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AI datasets

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Jul 21, 2026 · Artificial Intelligence

Building High-Quality AI Datasets: From Business Scenarios to Semantic Data Products

This article outlines a six-step methodology for building high-quality AI datasets as semantic data products, starting from business scenario definition through semantic modeling, evidence mapping, task-specific processing, multi-dimensional validation, and continuous iteration via runtime feedback.

AI datasetsAgentData Validation

0 likes · 12 min read

Building High-Quality AI Datasets: From Business Scenarios to Semantic Data Products

Old Zhang's AI Learning

Feb 5, 2026 · Artificial Intelligence

Distilling GLM‑4.7‑Flash with Claude‑Opus‑4.5 for Easy Consumer‑GPU Deployment

The article explains how TeichAI used Claude‑Opus‑4.5 to generate a high‑quality 250‑sample reasoning dataset and distill the GLM‑4.7‑Flash model into a compact GGUF version that runs on a single consumer‑grade GPU via llama.cpp, detailing the workflow, quantization options, and practical considerations.

AI datasetsGGUFUnsloth

0 likes · 6 min read

Distilling GLM‑4.7‑Flash with Claude‑Opus‑4.5 for Easy Consumer‑GPU Deployment

Data Thinking Notes

Sep 3, 2025 · Artificial Intelligence

What Makes a High‑Quality AI Dataset and How to Evaluate It?

This article defines what constitutes a high‑quality AI dataset, explains why such datasets are crucial—especially given the dominance of English resources and the scarcity in Chinese—and outlines the scientific evaluation framework covering completeness, accuracy, balance, timeliness, consistency, relevance, and other key dimensions.

AI datasetsdataset evaluationmachine learning

0 likes · 4 min read

What Makes a High‑Quality AI Dataset and How to Evaluate It?