Favorite The post is co-written with Michael Shaul and Sasha Korman from NetApp. Generative artificial intelligence (AI) applications are commonly built using a technique called Retrieval Augmented Generation (RAG) that provides foundation models (FMs) access to additional data they didn’t have during training. This data is used to enrich the
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Shared by AWS Machine Learning September 18, 2024
Favorite This post is co-written with Pradeep Prabhakaran from Cohere. Retrieval Augmented Generation (RAG) is a powerful technique that can help enterprises develop generative artificial intelligence (AI) apps that integrate real-time data and enable rich, interactive conversations using proprietary data. RAG allows these AI applications to tap into external, reliable
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Shared by AWS Machine Learning September 17, 2024
Favorite The clustered regularly interspaced short palindromic repeat (CRISPR) technology holds the promise to revolutionize gene editing technologies, which is transformative to the way we understand and treat diseases. This technique is based in a natural mechanism found in bacteria that allows a protein coupled to a single guide RNA
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Shared by AWS Machine Learning September 17, 2024
Favorite Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and confidently build, train, and deploy ML models into a production-ready hosted environment. SageMaker provides a broad selection of ML infrastructure and model deployment options to help meet your ML inference
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Shared by AWS Machine Learning September 14, 2024
Favorite Intricate workflows that require dynamic and complex API orchestration can often be complex to manage. In industries like insurance, where unpredictable scenarios are the norm, traditional automation falls short, leading to inefficiencies and missed opportunities. With the power of intelligent agents, you can simplify these challenges. In this post,
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Shared by AWS Machine Learning September 14, 2024
Favorite Managing cloud costs and understanding resource usage can be a daunting task, especially for organizations with complex AWS deployments. AWS Cost and Usage Reports (AWS CUR) provides valuable data insights, but interpreting and querying the raw data can be challenging. In this post, we explore a solution that uses
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Shared by AWS Machine Learning September 14, 2024
Favorite Thomson Reuters, a global content and technology-driven company, has been using artificial intelligence and machine learning (AI/ML) in its professional information products for decades. The introduction of generative AI provides another opportunity for Thomson Reuters to work with customers and advance how they do their work, helping professionals draw
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Shared by AWS Machine Learning September 13, 2024
Favorite As generative AI moves from proofs of concept (POCs) to production, we’re seeing a massive shift in how businesses and consumers interact with data, information—and each other. In what we consider “Act 1” of the generative AI story, we saw previously unimaginable amounts of data and compute create models
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Shared by AWS Machine Learning September 13, 2024
Favorite In this post, we discuss how generative artificial intelligence (AI) can help health insurance plan members get the information they need. Many health insurance plan beneficiaries find it challenging to navigate through the complex member portals provided by their insurance plans. These portals often require multiple clicks, filters, and
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Shared by AWS Machine Learning September 13, 2024
Favorite Llama 3, Meta’s latest large language model (LLM), has taken the artificial intelligence (AI) world by storm with its impressive capabilities. As developers and businesses explore the potential of this powerful model, crafting effective prompts is key to unlocking its full potential. In this post, we dive into the
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Shared by AWS Machine Learning September 13, 2024
Shared by AWS Machine Learning September 18, 2024
