Imagine trying to learn about different terms in NLP and connecting the dots between them. It can be overwhelming, but a clever analogy can make all the difference. That’s exactly what I got when I stumbled upon a Reddit post that explained NLP terms using a continent analogy.
According to this analogy, ‘Language’ is a vast continent, and NLP is the science and engineering discipline that studies how to navigate, understand, and build things on that continent. Machine Learning is the primary toolset that NLP engineers use, like advanced surveying equipment and construction machinery. Deep Learning is a specific, powerful type of machine learning tool that has enabled NLP engineers to build much larger and more sophisticated structures.
Large Language Models (LLMs) are the ‘megastructures’ built using Deep Learning on the Language continent. Generative AI, in the context of text, is the function or purpose of some of these structures – they produce new parts of the landscape, or new text. And RAG is a sophisticated architectural design pattern or methodology for connecting these structures to external information sources, making them even more functional and reliable for specific tasks.
This analogy is not only helpful for understanding individual NLP terms but also for seeing how they fit together. It’s a great starting point for exploring the Language continent and discovering new, unheard-of terms. So, what are other NLP terms that fit into this analogy, and how do they contribute to the landscape of language?
Share your thoughts in the comments!