Generating a distilled generative response engine trained on distillation data generated with a language model program
Topics: Information Gain, LLM Readability, LLMO / GEO, OpenAI / ChatGPT, Retrieval Augmented Generation (RAG), Search Query Processing
This patent, filed by OpenAI, describes a system for building a faster, smaller AI model (called a “distilled generative response engine”) that can answer Internet search queries quickly and accurately. A large, complex language model is first guided by a structured set of instructions (a “language model program”) to produce high-quality answers. Those answers are then used as training data to teach a smaller, faster model to produce similarly good answers on its own, without needing all those extra instructions each time.
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