Decoder-only models, like GPT, are a type of neural network that generate text by predicting the next word based solely on previous words. They are designed for tasks such as writing, summarizing, and conversation without requiring separate encoding of inputs.
These models process input sequentially, attending only to prior tokens to generate the next token step-by-step. They use self-attention to weigh context and learn patterns from large datasets, enabling coherent and contextually relevant text generation.
For AI product managers, decoder-only models offer scalable, flexible solutions for natural language generation. They reduce latency by generating outputs in a single pass and simplify deployment versus more complex architectures. This enables enhancement of user experience in chatbots, content creation, and automation while managing compute costs and maintaining high-quality results.