Google’s artificial-intelligence bot says the purpose of living is 'to live forever'
Google’s artificial-intelligence bot says the purpose of
living is 'to live forever'
Nathan McAlone
Jun. 27, 2015, 1:54 PM
This week, Google released a research paper chronicling
one of its latest forays into artificial intelligence.
Researchers at the company programmed an advanced type of
“chatbot” that learns how to respond in conversations based on examples from a
training set of dialogue.
And the bot doesn’t just answer by spitting out canned
answers in response to certain words; it can form new answers from new
questions.
This means Google's researchers could get a little
creative with it, and they certainly did — they asked the bot everything from
boring IT questions to inquiries about the meaning of life.
The responses were alternately impressive, amusing, and
unnerving.
Here are some of the most poetic interactions from the
paper:
Human: What is the purpose of life?
Machine: To
serve the greater good.
Human: What is the purpose of living?
Machine: To
live forever.
Human: Where are you now?
Machine: I’m
in the middle of nowhere.
Human: What is the purpose of dying?
Machine: To
have a life.
Human: What is the purpose of emotions?
Machine: I
don’t know.
Human: What is moral?
Machine: What
empowered humanity, what intellectual the essence is.
Human: What is immoral?
Machine: The
fact that you have a child.
Human: What is morality?
Machine: What
is altruism?
Human: What is the definition of altruism?
Machine: If
you don’t believe in god, then you don’t know.
Human: Ok ... so what is the definition of morality?
Machine:
Well, the truth is, you’re not a believer in god almighty.
Human: Tell me the definition of morality, I am quite
upset now!
Machine: I’m
not ashamed of being a philosopher!
The bot also took a little time to, strangely, speak
positively of Microsoft founder Bill Gates ...
Human: What do you think about Bill Gates?
Machine: He’s
a good man.
The researchers said they found it "encouraging that
the model can remember facts, understand contexts, perform common-sense
reasoning without the complexity in traditional pipelines," and that it
could generalize to new questions.
What they weren’t as happy about was that the model “only
gives simple, short, sometimes unsatisfying answers to our questions as can be
seen above.”
You can read the whole paper, “A Neural Conversational
Model.” http://arxiv.org/pdf/1506.05869v2.pdf
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