Welcome to above the clouds

AWS – Amazon Braket now supports PennyLane
Amazon Braket now supports PennyLane, an open source software framework for hybrid quantum computing. Pennylane provides interfaces to common machine learning libraries, including PyTorch and TensorFlow, so you can train quantum circuits in the same way you would train a neural network. The integration with Amazon Braket allows you to test and fine-tune algorithms faster […]

AWS – Amazon Braket tensor network simulator supports 50-qubit quantum circuits
Amazon Braket provides a fully managed and high-performance tensor network simulator (TN1). This tensor-network-based circuit simulator can support quantum computing simulations with up to 50 qubits, and is particularly powerful for sparse circuits, circuits with local gates, and other circuits with inherent structure. Read More for the details.

AWS – Amazon ECR announces cross region replication of images
Amazon Elastic Container Registry (Amazon ECR) now supports cross region replication of images in private repositories, enabling developers to easily copy container images across multiple AWS accounts and regions with a single push to a source repository. Storing images in-region to your infrastructure helps applications start up faster as image download time is reduced due […]

GCP – Integrating Dialogflow with Google Chat
In today’s world, where online collaborative work is crucial and maintaining productivity is key, chatbots have an important role to play. Why chatbots? Workers frequently need to incorporate information from external sources in their communications, and chatbots can help them find that information all in one place. In this post we’ll walk you through a […]

GCP – Google Cloud Public Sector Summit Day One in Review
Bright and early this morning, we were thrilled to welcome thousands of attendees from government organizations, education institutions, and nonprofits around the globe to our first-ever digital Google Cloud Public Sector Summit. Thomas Kurian, CEO of Google Cloud, and Mike Daniels, Vice President of Global Public Sector at Google Cloud, opened the Summit with a […]

AWS – Detect bias in ML models and explain model behavior with Amazon SageMaker Clarify
Today we are introducing Amazon SageMaker Clarify to help machine learning developers achieve greater visibility into their training data and models so they can identify and limit bias and explain predictions. Read More for the details.

AWS – Introducing Amazon HealthLake to make sense of health data
Amazon HealthLake is a HIPAA-eligible service that enables healthcare providers, health insurance companies, and pharmaceutical companies to store, transform, query, and analyze health data at petabyte scale. Read More for the details.

AWS – Introducing Amazon SageMaker Data Wrangler – The fastest and easiest way to prepare data for machine learning
Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. With Amazon SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from […]

AWS – Introducing Amazon SageMaker Feature Store – a fully managed repository to store, discover, share and serve machine learning features
We’re excited to announce Amazon SageMaker Feature Store, a new capability of Amazon SageMaker to ingest, store, share, reuse, and serve features for real time and batch machine learning (ML) applications. Read More for the details.
AWS – Introducing Amazon SageMaker Pipelines, first purpose built CI/CD service for machine learning
We’re excited to announce Amazon SageMaker Pipelines, a new capability of Amazon SageMaker to build, manage, automate, and scale end to end machine learning workflows. SageMaker Pipelines brings automation and orchestration to ML workflows, enabling you to accelerate machine learning projects and scale up to thousands of models in production. Read More for the details.