Analyst Commentary: Up close with Google cloud AI platform notebooks

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Pages: 8
Publication Date: 3Q 2020
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Google has delivered its Google Cloud AI Platform Notebooks, featuring close ties to other Google Cloud Platform (GCP) services and built-in open-source frameworks. The company is following a broad market trend toward the modernization of data science and machine learning (ML) as a fully integrated enterprise IT service. Omdia takes an in-depth look at the new platform, which gives Google a much needed unifying experience for what is otherwise a highly distributed set of AI development services.

Key Questions Addressed:

  • Does Google’s new JupyterLab-based notebook environment successfully meld DevOps methodologies with open-source data science technologies?
  • Which data science user role is Google targeting with Google Cloud AI Platform Notebooks?
  • How does Google Cloud AI Platform Notebooks tackle JupyterLab-based ML software development requirements?
  • How is Google integrating GitHub into Google Cloud AI Platform Notebooks as a means of versioning data science experiments?
  • Does Google Cloud AI Platform Notebooks provide direct access to Google’s portfolio of AI services beyond hardware accelerators?

Who Needs This Report?

  • Public cloud service providers
  • Private and managed cloud data center solution providers
  • Enterprises building AI and ML solutions
  • MLOps solution vendors and service providers
  • Investor community

Table of Contents

Omdia View
Summary
Background
Key findings
Future developments

 

List of Charts, Figures, and Tables

Figures
  • Basic Google Cloud AI Platform Notebooks interface with imported libraries
  • GPU selection options
  • GitHub integration
  • Google What-If Tool