Customizing generative AI for unique value

Since the emergence of enterprise-grade generative AI, organizations have tapped into the rich capabilities of foundational models, developed by the likes of OpenAI, Google DeepMind, Mistral, and others. Over time, however, businesses often found these models limiting since they were trained on vast troves of public data. Enter customization—the practice of adapting large language models (LLMs) to better suit a business’s specific needs by incorporating its own data and expertise, teaching a model new skills or tasks, or optimizing prompts and data retrieval. Customization is not new, but the early tools were fairly rudimentary, and technology and development teams were often unsure how to do it. That’s changing, and the customization methods and tools available today are giving businesses greater opportunities to create unique value from their AI models. ... Read full article.