Learning Outcomes

By the end of this tutorial, learners will be able to define Generative AI, identify key examples of its use and recognize its basic applications and limitations.

​What is Generative AI?

Generative AI is a type of artificial intelligence that can create new and original content, like text, images, music, and code. Unlike other AI that only analyzes or categorizes data, Generative AI *produces* something new.

​Examples of Generative AI Tools

You've likely seen Generative AI in action. Tools like ChatGPT for text, Midjourney for images and GitHub Copilot for code are all popular examples of this technology.

​AI Models that Power Generative AI

The models behind these tools are often called Large Language Models (LLMs) or Foundation Models. They are trained on vast amounts of data from the internet, books and other sources to learn patterns, grammar, and concepts.

​Limitations or Concerns Associated with Generative AI

While powerful, Generative AI has limitations. It can sometimes produce incorrect or biased information (called 'hallucinations') and there are ethical concerns about its use for creating deepfakes or spreading misinformation.

Congratulations!

You've completed the tutorial and the creative challenge.

References

Laskar, P. (2024). Generative AI as a foundational model [LinkedIn post]. LinkedIn. https://www.linkedin.com/pulse/generative-ai-foundational-
model-pinaki-laskar/
LTS Group. (2024). Generative AI: Applications, limitations, risks and future outlook. LTS Group. https://ltsgroup.tech/blog/generative-ai/

Nguyen, T. (2024). What is generative AI? An in-depth look at machine creativity. Neurond. https://www.neurond.com/blog/generative-ai

Pushkar, A. (2025). Top 10 generative AI tools to use in 2025. Intellipaat. https://intellipaat.com/blog/generative-ai-tools/

Vijay, K. (2024). What are the limitations of generative AI? The AI Ops. https://www.theaiops.com/what-are-the-limitations-of-generative-ai/