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In the age of artificial intelligence, [massive amounts of data](https://arxiv.org/abs/2401.00676) fuel the growth and sophistication of machine learning models. But not all data is created equal; AI systems [require](https://dl.acm.org/doi/abs/10.1145/3394486.3406477) [high-quality](https://arxiv.org/abs/2212.05129) [data](https://proceedings.neurips.cc/paper/1994/hash/1e056d2b0ebd5c878c550da6ac5d3724-Abstract.html) to produce [high-quality](https://dl.acm.org/doi/abs/10.1145/3447548.3470817) [outputs](https://arxiv.org/abs/1707.02968).
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In the age of artificial intelligence, [massive amounts of data](https://arxiv.org/abs/2401.00676) fuel the growth and sophistication of machine learning models. But not all data is created equal; AI systems [require](https://dl.acm.org/doi/abs/10.1145/3394486.3406477) [high-quality](https://arxiv.org/abs/2212.05129) [data](https://proceedings.neurips.cc/paper/1994/hash/1e056d2b0ebd5c878c550da6ac5d3724-Abstract.html) to produce [high-quality](https://dl.acm.org/doi/abs/10.1145/3447548.3470817) [outputs](https://arxiv.org/abs/1707.02968).
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