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DeepSeek-OCR

LLM context cost is crushing your budget. The O² scaling of self-attention is a real economic barrier to long context. DeepSeek-OCR's solution is delightfully counterintuitive: Context Optical Compression. They turn text back into a picture to save tokens. The result? A game-changing ~10x lossless compression ratio. 🤯 We break down the architecture (the 16x convolutional compressor) and why this is the future of efficient long context management. What do you think of the idea of applying this to conversation history, simulating human memory decay (blurriness for older context)? 👇 🎧 Listen to the deep dive: YouTube:    • DeepSeek-OCR: Contexts Optical Compression...   Spotify: https://open.spotify.com/episode/2GFQ... Apple: https://podcasts.apple.com/us/podcast... #GenAI #LevelUP #AI #AiPapers #MultimodalAI #Innovation #MachineLearning