The GenAI life cycle delineates the steps for creating AI-based applications, such as chatbots, virtual assistants or intelligent agents. GenAI (or Generative AI), refers to advanced machine learning systems capable of creating content, such as text, images, and even code, that is often indistinguishable from content produced by humans. Understanding the GenAI life cycle is important for enabling teams to leverage the full potential of a GenAI project.
To help manage GenAI projects, below I first describe the GenAI life cycle, compare it with the CRISP-DM life cycle, which is the most common life cycle used in traditional data science projects, and then discuss key project challenges that introduce uncertainty into GenAI projects.
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