How is your explanation simple and where is the data to back that? This theory isn’t crackpot, global sperm rates are declining, the average testosterone of men is lower than it was during your grand-fathers time. Certain plastics have been shown to be endocrine disrupters.
Your theory might work in westernized countries but this trend is global according to the article, certain countries enforce more traditional values for men and women and those countries are also seeing a decline.
I never understand this argument, we have lots of space on this planet for humans, it’s the industrialization that’s harming the planet not more people
This is pure speculation, but I wonder if endocrine disrupters present in plastics are leading to a decline in testosterone and therefore decline in fertility (I also wonder how those disrupters affect women)
Projections and forecasts for entire sectors use the data to make decisions, for example China built so many homes in projections of population / census estimates, their source data turned out to be incorrect that’s why you see a situation like Evergrande.
A well known very large successful trillion dollar company emphasizes this heavily and it’s called identifying Cause By, regressions are categorized before a build is submitted, in the current build, or in previous builds. It’s extremely important to identify cause by (commit) in order to either revert or fix.
I actually quite liked Radar, the focus on Radar hygiene, finding cause-bys, diagnosis, discussion comments and attached sysdiagnose reports were quite helpful compared to previous companies I worked at.
But you are right there were moments in my time there where just by looking at the build configuration I could rule out an issue immediately
[0] abort()
[1] call-site 1
[2] call-site 2 <actual place of issue>
[3] call-site 3
Dealt with this enough at a previous company I’m glad on my team at FAANG people are reasonable and don’t just shoehorn functional paradigms unnecessarily
While I find these topics esoteric and very interesting in normal day to day code during a code review I’d probably say make it less complex, because majority of the time spent is reading code this makes code harder to read
The feedback loop needs to be very small, from thought to insight, to storage, to retrieval at a later time. Probably the best is maybe audio => transcription => storage The audio => transcription UX isn’t too great at the moment
Edit: I should add the BEST experience here is direct thought => storage => retrieval
This is how our brains work but we need a module extender for our brain when we are doing a fuzzy search
During the first year of COVID in San Francisco I had a date with a girl who I found completely annoying, she was rude to the waiting staff and insisted on finding “sugar daddy.” I couldn’t believe I was listening to the delusional beliefs this woman had, especially regarding she lied to me about her career after I sat down with her.
I told her exactly how I felt about her and that she really needs to fix her attitude towards people and men, and that I’m done with the date. I left, and never contacted her again.
Coincidentally the next day my tinder account got flagged and banned. I knew it was something to do with her and she was spiteful (though I couldn’t prove it), but the timing was impeccable. Someone had filed a report against me and the automation system at Tinder wouldn’t allow me to speak to anyone.
I couldn’t find a partner and every bar / club / restaurant / location in the city was closed for MONTHS! Tinder was literally exiling me to my room and closing off dating matches (I realize there are other apps but the pool is huge on tinder and I always found the most matches there and best outcomes for my lifestyle).
I think this should be against some policy or something. If folks just understood the isolation I felt those months, going from meeting women every week to 0 was very bad on my mental state.
1. Why use Postgres distributed cluster vs say an incremental store that supports real time data like Materialize? A streaming database sounds like the right use case for your requirements no? Under 1 min real time latency? Is Postgres distributed able to do it efficiently? (Never tried Postgres dist.)
2. Why use typescript at all? Pick a language that actually enforces class validation and enforces type validation baked into the language itself (like Rust or Go)? Sounds like programmer error is root cause of issue that should be looked into as a mitigation step (add real class validation at the minimum)
3. Regarding audit tables, are you also keeping audit tables for user and events tables too? That would seem… excessive and now duplicated data (especially billions of rows). Doesn’t the database come with audit tables baked into it?
If you scrolled down in the link provided above, it mentions with BOTH Standard and Advanced data protection messages are end to end encrypted, it’s just with advanced data protection the encryption key also ends up being encrypted too, but I’m positive even this has changed recently. You can try looking at logs when you turn on messages in iCloud and see that your messages are encrypted.
So lots of confusion in this thread, my advice for Apple would be make it very very clear to users that your data is safe. I mean they are threatening to back out of UK, so it’s against their core principles and also probably very technically expensive to undo they end to end encrypted system.