Frequently Asked Questions (FAQs)

What is the Difference between 'Diffusion Model' and 'Generative Model using Transformers' ?

What is the main difference between the GPT-4 'Transformer Network' and 'Diffusion Model' ?

Is a Transformer Network a Feed-forward Neural Network?

What is a Recursive Neural Network (RNN), Recurrent Neural Network (RNN) and Feed-forward Neural Network (FNN)?

What is a Convolution Neural Network (CNN)?

Is CNN connected or related to Diffusion Models in any way?

Can Transformer Networks be used with Diffusion Models just as CNN is used?

Are CNN's are a better combination with Diffusion Models?

Can backpropagation be considered 'Fine Tuning'?

What is a 'feature detector' and how are 'feature detectors' related to 'back propagation' in Ai?

If the idea of back propagation is to just put in random weights to begin with, would that make the feature detector useless?

Besides Convolutional Neural Networks (CNNs), which other type of Deep Learning Architectures use feature detectors and back propagation?

How do Multilayer Perceptron (MLP) networks compare to Convolutional Neural Networks (CNNs)?

Do Transformer Networks have similar Layers as CNN's ?

Do RNN's have layers like CNN's?

How do you compare the Layers between Transformers and RNN's?

What is the main difference between Transformer Networks and RNN's 'Self-Attention' layer and other major differences?

Why is it called a 'Transformer'? What has the transformer got to do with 'Attention'?

Does a transformer architecture also have Layers like Convolutional Neural Networks (CNNs) Architecture?

What is a .cpkt file?

Why wouldn't we stick with Current Digital Computers AI?

What is 'The next things' you think this technology will do that will impact people's lives?

Will Google be careful in the 'labeling' or careful in the way they meddle with it so it doesn't do lousy things?

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