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How do you measure fairness in an AI model?
What methods are used to make AI decisions more transparent?
Explain the difference between data bias and algorithmic bias.
What are the limitations of current Generative AI models?
Can you describe the importance of model interpretability in Explainable AI?
What are the hardware constraints to consider when developing Edge AI applications?
What are Large Language Models (LLMs), and how do they relate to foundation models?
What is prompt engineering, and why is it important for Generative AI models?
What are the best practices for deploying Generative AI models in production?
How do you approach deployment of AI models?
How can you optimize AI models for edge deployment?
Is this artificial intelligence lives over the other software programs and their flexibility?
Tell me what are the last machine learning papers you've read?
What are the ethical considerations in deploying Generative AI solutions?
Why is data considered crucial in AI projects?