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Distributed data preprocessing with GKE and Ray: Scaling for the enterprise

The exponential growth of machine learning models brings with it ever-increasing datasets. This data deluge creates a significant bottleneck in the Machine Learning Operations (MLOps) lifecycle, as traditional data preprocessing methods struggle to scale. The preprocessing phase, which is critical for transforming raw data into a format suitable for model training, can become a major …

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Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

Generative AI applications are gaining widespread adoption across various industries, including regulated industries such as financial services and healthcare. As these advanced systems accelerate in playing a critical role in decision-making processes and customer interactions, customers should work towards ensuring the reliability, fairness, and compliance of generative AI applications with industry regulations. To address this …

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Supervised Fine Tuning for Gemini: A best practices guide

Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning (SFT) comes in. When done right, it unlocks incredible precision to tailor Gemini for specialized tasks, domains, and …