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• IT & AI· Artificial Intelligence· 6 jam yang lalubelum diringkas

  Day 0 support for Reflection’s Beam on Google Cloud: 5x faster perf with llm-d and NVIDIA Dynamo

  Today, Reflection released Beam , its first open-weight model built to give developers, researchers, and enterprises open control and customization for frontier software engineering and long-horizon agentic tasks. Released under a permissive Apache 2.0 license with BF16 , FP8 , and NVFP4 checkpoints

  Google Cloud Blog

• IT & AI· Artificial Intelligence· 31 jam yang lalubelum diringkas

  Modernizing perimeter security: Scalable perimeters with VPC Service Controls

  Agents represent a fundamental shift in cloud operations. They can act on behalf of users or autonomously, make non-deterministic decisions, and request data across projects at unprecedented speed and scale. Because agents are a distinct category of non-human identity (NHI), they require unique secu

  Google Cloud Blog

• IT & AI· Artificial Intelligence· 11 jam yang lalubelum diringkas

  Mini book: Evolutionary Architecture in Practice

  Discover how to keep software evolvable as systems, technology, and teams shift. This edition explores agentic fitness functions for semantic drift, treating human comprehension as a core design metric, cross-cloud guardrails for regional autonomy, and aligning technical boundaries with Conway’s Law

  InfoQ

• IT & AI· Artificial Intelligence· 14 jam yang lalubelum diringkas

  Chainguard Launches Secure Workspaces and Checks for AI Coding Agents

  Software supply chain security company Chainguard has announced two beta products for running and testing code written by developers and AI agents. Chainguard Workspaces provides remote development environments based on hardened microVMs, while Chainguard Checks moves continuous integration into the

  InfoQ

• IT & AI· Artificial Intelligence· 7 jam yang lalubelum diringkas

  Four evaluation engineering lessons learned from building agent plugins

  The real challenge of building an agentic system isn't the construction, it's the measurement. Evaluation engineering is a critical foundation for building reliable AI systems. Setting up systematic, repeatable tests to measure your agent’s true behavior can be the difference between shipping a tool

  Google Cloud Blog