Why Transformers Are Becoming As Important As RNN & CNN?

Google AI unveiled a new neural network architecture called Transformer in 2017. The GoogleAI team had claimed the Transformer worked better than leading approaches such as recurrent neural networks and convolutional models on translation benchmarks. In four years, Transformer has become the talk of the town: A big part of the credit goes to its self-attention mechanism, which helps models to focus on only certain parts of the input and reason more effectively. BERT and GPT-3 are some popular Transformers. Now, the looming question is: With Transformer adoption on the rise, could it surpass or become as popular as RNN and CNN?