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submitted 2 months ago by Vittelius@feddit.org to c/fuck_ai@lemmy.world

Somebody built a chatGPT powerded calculator as a joke

https://github.com/Calvin-LL/CalcGPT.io

TODO: Add blockchain into this somehow to make it more stupid.

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[-] jacksilver@lemmy.world 2 points 2 months ago

One of thing I love telling the that always surprises people is that you can't build a deep learning model that can do math (at least using conventional layers).

[-] rain_worl@lemmy.world 0 points 6 days ago

sure you can, it just needs to be specialized for that task

[-] jacksilver@lemmy.world 1 points 6 days ago

I'm curious what approaches you're thinking about. When last looking into the matter I found some research in Neural Turing Machines, but they're so obscure I hadn't ever heard of them and assume they're not widely used.

While you could build a model to answer math questions for a set input space, these approaches break down once you expand beyond the input space.

[-] rain_worl@lemmy.world 0 points 6 days ago

neural network, takes two numbers as input, outputs sum. no hidden layers or activation function.

[-] jacksilver@lemmy.world 1 points 5 days ago

Yeah, but since Neural networks are really function approximators, the farther you move away from the training input space, the higher the error rate will get. For multiplication it gets worse because layers are generally additive, so you'd need layers = largest input value to work.

[-] rain_worl@lemmy.world 1 points 5 days ago* (last edited 5 days ago)

hear me out: evolving finite state automaton (plus tape)

[-] jacksilver@lemmy.world 1 points 5 days ago

Is that a thing? Looking it up I really only see a couple one off papers on mixing deep learning and finite state machines. Do you have examples or references to what you're talking about, or is it just a concept?

[-] rain_worl@lemmy.world 1 points 5 days ago* (last edited 5 days ago)

just a slightly seared concept
though it's just an evolving turing machine

this post was submitted on 09 Sep 2024
139 points (98.6% liked)

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