Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...

With HeatWave GenAI, developers can create a vector store for enterprise unstructured content with a single SQL command, using built-in embedding models. Users can perform natural language searches in ...

In the age of generative AI (genAI), vector databases are becoming increasingly important. They provide a critical capability for storing and retrieving high-dimensional vector representations, ...

A 'picker' gathers items at Amazon's Fulfilment Centre in Peterborough, central England, on November 28, 2013. 'Cyber Monday' which falls this year on Monday December 2, 2013, is expected to be the ...

Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data to enable grounding of AI prompts and Einstein Copilot, ...

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.

Vector databases are all the rage, judging by the number of startups entering the space and the investors ponying up for a piece of the pie. The proliferation of large language models (LLMs) and the ...

Oracle is expanding its HeatWave cloud database service with a set of new generative AI services, known collectively as HeatWave GenAI. The HeatWave platform was formerly branded as MySQL HeatWave. It ...

HeatWave GenAI is 30X faster than Snowflake, 18X faster than Google BigQuery, and 15X faster than Databricks for vector processing With HeatWave GenAI, developers can create a vector store for ...