What is the difference between computer and brains? Can  computer memory be compared with the human
brain?  The first scientist who
experimented to answer these questions related with the differences between
machinery and humans was Alan Turing, one british scientist. The first  idea for measuring artificial intelligence
was famously  known  as the “Turing test”. In the 1950 paper, “computer
machinery and intelligence”  Turing
propose the following game.

 A human judge had a
small talk with  players that they could
not see. Their tasks was to appreciate  their responses. In order to pass the test a
computer machinery,  must had the
capability  to substitute  one of the game  players without shifting  results. In more easily  words, a computer would be considered
intelligent if the conversation could not be easily differ  from humans. Turing forecasted  that by the year 2000 machines with 100 MB of
memory would have the  capability  to easily pass his test, but he made a jumping
on. Even though today computers have far more memory than that, he has
succeeded and those  that have done well
,focused more on finding  clever ways to
full judges  then using  impenetrable   computing powers. Thought it was never  vanquished  to a real test, the first program  that was thought to success was called
“Eliza”. With a short and easy  script,
it ménage to lead astray  many people,
motivating  them to talk more and
mirroring  their own individual  questions back at them. Another paw  was  named  “parry”.
This script  took the opposite transaction
 by imitating a paranoid schizophrenic  who caped running  the conversation back to his own
pre-programmed obsessions. Their success in fooling people pointed out one impotence
of the test. Humans regularly predicate intelligence to all series  of things that are not actually intelligent.

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 Nerveless,  annual competition has made the test more
nominal  with judges knowing   that
some of their conversation’s partners are machines , but while the quality has
proved  that many chatbot programmers
have used similar strategies to Eliza and Parry. 1997’s winner of competition
“Catherine”, could carry amazingly focused in an intelligence conversation, but
mostly if the judge wanted to talk about Bill Clinton and the more recent
winner  Jugine Goustman  was giving the persona the 13 years  young old Ukrainian boy, so judges interpreted
its non isolation by using  a clear grammar
as language and cultural barriers.

Meanwhile, others programs like “cleverbot” have
taken an different approach by  analyzing  very big data bases and real conversation to
determine the best responses. Some machinery 
also stored  memory of last
conversations in order to improve over time. But, while cleverbot’s individual
responses can sound like human, it is lack of consistent personality and
inability to deal with brand new topics which 
have been  predicting  that today’s computers would be able to
discover planets and stars, perform 
difficult medicine operations  and
solve the most difficult math equations but, still struggle with the most basic
small talk?! Human language turns out to be an amazing complex phenomenon that
can not be captured even by the largest dictionary. Chatbots can be befoul  by simple exclamatory like:”Umm..” or  complex 
questions with no correct answer. In a simple conversation, composite
sentences like:” I took the juice out of the fridge and gave it to them , but
forgot to check the date”,  requires  a wealth of underlining knowledge and
intuition. It turns out that simulating a human 

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