What are the main challenges faced in AI and QA?

What are the main challenges faced in AI and QA?

Some key challenges include data quality, bias in algorithms, and the need for continuous learning.

How does data quality impact AI performance?

Data quality directly affects the accuracy and reliability of AI models; poor data can lead to incorrect predictions.

What are some ways to mitigate bias in AI?

Mitigating bias can involve diverse training data, regular audits, and implementing fairness algorithms.

Can you explain the importance of continuous learning in AI?

Continuous learning allows AI systems to adapt to new data and changing environments, improving their effectiveness.