This just makes it even more frustrating to me. Everything good about go is more about the tooling and ecosystem but the language itself is not very good. I wish this effort had been put into a better language.

Go has transparent async io and a very nice M:N threading model that makes writing http servers using epoll very simple and efficient.

The ergonomics for this use case are better than in any language I ever used.

Implementing HTTP servers isn’t exactly a common use case in software development, though.

Sorry I didn’t mean implementing a raw http server like nginx, but just writing a backend.

> I wish this effort had been put into a better language.

But it is being put. Read newsletters like "The Go Blog", "Go Weekly". It's been improving constantly. Language-changes require lots of time to be done right, but the language is evolving.

I don't agree that it is because of the "quality" of the video. The issue with AI art is that it lacks intentional content. I think people like art because it is a sort of conversation between the creator and the viewer. It is interesting because it has a consistent perspective. It is possible AI art could one day be indistinguishable but for people to care about it I feel they would need to lie and say it was made by a particular person or create some sort of persona for the AI. But there are a lot of people who want to do the work of making art. People are not the limiting factor, in fact we have way more people who want to make art than there is a market for it. What I think is more likely is that AI becomes a tool in the same way CGI is a tool.

> The issue with AI art is that it lacks intentional content. I think people like art because it is a sort of conversation between the creator and the viewer.

Intent is in the eye of the beholder.

The trouble with AI shit is it's all contaminated by association.

I was looking on YT earlier for info on security cameras. It's easy to spot the AI crap: under 5 minutes and just stock video in the preview or photos.

What value could there be in me wasting time to see if the creators bothered to add quality content if they can't be bothered to show themselves in front of the lens?

What an individual brings is a unique brand. I'm watching their opinion which carries weight based on social signals and their catalogue etc.

Generic AI will always lack that until it can convincingly be bundled into a persona... only then the cycle will repeat: search for other ways to separate the lazy, generic content from the meaningful original stuff.

> I do feel that there is a routine bias on HN to underplay AI

It's always interesting to see this take because my perception is the exact opposite. I don't think there's ever been an issue for me personally with a bigger mismatch in perceptions than AI. It sometimes feels like the various sides live in different realities.

It's a Rorschach test isn't it.

Because the technology itself is so young and so nebulous everyone is able to unfalsifiably project their own hopes or fears onto it.

Any big AI release, some of the top comments are usually claiming either the tech itself is bad, relaying a specific anecdote about some AI model messing up or some study where AI isn't good, or claiming that AI is a huge bubble that will inevitably crash. I've seen the most emphatic denials of the utility of AI here go much farther than anywhere else where criticism of AI is mild skepticism. Among many people it is a matter of tribal warfare that AI=bad.

Coping mechanisms. AI is overhyped and useless and wouldn't ever improve, because the alternative is terrifying.

I'm very skeptical of this psychoanalysis of people who disagree with you. Can't people just be wrong? People are wrong all the time without it being some sort of defense mechanism. I feel this line of thinking puts you in a headspace to write off anything contradictory to your beliefs.

You could easily say that the AI hype is a cope as well. The tech industry and investors need there to be be a hot new technology, their career depends on it. There might be some truth to the coping in either direction but I feel you should try to ignore that and engage with the content of whatever the person is saying or we'll never make any progress.

I have the impression a lot depends on people's past reading and knowledge of what's going on. If you've read the likes of Kurzweil, Moravec, maybe Turing, you're probably going to treat AGI/ASI as inevitable. For people who haven't they just see these chatbots and the like and think those won't change things much.

It's maybe a bit like the early days of covid when the likes of Trump were saying it's nothing, it'll be over by the spring while people who understood virology could see that a bigger thing was on the way.

These people's theories (except Turing) are highly speculative predictions about the future. They could be right but they are not analogous to the predictions we get out of epidemiology where we have had a lot of examples to study. What they are doing is not science and it is way more reasonable to doubt them.

The Moravec stuff I'd say is more moderately speculative than highly. All he really said is compute power had tended to double every so long and if that keeps up we'll have human brain equivalent computer in cheap devices in the 2020s. That bit wasn't really a stretch and has largely proved true.

The more unspoken speculative bit is there will then be a large economic incentive for bright researchers and companies to put a lot of effort into sorting the software side. I don't consider LLMs to do the job of general intelligence but there are a lot of people trying to figure it out.

Given we have general intelligence and are the product of ~2GB of DNA, the design can't be that impossible complex, although likely a bit more than gradient descent.

I think it's fair to point out that they were never intended to be a good framework for aligning robots and humans. Even in his own stories they lead to problems. They were created precisely to make the point that encoding these things in rules is hard.

As for practical problems they are extremely vague. What counts as harm? Could a robot serve me a burger and fries if that isn't good for my health? By the rules they actually can't even passively allow me to get harmed so should they stop me from eating one? They have to follow human orders but which human? What if orders conflict?

> I think it's fair to point out that they were never intended to be a good framework for aligning robots and humans. Even in his own stories they lead to problems. They were created precisely to make the point that encoding these things in rules is hard.

That seems like the biggest point missed here. They're intended to be able to lend themselves to "surprising" conclusions, which is exactly what we don't want, so it seems obvious to me that those laws aren't good enough? That's how I remember the stories at least.

This seems very much a “did you even read the book??” moment. That Asimov’s laws didn’t work, and indeed failed spectacularly, was kinda the whole point.

The UX is nowhere near close to native apps, particularly on platforms that take UX seriously like macOS, iOS or Gnome.

There are some great native apps out there and a lot of them do things you couldn't do on the web, but nowhere near close seems like a stretch to me. There are some great web apps out there. And while there are great native apps made with love there are also perfunctory, rushed, clunky ones that could have just been a website.

People often overlook some of the functional UX the web brings to the table. For example: on the web I get consistent search and text highlighting behavior, consistent notifications, consistent navigation behavior (back buttons, history), I can tab to focus (usually), and I can use plugins to customize the content. Even the idea that you can reset the application state with a refresh is something I wish I had on some native apps.

Can you give some examples, please? I can't think of a single thing that cannot be overcome by good design.

They never look and feel exactly like native apps, even the ones that try a bit.

Some widget will be rendered wrong, they'll use the wrong font (or even hinting!), right click may not work as expected, they won't use multiple windows correctly, etc.

Even React Native gets some of this wrong, although few use that on desktop.

If you're a user that appreciates consistency on your OS, all of this will stick out and annoy you. And you'll end up using Apple's Mail.app over GMail's UI.

Things.app, Bear.app, and a few others from the macOS side are nice example of UX.

While the web can be great for RAD, the native side gives you raw control when you want it. And actual desktop UI widgets, like table, list, and windows.

This doesn't make any sense. When people say this they mean they want more social spending and they are willing to pay more taxes to get it. The budget is what it is, the administration has made it clear that keeping the deficit low has nothing to do with the level of social spending they are willing to do. Sending money won't really do anything.

I think this is fair. Untracked TODOs should be minimized but I think there is value in recording how some section of code could be improved even if you know you are unlikely to do it. I don't think the triple click thing is a good example because that seems like a bug to me.

An example from my codebase is that I implemented a daily scheduled job that may display inconsistent results during short time per day it is running. Realistically fixing this will never be worth my time, this is a transit app and it is scheduled to do this at night when the buses aren't running and it will only be inconsistent if they change the schedule after already publishing it for a given day which happens pretty much never. It is also a personal project with no issue tracking.

Eventually I will rewrite this loader logic to support multiple transit systems so it is good to have my notes of how I would do it better next time. Also, if this does result strange schedule behavior I would immediately go to this file and see my explanation of the flaws with my approach. Maybe I shouldn't call this a TODO but it seems like a good fit.

Not really. These other industries are evaluating people somehow. Whether it's vibes, connections, resume, or some sort of technical evaluation you'll have a grown adult evaluating you. Hiring will always feel a bit lame and arbitrary, you have limited time and information to pick someone. You're not going to be able to understand candidates fully and you'll probably pick wrong a fair bit. So we come up with criteria that's a bit arbitrary but you need at least some effort and smarts to meet them so it's at least a bit correlated with a good hire. I don't think the non technical methods are any more or less dignified.

I somewhat agree that there is a problem but there is a glimmer of hope. As these medical terms are used more in everyday speech they lose their medical connotations and just become new words for personality traits. A lot of people who casually describe things as ADHD are using it more as an adjective than a diagnosis. We have had medical terms make it into this usage before: moron, hysterical, humourous (we're going all the way back to the four humours).

AGI is a marketing term. It has no consistent definition. It's not very useful when trying to reason about AI's capabilities.