The Transformer is the neural network architecture introduced in Google's 2017 paper "Attention is All You Need" that now powers virtually every modern foundation model. It replaced earlier sequence-processing approaches (RNNs and LSTMs) and underlies GPT, Claude, Gemini, Llama, BERT, T5, and others. Its core innovation is the self-attention mechanism, which allows the model to consider all positions in a sequence simultaneously rather than processing them sequentially. It's the architectural breakthrough that enabled the modern AI revolution; understanding it (at least conceptually) is foundational vocabulary for anyone in tech.
The pre-Transformer era:
RNNs (Recurrent Neural Networks) and LSTMs (Long Short-Term Me...