Synthetic data is on the rise in artificial intelligence. It’s going to make AI cheaper, better and less biased.
It’s also very obtainable and usable. In a short while, it has gone from being an experimental technology. To something, I would not hesitate to use for production AI solutions.
To illustrate that, I will build an AI that can classify the difference between apples and bananas. I will only use images of the two classes generated by another AI – In this case, using DALL-E Mini.
An Apple or Banana recognizer
I will build an image classifier using only easy-to-access, free AutoAI tools.
Generating data
We need around 30 images of each label, bananas and apples.
We will be using DALL-E Mini, an open-source version of NVIDIAs text-to-image model DALL-E 2.
To generate the images, you can go to https://huggingface.co/spaces/dalle-mini/dalle-mini. Here you can prompt the text-to-image model with queries such as:
“Banana on table”
“Banana on random background”
“Apple on table”
“Apple on random background”
Try to match the background you will be testing on.