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A non-technical explanation of deep learning

parand.com

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Re: A non-technical explanation of deep learning

#21

Post by time_to_smile »

pkdpic wrote: post #13

I love this, but Im always confused in these kinds of analogies what the reward / punishment system really equates to... Also reminds me of Ted Chiang warning us that we will torture innumerable AI entities long before we start having real conversations about treating them with compassion.

Don't love it, it's not correct.

> what the reward / punishment system really equates to

Nothing, and least as far as neural network training goes. This is an extremely poor analogy regarding how neural networks learn.

If you've ever done any kind of physical training and have had a trainer sightly adjust the position of your limbs until what ever activity you're doing feels better, that's a much closer analogy. You're gently searching the space of possible correct positions, guided by an algorithm (your trainer) that knows how to move you towards a more correct solution.

There's nothing analogous to a "reward" or "punishment" when neural networks are learning.

Re: A non-technical explanation of deep learning

#22

Post by [deleted] »

Utkarsh_Mood wrote: post #17
amelius wrote: post #8

The problem with deep learning is opposite. You can understand most of it with just high school math. Advanced math is mostly useless because of the dimensionality of neural nets.

can you elaborate further on what you mean by 'dimensionality of neural nets'? Thanks!

[deleted]

Re: A non-technical explanation of deep learning

#23

Post by jstx1 »

Does stuff like this help anyone?

I still haven’t forgiven CGP Grey for changing the title to his 2017 ML video to “How AIs, like ChatGPT, learn”. The video is about genetic algorithms and has nothing to do with ChatGPT. (or with anything else in modern AI)

Re: A non-technical explanation of deep learning

#24

Post by adrianmonk »

nailer wrote: post #14
teacpde wrote: post #10

Earlier quoted context omitted.

Not the author, but to the author's defense, it is meant to be non-technical. And the first paragraph reads interesting to me.

Most non technical people would think there are zero circumstances where a spreadsheet could be a cat.

It's obvious from context that it's the content of the media. To me at least.

If I play you a song on Spotify and say, "Is this a saxophone?", you wouldn't say, "No, it's a iPhone running Spotify."

If a policeman holds up a photograph of a person and says, "Is this the person who attacked you?", the victim doesn't say, "No, it's an 8 by 10 glossy print."

Re: A non-technical explanation of deep learning

#25

Post by GaggiX »

time_to_smile wrote: post #21
pkdpic wrote: post #13

I love this, but Im always confused in these kinds of analogies what the reward / punishment system really equates to... Also reminds me of Ted Chiang warning us that we will torture innumerable AI entities long before we start having real conversations about treating them with compassion.

Don't love it, it's not correct. > what the reward / punishment system really equates to Nothing, and least as far as neural network training goes. This is an extremely poor analogy regarding how neural networks learn. If you've ever done any kind of physical training and have had a trainer sightly adjust the position of your limbs until what ever activity you're doing feels better, that's a much closer analogy. You'…

>There's nothing analogous to a "reward" or "punishment" when neural networks are learning.

Well deep reinforcement learning.

Re: A non-technical explanation of deep learning

#28

Post by tasty_freeze »

pringk02 wrote: post #12
wrs wrote: post #9

This is the funniest refutation of the Chinese Room argument that I’ve seen. Note that at the end, it’s still the case that none of these people can recognize a cat.

Doesn't that mean it supports the Chinese room argument? I'm not sure I follow your reasoning. (also, popular conciousness forgets that technically the Chinese Room argument is only arguing against the much narrower, and now philosophically unfashionable, "Hard AI" stance as it was held in the 70s)

> the Chinese Room argument is only arguing against the much narrower, and now philosophically unfashionable, "Hard AI" stance as it was held in the 70s

Searle has stood behind his argument in the 70s, but in every decade since then too.

The main failure is that most people fundamentally don't believe they are mechanistic. If one believe in dualism, then it easy to attribute various mental states to that dualism, and of course a computer neural network cannot experience qualia like humans do.

I don't believe in a soul, and thus believe that a computer neural network, probably not today's models but a future one that is large enough and has the right recurrent topology, will be able to have qualia similar to what humans and animals experience.

Re: A non-technical explanation of deep learning

#29

Post by amelius »

Utkarsh_Mood wrote: post #17
amelius wrote: post #8

The problem with deep learning is opposite. You can understand most of it with just high school math. Advanced math is mostly useless because of the dimensionality of neural nets.

can you elaborate further on what you mean by 'dimensionality of neural nets'? Thanks!

Yes, I mean the huge number of trainable parameters.

Re: A non-technical explanation of deep learning

#30

Post by [deleted] »

jstx1 wrote: post #23

Does stuff like this help anyone? I still haven’t forgiven CGP Grey for changing the title to his 2017 ML video to “How AIs, like ChatGPT, learn”. The video is about genetic algorithms and has nothing to do with ChatGPT. (or with anything else in modern AI)

[deleted]
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