Summary
Generative AI models can be used to develop machine learning models, such as Generative Adversarial Networks (GANs) and Transformer-based models.
1
2
These models are capable of creating artifacts from real-world content, such as text-to-image translation, face identification and verification systems, healthcare, marketing, and more.
1
2
To train a generative model, a large amount of data in some domain is collected (e.g. millions of images, sentences, or sounds) and then used to generate data like it.
1
According to
See more results on Neeva
Summaries from the best pages on the web
Summary
Generative AI is a type of machine learning algorithm that uses existing content like text, audio and video files, images, and even code to create new possible content. It is used to create artifacts that look like the real deal, such as text-to-image translation, face identification and verification systems, healthcare, marketing, and more. GANs and Transformer-based models are two of the most widely used generative AI models, and they are modeled to make them capable of creating artifacts from real-world content.
Generative AI Models Explained | AltexSoft
altexsoft.com
First, do your best to avoid biased sources, such as data sources that have a known history of bias or discrimination. This is the hard part. Manually check the training…
Five Ways to Safely Use Generative AI
medium.com
