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The Theory of Deep Learning: Why Do Ne…
Deep learning shines in practice, but why does theory always lag behind? This article surveys the over-parameterization paradox, implicit regularization, NTK, the information bottleneck, and more.

A deep dive into building a Variational Autoencoder (VAE) from scratch with PyTorch and PIL. Covers the encoder, decoder, reparameterization trick, and KL divergence loss to help you truly understand the fundamentals of generative AI.

The Lily Jay incident exposes the AI fraud industry chain: how deepfakes, image synthesis, and content automation create fake identities. Practical methods for identifying false content in the AI era.