Conscious Artificial Intelligence - Project Update

[schuler]

Some of my own models have millions of trainable parameters with 224x224x3 (150k) inputs. So, input size isn't a limit.

[daringly]

I figured out the error, thanks. I was doing something idiotic.

[schuler]

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]

Very nice 

[schuler]

@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