At Google I/O, Google Cloud announced the general availability of Vertex AI, a managed machine learning (ML) platform that allows companies to accelerate the deployment and maintenance of artificial intelligence (AI) models.
Vertex AI requires nearly 80% fewer lines of code to train a model versus competitive platforms, enabling data scientists and ML engineers across all levels of expertise the ability to implement Machine Learning Operations (MLOps) to efficiently build and manage ML projects throughout the entire development lifecycle.
According to the company, Vertex AI brings together the Google Cloud services for building ML under one unified UI and API, to simplify the process of building, training, and deploying machine learning models at scale. In this single environment, customers can move models from experimentation to production faster, more efficiently discover patterns and anomalies, make better predictions and decisions, and generally be more agile in the face of shifting market dynamics.
With Vertex AI, data science and ML engineering teams can access the AI toolkit used internally to power Google that includes computer vision, language, conversation and structured data, continuously enhanced by Google Research.
They can also deploy more useful AI applications, faster with new MLOps features like Vertex Vizier, which increases the rate of experimentation, the fully managed Vertex Feature Store to help practitioners serve, share, and reuse ML features, and Vertex Experiments to accelerate the deployment of models into production with faster model selection.
The Vertex AI platform is now generally available.