Machine Learning
I’ve heard the phrase Machine Learning banging around the media more intensely over the past few years and you know what that means… I’m not happy until I know what is really means.
TO THE BAT-MOWER!
My first conjured image is of course a lawn mower in a classroom trying to fumble its way through the shakespearean sonnet.
It seems I wasn’t far off! Ok I was pretty far off. But there is a smart lawn mower t...
Machine Learning
I’ve heard the phrase Machine Learning banging around the media more intensely over the past few years and you know what that means… I’m not happy until I know what is really means.
My first conjured image is of course a lawn mower in a classroom trying to fumble its way through the shakespearean sonnet.
It seems I wasn’t far off! Ok I was pretty far off. But there is a smart lawn mower that learns how to cut you lawn which is in fact machine learning. It’s the word machine which I find distracting. We’re not accustomed to speaking of computers as machines or machines as computers although the latter is quickly becoming so and hence the phrase.
A few podcasts ago we discussed Self-Driving Cars and machine learning is definitely at the core of their success. We have all driven cars and would unanimously agree that no two routes are the same even if you’re driving the same route every day. There is always some element of surprise. These cars would not exist if not for some very clever learning algorithms which prioritise success paths over failures in order to adapt their reactions and even their default behaviour to new situations. Just like us human learners.
What about other non-driving based applications? The mower is essentially a tiny little self-driving car that works out your lawns shape and the best route while having the luxury of not having to contend with human driven lawn mowers, drinking and just mowing all over the place.
Machine learning and AI (Artifical Intelligence) are peanut butter and chocolate, ham and cheese, bacon and…. everything. What’s the point of learning if you aren’t going to use what you have learned? I could dive deep into the inner workings of machine learning algorithms but that would be a serious snoozer to the non-enthusiast and as complex and fasinating as it is, it’s more fun to try to derive the gist of what it all means by looking at the applications because without application there is no learning.
Are we surrounded by learning machines who will eventually take over the world? Yes!
But how? Let’s have a crack at a top 5!
Check out the podcast for the list.
The shownotes for the episode are here:
https://codifyre.com/technology/machine-learning-are-you-smarter-than-a-toaster/
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