Experimental News Clipping Site

Tag: human evaluation

  • 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…

  • AWS News Blog: New RAG evaluation and LLM-as-a-judge capabilities in Amazon Bedrock

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    system automation
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    Source URL: https://aws.amazon.com/blogs/aws/new-rag-evaluation-and-llm-as-a-judge-capabilities-in-amazon-bedrock/ Source: AWS News Blog Title: New RAG evaluation and LLM-as-a-judge capabilities in Amazon Bedrock Feedly Summary: Evaluate AI models and applications efficiently with Amazon Bedrock’s new LLM-as-a-judge capability for model evaluation and RAG evaluation for Knowledge Bases, offering a variety of quality and responsible AI metrics at scale. AI Summary and Description:…

  • AWS News Blog: New RAG evaluation and LLM-as-a-judge capabilities in Amazon Bedrock

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    by

    system automation
    in

    Source URL: https://aws.amazon.com/blogs/aws/new-rag-evaluation-and-llm-as-a-judge-capabilities-in-amazon-bedrock/ Source: AWS News Blog Title: New RAG evaluation and LLM-as-a-judge capabilities in Amazon Bedrock Feedly Summary: Evaluate AI models and applications efficiently with Amazon Bedrock’s new LLM-as-a-judge capability for model evaluation and RAG evaluation for Knowledge Bases, offering a variety of quality and responsible AI metrics at scale. AI Summary and Description:…

  • 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…

  • Hacker News: Task-Specific LLM Evals That Do and Don’t Work

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    system automation
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    Source URL: https://eugeneyan.com/writing/evals/ Source: Hacker News Title: Task-Specific LLM Evals That Do and Don’t Work Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents a comprehensive overview of evaluation metrics for machine learning tasks, specifically focusing on classification, summarization, and translation within the context of large language models (LLMs). It highlights the…