Vertex AI
Vertex AI provides fully managed machine learning tools to build, deploy, and scale machine learning models.
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October 11, 2023
Vertex AI
Vertex AI provides fully managed machine learning tools to build, deploy, and scale MLmachine learning models.
- AutoML—allows users to train tabular, image, text, or video data without writing code or preparing data splits.
- Custom training—gives users control over the training process, including utilizing their preferred ML framework, writing their own training code, and choosing hyperparameter tuning options.
- Data preparation
On May 2, 2023, Google Cloud and GitLab announced an extension of their partnership, working together to deliver secure AI offerings to businesses. GitLab will leverage Google Cloud's customizable foundation models and open generative AI infrastructure to provide AI-assisted features within its DevSecOps platform. During the partnership, generative AI support will be provided in Vertex AI, allowing GitLab to tune Google's foundation models with their own data to deliver new generative AI-powered experiences.
Vertex AI
Vertex AI provides fully managed machine learning tools to build, deploy, and scale machine learning models.
Vertex AI is a unified machine learning (ML) platform from Google for training and deploying AI and ML models. Vertex AI offers all of Google's cloud services in a single platform, combining data engineering, data science, and ML engineering workflows, enabling teams to collaborate using a common toolset. Vertex AI allows users to build, deploy, and scale ML models using pre-trained and custom tooling. Google's aim with Vertex AI is to build a single platform catering to all developers, an intuitive platform for people new to AI models, and a time-solving solution for experts. Google first released a unified AI platform in preview in November 2020. The platform was renamed Vertex AI on May 18, 2021, at Google I/O, the company's annual developer conference.
What is Vertex AI?
Vertex AI provides multiple options for training ML models:
- AutoML—allows users to train tabular, image, text, or video data without writing code or preparing data splits.
- Custom training—gives users control over the training process, including utilizing their preferred ML framework, writing their own training code, and choosing hyperparameter tuning options.
Post-deployment, Vertex AI provides MLOps tools to automate and scale projects across the ML lifecycle. These tools can be customized depending on performance and budgetary requirements. Vertex AI interfaces include a software development kit for Python that runs ML workflows in Vertex AI Workbench, a Jupyter notebook-based development environment, Google Cloud Console, the gcloud command line tool, client libraries, and Terraform.
Vertex AI can be used across ML workflows:
- Data preparation
- Model training
- Model evaluation and iteration
- Model serving
- Model monitoring
On May 2, 2023, Google Cloud and GitLab announced an extension of their partnership, working together to deliver secure AI offerings to businesses. GitLab will leverage Google Cloud's customizable foundation models and open generative AI infrastructure to provide AI-assisted features within its DevSecOps platform. During the partnership generative AI support will be provided in Vertex AI, allowing GitLab to tune Google's foundation models with their own data to deliver new generative AI-powered experiences.
May 2, 2023
GitLab plans to tune Google's foundation models with their own data to deliver new generative AI-powered experiences.
May 18, 2021
Vertex AI adds support for custom model training, custom model batch prediction, custom model online prediction, and other services.
November 16, 2020
Vertex AI
Vertex AI provides fully managed machine learning tools to build, deploy, and scale ML models.
Vertex AI
Vertex AI provides fully managed machine learning tools to build, deploy, and scale machine learning models.
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