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@mpcute_dangiu:
phun cute
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Region: VN
Wednesday 23 September 2026 07:06:00 GMT
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1- Sparse encoding: Like describing a beach photo using only “ocean,” “sand” and “sun,” instead of storing every tiny detail. 2. Autoencoders: compressing a photo into a smaller file and then reconstructing a close copy of the original. 3. Pruning: cutting unnecessary branches from a tree—the model becomes smaller while keeping the parts that matter. 4. Overfitting: Like memorising every practice-test answer but failing when the real exam asks different questions. 5. Inference: When you ask ChatGPT a question, inference is the process it uses to generate its answer. 6. Grokking: Example would be like struggling with maths for weeks and then suddenly understanding the rule instead of memorising the answers. 7. Distillation: a large expert model teaching a smaller model to give similar answers with less computing power. 8. Quantization: Like rounding 3.14159265 to 3.14 so the model’s numbers require less memory and are faster to calculate.
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