The inertia (or actively maintained status quo) in Europe towards the US platforms is massive.
Anecdotally, I recently found myself in the local government building of a small European town. They run several free digitalisation classes for small businesses.
It might be worth considering that if those are intro classes, then it's not like they can't be easily replaced: it's not like the audience is wedded to any of those at an introductory level.
I am not much of a devops person but running your own DB in a VPS with docker containers don't you also need to handle all this manually too?
1) Creating and restoring backups
2) Unoptimized disk access for db usage (can't be done from docker?)
3) Disk failure due to non-standard use-case
4) Sharding is quite difficult to set up
5) Monitoring is quite different from normal server monitoring
But surely, for a small app that can run one big server for the DB is probably still much cheaper. I just wonder how hard it really is and how often you actually run into problems.
My guess is some people have never worked with the constraints of time and reliability. They think setting up a database is just running a few commands from a tutorial, or they're very experienced and understand the pitfalls well; most people don't fall into the latter category.
But to answer your question: running your own DB is hard if you don't want to lose or corrupt your data. AWS is reliable and relatively cheap, at least during the bootstrapping and scaling stages.
Maybe it's unfair, unhelpful or overdone to call out llmisms, but if OP is reading this I stopped reading pretty quickly as a result of things like:
> [CUE] does not just hold the text; it validates that the pieces actually fit. It ensures that the code in your explanation is the exact same code in your final build. It is like having a Lego set where the bricks refuse to click if you are building something structurally unsound.
And that's despite having a passing interest in both cue and LP
> Maybe it's unfair, unhelpful or overdone to call out llmisms
Not anywhere near as overdone as posting AI generated/revised articles to HN that are an absolute slog to read.
A real shame, honestly, because the other article[1] from this blog that made it to the front page recently was good. The difference in writing style between them is striking, and I think it serves as a really good example of why I just can't stand reading AI articles.
Ah, the negative positive construction. Another casualty of the anti-AI movement. The semicolon was almost certainly inserted manually in place of an em-dash, models almost never use them.
Accusing people of using generative AI is definitely one of those things you have to be careful with, but on the other hand, I still think it's OK to critique writing styles that are now cliche because of AI. I mean come on, it's not just the negative-positive construction. This part is just as cliche:
> It is like having a Lego set where the bricks refuse to click if you are building something structurally unsound.
And the headings follow that AI-stank rhythmic pattern with most of them starting with "The":
> The “Frankenstein” Problem
> The Basic Engine
> The Ignition Key
> The Polyglot Pipeline
I could go on, but I really don't think you have to.
I mean look, I'm no Pulitzer prize winner myself, but let's face it, it would be hard to make an article feel more it was adapted from an LLM output if you actually tried.
There are a few like this. You can bet on Jesus not coming back in the calendar year for a little pocket money.
Funny, because a bit like the yes side of the civil war scenario, if JC comes back and someone is the sort of person to bet that he will, then do they really need the payout in those circumstances; and will the gambling website be in a position to pay out?
Polymarket and other prediction markets dont take risk on the trades. Two sides are needed to make a market so you’re likely to get your payout. So all the people taking the “safe” bet lose their collateral and the winners get the proceeds if the unlikely event happens.
You're exactly right.
No -- you're exactly right!
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