AWS Architecture Blog

Tag: machine learning

Let's Architect

Let’s Architect! Architecting with custom chips and accelerators

It’s hard to imagine a world without computer chips. They are at the heart of the devices that we use to work and play every day. Currently, Amazon Web Services (AWS) is offering customers the next generation of computer chip, with lower cost, higher performance, and a reduced carbon footprint. This edition of Let’s Architect! […]

Let's architect! logo

Let’s Architect! Architecting for Machine Learning

Though it seems like something out of a sci-fi movie, machine learning (ML) is part of our day-to-day lives. So often, in fact, that we may not always notice it. For example, social networks and mobile applications use ML to assess user patterns and interactions to deliver a more personalized experience. However, AWS services provide […]

Figure 1. Architecture for batch inference at scale with Amazon SageMaker

Batch Inference at Scale with Amazon SageMaker

Running machine learning (ML) inference on large datasets is a challenge faced by many companies. There are several approaches and architecture patterns to help you tackle this problem. But no single solution may deliver the desired results for efficiency and cost effectiveness. In this blog post, we will outline a few factors that can help […]

Amazon Personalize: from datasets to a recommendation API

Automating Recommendation Engine Training with Amazon Personalize and AWS Glue

Customers from startups to enterprises observe increased revenue when personalizing customer interactions. Still, many companies are not yet leveraging the power of personalization, or, are relying solely on rule-based strategies. Those strategies are effort-intensive to maintain and not effective. Common reasons for not launching machine learning (ML) based personalization projects include: the complexity of aggregating […]

Human/robot head

AWS Architecture Monthly Magazine: Robotics

September’s issue of AWS Architecture Monthly issue is all about robotics. Discover why iRobot, the creator of your favorite (though maybe not your pet’s favorite) little robot vacuum, decided to move its mission-critical platform to the serverless architecture of AWS. Learn how and why you sometimes need to test in a virtual environment instead of […]

Tractor in a field

AWS Architecture Monthly Magazine: Agriculture

In this month’s issue of AWS Architecture Monthly, Worldwide Tech Lead for Agriculture, Karen Hildebrand (who’s also a fourth generation farmer) refers to agriculture as “the connective tissue our world needs to survive.” As our expert for August’s Agriculture issue, she also talks about what role cloud will play in future development efforts in this […]

Machine learning solution developed for customer

Building a Self-Service, Secure, and Continually Compliant Environment on AWS

Introduction If you’re an enterprise organization, especially in a highly regulated sector, you understand the struggle to innovate and drive change while maintaining your security and compliance posture. In particular, your banking customers’ expectations and needs are changing, and there is a broad move away from traditional branch and ATM-based services towards digital engagement. With […]

ML Lens-Well Architected (1)

Introducing the Well-Architected Framework for Machine Learning

We have published a new whitepaper, Machine Learning Lens, to help you design your machine learning (ML) workloads following cloud best practices. This whitepaper gives you an overview of the iterative phases of ML and introduces you to the ML and artificial intelligence (AI) services available on AWS using scenarios and reference architectures. How often […]

Pre-processing pipeline architecture

Building a Scalable Document Pre-Processing Pipeline

In a recent customer engagement, Quantiphi, Inc., a member of the Amazon Web Services Partner Network, built a solution capable of pre-processing tens of millions of PDF documents before sending them for inference by a machine learning (ML) model. While the customer’s use case—and hence the ML model—was very specific to their needs, the pipeline that does […]

Formula 1 logo - 2020

Formula 1: Using Amazon SageMaker to Deliver Real-Time Insights to Fans

The Formula One Group (F1) is responsible for the promotion of the FIA Formula One World Championship, a series of auto racing events in 21 countries where professional drivers race single-seat cars on custom tracks or through city courses in pursuit of the World Championship title. Formula 1 works with AWS to enhance its race […]