I wonder if there’s a simpler and less interesting answer? That it’s just picking up on voice and style, not anything that would apply to the average non-writer?
This person is a skilled writer. Part of that skill is developing a unique voice and style. The AI can identify that - and while that’s certainly impressive because it can identify even relatively niche authors, it has nothing to do with a wider capability to deanonymize people based on arbitrary written text (ex Facebook or text messages).
If you are a professional musician, it’s not difficult to identify a well known musician / recording after listening to only a few seconds - whether they’re playing Bach or Rachmaninov, the style is just “them” - this is the same thing. But you couldn’t take some anonymous high school musician and guess who they were, even if they were your student - the median quickly regresses towards a homogenous, non-distinct style / voice.
I once was responsible for migrating a legacy business app to Azure, and the app had a local MSSQL server co-running with the app (the same pattern that Litestream is using).
As have been mentioned below, the app had been developed assuming the local access (and thus <1ms latency), so it had a ton of N+1 everywhere.
This made it almost impossible to migrate/transition to another configuration.
So, if this style of app hosting doesn't take off and you're at all worried about this being a dead end storage once you reach a certain scale, I'd recommend not doing this, otherwise your options will be very limited.
Then again - I bet you could get very very far on a single box, so maybe it'd be a non factor! :)
Rails went through a down period 2014-2020 due to several reasons:
1. React burst on the scene in 2014
2. the hyperscale FANG companies were dominating the architecture meta with microservices, tooling etc, which worked for them at 500+ engineers, but made no sense for smaller companies.
3. there was a growing perception that "Rails doesn't scale" as selection bias kicked in - companies that successfully used rails to grow their companies, then were big enough to justify migrating off to microservices, or whatever.
4. Basecamp got caught up in the DEI battles and got a ton of bad press at the height of it.
5. Ruby was legitimately seen as slow.
The big companies that stuck with Rails (GH, Shopify, Gitlab, etc, etc) did a ton of work to fix Ruby perf, and it shows. Shopify in particular deserves an enormous amount of credit for keeping Ruby and Rails going. Their continued existence proves that Rails does, in fact, scale.
Also the meta - tech-architecture and otherwise - seems to be turning back to DHH's favor, make of that what you will.
I had a bad experience with Action Cable + Redis (extremely high memory overhead, tons of dead redis connections), so it's a bit "fool me once" with regard to action cables.
The main argument for caching in the DB (the slight increase in latency going from in-memory->DB-in-memroy is more than countered by the DB's cheapness of cache space allowing you to have tons more cache) is one of those brilliant ideas that I would like to try at some point.
Solid job - i just am 100% happy with Sidekiq at this point, I don't understand why I'd switch and introduce potential instability/issues.
This person is a skilled writer. Part of that skill is developing a unique voice and style. The AI can identify that - and while that’s certainly impressive because it can identify even relatively niche authors, it has nothing to do with a wider capability to deanonymize people based on arbitrary written text (ex Facebook or text messages).
If you are a professional musician, it’s not difficult to identify a well known musician / recording after listening to only a few seconds - whether they’re playing Bach or Rachmaninov, the style is just “them” - this is the same thing. But you couldn’t take some anonymous high school musician and guess who they were, even if they were your student - the median quickly regresses towards a homogenous, non-distinct style / voice.