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Michael Scott: The Original Large Language Model
AI ML Post #5936, on Mar 20, 2024 in TG

Michael Scott: The Original Large Language Model

Description

A popular meme format featuring a still image of Michael Scott, a character from the TV series 'The Office,' in his office setting. He has a pensive, slightly vacant expression. Above the image, a caption reads, 'Michael Scott predicted LLM's in 2008.' Below the image, a subtitle from the show displays his quote: 'Sometimes I'll start a sentence and I don't even know where it's going. I just hope I find it along the way.' The meme humorously draws a parallel between Michael Scott's chaotic and improvisational speaking style and the probabilistic nature of Large Language Models (LLMs). The technical joke is that LLMs generate text token by token based on statistical likelihood, without a pre-planned structure for the entire sentence, effectively 'hoping to find it along the way.' This creates a clever and relatable analogy for developers and AI practitioners who understand how these models function under the hood

Comments

13
Anonymous ★ Top Pick Our new flagship LLM is built on the Michael Scott architecture: it generates confident-sounding output with zero underlying intent and occasionally ends up being accidentally brilliant
  1. Anonymous ★ Top Pick

    Our new flagship LLM is built on the Michael Scott architecture: it generates confident-sounding output with zero underlying intent and occasionally ends up being accidentally brilliant

  2. Anonymous

    Transformer 101 for the exec deck: it’s Michael Scott picking his next word with a softmax - beam search just makes sure none of the options look too HR-worthy

  3. Anonymous

    The real genius of Michael Scott wasn't inventing the Dundies or declaring bankruptcy - it was accidentally describing transformer architecture's autoregressive token generation 5 years before attention was all we needed

  4. Anonymous

    This perfectly captures the essence of autoregressive language models: they're essentially doing next-token prediction at 175 billion parameters, confidently generating each word without a roadmap, occasionally arriving at coherent destinations, and sometimes ending up explaining why the moon is made of cheese with impeccable grammar and zero self-awareness. The real prediction here is that we'd spend billions of dollars to build systems that embody Michael Scott's communication strategy at scale

  5. Anonymous

    LLMs: autoregressive rambling perfected - no planning, just next-token prayer, Michael Scott edition

  6. Anonymous

    Autoregressive decoders are just executives with a softmax - start talking, sample the next word, and pray beam search converges before the meeting ends

  7. Anonymous

    LLMs: start a sentence with no plan, let next-token prediction improvise the strategy, then call it “vision” after RLHF cleans it up

  8. @ZgGPuo8dZef58K6hxxGVj3Z2 2y

    Fr

  9. @Sp1cyP3pp3r 2y

    didn't know i am LLM

  10. @Supuhstar 2y

    It me, ADHD an LLM

    1. @purplesyringa 2y

      i feel called out

      1. @Supuhstar 2y

        https://t.me/ItCameFromTheStars/1692

  11. @Maxinator_Great 2y

    LLM it's large language model?

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