AI

Generate synthetic counterparty (CR) risk data with generative AI using Amazon Bedrock LLMs and RAG

Data is the lifeblood of modern applications, driving everything from application testing to machine learning (ML) model training and evaluation. As data demands continue to surge, the emergence of generative AI models presents an innovative solution. These large language models (LLMs), trained on expansive data corpora, possess the remarkable capability to generate new content across […]

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Turbocharging premium audit capabilities with the power of generative AI: Verisk’s journey toward a sophisticated conversational chat platform to enhance customer support

This post is co-written with Sajin Jacob, Jerry Chen, Siddarth Mohanram, Luis Barbier, Kristen Chenowith, and Michelle Stahl from Verisk. Verisk (Nasdaq: VRSK) is a leading data analytics and technology partner for the global insurance industry. Through advanced analytics, software, research, and industry expertise across more than 20 countries, Verisk helps build resilience for individuals,

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Build verifiable explainability into financial services workflows with Automated Reasoning checks for Amazon Bedrock Guardrails

Foundational models (FMs) and generative AI are transforming how financial service institutions (FSIs) operate their core business functions. AWS FSI customers, including NASDAQ, State Bank of India, and Bridgewater, have used FMs to reimagine their business operations and deliver improved outcomes. FMs are probabilistic in nature and produce a range of outcomes. Though these models

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Best practices for Amazon SageMaker HyperPod task governance

At AWS re:Invent 2024, we launched a new innovation in Amazon SageMaker HyperPod on Amazon Elastic Kubernetes Service (Amazon EKS) that enables you to run generative AI development tasks on shared accelerated compute resources efficiently and reduce costs by up to 40%. Administrators can use SageMaker HyperPod task governance to govern allocation of accelerated compute

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