Experimental News Clipping Site

Tag: efficient fine

  • Cloud Blog: Your guide to taking an open model from discovery to a production-ready endpoint on Vertex AI

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/take-an-open-model-from-discovery-to-endpoint-on-vertex-ai/ Source: Cloud Blog Title: Your guide to taking an open model from discovery to a production-ready endpoint on Vertex AI Feedly Summary: Developers building with gen AI are increasingly drawn to open models for their power and flexibility. But customizing and deploying them can be a huge challenge. You’re often left wrestling…

  • AWS News Blog: Announcing Amazon Nova customization in Amazon SageMaker AI

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    by

    Kurt Seifried
    in

    Source URL: https://aws.amazon.com/blogs/aws/announcing-amazon-nova-customization-in-amazon-sagemaker-ai/ Source: AWS News Blog Title: Announcing Amazon Nova customization in Amazon SageMaker AI Feedly Summary: AWS now enables extensive customization of Amazon Nova foundation models through SageMaker AI with techniques including continued pre-training, supervised fine-tuning, direct preference optimization, reinforcement learning from human feedback and model distillation to better address domain-specific requirements across…

  • Cloud Blog: What’s new with Google Data Cloud

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/data-analytics/whats-new-with-google-data-cloud/ Source: Cloud Blog Title: What’s new with Google Data Cloud Feedly Summary: June 9 – June 13 Introducing Pub/Sub Single Message Transforms (SMTs), to make it easy to perform simple data transformations such as validate, filter, enrich, and alter individual messages as they move in real time right within Pub/Sub. The first…

  • Cloud Blog: From analytics to data management: New BigQuery transactional features

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/data-analytics/bigquery-features-for-transactional-data-management/ Source: Cloud Blog Title: From analytics to data management: New BigQuery transactional features Feedly Summary: For years, BigQuery has been synonymous with fully managed, fast, petabyte-scale analytics. Its columnar architecture and decoupled storage and compute have made it the go-to data warehouse for deriving insights from massive datasets.  But what about the…

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

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    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: Google, Bytedance, and Red Hat make Kubernetes generative AI inference aware

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/google-bytedance-and-red-hat-improve-ai-on-kubernetes/ Source: Cloud Blog Title: Google, Bytedance, and Red Hat make Kubernetes generative AI inference aware Feedly Summary: Over the past ten years, Kubernetes has become the leading platform for deploying cloud-native applications and microservices, backed by an extensive community and boasting a comprehensive feature set for managing distributed systems. Today, we are…

  • Cloud Blog: Supervised Fine Tuning for Gemini: A best practices guide

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/master-gemini-sft/ Source: Cloud Blog Title: Supervised Fine Tuning for Gemini: A best practices guide Feedly Summary: Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning…

  • 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…