Google Cloud AI Platform: AI and ML are Now Hyper-Accessible than Ever

CIO Review Europe | Tuesday, August 31, 2021

Google Cloud's AI service offers advanced machine learning capabilities, including pre-trained models and a facility for creating custom models.

FREMONT, CA: For those unfamiliar with Google Cloud, the Google Cloud Platform (GCP) is a collection of cloud-based computing services designed to support a variety of simple use cases, from hosting containerized applications like a social media application to massive-scale data analytics platforms and the application of advanced machine learning and artificial intelligence.

Google Cloud, which was released in April 2008, is built on the same infrastructure that Google employs internally to power its end-user applications, such as Google Search, Gmail, file storage, and YouTube. This global network is an engineering marvel in and of itself, and Google has created an enthralling, interactive showcase for users to explore.

Google Cloud is one of three major cloud providers available today, the others being Microsoft's Azure and Amazon Web Services (AWS).

AI and Google

Google is frequently said to as the world leader in artificial intelligence.

Google's objective is to organize and make accessible all of the world's information. AI enables us to do so in novel and exciting ways, resolving challenges for our users, customers, and the world.

Every day, AI makes it easier for individuals to do tasks, whether searching for images of loved ones, overcoming language barriers with Google Translate, drafting emails on the move, or completing tasks with the Google Assistant. Additionally, AI enables new perspectives on current challenges, from reimagining healthcare to boosting scientific discoveries.

Google Cloud AI Platform

The Google Cloud AI Platform is a collection of services focused on developing, implementing, and administering machine learning models on the cloud.

The hyper-accessible machine learning

AI platform is meant to simplify data scientists and engineers to optimize machine learning workflows and gain access to Google's ground-breaking AI. Users frequently use it in conjunction with AutoML (Google's point-and-click machine learning engine). Still, it also supports the training, prediction, and version control of complex models developed using Tensorflow and SKLearn.

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