godelski
> but can also be the formula for monsters to use that are "hoping for" things that most would find repugnant
As an American, we don't like kings and queens because they are always monsters. Just as the very recent attempt to make a king has illustrated. And frankly, the wiki article even downplays Diana.The problem is they are explicitly saying to do things in the shadows.
| Above all things our royalty is to be reverenced, and if you begin to poke about it you cannot reverence it... Its mystery is its life. We must not let in daylight upon magic
Without that daylight you can't differentiate monsters from men. They claim it's because you can't differentiate saints from men, but I'd make the claim that any man who wishes to be seen as a saint is more monster than saint.And we've seen what these people do in the shadows. The disgraced Andrew was far from the only Royal in the Epstein files. We saw what they did to Diana, who tried to shed some light. We've seen it over and over.
I'll take the light, because I'd rather live in a world where we make things better than live in a world with the appearance of magic. The only magic is what we create
>> words that label parts of continua are useful
and I'll add one more point: there's a difference in how people speak colloquially and how words are used by experts. In fact, different groups of experts may use the same word to mean different things (e.g. a mathematician and mechanic both call things "manifolds", yet you shouldn't confuse them). Natural language is highly overloaded (which is a big reason we invented formal languages).A problem with the word "intelligent" is that very few people look to see how it is actually used in different fields like neuroscience, psychology, or machine learning, which all use the word a bit differently, and none of them use it in the way that we use in natural speech.
> "yellow" that isn't every color.
But I can ask you how "yellow" is the color green. It is certainly some yellow. Definitely more yellow than red is. Even more so, we might argue over if black is more yellow than white or not. Which in some settings black is more yellow than white and in other settings white is more yellow than black. Hell, the fact that you can read this and understand it is clear evidence of both utility and ambiguity. We haven't even mentioned that people may use the same definition but use a word to mark a certain threshold and disagree on that threshold (the root of so many painful to watch arguments).Everything is just a bit fuzzier than you think.
> If basically everything is <X>, does that word mean much then/is it a useful term?
Yes and no, because nothing is as well defined as you imply.Let's let X = "chair", to make my point a little more fun.
Obviously we know what a chair is, use the Potter definition[0]. Everyone has several of them in their houses, offices, and all around. But can you state a well defined definition? Is a table a chair? I can sit on it (I often do), it has four legs, and practically all things we'd consider a chair. Okay, it has no back (usually), but then we got to throw out the stool. It has no back. It doesn't even have to have 4 legs! So what about that stump on the ground? Is that a chair? I think most people would argue through a definition of convenience. Or maybe closer to a cat's definition of "if I fits, I sit."
You can replace X with just about anything and you'll find this ambiguity runs rampant. A cup, a table, cereal, sandwich, a tomato; you name it and I'm sure someone here will point out an instance that makes that definition look a lot fuzzier than you initially thought.
So that really shows us the crux of it all: how well defined is something. That only tells us our ability to distinguish something, though it doesn't tell us how well that thing fits into the category. So the stump is a little chair-like, the table is pretty chair, a stool is usually considered a chair, and that thing I'm sitting on is unambiguously a chair[1]. s/chair/intelligence/g and you have your answer. But the if you needed that last sentence, well, there's two types of people: those that can infer.
All models are wrong, but some models are useful
[0] Incidentally this is also a good definition for explaining RLHF and has all the same problems: https://en.wikipedia.org/wiki/I_know_it_when_I_see_it
[1] Though that doesn't mean it also isn't other things!
I abhor people who make the claim that words they didn't spend the time to understand are meaningless simply because they are incomplete. It is idiocracy masquerading as intelligence. I hate it so much because the logic doesn't just fool the listener, it fools the speaker.
I'll let Asimov rant to you all instead, since half a century ago he too was frustrated with this millennia old egomaniac claims https://hermiene.net/literature/essays/relativity-of-wrong
To put it another way, I still put a lock on my door even though lockpicks exist. I still use passwords on my accounts even though people could guess or brute force them.
Don't trivialize things to uselessness
- Search is atrocious
- I can't find emails from this week but it'll dig up stuff from 5 years ago
- no tagging
- no filtering (tbf, this could be a lot better in most platforms)
- Mail automatically renders PDFs (helps spammers)
- doesn't play well with aliased emails
And a bunch of other things. All minor but they add up > they ask you for a state-issued ID to appeal bans
Requires ID for "age verification" to ensure pedos aren't talking to children"Move fast and break things" mentality, so IDs leak
Pedos use your leaked ID. You land on a list. Meta/Google/Discord/Persona/whoever pays you $20 and gets a slap on the wrist
IDs become useless, so Altman promotes WorldCoin and we all get our eyeballs scanned
Rinse, lather, repeat. Surveillance state grows. Terrorists continue to do terrorist stuff. Pedos continue to do pedo stuff. Normal people get random visits from gestapo because they are 110% sure you were involved in a crime despite proof that you were in a different state at the time.
We're really creating a great world...
I also notice it doesn't handle relayed emails well. I have a bunch of dummy emails and Mail doesn't show me the relayed name, which really hinders my ability to track and combat spam
If I only had one email account I probably wouldn't care as much but that's not as common these days
I also don't like that it renders PDF attachments. Just seems to be enabling scammers
What I like about Mozilla is they made a hackable browser so we can have things like Zen, WaterFox, or whatever floats your boat.
It's such a petty argument when everything is so hackable and Google is eating the internet. I wish people would put half the energy they use to complain to solve the things they are upset about.
Clothing companies do typically put items on sale first. They'll even sell "at a loss"
It's very simple: some is better than none
People have been saying "we don't need docs", "nobody reads docs", "they'll figure it out". They experience the pain of a new employee onboarding but never treat this as a signal for the user experience. The user can't just walk over to the developer's desk. But luckily we got stack overflow, blogs, and Google. Somewhere someone explains it! The problem became finding it!
But hey, why do things the "hard" way when you can just throw money at the problem? Or better yet, dismiss the problem by calling the user an idiot.
You're right. What a time to be alive. We've created a world where this product is useful. And not even to because dark patterns exist, but simply because we've always wanted to avoid taking a step back and thinking or getting an outside view. Because it isn't obvious if a robot has to teach you what button to press. If it does, you probably should be ashamed (there are, as always, exceptions)
That said, I do think there's still a lot of utility you this. Those exceptions aren't uncommon. This'll help people learn programs like FreeCAD or Blender, or whatever. Where the complexity is naturally high. But also I do think we should recognize the silliness of many problems that this does solve that shouldn't be problems in the first place.
> I don't think Copernicus did any explaining why at all.
He did. I mean even ask yourself, why would he do what he did if he was just concerned with motion? Ptolemy's model was accurate for predicting motion. If it was just about motion, then the viewer's position doesn't matter.But Copernicus's enables us to say more. It is more elegant (it was not simpler though). Copernicus was seeking realism. He was the person annoyed with how complex a system was while everyone around him was saying "who cares, it works".
> That's what I mean by it being a matter of taste, not of truth.
There is no taste to truth, only taste in how you convey truth > It is good for the company.
I disagree >> IDK, with a lot of things it seems like big companies are just incredibly myopic.
It may be good for the company in the short term, but that does not mean it is good for the company in the long term. I don't buy the argument that it is good for the company in the long term > but Ptolemy and Copernicus weren't talking about mass or causality
Except they wereMy critique is that there's a difference between "x is the center" and "motion looks like y when sitting at x".
Those are different claims with very different consequences. You're dismissing this as minutia but that minutia is the critical point. In a geocentric model you need to explain why things revolve around the earth. In a heliocentric model you need to explain why things move around the sun. Predicting the motion of the planets doesn't answer these. But answering these *correctly* allows you to build a generalized model in which you can predict the motion of planets, in any arbitrary system.
I'll also add that I love the geocentric model as a good illustration of why observation alone can't give you causality. There's far more to science than data fitting. In fact, that's why all the mathematicians are getting upset and what Tao has been talking about this whole time
While you're technically correct, everyone already understood
> you're not incorrect if you pick a frame that puts the moon in the center or any other point
I think you're conflating different things. Yes, we can predict motion from the view of any point and that would likely involve epicycles. But that's not what people were after. Causality matters, a lot. It's kinda the whole point of physics (and what makes it so expressive and powerful).What classical relativity does not allow you to do is place yourself at an arbitrary point and call that the center of mass of the system (i.e. things orbit around you). That's not invariant. It's a very different thing than predicting the motion of objects from your vantage point.
> they have no power to push back on the boss
As an American I notice this also more broadly affects the company culture. Most of my peers (who are mostly non-Americans) are afraid to speak up. It even causes the (few) Americans to typically not speak up. So it just creates a culture where management is surrounded my yes men. I actually don't think that's good for anyone. Not the American workers, not the foreign workers, and not the company. Your job as an engineer is to talk back to your boss. They aren't the engineer, you are. Even if the boss is an engineering manager. We all know that there's a huge difference in how someone understands code between having written it and just read it (LLMs are certainly blurring this line now...)IDK, with a lot of things it seems like big companies are just incredibly myopic. When I got my PhD people interviewing me used to love to say "well in industry, we do things that actually matter" (a weird premise) and boast about how efficient they are. Yet IME I just see an incredibly suboptimal setting. They routinely waste tons of money to save pennies and the attitude of "I just care that it works" really just ends up with "it looks like it worked but it's actually broken". But that's the obvious result if you surround yourself with yes men and don't let people do their jobs
> At least in machine learning
You should read math papers lol.Honestly, I feel the opposite. But maybe that's because my doctorate is in ML. But we might also have a different definition of what the hallmark papers are. Many of the well known papers are ones that model scaled an existing method (ViT and ddpm are good examples). Important papers, but in which sense? I do think we have space for all types of papers and written to different audiences, but I don't think we should punish papers just because they're written to their niche domain. In the past decade there's been a huge increase in citation farming and I don't think that helps. Math is probably too much on one extreme but I think ML is on the other. You have to write your papers so a first year PhD can understand, because they're the ones reviewing your work. I don't think that's a desirable outcome
I'll admit that sometimes I'm frustrated with HN comments on arxiv articles. Despite being a nerdy forum most papers aren't written for this audience. Hell, I have a PhD and most papers aren't written for me. Nor should they. I'm perfectly okay if I don't understand a paper. Arguably the hardest thing about a PhD is learning to be comfortable with being dumb and willing to work on becoming less dumb (you're never not dumb, only less dumb)