Tag: GPU cluster

  • Cloud Blog: Taming the stragglers: Maximize AI training performance with automated straggler detection

    Source URL: https://cloud.google.com/blog/products/compute/stragglers-in-ai-a-guide-to-automated-straggler-detection/ Source: Cloud Blog Title: Taming the stragglers: Maximize AI training performance with automated straggler detection Feedly Summary: Stragglers are an industry-wide issue for developers working with large-scale machine learning workloads. The larger and more powerful these systems become, the more their performance is hostage to the subtle misbehavior of a single component.…

  • Cloud Blog: Accelerate your gen AI: Deploy Llama4 & DeepSeek on AI Hypercomputer with new recipes

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/deploying-llama4-and-deepseek-on-ai-hypercomputer/ Source: Cloud Blog Title: Accelerate your gen AI: Deploy Llama4 & DeepSeek on AI Hypercomputer with new recipes Feedly Summary: The pace of innovation in open-source AI is breathtaking, with models like Meta’s Llama4 and DeepSeek AI’s DeepSeek. However, deploying and optimizing large, powerful models can be  complex and resource-intensive. Developers and…

  • Cloud Blog: Driving enterprise transformation with new compute innovations and offerings

    Source URL: https://cloud.google.com/blog/products/compute/delivering-new-compute-innovations-and-offerings/ Source: Cloud Blog Title: Driving enterprise transformation with new compute innovations and offerings Feedly Summary: In the last 12 months, we’ve made incredible enhancements to our Compute Engine platform. This is driven most notably by new fourth-generation compute instances and Hyperdisk block storage as well as major customer experience enhancements. Across all…

  • Cloud Blog: Accelerating AI in healthcare using NVIDIA BioNeMo Framework and Blueprints on GKE

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/accelerate-ai-in-healthcare-nvidia-bionemo-gke/ Source: Cloud Blog Title: Accelerating AI in healthcare using NVIDIA BioNeMo Framework and Blueprints on GKE Feedly Summary: The quest to develop new medical treatments has historically been a slow, arduous process, screening billions of molecular compounds across decade-long development cycles. The vast majority of therapeutic candidates do not even make it…

  • The Register: Despite Wall Street jitters, AI hopefuls keep spending billions on AI infrastructure

    Source URL: https://www.theregister.com/2025/02/25/shaking_off_wall_street_jitters/ Source: The Register Title: Despite Wall Street jitters, AI hopefuls keep spending billions on AI infrastructure Feedly Summary: Sunk cost fallacy? No, I just need a little more cash for this AGI thing I’ve been working on Comment Despite persistent worries that vast spending on AI infrastructure may not pay for itself,…

  • Cloud Blog: Networking support for AI workloads

    Source URL: https://cloud.google.com/blog/products/networking/cross-cloud-network-solutions-support-for-ai-workloads/ Source: Cloud Blog Title: Networking support for AI workloads Feedly Summary: At Google Cloud, we strive to make it easy to deploy AI models onto our infrastructure. In this blog we explore how the Cross-Cloud Network solution supports your AI workloads. Managed and Unmanaged AI options Google Cloud provides both managed (Vertex…

  • CSA: DeepSeek: Rewriting the Rules of AI Development

    Source URL: https://cloudsecurityalliance.org/blog/2025/01/29/deepseek-rewriting-the-rules-of-ai-development Source: CSA Title: DeepSeek: Rewriting the Rules of AI Development Feedly Summary: AI Summary and Description: Yes **Short Summary with Insight:** The text presents a groundbreaking shift in AI development led by DeepSeek, a new player challenging conventional norms. By demonstrating that advanced AI can be developed efficiently with limited resources, it…

  • Hacker News: Training AI models might not need enormous data centres

    Source URL: https://www.economist.com/science-and-technology/2025/01/08/training-ai-models-might-not-need-enormous-data-centres Source: Hacker News Title: Training AI models might not need enormous data centres Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the increasing competition among tech leaders to secure vast computational resources, specifically GPUs, which are crucial for training advanced AI models like GPT-4. This arms race highlights…