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Overview: Amid the discourse surrounding the controversial role of generative AI in education, Practical AI Strategies goes beyond the hype to explore the opportunities and challenges of the technology in K-tertiary education. The book looks past individual applications to explore the broader landscape of generative AI, offering educators invaluable insights into its workings and ethical considerations. Divided into six parts, Practical AI Strategies guides readers through the construction and ethics of generative AI technologies, navigates policy landscapes and provides practical strategies for using these technologies in education. Detailed sections on text and image generation provide a solid foundation for using generative AI, and prepare educators for multimodal technologies on the near horizon including video, audio and 3D generation. Generative artificial intelligence (GenAI) is a subfield of AI in which ML is applied to large datasets in order to learn ways to generate new data. That data might be in the form of text, code, images, audio or anything else that can be turned into machine-readable content. In practice, that means that GenAI models are multimodal and can both read and create data in a variety of modes, such as text generation, audio (like speech-to-text), and even video and 3D assets. Right now, you can use GitHub Copilot (owned by Microsoft), ChatGPT, Google’s Bard chatbot and a variety of other LLM-based applications to generate – and in some cases execute – code in many languages. Programming languages like Python, HTML, CSS, JavaScript and C++ can all be generated with these models, meaning you can theoretically build applications, plugins, websites and all manner of software even with very low levels of technical understanding.
Genre: Non-Fiction > Tech & Devices
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