Why settle on cammel case (“saveGame”) or upper cammel case (“SaveGame”) when you can have one of each?

Yeah the way I got out was a bit cryptic, although I think there are multiple ways. I’m shameless enough to use a walkthrough when I’ve been stuck for a while, otherwise I’d be having an even harder time.

It can be hard to bootstrap yourself up from zero followers. I’d recommend posting something just so that people have an idea of the kind of thing they can expect if they follow you from checking out your profile. But you probably won’t get much engagement from your own posts at first, so it will probably be more fun to just reply to other accounts.

Bluesky has a feature where you can set up customized feeds to filter for any kind of content you want. The person who saw your post might have seen it in the “newskies” feed which just contains every first post that any account makes for example. So one way to get engagement can be to write posts that show up in a certain feed that people follow, like there exist some feeds that are based around certain topics that usually trigger based on your post containing certain keywords. Most people just use the following feed though, I think.

Planescape: Torment

I haven’t played a lot infinity engine games and I’ve struggled with understanding what the game expects of me in terms of gameplay. Hopefully I’ll internalize that eventually but I’ve been enjoying the writing and vibes so far even if the gameplay feel a bit frustrating and a bit like a chore at the moment.

I’m developing a system that causes people to give me VC funding because it sounds cool

Twitter has historically been used as a platform by a lot of different fandoms and the network effect is strong enough that they haven’t managed to leave en masse until now

As long as you have your windows license key you can change your mind later so really you can do whatever. I’d recommend giving 100% linux a try if that seems fun. Obviously you’re gonna want to back up any interesting files that you have on windows either way.

Ah ok just read the article and not the proposal. I’m surprised that they went that far but as I wrote I think that lifetime annotations are a good idea, hope the C++ people find a way to add them to the language that actually works well, which sounds like an incredibly difficult task.

I’m a bit skeptical that a borrow checker in C++ can be as powerful as in rust, since C++ doesn’t have lifetime annotations. Without lifetime annotations, you have to do a whole program analysis to get the equivalent checks which isn’t even possible if you’re e.g. loading dynamic libraries, and prohibitively slow otherwise. Without that you can only really do local analysis which is of course good but not that powerful.

Lifetime annotations in the type system is the right call, since it allows library authors to impose invariants related to ownership on their consumers. I doubt C++ will add it to their typesystem though.

Vim sort of already has this feature via set foldmethod=syntax. This doesn’t work exactly like the author suggests but you can also use set foldmethod=expr and then set foldexpr to a more complicated expression to only get nested function/method bodies, via tree sitter for example if you’re on neovim.

My favorite example of haskell arcane wizardry is löb. It’s mentioned in this list but not really done justice imo.

To add on this, this doesn’t necessarily mean that there are fewer programing jobs in total. If people work 10% more efficently, that means that the cost of labor is only 91% of what it was before meaning that people might be able to afford to finance more programing projects. One thing that does matter is for example things like entry level jobs disappearing or the nature of the work changing. Doing less boring gruntwork can make the job more fun, but otoh digitization sometimes results in the worker having less agency in what they do since they have to fit everything into a possibly inflexible digital system.

No, the podcast can absolutely missrepresent the thing that it’s sumarizing. The podcast also adds commentary, and I think it’s especially this commentary that I find unreliable.

I’m using “OOP” more in the sense that is described in the article, but that is a fair perspective on rust and OOP. It is a term with a lot of different interpretations after all.

Curious to hear what in Rust could be more easily solved with OOP! I think one reason for rust not using OOP is because they want to minimize dynamic dispatch and keep it explicit where it happens, because it’s a language that gives you very fine grained control of resource usage, kinda similar to how you have to be explicit about copying for most types. Most trait calls are static dispatch unless you have a Box::<dyn SomeTrait>

I think that it is impressive, but not necessarily that useful? In particular, you can’t really trust what they’re saying to be accurate so it doesn’t actually give you that much usable information.

Very cool, but I’m not sure what I would actually use it for.

Yeah thought that might be the case! It’s just a thing that a lot of people have misconceptions about so it’s something that I have a bit of a knee jerk reaction to.

There are a couple of reasons that might not work:

• Maybe we’ll asymptotically approach a point that is lower than human-level cognitive capabilities
• Gradual improvements are susceptible to getting stuck in a local maxima. This is a problem in evolution as well. A lot of animals could in theory evolve, say, human level intelligence in principle, but to reach that point they’d have to go through a bunch of intermediate steps that lead to worse fitness. Gradual scientific improvements are a bit like evolution in this way.
• We also lose knowledge over time. Something as dramatic as a nuclear war would significantly set back the progress in developing AGI, but something less dramatic might also lead to us forgetting things that we’ve already learned.

To be clear, most of the arguments I’m making aren’t really about AGI specifically but about humanities capability to develop arbitrary in principle feasible technologies in general.

Another possibility is that humans just aren’t smart enough to figure out AGI. While I’m sure that we will continue incrementally improving technology in some form, it’s not at all self-evident that these improvements will eventually add up to AGI.

A breakthrough in quantum computing wouldn’t necessarily help. QC isn’t faster than classical computing in the general case, it just happens to be for a few specific algorithms (e.g. factoring numbers). It’s not impossible that a QC breakthrough might speed up training AI models (although to my knowledge we don’t have any reason to believe that it would) and maybe that’s what you’re referring to, but there’s a widespread misconception that Quantum computers are essentially non-deterministic turing machines that “evaluate all possible states at the same time” which isn’t the case.