enigma machine had far too many possible settings for the bombe just to search
blindly through them until it happened to stumble on the right answer—the war might have
been over before it produced a result. Turing’s brilliant idea was to use heuristics to narrow, and
so to speed up, the search.
Turing’s idea of using crib-loops to narrow the search was the principal heuristic employed
in the bombe (as Chapter 12 explains). Another heuristic that Turing mentioned in his 1940
write-up of the bombe was known as ‘Herivelismus’ (so named after its inventor, John Herivel).^5
Herivelismus involved a simple yet powerful idea. It could be assumed that when an operator
enciphered his first message of the day, the starting positions of his Enigma machine’s three
encoding wheels would be in the vicinity of the wheels’ ‘base’ position for the day. This base
position was determined by one of the variable settings of the Enigma machine, which the
operators would change every day (by referring to a calendar that specified the day’s setting).
This setting was known as the Ringstellung, or ring position, and the Ringstellung fixed this daily
base position of the three wheels. The German operator was supposed to twist the three wheels
away from their base position before enciphering the first message, but operators—in a hurry,
under fire, or perhaps just lazy—often did not turn the wheels far from their base position
before starting to encipher the message. So when the bombe was searching for the positions of
the three encoding wheels at the beginning of what was believed to be an operator’s first mes-
sage, only settings in the neighbourhood of the base position were considered.
This procedure narrowed the search considerably and saved a lot of time. The assumption
that the wheels were in the vicinity of the base position when operators began encoding their
first message was not always true, but it was true often enough. The Herivelismus heuristic
broke a lot of messages.
Spreading the word
Thanks to the bombe, Turing glimpsed the possibility of achieving machine intelligence of a
general nature by means of guided search. This idea fascinated him for the rest of his life. He was
soon talking enthusiastically to his fellow codebreakers about using this new concept of guided
search to mechanize the thought processes involved in playing chess (see Chapter 31).^6 He also
wanted to mechanize the process of learning itself. At Bletchley Park, he actually circulated a
typescript on machine intelligence—now lost, this was undoubtedly the earliest paper in the
field of AI.^7
Once the war was over, Turing began making his radical ideas public. In February 1947,
in an ornately grand lecture theatre in Burlington House, a Palladian mansion near London’s
Piccadilly, Turing gave what was, so far as we know, the first public lecture ever to mention
computer intelligence.^8
Turing offered his audience a breathtaking glimpse of a new field, predicting the advent
of machines that act intelligently, learn from experience, and routinely beat average human
opponents at chess. Speaking more than a year before the Manchester Baby ran the first com-
puter program, his far-seeing predictions must have baffled many in his audience. In the lecture
Turing even anticipated some aspects of the Internet, saying:^9
It would be quite possible to arrange to control a distant computer by means of a telephone line.