Category: FAANG

This series tackles the rarely simple and often messy solicitation process. We explore how organizations can better evaluate digital transformation software. Welcome to the RFx Blog Series, which explores the question: how should commercial organizations evaluate digital transformation software? In this series, we use language commonly found in formal solicitations, including specific questions and functional …

Read more “Evaluating Software (Palantir RFx Blog Series, #0)”

Machine learning (ML) has improved business across industries in recent years—from the recommendation system on your Prime Video account, to document summarization and efficient search with Alexa’s voice assistance. However, the question remains of how to incorporate this technology into your business. Unlike traditional rule-based methods, ML automatically infers patterns from data so as to …

Read more “Create high-quality data for ML models with Amazon SageMaker Ground Truth”

This post is a joint collaboration with Andries Engelbrecht and James Sun of Snowflake, Inc. The cloud computing revolution has enabled businesses to capture and retain corporate and organizational data without capacity planning or data retention constraints. Now, with diverse and vast reserves of longitudinal data, companies are increasingly able to find novel and impactful …

Read more “Automate your time series forecasting in Snowflake using Amazon Forecast”

Amazon Elastic Compute Cloud (Amazon EC2) G5 instances are the first and only instances in the cloud to feature NVIDIA A10G Tensor Core GPUs, which you can use for a wide range of graphics-intensive and machine learning (ML) use cases. With G5 instances, ML customers get high performance and a cost-efficient infrastructure to train and …

Read more “Achieve four times higher ML inference throughput at three times lower cost per inference with Amazon EC2 G5 instances for NLP and CV PyTorch models”

One of the best ways to share, reuse, and scale your ML workflows is to run them as pipelines. To maximize their value, it’s important to build these pipelines in such a way that you can easily reproduce runs that produce similar results, as described in the paper “Hidden Technical Debt in Machine Learning Systems”.  …

Read more “Building reusable Machine Learning workflows with Pipeline Templates”

AWS Panorama is a collection of machine learning (ML) devices and a software development kit (SDK) that brings computer vision to on-premises internet protocol (IP) cameras. AWS Panorama device options include the AWS Panorama Appliance and the Lenovo ThinkEdge SE70, powered by AWS Panorama. These device options provide you choices in price and performance, depending …

Read more “AWS Panorama now supports NVIDIA JetPack SDK 4.6.2”

Be our guest as we celebrate 20 years of AI/ML innovation on October 25, 2022, 9:00 AM – 10:30 AM PT.  The first 1,500 people to register will receive $50 of AWS credits. Register here. Over the past 20 years, Amazon has delivered many world firsts for artificial intelligence (AI) and machine learning (ML). ML …

Read more “Celebrate over 20 years of AI/ML at Innovation Day”

In this post, we demonstrate how Kubeflow on AWS (an AWS-specific distribution of Kubeflow) used with AWS Deep Learning Containers and Amazon Elastic File System (Amazon EFS) simplifies collaboration and provides flexibility in training deep learning models at scale on both Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon SageMaker utilizing a hybrid architecture approach. …

Read more “Build flexible and scalable distributed training architectures using Kubeflow on AWS and Amazon SageMaker”