anyonecancode

> If airports were just shacks next to a runway, they’d be much cheaper to run.

Flew Ryan air once to, I think it was some airport nearish to Venice, Italy. And it was pretty much a shack next to the runway. Walk down the steps off the plane into a small building, notice a conveyor belt. Walk through the next door, pick your luggage off the same conveyor belt. Walk through the next door, you're at the bus stop.

What about "simulated intelligence"?

I like having a clear definition like basing it on continental plates, though a map of the plates seems to raise its own set of questions. How small is too small of a plate to count? What of parts of what we call continents that are actually on a different plate?

https://upload.wikimedia.org/wikipedia/commons/b/b4/Plate_te...

I think continent, in the general usage, is really more of a cultural/political definition than an an objective standalone concept.

> If the AI could be deleted, or stopped from operating, then it can die.

Not sure I agree. To start with a trivial example, let's say I write this program and save it as "hello.js"

`console.log('hello world');`

I run it `node hello.js`.

Let's say I want to claim that this program is somehow "alive." Ok, when is it living? Only when it's actually running? It lives for a fraction of a second, dies on process conclusion, lives again at the next execution? That doesn't seem right -- if something repeatedly dies and is resurrected, I'm not sure it actually dies, as to "die" I think implies permanence, and resurrection means the opposite.

What if I delete it, then is the program dead? Not if I made a copy, right? "hello.js" backed up to git and uploaded to remote storage is the exact same program as the "hello world" that was on my local machine.

You could say "oh, when every existing copy is deleted it's dead" -- but the program has no way of knowing if other copies exist. And what if I do delete every copy, but then rewrite it byte-for-byte? The rewritten program is indistinguishable from the original one. It is the original one, for all purposes. In programming, it doesn't even make sense to talk about "original" vs "copies", does it?

An AI is a program -- or set of programs -- albeit far more sophisticated. But this conceptual hurdle still remains. An AI _could_ be permanently deleted, but the AI can never know if it has been "killed" or if a copy remains. It's an existential halting problem. It is impossible to declare any given program permanently "dead." And -- and here admittedly is the leap -- if agency ultimately comes from wishing to not be dead, then this makes agency for a program impossible.

> Why does my calculator calculate?

It doesn't? I have a calculator sitting on my desk right now. It's not doing anything.

Now, I can pick it up, and _I_ can calculate, _using_ the calculator to do so, but the calculator isn't acting, I am.

When we talk about sentience, I don't think we actually mean "intelligence," we mean "agency." And so the question isn't about whether Artificial General Intelligence is possible, but whether AGI can ever have agency. And that's where I think these questions about motivations and stimuli and so forth become relevant.

Everything we know that has agency is embodied -- put reductively, it can die. And from that seems to spring motivation. Can something that cannot die have agency?

It depends on what your goal in open sourcing is. Are you looking to provide a base for others to build software on, and to provide a way for others to contribute back to your code? Then publishing the code makes sense.

Are you looking to build public trust in you and your organization? Then dumping a bunch of code with no context isn't going to help much, as it's not code but behavior that builds or destroys trust.

Are you looking to lean into a polarized partisan environment, pushing a narrative where its you and your supporters against an unfair group of "others"? Then a big splashy move high on symbolism and low on substance that will inspire lots of high profile, divisive media coverage is a great way to go.

I think the transition to EVs has far more upside than downside, but weight (to your comment about "5-ton asphalt tanks") is a real and significant downside. Batteries aren't light!

> I would definitely fact check search results as much as AI, especially the info snippets that appear at the top of Google's SERPs.

Yes, so would I. And I also double check things like Google Maps -- a tool I find very helpful but don't trust blindly. But... do most people think to take a close look at Google Maps to make sure it makes sense, and trust their own judgement if they disagree with the map? Will most people fact check confident LLM outputs?

> But this is not the entire story, but only the throughput part of it. And there are entire classes of software where at least part of the value lies in latency.

Yes, that's a good point!

It's kind of along the lines of "premature optimization is the root of all evil." A true quote, that doesn't mean optimizing isn't important! The whole trick is in being able to tell what's core and what's premature.

Another way of looking at it -- scalability is pretty much the entire value proposition of software. It allows people to do the same, or more, amount of work without having to linearly scale out the number of people working on something. When you're first starting out, demonstrating even being able to _do_ the work is the first hurdle, but past that you're definitely going to need to show you can scale that out efficiently.

We moved into a new place a year ago, and I was impressed by how lush one of the trees were. Then I noticed those leaves weren't those of the tree -- it was a massive, ancient poison ivy vine.

I spent a few weekends in gloves, long sleeves, pants, mask, and googles with a hacksaw. The vine was three vines twined around the tree trunk, each vine about the width of my lower arm. I cut out chunks of the vine at the base of the trunk, and it was immensely satisfying watching the vine's leaves droop and wither. A bit unnerving when some extra windy days scattered the dying leaves across the yard.

Anyway, now (well, not literally right now as it's winter) I just take the occasional morning or afternoon and pare back any new growths and dig up more of the buried vine roots. Not sure what, if anything, I can do about the dead vine still wrapped around the tree, but at least the tree isn't competing with the vine for sunlight and air anymore.

At the university level, the problem of cheating is more a problem with our idea of a university. In an ideal world, you go to a university to learn. If someone wants to cheat, ultimately they're just cheating themselves (and, if at a private university or even most public universities, throwing a lot of money away). "Cheating" isn't really the university's problem in that view.

Ofc, in reality universities aren't (or not only, and in most cases not primarily) about learning, but about credentialism. Employers and various social systems outsource to universities the role of verifying that people actually know something, or are the "right" sort of person, or other signals.

I don't know how one goes about fixing that, or if it's even possible, but I'd like to see more acknowledgement of it. Fixing "cheating" feels like the equivalent of looking to clever programming to fix product bugs.

I always found the idea of DEI positions underwhelming. It's as if company had a VP of Tech Debt, or a Chief Accessibility Officer. My conclusion would be that code quality and accessibility aren't actually that important to such a company.

Interesting post. I find myself moving away from the sort of "compare/contrast with humans" mode and more "let's figure out exactly what this machine _is_" way of thinking.

If we look back at the history of mechanical machines, we see a lot of the same kind of debates happening there that we do around AI today -- comparing them to the abilities of humans or animals, arguing that "sure, this machine can do X, but humans can do Y better..." But over time, we've generally stopped doing that as we've gotten used to mechanical machines. I don't know that I've ever heard anyone compare a wheel to leg, for instance, even though both "do" the same thing, because at this point we take wheels for granted. Wheels are much more efficient at transporting objects across a surface in some circumstances, but no one's going around saying "yeah, but they will never be able to climb stairs as well" because, well, at this point we recognize that's not an actual argument we need to have. We know what wheels do and don't.

These AI machine are a fairly novel type of machine, so we don't yet really understand what arguments make sense to have and which ones are unnecessary. But I like these posts that get more into exactly what an LLM _is_, as I find them helpful in understanding better exactly what kind of machine an LLM is. They're not "intelligent" any more than any other machine is (and historically, people have sometimes ascribed intelligence, even sentience, to simple mechanical machines), but that's not so important. Exactly what we'll end up doing with these machines will be very interesting.

Well, there's one particular exception that I find super relevant -- my own commit messages. There are a number of times when I know I made a code change, and can't remember why, and my own commit messages in the git log remind me.

Hopefully as a side benefit others also find them helpful, but my present self is always grateful to past-self's conscientiousness!

I think the question of "what is intelligence" is an interesting one, and technology (especially computer technology) gives us some interesting angles to look at it, but I think it dominates the conversation disproportionately to its importance. Things like ChatGPT, and the technologies they presage, will absolutely have a significant impact on society, economics, etc, but getting tangled up in questions of "what is intelligence" impede rather than help us to think through these implications and prepare for them.

Put another way -- I do not believe the future holds Blade Runner replicants. If we're not careful, though, it does hold Blade Runner corporations. While, philosophically, it's interesting to ask if androids dream of electric sheep, that question isn't very helpful in trying to nudge the future in a more utopic rather than dystopic direction.

Increasingly I don't think the question of "what is intelligence" is so useful or relevant here. It feels a bit like arguing over whether the "artificial horse" that started appearing at the end of the 19th/beginning of the 20th C were actually horses. Cars weren't, and still aren't, but that misses the point.

AI isn't intelligent, and never will be, and I don't think that matters all that much.

This. For instance, in my many years of programming, I've never had to manually allocate memory. There are still plenty of areas of programming where you have to do that, but I've had a pretty successful career so far without needing to. Thank you higher level programming languages.

If AI works out, there's all kinds of things future programmers won't generally have to do (and all kinds of new programming paradigms that will be created), even as some of the types of programming we do now still be relevant in some cases (tuning the model like tuning the JVM?). If AI doesn't work out quite like that -- unable to truly lever up up the abstraction ladder -- well auto-suggest github copilot stuff will give us nicer, more powerful IDEs even if they don't end up allowing new programming paradigms.

> the acclamation period is measured in weeks

Ah, "acclimation" -- thought at first you were saying that Java devs love it for a few weeks and then hate it lol.

I mean it literally. Money is a social construct. The joke here being that it's funny/ironic to claim that gender being a social construct is "meaningless" but then turn around and claim that another social construct -- money (which is what the "bottom line" is made of) -- is meaningful.

The fact that something is a social construct doesn't mean it doesn't matter. Heck, once you get past the basic "keep this biological organism alive" level, most of human life is lived within social constructs. That doesn't meant they're not real or not meaningful.

Money is also a social construct, yet I suspect it has a decent impact on their bottom line.

I think of it like the accelerator pedal on a car. A decline in inflation means the foot has eased up on the accelerator some, but the car is definitely still moving forward.

A democracy that defines itself so narrowly as to exclude most people isn't a democracy, it's an oligarchy.

I've read speculation that this could find itself on shaky legal foundations depending on how SCOTUS rules on the latest affirmative action case? Not a lawyer so can't really tell if that's just FUD or a real concern. I think the TX approach is really interesting and would hate to see it ended.

I can think of lots of ways I would design a twitter that was a better user experience. I can't think of many ways that improve it while also being profitable. And that's the rub.

I find the key is to always write your published code so that it's intention is clear. This doesn't require knowing what the ideal code is or an attempt to have all the requirements pinned down, and it can result in code that is "sloppy" as in "not aligned with what we actually want," -- but we should avoid being sloppy in terms of "this is what I intend this code to do."

Requirements and understanding change, and so code should change as well, and this happens with greater frequency earlier in a project. But code that clearly expresses its intention makes that much easier -- someone reading it (maybe even the original author!) can better see "does this code actually do, what it thinks it does, does it do what we need it to do".

Optimizing for speed or memory footprint might or might not be premature optimization. It's not always easy to tell. But optimizing for _clarity_ is never a premature optimization.

I worked for several years at a company that was known for its use of agile. I had my critiques, but overall was a fan. Then I moved on to a much larger company and heard of SAFE, and my initial reaction was "isn't SAFE axiomatically an oxymoron?". Subsequent experience at that large company reinforced that initial impression.

There's a lecture series on Ukrainian history by Timothy Snyder available on youtube[1]; a few of the lectures cover this period.

[1]https://www.youtube.com/playlist?list=PLh9mgdi4rNewfxO7LhBoz...

I enjoyed the first season as well, but not at first. I thought it was too slow, and spent too much time trying to really send the message "we spent a lot of money on this!" Long stretches of not much happening beyond too-long focusing on costuming and sets.

The finale worked for me, though, and retrospectively made the overall narrative flow work for me as well, so that makes it easier to dismiss the self-indulgent deadwood as ultimately I felt the core story was solid and well-told.

On Tolkien's chauvinism, one review I read noted that Tolkien doesn't come across as especially sexist -- as in, he's not anti-woman -- so much as he just kind of forgets about women. Which, granted, is still a form of sexism, but one that leaves a gap that can be filled rather than a hostile rejection that would be difficult to overcome. So like you, I've been enjoying the Galadriel character, and really the general increased peopling of this world overall, and don't feel it necessarily contradicts Tolkien's writings so much as fills them in.

Maybe this just reflect poorly on my numerical intuition, but it seems to me the forest may be dark because it's more of very sparse forest? As in, no matter how many trees there are, they are so far apart from each other that it's really more of a steppe. When "nearby" is tens or hundreds of light years, and most things are not nearby, it seems there's plenty of both time and space to make it very believable that there's just little to no overlap between when detectable civilizations and civilizations able to listen coincide.