Generative AI vs Traditional AI

Summary: The video discusses the evolution from traditional AI to Generative AI (GenAI), highlighting the fundamental architectural changes and the role of large language models (LLMs) in processing vast amounts of data from the internet. It emphasizes the importance of fine-tuning and prompting to tailor AI applications for specific business use cases.

Keypoints:

• GenAI differs from traditional AI in its architecture and data sources.
• Traditional AI relied on a repository, analytics platform, and application layer.
• GenAI utilizes massive amounts of internet data, expanding beyond organizational data.
• Large Language Models (LLMs) are central to processing this data but often require specifics.
• Prompting and tuning are essential for fine-tuning models to specific use cases.
• The application layer consumes AI outputs to achieve business objectives.
• A feedback loop exists that influences the prompting and tuning process.
• The shift in focus on the size and quantity of data necessitates new architectural approaches.