

Comparing the hallucinations of four similarly trained neural nets [video] - bemmu
https://www.youtube.com/watch?v=32GnAI3nrsQ

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Ygg2
Could someone give a bit more background on what hallucination mean in context
of neural nets?

I'm not sure what the goal or methods of achieving it are?

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bemmu
As I understood it, you ask the net what it sees in the image and then make it
adjust the image so that it sees more of that thing.

So if a cloud looks slightly like a dog, it will make it even more doggy.

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Nursie
Dogs in particular seem to drop out of the nets I've played with very
regularly.

I did find the lizard setting eventually though...

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m-i-l
I depends on what the networks have been trained to recognise - if they have
been trained to recognise images of dogs then they are more likely to detect
dogs in clouds. See also
[https://news.ycombinator.com/item?id=9818077](https://news.ycombinator.com/item?id=9818077)
.

And see also
[https://news.ycombinator.com/item?id=9736598](https://news.ycombinator.com/item?id=9736598)
for more background to the topic.

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dharma1
was thinking about this, all the deepdream images we've been seeing look
really similar because they all use the same network, would be interesting to
use custom trained networks more variation

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dmd
Well, really they look similar because nobody bothers to use anything but the
default training set it comes with - which happens to contain tons of dogs.

