Computer Vision
Diffusion Models Explained: How AI Turns Noise Into Images
How diffusion models work: from noise to image step by step, text prompts and guidance, latent diffusion, flow matching, and how Stable Diffusion and Sora use them.
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Computer Vision
Segment Anything (SAM) Explained: Click-to-Cut-Out AI
What Meta's Segment Anything Model does: prompts, its three-part design, the 1-billion-mask SA-1B dataset, zero-shot results, and SAM 2 for video.
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Computer Vision
Vision Transformer (ViT) Explained: How an Image Becomes Patches
How the Vision Transformer cuts an image into 16x16 patches and reads them like words, why it needed large datasets, its three sizes, and ViT vs CNN.
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Computer Vision
Computer Vision Explained: How AI Sees Images
Computer vision explained simply: how a computer reads an image, classification vs detection vs segmentation, how models are trained, uses and limits.
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