Synthetic data is essentially artificial information created by computers, rather than collected from real-world events. There are a few key reasons why synthetic data is useful:

• Privacy: Real-world data often contains sensitive information that can't be shared freely. Synthetic data can be created to mimic real data without including any personal details, allowing researchers and developers to work with data without compromising privacy.

• Data augmentation: Sometimes there just isn't enough real-world data available. Synthetic data can be used to supplement real data sets, giving AI models more information to learn from.

• Control: Synthetic data is flexible. Researchers can tailor it to include specific scenarios or features that might be difficult or expensive to find in real data.

In essence, synthetic data is a tool that helps us leverage the power of AI and machine learning responsibly and efficiently.

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