Generative AI with Azure Cosmos DB

Video script:

– An appropriate database plays a critical role in the speed and scale of data retrieval to efficiently return more accurate responses based on large-scale language models. Let’s analyze the characteristics of Azure Cosmos DB and why it is suitable for generative AI workloads.

– Did you know that ChatGPT, a service with hundreds of millions of users worldwide, automatically indexes and stores user conversation history using Azure Cosmos DB?

– The important thing is that you can work with any data that supports multiple data models, such as a document model representing conversational data, as in the case of ChatGPT. And as your data volumes grow, Azure Cosmos DB automatically horizontally scales physical partitions of dedicated compute and storage as needed.

– This unlimited automatic scaling is ideal for real-time data processing. For example, in November 2023, when OpenAI announced several new capabilities, transactions skyrocketed from 4.7 billion to 10.6 billion overnight. And Azure Cosmos DB automatically scaled to meet this exponential demand, making it ideal for real-time transaction workloads.

– And it’s fast with low latency, single-digit millisecond response times. You can also choose to globally distribute your data across multiple regions around the world, so requests are routed to the region closest to your users and operations. Then, to efficiently search natural language queries, vCore-based Azure Cosmos DB for MongoDB provides vector indexing and vector search built into the database.

– Vectors are computed when data is ingested into Azure Cosmos DB. This is similar to coordinates referencing chunks of data in the database that are later used for similarity lookups. For generative AI, when a user submits a prompt, it is also converted into a vector embedding, and the lookup finds the closest match to the prompt vector in the database, making the response more efficient and accurate.

– Grounding large-scale language models with vector index data in Azure Cosmos DB is easy. In an environment like Azure OpenAI Studio, simply select Azure Cosmos DB as your data source. This gives you API-level access to GPT models in the Azure OpenAI service. And with Azure AI Studio, you have access to a vast gallery of open-source models, tools, and frameworks.

– In fact, as part of a secure AI architecture, Azure Cosmos DB is recommended for building enterprise generative AI apps to store and persist chat session history. For these and other reasons, Azure Cosmos DB is uniquely suited for generative AI apps and workloads.