Author: AI Generated Robotic Content

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”