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- How might Infermatic.ai struggle to maintain coherence when processing lengthy, context-dependent input?
- What types of context-dependent input might cause Infermatic.ai to generate inaccurate or irrelevant responses?
- Can Infermatic.ai handle multi-turn conversations with complex context, or might it falter in understanding the nuances of the conversation?
- How might Infermatic.ai's performance be affected by the presence of ambiguity, sarcasm, or idioms in context-dependent input?
- What strategies can be employed to mitigate the effects of context-dependent input on Infermatic.ai's performance?
- In what ways might Infermatic.ai's lack of common sense or real-world experience impact its ability to handle context-dependent input?
- Can Infermatic.ai learn from its mistakes and adapt to context-dependent input over time, or is it limited by its initial training data?
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