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Tag: Trillium

  • Cloud Blog: The Year in Google Cloud – 2024

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    Source URL: https://cloud.google.com/blog/products/gcp/top-google-cloud-blogs/ Source: Cloud Blog Title: The Year in Google Cloud – 2024 Feedly Summary: If you’re a regular reader of this blog, you know that 2024 was a busy year for Google Cloud. From AI to Zero Trust, and everything in between, here’s a chronological recap of our top blogs of 2024, according…

  • Slashdot: Google Unveils Gemini 2.0

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    Source URL: https://tech.slashdot.org/story/24/12/12/2129245/google-unveils-gemini-20 Source: Slashdot Title: Google Unveils Gemini 2.0 Feedly Summary: AI Summary and Description: Yes **Summary:** Google has launched Gemini 2.0, enhancing its AI capabilities with multimodal functionalities, real-time tool use, and advanced reasoning to foster unique experiences. This upgrade features notable projects like Project Astra and specialized agents for automation, supported by…

  • Hacker News: Trillium TPU Is GA

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    Source URL: https://cloud.google.com/blog/products/compute/trillium-tpu-is-ga Source: Hacker News Title: Trillium TPU Is GA Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the introduction of Google’s latest TPU, Trillium, which is tailored for large-scale AI workloads, focusing on its advancements in computational power, energy efficiency, and training capabilities. This is crucial for organizations leveraging…

  • Cloud Blog: Announcing the general availability of Trillium, our sixth-generation TPU

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    Source URL: https://cloud.google.com/blog/products/compute/trillium-tpu-is-ga/ Source: Cloud Blog Title: Announcing the general availability of Trillium, our sixth-generation TPU Feedly Summary: The rise of large-scale AI models capable of processing diverse modalities like text and images presents a unique infrastructural challenge. These models require immense computational power and specialized hardware to efficiently handle training, fine-tuning, and inference. Over…

  • Cloud Blog: What’s new with HPC and AI infrastructure at Google Cloud

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    Source URL: https://cloud.google.com/blog/topics/hpc/whats-new-with-hpc/ Source: Cloud Blog Title: What’s new with HPC and AI infrastructure at Google Cloud Feedly Summary: At Google Cloud, we’re rapidly advancing our high-performance computing (HPC) capabilities, providing researchers and engineers with powerful tools and infrastructure to tackle the most demanding computational challenges. Here’s a look at some of the key developments…

  • Cloud Blog: 65,000 nodes and counting: Google Kubernetes Engine is ready for trillion-parameter AI models

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    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/gke-65k-nodes-and-counting/ Source: Cloud Blog Title: 65,000 nodes and counting: Google Kubernetes Engine is ready for trillion-parameter AI models Feedly Summary: As generative AI evolves, we’re beginning to see the transformative potential it is having across industries and our lives. And as large language models (LLMs) increase in size — current models are reaching…

  • Cloud Blog: Unlocking LLM training efficiency with Trillium — a performance analysis

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    Source URL: https://cloud.google.com/blog/products/compute/trillium-mlperf-41-training-benchmarks/ Source: Cloud Blog Title: Unlocking LLM training efficiency with Trillium — a performance analysis Feedly Summary: Rapidly evolving generative AI models place unprecedented demands on the performance and efficiency of hardware accelerators. Last month, we launched our sixth-generation Tensor Processing Unit (TPU), Trillium, to address the demands of next-generation models. Trillium is…

  • Cloud Blog: Powerful infrastructure innovations for your AI-first future

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    Source URL: https://cloud.google.com/blog/products/compute/trillium-sixth-generation-tpu-is-in-preview/ Source: Cloud Blog Title: Powerful infrastructure innovations for your AI-first future Feedly Summary: The rise of generative AI has ushered in an era of unprecedented innovation, demanding increasingly complex and more powerful AI models. These advanced models necessitate high-performance infrastructure capable of efficiently scaling AI training, tuning, and inferencing workloads while optimizing…