Category: FAANG

In a rapidly changing Consumer Packaged Goods (CPG) industry, business agility and digital innovation are essential to achieve business outcomes. Cost pressures, rising demand, and new consumer expectations have led to whiplash for CPG companies who need to accelerate digital transformation to remain competitive. Google Cloud has a tradition of delivering solutions specifically designed to …

Read more “Accelerating SAP CPG enterprises with Google Cloud Cortex Framework”

It’s no secret that many organizations and job seekers find the hiring process exhausting. It can be time consuming, costly, and somewhat risky for both parties. Those are just some of the experiences we wanted to change when we started Gyfted, a pre-vetted talent marketplace for people who complete tech training or degree programs and …

Read more “Gyfted uses Google Cloud AI/ML tools to match tech workers with the best jobs”

Posted by Srivatsan Krishnan, Student Researcher, and Aleksandra Faust, Senior Staff Research Scientist, Google Research, Brain Team Deep reinforcement learning (RL) continues to make great strides in solving real-world sequential decision-making problems such as balloon navigation, nuclear physics, robotics, and games. Despite its promise, one of its limiting factors is long training times. While the …

Read more “Quantization for Fast and Environmentally Sustainable Reinforcement Learning”

Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. An enterprise search solution should …

Read more “Index your Dropbox content using the Dropbox connector for Amazon Kendra”

The proliferation of machine learning (ML) across a wide range of use cases is becoming prevalent in every industry. However, this outpaces the increase in the number of ML practitioners who have traditionally been responsible for implementing these technical solutions to realize business outcomes. In today’s enterprise, there is a need for machine learning to …

Read more “Provision and manage ML environments with Amazon SageMaker Canvas using AWS CDK and AWS Service Catalog”

Amazon SageMaker Pipelines allows data scientists and machine learning (ML) engineers to automate training workflows, which helps you create a repeatable process to orchestrate model development steps for rapid experimentation and model retraining. You can automate the entire model build workflow, including data preparation, feature engineering, model training, model tuning, and model validation, and catalog …

Read more “New features for Amazon SageMaker Pipelines and the Amazon SageMaker SDK”

Data scientists often train their models locally and look for a proper hosting service to deploy their models. Unfortunately, there’s no one set mechanism or guide to deploying pre-trained models to the cloud. In this post, we look at deploying trained models to Amazon SageMaker hosting to reduce your deployment time. SageMaker is a fully …

Read more “Reduce the time taken to deploy your models to Amazon SageMaker for testing”