#architecture

機械支援の翻訳下書き (Japanese) for "RAG": Retrieval-Augmented Generation - An AI architecture pattern that combines a language model with external knowledge retrieval to provide more accurate and up-to-date responses.

“例文の下書き: We implemented RAG to give our chatbot access to the latest product documentation.”

機械支援の翻訳下書き (Japanese) for "Transformer": A neural network architecture introduced in 2017 ("Attention Is All You Need") that underlies virtually all modern language models. Transformers use self-attention mechanisms to process entire sequences in parallel, capturing long-range dependencies that earlier recurrent architectures struggled with.

“例文の下書き: Every major LLM from GPT to Claude is built on the transformer architecture.”

機械支援の翻訳下書き (Japanese) for "Neural Network": A computational model loosely inspired by biological neurons, consisting of interconnected layers of mathematical functions (nodes) that transform input data into output predictions. Neural networks learn by adjusting the weights of connections through exposure to training data.

“例文の下書き: The neural network learned to recognize handwritten digits with over 99% accuracy.”

機械支援の翻訳下書き (Japanese) for "API-First": A design philosophy where the API contract is defined and agreed upon before any implementation begins. API-first teams treat the API as the product — writing the specification first (e.g., in OpenAPI), getting feedback from consumers, then building both client and server simultaneously against the agreed contract.

“例文の下書き: Their API-first approach meant the mobile app team could start building against the spec before the backend was done.”