In recent years, Google Cloud services have made giant strides to equip data scientists and AI researchers with easy-to-use and accessible tools. Introducing products such as TensorFlow, Google Colab, Cloud AI, Cloud AutoML, and BigQueryML has empowered companies to harness the power of AI and ML capabilities to transform their business. However, frequent barriers underpin the advancement of ML: development and deployment of ML models into production at scale, monitoring and retraining ML models, and constantly toggling between various platforms. The general availability of Vertex AI from Google marks an important milestone in removing these barriers.
In this blog post, we will explore what Vertex AI is, what it does, who should use it, and why.
What is Vertex AI?
Vertex AI is an end-to-end machine learning platform offered by Google Cloud that allows organizations to build, deploy, and manage machine learning models at scale. With Vertex AI, users can access pre-built and custom machine learning models, data processing pipelines, and model training and deployment infrastructure to build intelligent applications that can perform a wide range of tasks, from image and video analysis to natural language processing and predictive analytics.
Vertex AI serves as a PaaS for machine learning developers. The adoption of machine learning operations (MLOps) facilitates the automation of production-grade ML models deployment. Once deployed, MLOps tools that run on fully-managed infrastructure can be leveraged on Vertex AI to automate and scale projects through the ML lifecycle.
Google Cloud Vertex AI provides a wide range of capabilities that enable businesses to build, deploy, and manage machine learning models. These capabilities include:
- AutoML: AutoML is a suite of tools that helps businesses build custom machine learning models without requiring extensive knowledge of machine learning. With AutoML, businesses can use pre-built models to train and deploy their own models.
- Data preparation: Vertex AI provides tools for cleaning, transforming, and preparing data for use in machine learning models. These tools include data labeling, data preprocessing, and data augmentation.
- Model training and deployment: Vertex AI makes it easy to train and deploy custom machine learning models. It provides pre-built APIs and frameworks for popular machine learning tasks such as image recognition, speech recognition, and natural language processing.
- Monitoring and management: Vertex AI provides a unified platform for managing machine learning models and data. It makes it easy to monitor model performance, manage data, and make updates to models.
- Easy sync with GitHub: Workbench can be easily synced with a GitHub repository and support GPU accelerators. It is also protected by Google Cloud authorization.
A key benefit that sets Vertex AI apart from other AI platforms is its ease of operability. It allows its users to collaborate using a common toolset by combining data science, machine learning and data engineering workflow with nearly 80% fewer lines of code, accelerating ML development and experimentation by 5X.
Who Should Use Vertex AI?
Vertex AI is designed for organizations of all sizes that want to incorporate machine learning capabilities into their applications or processes. Whether you're a startup looking to build a recommendation engine or a large enterprise seeking to automate business processes using natural language processing, Vertex AI provides the tools and services necessary to help you achieve your goals.
Vertex AI is also ideal for businesses that do not have extensive knowledge of machine learning. Its AutoML tools make it easy for businesses to build custom models without requiring a deep understanding of the underlying technology.
In particular, Vertex AI is ideal for:
- Data Scientists: Vertex AI provides a user-friendly interface and robust set of tools that allow data scientists to rapidly build and train custom machine learning models.
- Developers: Vertex AI includes a variety of APIs and SDKs that enable developers to integrate machine learning functionality into their applications with minimal effort.
- Business Leaders: Vertex AI provides insights into model performance and enables business leaders to make data-driven decisions that can drive business growth and innovation.
Why Use Vertex AI?
There are several reasons why organizations should consider using Vertex AI to build and deploy their machine learning models:
- End-to-End Solution: Vertex AI provides an end-to-end solution for machine learning model development, training, and deployment, which enables organizations to streamline their workflows and reduce the time and cost required to build and deploy models.
- Scalability: Vertex AI is built on Google Cloud's highly scalable infrastructure, which enables organizations to process large datasets and train and deploy models quickly and efficiently.
- Customizability: Vertex AI provides a suite of tools that enable organizations to create custom machine learning models tailored to their specific needs and use cases.
- Pre-built Models: Vertex AI includes a library of pre-built machine learning models that can be easily integrated into existing applications, enabling organizations to leverage the power of machine learning without requiring extensive data science or machine learning expertise.
- Security: Vertex AI is built on Google Cloud's highly secure infrastructure, which provides enterprise-grade security features such as data encryption, access controls, and threat detection and response.
In short, Vertex AI is a powerful machine learning platform that provides organizations with the tools and services necessary to build, train, and deploy custom machine learning models at scale. With Vertex AI, organizations can accelerate their machine learning workflows, streamline their model development and deployment processes, and leverage the power of machine learning to drive business growth and innovation. Whether you're a data scientist, developer, or business leader, Vertex AI provides the features and functionality necessary to help you achieve your machine learning goals.
Get in touch with our experts to learn more about how you can scale your machine learning operations with Vertex AI.
