GANs : The AI that can create anything almost

GAN stands for Generative Adversarial Network. It’s a type of artificial intelligence (AI) system that uses two neural networks to create new data.

It basically contains two neural networks, a discriminator and a generator.

Let's imagine it like a competition. One network, the generator, tries to create new data, like images or music, that are indistinguishable from real data. The other network, the discriminator, tries to tell the difference between the generated data and the real data.

Here’s a breakdown of how it works roughly:

1. Training data: GANs are trained on a large dataset of existing data, like real pictures, songs and articles.
2. Generator vs. Discriminator: The generator takes random noise as input and tries to create new data that resembles the training data. The discriminator analyzes both the generated data and real data from the training set and tries to identify which is which.
3. Getting better: Through this competition, both networks improve. The generator gets better at creating realistic data, and the discriminator gets better at spotting fakes.

GAN is based on this back-and-forth training process that helps to identify the underlying patterns and features of the real data. Once trained, the generator can create entirely new, but realistic, data.

Here are some of the things GANs can be used for:

• Medical Marvels: Imagine training AI for faster diagnoses using synthetic medical scans created by GANs. Rare diseases often don’t have a large pool of real-life patient data. GAN-generated scans could help bridge this gap and allow us to learn the subtle patterns associated with these diseases.
• Drug Discovery on Fast Forward: GANs can accelerate drug development by designing new drug molecules virtually. GANs can create thousands of simulations of different altercations of drugs and see what affects it might have on patients.
• The Art of Creation: There are now plenty of GAN models that can create new artistic photos or images based on a just a single prompt. From crafting unique artistic styles to restoring old photos, GANs are revolutionizing creative fields.
• Analyzing business scenarios: Identifying the subtle trends in the market and understanding the best strategy to launch a product in the market or to perform competitive analysis simulations of new products, GANs can perform all these tasks with ease.

Overall GANs are a powerful tool with a lot of potential applications, but they’re also a complex technology that’s still under development. Researchers are still working day and night as we speak on improving their stability and finding new ways to use them.