I used to worked at Intel as a design engineer and I had to look through data-sheets to find the ICs with features and specs that I needed for the design.
I checked out the Gold Mine problem on geeksforgeeks (assuming it is the same problem at firebase). Can you explain why it is "potentially impossible" to get the optimal solution?
I say insect intelligence is good enough to at least drive car. Bee, for example, is pretty damn amazing at flying & navigation. I mean flying and avoiding obstacles through miles of forest to find food is no easy task.
If the radiologist has to look at and double check every scan that algo looked at, then what is the point of the algo? Seems like a useless middleman that get in the way.
The act of making a measurement/observation is nothing more than an interaction where the system is exchanging information or this this case quantum states which is described by quantum mechanics. I don't get where this "special/outside" observer coming from.
Correct me if I am wrong, the "paradoxes" described here are due to our lack of understanding of the theory right and not because the theory is inconsistent.
From my experience, LSTM or other recurrent neural network models only work "well" at forecasting bounded and periodic or oscillating time series. Might work for something like seasonal sale data, but would fail spectacularly with unbounded and chaotic time series like stock prices.