Remove Knowledge Base Remove Machine Learning Remove Metrics Remove Scalability
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Vitech uses Amazon Bedrock to revolutionize information access with AI-powered chatbot

AWS Machine Learning - AI

Retrieval Augmented Generation vs. fine tuning Traditional LLMs don’t have an understanding of Vitech’s processes and flow, making it imperative to augment the power of LLMs with Vitech’s knowledge base. Additionally, Vitech uses Amazon Bedrock runtime metrics to measure latency, performance, and number of tokens. “We

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Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

As successful proof-of-concepts transition into production, organizations are increasingly in need of enterprise scalable solutions. This post explores the new enterprise-grade features for Knowledge Bases on Amazon Bedrock and how they align with the AWS Well-Architected Framework.

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Enhance conversational AI with advanced routing techniques with Amazon Bedrock

AWS Machine Learning - AI

Additionally, you can access device historical data or device metrics. Additionally, you can access device historical data or device metrics. The device metrics are stored in an Athena DB named "iot_ops_glue_db" in a table named "iot_device_metrics". The AI assistant interprets the user’s text input.

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Boost employee productivity with automated meeting summaries using Amazon Transcribe, Amazon SageMaker, and LLMs from Hugging Face

AWS Machine Learning - AI

For a generative AI powered Live Meeting Assistant that creates post call summaries, but also provides live transcripts, translations, and contextual assistance based on your own company knowledge base, see our new LMA solution. Jahed Zaïdi is an AI & Machine Learning specialist at AWS Professional Services in Paris.

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Evaluation of generative AI techniques for clinical report summarization

AWS Machine Learning - AI

Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. We benchmark the results with a metric used for evaluating summarization tasks in the field of natural language processing (NLP) called Recall-Oriented Understudy for Gisting Evaluation (ROUGE). It is time-consuming but, at the same time, critical.

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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning - AI

To create AI assistants that are capable of having discussions grounded in specialized enterprise knowledge, we need to connect these powerful but generic LLMs to internal knowledge bases of documents. To understand these limitations, let’s consider again the example of deciding where to invest based on financial reports.

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Unleashing the power of generative AI: Verisk’s journey to an Instant Insight Engine for enhanced customer support

AWS Machine Learning - AI

Verisk FAST’s AI companion aims to alleviate this burden by not only providing 24/7 support for business processing and configuration questions related to FAST, but also tapping into the immense knowledge base to provide an in-depth, tailored response. However, they understood that this was not a one-and-done effort.