How Twilio used Amazon SageMaker MLOps pipelines with PrestoDB to enable frequent model retraining and optimized batch transform
This post is co-written with Shamik Ray, Srivyshnav K S, Jagmohan Dhiman […]
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Scalable intelligent document processing using Amazon Bedrock
In today’s data-driven business landscape, the ability to efficiently extract and process […]
Read moreBuild a custom UI for Amazon Q Business
Amazon Q is a new generative artificial intelligence (AI)-powered assistant designed for […]
Read moreUse weather data to improve forecasts with Amazon SageMaker Canvas
Photo by Zbynek Burival on Unsplash Time series forecasting is a specific […]
Read moreReimagining software development with the Amazon Q Developer Agent
Amazon Q Developer is an AI-powered assistant for software development that reimagines […]
Read moreHow Wiz is empowering organizations to remediate security risks faster with Amazon Bedrock
Wiz is a cloud security platform that enables organizations to secure everything […]
Read moreGet started quickly with AWS Trainium and AWS Inferentia using AWS Neuron DLAMI and AWS Neuron DLC
Starting with the AWS Neuron 2.18 release, you can now launch Neuron […]
Read moreSprinklr improves performance by 20% and reduces cost by 25% for machine learning inference on AWS Graviton3
This is a guest post co-written with Ratnesh Jamidar and Vinayak Trivedi […]
Read moreCode generation using Code Llama 70B and Mixtral 8x7B on Amazon SageMaker
In the ever-evolving landscape of machine learning and artificial intelligence (AI), large […]
Read moreBuild RAG applications using Jina Embeddings v2 on Amazon SageMaker JumpStart
Today, we are excited to announce that the Jina Embeddings v2 model, […]
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