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Why is the sky blue?

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Re: Why is the sky blue?

#272

In The Cuckoo's Egg Cliff Stoll recounts an episode from the oral defense of his astrophysics PhD thesis. A bunch of people ask questions but one prof holds back until... """ “I’ve got just one question, Cliff,” he says, carving his way through the Eberhard-Faber. “Why is the sky blue?” My mind is absolutely, profoundly blank. I have no idea. I look out the window at the sky with the primitive, uncomprehending wonder…

A great story, though it seems a little odd to me since Rayleigh scattering was covered in my undergrad exoplanets course. I'd expect an astrophysics PhD to have a better first answer than "scattered sunlight".

Re: Why is the sky blue?

#273

Earlier quoted context omitted.

Ah, perhaps I should have said something like "educational materials, and apps, and other useful things" (disapproving judgement in the original). > Well, the thing is that the educational materials are largely free. A triumph and fruition of these last decades of massive effort. Now we just need to deal with their quality (with commercial as bad as free). AI may help, by reducing barriers to content creation - you m…

I’m pretty curious. What are those too 30 misconceptions in US commercial astronomy texts? Is there a list somewhere? Or can you name some?

Sigh. One impact of AI will hopefully be more readily available systemic survey papers. [1] might-or-not be a good place to start... but it's paywalled (by the National Science Teacher Association no less), and I don't quickly see preprints/scihub/etc. Here's an old unordered list for browsing[2], and a more recent one[3]. Trumper did a series of papers asking the same few questions of various populations, to give a feel for numbers - like half not knowing day-night cause. Most lists are on subsets of astronomy, and most info on frequency on short lists. So... it's a mess. As are textbook reviews. Key phrases are "astronomy education research" and "misconceptions".

The one bit I explored was 'what color is the Sun (the ball)'. Asking first-tier astronomy graduate students became a hobby, as most get it wrong (except... for those who had taken a graduate seminar covering common misconceptions in astronomy education). So I libgen'ed the 10-ish most used intro astronomy textbooks in US according to some list. IIRC, it broke down roughly into thirds of: correct (white); didn't explicitly say but given surrounding photos, or "yellow" (as classification without clarification), there's no way students won't be misled; and explicitly incorrect (yellow). Hmm, bulk evaluation of textbooks against some criteria is another thing multi-modal models could help with.

(A musing aside re AI for systemic reviews. Creating one is a structured process. They have been very manpower intensive, so they aren't refreshed as often as is desired, nor consistently available. And at least in medicine ("X should be done in condition Y"), there's a potential for impact. I imagine close reads of papers isn't quite there yet. But maybe a human-AI hybrid process?)

[1] https://www.per-central.org/items/detail.cfm?ID=14009 [2] https://web.archive.org/web/20070209033543/http://www.physic... [3] appendix A of https://digitalcommons.library.umaine.edu/etd/2200/ [4] https://www.oranim.ac.il/sites/heb/SiteCollectionImages/pers...

Re: Why is the sky blue?

#274

Earlier quoted context omitted.

Now do clam steamers and shrimp fried rice.

I'm familiar with "steamer clams", but not "clam steamers". In "shrimp fried rice", "shrimp" is a noun adjunct [1], which is when you use a noun as an adjective. The charming ambiguity comes from it being unclear whether "shrimp" is an adjunct noun modifying "fried rice" ("shrimp fried-rice") or modifying the past participle verb "fried" ("shrimp-fried rice"). [1] https://en.wikipedia.org/wiki/Noun_adjunct [2] https:…

Yeah, they're usually just called "steamers". I put clam in front of them to disambiguate. But it's always bugged me. They're not steaming anything! They're getting steamed.

Re: Why is the sky blue?

#275

Earlier quoted context omitted.

We already have mutations, generally in women, for tetrachromaticism, who usually have male relatives with severe or moderate color blindness, in which the X chromosome encodes a different green cone. So they end up seeing red, strange-green, green, and blue, where strange-green is somewhere closer to red than green. Only a few on record but they tend to have absolutely insane color matching and color perception. One…

I have that already ;) it actually looks like muddy puke green than green. However, green stop lights look more “white” than green. Some reds look like brown. I hate reds. I’m not sure about the Pantone-like color matching but I definitely see different colors than most people. To the point where my flight license is restricted. Dichromatic but not trichromatic.

Not sure if you'll see this but you should check color perception with any female relatives, they're much more likely than average to be tetrachromats!

Re: Why is the sky blue?

#276

In The Cuckoo's Egg Cliff Stoll recounts an episode from the oral defense of his astrophysics PhD thesis. A bunch of people ask questions but one prof holds back until... """ “I’ve got just one question, Cliff,” he says, carving his way through the Eberhard-Faber. “Why is the sky blue?” My mind is absolutely, profoundly blank. I have no idea. I look out the window at the sky with the primitive, uncomprehending wonder…

I am positively excited about the upcoming first generation of humans who will have all their questions answered, correctly and in the way they can best understand, and as often and many of them as they want – and what that is going to enable.

> who will have all their questions answered, correctly and in the way they can best understand

Highly unlikely as the feedback cycle used to train LLMs will choke off all future learning.

In other words if AI bots consume and regurgitate everything you publish on the internet what is the incentive to publish anything? No one will read it except the bots. The training datasets will either become stale (no longer learning anything new because nothing new and useful is published) or actively poisoned (because only bad actors will bother to publish).

And the generation constantly fed mostly correct information by AI will implicitly trust it further making poisoning of the models a high-value target.

Very few people will be left who understand how to think and have the motivation to do so. Even fewer will have the motivation and the means to publish to others.

Re: Why is the sky blue?

#277

Earlier quoted context omitted.

> s sending you more blue light than the background level. The background level is black! No air, no scattering. d > A cloud that isn't between you and the sun is getting its light from the sky background, which is blue. Why is the cloud not blue? The cloud is bathed in intense, direct sunlight which is slightly yellow, and it is exposed to a small amount of scattered blue light. It could be that this mixture whitens…

> The background level is black! By "the background level", what I mean is the emission spectrum of the sun. (And by "more blue", I mean in a relative sense, not an absolute sense.)

[deleted]

Re: Why is the sky blue?

#278

Earlier quoted context omitted.

I’m pretty curious. What are those too 30 misconceptions in US commercial astronomy texts? Is there a list somewhere? Or can you name some?

Sigh. One impact of AI will hopefully be more readily available systemic survey papers. [1] might-or-not be a good place to start... but it's paywalled (by the National Science Teacher Association no less), and I don't quickly see preprints/scihub/etc. Here's an old unordered list for browsing[2], and a more recent one[3]. Trumper did a series of papers asking the same few questions of various populations, to give a…

s/systemic/systematic/g - oops.

> Systematic reviews are rigorous, transparent, and reproducible research studies that synthesize all existing evidence on a specific topic to answer a focused question and minimize bias. Unlike narrative reviews, they use predefined eligibility criteria, comprehensive searching, and critical appraisal to evaluate primary literature, often employing meta-analysis for quantitative results. [goog ai overview, edited]

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