Oct 11, 2017

How To Build A Great House

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714435 comments

  • Kenneth Hernandez
    Kenneth Hernandez 18 May 2026 05:38 AM

    Seeing Grok-3 hit 94% on CJR is impressive, but these benchmarks rarely reflect how models actually behave in our production environments. I am curious how much of that accuracy relies on specific prompt engineering versus the core model architecture http://padlet.com/interworldradiodavlq/bookmarks-wqsavqy0w94y1dab/wish/jpoxajk1bA3OQbPE

  • Sophie Hernandez
    Sophie Hernandez 18 May 2026 05:05 AM

    It is refreshing to see more transparency in how these models fail. Seeing the HalluHard benchmark land at 30.2% even with web search enabled really highlights how much ground we still have to cover regarding grounding HalluHard benchmark

  • Winifred Gilbert
    Winifred Gilbert 18 May 2026 05:40 AM

    It’s interesting to see Grok-3 hitting 94% on CJR, but I am curious how these benchmarks actually correlate with real-world RAG performance. In my experience, these scores often look great on paper but collapse when dealing with messy enterprise data http://mighty-wiki.win/index.php/Why_Do_Multi-Turn_Chats_Repeat_Earlier_Hallucinations_(3-20%25)%3F

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    nn777 18 May 2026 04:53 AM

    Today, I went to the beach front with my kids. I found a sea shell and gave it to my 4 year old daughter and said "You can hear the ocean if you put this to your ear." She placed the shell to her ear and screamed. There was a hermit crab inside and it pinched her ear. She never wants to go back! LoL I know this is totally off topic but I had to tell someone!

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  • Cora Phillips
    Cora Phillips 18 May 2026 04:04 AM

    The HalluHard results showing 30.2% with web search are sobering for anyone deploying these models in production. It reinforces why we cannot rely on retrieval-augmented generation as a silver bullet for factual consistency GPT-5 hallucination

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  • Wesley Newman
    Wesley Newman 18 May 2026 04:22 AM

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