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Understanding Amazon Bedrock model lifecycle

Amazon Bedrock regularly releases new foundation model (FM) versions with better capabilities, accuracy, and safety. Understanding the model lifecycle is essential for effective planning and management of AI applications built on Amazon Bedrock. Before migrating your applications, you can test these models through the Amazon Bedrock console or API to evaluate their performance and compatibility. …

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Guardrails at the gateway: Securing AI inference on GKE with Model Armor

Enterprises are rapidly moving AI workloads from experimentation to production on Google Kubernetes Engine (GKE), using its scalability to serve powerful inference endpoints. However, as these models handle increasingly sensitive data, they introduce unique AI-driven attack vectors — from prompt injection to sensitive data leakage — that traditional firewalls aren’t designed to catch. Prompt injection …

Governance-Aware Agent Telemetry for Closed-Loop Enforcement in Multi-Agent AI Systems

Enterprise multi-agent AI systems produce thousands of inter-agent interactions per hour, yet existing observability tools capture these dependencies without enforcing anything. OpenTelemetry and Langfuse collect telemetry but treat governance as a downstream analytics concern, not a real-time enforcement target. The result is an “observe-but-do-not-act” gap where policy violations are detected only after damage is done. …

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Customize Amazon Nova models with Amazon Bedrock fine-tuning

Today, we’re sharing how Amazon Bedrock makes it straightforward to customize Amazon Nova models for your specific business needs. As customers scale their AI deployments, they need models that reflect proprietary knowledge and workflows — whether that means maintaining a consistent brand voice in customer communications, handling complex industry-specific workflows or accurately classifying intents in …

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New GKE Cloud Storage FUSE Profiles take the guesswork out of configuring AI storage

In the world of AI/ML, data is the fuel that drives training and inference workloads. For Google Kubernetes Engine (GKE) users, Cloud Storage FUSE provides high-performance, scalable access to data stored in Google Cloud Storage. However, we learned from customers that getting the maximum performance out of Cloud Storage FUSE can be complex. Today, we …

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Frontend Engineering at Palantir: Plotlines in Three.js

About this SeriesFrontend engineering at Palantir goes far beyond building standard web apps. Our engineers design interfaces for mission-critical decision-making, build operational applications that translate insight to action, and create systems that handle massive datasets — thinking not just about what the user needs, but what they need when the network is unreliable, the stakes are high, …

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Manage AI costs with Amazon Bedrock Projects

As organizations scale their AI workloads on Amazon Bedrock, understanding what’s driving spending becomes critical. Teams might need to perform chargebacks, investigate cost spikes, and guide optimization decisions, all of which require cost attribution at the workload level. With Amazon Bedrock Projects, you can attribute inference costs to specific workloads and analyze them in AWS …

Claude Mythos Preview: Available in private preview on Vertex AI

Claude Mythos Preview, Anthropic’s newest and most powerful model, is now available in Private Preview to a select group of Google Cloud customers, as part of Project Glasswing.  The availability of Claude Mythos Preview on Vertex AI underscores our commitment to offer our customers access to models from frontier AI labs. Combined with the enterprise-grade …

SQUIRE: Interactive UI Authoring via Slot QUery Intermediate REpresentations

Frontend developers create UI prototypes to evaluate alternatives, which is a time-consuming process of repeated iteration and refinement. Generative AI code assistants enable rapid prototyping simply by prompting through a chat interface rather than writing code. However, while this interaction gives developers flexibility since they can write any prompt they wish, it makes it challenging …

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Frontend Engineering at Palantir: Building a Backend-less Cross-Application API

About this SeriesFrontend engineering at Palantir goes far beyond building standard web apps. Our engineers design interfaces for mission-critical decision-making, build operational applications that translate insight to action, and create systems that handle massive datasets — thinking not just about what the user needs, but what they need when the network is unreliable, the stakes are high, …