The architecture of Artificial Intelligence (AI) has been evolving rapidly, with the rise of Generative AI marking a significant shift from traditional Machine Learning (ML) approaches. This article explores the key differences between these two architectures and the evolving tech stack that supports them.
Traditional ML vs. Generative AI
Traditional ML involves a series of steps including data pre-processing, feature engineering, training & tuning, and deployment & monitoring. The primary focus is on extracting meaningful features from the data, training models to learn from these features, and tuning these models for optimal performance.
Generative AI, on the other hand, involves data pre-processing, prompt engineering/fine-tuning, foundational/fine-tuned language le
The Evolution of AI Architecture: From Traditional Machine Learning to Generative AI
- By 理想
- Published on
The evolution from traditional Machine Learning to Generative AI represents a significant shift in AI architecture, accompanied by changes in tech stack and a growing emphasis on AI governance and dialog interfaces.
