I heared the same distinction as OP, but it is the other way around, it's the degree to what a trait is inherited from you parents which cannot be explained by the enviroment or Random Chance.
IMHO, it's a people Thing. People developed better practices, talked about IT in conferences, maybe left the company. AS a result the knowlegde spread. On the other Hand, If the places where a skilled individual can work and honey their skills, the knowlegde become scarce, the knowlegde cannot spread anymore and it will vanish. If you only program with AI and 5 people do the Work of 100, then you end Up in such a scenario.
So If Amazon wante to be the lowest price Destination, but Takes fees for Listings, FBA etc, then the product price needs to include that fees. That will make the product more expensive and since amazon wanted to be the cheapest Destination, the price does need to gonup everywhere?
It's maybe the Fairest Thing, but is it good for the Overall Economy?
Sorry to hear that and that you and your Family could find some peace and strength, i remember a quote which maybe fits Here: you can play a perfect Game and still loose. That's not a weakness, that's life.
The funny Thing is, If these LLMs withold this information. What does it withhold else? Can i trust These Corporate LLMs If i Look for information and i am not deemed a Domain expert?
Normally in this kind of systems, the detection is the nonlinearity.
That is, you send light through the system, the light can interfere, Changes path through the system but in the end you can detect only the intensities, |E|^2.
This Has it's use. The continouus Fourier Transform is is based on that. You are asking what frequencies is this continouus signal made of. Time is normally defined as a real number in that context, but If you have a continouus time you need continouus frequencies to map time space to frequency space. You can think about an Index as a lego Block, that you need to construct Something.
Does this Not make sense? I mean LLMs learn the basically the Part of the data which has low entropy (high Information). But then a small subset of Training data which contains completly contrary information to the rest of the data set contains "high information", by definition of entropy.