From the course: Understanding Generative AI in Cloud Computing: Services and Use Cases

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GenAI case study: System architecture

GenAI case study: System architecture

From the course: Understanding Generative AI in Cloud Computing: Services and Use Cases

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GenAI case study: System architecture

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- [Instructor] Designing a GenAI system architecture begins with understanding the problem and the requirements. A clear goal guides the selection of AI tools, infrastructure, and workflows, ensuring alignment with business needs and efficient resource use. The process starts with data. Gather, clean, and organize the necessary text, audio, or image data. Data pipelines help automate this journey, supporting continued learning and model improvement after the initial launch. Next, select a suitable generative model type, such as a transformer, rRNN, based on your data and objectives. Use cloud platforms, as they offer prebuilt libraries, scalable compute resources, and easier model management. Training and fine tuning comes next. Leverage cloud services to optimize model training using GPUs or TPUs to accelerate computation. Experimentation and version control ensure reproducibility and help find the best performing model. Once trained, deploy your model on the cloud for efficient…

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