mncharity

Oops - that's not transclusion. Merely literate programming tangles.

"ランデン先生Time" -> "Professor Landen Time"

> how powerful and unique this situation is [...] cannot be easily replicated

I've long wished for an HN-like community which combined software folks, sci ed researchers and creators, and teachers - to get tighter loops around "What do you think? / Could you try this?". But it still wouldn't be the power of playtesting.

I wonder how one might offer playtesting as a service?

> I want to target people of all ages and backgrounds

This opens up opportunities for guerrilla usability testing with adults. Though I've little idea what forms of it might fit culturally in Japan. In Cambridge MA, I could easily do street conversation testing.

Which still leaves ethical issues. One participant was distressed, "Disgusting!", and I only figured it out later... a (Powers of Ten zoomed) E. coli micrograph can look like poop.

> The importance of playtesting cannot be understated.

s//overstated/. Very yes. I've been gobsmacked by things which turned up in user testing. Example: a scene opens with a cartoon character reading a sign aloud... and the cognitive load spike (new setting + audio + text) disappears the entire event from memory. Literally: pause for feedback, "You should say what this is up front", hit replay, "Oh yes, this version is much better than the first one".

Brainstorming, perhaps `<<named-block-code-transclusion>>`? It goes against the grain of "eval() line-by-line", even if it's handled ASAP. But it might relax the order constraint on codegen. Especially if the UI gets complex, or rendered on a "pane off to the side".

Here's[1] the rest of the prompt which begins the video.

[1] https://github.com/FabianKuebler/fenced/blob/main/packages/l...

> I would love to see e.g. a butterfly image with a slider that I could drag to choose the wavelength shown!!

Here[1] are some 31-band hyperspectral images of butterflies. Numpy/pillow can unpack the .mat files into normal images. Then perhaps vibecode a slider, or just browse the band images?

[1] http://www.ok.sc.e.titech.ac.jp/res/MSI/MSIdata31.html (includes 8 butterfly 31-band hyperspectral visible-light images). These butterflies are also in their VIS-SNIR dataset, and others.

I knew of the site having explored "First-tier physical-sciences graduate students are often deeply confused about color. Color is commonly taught, starting in K... very very poorly. So can we create K-3 interactive content centered around spectra, and give an actionable understanding of color?"

I like distinguishing "light" (physical world) from "color" (species-specific biology). Sunbeam blue light is already less intense than NIR-I, but human bio juices the blue. Most humans are bright-light trichromats and low-light monochromats. Rod sensitivity is 3 orders of magnitude up, with single-ish photon sensitivity. Some amphibians have an extra rod type, for low-light bichromaticity. Some deep-sea fish are bright mono and dark lotschromats (12+ rod opsins). So why not imagine seeing the world with a triple (or more) of short-wavelength super-rods, a few orders of magnitude more sensitive still, with whatever curves seem fun? Perhaps curves naturally selected for by "makes intriguing images of the world for social media"...

The canonical Q/A pair "Why does the Sun shine?"/"Fusion in its core" perhaps contributes confusion here? Where the question is silently swapped out for "Why is the Sun still shining after 4+ Gyr?". You're primed for a close connection between core and surface photons. Asking "Why is there fog over the uncovered corner of the pool?", one seems unlikely to appreciate "the fog comes from a small aquarium heater somewhere on the bottom!" (IIRC the magnitudes). "The Sun is hot, and hot things glow" creates less of that association between core and light.

> You could calculate how long it would take to notice anything if the core suddenly stopped fusing.

FW(little)IW (very not my field, just AI, quick&sloppy), for a Sun magically switched to contraction-dominated heating, I'm sloping order 10^6-7 yr for a 1% increase in surface temp, with core contraction dynamics being just one uncertainty.

> nowadays Google AI Overview's accuracy is so good

I felt similarly yesterday. This morning AIMode fabricated for me a diverse science education publishing and research effort around using generative AI to teach rough-quantitative reasoning. My face-nibbling canary was a linked cite to a book "Orders of Magnitude"... a sci-fi horror novella about space marines. Would be nice if the outlined work actually existed. There we some nice ideas. I look forward to it. The education stuff, not the space marines.

>> I really wish they'd cite the original Japanese.

Given the Japanese above, translate.google can do text to speech[1], and goog AIMode[3] and bing/chat[2][4] can give multiple translations with notes.

But finding that Japanese, given only the TFA's description? I only saw AIMode manage that, not vanilla search. Perhaps using the author's Japanese wikipedia page[5], or perhaps here, or?

[1] https://translate.google.com/?sl=auto&tl=en&text=%E3%81%8A%E... [2] https://copilot.microsoft.com/shares/JcJSRgDDvT84M16x7RJDb [3] https://share.google/aimode/FNEXZGRPFPANlvNwd [4] https://copilot.microsoft.com/shares/wjaWnGHNpGs18X4M6CJV6 [5] https://ja.wikipedia.org/wiki/%E8%99%9A%E7%99%BD

> On the wiki, I have decided to expand Section 2(d), "AI tools used to rewrite an existing argument" to also include cases such as the one here, in which the AI tool indirectly caused the argument to be rewritten in a substantive way (beyond mere typos etc.) by identifying a non-trivial mathematical issue in the previous version of the text, which was then fixed by a human author.

Fwiw, wiki Section 2(d): https://github.com/teorth/erdosproblems/wiki/AI-contribution...

Hmm... TikTok has apparently long had "text enhanced with background" genres, and TIL, text posts since 2023. So text is ok. But non-independent items? For generative storytelling, "here is a next paragraph for the story", swipe left/right might work? Want to avoid "I don't much like this new paragraph, but I'm afraid to lose it and be stuck with something worse". Swipe left/right and up for continue? Swipe down to revisit old choices? Maybe present new text bolded, appended to old text, for context. Or a "next page of a picture book" idiom. A text field for direct creative or editorial intervention - speech to text. Maybe a side channel input for "story and background should now be soporific". Generative bedtime stories, but incrementally collaboratively created... Thanks for the brainstorming prompt.

Yes. Not quite a decade before JSON and YAML, what's at hand for a human-readable interchange format for nested data? SGML (no XML yet), something FORTH-ish, make up your own thing, and...? Contemporary WAIS (search as a distinct non-HTTP protocol) shrugged off human-readable, and tried nightmarish binary ASN.1.

Yesterday IMG tag history came up, prompting a memory lane wander. Reminding me that in 1992-ish, pre `www.foo` convention, I'd create DNS pairs, foo-www and foo-http. One for humans, and one to sling sexps.

I remember seeing the CGI (serve url from a script) proposal posted, and thinking it was so bad (eg url 256-ish character limit) that no one would use it, so I didn't need to worry about it. Oops. "Oh, here's a spec. Don't see another one. We'll implement the spec." says everyone. And "no one is serving long urls, so our browser needn't support them". So no big query urls during that flexible early period where practices were gelling. Regret.

There's an old idea of adaptive media. Imagine a video drama that's composed of a graph of clips, like an old "choose your own adventure" book ("Do you X? If yes, goto page 45"). With gaze tracking, one can "hmm, the viewer is more focused on character A than B... so we'll give clips and subplots with more A".

Now, when reading, the eye moves in little jumps - saccades. They last 10's of ms, the eye is blind during them, and with high-quality tracking, you know quite early just where that foveal peephole is going to land. So handwave a budget of a few ms for trajectory analysis, a few for 200 Hz rendering latency, and you still have 10-ish ms to play with. At 20k tok/s, that's 200 tok.

So perhaps one might JIT the next sentence, or the topic of the next paragraph, or the entire nature of the document, based on the user's attention. Imagine a universal document - you start reading, and you find the document is about, whatever you wanted it to be about?

But I'm glad for the ground-truthy approach taken. I suggest a pattern, of interesting data being unavailable, because it doesn't align with incentives around science or commerce. Often it exists, just sitting on someone's disk, because they think no one is likely to care.

> The right approach would have been to select a color appearance model (CIECAM02 is the standard), convert all our colors to this coordinate system, do the mixing in this coordinate system and then convert back to RGB. That being said, I did not want to deal with all the extra complexity that would have come along with this. Instead, I opted for a much simpler approach.

Python's nice `colour` package supports several color appearance models.[1]

[1] https://colour.readthedocs.io/en/master/colour.appearance.ht...

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]

> In his later years, Tinney grew philosophical about the future of illustration as a profession, noting that stock image databases had changed the economics of the field. But he remained upbeat about the value of artistic talent, comparing it in that 2006 interview to the skill of public speaking: “It’s a nice talent to have, but it isn’t easy to find someone who’ll pay you just to do it. You need to combine that basic talent with another skill to really have a marketable service.”

Perhaps something to ponder as AI stirs up what constitutes a marketable service.

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...

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 might for example, now more easily author an intro astronomy textbook, one that doesn't reinforce top-30 common misconceptions, something the most used (US; commercial) texts still don't manage.

Imagine a chromaticity diagram, but on a perceptual color space where long-range euclidean distance at least attempts to describe the magnitude of perceived difference (rather than the usual model artifacts) - so round-ish. Then decreasing perceived difference between red and green shows up as a smush to oval.

Does that confuse sales staff when shopping for clothes? ... :) The general observation being that sometimes educational descriptions of things get hedges which wouldn't usually be applied in everyday life. Yes, the nice red shirt will look black under some lighting, like some meters underwater... but it usually isn't mentioned. Yet for example, colors of unfamiliar objects in education content can get an "appears" hedge -"it appears white", rather than the more usual, simpler concept of "if its light looks white, it's 'white'".

"To whom have I given blue from my sunbeam?!?" might be another fun question. I explored it as a potential interactive, to see, geographically, where your direct sunlight is donating sky blue-ification. Especially around sunset - IIRC, think a 100 km neon tube, at 7ish km altitude, near-end 150 km up range, with a 15-ish km wide ground footprint with 3/4-ish of the ground-impinging light, and the rest of a 100 km wide path with the 1/4-ish.

Perhaps "transparent with a blue tint"?

As confusion elsewhere on this page illustrates, one also needs to clarify absorption. "It's just blue" sky and "it's just blue" stained-glass have quite different behavior. Both side scatter some blue, but while one mostly transmits the rest, the other mostly absorbs the rest, for very different experiences peering through it.

So perhaps "clear with a blue tint"?

IIUC, saturation is a (not uncommon) distractor here. As you get the same observation when desaturated by a neutral filter. Even on the "ground" with low air mass (Sun vertical, at altitude, etc).

Does anyone have experience of early-childhood "Why?"-phase meets speech-enabled LLMs?

Startup wise, there's old work on conversational agents for toddlers, language acquisition, etc. But pre‑literate developmental pedagogy, patient, adaptive, endlessly repetitive, responsive, fun... seems a potential fit for LLMs, and not much explored? Explain It Like I'm 2-4. Hmm, there's a 3-12 "Curio" Grok plushie.

I saw a Microsoft talk decades back, that was a dispirited "the people of India could be buying educational materials and... but no, all the money is in ringtones". For some kinds of business perspective, ok I guess. But for others, and for civilizational change, what's going on in the tail can matter a lot. Does China become a US engineering/science peer in early 21st C absent an internet/WWW?

I puttered on a color interactive where, to emphasize this distinction between world-spectra vs brain-color, you could swap in color deficiencies, a non-primate mammal ( dichromats), and a monochromat.