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Oct '25 • General Discussion 💬
🐋 DeepSeek-OCR
Could this be the JPEG moment for AI?!
Optical compression doesn't just make context cheaper. It makes AI memory architectures viable.
Training data bottlenecks? Solved.
- 200k pages/day on ONE GPU
- 33M pages/day on 20 nodes
- Every multimodal model is data-constrained. Not anymore.
Agent memory problem? Solved.
- The #1 blocker: agents forget
- Progressive compression = natural forgetting curve
- Agents can now run indefinitely without context collapse
RAG might be obsolete.
- Why chunk and retrieve if you can compress entire libraries into context?
- A 10,000-page corpus = 10M text tokens OR 1M vision tokens
- You just fit the whole thing in context
Multimodal training data generation: 10x more efficient
- If you're OpenAI/Anthropic/Google and you DON'T integrate this, you're 10x slower
- This is a Pareto improvement: better AND faster
Real-time AI becomes economically viable
- Live document analysis
- Streaming OCR for accessibility
- Real-time translation with visual context
- All were too expensive. Not anymore.
Karpathy's post
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