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Three bad recipes generated by neural network (2017)

aiweirdness.com

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Re: Three bad recipes generated by neural network (2017)

#3
If you put whole recipes into the neural network, of course it won't work. You need to separate the parts. One neural network for ingredients, and a separate one for "instructions".

Then you feed the output of the first network into the second to get a set of preparations that actually prepare the chosen ingredients.

Re: Three bad recipes generated by neural network (2017)

#4
post #2

It failed at making recipes but it excels at comedy!

apparently randomness is important factor in comedy, just like somewhat funny memes created by neural network https://news.ycombinator.com/item?id=17302917 maybe joke-generation is actual future of AI?

Re: Three bad recipes generated by neural network (2017)

#5
_Highly_, highly related: https://gist.github.com/nylki/1efbaa36635956d35bcc

I tried condensing it a couple years ago ( https://news.ycombinator.com/item?id=14376816 - I was i336_ then), but I think the original is worth slowly reading through.

There are some definite gems in there that will most definitely cheer you up at the very least.

Re: Three bad recipes generated by neural network (2017)

#7
post #4
post #2

It failed at making recipes but it excels at comedy!

apparently randomness is important factor in comedy, just like somewhat funny memes created by neural network https://news.ycombinator.com/item?id=17302917 maybe joke-generation is actual future of AI?

Perhaps randomness is a shortcut to absurdity, but good comedy is rarely random. (Is it ever? Honest question.)

Re: Three bad recipes generated by neural network (2017)

#9
post #3

If you put whole recipes into the neural network, of course it won't work. You need to separate the parts. One neural network for ingredients, and a separate one for "instructions". Then you feed the output of the first network into the second to get a set of preparations that actually prepare the chosen ingredients.

What about your solution makes it right?

Re: Three bad recipes generated by neural network (2017)

#10
What I get from this is that neural networks really have no idea what they are talking about (which of course is no news). How could they? Is a feature more important or relevant than another just because of its frequency?

People look at the output of neural networks and when they work they say - of course they do. And when they don't they rationalize it with "your model was wrong from the start".

(This is similar to how Alpha-Zero "discovered" the optimal chess openings. Of course it did, it was bound to find them by the rules of chess).

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