Watch them :)

Seriously though, this happens every time technology is introduced, for better or worse.

And while it's annoying, it's actually very helpful too, but you need to get further into your understanding than the emotion arguments people usually have front and center in their mind, because there is real criticism that has real value in there, it's just behind all the annoying knee-jerk reactions.

But again, this happens over and over, every time, seemingly in every community. Even HN has these soft spots, maybe not for AI but for example blockchain and cryptocurrencies are still subjects that somehow bring out these knee-jerk reactions to people (again, sometimes for good reasons, although the initial reaction masks the real cause).

Best we can do is listen and actually understand, instead of just brushing it away as "irrational hatred", because it always comes from somewhere, sometimes personal reasons, sometimes illogical reasons, but always because of something.

Power is more expensive because data centres are using so much of it. Climate change is a tougher problem to solve because we're trying to reduce emissions while the energy requirements of big AI companies is eclipsing that of some nations. GHG emissions are going up when they need to go down. Computer hardware prices are through the roof. Fresh graduates, including those in STEM, face uncertainty in a job market that's trying to replace inexperienced, unspecialized, non-experts (i.e. them) with AI. Many of them know how to use AI just fine, but that doesn't necessarily make them employable. You may dream of being a AI-powered super-developer, but the path to that job may go through entry level positions that become harder to find each day.

Critics of AI are not being irrational. They're paying the costs but not reaping the benefits and they don't see a clear path to changing that. I suggest you look into the history of the luddites and the industrial revolution. Today, we see the industrial revolution as a tremendous boon, but it wasn't that for everyone initially. Multitudes spent their entire lives being shafted before the benefits started tricking down. The real kicker is that only some of the people who suffered were luddites. Many were just like you. You can love a fission bomb for the beauty of its physics, but you'll suffer exactly the same fate as an nuclear abolitionist if one is dropped over your city.

I've heard so many different takes on this. Where did you get this information?

If AI were a country, it'd be 12th place in the world for energy consumption.

https://en.wikipedia.org/wiki/List_of_countries_by_electrici...

It's gone up considerably since last time I looked. Jeez.

What "insane productivity boosts" are non-coding fields seeing from AI? If anything, coding is the most affected space, and even there I'm not sure I'd classify it as an "insane" productivity boost yet.

They were against that. And people were impoverished, as can be seen in the drop of life expectancy until labour laws were enacted.

Edit: https://pubmed.ncbi.nlm.nih.gov/36335796/

>The initial wave of poor health during the industrial revolution gave way to increased life expectancy and decreased levels of infectious disease during the later 19th century, linked to various public health measures.

>By the latter part of the nineteenth century, life expectancy and health improved, and the growing health disparity between rural and urban areas started to decrease.

>Our knowledge of the living conditions of the 19th century, particularly amongst the urban poor, has led to a strong assumption that a significant decline in health occurred at the onset of the Industrial Revolution. We must be cautious not to overly sentimentalise the medieval and early modern periods, when air pollution (primarily from woodsmoke and also sea coal) was common (Brimblecombe, 1976) and adult life expectancy was lower.

Productivity as the be-all-and-end-all of personal aspiration exemplifies what is rotten in our industry and society at large: more for the sake of more, faster for the sake of better, no matter the consequences and with certainty no mind for the quality.

Every new technology brings with it much promise, MUCH bigger hype, grave disappointment once the people who have been using it wrong fail, and then the new batch of winners. This happens any time there's a big leap in our tools, and AI is no exception.

Productivity is how we make things better. We have enough food for everyone because we've leveraged new tools to make the task more productive (the fact that the food is unevenly distributed is a separate problem).

That's a tautology. No, those tech stacks are mainstream because it is easy to get something that looks OK up and running quickly. That's it. That's what makes a framework go mainstream: can you download it and get something pretty on the screen quickly? Long-term maintenance and clarity is absolutely not a strong selection force for what goes mainstream, and in fact can be an opposing force, since achieving long-term clarity comes with tradeoffs that hinder the feeling of "going fast and breaking things" within the first hour of hearing about the framework. A framework being popular means it has optimized for inexperienced developers feeling fast early, which is literally a slightly negative signal for its quality.

If the AI can only decently do JS and Python, then it can fully explain the observed disparity in opinion of its usefulness.

Luckily there are superior alt coins that don't have that flaw.

That should be the point where the intellectual curious hacker should try to broaden there horizon beyond the superficial surface.

I don't see the seedy nature you try to apply to a whole industry if anything i experience the opposite.

What does an algorithmic task such as array comparison have to do with language syntax? The answer is nothing.

Sure, some languages might have builtins for comparing certain things, or doing intersections/differences, but those only apply to arrays of primitives, and even in those cases the utility of the builtins completely depends on the use case, and those builtins still have nothing to do with syntax.

I guess you've not written much python, or just not used any custom types in lists if you have.

    class Thing:
        def __init__(self, a, b):
            self.a = a; self.b = b
        def __eq__(me, them):
            return me.a == them.a and me.b == them.b
    >>>[1, 2, Thing(6, "Hi")] == [1, 2, Thing(6, "Hi")]
    True
    >>>[1, 2, Thing(6, "Hi")] == [1, 2, Thing(6, "Hello")]
    False

https://en.wikipedia.org/wiki/Superior_orders

I don't know, this just seems more like inertia. "I'd rather stick to what I know best than this popular thing." Which is fine, and I'm glad Java has made improvements making it easier to hit the ground running. But blaming the use of Java on the inadequacies of Python? The python API can do just about anything, it has regex toolings, I've never found myself needing anything else. And the typing complaints? Yeah it can be annoying if you're not good at keeping track of your own typing hints, but modern python supports type annotations and linters like mypy[1] catch everything related to that just fine. I've always admired many of Java's features, but let's not act like the reason for using Java for scripting is the pitfalls of Python. It's just because of an underlying preference for Java.

1. https://mypy-lang.org/

If you write all the code you deal with, then sure. My experiences on big projects tend to be typing problems introduced by libraries. The kind where documentation and the decorators suggest it'll only ever return some specific value type, but then very occasionally it'll return a tuple of that value type and a message.