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Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

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Ethically Leveraging AI – Forbes Business Council Insights

Real Blue Sky

.” Bryant’s contribution focused on the importance of establishing good governance. Ethically Leveraging AI Requires Governance Effective and ethical use of AI hinges on robust governance structures which integrate interdisciplinary expertise to navigate complex ethical considerations.

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Establishing an AI/ML center of excellence

AWS Machine Learning

Organizations across industries face numerous challenges implementing generative AI across their organization, such as lack of clear business case, scaling beyond proof of concept, lack of governance, and availability of the right talent. What is an AI/ML CoE?

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Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

These generated scripts are tailored to meet your organization’s unique requirements while conforming to industry standards for security and compliance. These scripts serve as a foundational starting point, requiring further refinement and validation to make sure they meet production-level standards.

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Charting the Future of Trust & Safety at TrustCon 2024

24-7 InTouch

Setting Standards: Establishing unified industry standards guides AI governance, promoting transparency, accountability, and ethical deployment across sectors. Bias Mitigation: Alignment between trust and safety protocols and AI development prevents biases in AI models, promoting fairness and inclusivity.

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Top Benefits of ID Document Verification for Financial Services

CSM Magazine

Validating identification documents is an everyday part of the financial services industry. It comes into play when performing different financial services like opening bank accounts and approving loans. It’s crucial for ensuring encrypted transactions and preventing fraudulent behaviors.

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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. All these capabilities are built to help multiple lines of business innovate with speed and agility while governing at scale with central controls.