What You Need to Know About Machine Learning – Part One
The quest for Artificial Intelligence is a field which has both fascinated and terrified mankind for decades. Books like Isaac Asimov’s “Robot” series and Douglas Adams’ “Hitchiker’s Guide to the Galaxy” envision dystopian futures in which Intelligent machines have become indispensable to human life, whilst films like “The Terminator” and “Ex Machina” explore a darker side of AI, where machines become a threat to mankind’s very survival.
So what is the truth? Do we get C-3PO, or do we get Ultron?
Thankfully, that is a debate for another generation to grapple with. For the moment, things are much simpler. At this point, AI– a machine which mimics the human mind, is still a pipe dream.
Machine Learning, however, has been a reality in our lives for quite some time.
A computer program is said to learn from experience “E” with respect to some class of tasks “T” and performance measure “P” if its performance in tasks “T”, as measured by “P” improves with experience “E”
This, of course, is just a fancy way of saying that if a machine is able to perform a task more effectively over time based on measuring its own performance and changing how it performs its tasks accordingly, it can be considered a learning machine.
Today, as ever, mankind has put most of its collective resources in this area into finding ways to get these learning machines to make us money.
And make us money they have.
How, you ask?
It turns out the world is not as chaotic and random as we once thought. Almost everything is predictable on some level, even human behaviour. If one is able to effectively recognize patterns, and use these patterns to anticipate future events, one can do a lot of things much more effectively.
This is what algorithms do.
We won’t bore you with a bunch of math here, you’ll just have to take our word for it for the moment. Mining and compiling enough data and exhaustively analyzing all the variables involved may not produce perfect predictions of future events, but it can get you pretty darn close.
