Generative AI
July 2025
,◼ Introduction to Generative AI
◼ How Does Generative AI Work
◼ How Generative AI Differs from Traditional AI
◼ The History of Generative AI
◼ Applications of Generative AI
◼ Benefits and Challenges of Generative AI
◼ Language Models
◼ Language Model Basics
◼ Large Language Models
◼ Natural Language Processing
◼ The Evolution of Generative AI
◼ Lab Works: Use Cases Of Generative AI In Investing
◼ Generative AI for Investing?
◼ Use Cases
◼ Knowledge Database
◼ Cognitive Ability
◼ Quantitative Modelling
◼ Sentiment Analysis
◼ Key Benefits
2
,Introduction to Generative AI
◼ How Does Generative AI Work
◼ How Generative AI Differs from Traditional AI
◼ The History of Generative AI
◼ Applications of Generative AI
◼ Benefits and Challenges of Generative AI
◼ Generative AI and Investing
3
, How Does Generative AI Work
◼ Generative AI models are designed to generate new, synthetic data that mimics the
distribution of a training dataset. They can be used to create anything from realistic human
faces to coherent paragraphs of text. By understanding the structure and patterns in the
training data, these models can produce novel outputs that are not direct copies of any
specific data points they were trained on.
◼ ChatGPT (Chat Generative Pre-Trained Transformer) is chatbot created by Open.AI using this
technology and the most well-known implementation that uses Large Language Models
(LLMs) to generate sophisticated content. However, it is not the only model as Google and
other vendors have/are developing their own or partnering with AI firms such as Microsoft is
doing with Open.AI.
◼ The disruptive power of these platforms is that people can interact using human language
and the platform can decipher the request and create detailed content that appears to be
written by humans - Traditionally something only reserved for humans!
4
July 2025
,◼ Introduction to Generative AI
◼ How Does Generative AI Work
◼ How Generative AI Differs from Traditional AI
◼ The History of Generative AI
◼ Applications of Generative AI
◼ Benefits and Challenges of Generative AI
◼ Language Models
◼ Language Model Basics
◼ Large Language Models
◼ Natural Language Processing
◼ The Evolution of Generative AI
◼ Lab Works: Use Cases Of Generative AI In Investing
◼ Generative AI for Investing?
◼ Use Cases
◼ Knowledge Database
◼ Cognitive Ability
◼ Quantitative Modelling
◼ Sentiment Analysis
◼ Key Benefits
2
,Introduction to Generative AI
◼ How Does Generative AI Work
◼ How Generative AI Differs from Traditional AI
◼ The History of Generative AI
◼ Applications of Generative AI
◼ Benefits and Challenges of Generative AI
◼ Generative AI and Investing
3
, How Does Generative AI Work
◼ Generative AI models are designed to generate new, synthetic data that mimics the
distribution of a training dataset. They can be used to create anything from realistic human
faces to coherent paragraphs of text. By understanding the structure and patterns in the
training data, these models can produce novel outputs that are not direct copies of any
specific data points they were trained on.
◼ ChatGPT (Chat Generative Pre-Trained Transformer) is chatbot created by Open.AI using this
technology and the most well-known implementation that uses Large Language Models
(LLMs) to generate sophisticated content. However, it is not the only model as Google and
other vendors have/are developing their own or partnering with AI firms such as Microsoft is
doing with Open.AI.
◼ The disruptive power of these platforms is that people can interact using human language
and the platform can decipher the request and create detailed content that appears to be
written by humans - Traditionally something only reserved for humans!
4
