How do AI systems learn and improve over time?

How do AI systems learn and improve over time?

AI systems learn through a process called machine learning, where they analyze data to identify patterns.

What types of data are used for training AI?

AI can be trained on various types of data, including text, images, and audio, depending on the application.

Can you explain supervised and unsupervised learning?

Sure! Supervised learning uses labeled data to train models, while unsupervised learning finds patterns in unlabeled data.

How do you evaluate the performance of an AI model?

Performance is often evaluated using metrics like accuracy, precision, recall, and F1 score, depending on the task.

What are some challenges in training AI systems?

Challenges include data quality, bias, overfitting, and the need for significant computational resources.