Tag: latency

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Source URL: https://www.docker.com/blog/how-to-build-an-ai-tutor-with-model-runner/ Source: Docker Title: Prototyping an AI Tutor with Docker Model Runner Feedly Summary: Every developer remembers their first docker run hello-world. The mix of excitement and wonder as that simple command pulls an image, creates a container, and displays a friendly message. But what if AI could make that experience even better?…

Cloud Blog: 101+ gen AI use cases with technical blueprints

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Source URL: https://cloud.google.com/blog/products/ai-machine-learning/real-world-gen-ai-use-cases-with-technical-blueprints/ Source: Cloud Blog Title: 101+ gen AI use cases with technical blueprints Feedly Summary: A little over a year ago, we published a list of generative AI use cases that has since grown to include more than 600 examples of how organizations are putting AI to work. Yet for many developers and…

Cloud Blog: How to build a real-time voice agent with Gemini, Google ADK, and A2A protocol

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Source URL: https://cloud.google.com/blog/products/ai-machine-learning/build-a-real-time-voice-agent-with-gemini-adk/ Source: Cloud Blog Title: How to build a real-time voice agent with Gemini, Google ADK, and A2A protocol Feedly Summary: Building advanced conversational AI has moved well beyond text. Now, we can use AI to create real-time, voice-driven agents. However, these systems need low-latency, two-way communication, real-time information retrieval, and the ability…

Cloud Blog: How much energy does Google’s AI use? We did the math

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Source URL: https://cloud.google.com/blog/products/infrastructure/measuring-the-environmental-impact-of-ai-inference/ Source: Cloud Blog Title: How much energy does Google’s AI use? We did the math Feedly Summary: AI is unlocking scientific breakthroughs, improving healthcare and education, and could add trillions to the global economy. Understanding AI’s footprint is crucial, yet thorough data on the energy and environmental impact of AI inference —…

Cloud Blog: Rightsizing LLM Serving on vLLM for GPUs and TPUs

Aug 19, 2025

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Source URL: https://cloud.google.com/blog/topics/developers-practitioners/rightsizing-llm-serving-on-vllm-for-gpus-and-tpus/ Source: Cloud Blog Title: Rightsizing LLM Serving on vLLM for GPUs and TPUs Feedly Summary: Additional contributors include Hossein Sarshar and Ashish Narasimham. Large Language Models (LLMs) are revolutionizing how we interact with technology, but serving these powerful models efficiently can be a challenge. vLLM has rapidly become the primary choice for…

Cloud Blog: Beyond guardrails: A taxonomy of platform engineering control mechanisms

Aug 15, 2025

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Source URL: https://cloud.google.com/blog/products/application-modernization/platform-engineering-control-mechanisms/ Source: Cloud Blog Title: Beyond guardrails: A taxonomy of platform engineering control mechanisms Feedly Summary: The promise of platform engineering is to accelerate software delivery by empowering developers with self-service capabilities. However, this must be balanced with security, compliance, and operational stability, and for this, you need robust controls. But all too…

Slashdot: Google Releases Pint-Size Gemma Open AI Model

Aug 14, 2025

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Source URL: https://tech.slashdot.org/story/25/08/14/2150230/google-releases-pint-size-gemma-open-ai-model?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Google Releases Pint-Size Gemma Open AI Model Feedly Summary: AI Summary and Description: Yes Summary: Google has introduced the Gemma 3 270M, a compact AI model optimized for local deployment, which offers significant advantages in terms of privacy and efficiency. While it may not match the performance of larger…

Cloud Blog: Scalable AI starts with storage: Guide to model artifact strategies

Aug 14, 2025

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Source URL: https://cloud.google.com/blog/topics/developers-practitioners/scalable-ai-starts-with-storage-guide-to-model-artifact-strategies/ Source: Cloud Blog Title: Scalable AI starts with storage: Guide to model artifact strategies Feedly Summary: Managing large model artifacts is a common bottleneck in MLOps. Baking models into container images leads to slow, monolithic deployments, and downloading them at startup introduces significant delays. This guide explores a better way: decoupling your…

Cloud Blog: How Keeta processes 11 million financial transactions per second with Spanner

Aug 14, 2025

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