What steps are involved in defining the use case and scope of an LLM project?
What are the key elements to consider when creating user interfaces for LLM applications?
What are the challenges of using large datasets in LLM training?
How do you implement beam search for text generation?
What strategies can be used to adapt LLMs to a specific use case?
What distinguishes general-purpose LLMs from task-specific and domain-specific LLMs?
What are the differences between encoder-only, decoder-only, and encoder-decoder architectures?
How do you ensure that your LLM generates contextually accurate and meaningful outputs?
How do you ensure compliance with industry regulations in AI projects?
What does "accelerating AI functions" mean, and why is it important?
How do you prepare and clean data for training a generative model?
How can Generative AI be used for text summarization?
Why is security and governance critical when managing LLM applications?
What are the best practices for integrating LLM apps with existing data?
How do you ensure collaboration between data scientists and software engineers?