How do you prepare and clean data for training a generative model?
What is prompt engineering, and why is it important for Generative AI models?
How do you handle conflicts in an AI team?
How do you ensure collaboration between data scientists and software engineers?
How do you ensure compliance with industry regulations in AI projects?
How do few-shot and zero-shot learning influence prompt engineering?
Explain the importance of tokenization in LLMs.
What are Large Language Models (LLMs), and how do they relate to foundation models?
Explain the concepts of pretraining and fine-tuning in LLMs.
How does a cloud data platform help in managing Gen AI projects?
How do you measure diversity and coherence in text generated by LLMs?
How is Generative AI used in healthcare?
What steps are involved in defining the use case and scope of an LLM project?
How do you balance innovation with practical business constraints?
What are the privacy implications of using large datasets for Generative AI?
