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This has been my experience as well. I treat LLMs like an intern or junior who can do the legwork that I have no bandwidth to do myself. I have to supervise it
by wenc 2y ago
This has been my experience as well. I treat LLMs like an intern or junior who can do the legwork that I have no bandwidth to do myself. I have to supervise it and help it along, checking for mistakes, but I do get useful results in the end.
Attitudinally, I suspect people who have had experience supervising interns or mentoring juniors are probably those who are able to get value out of LLMs (paid ones - free ones are no good) rather than grizzled lone individual contributors -- I myself have been in this camp for most of my early career -- who don't know how to coax value out of people.
- wslh 2y ago> ... that I have no bandwidth to do myself. One of the most interesting aspects of this thread is how it brings us back to the fundamentals of attention in machine learning [1]. This is a key point: while humans have intelligence, our attention is inherently limited. This is why the concept behind Attention Is All You Need [2] is so relevant to what we're discussing. My 2 cents: our human intelligence is the glue that binds everything together. [1] https://en.wikipedia.org/wiki/Attention_(machine_learning) https://en.wikipedia.org/wiki/Attention_(machine_learning) [2] https://en.wikipedia.org/wiki/Attention_Is_All_You_Need https://en.wikipedia.org/wiki/Attention_Is_All_You_Need