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Author Topic: Conscious Artificial Intelligence - Project Update  (Read 24658 times)

schuler

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Re: Conscious Artificial Intelligence - Project Update
« Reply #105 on: October 15, 2020, 11:08:46 am »
Some of my own models have millions of trainable parameters with 224x224x3 (150k) inputs. So, input size isn't a limit.

daringly

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Re: Conscious Artificial Intelligence - Project Update
« Reply #106 on: October 21, 2020, 07:35:33 pm »
I figured out the error, thanks. I was doing something idiotic.

schuler

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Re: Conscious Artificial Intelligence - Project Update
« Reply #107 on: October 22, 2020, 07:42:42 pm »
Cool.

In the case that you are interested, I coded a new Hypotenuse Example without preallocating all the training data into memory. This is useful if you have a too large dataset to fit into memory (I've seen training datasets approaching 1TB).

https://github.com/joaopauloschuler/neural-api/blob/master/examples/HypotenuseFitLoading/HypotenuseFitLoading.lpr

:) Wish everyone happy pascal coding :)

nouzi

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Re: Conscious Artificial Intelligence - Project Update
« Reply #108 on: October 22, 2020, 08:04:14 pm »
Very nice  8-)
my english is  bad
Lazarus 2.0.6 free pascal 3.0.4
Lazarus trunk  free pascal trunk 
System : linux mint 19.3 64bit  windows 7 64bit

schuler

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Re: Conscious Artificial Intelligence - Project Update
« Reply #109 on: Today at 01:02:18 am »
@nouzi, thank you for your kind words.

I have 2 news:
  • A new layer type: TNNetConvolutionSharedWeights.
  • Beautiful images created by a neural network.

Beautiful Images
I've attached some images created by a generative adversarial network. The source code can be found here:
https://sourceforge.net/p/cai/svncode/1485/tree/trunk/lazarus/examples/VisualGANTinyImagenet/

TNNetConvolutionSharedWeights
Added today to the API a new convolutional layer type: TNNetConvolutionSharedWeights . Instead of having its own neurons and weights, this convolutional layer uses the same neurons and weights from another existing layer. So, if you need 2 layers with the same neurons, you can add TNNetConvolutionSharedWeights to your network. Why would you need something like this? Maybe, your NN needs to learn the same patterns in different scales (such as big and small dogs are all dogs).

I added an example at:
https://github.com/joaopauloschuler/neural-api/blob/master/examples/SimpleImageClassifier/SimpleImageClassifierSharedWeights.lpr

:) wish everyone happy pascal coding :)

 

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