Git Diagramming "The Weave"
It could take 20 minutes until we reach the conclusion, at which point he finally explains what the purpose of the final formula is and why we want it.
I got the habit of reading his book in reverse before the lectures; reading section by section in reverse order from the end. This way the mathematical calculations had a clear goal and were faar easier to follow.
... brilliant maths, but he was fully and utterly incompetent at teaching it. And he had a bit of an ego about how many students fail each year because "they're lazy".
Me and a few friends did deep recaps to de-tangle the explanations using his book, rephrasing it in a easier and shorter format; and he accused us of cheating because our scores deviated from the normal distribution.
All this to say; sometimes clever doesn't correlate well to great with words.... though dont take that as a endorsement of trump.
“…at which point he finally explains what the purpose of the final formula is and why we want it.”
I can’t learn this way. Great description of some of my instructors. I gravitate towards design and engineering. Goals are first. This sounds like play: “…and this happened, and this happened…” nope. Not me.
It failed badly. While it's easy to construct sentences that way, it puts immense cognitive load on the receiver. Probably because you don't have any structure in which to put all these terms thrown at you, we reasoned, so we reversed the order to get structure (connectives) first, followed by the terms.
It wasn't better. Turns out, receiving a structure with a bunch of holes to be filled later also results in high cognitive load.
Why? My guess is that the cognitive load mainly comes from the number of unfinished structural connections. To minimize that, you need to transmit a tree in such a way that the terms come as close as possible to the connective. In other words, not bottom or top first, but "side first".
I believe this is why infix notation is so popular. While you parse "A and B" or "X + Y" you never have more than one open connection. When you parse "(+ X Y)" you have two open connections after reading the "+". Five levels deep that begins to matter a lot.
I like the purist lispy idea of operation-first expressions, but I struggle to make my mind actually work like that. If you like clojure-type threading macros, consider that they do something similar to infix notation: they reduce the number of open structural connections during parsing.
I feel it too, it's a higher context language and I agree that it is probably the fact that you are holding onto more unresolved threads at a time. But perhaps that's just because I didn't grow up with it? I would love to find out.
An interesting observation related to this is that on top of the sentence order differences, things are generally spoken about from the largest concept to the smallest which is different to English as well.
So where we would say "I ate lunch at the park today", in Japanese you might say Today, I at the park ate lunch.
In the second sentence it feels like there is a cliffhanger until we get to the end, the smallest details are often the point of a sentence, and so it's like waiting for the punchline. My brain is on hold until we get there, but in English I must admit I can tune out of a sentence early on and usually get the gist anyway.
https://wiki.improvresourcecenter.com/index.php?title=Harold
Trying to search that post.
Edit: in the discussion there was a link to a do a YouTube video where to movie characters were playing word badminton with each other.
Edit: this clip https://youtu.be/swqfFHLck1o
The idea helps when talking with autistic people who might have quite extreme versions of weaving. A conversation between two weavers is kind of an exchange of blunt facts about their world views, which does sound a lot like disparate unrelated tidbits. In contrast to storytellers, who have a discrete path and story to tell, with a start and a finish.
The difference between posting an image url without and with a random string in the url.
Blue line is successful requests (people viewing the image I posted), green are unsuccessful requests (people trying to find other files).
Second blue bump is the screenshot with a randomized „hard“ to guess url. First bump the default iOS screenshot name in the url.
I understand it's made for personal use but if it's posted on the public web at least a disclaimer would've been nice.
For example, it could be truly true that a developer is roughly as good as a 1.5b model. It could really be true, in which case we’re not valuing these models for their true simulation power (yet). Might be the best interview test, you must generate hand written code that’s better than a small model (or show better judgement).
For the presidency, the current benchmark to beat is GPT2 it seems.
Humans can indeed make sense. Not to be too Swiftian, but in some countries, children even go to school for it.
For semantic analysis, however, git is just not the right tool. It's a chronological graph that affords diffs. For code.
We need Python NLP and spacy here. But even the best tooling won't get far. A compiler would abort nonsequential logic and unsatisfied contracts and grammar.
An important business presentation would have structure and facts. Inside the theoretical classroom, a public speech is different from casual, random remarks. Unless the speech is intended for entertainment (e.g. comedy, theatre) or some dark usage, such as propaganda.
From TFA:
the cyclical pattern of his speeches, little snippets of “the best words” and talking points assembled like a ransom note cut from a magazine
That's gold!
Four minutes of the weave was about all I could handle
I wouldn't want to torture the author by force-exposing him more to Trump's inanities. That's already 5x longer than I can stand before the urge to tear my ears off becomes unmanageable.
this actually does seem kind of like a good thing for AI to do
Actually this type of applications should be the killer application of AI.
The extreme analogy is that robot instead of human should explore the nuclear incident of Chernobyl and Fukushima.
Now we're trying to build automated analysis of ECG interpretation using AI. In order to interpret standard 12-lead ECG waveforms signal of 5 minutes for Afib detection that's equivalent of 60 minutes duration. For long duration multi-lead Holter ECG it's at least 24-hour, but I think you get the idea.
You can hire cardiologist that interpret the ECG but you probably need sub-specialist cardiologists specializing in ECG interpretation for the best results but only handful of them exist in the world with ratio of 1:100K or 1:1M for experts:populations, depending on where you're living. These expert cardiologist would rather spent the time doing more meaningful exercises for them like pace maker & IPC surgeries, teaching future cardiologists, and having holidays once in a blue moon.Even they can mistake due to human errors and other limitations. Thus this exercise is tailor made for AI.