LLMs, NLP, GANs, and generative AI
Just as “AI” is an umbrella term, “generative AI” follows suit. As you might have inferred from its name, generative AI is an area of AI that’s all about generating new content, whether that’s text, an image, or even code. The ML models that power generative AI are creating outputs that closely resemble the training data they learn from.
When you think of generative AI, think primarily of advanced DL models; these can be grouped into three major categories:
- Latent variable models: These models try to decipher hidden factors (latent variables) from the data they are given to train on. From the visible data they receive, they try to understand the determinants that are hidden in that data. Examples of latent variable models include variational autoencoders (VAEs) and energy-based models (EBMs). Examples of tools that are made with these kinds of models include Artbreeder, NSynth (Google Magenta...
