AWS Machine Learning Blog

FEBRUARY 12, 2025

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. Responsible AI Implementing responsible AI practices is crucial for maintaining ethical and safe deployment of RAG systems.

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Auto-classification Metadata Generative AI Machine Learning 96

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.

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Large Language Models LLM Deep Learning Data Science 52

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 Scientist Data Quality 134

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 130

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 136

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 117

AWS Machine Learning Blog

DECEMBER 17, 2024

Amazon SageMaker helps data scientists and machine learning (ML) engineers build FMs from scratch, evaluate and customize FMs with advanced techniques, and deploy FMs with fine-grain controls for generative AI use cases that have stringent requirements on accuracy, latency, and cost. Of the six challenges, the LLM met only one.

LLM 101

LLM Prompt Engineering Prompt Engineer Generative AI 101