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Every day, a large portion of the population
is at the mercy of a rising technology,
yet few actually understand what it is.
Artificial intelligence. You know, HAL 9000
and Marvin the Paranoid Android?
Thanks to books and movies,
each generation has formed
its own fantasy of a world ruled
-- or at leased served -- by robots.
We've been conditioned to expect flying cars
that steer clear of traffic
and robotic maids whipping up our weekday dinner.
But if the age of AI is here,
why don't our lives look more like the Jetson's?
Well, for starters, that's a cartoon.
And really, if you've ever browsed Netflix movie suggestions
or told Alexa to order a pizza,
you're probably interacting with artificial intelligence
more than you realize.
And that's kind of the point.
AI is designed so you don't realize
there's a computer calling the shots.
But that also makes understanding what AI is,
and what it's not, a little complicated.
In basic terms, AI is a broad area of computer science
that makes machines seem
like they have human intelligence.
So it's not only programming a computer to drive a car
by obeying traffic signals, but it's when that program
also learns to exhibit signs of human-like road rage.
As intimidating as it may seem,
this technology isn't new.
Actually, for the past half-a-century,
it's been an idea ahead of its time.
The term "artificial intelligence" was first coined back in
1956 by Dartmouth professor John McCarthy.
He called together a group of computer scientists and mathematicians
to see if machines could learn like a young child does,
using trial and error to develop formal reasoning.
The project proposal says they'll figure out how to make machines
"use language, form abstractions and concepts,
solve kinds of problems now reserved for humans,
and improve themselves."
That was more than 60 years ago.
Since then, AI has remained for the most part
in university classrooms and super secret labs ...
But that's changing.
Like all exponential curves, it's hard to tell when a line
that's slowly ticking upwards is going to skyrocket.
But during the past few years, a couple of factors
have led to AI becoming the next "big" thing:
First, huge amounts of data are being
created every minute. In fact, 90% of the world's data
has been generated in the past two years.
And now thanks to advances in processing speeds,
computers can actually make sense
of all this information more quickly.
Because of this, tech giants and venture capitalists
have bought into AI and are infusing the market
with cash and new applications.
Very soon, AI will become a little less artificial,
and a lot more intelligent.
Now the question is: Should you brace yourself for yet
another Terminator movie, live on your city streets?
Not exactly. In fact, stop thinking of robots.
When it comes to AI, a robot is nothing more than
the shell concealing what's actually used
to power the technology.
That means AI can manifest itself in many
different ways. Let's break down the options.
First, you have your bots. They're text-based and
incredibly powerful, but they have limitations.
Ask a weather bot for the forecast, and it will tell you
it's partly cloudy with a high of 57.
But ask that same bot what time it is in Tokyo,
and it'll get a little confused.
That's because the bot's creator only programmed it to
give you the weather by pulling from a specific data source.
Natural language processing makes these bots
a bit more sophisticated.
When you ask Siri or Cortana
where the closest gas station is,
it's really just translating your voice into text,
feeding it to a search engine,
and reading the answer back in human syntax.
So in other words, you don't have to speak in code.
At the far end of the spectrum is machine learning,
and honestly, it's one of the most exciting areas of AI.
Like a human, a machine retains information
and becomes smarter over time.
But unlike a human, it's not susceptible to things like
short-term memory loss, information overload,
sleep deprivation, and distractions.
But how do these machines actually learn?
Well, while it may be easy for a human to know
the difference between a cat and a dog,
for a computer, not so much.
You see, when you're only considering
physical appearance, the difference between
cats and dogs can be a little gray.
You can say cats have pointed ears
and dogs have floppy ears,
but those rules aren't universal.
Between tail length, fur texture, and color,
there are a lot of options,
and that means a lot of tedious rules someone would
have to program manually to help a computer
spot the difference.
But remember -- machine learning is about making
machines learn like humans. And like any toddler,
that means they have to learn by experience.
With machine learning, programs analyze
thousands of examples to build an algorithm.
It then tweaks the algorithm
based on if it achieves its goal.
Over time, the program actually gets smarter.
That's how machines like IBM's Watson can
diagnose cancer, compose classical symphonies,
or crush Ken Jennings at Jeopardy.
Some programs even mimic the way
the human brain is structured,
complete with neural networks that help humans --
and now machines -- solve problems.
Generations have long imagined the ramifications of AI,
visualizing a society where machines seek revenge
and wreak havoc on human society.
However, the more logical and pressing question is:
How will AI affect your job?
Will it make your work obsolete?
Just like the Industrial Revolution,
it's not human versus machine.
It's human and machine versus problem.
The point is that artificial intelligence
helps you accomplish more in less time,
taking on the repetitive tasks of your job
while you master the strategy and relationships.
That way, humans can do what they do best … be human.