How do you decide whether to fine-tune or train a model from scratch?
What factors should be considered when comparing small and large language models?
What are some real-world applications of Generative AI?
What is the role of Generative AI in gaming and virtual environments?
What is context retrieval, and why is it important in LLM applications?
What is a vector database, and how is it used in LLM applications?
What tools do you use for managing Generative AI workflows?
What is semantic caching, and how is it used in LLMs?
Can you explain the concept of feature injection and its role in LLM workflows?
How does learning from context enhance the performance of LLMs?
How can latency be reduced in LLM-based applications?
How do you train a model for generating creative content, like poetry?
How can LLM hallucinations be identified and managed effectively?
What is prompt engineering, and why is it important for Generative AI models?
How do few-shot and zero-shot learning influence prompt engineering?