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Tag: SageMaker

Build trust and safety for generative AI applications with Amazon Comprehend and LangChain | Amazon Web Services

We are witnessing a rapid increase in the adoption of large language models (LLM) that power generative AI applications across industries. LLMs are capable...

Use machine learning without writing a single line of code with Amazon SageMaker Canvas | Amazon Web Services

In the recent past, using machine learning (ML) to make predictions, especially for data in the form of text and images, required extensive ML...

Simplifying data processing at Capitec with Amazon Redshift integration for Apache Spark | Amazon Web Services

This post is co-written with Preshen Goobiah and Johan Olivier from Capitec. Apache Spark is a widely-used open source distributed processing system renowned for...

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD | Amazon Web Services

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is...

Customizing coding companions for organizations | Amazon Web Services

Generative AI models for coding companions are mostly trained on publicly available source code and natural language text. While the large size of...

Real-time streaming data top picks you cannot miss at AWS re:Invent 2023 | Amazon Web Services

Save the date: AWS re:Invent 2023 is happening from November 27 to December 1 in Las Vegas, and you cannot miss it. re:Invent is...

Build a medical imaging AI inference pipeline with MONAI Deploy on AWS | Amazon Web Services

This post is cowritten with Ming (Melvin) Qin, David Bericat and Brad Genereaux from NVIDIA. Medical imaging AI researchers and developers need a scalable,...

Optimize for sustainability with Amazon CodeWhisperer | Amazon Web Services

This post explores how Amazon CodeWhisperer can help with code optimization for sustainability through increased resource efficiency. Computationally resource-efficient coding is one technique that...

Connect your data for faster decisions with AWS | Amazon Web Services

The most impactful data-driven insights come from connecting the dots between all your data sources—across departments, services, on-premises tools, and third-party applications. But typically,...

Introducing Amazon MWAA support for Apache Airflow version 2.7.2 and deferrable operators | Amazon Web Services

Amazon Managed Workflow for Apache Airflow (Amazon MWAA) is a managed service that allows you to use a familiar Apache Airflow environment with improved...

Deploy ML models built in Amazon SageMaker Canvas to Amazon SageMaker real-time endpoints | Amazon Web Services

Amazon SageMaker Canvas now supports deploying machine learning (ML) models to real-time inferencing endpoints, allowing you take your ML models to production and drive...

Dialogue-guided visual language processing with Amazon SageMaker JumpStart | Amazon Web Services

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing....

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