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NOVEMBER 28, 2023

In 2023, the pace of adoption of AI technologies has accelerated further with the development of powerful foundation models (FMs) and a resulting advancement in generative AI capabilities. To realize the full potential of generative AI, however, it’s important to carefully reflect on any potential risks.

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AWS Machine Learning Blog

JUNE 19, 2024

In this post, we show you how to unlock new levels of efficiency and creativity by bringing the power of generative AI directly into your Slack workspace using Amazon Bedrock. To learn more about how to use generative AI with AWS services, see Generative AI on AWS.

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AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. According to a McKinsey study , across the financial services industry (FSI), generative AI is projected to deliver over $400 billion (5%) of industry revenue in productivity benefits.

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AWS Machine Learning Blog

OCTOBER 15, 2024

Fast Bria AI offers a family of high-quality visual content models. Fast in SageMaker JumpStart and AWS Marketplace, enterprises can now use advanced generative AI capabilities to enhance their visual content creation processes. About the Authors Bar Fingerman is the Head of AI/ML Engineering at Bria.

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ODSC - Open Data Science

JANUARY 10, 2024

The AI Paradigm Shift: Under the Hood of a Large Language Models Valentina Alto | Azure Specialist — Data and Artificial Intelligence | Microsoft Develop an understanding of Generative AI and Large Language Models, including the architecture behind them, their functioning, and how to leverage their unique conversational capabilities.

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AWS Machine Learning Blog

AUGUST 1, 2024

Amazon Bedrock also provides a broad set of capabilities needed to build generative AI applications with security, privacy, and responsible AI practices. However, deploying customized FMs to support generative AI applications in a secure and scalable manner isn’t a trivial task.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The risks associated with generative AI have been well-publicized. Research shows that not only do risks for bias and toxicity transfer from pre-trained foundation models (FM) to task-specific generative AI services, but that tuning an FM for specific tasks, on incremental datasets, introduces new and possibly greater risks.

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AWS Machine Learning Blog

AUGUST 4, 2023

With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code. Einstein Studio’s bring your own model (BYOM) experience provides the capability to connect custom or generative AI models from external platforms such as SageMaker to Data Cloud.

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AWS Machine Learning Blog

OCTOBER 11, 2024

Customers across all industries are experimenting with generative AI to accelerate and improve business outcomes. They contribute to the effectiveness and feasibility of generative AI applications across various domains.

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AWS Machine Learning Blog

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

Use case and model governance plays a crucial role in implementing responsible AI and helps with the reliability, fairness, compliance, and risk management of ML models across use cases in the organization. Anastasia Tzeveleka is a Senior Generative AI/ML Specialist Solutions Architect at AWS.

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AWS Machine Learning Blog

FEBRUARY 12, 2024

The Ranking team at Booking.com learned that migrating to the cloud and SageMaker has proved beneficial, and that adapting machine learning operations (MLOps) practices allows their ML engineers and scientists to focus on their craft and increase development velocity. Daniel Zagyva is a Data Scientist at AWS Professional Services.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

However, harnessing this potential while ensuring the responsible and effective use of these models hinges on the critical process of LLM evaluation. An evaluation is a task used to measure the quality and responsibility of output of an LLM or generative AI service.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

As generative AI moves from proofs of concept (POCs) to production, we’re seeing a massive shift in how businesses and consumers interact with data, information—and each other. While these layers provide different points of entry, the fundamental truth is that every generative AI journey starts at the foundational bottom layer.

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AWS Machine Learning Blog

NOVEMBER 18, 2024

Generative AI is transforming the way healthcare organizations interact with their data. MSD collaborated with AWS Generative Innovation Center (GenAIIC) to implement a powerful text-to-SQL generative AI solution that streamlines data extraction from complex healthcare databases.

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