Thread

1. walrus01 · 1785887768 · focus · HN ↗

   I wish that "small" LLMs would stop being confidently very incorrect. Admittedly this is a bit of an intentionally esoteric test, but the confident way in which it presents a totally incorrect answer is a bit concerning.

   "please write 250 words on the etymology and history of the word schlong"

   <a href="https:&#x2F;&#x2F;pastes.io&#x2F;uhshFgn4" rel="nofollow">https:&#x2F;&#x2F;pastes.io&#x2F;uhshFgn4

   The actual origin of the word is from middle high German and Yiddish-speaking Ashkenazi Jewish communities.

   For comparison qwen 3.6 35B A3B does perfect on this and will give a solid description of the word&#x27;s real origins and how it has made it into casual profanity&#x2F;vulgarity as used in US English, and even mentions specific stand-up comedians and famous public figures of specific ethnic&#x2F;religious origin in the US NE who introduced it into wider use.

   Ask it for something that&#x27;s not a narrow niche scientific or technical field, but something that would be less common to make it into a 20B size model, and see just how it does.

   chat test link: <a href="https:&#x2F;&#x2F;chat.deepgrove.ai&#x2F;">https:&#x2F;&#x2F;chat.deepgrove.ai&#x2F;

   1. sajithdilshan · 1785917321 · focus · HN ↗

      I think for smaller models, they need to be more defensive on unknown information and frontier model level tool calling capabilities.

      LLMs are kind of a compact knowledge box of its training data and it&#x27;s understandable it would not have information about every topic and in that case just do a web search or a proper tool invocation to get the data and then synthesize.

      1. miohtama · 1785935164 · focus · HN ↗

         You need a small LLM that can reason very well and use tools like web search very well.

         No one is going to compress human knowledge into few bits.

         1. sajithdilshan · 1785937073 · focus · HN ↗

            Not at the moment, but who knows what types of models and storage types we would have in 100 years.

            1. jasonjmcghee · 1785939915 · focus · HN ↗

               It&#x27;s far more likely basic consumer devices will advance such that much larger models efficiently run than finding novel ways to compress all of human experience to fit on today&#x27;s mobile hardware.

               Information can only be compressed so much

               1. wolttam · 1785940632 · focus · HN ↗

                  We’re already seeing incredible knowledge compression out of the models the GP mentioned like Qwen 35B-A3B, which feels well within the realm of “runs on a phone” in the next handful of years.

                  And by then we’ll probably have been further surprised by just how much information and capacity for reasoning can be crammed into a few gigs of weights. Models just keep getting better for a given size, it’ll be interesting to see where the limit of that is.

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