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Diffusion model’s were not built in a day, so we will learn the underlying concepts that helped us reach to diffusion model. Autoencoders These are the most basic type, its used for reconstruction of data, for example, if you are given an image, you can train an autoencoder to reconstruct the image. These can be used for dimensionality reduction, feature extraction and data compression. Variational Autoencoders They are first in the category to produce new data points from the existing dataset by learning the latent space of the data. We produce 2 vectors from the encoder namely, mean and log variance and we sample a vector from a gaussian distribution with mean and variance as parameters. This latent vector is then given to the decoder to reconstruct the image of the same size as the original image. ...

Wireless Network Adapter aka wifi card that is used to connect to wifi’s WEP : oldest WPA : Any certificate can lead to leak WPA2 : kick a user, then he reconnects, capture the certificate, 4-way handshake ,capture the certificate in betweeen WPA3 : all password attempts need to be on internet Monitor mode In this mode it becomes a radio sniffer, listens to all wireless signals in the air on a specific channel. Hear’s everything happening in the room ...