Part 1
I have split this blog into two parts, as it is over 2000
words in its entirety. Here’s a link to
Part 2:
The AMII Institute
We went to a lecture the other week (Feb 20, 2018) about
developments in artificial intelligence.
The talk was put on by the University of Alberta Faculty of Extension,
partnering with the Alberta Machine Intelligence Institute (AMII). The presentation was given by Geoff Kliza, one
of the researchers at AMII.
AMII has been around for 15 years or so, though there has
been a name change. It is an academic
unit at the U of Alberta, which is involved in cutting edge research,
especially in reinforcement learning. In
fact, it is one of the top 3 such institutes, based on publications. The University of Alberta has a long history
of research into artificial intelligence, especially in the gaming area. For example, it has partnered with Google on
reinforcement learning, and a large number of the researchers that were
involved with Alpha Go (the program that beat the best human Go players) had
connections to the U of A.
The talk was put on by their Applied Research Group. They are a team that has been put together to
partner with industry, government and other organizations, investigating areas
where AI could help improve efficiencies and make money.
To some extent, the talk was a pitch to drum up business and
let people know about the initiative. The
idea was to explain AI, in general and understandable terms, for a lay
audience. It was to be followed by a
seminar day, where interested parties could practice some of the technologies
on real-life data and develop a feel for what it can do. Eventually, this could lead to ongoing
partnerships with industry.
I should note that I am a statistician by profession, who
works in applied research for a university (things like predicting who will
graduate, male/female pay gaps, etc.), so I have a pretty good understanding of
data analysis. But, I have only used the
newer machine learning techniques to a limited experimental extent, so bear
that in mind as I describe what I heard at the talk, and add some comments of
my own.
How Intelligent is Artificial Intelligence (AI)?
There is, of course, a great deal of debate about just what
we mean by intelligence. This can be debated
in terms of philosophy, religion, cognitive science, neurological science or
practical engineering terms. But for the
purposes of the talk it was defined in operational terms as:
- Agent perceives environment.
- Agent calculates appropriate response, depending on data inputs and desired outcome (goal).
- Agent takes the calculated action.
Some traditional forms of AI and areas of research and
development that were mentioned in the talk included:
- Reasoning or logic (e.g. equations and other symbol manipulations)
- Knowledge Representation (e.g. expert systems).
- Planning (logistics and the like).
- Natural Language Processing NLP (e.g. Apple’s Siri).
- Translation.
- Artificial vision.
- Robotics.
AI Up and Down (History)
Artificial intelligence has a long history, with a lot of
ups and downs - in some senses, it goes back to Babbage and his analytical
engine. And certainly AI has been a sort
of fever dream of the hopes and fears of human beings in culture for at least
that long. Movies such as Colossus, 2001
or Terminator are prime examples of that.
And lets not forget all of the episodes where Kirk and Spock had to kick
some AI in the brain, metaphorically speaking.
In modern times it has had starts and stops, periods of
enthusiasm where human-like intelligence is just around the corner, and periods
of disillusion, often known as “AI Winters”.
The Gartner Hype Cycle (pictured) is a good encapsulation of
this phenomenon. One suspects that many
of the AI techniques are currently at “Peak of Inflated Expectations”, while
others have moved on to the Trough of Disillusionment. Some are probably crawling out of that, via
the Slope of Enlightenment to the Plateau of Productivity.
The latter would include things like the Google and Amazon
recommendation engines. Siri and Alexa
might be there too. Self driving cars
are probably early in the cycle – I think there will be a lot of issues to work
out, as they go through their Trough of Disillusionment. That probably goes for many of the machine
learning type applications, as well.
By the way, “Big Data” seems to have gone through its own
Peak of Inflated Expectations, though I am not sure just where it is now. You don’t hear nearly as much about it, as
you did in the recent past. Though, interestingly,
big data has an important role to play in the increased interest in, and
usefulness of, AI.
Along with the tidal wave of Big Data, AI has been
revivified by improvements in hardware (especially fast GPU chips), intensive
development of algorithms (especially variations on artificial neural nets),
and investor interest. The shift of
algorithmic focus from expert systems to neural nets has been a major factor,
as expert systems are difficult to implement and require experts to provide
deep knowledge bases in very specific domains.
On the other hand, neural nets learn by themselves, needing
only “ground truth” and algorithms development from people. Of course, that brings up the problem that
their solutions are black box solutions – you can’t really tell why they give
the answers that they do.
Link to Part 2:
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Now that you have read of some cutting edge science, you
should consider reading some Science Fiction.
How about a short story, set in the Arctic, with some alien and/or
paranormal aspects. Only 99 cents on
Amazon.
The Magnetic Anomaly: A Science Fiction Story
“A geophysical crew went into the Canadian north. There were
some regrettable accidents among a few ex-military who had become geophysical
contractors after their service in the forces. A young man and young woman went
temporarily mad from the stress of seeing that. They imagined things, terrible
things. But both are known to have vivid imaginations; we have childhood
records to verify that. It was all very sad. That’s the official story.”
Amazon U.S.: https://www.amazon.com/dp/B0176H22B4
Amazon U.K. https://www.amazon.co.uk/dp/B0176H22B4
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“The Zoo Hypothesis”, an Alien Invasion Story
Basically, Enrico Fermi argued (quite convincingly, to many observers), that there had been ample time for an alien intelligence to colonize the galaxy since its formation, so where are they? The Zoo Hypotheses says that they are out there, but have cordoned off the Earth from contact, until we are sufficiently evolved or culturally advanced to handle the impact of alien contact.
This story takes a humorous tongue in cheek approach to that explanation. It also features dogs and sly references to Star Trek. Talk about man’s Best Friend.
Amazon U.S.: https://www.amazon.com/dp/B076RR1PGD
Amazon U.K.: https://www.amazon.co.uk/dp/B076RR1PGD
Amazon Canada: https://www.amazon.ca/dp/B076RR1PGD
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