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How does the bias in training data affect the performance of AI models?
Explain the difference between supervised, unsupervised, and reinforcement learning.
What is model interpretability, and why is it important?
What frameworks can you use for ethical AI development?
What techniques can improve the explainability of AI models?
What are standardization and normalisation? Give one advantage of each over the other?
Why is data considered crucial in AI projects?
How can you optimize AI models for edge deployment?
Can you explain how AI is used in predictive maintenance for industrial equipment?
Can you describe the importance of model interpretability in Explainable AI?
What are some of the major challenges facing AI research today?
What are the risks of using open-source Generative AI models?
How is AI used in procedural content generation?
What are some techniques for developing low-power AI models?
How do you approach deployment of AI models?
