Unleash the power of generative AI with Amazon Q Business: How CCoEs can scale cloud governance best practices and drive innovation

Favorite This post is co-written with Steven Craig from Hearst.  To maintain their competitive edge, organizations are constantly seeking ways to accelerate cloud adoption, streamline processes, and drive innovation. However, Cloud Center of Excellence (CCoE) teams often can be perceived as bottlenecks to organizational transformation due to limited resources and

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Shared by AWS Machine Learning November 6, 2024

Use Amazon Q to find answers on Google Drive in an enterprise

Favorite Amazon Q Business is a generative AI-powered assistant designed to enhance enterprise operations. It’s a fully managed service that helps provide accurate answers to users’ questions while adhering to the security and access restrictions of the content. You can tailor Amazon Q Business to your specific business needs by

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Shared by AWS Machine Learning November 1, 2024

Advance environmental sustainability in clinical trials using AWS

Favorite Traditionally, clinical trials not only place a significant burden on patients and participants due to the costs associated with transportation, lodging, meals, and dependent care, but also have an environmental impact. With the advancement of available technologies, decentralized clinical trials have become a widely popular topic of discussion and

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Shared by AWS Machine Learning November 1, 2024

Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

Favorite As enterprises increasingly embrace generative AI , they face challenges in managing the associated costs. With demand for generative AI applications surging across projects and multiple lines of business, accurately allocating and tracking spend becomes more complex. Organizations need to prioritize their generative AI spending based on business impact

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Shared by AWS Machine Learning November 1, 2024

Best practices and lessons for fine-tuning Anthropic’s Claude 3 Haiku on Amazon Bedrock

Favorite Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI, allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications. By fine-tuning, the LLM can adapt its knowledge base to

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Shared by AWS Machine Learning November 1, 2024

Accelerate custom labeling workflows in Amazon SageMaker Ground Truth without using AWS Lambda

Favorite Amazon SageMaker Ground Truth enables the creation of high-quality, large-scale training datasets, essential for fine-tuning across a wide range of applications, including large language models (LLMs) and generative AI. By integrating human annotators with machine learning, SageMaker Ground Truth significantly reduces the cost and time required for data labeling.

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Shared by AWS Machine Learning October 31, 2024

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

Favorite AWS offers powerful generative AI services, including Amazon Bedrock, which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. Many businesses want to integrate these cutting-edge AI capabilities with their existing collaboration

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Shared by AWS Machine Learning October 31, 2024

Create and fine-tune sentence transformers for enhanced classification accuracy

Favorite Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval. In this post, we showcase how to fine-tune a sentence

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Shared by AWS Machine Learning October 30, 2024