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Unlocking the Power of Vertex AI: All-in-One ML and AI Platform

The 2023 TechRadar by Devoteam report identifies Vertex AI as a technology that businesses should ‘adopt’. But what is Vertex AI, and why should organisations consider rolling it now?

What is Vertex AI and what is it used for?

Google describes their Vertex AI offering as:

A machine learning (ML) platform that lets you train and deploy ML models and AI applications. Vertex AI combines data engineering, data science, and ML engineering workflows, enabling your teams to collaborate using a common toolset.

Simply put, Vertex AI provides a unified set of APIs for the ML lifecycle. For many businesses, having all of the tools required to build a production-quality AI model in one place will be a powerful proposition.

Vertex AI includes tools and features to support the entire machine-learning workflow:

· Data Preparation

· Model Training

· Model Evaluation 

· Model Deployment

· Model Monitoring

· Model Explainability

Vertex AI also includes tools that can identify holes in your machine learning processes, offering opportunities to constantly improve operations.

What are the ideal use cases for Vertex AI?

As an ‘all in one’ platform, Vertex AI is a good choice for businesses that want to:

  • Productionize their machine learning workflows.
  • Consolidate ML and AI tools into a single platform
  • Develop AI systems which are entirely infrastructure managed 
  • Extend their existing investment in Google Cloud services
  • Use pre-configured APIs to speed up development and deployment
  • Evolve their use of AI over time from pre-configuration to complete customisation

Thanks to its flexibility and the comprehensive nature of the AI / ML tool offerings, Vertex AI is a good choice for most businesses and use cases.

Who uses Vertex AI?

According to a report published by TechCrunch, high-profile Vertex AI customers include Ford, Seagate, Wayfair, Cashapp, Cruise and Lowe’s. These are obviously enterprise-class businesses, but the pay-as-you-use resource billing model makes Vertex AI a potential choice for far smaller organisations too.

What are the top benefits of Vertex AI?

As we have already discussed, Vertex AI is a powerful and flexible choice for machine learning and artificial intelligence operations (MLOps). Here are some of the specific benefits available to users:

1. One platform for all ML and AI tasks

Vertex AI brings all of Google’s machine learning and artificial intelligence tools into a single platform. This means that data engineering, data science, and ML engineering workflows can all be coordinated through a common toolset.

Centralising ML operations on one platform will help to reduce costs and administrative overheads. It will also allow your data science teams to collaborate more closely.

2. Fully managed infrastructure

Machine learning tends to be extremely resource-intensive, requiring significant capital investment in powerful infrastructure. Vertex AI allows you to scale resources in line with demand, charged according to use. In the meantime, Google retains responsibility for ensuring the platform is managed, maintained and optimised, reducing workloads on your own infrastructure team.

3. Faster GTM

Google claims that Vertex AI requires 80% less code than other ML platforms when training models. The platform also offers pre-trained APIs that allow your teams to accelerate development and to focus on delivering value to end users.

4. MLOps ready

As artificial intelligence becomes a cornerstone for strategic computing activity, your internal operating processes will need to evolve to improve the stability and reliability of your ML systems. According to Google, the MLOps tools included with Vertex AI will ‘help you collaborate across AI teams and improve your models through predictive model monitoring, alerting, diagnosis, and actionable explanations’. 

Or, more simply, MLOps will help make your operations more efficient.

5. Open Source support

Many businesses will already have AI models in operation, often built on Open Source frameworks like PyTorch and TensorFlow. Vertex AI supports these, and other Open Source frameworks, making it an ideal target platform for any organisation wanting to move their models to the cloud.

Is Vertex AI free?

No, Vertex AI is not free. As a cloud-based platform, Vertex AI is billed according to the compute resources and services used. Google provides a comprehensive document outlining charges that are determined according to the type and volume of data being analysed, the type of analysis being undertaken along with other factors, such as CPU choice and physical storage type.

Is there anything else I should know about Vertex AI?

Vertex AI is ranked number one on Devoteam’s Top-7 Google Cloud technologies for the Cloud-Native era.

You can also check out our Whitepaper on Machine Learning and MLOps in Google Cloud.

How can I learn more?

This article is part of a larger series centered around the technologies and themes found within the 2023 edition of the  TechRadar by Devoteam . To learn more about Vertex AI and other technologies you need to know about, please download the TechRadar by Devoteam .