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Why is security and governance critical when managing LLM applications?
What are the differences between encoder-only, decoder-only, and encoder-decoder architectures?
Why is specialized hardware important for LLM applications, and how can it be allocated effectively?
What are Large Language Models (LLMs), and how do they relate to foundation models?
What are the limitations of current Generative AI models?
Can you explain the concept of feature injection and its role in LLM workflows?
How do you train a model for generating creative content, like poetry?
How can organizations identify business problems suitable for Generative AI?
This list covers a wide spectrum of topics, ensuring readiness for interviews in Generative AI roles.
What measures do you take to secure sensitive data during model training?
What does "accelerating AI functions" mean, and why is it important?
How do you ensure compatibility between Generative AI models and other AI systems?
What key terms and concepts should one understand when working with LLMs?
How do you manage context across multiple turns in conversational AI?
How do you handle setbacks in AI research and development?
