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This course on generative AI at Washington University covers various AI models and technologies, including the OpenAI API and others like Amazon Bedrock and Google Cloud. Students will learn through modules focusing on topics such as prompt-based development, text-to-image generation, and fine-tuning language models. The course encourages the use of generative AI in assignments and provides opportunities for hands-on projects, including Kaggle competitions and the development of chatbots, emphasizing multimodal models and their applications in real-world scenarios.
Course modules introduce a structured approach to learning generative AI applications.
Generative AI is directly programmed into the course curriculum.
Retrieval Augmented Generation (RAG) enhances model capabilities with external data.
Text-to-image generation illustrates AI's ability to create visuals from prompts.
The video highlights the importance of responsible AI usage in educational contexts. Integrating generative AI into coursework reflects a broader trend towards experiential learning, fostering students' capability in AI ethics and governance. As AI technologies like OpenAI are leveraged, it is crucial to instill awareness on the implications of deploying such models in real-world applications, ensuring students are prepared to navigate ethical challenges they may face post-education.
The discussions around models such as text-to-image generation exemplify the advancements in generative AI capabilities. As students learn about RAG and prompt engineering, they gain insights into practical data-science workflows that enhance AI performance. Understanding the mechanics behind these technologies is vital for future data scientists, offering them tools to innovate effectively and responsibly in their projects and professional careers.
A class of artificial intelligence that can generate new content.
Generative AI is central to the course, focusing on how to create applications using this technology.
An application programming interface allowing access to OpenAI's models.
The course primarily leverages the OpenAI API for students to build generative AI applications.
A technique combining generation with the retrieval of relevant data to enhance outputs.
The video discusses how RAG can be used to improve the accuracy of AI model responses by accessing databases.
A leading AI research laboratory known for developing advanced language models.
The course focuses on using OpenAI's tools through the OpenAI API for practical applications.
Mentions: 6
A multinational technology company that offers AI services and solutions.
Amazon's Bedrock is mentioned as an alternative to OpenAI for generative AI applications.
Mentions: 3
A suite of cloud computing services that runs on the same infrastructure as Google's end-user products.
Google Cloud products were referenced as part of the competitive landscape alongside OpenAI.
Mentions: 1
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