> I've been trying to square the physics and my experience.
> Pedal B flat is the fundamental, low B flat is the 2x, F 3x, mid B flat the 4x, D the 5X, high F is 6X, G half sharp is 7X and high B flat is 8X.
I've always been amused at how many sources state the "tube with one end open" model, derive the "odd harmonics only" behavior from the model, and then never engage with the observable behavior of the instrument or reconcile it with the model.
I did find this when trying to understand that disparity, but I don't know enough to confirm/refute/amend the explanation:
I took that to mean ≈ "Amount of training data isn't the big factor dwarfing all else." Depends who "we" refers to, I guess. Back when LLM-generated code was new, I definitely saw predictions that LLMs would struggle with niche or rarely used languages. These days, consensus among colleagues within earshot is that LLMs handle Rust much better than Python or C++ (corpus size and AutoCodeBench scores notwithstanding).
And yet a lot of speakers still seem to need that self-evidently true statement pointed out to them. Tautological advice isn't necessarily bad or useless, especially for beginners.
> Ever try or even see a "Leet-Code" style question that stated the problem without providing example results?
This style of question asks the examinee to devise a procedure for producing those results, not to come up with the individual results themselves. If a student is given a bunch of systems of linear equations to solve, an answer key isn't especially useful since checking a candidate solution is pretty straightforward.
Apple did not need to be controlled by a majority shareholder in order to follow an ambitious, cohesive vision.
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