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YOU ARE YOUR GUIDE TO
ITALIAN PHILOSOPHY
BY PATCHEN BARSS
M
any more CIFAR researchers have
answers to the question, “Who are you?”
Geoffrey Hinton, CIFAR Program Director
and recent Herzberg medal winner is
no exception.
“You are the result of powerful learning
procedures interacting with a highly
structured environment to set trillions of
connection strengths in a huge parallel
computer that has evolved to have
processing elements and connectivity
patterns that make this work,” he said.
The “huge parallel computer” he refers to
is the human brain. Dr. Hinton works in
artificial intelligence and machine learning,
trying to duplicate human cognitive powers
in an artificial neural network.
So how would an artificial brain answer
the question?
Hinton and a small team of researchers
recently designed a relatively simple
neural network that has massive capacity
to analyze patterns and make predictions
based on those patterns. The researchers
“taught” this recurrent neural network
on 100-million characters of text drawn
from Wikipedia. They can now give the
network just a few words to start, and it
will compose text based on the patterns
it has learned. Sometimes the results
are nonsense, but they do demonstrate
a surprisingly sophisticated ability to
create words and sentences.
Here are some unfiltered results of how
this software completed the sentence
“You are your ...”
You are your lives?
You are your finestone for a leather’s
paper, or is stocked with the noise
unmanned.
You are your last even science.
You are your career.
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With a little human intervention (which
means having a graduate student pick out
some of the network’s more interesting
responses) the list becomes quite evocative.
All of these were generated by the network
in its first 70 attempts:
You are your name.
You are your descendant!
You are your guide to Italian philosophy.
You are your past.
You are your knowledge.
You are your real life.
You are your face.
You are your reasoning.
You are your government agent.
“Artificial neural networks are very far from
having their own personal identity,” said
Ilya Sutskever, who is a graduate student
in Hinton’s laboratory. (Sutskever was the
researcher who developed this particular
network.) But with neural networks rapidly
gaining more sophisticated understanding
of syntax, music, images and objects,
the gap between human and computer
understanding of the world is getting smaller.
Many non-researchers have started to become
familiar with computers that match or
exceed human capacity with specific tasks
of reasoning or strategy – playing chess,
poker, or Jeopardy! for example. But Hinton,
Sutskever and others are working on artificial
brains that are more universal in their ability
to learn. Inevitably, this leads to questions
related to identity.
“Since the brain’s function is to process
information in incredibly complex ways, if we
process the same information in essentially
the same way on a supercomputer, we should
get the same result: identity,” Sutskever said.