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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. By providing an expected outcome to measure against, ground truth data unlocks the ability to deterministically evaluate system quality. Amazons operating margin in 2023 was 6.4%.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

Manually reviewing and processing this information can be a challenging and time-consuming task, with a margin for potential errors. BQA reviews the performance of all education and training institutions, including schools, universities, and vocational institutes, thereby promoting the professional advancement of the nations human capital.

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Solution overview The policy documents reside in Amazon Simple Storage Service (Amazon S3) storage. Verisk has a governance council that reviews generative AI solutions to make sure that they meet Verisks standards of security, compliance, and data use.

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Using responsible AI principles with Amazon Bedrock Batch Inference

AWS Machine Learning - AI

Ethical prompting techniques When setting up your batch inference job, it’s crucial to incorporate ethical guidelines into your prompts. The following is a more comprehensive list of ethical guidelines: Privacy protection – Avoid including any personally identifiable information in the summary. For instructions, see Create a guardrail.

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Revolutionizing clinical trials with the power of voice and AI

AWS Machine Learning - AI

Audio-to-text translation The recorded audio is processed through an advanced speech recognition (ASR) system, which converts the audio into text transcripts. Data integration and reporting The extracted insights and recommendations are integrated into the relevant clinical trial management systems, EHRs, and reporting mechanisms.

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Model customization, RAG, or both: A case study with Amazon Nova

AWS Machine Learning - AI

In this post, we seek to address this growing need by offering clear, actionable guidelines and best practices on when to use each approach, helping you make informed decisions that align with your unique requirements and objectives. On the Review and create page, review the settings and choose Create Knowledge Base.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

The workflow includes the following steps: Documents (owner manuals) are uploaded to an Amazon Simple Storage Service (Amazon S3) bucket. This allows the agent to provide context and general information about car parts and systems. Review and approve these if you’re comfortable with the permissions. State uncertainties clearly.

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