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@nguyenlieudungcuquynhnhu: Chè đậu đỏ wonderful lon 900g #xuhuong#nguyenlieuphachequynhnhu#nguyenlieuphache#chedaudo#wonderfull

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Saturday 06 December 2025 07:52:24 GMT
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DeepSeek may have just changed the entire future of AI — and no one saw it coming. They released a new open-source model called DeepSeek OCR, and it’s going viral for a reason. It compresses 1,000 words of text into just 100 tokens — while keeping 97% of the original information. Here’s why that’s a massive breakthrough. Every AI model today is limited by something called the context window — basically how much information it can process at once. The more data you feed in, the more expensive and computationally heavy it gets. DeepSeek found a workaround — and it’s kind of genius. They flipped an old saying — a picture is worth a thousand words — into literal AI engineering. Instead of feeding text as digital words, they convert it into an image first. Then: • The image gets split into tiny visual “patches.” • A model compresses those patches down to capture patterns and details. • Another model reassembles everything and converts it back into text the AI can understand. The result? AI can now handle 10 times more information in the same space. A model that could process 1 million tokens can now handle 10 million. Even at extreme compression — 10 to 12x — it still keeps 90% accuracy. And it’s incredibly fast: one NVIDIA A100 GPU can process about 200,000 pages per day. They trained it on 30 million PDF pages across 100+ languages. The implications are huge: • You can feed entire legal libraries or research databases into AI — all at once. • No more chunking documents or losing context halfway through. • AI could reason over massive knowledge bases that were previously too big to fit. Even Andrej Karpathy (former Director of AI at Tesla) said maybe all AI inputs — even text — should be images from now on. Because they’re just more efficient. And the best part? DeepSeek made it fully open-source on GitHub. Anyone can use it, improve it, or integrate it into their own systems. This isn’t just a small performance boost. It’s a fundamental shift in how AI processes information.
DeepSeek may have just changed the entire future of AI — and no one saw it coming. They released a new open-source model called DeepSeek OCR, and it’s going viral for a reason. It compresses 1,000 words of text into just 100 tokens — while keeping 97% of the original information. Here’s why that’s a massive breakthrough. Every AI model today is limited by something called the context window — basically how much information it can process at once. The more data you feed in, the more expensive and computationally heavy it gets. DeepSeek found a workaround — and it’s kind of genius. They flipped an old saying — a picture is worth a thousand words — into literal AI engineering. Instead of feeding text as digital words, they convert it into an image first. Then: • The image gets split into tiny visual “patches.” • A model compresses those patches down to capture patterns and details. • Another model reassembles everything and converts it back into text the AI can understand. The result? AI can now handle 10 times more information in the same space. A model that could process 1 million tokens can now handle 10 million. Even at extreme compression — 10 to 12x — it still keeps 90% accuracy. And it’s incredibly fast: one NVIDIA A100 GPU can process about 200,000 pages per day. They trained it on 30 million PDF pages across 100+ languages. The implications are huge: • You can feed entire legal libraries or research databases into AI — all at once. • No more chunking documents or losing context halfway through. • AI could reason over massive knowledge bases that were previously too big to fit. Even Andrej Karpathy (former Director of AI at Tesla) said maybe all AI inputs — even text — should be images from now on. Because they’re just more efficient. And the best part? DeepSeek made it fully open-source on GitHub. Anyone can use it, improve it, or integrate it into their own systems. This isn’t just a small performance boost. It’s a fundamental shift in how AI processes information.
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