Experimental News Clipping Site

Tag: data extraction

  • Slashdot: ‘Please Stop Inviting AI Notetakers To Meetings’

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    Kurt Seifried
    in

    Source URL: https://slashdot.org/story/25/02/15/006253/please-stop-inviting-ai-notetakers-to-meetings?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: ‘Please Stop Inviting AI Notetakers To Meetings’ Feedly Summary: AI Summary and Description: Yes Summary: The text analyzes the implications of AI-powered notetaking tools in virtual meetings, focusing on privacy concerns, miscommunication risks, and the evolving workplace dynamics they create. It emphasizes how reliance on such technology could undermine…

  • Hacker News: Why LLMs still suck at OCR

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    Kurt Seifried
    in

    Source URL: https://www.runpulse.com/blog/why-llms-suck-at-ocr Source: Hacker News Title: Why LLMs still suck at OCR Feedly Summary: Comments AI Summary and Description: Yes Summary: The text explores the challenges faced when using Large Language Models (LLMs) for tasks like Optical Character Recognition (OCR) and complex data extraction, emphasizing their limitations in processing intricate document layouts and the…

  • Simon Willison’s Weblog: DeepSeek API Docs: Rate Limit

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Jan/18/deepseek-api-docs-rate-limit/#atom-everything Source: Simon Willison’s Weblog Title: DeepSeek API Docs: Rate Limit Feedly Summary: DeepSeek API Docs: Rate Limit This is surprising: DeepSeek offer the only hosted LLM API I’ve seen that doesn’t implement rate limits: DeepSeek API does NOT constrain user’s rate limit. We will try out best to serve every request. However,…

  • Hacker News: Nvidia-Ingest: Multi-modal data extraction

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    Kurt Seifried
    in

    Source URL: https://github.com/NVIDIA/nv-ingest Source: Hacker News Title: Nvidia-Ingest: Multi-modal data extraction Feedly Summary: Comments AI Summary and Description: Yes Summary: The NVIDIA-Ingest microservice represents a significant advancement in multi-modal document data extraction, crucial for leveraging generative AI and machine learning applications. By effectively contextualizing and extracting diverse content types from documents, it offers enhanced performance…

  • Simon Willison’s Weblog: My AI/LLM predictions for the next 1, 3 and 6 years, for Oxide and Friends

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Jan/10/ai-predictions/#atom-everything Source: Simon Willison’s Weblog Title: My AI/LLM predictions for the next 1, 3 and 6 years, for Oxide and Friends Feedly Summary: The Oxide and Friends podcast has an annual tradition of asking guests to share their predictions for the next 1, 3 and 6 years. Here’s 2022, 2023 and 2024. This…

  • Cloud Blog: Enhance viewer engagement with gen AI-powered scene detection for ads

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/topics/developers-practitioners/use-ai-powered-scene-detection-for-more-effective-ad-placement/ Source: Cloud Blog Title: Enhance viewer engagement with gen AI-powered scene detection for ads Feedly Summary: Online video consumption has skyrocketed. A staggering 1.8 billion people globally subscribed to streaming services in 20231, and 92% of internet users worldwide watched online videos every month in 20242. This growth creates a significant opportunity…

  • Hacker News: Show HN: DataFuel.dev – Turn websites into LLM-ready data

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    system automation
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    Source URL: https://www.datafuel.dev/ Source: Hacker News Title: Show HN: DataFuel.dev – Turn websites into LLM-ready data Feedly Summary: Comments AI Summary and Description: Yes Summary: The text is highly relevant to the categories of LLM Security and MLOps as it discusses a platform that converts web content into datasets prepared for Large Language Models (LLMs).…

  • Hacker News: Structured Outputs with Ollama

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    system automation
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    Source URL: https://ollama.com/blog/structured-outputs Source: Hacker News Title: Structured Outputs with Ollama Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text elaborates on enhancements to the Ollama libraries that support structured outputs, allowing users to constrain model responses to predefined JSON formats. This innovation can improve the reliability and consistency of data extraction in…

  • Cloud Blog: Build agentic RAG on Google Cloud databases with LlamaIndex

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    system automation
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    Source URL: https://cloud.google.com/blog/products/databases/llamaindex-integrates-with-alloydb-and-cloud-sql-for-postgresql/ Source: Cloud Blog Title: Build agentic RAG on Google Cloud databases with LlamaIndex Feedly Summary: AI agents are revolutionizing the landscape of gen AI application development. Retrieval augmented generation (RAG) has significantly enhanced the capabilities of large language models (LLMs), enabling them to access and leverage external data sources such as databases.…

  • Simon Willison’s Weblog: Structured Generation w/ SmolLM2 running in browser & WebGPU

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    system automation
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    Source URL: https://simonwillison.net/2024/Nov/29/structured-generation-smollm2-webgpu/#atom-everything Source: Simon Willison’s Weblog Title: Structured Generation w/ SmolLM2 running in browser & WebGPU Feedly Summary: Structured Generation w/ SmolLM2 running in browser & WebGPU Extraordinary demo by Vaibhav Srivastav. Here’s Hugging Face’s SmolLM2-1.7B-Instruct running directly in a web browser (using WebGPU, so requires Chrome for the moment) demonstrating structured text extraction,…