Language models have been around for a very long time. However, they were much smaller than today and were mainly used to check the fluency of a text, basically

Language models have been around for a very long time. However, they were much smaller than today and were mainly used to check the fluency of a text, basically if a text was a problable text in English or in French for instance. These models were trained over words and had a huge problem with unknown words or spelling errors. They were used in translation models to check the quality of what was produced. In this sense, a language model might seem something ancient. However, if we take your analogy with a car, modern LM are to ancient LM what a plane is to a car. You still travel with it but it is a complete different beast. To say that these models are nothing new is a total travesti of reality. Transformer architectures have been around since 2017, a mere 6 years, but they have revolutionized the way LLM are trained and implemented. If you speak about language models without talking about transformer or attention, you are basically saying that a plane is the same as a car.