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Cake day: June 11th, 2023

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  • The one case where I prefer video is when I know next to nothing about the topic and the other choice is mediocre to low-quality writing. Most people aren’t great technical writers, and it’s easy to skip over steps either because the writer assumes too much prior knowledge or simply because it takes effort to put that information in. On the other hand, videos are the opposite where it takes effort to cut stuff out, so you usually get all the steps which is what I need when I don’t know anything.

    If I have the option of a well-written, step-by-step tutorial though, or if I already know the topic and have a vague idea of what I’m looking for, then text is much better for being able to search/skim/go back and forth at my own pace.



  • The behavior is defined; the behavior is whatever the processor does when you read memory from address 0.

    If that were true, there would be no problem. Unfortunately, what actually happens is that compilers use the undefined behavior as an excuse to mangle your program far beyond what mere variation in processor behavior could cause, in the name of optimization. In the kernel bug, the issue wasn’t that the null pointer dereference was undefined per se, the real issue was that the subsequent null check got optimized out because of the previous undefined behavior.





  • I’m not sure this blog post makes the right comparison. Based on my admittedly limited experience, OCaml modules seem more comparable to Java classes than packages. They’re both bundles of functions and data, except the module contains data types instead of being the data type itself. Classes have basically all the features of strong modules like separate compilation, signatures (interfaces), functors (generics), namespacing, access control. These examples of OCaml modules are all things that would be implemented as a class in Java.

    From this perspective, rather than Java lacking strong modules, it actually has them in the form of classes. It’s OCaml which lacks (or doesn’t need) an additional package system on top of its modules.


  • My main point is that PRQL makes no distinction. If you didn’t inspect that SQL output and already know about the difference between WHERE and HAVING, you would have no idea, because in PRQL they’re both just “filter”.

    Hmm, I have to disagree here. PRQL has no distinction in keyword, but it does have a distinction in where the filter goes relative to the aggregation. Given that the literal distinction being made is whether the filter happens before or after the aggregation, PRQL’s position-based distinction seems a lot clearer than SQL’s keyword-based distinction. Instead seeing two different keywords, remembering that one happens before the aggregation and the other after, then deducing the performance impacts from that, you just immediately see that one comes before the aggregation and the other after then deduce the performance impacts.

    As far as removing arbitrary SQL features, I agree that that is it’s main advantage. However, I think either the developers or else the users of PRQL will discover that far fewer of SQL’s complexities are arbitrary than you might first assume.

    That’s fair, I was just thinking of things that frustrate me with SQL, but I admittedly haven’t thought too hard about why things are that way.


  • What are the implications of WHERE vs HAVING? I thought the only primary difference was that one happens before the aggregation and the other happens after, and all the other implications stem from that fact. PRQL’s simplification, rather than obscuring, seems like a more clear and reasonable way to express that distinction.

    I don’t know if PRQL supports all SQL features, but I think it could while being less complex than SQL by removing arbitrary SQL complications like different keywords for WHERE vs HAVING, only being able to use column aliases in certain places, needing to recompute a transformation to use it in multiple clauses, not forcing queries to be in SELECT… FROM… WHERE… order, etc.



  • Agreed, smartness is about what it can do, not how it works. As an analogy, if a chess bot could explore the entire game tree hundreds of moves ahead, it would be pretty damn smart (easily the best in the world, probably strong enough to solve chess) despite just being dumb minmax plus absurd amounts of computing power.

    The fact that ChatGPT works by predicting the most likely next word isn’t relevant to its smartness except as far as its mechanism limits its outputs. And predicting the most likely next word has proven far less limiting than I expected, so even though I can think of lots of reasons why it will never scale to true intelligence, how could I be confident that those are real limits and not just me being mistaken yet again?