Can synthetic data help train your AI model?

The saying « data is the new oil, » was reportedly coined by British mathematician and marketing whiz Clive Humby in 2006. Humby’s remark rings true more now than ever with the rise of deep learning.

Data is the fuel powering modern AI models; without enough of it the performance of these systems will sputter and fail. And like oil, the resource is scarce and controlled by big businesses. What do you do if you’re a small computer vision company? You can turn to fake data to train your models, and if you’re lucky it might just work.

The market for synthetic data generation grew to over $110 million in 2021 and is expected to increase to $1.15 billion by the end of 2027, according to a report published by research firm Cognilytica.

Numerous startups have built tools to spin up synthetic images to help companies train their machine learning algorithms.

The startup, founded in 2018 and based in Israel, has built a software platform that allows customers to easily create mock images at the click of a button. Synthetic data provides a way to scale up datasets and automatically annotate each picture with the necessary metadata without much human labor.

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