> I ended up with like 2 or 3 out of 10 complete proofs and the rest half finished on the final exam because I had the right starting points, but not enough practice using what I knew in unexpected ways.
I feel ya. I memorised definitions for my algorithms course as well and also experienced diminishing rewards of using SRS flashcards (especially when the conceptual questions get more novel).
Like what you say, we have to practice using the factual knowledge enough by writing proofs.
The next generation of flashcards would probably use AI to generate concise questions on writing proofs.
> From this perspective, fields that require deep understanding, like math, require memory just as fields with a breadth of shallow knowledge do, though in different ways.
I'm interested in understanding how others use Anki for conceptual subjects like pure math or physics. I believe many fundamental rules in Spaced Repetition (e.g. like keeping cards concise) are thrown out the window for conceptual subjects.
In short, P means Polynomial time (i.e. markets can solve computation problems efficiently) and NP means Non-Deterministic Polynomial time (i.e. markets can verify solutions of computation problems efficiently but solutions are found by luck).
If P != NP, it means luck CANNOT be engineered and markets are competitive.
> ... Costco has a variety of "bad governance" provisions, such as a super-majority (of all shares, not just votes) provision threshold for shareholder votes
Do you believe there's a fundamental tradeoff between structural constraints (i.e. the 'democratic' model, where dispersed shareholders and markets have a voice) vs. insulated leadership (i.e. the 'benevolent dictator' model, where competent leaders are shielded from short-term shareholder pressure)?
> “These bears have become synonymous with gentrification in San Francisco,” he told fnnch, “and the displacement of the artists that come from here.”
I have mixed feelings (i.e. I understand your boredom) of his honeybear art from a pure aesthetic pov. However, (as any modern viral influencer knows), any successful artist will invite haters. This article reinforces the notion that fnnch is very successful...
I concur with you (that this is an excellent introduction)!
Imo, your suggestions are more for intermediate/advanced active listeners that need to interact with folks in their job (e.g. bartenders, reporters, middle managers...).
Still, I feel being repetitive (e.g. 'It sounds like XYZ...is that right?') is better than nothing. Sometimes, training wheels aren't bad when learning how to ride a bike.
I think the problem statement is: How do you know when to Let Go of the current boulder?
The poem suggested many many many possible when. Here's one: "unless it comes out of / your soul like a rocket,".
Unfortunately (or fortunately), in life, there is no methodology to prove that a given search problem is futile (e.g. NP-complete)... so we have to take our chances and choose. I believe that's the beauty of life: choice.
This is correct. To delve into a topic about cognitive load without talking about germane overhead disqualifies this article (i.e. similar to extraneous overhead in terms of effort but germane overhead is beneficial. Because it helps the coder's reading ability.)
The examples are good but every reader must not have the takeaway that every effortful code is bad (e.g. haskell is extremely hard to read at first but every developer swears it has very high intrinsic cognitive load)
I feel ya. I memorised definitions for my algorithms course as well and also experienced diminishing rewards of using SRS flashcards (especially when the conceptual questions get more novel).
Like what you say, we have to practice using the factual knowledge enough by writing proofs.
The next generation of flashcards would probably use AI to generate concise questions on writing proofs.
[1] A Little Randomness May Not Be Enough - https://www.scotthyoung.com/blog/2014/11/07/srs-for-concepts...
Thank you for sharing your experiences!