Vision Transformer (ViT)
Patch-based attention architecture for image understanding
Episodes
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#6311: How Transformers Process Images and VideoA Vision Transformer divides a standard image into a grid of 16-by-16 pixel patches rather than processing each individual pixel as a token. -
#4672: How Magic Eraser Tools Actually Work: Segmentation + InpaintingTwo AI stages — pixel-level segmentation and generative inpainting — explain how your phone erases objects cleanly. -
#2622: How Transformers Actually Work: Attention, Tokens, and ContextHow one architectural change unlocked chatbots, image generation, and protein folding — explained without the jargon. -
#2060: The Tokenizer's Hidden Tax on Non-English TextWhy does a simple greeting in Mandarin cost more to process than in English? It's the tokenizer's hidden inefficiency. -
#1322: When AI Stops Seeing and Starts ReasoningExplore how AI evolved from simple pixel labeling to understanding intent and context through Vision-Language Models and agentic frameworks.