Google has announced that it is expanding its open-source support for Vertex AI, its machine learning platform, by adding support for Ray, an open-source unified compute framework. This move is aimed at efficiently scaling AI workloads and enhancing the productivity and operational efficiency of data science teams.
The announcement was made during Google Cloud Next, an annual conference where Google shares updates and advancements in its cloud-based services. "We believe that making AI helpful for everyone is the best way we'll deliver on our mission in the next decade," Google CEO Sundar Pichai said during a keynote.
The addition of Ray to Vertex AI is part of Google's broader strategy to supercharge its AI platform with new features and capabilities. Ray is designed to scale AI and Python workloads, providing managed, enterprise-grade security and increased productivity. With integrations across Vertex AI products like Colab Enterprise, Training, Predictions, and MLOps features, it’s easy to implement Ray on Vertex AI within existing workflows.
Google's decision to add Ray support to Vertex AI is seen as a significant move towards providing more flexibility and choice to data science teams. Vertex AI already supports a range of open-source frameworks such as Tensorflow, PyTorch, scikit-learn, and XGBoost.
The addition of Ray will further enhance the platform's capabilities and make it more appealing to developers and data scientists. "Through Ray on Vertex, it is easier to scale up the training procedure and train machine and reinforcement learning agents to optimize across a variety of warehouse operating conditions," said Matthew Haley, lead AI scientist, and Murat Cubuktepe, senior AI scientist, at materials handling, software, and services firm Dematic.
In addition to Ray support, Google also announced the launch of Colab Enterprise, a managed service that combines the ease-of-use of Google’s Colab notebooks with enterprise-level security and compliance support capabilities. Google also announced Duet AI in BigQuery to provide contextual assistance for writing SQL and Python, connectors for third-party applications like Confluence, Salesforce, and a Grounding feature in Vertex AI is aimed at increasing confidence in a user’s generative AI search and conversational applications.
Developers looking to learn more about Vertex AI can view documentation here. Google has also developed an AI Readiness Quick Check tool (authentication required).