That is not a contradiction. Just look at social media use where you can observe the same.
People can hate on AI e.g. because they see it as a symbol of inequality and billionaires deciding important things over our heads and also actively use it.
They don't if you mean STEM and emancipation, quite the opposite, actually (compared to West Germany).
In addition to the points of sibling comments, their respective starting posititions were drastically different: West Germany got the marshal plan, which benefitted their economy, the East had to pay reparations to the USSR, which meant whole factories, trains, even railroad tracks, all in all amounting to about a third of industrial capacity, were transferred to the USSR.
You think standing in for people's rights against the profit interests of transnational corporations means "making life difficult"? Whose life exactly? That of the CEO of Microsoft?
How can this become a monopoly/duopoly? There is no moat, the Chinese providers will continue to hunt the market leader at 10% of the price, there is no network effect (OpenAI's Sora was a play in that direction and failed).
I'm constantly amazed how this AGI/monopoly narrative can be kept up so long in the West, it just doesn't make sense (unless the state creates said monopoly by forbidding competition).
That's not what "moat" means. Claude Code has a castle. A "moat" is meant to protect the castle from invaders. It would be things like high switching costs, proprietary formats, network effects, etc. that aren't there.
In other comments people mention the "flywheel" of data and money feeding training, but there's a view that at some point the baseline open-weight models are "good enough" that the money will dry up.
> Open-weight models aren't going to be free forever.
The ones that are already released are, and they're already very good for most purposes and can be fine-tuned indefinitely, includin months or years down the line when processes have been optimized and things aren't as compute-heavy as they are now.
But all the open-weight players make money right now. Google (Gemma), Alibaba (Qwen), z.ai (GLM), minimax.io (Minimax) - they all have hosted offers and sometimes closed-weight max versions.
And the fact that the open-weight as well as cheaper tier 2 offers exist both place a ceiling on the prices the SOTA companies can demand - and as far as we know current prices don't even fully pay for inference alone already, at least not for OpenAI.
To my knowledge none of the players is even profitable on inference, though Google probably is, considering the continuous release of papers around kv cache optimizations, mtp etc.
No, a moat would be a feature preventing the competition from competing successfully. Classically things like patents, for example, or process knowledge like ASML currently has for EUV lithography, or the network effects of a social media platform, or access to data no one else has access to.
ARR is not a moat at all, because the revenue of OpenAI is not preventing Alibaba, z.ai and so on from generating revenue as well. The opposite is true, actually, because the first mover prepared the market (e.g. user education about application possibilities, creating the willingness to pay for the service in the first place) for the second movers.
People here write about switching from Claude to Codex mid-workday - that is the absolute opposite of a moat.
The only companies that have a chance of not losing everything in this market are those with established non-AI revenue streams, like Google or Alibaba, or those focusing on profitability in niche markets instead of participating in the SOTA death race.
A moat is protection so you can keep your ARR up or increase it over years. Arguably only google have a moat with their TPUs. NVidia has a moat. But the others who just train some models on NVidia hardware have no moat.
I bet you actually have. Its those gaps in the threads for screwing on the lid. The pressure get escape through these gaps while the lid still stays on the bottle.
Lots of important points already posted, from reliability over accessibility to SEO. To add a personal reason: speed. I hate slow computer things. If I open a page I e.g. don't have to use for work or similar (like Google Ads or Linkedin or similar horror shows), and loading the page takes longer than a second, I just bounce.
I built and maintain a static site for a company, and it's just wonderful. It opens instantly (which the search engines like), rebuilding and deploying is trivial, I am not forced to update every week because the JS framework has a new vuln.(There are a few dynamic, JS-based parts that load dynamically and fail gracefully.)
None of this refutes my post whatsoever. The amount of JavaScript to open a hamburger menu is literally around 500 bytes. It can easily gracefully degrade just like your last sentence said. You're going to load much, much more than that by following TFA. It loads an entire new HTML page! This argument just doesn't work here.
There's nothing to refute in your post; you only told the audience that you don't get OP, and people tried to explain the appeal to you. What you do with that information is your thing.
None of what you said explained the appeal of OP's technique! Using JavaScript doesn't have to affect your reliability, accessibility, SEO, or any of the things you said. How am I supposed to do anything with useless information?
If anything, hiding the hamburger menu behind an HTTP response is *less accessible*!
Not to mention the article's menu "close" button relies on JS to send you back to the correct page, and doesn't work with open in new tab / window even with JS enabled.
Having an economic science without politics at all isn't really possible - you have to define a goal for economic development to evaluate different approaches. And defining that goal introduces politics into economics. "Development for what or whom or whether at all" simply can't answered in a neutral way, it will always be in the interests of some and against the interests of others.
Isn’t the whole point of a ‘scientific approach’ to reduce biases and to study the problem independently of how the problem affects us? Why do we call things sciences but we’re unwilling/unable to divorce our biases from the process of studying a thing?
My background is in educational science where we face similar dilemmas. In both fields I'd say there is no conflict between scientific rigor and political goals as long as you make your goals transparent.
The fact that you want to study economic processes because you want to e.g. better the live of the poor half of society does not mean you can't apply scientific principles. But the results will not necessarily be applicable for those who think a rising tide lifts all boats and therefore want to develop the economy in the interest of the upper class.
In fact I'd be suspicious if people claim to be unbiased in any field that even remotely has something to do with humans or society - it usually just means they either hide their interests, or aren't aware of their biases.
Clickety_clack propably wasn't referring to people with aphantasia not seeing the story unfolding while reading the book, but the book itself: We predict that the thing we hold in our hands is a book entity, and then we use our sensory perception to affirm or change that prediction. We don't continuously parse a 2D array of pixels and interpret that as as a book every frame.
People can hate on AI e.g. because they see it as a symbol of inequality and billionaires deciding important things over our heads and also actively use it.