Mastering Generative AI with OpenAI
What is Generative AI
Section Introduction
Welcome to Mastering Generative AI with OpenAI. This section lays the groundwork for understanding how generative models differ from traditional discriminative approaches. Whether you’re a seasoned developer or new to AI, you’ll gain the essential context needed to follow along with the rest of this course.
Note
This material is designed for software developers with no prior machine learning experience. A basic understanding of programming concepts is sufficient.
What You’ll Learn
- Key milestones in AI evolution
- Core differences between discriminative and generative models
- Practical applications of generative AI
By the end of this section, you will have a clear understanding of:
| Aspect | Discriminative AI | Generative AI |
|---|---|---|
| Primary Goal | Learn decision boundaries | Learn data distribution |
| Techniques | Logistic Regression, CNNs | GANs, VAEs, Large Language Models |
| Outputs | Class labels or predictions | New text, images, or other data |
| Use Cases | Spam detection, image classification | Text generation, image synthesis |
Let’s begin with our first lesson, where we’ll dive into the foundational concepts of generative AI and explore how OpenAI’s platform brings these models to life.
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