Back in those times we made a distinction between nerds and geeks, with geeks really being a sort of subset of nerds that was just interested in the technicals.
I apologize. I didn't mean to suggest it is a super power, and it has also been a struggle in my life. I find it useful to frame this way because the struggle is not only because of the way that I am, but also because of the way everyone else is. I'm not asking anyone to change on my behalf, but it took me a long time to accept myself as I am. It took me a long time to accept that I didn't need to change for the benefit of everyone else.
For me, one of the big improvements is the ability to legitimately work via text message. That probably sounds dystopian in a bunch of ways to some people. But there are times that I want to work, but couldn't, previously.
Now I can work from wherever, whenever, by speaking into my headphones, and have it persist. Sure, I want to be in front of a screen to do final syntax review, but I don't mind planning out architecture and guiding an LLM towards a cohesive result while going for a walk or jog. That's just not a workflow that would have been viable 3 years ago.
I always thought of myself as merely ADD, but your comment is so incredibly relatable across all dimensions that I find myself wondering how far along the autism spectrum I am. Although, in my personal opinion, neither term is especially helpful: it's not a sensory/executive processing disorder if it's clearly benefiting both yourself and the people around you. It might make being sociable difficult, but that's the tradeoff for being willing to engage your mind in ways that others filter out as "too much information."
They are building them because they can ask an AI to spin it up. They could have asked it to spin up the public API just as easily. The MCP choice is a fashion choice vs an openapi spec with similar documentation (or any number of other human+machine readable tooling). It might accidentally win or accidentally lose just because of the timing / network effects.
Right; isn't this already captured by an openapi spec with RBACs? Plus the benefit that your ai agent can keep using all the pre-AI tools that already interface with those specs. What is MCP bringing that an openapi spec doesn't?
Caveat emptor, I'm not a Haskeller, just an admirer. But Haskell let's you run functions over the type system itself very elegantly, so you can have a type that is derived from a type that composes three types that are derived from several functions' declared runtime behavior. This kind of type inference can provide arbitrarily rich information about anything in the entire program, letting you encode more than just range-types etc at compile time.
This comes with some design drawbacks. I think Rust's borrow checker would be implementable but unreasonable in Haskell: Haskell already does lazy-evaluation on types to enable its arbitrary depth of type expressivity. But the borrow checker also wouldn't really make sense for Haskell because the default programming model uses a GC. I think Linear Haskell might be a kind of Rust-in-Haskell, though.
Depends. Within the US, there are data export laws that could make the "whoever" part illegal. There are also conspiracy to commit a crime laws that could imply liability. There are also laws that could make performing/demonstrating certain exploits illegal, even if divulging it isn't. That could result in some legal gray area. IANAL but have worked in this domain. Obviously different jurisdictions may handle such issues differently from one another.
What do you recommend if I've been regularly producing blog-length posts in Slack for years, no LLM present? It's where I write man...should I quit that out? I try to be information dense...
To me, you are describing a fluency problem. I don't know you or how fluent you are in code, but what you have described is the case where I have no problem with LLMs: translating from a native language to some other language.
If you are using LLMs to precisely translate a set of requirements into code, I don't really see a problem with that. If you are using LLMs to generate code that "does something" and you don't really understand what you were asking for nor how to evaluate whether the code produced matched what you wanted, then I have a very big problem with that for the same reasons you outline around prose: did you actually mean to say what you eventually said?
Of course something will get lost in any translation, but that's also true of translating your intent from brain to language in the first place, so I think affordances can be made.
Totally agree on js, but it doesn't have the same easy same-language comparison that you get from compiled Lua vs LuaJIT. Although I suppose you could pre-compile JavaScript to a binary with eg QuickJS but I don't think this is as apples-to-apples comparison as compiled Lua to LuaJIT.
I think it's worth remembering that this was a storage procedure that was also already abnormal/odd because of the specifics of the existing shielding. I think it's somewhat understandable for a technician to trust that the chemists know what they're doing in that kind of circumstance. If they had concerns, they may have even voiced them, but as is often the case, if the authority confirms that even though it's strange it's correct, it's not surprising that a technician would follow the directive. Even the authority figure may have verbally confirmed, "you said an organic absorbent??" "Yes, that's right, inorganic absorbent." Maybe even in a meeting that was meant to clarify written procedures.
Compiled Lua vs LuaJIT is a major example imho, but maybe it's not especially pertinent given the looseness of the Lua language. I do think it demonstrates that the concept that it is possible to have a tighter type-system at runtime than at compile time (that can in turn result in real performant benefits) is a sound concept, however.
I simply choose to believe that people do this out of a place of genuine curiosity / excitement to share knowledge. I believe this approach of assuming the best of intentions is even in the HN guidelines! Or maybe it was just the old Reddit ones from long long ago when Reddit was more like what HN is now. Either way, maintaining the background assumption, even when it is challenging to do so, makes HN a far more pleasant place to inhabit.
In the broadest sense of the word, aliasing refers to a problem where an insufficient number of samples create a misrepresentation of an intended signal source. I was being a bit poetic, because in graphics programming, where the term "antialiasing" is most often encountered by lay audiences, antialiasing generally refers to X/Y sampling coordinate correction rather than representations across time. It's not usually considered a major issue in vision, because our brains naturally fill in the gaps pretty easily across time for motion (they already naturally do this for eg blinking, you don't see your eyelids when you blink). So usually antialiasing across time is only an issue in audio domains for the layperson, where a misrepresentation of a sample might be perceived as an entirely different pitch, since our ears need >40k samples per second (for accurate high pitches) vs the 24 samples per second that we are accustomed to getting in old fashioned film. When our eyes "miss" a frame or two, our brain is happy to fill in the gaps, ie "antialiasing."
Edit: to clarify, I'm suggesting that some people might prefer to let their brains "fill in the missing frames" rather than see the extra frames shown explicitly. For example, you might be more likely to notice visual tearing at 60Hz than you are to take note of visual tearing at 24Hz when you're already accustomed to filling in the missing pieces, or to a greater extreme, across two panels of a comic strip portraying motion.