AI

How Thomson Reuters Labs achieved AI/ML innovation at pace with AWS MLOps services

This post is co-written by Danilo Tommasina and Andrei Voinov from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted information organizations for businesses and professionals. TR provides companies with the intelligence, technology, and human expertise they need to find trusted answers, enabling them to make better decisions more quickly. TR’s customers […]

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Build a generative AI image description application with Anthropic’s Claude 3.5 Sonnet on Amazon Bedrock and AWS CDK

Generating image descriptions is a common requirement for applications across many industries. One common use case is tagging images with descriptive metadata to improve discoverability within an organization’s content repositories. Ecommerce platforms also use automatically generated image descriptions to provide customers with additional product details. Descriptive image captions also improve accessibility for users with visual

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. From deriving insights to powering generative artificial intelligence (AI)-driven applications, the ability to efficiently process and analyze large datasets is a vital capability. However, managing the complex infrastructure required for big data workloads has traditionally been a

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Best practices for prompt engineering with Meta Llama 3 for Text-to-SQL use cases

With the rapid growth of generative artificial intelligence (AI), many AWS customers are looking to take advantage of publicly available foundation models (FMs) and technologies. This includes Meta Llama 3, Meta’s publicly available large language model (LLM). The partnership between Meta and Amazon signifies collective generative AI innovation, and Meta and Amazon are working together

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Implementing advanced prompt engineering with Amazon Bedrock

Despite the ability of generative artificial intelligence (AI) to mimic human behavior, it often requires detailed instructions to generate high-quality and relevant content. Prompt engineering is the process of crafting these inputs, called prompts, that guide foundation models (FMs) and large language models (LLMs) to produce desired outputs. Prompt templates can also be used as

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Study: Transparency is often lacking in datasets used to train large language models

In order to train more powerful large language models, researchers use vast dataset collections that blend diverse data from thousands of web sources. But as these datasets are combined and recombined into multiple collections, important information about their origins and restrictions on how they can be used are often lost or confounded in the shuffle.

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