Welcome to the FAQ page for Infermatic.ai! Here, you can find answers to your questions about large language models and the AI industry. Whether you’re curious about how to use our tools or want to learn more about AI, this page is a great place to start.
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Related Questions
- What are some common sources of bias in training data that can impact model performance and fairness outcomes?
- Can you explain the concept of representation bias and how it affects model performance?
- How do human annotators assess the quality and diversity of training data to identify potential biases?
- What are some techniques used to detect bias in training data, and how do they impact model performance?
- How do human annotators evaluate the fairness of model outcomes, and what are some common fairness metrics used?
- What role do human annotators play in identifying and addressing bias in training data?
- Can you provide examples of how bias in training data can impact model performance and fairness outcomes in real-world applications?
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