What is “Generative AI,” and How Did it Get So Smart?

Recently, there has been a surge in popularity among generative AI tools like ChatGPT, text-to-image applications, and AI avatars featured on social media. However, the use of AI is more than just a trend. Generative AI tools, like Contentware, are anticipated to have a major impact on the way businesses and creators function, innovate, and thrive.

The First Step in Taking Advantage of this Technology is Understanding How it Works

Generative Artificial Intelligence (AI) is a type of machine learning system that creates new content such as text, images, audio, or other types of media. In comparison, traditional AI systems can perform specific tasks or make decisions based on input data, but can’t create new content on its own.

Generative AI tools must go through a version of “employee training” before they can create original content.  One way of teaching generative AI systems is by giving the tool numerous examples of content.  The software learns from these examples, and creates new outputs similar to what it was shown.  In this case, the new outputs would be original content. 

For example, if one gives a generative AI system photos of animals, the system will output original photos of animals.  These images are realistic, but not exact copies of the photos it was trained with. Behind the scenes, the AI system learns the patterns and features of the training images in order to create accurate output. 

There are several different types of generative AI models, including:

 

    • Autoregressive Models: Using past information to predict future outcomes. (Ex. predicting weather patterns or stock prices)

 

    • Generative Adversarial Networks (GANs): A method of machine learning where two neural networks, a generator and a discriminator, compete with each other. The generator creates new data and the discriminator tries to identify if it is real or fake. The generator learns to create realistic data through this competition. GANs are used to create realistic images, videos, and audio, and for other applications.

 

    • Transformer Models: These are types of AI that help computers understand and generate human language. They are used in tasks like language translation and text generation. They work well with longer text, and can understand the relationships between words and phrases.

Each of these models has its own unique approach to generating output, but they all involve training the AI system in a similar way. 

Why does this matter? 

Generative AI has the potential to revolutionize a wide range of fields, including marketing.  Generative AI enhances marketing efforts by allowing marketers to create more content, personalize messaging, segment customers, make more accurate predictions, and optimize creativity.  It’s important to note that AI is a tool to augment and support human marketing efforts rather than replace them.

Overall, Generative AI is a rapidly evolving field with enormous potential to transform many aspects of our lives. As Contentware and other Generative AI tools continue to develop, we’re excited to see how users benefit from this technology.

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