SpecMD: A Comprehensive Study on Speculative Expert Prefetching

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Mixture-of-Experts (MoE) models enable sparse expert activation, meaning that only a subset of the model’s parameters is used during each inference. However, to translate this sparsity into practical performance, an expert caching mechanism is required. Previous works have proposed hardware-centric caching policies, but how these various caching policies interact with each other and different hardware …

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Cost effective deployment of vision-language models for pet behavior detection on AWS Inferentia2

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Tomofun, the Taiwan-headquartered pet-tech startup behind the Furbo Pet Camera, is redefining how pet owners interact with their pets remotely. Furbo combines smart cameras with AI to detect behaviors such as barking, running, or unusual activity, and alerts owners in real time. At the core of this capability are computer vision and vision-language models that …

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Pioneering AI-assisted code migration: How Google achieved 6x faster migration from TensorFlow to JAX

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AI coding agents are rapidly becoming ubiquitous across the software industry, fundamentally changing how developers write, test, and debug daily code. While these tools excel at localized, self-contained tasks, applying them to massive, systemic codebase migrations requires an entirely new approach. Google is already addressing this challenge by incorporating AI into many migration workflows: x86 …

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AI training method helps robots carry lab-learned skills into real-world tasks

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Robots are trained for specific tasks, such as cutting, using simulation. However, collecting real-world data is expensive, slow, and sometimes unsafe, particularly for tasks involving physical interaction. A new AI-based method co-developed by Aston University’s Dr. Alireza Rastegarpanah could revolutionize the way advanced robotic systems are trained for real-life tasks, making them more practical and …

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Stochastic KV Routing: Enabling Adaptive Depth-Wise Cache Sharing

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Serving transformer language models with high throughput requires caching Key-Values (KVs) to avoid redundant computation during autoregressive generation. The memory footprint of KV caching is significant and heavily impacts serving costs. This work proposes to lessen these memory requirements. While recent work has largely addressed KV cache reduction via compression and eviction along the temporal …

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How Hapag-Lloyd uses Amazon Bedrock to transform customer feedback into actionable insights

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Hapag-Lloyd stands as one of the world’s leading liner shipping companies, operating a modern fleet of 313 container ships with a total transport capacity of 2.5 million TEU (Twenty-foot Equivalent Unit—a standard unit of measurement for cargo capacity in container shipping). The company maintains a container capacity of 3.7 million TEU, which includes one of …

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Five must-have guides to move agents into production with Gemini Enterprise Agent Platform

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Building AI agents that work well in a demo is one thing, but running them in production requires serious infrastructure.  At Google Cloud Next ’26, we introduced Gemini Enterprise Agent Platform to help developers build, deploy, scale, govern, and optimize  autonomous AI agents. From managing long-running state and enforcing security with the Agent Governance Stack, …

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