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

MaMMUT: A simple vision-encoder text-decoder architecture for multimodal tasks

Favorite Posted by AJ Piergiovanni and Anelia Angelova, Research Scientists, Google Research Vision-language foundational models are built on the premise of a single pre-training followed by subsequent adaptation to multiple downstream tasks. Two main and disjoint training scenarios are popular: a CLIP-style contrastive learning and next-token prediction. Contrastive learning trains

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Shared by Google AI Technology 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