Was ist Transformer Architecture

Definition

Transformer architecture is a neural network design that leverages the self-attention mechanism. This allows it to efficiently process relationships between words or data points, irrespective of their position within a given sequence or text.

Explanation

Introduced in 2017, the Transformer architecture fundamentally revolutionized generative artificial intelligence. Unlike older, sequential models such as Recurrent Neural Networks (RNNs), Transformers can process entire sentences in parallel. This capability dramatically accelerates their training on powerful Graphics Processing Units (GPUs). It serves as the technological cornerstone for nearly all modern Large Language Models (LLMs), including prominent examples like GPT and Claude. For B2B and SaaS providers, this architecture translates into AI systems that can accurately grasp and process the context of lengthy documents, such as contracts, email threads, or support tickets. This capability unlocks a new level of intelligent automation across sales and customer relationship management.