Understanding Generative AI as a Beginner: From the Basics to GANs

Author(s): Sarah Lea

Originally published on Towards AI.

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Ever since the hype surrounding ChatGPT and Co, everyone has been talking about Generative AI. Based on a short prompt, machines generate new content — writing texts, painting pictures or developing program code. Now, for example, the latest marketing product launched by Salesforce — Marketing Cloud Growth — has added further Einstein features based on Gen AI. In addition to the benefits that such tools based on Gen AI bring, it would now be important as a society to discuss how we want such tools to be integrated into our society and to what extent.

In this article, I explain the basic principles of GenAI, the difference between discriminative models and generative models, how GANs and transformer models basically work.

Generative Artificial Intelligence (Gen AI) refers to machine learning models that can generate new content based on data that the models have already seen. Examples include generating text based on a question from a user, creating images based on prompt information or writing code to help with development.

Generative AI has become known to the public since the Transformer architecture has been used in natural language processing (NLP). Generative AI models in… Read the full blog for free on Medium.

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Published via Towards AI