Google Launches New AI Platform, Makes AI Model Development a Must Have for the Enterprise
by Jim Lundy
Summary: Google announced over 25 new artificial intelligence (AI) offerings, that included an AI platform offering, on-premise AI capabilities, and a full content analytics portfolio.
Event: On April 10th at Google Cloud Next, Google announced its new and updated AI fleet of offerings that make it easier for enterprises to develop and deploy custom AI models.
Last year, Google outlined an ambitious vision of helping every company become a machine learning company. Google continues to deliver on that mission and advance the AI market by supporting AI model development for both structured and unstructured data (which includes content). This will enable enterprises to leverage AI in more innovative ways that will make them more competitive as digital enterprises.
The Google AI Platform
The objective of the Google AI platform is to make it easier for enterprises to leverage AI—in advanced content analytics on documents, images and video, along with enterprise data.
Cloud AutoML Makes AI Models Customizable for Data and Content Analytics
Google introduced Cloud AutoML last year and this year it got a significant update with 5 new offerings:
- New AutoML Tables
- New AutoML Vision—now extended to Edge Computing
- New AutoML Video Intelligence
- AutoML Vision with Object Detection
- AutoML Natural Language—for Entity extraction
Becoming a Complete Intelligent Content Analytics Platform
With these announcements, Google can leverage AI to process documents, images, video, and voice, making it one of the first complete ICA offerings, although they are still distinct services.
In particular, we predict that there will be significant interest on leveraging all of the capabilities, but given the advanced video analytics, many enterprises may want to start to develop pilots to help automate analysis and discovery and content editing (taking ads out of videos).
Google Ignites New Race to AI-Enabled Clouds
Google’s full refresh of its AI capabilities along with AutoML modeling updates will put pressure on the other cloud providers, such as Amazon and AWS, to follow suit. IBM was an early entrant into the automated machine learning model generation space with Watson Discovery, and is now taking a more open approach to offering Watson services on non-blue cloud platforms. The virtuous cycle of opening up AI services to cross-platform development and deployment is good for all users.
- Enterprises should evaluate Google’s AI platform as a strong option to add intelligence to existing applications and also to design new ones.
- Automated machine learning model generation is now a standard capability, though not yet a commodity. Enterprises need to demand this from their providers.
- For enterprises that want to develop an AI offering but are not ready to commit to a specific cloud provider, the combination of Google’s container service along with its on-premise support for AI gives enterprises choice.
- Enterprises should also look carefully at their content to see how Google and other firms’ analytics offerings can be game-changers to get to faster business outcomes.
Google has put the industry on notice that it is committed to relentless AI innovation. That, along with its revamp of the Google Cloud platform, makes it a key vendor to evaluate for cloud migration and re-platforming using AI and the digital transformation platform. Google should also be looked at as innovating in the intelligent content analytics market.