Significant advances in generative AI in recent years have made artificial intelligence a top priority for businesses globally. As a result, large language models (LLMs) have become foundational in powering everything from virtual service agents to online search engines to fraud detection.
In entertainment media, LLMs will be foundational in powering rich search and discovery experiences, but they can’t do it alone. Because LLMs are prediction engines, they require complementary technologies to fact check the results they provide. These technologies improve accuracy, provide contextual relevance, enrich results, and align LLM outputs with real-world knowledge.
The Model Context Protocol (MCP) is ideal for ensuring that an LLM’s output is a reliable single source of truth facilitating a dynamic connection between an LLM and Gracenote’s knowledge base. This white paper details how MCP facilitates that connection to ensure that search and discovery experiences are rich and personalized, as well as accurate, recent and complete.
For next-gen entertainment experiences, LLMs are only as good as the data they can access
In order for enterprise LLMs to provide the next-gen content experiences they have the ability to, access to trusted, industry-specific data is paramount.
AI can improve content discovery, but not if people don’t trust it
GenAI has the power to connect people with the content they’re looking for, but trust is a considerable hurdle.
TV search and discovery in the AI era
The way people search for information is changing, but without the right data, AI will simply confirm that it can’t be trusted.