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Related Questions
- What are some common types of out-of-distribution inputs that AI models may encounter?
- How can AI models overfit to in-distribution data and fail on out-of-distribution inputs?
- What are some strategies for detecting and handling out-of-distribution inputs in AI models?
- Can AI models learn to adapt to new or unseen data distributions, and if so, how?
- How do different types of AI models (e.g. neural networks, decision trees) handle out-of-distribution inputs?
- What are some potential consequences of AI models failing on out-of-distribution inputs, and how can they be mitigated?
- Are there any techniques for training AI models to be more robust to out-of-distribution inputs, and if so, what are they?
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