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Off the top of my head: Shannon, Nyquist, Hamming. Lapping them you say.

I think my reading of your comment is: that's just wrong. And I tend to agree. The current STEM and FAANG activity is second order work in the main. I wouldn't hold AI work up as a paragon, myself. It's diverting from progress across a field.

I have hopes of a resurgence of operations research and linear optimisation as goods in themselves: we could be plotting more nuanced courses in dark waters of competing pressure. Decision systems support across many fields would remove subjective, politicised pressures.

Do you think there is room for a resurgence in linear optimization?

Linear programming, and even integer linear programming are pretty well solved practically speaking.

I tried using some online systems to help formulate weighted sum decisions over unrankable choices and it's bloody hard work getting people on board. I think how the logic presents could improve.

This stuff while old, is not routine for decision makers. They don't seem to grok how to formulate the questions and the choices.

I think it’s fundamentally hard to make tools like that because models can be sensitive to specifics, so dumbing them down is generally not great

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