Experimental News Clipping Site

Tag: ML inference

  • Cloud Blog: New GKE inference capabilities reduce costs, tail latency and increase throughput

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/understanding-new-gke-inference-capabilities/ Source: Cloud Blog Title: New GKE inference capabilities reduce costs, tail latency and increase throughput Feedly Summary: When it comes to AI, inference is where today’s generative AI models can solve real-world business problems. Google Kubernetes Engine (GKE) is seeing increasing adoption of gen AI inference. For example, customers like HubX run…

  • Cloud Blog: An SRE’s guide to optimizing ML systems with MLOps pipelines

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/devops-sre/applying-sre-principles-to-your-mlops-pipelines/ Source: Cloud Blog Title: An SRE’s guide to optimizing ML systems with MLOps pipelines Feedly Summary: Picture this: you’re an Site Reliability Engineer (SRE) responsible for the systems that power your company’s machine learning (ML) services. What do you do to ensure you have a reliable ML service, how do you know…

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

    —

    by

    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…

  • The Register: Foundation model for tabular data slashes training from hours to seconds

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.theregister.com/2025/01/15/foundation_model_tabular_data/ Source: The Register Title: Foundation model for tabular data slashes training from hours to seconds Feedly Summary: Good ol’ spreadsheet data could benefit from ‘revolutionary’ approach to ML inferences Move over ChatGPT and DALL-E: Spreadsheet data is getting its own foundation machine learning model, allowing users to immediately make inferences about new…

  • AWS News Blog: AWS Lambda SnapStart for Python and .NET functions is now generally available

    —

    by

    system automation
    in

    Source URL: https://aws.amazon.com/blogs/aws/aws-lambda-snapstart-for-python-and-net-functions-is-now-generally-available/ Source: AWS News Blog Title: AWS Lambda SnapStart for Python and .NET functions is now generally available Feedly Summary: AWS Lambda SnapStart boosts Python and .NET functions’ startup times to sub-second levels, often with minimal code changes, enabling highly responsive and scalable serverless apps. AI Summary and Description: Yes Summary: The announcement…

  • Cloud Blog: Data loading best practices for AI/ML inference on GKE

    —

    by

    system automation
    in

    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/improve-data-loading-times-for-ml-inference-apps-on-gke/ Source: Cloud Blog Title: Data loading best practices for AI/ML inference on GKE Feedly Summary: As AI models increase in sophistication, there’s increasingly large model data needed to serve them. Loading the models and weights along with necessary frameworks to serve them for inference can add seconds or even minutes of scaling…