Transformers are a groundbreaking architecture for artificial neural networks, developed by Google in 2017, and now form the foundation for modern AI language models such as ChatGPT, Claude, or Google’s own Gemini.
The name “Transformer” refers to these systems’ ability to transform input data (for example, texts) into another form.
What makes Transformers special is their ability to capture relationships in texts, even when the relevant information is far apart. This is achieved through a mechanism called “attention,” where the system simultaneously considers all words in a text and analyzes their relationships to each other – similar to how a human understands the meaning of all words in context when reading a sentence. Unlike older AI models that had to process texts sequentially word by word, Transformers can work in parallel, making them significantly more efficient.
This architecture enables modern AI systems to understand, translate, summarize, or generate texts themselves.