Episode 27: How to Build Terrible AI Systems
Vanishing Gradients
The Importance of Fine-Tuning AI Systems
This chapter emphasizes the significance of fine tuning in AI systems, discussing how validations and re-asking can improve accuracy and performance. It explores the impact of fine tuning on making systems faster, more accurate, and error-free, leading to better outcomes. Additionally, the chapter touches on the concept of synthetic data generation in training models and transitioning from vendor-based API models to cost-effective open-source models.
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