Experimental News Clipping Site

Tag: open models

  • Cloud Blog: Guide: Our top four AI Hypercomputer use cases, reference architectures and tutorials

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/ai-hypercomputer-4-use-cases-tutorials-and-guides/ Source: Cloud Blog Title: Guide: Our top four AI Hypercomputer use cases, reference architectures and tutorials Feedly Summary: AI Hypercomputer is a fully integrated supercomputing architecture for AI workloads – and it’s easier to use than you think. In this blog, we break down four common use cases, including reference architectures and…

  • Cloud Blog: Introducing A4X VMs powered by NVIDIA GB200 — now in preview

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/compute/new-a4x-vms-powered-by-nvidia-gb200-gpus/ Source: Cloud Blog Title: Introducing A4X VMs powered by NVIDIA GB200 — now in preview Feedly Summary: The next frontier of AI is reasoning models that think critically and learn during inference to solve complex problems. To train and serve this new class of models, you need infrastructure with the performance and…

  • Cloud Blog: News you can use: What we announced in AI this month

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/what-google-cloud-announced-in-ai-this-month/ Source: Cloud Blog Title: News you can use: What we announced in AI this month Feedly Summary: 2025 is off to a racing start. From announcing strides in the new Gemini 2.0 model family to retailers accelerating with Cloud AI, we spent January investing in our partner ecosystem, open-source, and ways to…

  • Cloud Blog: Announcing smaller machine types for A3 High VMs

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/compute/announcing-smaller-machine-types-for-a3-high-vms/ Source: Cloud Blog Title: Announcing smaller machine types for A3 High VMs Feedly Summary: Today, an increasing number of organizations are using GPUs to run inference1 on their AI/ML models. Since the number of GPUs needed to serve a single inference workload varies, organizations need more granularity in the number of GPUs…

  • Hacker News: AI Engineer Reading List

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    Kurt Seifried
    in

    Source URL: https://www.latent.space/p/2025-papers Source: Hacker News Title: AI Engineer Reading List Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text focuses on providing a curated reading list for AI engineers, particularly emphasizing recent advancements in large language models (LLMs) and related AI technologies. It is a practical guide designed to enhance the knowledge…

  • Hacker News: Nvidia releases its own brand of world models

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    Kurt Seifried
    in

    Source URL: https://techcrunch.com/2025/01/06/nvidia-releases-its-own-brand-of-world-models/ Source: Hacker News Title: Nvidia releases its own brand of world models Feedly Summary: Comments AI Summary and Description: Yes **Summary:** Nvidia has introduced Cosmos World Foundation Models (Cosmos WFMs), a new family of AI models aimed at generating physics-aware video content. These models, available through various platforms, are designed for diverse…

  • Cloud Blog: Optimizing RAG retrieval: Test, tune, succeed

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    system automation
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/optimizing-rag-retrieval/ Source: Cloud Blog Title: Optimizing RAG retrieval: Test, tune, succeed Feedly Summary: Retrieval-augmented generation (RAG) supercharges large language models (LLMs) by connecting them to real-time, proprietary, and specialized data. This helps LLMs deliver more accurate, relevant, and contextually aware responses, minimizing hallucinations and building trust in AI applications. But RAG can be…

  • Cloud Blog: Orchestrating GPU-based distributed training workloads on AI Hypercomputer

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    system automation
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/gpu-orchestration-options-on-ai-hypercomputer/ Source: Cloud Blog Title: Orchestrating GPU-based distributed training workloads on AI Hypercomputer Feedly Summary: When it comes to AI, large language models (LLMs) and machine learning (ML) are taking entire industries to the next level. But with larger models and datasets, developers need distributed environments that span multiple AI accelerators (e.g. GPUs…

  • Slashdot: Google Says Its New PaliGemma 2 AI Models Can Identify Emotions. Should We Be Worried?

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    system automation
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    Source URL: https://tech.slashdot.org/story/24/12/06/0222235/google-says-its-new-paligemma-2-ai-models-can-identify-emotions-should-we-be-worried?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Google Says Its New PaliGemma 2 AI Models Can Identify Emotions. Should We Be Worried? Feedly Summary: AI Summary and Description: Yes Summary: The emergence of Google’s PaliGemma 2 AI model, which possesses emotion recognition capabilities, raises significant ethical and security concerns. The profession must be aware of the…