Google Announces General Availability Of AI Platform Prediction.
                     Google Announces General Availability 
Of AI Platform Prediction
Introduction
• Google launched AI Platform Prediction in general availability, a service 
that lets developers prep, build, run, and share machine learning 
models in the cloud.
Source: The Cloud Report
Google Kubernetes Engine
• It is based on a Google Kubernetes Engine backend and features an 
architecture designed for high reliability, flexibility, and low overhead 
latency.
Source: analyticsindiamag.com/
Machine learning 
• Emerging technologies like machine learning and AI have transformed 
the way most processes and industries work around us. 
• Machine learning has brought various significant features that require 
predictions. 
Source: analyticsindiamag.com/
Issues Considered
• Building a robust and enterprise-ready 
machine learning environment can 
include various issues like it being time-
consuming, costly as well as complex. 
• Google’s AI Platform Prediction takes 
into account all these issues to provide 
a robust environment for ML-based 
tasks.
Source: analyticsindiamag.com/
AI Platform Pipelines
• Previously the tech giant launched the AI Platform Pipelines in beta 
version to ensure in delivering an enterprise-ready and a secure 
execution environment for the machine learning workflows. 
Source: CIO Bulletin
Functioning
• The new platform is designed for various functions in machine learning models 
such as:
– Improved reliability
– More flexibility via new hardware options such as Compute Engine machine 
types and NVIDIA accelerators
– Reduced overhead latency
– Improved tail latency.
Source: Google Cloud
Behind AI Platform Prediction
• AI Platform Prediction is one of the key 
components of the AI Platform. 
• It is a platform to train machine learning 
models, host trained models in the cloud 
and use the ML model to make 
predictions about the new data. 
Source: Google Cloud
Services
• It brings the power and flexibility of 
TensorFlow, Scikit-Learn and XGBoost 
to the cloud. 
• The AI Platform Prediction service 
allows a user to serve predictions 
based on a trained model, whether or 
not the model was trained on the AI 
Platform. 
Source: Google Cloud
XGBoost/Scikit-Learn Models
• AI Platform Prediction includes the power of XGBoost and Scikit-Learn models for 
predictions in production. 
• This makes the platform simple to deploy on models trained using these 
frameworks.
Source: analyticsindiamag.com/
Resource Metrics 
• Resource metrics are now visible for models deployed on GCE machine types from 
Cloud Console and Stack driver Metrics.
• In this platform, the developers have introduced new endpoints in three regions 
(us-central1, Europe-west4, and Asia-east1) with better regional isolation for 
improved reliability. 
Source: analyticsindiamag.com/