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When it comes to optimizing Large Language Models (LLMs) for business success, two approaches often come into play: context optimization and LLM optimization. But what's the difference between these two techniques, and how can you choose the right one for your use case? Avinash Asthana, explores the fundamentals of context optimization and LLM optimization, and discuss how to use each approach to improve accuracy, reduce hallucinations, and increase efficiency. Whether you're a seasoned AI practitioner or just starting out, you'll be better equipped to make informed decisions about how to optimize your LLMs for improved performance.

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