How to Train Generative AI Using Your Company’s Data.

The article focuses on how companies can train generative AI models using their proprietary data to enhance knowledge management, innovation, and performance. It outlines three main approaches: training a large language model (LLM) from scratch, fine-tuning an existing LLM with domain-specific content, and prompt-tuning an existing LLM using curated documents and vector embeddings. Examples include Bloomberg's BloombergGPT, Google's Med-PaLM2, and Morgan Stanley's prompt-tuned GPT-4 system. The article also discusses the importance of content curation, quality assurance, legal and governance considerations, and shaping user behavior to ensure effective and responsible use of generative AI in organizational contexts.