Generative artificial intelligence (GAI) seems to have taken the world by storm. Relying on models that can create new content in the form of text, media, code, and the like, generative AI is used in a variety of globally popular tools such as ChatGPT, Elicit, or Bard. Its unique appeal is linked to its ability to learn the paradigms of its input and use it to generate new information with similar characteristics.
This guide is intended to help students, faculty, and staff at Georgetown University to navigate the quickly evolving terrain of generative AI. It provides an overview of popular AI research tools, offers guidance on crafting prompts in these tools, and points out key library databases and e-books on AI. It also supplies resources related to core AI ethical issues while laying out basic citation rules.
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Rose, D. (2023, September 25). Generative AI vs. Traditional AI: Explore generative AI vs. traditional AI. [Video] LinkedIn Learning.
In this LinkedIn Learning course, Doug Rose looks at the differences between traditional and generative AI. Traditional concepts like supervised and unsupervised deep learning networks have inspired newer generative AI concepts like self-supervised learning, foundation models, diffusion models, and generative adversarial networks. To understand where a technology is heading, it's important to know its story. These generative AI tools are a big leap, but they’re still just another chapter in the exciting story of artificial intelligence. (60m) GU LinkedIn Account required to view.
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