Experimental News Clipping Site

Tag: Evaluation Metrics

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

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    Kurt Seifried
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    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…

  • Hacker News: Empirical Study of Test Generation with LLM’s

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    system automation
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    Source URL: https://arxiv.org/abs/2406.18181 Source: Hacker News Title: Empirical Study of Test Generation with LLM’s Feedly Summary: Comments AI Summary and Description: Yes Summary: This paper evaluates the use of Large Language Models (LLMs) for automating unit test generation in software development, focusing on open-source models. It emphasizes the importance of prompt engineering and the advantages…

  • 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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    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:…

  • 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…

  • 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:…

  • Hacker News: We need data engineering benchmarks for LLMs

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    system automation
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    Source URL: https://structuredlabs.substack.com/p/why-we-need-data-engineering-benchmarks Source: Hacker News Title: We need data engineering benchmarks for LLMs Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses the shortcomings of existing benchmarks for evaluating the effectiveness of AI-driven tools in data engineering, specifically contrasting them with software engineering benchmarks. It highlights the unique challenges of data…

  • Hacker News: Full LLM training and evaluation toolkit

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    system automation
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    Source URL: https://github.com/huggingface/smollm Source: Hacker News Title: Full LLM training and evaluation toolkit Feedly Summary: Comments AI Summary and Description: Yes Summary: The text introduces SmolLM2, a family of compact language models with varying parameters designed for lightweight, on-device applications, and details on how they can be utilized in different scenarios. Such advancements in AI…

  • Hacker News: Evaluating the World Model Implicit in a Generative Model

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    system automation
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    Source URL: https://arxiv.org/abs/2406.03689 Source: Hacker News Title: Evaluating the World Model Implicit in a Generative Model Feedly Summary: Comments AI Summary and Description: Yes Summary: This paper delves into the evaluation of world models implicitly learned by generative models, particularly large language models (LLMs). It highlights the potential limitations and fragilities of these models in…