Emerging Architectures for LLM Applications - Raja Iqbal

Raja explores three key approaches: training a model from scratch, fine-tuning a foundation model with custom data, and the innovative concept of "in-context learning." He emphasizes the significance of data engineering in using vector databases, indexing, and semantic caching to enhance LLM applications. The talk covers common design patterns, challenges in real-world scenarios, and the importance of simplicity in handling complex problems.
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