The Future of Generative Models

In this book, so far, we have discussed generative models for building applications, and we have implemented a few simple ones – for example, for semantic search, applications for content creation, customer service agents, and assistants for developers and data scientists. We have explored techniques such as tool use, agent strategies, semantic search with retrieval augmented generation, and the conditioning of models with prompts and fine-tuning.

In this chapter, we’ll deliberate on where this leaves us and where the future leads us. We’ll consider weaknesses and socio-technical challenges of generative models, and strategies for mitigation and improvement. We’ll focus on value creation opportunities, where unique customization of foundation models for specific use cases stands out. It remains uncertain which entities – big tech firms, start-ups, or foundation model developers – will capture the most upsides...