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MLOps deployment best practices for real-time inference model serving endpoints with Amazon SageMaker

After you build, train, and evaluate your machine learning (ML) model to ensure it’s solving the intended business problem proposed, you want to deploy that model to enable decision-making in business operations. Models that support business-critical functions are deployed to a production environment where a model release strategy is put in place. Given the nature …

Document AI Workbench is now Generally Available to train document extraction models for your production use cases

Each day, more documents are created and used across companies to make decisions. However, the value in these documents is primarily expressed as unstructured data, which makes the value difficult and manually intensive to extract and use for business processes.  As the number and variety of documents used by businesses proliferate, machine learning (ML) solutions …

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Fine-tune text-to-image Stable Diffusion models with Amazon SageMaker JumpStart

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart. Stable Diffusion is a deep learning model that allows you to generate realistic, high-quality images and stunning art in just a few seconds. Although creating impressive images can find use in industries ranging from …

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FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation

Posted by Parker Riley, Software Engineer, and Jan Botha, Research Scientist, Google Research Many languages spoken worldwide cover numerous regional varieties (sometimes called dialects), such as Brazilian and European Portuguese or Mainland and Taiwan Mandarin Chinese. Although such varieties are often mutually intelligible to their speakers, there are still important differences. For example, the Brazilian …

Serving PyTorch models with prebuilt containers on Vertex AI

Machine learning (ML) practitioners using PyTorch tell us that it can be challenging to advance their ML project beyond experimentation. That’s why over the last year, we’ve prioritized development workthat makes it easier for PyTorch users to deploy models in the cloud using Vertex AI. Vertex AI is a fully-managed machine learning platform with tools, …

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How should AI systems behave, and who should decide?

We’re clarifying how ChatGPT’s behavior is shaped and our plans for improving that behavior, allowing more user customization, and getting more public input into our decision-making in these areas. OpenAI’s mission is to ensure that artificial general intelligence (AGI)[1] benefits all of humanity. We therefore think a lot about the behavior of AI systems we …

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Scaling Large Language Model (LLM) training with Amazon EC2 Trn1 UltraClusters

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. At the server level, such training workloads demand faster compute and increased memory allocation. As models grow to hundreds of billions of parameters, they require a distributed training mechanism that spans multiple nodes (instances). In October 2022, we launched Amazon EC2 …

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8 ways to cut costs and drive profits using data and AI

We are increasingly seeing one question arise in virtually every customer conversation: How can the organization save costs and drive new revenue streams?  Everyone would love a crystal ball, but what you may not realize is that you already have one. It’s in your data. By leveraging Data Cloud and AI solutions, you can put …

UK’s Conservation AI Makes Huge Leap Detecting Threats to Endangered Species Across the Globe

The video above represents one of the first times that a pangolin, one of the world’s most critically endangered species, was detected in real time using artificial intelligence. A U.K.-based nonprofit called Conservation AI made this possible with the help of NVIDIA technology. Such use of AI can help track even the rarest, most reclusive …

Improving Human Annotation Effectiveness for Fact Collection by Identifying the Most Relevant Answers

This paper was accepted at the Workshops on Data Science with Human in the Loop at EMNLP 2022 Identifying and integrating missing facts is a crucial task for knowledge graph completion to ensure robustness towards downstream applications such as question answering. Adding new facts to a knowledge graph in real world system often involves human …