toponaut

"the discrimination makes factual sense."

I can't figure out what you mean. Examples?

You seem to be linking religion with "moral standards" and science with "facts". Neither of those are appropriate.

Not all religions teach morality and, if there is such a thing as "fact" on some topic, there is no need to do science on it.

Science and religion are both about our "best guesses". They can point in different directions but that happens within each domain too (Islam vs Buddhism / string theory vs standard model) and doesn't make them incompatible tools.

Not only is that possible but that tendency was the cause (and unexpected finding) of the most famous social psychology "experiment" of them all: https://en.m.wikipedia.org/wiki/Milgram_experiment

I was at Stanford for nearly 10 years. Not formally in CS or AI, granted, but SAIL doesn't ring a bell for me. Maybe it's just not that well known.

Was the final manuscript glued together then? If so, this whole article seems off-point. Why not just say "this old manuscript has images made up of several layers, it looks like collage"?

I was assuming this college technique was used to make a (plan for a) new woodcutting.

Edit:college -> collage

I agree. I didn't mean to imply this was a good explanation or example. I still think "abstraction/classes are good" was the intention/gist of the article.

The author's solution to the toy problem is

---

die = Die(12)

expected_values(die, n=10000)

gaussian = Gaussian(mu=4.0, sigma=2.0)

expected_value(gaussian, n=100000)

coin = Coin(fairness=0.75)

expected_value(coin, f=lambda x: np.where(x == "H", 1.0, 0.0)

---

After all this work, the answers to the problems are right there in the constraints.

ev_die = (sides+1)/2

ev_gaussian = mu

ev_coin = sign * fairness

What is the point?

To a software engineer this will also read mad. This article is ultimately explaining why abstraction is good and why it's helpful to build classes in python. That is already obvious to SWEs, not at all specific to "scientific computing", and explained elsewhere much more succinctly.