In a 2023 living note from Shalizi, it's proposed that LLMs are Markov. Therefore there's nothing special about them other than being large; any other Markov model would do just as well. Shalizi therefore proposes Large Lempel-Ziv: LZ78 without dictionary truncation. This is obviously a little silly, because Lempel-Ziv dictionaries don't scale; we can't just magically escape asymptotes. Instead, we will do the non-silly thing: review the literature, design novel data structures, and demonstrate a brand-new breakthrough in compression technology.
A regression at the occupation level weighted by current employment finds that growth projections are somewhat weaker for jobs with more observed exposure. For every 10 percentage point increase in coverage, the BLS’s growth projection drops by 0.6 percentage points. This provides some validation in that our measures track the independently derived estimates from labor market analysts, although the relationship is slight. Interestingly, there is no such correlation using the Eloundou et al. measure alone.
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Марина Совина (ночной редактор)