Large Language Labor Markets §
Highlights §
- The introduction of Dolly suggests that LLMs and other generative AI models are also “skilled,”4 and could be divided along the same crude lines that economists use to divide the labor force. Dolly is low-skill. You might not trust it to send an important email to your boss, but you’d probably be fine with it making a restaurant reservation for you. GPT-4 is high-skill—it might actually be good enough for that email to your boss. And companies will surely develop specialized models that extend GPT-4 ( (View Highlight)
- These high-skill models are likely to be more expensive to employ than their less-skilled counterparts. They would cost more to train because they’d have to be tuned, tested, and refined against a new set of complex tasks. They would also cost more to run. In order to perform advanced tasks, LLMs would probably require longer prompts, which are much more computationally expensive (View Highlight)
- There could be expensive AI therapists that keep years of dialogue in their conversational memory, and there could be cheap ones that start from scratch every session. There could be good AP U.S. History tutors (and test-takers), and bad ones that hallucinate facts about American history.6 There could be AI lawyers that specialize in obscure corporate tax law—for the right price. People with money may be able to train models on lookalike groups of patients and get personalized medical care, while people without it may have to rely on ChatWebMD. (View Highlight)