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AI performs best in non-deterministic environments where highly extensive if slightly imperfect (or even hallucinatory) knowledge works just fine. When mapped o
by ChiMan 1y ago
AI performs best in non-deterministic environments where highly extensive if slightly imperfect (or even hallucinatory) knowledge works just fine. When mapped onto today’s jobs, the fit feels less natural for high-level engineering than for “looser” tasks that would do well to be armed with wider knowledge. In other words, it seems like AI—or AI-armed humans—are more squarely aimed at executives.
- pfannkuchen 1y agoDelegating executive decision making to what is essentially an automated form of Reddit and stack overflow seems like it could possibly lead to bad results.
- ChiMan 1y agoThe point is not to delegate. It’s to augment.
- only-one1701 1y agoSerious question: do you not think these very executives are relying HEAVILY on ChatGPT etc right now?
- AquilaFasciata 1y agoNo, they rely on "consultants."
- pfannkuchen 1y agoFor me, LLMs have been a very useful interface to tutorials for ramping up on new areas. That’s about it, IME so far. I suppose the executive equivalent would be as an interface to business books, case studies, etc. With all the variance in such a high dimensional space, probably higher dimensional than starter tier tech projects in an area, I can’t imagine that it would actually be very useful when the long run results are considered. What do you think they’re being used for right now?