Achieve high performance with lowest cost for generative AI inference using AWS Inferentia2 and AWS Trainium on Amazon SageMaker

Favorite The world of artificial intelligence (AI) and machine learning (ML) has been witnessing a paradigm shift with the rise of generative AI models that can create human-like text, images, code, and audio. Compared to classical ML models, generative AI models are significantly bigger and more complex. However, their increasing

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Shared by AWS Machine Learning May 4, 2023

Optimized PyTorch 2.0 inference with AWS Graviton processors

Favorite New generations of CPUs offer a significant performance improvement in machine learning (ML) inference due to specialized built-in instructions. Combined with their flexibility, high speed of development, and low operating cost, these general-purpose processors offer an alternative to other existing hardware solutions. AWS, Arm, Meta and others helped optimize

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Shared by AWS Machine Learning May 3, 2023

Quickly build high-accuracy Generative AI applications on enterprise data using Amazon Kendra, LangChain, and large language models

Favorite Generative AI (GenAI) and large language models (LLMs), such as those available soon via Amazon Bedrock and Amazon Titan are transforming the way developers and enterprises are able to solve traditionally complex challenges related to natural language processing and understanding. Some of the benefits offered by LLMs include the

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Shared by AWS Machine Learning May 3, 2023

Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart

Favorite Today, we announce the availability of sample notebooks that demonstrate question answering tasks using a Retrieval Augmented Generation (RAG)-based approach with large language models (LLMs) in Amazon SageMaker JumpStart. Text generation using RAG with LLMs enables you to generate domain-specific text outputs by supplying specific external data as part

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Shared by AWS Machine Learning May 2, 2023

Bring your own ML model into Amazon SageMaker Canvas and generate accurate predictions

Favorite Machine learning (ML) helps organizations generate revenue, reduce costs, mitigate risk, drive efficiencies, and improve quality by optimizing core business functions across multiple business units such as marketing, manufacturing, operations, sales, finance, and customer service. With AWS ML, organizations can accelerate the value creation from months to days. Amazon

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Shared by AWS Machine Learning May 2, 2023