Synthetic Data

 Synthetic Data; research paper

Synthetic data is artificially generated data (not collected by physical events for example through surveys, questionnaires etcetera.)

Synthetic data is important in research as it provides true information about a specific topic (for example your gmail categorizing mail as spam, important or non-spam)

Moreover, it is also used for training machine models like robots like Siri, Google and ALEXA.

Synthetic data is also generated to avoid data scarcity (unavailability of data that satisfies the need of a system to provide more precise dynamics)

It can also be used to update the data in AI models and improve their sustainability, for example ChatGPT only has data up to 2021, synthetic data can be used to provide data to it about further years without having to collect it from multiple resources.

Synthetic data can also be used to validate mathematical models by testing its accuracy and reliability before releasing it into the real world 

Last but not least, synthetic data is important as it can be an asset to businesses for privacy concerns and data privacy, faster product testing (mathematical models as mentioned), training machine learning algorithms (instagram, tiktok, twitter etcetera).

Leakage or illegal sharing of data causes businesses huge losses, which is why they invest in synthetic data as it can disguise important data and secure it safely.

For fresh new products, data is almost always unavailable, for example a new mobile or camera being released. Human data is time consuming and cost ineffective so companies invest in synthetic data as it can quickly generate data about the product and help develop reliable machine learning models.

Some examples of synthetic data in the current world:

Synthetic data is used by Amazon’s ALEXA to train its language system (its answers, questions and responses to your queries.)

Google’s WAYMO uses synthetic data to train self driving cars

Health insurance company ANTHEM works with Google Cloud to generate synthetic data to identify things like fraudulent claims or abnormalities in someone's health records.

written by: ali