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What is semantic caching, and how does it improve LLM app performance?
What metrics do you use to evaluate the performance of a fine-tuned model?
What is the most innovative Generative AI project you have contributed to?
What techniques are used in Generative AI for image generation?
What techniques are used for handling noisy or incomplete data?
How do you ensure that your LLM generates contextually accurate and meaningful outputs?
How can Generative AI create value for enterprises?
How do few-shot and zero-shot learning influence prompt engineering?
How do you manage context across multiple turns in conversational AI?
Which developer tools and frameworks are most commonly used with LLMs?
How do you evaluate the impact of model updates on downstream applications?
Why is specialized hardware important for LLM applications, and how can it be allocated effectively?
Describe the Transformer architecture used in modern LLMs.
Why is data quality critical in Generative AI projects?
How do you prevent overfitting during fine-tuning?
