Advancements in Generative Artificial Intelligence

Advancements in Generative Artificial Intelligence
The emergence of ChatGPT has generated a new wave of interest in generative AI and its capabilities, leaving many wondering if generative AI is the future of AI technology.

What is generative AI?

Generative AI is any type of artificial intelligence that uses algorithms to produce, manipulate, or synthesize data. Although the AI is using the pre-existing input that it has been fed, this type of AI is technically creating new content based on that input. This differs from previous AI that could simply recognize patterns and make predictions, as generative AI is creating entirely new outputs. Generative AI accomplishes this task through generative adversarial networks (GANs), which consists of a generator and a discriminator. The generator creates the data, while the discriminator evaluates it, effectively generating content that is identical to real data. Generative AI can generate a multitude of content, including images, text, and audio.


ChatGPT

The interest in generative AI increased significantly with the release of ChatGPT. ChatGPT is an AI chatbot that launched in November 2022, and is one of the most successful generative AIs to date. It has received funding from Microsoft, and sparked interest from companies in China who wish to launch a competing AI in the domestic market.
Google was also inspired by the success of ChatGPT, and is beginning to softlaunch incorporating generative AI into Workspace, including Gmail and Google’s productivity tools. As of now, Google plans to bring AI features to its Chat, Meet, Sheets and Slides applications.

ChatGPT is a large language model (LLM), which means that it has been trained using large text datasets in order to perform language-based tasks such as translating, summarizing, and of course generating text. ChatGPT is so revolutionary due to the content it is able to generate. While most chatbots have set question-and-answer responses, ChatGPT is able to generate natural language responses. Users are able to influence the LLM to generate essays, poetry, and other text in a certain tone of voice. It can write basic computer programs and code, and hold realistic conversations with the user.

Advantages and Disadvantages

Introducing generative AI to the world is a huge step forward in technological advancement. It has the potential to make generating new data more time-efficient and cost-effective, improve data-based decision-making processes, and reduce dependence on human-generated data and content. However, all of these things come with drawbacks. The content generated by AIs would still need to be reviewed for quality and relevance and there is a learning curve for understanding how to use this new technology. There have been issues with copyright infringement, as generative AI often uses pre-existing images and artwork to generate content. Generative AI has the potential to be largely beneficial, but at the moment we will continue to rely on human-generated content.






Trinity Richardson

Trinity Richardson is a Junior at the University of South Florida majoring in Communication and Creative Writing, They are an active member of the Judy Genshaft Honors College. Besides being a content writer for WITI, Trinity is a volunteer at Letters Against Depression and an English tutor. You can find them on LinkedIn.

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