Efficiently train models with large sequence lengths using Amazon SageMaker model parallel

Favorite Large language models (LLMs) have witnessed an unprecedented surge in popularity, with customers increasingly using publicly available models such as Llama, Stable Diffusion, and Mistral. Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters

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Shared by AWS Machine Learning November 28, 2024

Embodied AI Chess with Amazon Bedrock

Favorite Generative AI continues to transform numerous industries and activities, with one such application being the enhancement of chess, a traditional human game, with sophisticated AI and large language models (LLMs). Using the Custom Model Import feature in Amazon Bedrock, you can now create engaging matches between foundation models (FMs)

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Shared by AWS Machine Learning November 28, 2024

Search enterprise data assets using LLMs backed by knowledge graphs

Favorite Enterprises are facing challenges in accessing their data assets scattered across various sources because of increasing complexities in managing vast amount of data. Traditional search methods often fail to provide comprehensive and contextual results, particularly for unstructured data or complex queries. Search solutions in modern big data management must

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Shared by AWS Machine Learning November 28, 2024

Connect SharePoint Online to Amazon Q Business using OAuth 2.0 ROPC flow authentication

Favorite Enterprises face significant challenges accessing and utilizing the vast amounts of information scattered across organization’s various systems. What if you could simply ask a question and get instant, accurate answers from your company’s entire knowledge base, while accounting for an individual user’s data access levels? Amazon Q Business is

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Shared by AWS Machine Learning November 27, 2024

Build a read-through semantic cache with Amazon OpenSearch Serverless and Amazon Bedrock

Favorite In the field of generative AI, latency and cost pose significant challenges. The commonly used large language models (LLMs) often process text sequentially, predicting one token at a time in an autoregressive manner. This approach can introduce delays, resulting in less-than-ideal user experiences. Additionally, the growing demand for AI-powered

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Shared by AWS Machine Learning November 27, 2024