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Data synthesis for SOTA LLMs
Practical AI: Machine Learning, Data Science, LLM
Understanding Synthetic Data and Data Distillation in AI Training
Synthetic data refers to data generated by AI models that can be utilized for training, particularly in situations where resources are limited, such as individuals using laptops instead of data centers. The challenge lies in enabling smaller models, like those with 7 billion parameters, to effectively compete with larger models that possess significantly more parameters. Synthetic data serves as a solution to this problem, as it allows for efficient training and enhances model capabilities. Data distillation complements this by simplifying complex knowledge into more consumable formats, akin to a seasoned expert condensing their extensive understanding into brief, insightful lessons. This process leverages high-quality data from advanced models to distill knowledge into concise, actionable insights, thus making sophisticated AI training more accessible and effective.
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