Looking back at the evolution of generative AI

The field of generative AI has experienced an unprecedented acceleration, leading to a surge in the development and adoption of foundation models such as GPT. However, this momentum has been building for several decades, driven by continuous and significant advancements in ML and natural language generation research. These developments have brought us to the current generation of state-of-the-art models.

To fully appreciate the current state of generative AI, it is important to understand its evolution, beginning with traditional language processing techniques and moving through to more recent advancements.

Overview of traditional methods in NLP

Natural language processing (NLP) technology has enabled machines to understand, interpret, and generate human language. It emerged from traditional statistical techniques such as n-grams and hidden Markov models (HMMs), which converted linguistic structures into mathematical models that...