AWS Generative AI Training 
AWS Machine Learning - AI
MARCH 4, 2025
To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process.
AWS Machine Learning - AI
APRIL 9, 2025
Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. The Basic tier would use a smaller, more lightweight LLM well-suited for straightforward tasks, such as performing simple document searches or generating summaries of uncomplicated legal documents.
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AWS Machine Learning - AI
NOVEMBER 7, 2024
While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle.
AWS Machine Learning - AI
NOVEMBER 15, 2024
With the QnABot on AWS (QnABot), integrated with Microsoft Azure Entra ID access controls, Principal launched an intelligent self-service solution rooted in generative AI. Principal also used the AWS open source repository Lex Web UI to build a frontend chat interface with Principal branding.
AWS Machine Learning - AI
APRIL 10, 2025
Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 During the training of Llama 3.1
AWS Machine Learning - AI
APRIL 29, 2025
Generative AI is rapidly reshaping industries worldwide, empowering businesses to deliver exceptional customer experiences, streamline processes, and push innovation at an unprecedented scale. Specifically, we discuss Data Replys red teaming solution, a comprehensive blueprint to enhance AI safety and responsible AI practices.
AWS Machine Learning - AI
DECEMBER 24, 2024
Training large language models (LLMs) models has become a significant expense for businesses. To reduce costs while continuing to use the power of AI , many companies have shifted to fine tuning LLMs on their domain-specific data using Parameter-Efficient Fine Tuning (PEFT).
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