Understanding Transformers: Big Ideas Without Getting Lost in Details

(You can find the Korean version of the post at this link.)

The Transformer architecture stands as a pivotal framework within the realm of artificial intelligence. Amidst a myriad of complex and diverse AI models, the Transformer garners considerable attention for its exceptional performance and versatility. However, like all technologies, comprehending the intricate structure and principles of the Transformer from the outset is not straightforward, nor is it necessary for everyone.

Drawing a parallel to driving can aid in understanding this concept better. A driver doesn’t need to know the ins and outs of a car’s engine or how each component operates to drive safely and efficiently. What’s crucial is grasping the operational aspects of the vehicle, such as how to use the accelerator, brakes, and steering wheel — the functional elements required for driving.

Similarly, in utilizing Transformers, it’s more practical to focus on the functional aspects and applications rather than delving deep into the inner workings and complex mechanisms. This post aims to explore the functional aspects of Transformers, namely their role in AI software and how we can leverage them. It’s advisable to seek a deeper understanding of the Transformer’s intricate structure and mathematical principles through specialized courses or materials (I plan to publish a comprehensive Transformer 101 series in the future).