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How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning Blog

Question and answering (Q&A) using documents is a commonly used application in various use cases like customer support chatbots, legal research assistants, and healthcare advisors. In this collaboration, the AWS GenAIIC team created a RAG-based solution for Deltek to enable Q&A on single and multiple government solicitation documents.

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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning Blog

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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DXC transforms data exploration for their oil and gas customers with LLM-powered tools

AWS Machine Learning Blog

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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Complete Guide on Gemma 2: Google’s New Open Large Language Model

Unite.AI

Google Open Source LLM Gemma In this comprehensive guide, we'll explore Gemma 2 in depth, examining its architecture, key features, and practical applications. ") print(response["result"]) This RAG system uses Gemma 2 through Ollama for the language model, and Nomic embeddings for document retrieval.

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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

Flipboard

Retrieval Augmented Generation (RAG) has become a crucial technique for improving the accuracy and relevance of AI-generated responses. The effectiveness of RAG heavily depends on the quality of context provided to the large language model (LLM), which is typically retrieved from vector stores based on user queries.

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Foundational data protection for enterprise LLM acceleration with Protopia AI

AWS Machine Learning Blog

New and powerful large language models (LLMs) are changing businesses rapidly, improving efficiency and effectiveness for a variety of enterprise use cases. Speed is of the essence, and adoption of LLM technologies can make or break a business’s competitive advantage.

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LLMOps: The Next Frontier for Machine Learning Operations

Unite.AI

But more than MLOps is needed for a new type of ML model called Large Language Models (LLMs). LLMs are deep neural networks that can generate natural language texts for various purposes, such as answering questions, summarizing documents, or writing code.