Synthetic Data Solutions
The conversation highlights the critical role of synthetic data in addressing edge cases during model training, particularly for large language models. It emphasizes the importance of selecting the right data to enhance model capabilities, especially in sensitive fields like healthcare, where privacy constraints limit data sharing. A small amount of targeted data can significantly improve a model's performance, demonstrating the potential of fine-tuning in specialized domains.In this clip
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Machine Learning Street Talk (MLST)
Cohere's SVP Technology - Saurabh Baji
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