ODSC - Open Data Science

JANUARY 10, 2024

In this talk, you’ll explore the need for adopting responsible AI principles when developing and deploying large language models (LLMs) and other generative AI models, and provide a roadmap for thinking about responsible AI for generative AI in practice through real-world LLM use cases.

Large Language Models 52

Large Language Models LLM Deep Learning ML 52

AWS Machine Learning Blog

MAY 9, 2024

Governance Establish governance that enables the organization to scale value delivery from AI/ML initiatives while managing risk, compliance, and security. Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI.

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ML Generative AI AI AI 106

AWS Machine Learning Blog

JANUARY 26, 2024

Being aware of risks fosters transparency and trust in generative AI applications, encourages increased observability, helps to meet compliance requirements, and facilitates informed decision-making by leaders. Learn more about our commitment to Responsible AI and additional responsible AI resources to help our customers.

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Generative AI LLM ML AI 122

AWS Machine Learning Blog

MAY 13, 2024

Amazon Bedrock also comes with a broad set of capabilities required to build generative AI applications with security, privacy, and responsible AI. You can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.

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Generative AI Prompt Engineer Prompt Engineering LLM 105

AWS Machine Learning Blog

NOVEMBER 29, 2023

Since launching in June 2023, the AWS Generative AI Innovation Center team of strategists, data scientists, machine learning (ML) engineers, and solutions architects have worked with hundreds of customers worldwide, and helped them ideate, prioritize, and build bespoke solutions that harness the power of generative AI.

Generative AI 82

Generative AI Prompt Engineer Prompt Engineering ML Engineer 82

The MLOps Blog

JUNE 27, 2023

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. It supports all machine learning use cases and model types by allowing you to completely customize your ML observability experience.

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Machine Learning Metadata Data Quality Data Scientist 134

AWS Machine Learning Blog

NOVEMBER 29, 2023

An evaluation is a task used to measure the quality and responsibility of output of an LLM or generative AI service. Furthermore, evaluating LLMs can also help mitigating security risks, particularly in the context of prompt data tampering.

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LLM Data Scientist Algorithm Generative AI 83