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Related Questions
- How do large language models cope with the rapid evolution of ontologies and linguistic nuances?
- What strategies can be employed to ensure that AI models adapt to changes in language usage and semantic shifts over time?
- Can you explain the impact of ontological drift on the accuracy and reliability of machine learning models?
- How do you address the challenge of updating and fine-tuning language models to keep up with emerging trends and concepts?
- What role does data curation play in maintaining the relevance and accuracy of ontologies used in AI applications?
- How can developers mitigate the effects of ontological mismatch between training and deployment environments?
- What are some best practices for handling the dynamic nature of ontologies and language models in real-world applications?
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