Author: AI Generated Robotic Content

Deploying large language models (LLMs) at scale on Amazon SageMaker AI Inference makes observability a critical pillar of any production machine learning (ML) strategy. Unlike conventional software that returns deterministic outputs, LLMs generate variable, free-form responses that are difficult to validate with standard metrics. LLM output quality can change over time as input distributions shift, …

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Welcome to the second Cloud CISO Perspectives for May 2026. Today, Usman Chaudhary, Field CISO, Google Public Sector, offers a guide for CISOs protecting government agencies and critical infrastructure on how to get started — and get the most out of — defending with AI. As with all Cloud CISO Perspectives, the contents of this …

Read more “Cloud CISO Perspectives: How to build an AI-ready security program for the public sector”

This solution builds on open source tools including PyTorch, Hugging Face Transformers, and Liger Kernels. The authors would also like to thank Aiham Taleb, Arefeh Ghahvechi, Manav Choudhary, Rohit Thekkanal, Daz Akbarov, Jamila Jamilova, Ross Povelikin, Almas Moldakanov, Christelle Xu, and Ivan Khvostishkov for their contributions in making this project possible. Azercell Telecom LLC, Azerbaijan’s …

Read more “Training Azerbaijani language models on Amazon SageMaker AI”

Since its inception over 20 years ago, Google has used Site Reliability Engineering (SRE) to keep services like Search, Gmail, Maps, YouTube and Google Cloud reliable and highly available, adhering to the principles and practices of the reliability-first mindset. Recently though, the emergence of AI has driven multiple step-changes in system complexity. Interactions between components …

Read more “AI in SRE: Where and how Google is deploying agentic AI to improve operations”