Experimental News Clipping Site

Tag: human evaluation

  • Simon Willison’s Weblog: Anthropic: How we built our multi-agent research system

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Jun/14/multi-agent-research-system/#atom-everything Source: Simon Willison’s Weblog Title: Anthropic: How we built our multi-agent research system Feedly Summary: Anthropic: How we built our multi-agent research system OK, I’m sold on multi-agent LLM systems now. I’ve been pretty skeptical of these until recently: why make your life more complicated by running multiple different prompts in parallel…

  • Cloud Blog: Evaluate your gen media models with multimodal evaluation on Vertex AI

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/evaluate-your-gen-media-models-on-vertex-ai/ Source: Cloud Blog Title: Evaluate your gen media models with multimodal evaluation on Vertex AI Feedly Summary: The world of generative AI is moving fast, with models like Lyria, Imagen, and Veo now capable of producing stunningly realistic and imaginative images and videos from simple text prompts. However, evaluating these models is…

  • Cloud Blog: Palo Alto Networks’ journey to productionizing gen AI

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/topics/partners/how-palo-alto-networks-builds-gen-ai-solutions/ Source: Cloud Blog Title: Palo Alto Networks’ journey to productionizing gen AI Feedly Summary: At Google Cloud, we empower businesses to accelerate their generative AI innovation cycle by providing a path from prototype to production. Palo Alto Networks, a global cybersecurity leader, partnered with Google Cloud to develop an innovative security posture…

  • Hacker News: Command A: Max performance, minimal compute – 256k context window

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    Kurt Seifried
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    Source URL: https://cohere.com/blog/command-a Source: Hacker News Title: Command A: Max performance, minimal compute – 256k context window Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text introduces Command A, a powerful generative AI model designed to meet the performance and security needs of enterprises. It emphasizes the model’s efficiency, cost-effectiveness, and multi-language capabilities…

  • AWS News Blog: DeepSeek-R1 now available as a fully managed serverless model in Amazon Bedrock

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    Kurt Seifried
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    Source URL: https://aws.amazon.com/blogs/aws/deepseek-r1-now-available-as-a-fully-managed-serverless-model-in-amazon-bedrock/ Source: AWS News Blog Title: DeepSeek-R1 now available as a fully managed serverless model in Amazon Bedrock Feedly Summary: DeepSeek-R1 is now available as a fully managed model in Amazon Bedrock, freeing up your teams to focus on strategic initiatives instead of managing infrastructure complexities. AI Summary and Description: Yes Summary: The…

  • Hacker News: Automated Capability Discovery via Foundation Model Self-Exploration

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    Kurt Seifried
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    Source URL: https://arxiv.org/abs/2502.07577 Source: Hacker News Title: Automated Capability Discovery via Foundation Model Self-Exploration Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper “Automated Capability Discovery via Model Self-Exploration” introduces a new framework (Automated Capability Discovery or ACD) designed to evaluate foundation models’ abilities by allowing one model to propose tasks for another…

  • Hacker News: Coping with dumb LLMs using classic ML

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    Kurt Seifried
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    Source URL: https://softwaredoug.com/blog/2025/01/21/llm-judge-decision-tree Source: Hacker News Title: Coping with dumb LLMs using classic ML Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides an innovative approach to utilizing local LLMs (large language models) to assess product relevance for e-commerce search queries. By collecting data on LLM decisions and comparing them against human…

  • Chip Huyen: Common pitfalls when building generative AI applications

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    Kurt Seifried
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    Source URL: https://huyenchip.com//2025/01/16/ai-engineering-pitfalls.html Source: Chip Huyen Title: Common pitfalls when building generative AI applications Feedly Summary: As we’re still in the early days of building applications with foundation models, it’s normal to make mistakes. This is a quick note with examples of some of the most common pitfalls that I’ve seen, both from public case…

  • 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…

  • 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:…