It’s because we’re also very used to seeing photographs of a subject in shade while the background is in full sunlight. If you take a picture of a white and gold dress in the shadow of a patio, with the background all fully lit by bright sunlight, the actual pixels representing white objects in the shade would be that bluish gray tint.

The problem here is that the dress isn’t in the shade but those of us who see white and gold simply assume that it is in shade, while black/blue viewers (correctly) assume that it is under the same lighting conditions of the overexposed background.

That’s…why it went viral. So many people couldn’t see it the other way, and both sides found it hard to believe that the other side was actually being sincere.

Since we have no context, the dress is white and gold objectively.

The actual physical object photographed is black and blue.

White and gold appear when the brain makes the assumption that the dress falls within a shadow (effectively applying a filter that shifts the white balance towards bluer colors and brightness down significantly compared to direct sunlight). Only in real life, the photographed dress did not fall within a shadow, and instead was affected by a yellowish lens flare, so the subconscious color correction that leads a viewer to assume white and gold was erroneously applied.

I see white and gold. But to claim that it’s “objectively” white and gold ignores how the human brain perceives color and ignores that the actual photograph was a blue and black dress.

It sounds like you’re agreeing with me that color perception relies on context, not just the color code of the pixel on the screen.

I found this image to be a really good way to distill the issue down into the two different modes or perception:

https://en.m.wikipedia.org/wiki/The_dress#/media/File:Wikipe-tan_wearing_The_Dress_reduced.svg

I think everyone knew about how human perception subconsciously color corrects a particular image, but this was shocking in that there was genuine disagreement between people who simply couldn’t see it the other way.

When you look at the checker shadow illusion, do you see the pixels as identical in color? If not, then obviously there’s more to human perception than just the color of the pixel code.

The point has never been about the actual pixel color codes. It’s about how human perception doesn’t follow those objective metrics.

Distilled down, we perceive color and brightness in comparison to the surrounding scene. The checker shadow illusion is a clear example of the same color looking different.

So the color perception on the dress depends on how the brain decides to color correct the white balance of the scene.

Phosphates were banned in dishwasher detergents in 2011, so most of the name brand companies switched to enzyme-based cleaners that use amylase and protease, which dissolve starches and proteins, respectively. And then some traditional detergent, which allows oil and water to mix, washes it all away.

The nature of the enzymes are that as soon as they’ve broken up the starch or protein, they survive the reaction and can happily move onto the next starch or protein molecule. So if they’re overactive, without enough targets, then any portion of the dishes that are sensitive to that particular cleaner is going to get a higher “dose” of that cleaner working specifically at it.

If you have 2 apples, and then I give you 2 more, you don’t suddenly have 5 apples because we all decided 2+2=5.

No, but some types of addition follow their own rules.

Sometimes 1+1 is 2. One Apple plus one Apple is two apples.

Sometimes 1+1 is 1. Two true statements joined together in conjunction are true.

Sometimes 1+1 is 0. Two 180° rotations is the same as if you didn’t rotate the thing at all.

If you don’t define what kind of addition you’re talking about, then it’s not precise enough to talk through what is or isn’t true.

I have a model of everything. Everything I am, my understanding of the world, it all fits together like a web. New ideas fit by their relationship to what I already know - maybe I’m missing nodes to fit it in and I can’t accept it

Same, and I would add the clarification that I have a model for when and why people lie, tell the truth, or sincerely make false statements (mistake, having been lied to themselves, changed circumstances, etc.).

So that information comes in through a filter of both the subject matter, the speaker, and my model of the speaker’s own expertise and motivations, and all of those factors mixed together.

So as an example, let’s say my friend tells me that there’s a new Chinese restaurant in town that’s really good. I have to ask myself whether the friend’s taste in Chinese restaurants is reliable (and maybe I build that model based on proxies, like friend’s taste in restaurants in general, and how similar those tastes are with my own). But if it turns out that my friend is actually taking money to promote that restaurant, then the credibility of that recommendation plummets.

For those who are wondering, this is an art installation called “Armoured Pram for Derry” by Eamonn O’Doherty, and appears to be from a 2016 “Making History” exhibition at Ulster Museum.

From what I can gather, it was created in 1991 but restored in 2012 after O’Doherty’s death.

Corporate buzzwords are cargo cult behavior. Jargon and industry-specific terms can be helpful for accurately communicating precise or nuanced ideas, but generic buzzwords are just people who try to sound professional or smart by mimicking the people they’ve seen in those roles.

Just asking “what’s my role in the meeting” is a simple way to get to the point, and isn’t impolite or unprofessional.

When I learned about taxonomy in the 90’s they hadn’t really sequenced many genomes, so taxonomy was still very much phenotype driven, rather than the modern genetic/molecular approaches. I just assumed that everything I learned has become out of date.

Gray sex.

You know, sex between people of Pierce’s age.

Black, brown, then the fucking colors of the rainbow in order, gray, white.

If you need a mnemonic to memorize that, you’re gonna have some trouble actually building out your lookup table in your head of immediately knowing that red=2, yellow=4, etc.

Is there another kind of table?

That’s the possibly apocryphal origin story of Spanish tapas, too: a slice of bread to cover the wine glass between sips (hence the name “tapa,” which means a “cover”), then a few things to dress up that slice of bread, maybe a piece of meat or cheese. So traditionally a single tapa is served for each glass of wine you order.

10 digits gets the diameter of the earth to within an inch.

Put another way, 10 digits means that your error will be caused by your imprecise model of the Earth’s shape, rather than imprecision in the value of pi.

What would be the “n” in that Big O notation, though?

If you’re saying that you want accuracy out to n digits, then there are algorithms with specific complexities for calculating those. But that’s still just an approximation, so those aren’t any better than the real-world implementation method of simply looking up that constant rather than calculating it anew.