Can you explain the historical context of Generative AI and how it has evolved?
What are the trade-offs between security and ease of use in Gen AI applications?
What is the role of vector embeddings in Generative AI?
What factors should be considered when comparing small and large language models?
What considerations are involved in processing for inference in LLMs?
How do you ensure knowledge sharing within your team?
Can you explain reinforcement learning and its role in improving LLMs?
How do you prioritize tasks in a Generative AI project?
How do AI agents function in orchestration, and why are they significant for LLM apps?
What steps can be taken to measure, learn from, and celebrate success in Generative AI projects?
What are the applications of Generative AI in finance?
What are the privacy implications of using large datasets for Generative AI?
What are Large Language Models (LLMs), and how do they relate to foundation models?
How do you ensure compliance with industry regulations in AI projects?
Explain the concepts of pretraining and fine-tuning in LLMs.