Category: FAANG

Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets. Use cases such as fraud detection, product recommendations, and traffic prediction are examples where milliseconds matter and are critical for business success. Strict service level agreements (SLAs) need to be met, …

Read more “Model hosting patterns in Amazon SageMaker, Part 1: Common design patterns for building ML applications on Amazon SageMaker”

Amazon Lex is an AWS service for building conversational interfaces into any application using voice and text, enabling businesses to add sophisticated, natural language chatbots across different channels. Amazon Lex uses machine learning (ML) to understand natural language (normal conversational text and speech). In this post, we go through a set of best practices for …

Read more “Best practices for creating Amazon Lex interaction models”

This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office Mojo Movies/TV/OTT licensable data package, which provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million …

Read more “Power recommendations and search using an IMDb knowledge graph – Part 3”

The recently published IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment positions AWS in the Leaders category. This was the first and only APEJ-specific analyst evaluation focused on AI life-cycle software from IDC. The vendors evaluated for this MarketScape offer various software tools needed to support end-to-end machine learning …

Read more “AWS positioned in the Leaders category in the 2022 IDC MarketScape for APEJ AI Life-Cycle Software Tools and Platforms Vendor Assessment”

This post is co-written by Hesham Fahim from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted information organizations for businesses and professionals. It provides companies with the intelligence, technology, and human expertise they need to find trusted answers, enabling them to make better decisions more quickly. TR’s customers span across the …

Read more “How Thomson Reuters delivers personalized content subscription plans at scale using Amazon Personalize”

Powered by Vertex AI (Google Cloud’s platform for accelerating development and deployment of machine learning models into production), SAVI (Semi Automated Vision Inspection)1 is transforming surgical instrument identification and cataloging, leading to fewer canceled surgeries and easing pressure on surgery waitlists.  Max Kelsen, an analytics and software agency that specializes in machine learning, has worked …

Read more “SAVI transforms global surgical instrument tracking with Google Cloud”

Training ML models can be computationally expensive. If you’re training models on large datasets, you might be used to model training taking hours, or days, or even weeks. But it’s not just a large volume of data that can increase training time. Nonoptimal implementations such as an inefficient input pipeline or low GPU usage can …

Read more “How to optimize training performance with the TensorFlow Profiler on Vertex AI”