Virtualization Technology News and Information
DataStax Launches Astra DB Vertex Extension for Google Cloud's Vertex AI Platform, Enabling Users to Easily Connect Data Directly from Astra DB to Vertex AI
DataStax announced the launch of a new Google Cloud Vertex AI extension that lets customers using Astra DB - the popular database-as-a-service (DBaaS) built on the open source Apache Cassandra database - easily connect their data directly to Google Cloud's Vertex AI platform.

Vertex AI is a cloud-based machine learning platform developed by Google Cloud that provides an end-to-end workflow for building, training, and deploying machine learning models. With this new connector, any Astra DB user can connect their data to Vertex AI for building with large language models (LLM) and other types of generative AI.

Enterprises building with generative AI require the ability to augment LLMs with their own proprietary data. In doing this, knowledge gaps within an enterprise LLM are filled with relevant data that is useful at the exact moment of a query via processes like retrieval augmented generation, which also helps to reduce AI hallucinations. Through integrations like that of DataStax's Vertex AI extension, AI models can access vectorized data stored in Astra DB and feed it to an LLM, thereby making it smarter, faster, and more relevant.

"At DataStax, we're innovating quickly around AI and we know our customers are, too," said Ed Anuff, chief product officer, Datastax. "One of the biggest concerns we hear is ensuring that proprietary enterprise data is accessible to LLMs, providing the fastest and most relevant responses possible. Integrating with Google Cloud's robust Vertex AI ecosystem via this new extension will help our customers leverage the power of their AI technology and the speed and scalability of Cassandra and Astra DB to fuel their generative AI projects."

Learn more about using the most powerful all-in-one vector database solution to build large LLM, AI assistant, and real-time generative AI projects with massive speed and scale, here.

Published Tuesday, August 29, 2023 8:22 AM by David Marshall
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