This is incorrect reasoning. Science is advancing. It is like saying we should not listen to physicists because "Didn't those physicists gave us the original heliocentric system?"
Who was lobbied? The lobbyists can’t publish things in the Federal Register. How it works is they try to influence the experts at the agencies to support their position. That’s what lobbying is. It’s all laundered through experts both in the private sector and the government.
>How it works is they try to influence the experts at the agencies to support their position
The real winning move if you can afford it to pay for a bunch of academic labs who won't at the margin publish stuff that's bad for their sugardaddy. This way the lawmakers, the bureaucrats and the public discourse is all built upon numbers and information that is favorable to you. So then when those officials you bought make the "right" decisions they can do so in comfort knowing that their decisions are backed by the numbers.
> The real winning move if you can afford it to pay for a bunch of academic labs who won't at the margin publish stuff that's bad for their sugardaddy.
No, that is plain old recursion. Dynamic programming is recursive programming with a twist. The twist is that identical sub-problems are short-circuited with memoization.
For me, Emacs on Mac OS is not all that stable. I see a freeze about twice a month, which is not "very rarely" in my book. It also leaks memory, albeit now (in the upcoming version) less so. (Disclaimer: I am a heavy user and contributor.)
What version of Emacs are you using? I stopped using Mitsuharu port because of its weird behaviors and instability and been using plain GNU/Emacs - typically I install it via emacs-plus homebrew formula. It's been very stable for me for the past few years.
Psychology is stuck in pre-Galilean era. Even if it studies "properties of thought", as you put it, it does so without formal basis, let alone understanding from first principles. As Chomsky said, about psychology and the like, "You want to move from behavioral science to authentic science." [1]
Yes. An artificial neuron, as a mathematical function f, is defined by f(x) = g(wx + b) where x is the input, w is the weight, b is the bias, and g is some non-linear activation function. Is that "good old linear regression followed by an activation function to make it non linear"? Yes, it is exactly that.
Abstraction is the opposite of specialization, not precision. Multiplication, for example, is an abstraction that can be defined in terms of repeated addition of the same term, which is less general, and so more special, than addition of two arbitrary terms, but it not less precise.