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Joined 3 years ago
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Cake day: June 30th, 2023

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  • The embedding layer post tokenization is not just a probability machine the way you’re suggesting it. You can argue that it is probabilistic with inferred sentiment, but too many people think it works like how text prediction on your phone does and that is just factually inaccurate.

    Verify output of course, but saying “it doesn’t understand anything” and “probability machine” is a borderline erroneous short sell. At the level of tokens it “understands” relationships, and those relationships are not probabilistic, though they are fundamentally approximated based on a training corpus.




  • There is a data point missing here.

    Do the same study and give some an LLM, some no LLM, and some a type A subject matter expert for reference. It may also matter if this person is a friend coworker or random passerby, but I would be willing to bet money that the same effect is present to a lesser (but still statistically significant) degree.

    Maybe a future study can be further refined to build some scaffolding for more effective teaching/learning “on the job” or in general.