Fast, cheap or good. Pick two.
It seems like they've been prioritizing fast (lots of planes) and cheap (low staffing, outdated equipment) and paying lip service to good (safety).
We're trying to hire an Angular design engineer, so now the recruiter is the person trying to get management to switch to React to make his search easier. The tech doesn't matter too much, but the market forces do.
An issue I've noticed with court imposed fines is that they seem to be set based on the cost of the incident involved, not relative to the finances of the org/person being fined. A pipeline is very expensive, so fines end up being very expensive regardless of the receiver's ability to pay. OTOH, a large company can destroy lives with impunity since the cost of a person's entire lifetime earnings is not material to a multinational corporation's bottom line. This seems backwards to me. Fines should be set in such a way as to properly disincentivize behavior and adjusted to the means of the person/organization paying them.
I'd love to see the training data open sourced for all models so we can be sure no copyright material has been used. Just kidding, we all know it's stolen.
Lots of people have mentioned Polars' sane API as the main reason to favor it, but the other crucial reason for us is that it's based on Apache Arrow. That allows us to use it where it's the best tool and then switch to whatever else we need when it isn't.
People here don't seem to realize the importance of Canadian content rules in maintaining a cohesive national identity and supporting local content producers. The overwhelming barrage of U.S. media necessitates funding the creation of Canadian content, artists and points of view.
A writer with a long history of published works probably had their works in the LLM training data. This would lead to LLMs duplicating their writing and thus their new work being classified as written by AI.
I'd like to see a weight tax on vehicles. Lighter vehicles have less tire wear, so less pollution. They also require less energy to move, so less emissions. Plus lighter vehicles would improve pedestrian safety.
I don't see the point of this acquisition. The products don't compete, so it's not eliminating market competition. The products also don't 'synergize' (ugh) well: they target different market demographics, have separate learning curves and different business models. Why?
1. Yes, that's reasonable and saves running another DB
2. You often can perform the embedding in the DB, but there are a lot of use cases where you want to manage your embedding models outside the DB. This way you aren't dependent on which models the DB supports and you don't duplicate them throughout your system
My main issue with pretty much all queue approaches is that they don't work across platforms. They are built for one technology stack, be it Python/NodeJS/etc. This is fine if you've only got one stack, but in a microservices world it doesn't work where jobs can span multiple systems. You might be able to find some abandoned library that supports that queue tech on the other platforms you need, but now you've basically become a queue tech maintainer.