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You’ve probably heard of machine learning and artificial intelligence, but are you sure you know what they are? If you’re struggling to make sense of them, you’re not alone. There’s a lot of buzz that makes it hard to tell what’s science and what’s science fiction. Starting with the names themselves…
Contrary to popular belief, machine learning is not a magical box of magic, nor is it the reason for $30bn in VC funding. At its core, machine learning is just a thing-labeler, taking your description of something and telling you what label it should get. Which sounds much less interesting...
What about artificial intelligence (AI)? While the academics argue about the nuances of what AI is and isn’t, industry is using the term to refer to a particular type of machine learning. In fact, most of the time people just use them interchangeably, and I can live with that. So AI’s also about thing-labeling. Were you expecting robots?
Something sci-fi with a mind of its own, something humanoid? Well, today’s AI is not that. But we’re a species that sees human traits in everything. We see faces in toast, bodies in clouds, and if I sew two buttons onto a sock, I might end up talking to it. That sock puppet’s not a person, and neither is AI.
Machine learning is a new programming paradigm, a new way of communicating your wishes to a computer.
In the traditional programming approach, a programmer would think hard about the pixels and the labels, communicate with the universe, channel inspiration, and finally handcraft a model. A model’s just a fancy word for recipe, or a set of instructions your computer has to follow to turn pixels into labels.
Wouldn’t it be better if you could just say to the computer, “Here, look at a bunch of examples of cats, look at a bunch of examples of not-cats, and just figure it out yourself”? That is the essence of machine learning. It is a completely different programming paradigm. Now, instead of giving explicit instructions, you program with examples and the machine learning algorithm finds patterns in your data and turns them into those instructions you couldn’t write yourself. No more handcrafting of recipes!
At its core, machine learning is just a thing-labeler, taking your description of something and telling you what label it should get. Which sounds much less interesting...
originally posted by: DupontDeux
a reply to: dug88
At its core, machine learning is just a thing-labeler, taking your description of something and telling you what label it should get. Which sounds much less interesting...
It may be simple, but it is not very accurate.
The above specifically applies to tasks like image recognition - putting the right label on the right item - but machine learning is also what is behind, say, the algorithms that make people spend as much time as possible on YouTube. That is far from as simple as labeling things.
CGP Gray explains it very well:
originally posted by: IgnoranceIsntBlisss
a reply to: Starbuck799
Unless you're name is Google and the core of your design that is behind all of the services is to study humans via all the inputs you get, including them all talking all the time not just on their phones but around them. Along the way you have 'all known' video (ever produced by humans) inside the 'data set' (to be studied by the AI / AGI), along with every book ever written, every sheet of newspaper ever printed, and so on, for years upon years upon years your global brain studying all human media ever produced, more and more every bit of communications being transmitted, every conversation every images every action within every moment people have in and around the Zombie Network of PC's, "phones" a billion of them all carrying around these nodes in the Zombie Network (not to mention google chips inside cars, tv's, etc robot Ai appliances and beyond)....
You're just not thinking the scale of what is, how far things can be pushed, let alone the Law of Accelerating Returns (which is increasingly exponentially running amok ever more ubiquitously).
originally posted by: IgnoranceIsntBlisss
a reply to: Starbuck799
Because at the end of every day every single thing going on inside us (and everything else) is math, is it not?