Finally, I understand machine learning

in Programming & Dev • 3 years ago

The distinction between machine learning (ML) and artificial intelligence (AI) is a puzzle to me. I'm still puzzled, but, I think I've got ML down now.

You know ML and AI are important because people Throw Around The Abbreviations (TATA).



Doing a bit of digging, I now realize there may be three things at play here: ML, AI, and hard code. I guess that's (HC), I dunno. Hard code consists of hard-and-fast rules that are carried out every single time in the same way.

Machine learning seems one step above hard code. As I understand, ML is still hard code, but next level HC. With ML, actions can change based on past actions in an attempt to get better results. When ML and AI cease to still be hard code, that is when ML and AI start to write and execute their own code...oh boy! We're in trouble then.

To understand machine learning I had to draw up an animation so that it'd stick in my chipmunk brain. In my analysis, here's the difference between machine learning and hard code.



tldr;

HC: Do the same thing every dang time no matter the result. It's hard coded.
ML: It's still hard coded, but this time is says to: (1) try it, (2) test the result, (3) if result is bad, then do something else, (4) if result is good, repeat it

To do next: figure out the difference between ML and AI.

With thanks to @iviaxpow3r for tickling my chipmunk brain on this topic which I've never understood.


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3 years ago in Programming & Dev by
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     3 years ago  

    As I understand from my graduation days, ML is a subset of AI. Well, everything has to be hard-coded in some ways. All the algorithms changing are just a few variables each time they perform a task and try to minimize the error in the system.

    The next logical goal will be to understand Deep learning and some NLP (natural language Processing) as well. Once, I knew all the buzzwords out there. But I need a refresher course. hehe

    Knowledge is Power! Keep on learning, brother. ✌️

    !LUV

    [-]
     3 years ago  

    From what I understand, this is essentially how humans learn too.

    I think ML becomes more of a full AI when we apply just a few more things to it:

    1. The ability to improve its own code (already possible with Codex by OpenAI)
    2. The ability to adapt/refine/change what it’s optimizing for… in your bridge example it would be like changing the code so that it removes the assuming it’s needs a bridge and rather just needs to get over the chasm, etc…

    I don’t know if we’re far off from either of these changes being very doable.

    !LUV the thoughts :)
    !PIZZA !ALIVE

    [-]
     3 years ago  

    Ahh. I was starting to figure think along what you're saying for AI, that altering the "hard code" as the next step. I'll keep thinking on it.
    As to how humans learn, no doubt we learn the same way. A quote I like by Will Rogers: Good judgment comes from experience, and a lot of that comes from bad judgment. The one thing that I'd also throw out is that sometimes, we humans have that stroke of genius lightbulb moment, that new hypothesis that just synthesizes seemingly from nowhere. It may be infrequent, but it happens.
    !LUV

    [-]
     3 years ago  

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       3 years ago  

      🍕 PIZZA !

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         3 years ago  

        This post just scared the bejesus out of me.
        AI : Build the platform and then kill all humans who built the other bridge.

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           3 years ago  


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