6,875 karma · joined January 28, 2012
Nothing against Python, but of all the reasons to choose a technology, whatever is more represented on the dataset of some LLM is the worst reason.
This is a death spiral. There's no hope for the future of this industry if newcomers are thinking like this.
This [1] type of control doesn't require taking eyes out the road to adjust temp, fan speed and fan direction. Since it's a simple fscking knob, it can be adjusted by feel alone, and both the clicks and the angle give feedback on what setting it is.
The suggested solution is bad, for these reasons:
It tries to be clever by providing the lost "clickness" with haptic feedback, but it still misses the most important feedback, which is the angle of the knob. So it still requires you take eyes out of the road to see the setting you're in.
It also commits one of the cardinal sins of good UI, which is being a modal control. So, again, you need to take eyes out of the road and keep clicking to put in the right setting.
[1] https://i0.wp.com/weberbrothersauto.s3.amazonaws.com/2022/12...
I guess this is the equivalent of the soundboard.
Nubank offers consumer credit (credit card, personal loans), but you're comparing portfolios that include mortgages, large companies, industry, agriculture, etc.
Similarly, the default rate of the entire portfolio varies according to the product mix, so you can't compare that way.
I have also seen a scheme where you store the hash, and have a separate lookup table for sensible data, that you can redact more easily without messing with the log.
Depending on the data model of your log, if calculating the current state is a commutative operation, I think it's fair to call it a "ledger".
That’s why I stressed it’s an opinion piece but no data. Unfortunately in this industry we have a lot of experience reports, but lack actual data on what is or isn’t more effective way to work.
I get it, every software engineer has strong opinions, but that’s a weak one. If you think writing a lot of code to see what sticks is the job description, you’ll be replaced by GPT in no time - it can do it faster and cheaper. The challenge is always in getting alignment on what should be built, you won’t code your way out of that.
The true reason it’s so cheap and available, is subsidies. $7 trillion as of 2023, to be exact.
Without subsidies, using a non-renewable, expensive to harvest resource, to produce single-use plastic would be an absolutely irrational decision.
https://www.imf.org/en/Blogs/Articles/2023/08/24/fossil-fuel...
IMO, reading “SELECT employee.first_name” makes much more sense than “SELECT staff.first_name”.
Productive land, specially timber, is a good way of capturing CO2, because it will end up stored in products.
We tend to naively think we should reforest land and leave it there, and it can be good for other reasons, but is a poor strategy for carbon capture. We need to _aggressively_ go back to using timber and vegetable fibers as construction material, instead of concrete and steel that have an enormous carbon footprint.
I'm from South America, and my grandma's house had: mango, peach, lime, orange, grapevine, berries, coconut, jaboticaba, pitanga, acerola, atemoia (native fruits), and many types of spices (including a bay laurel tree). All that in a lot that barely parked 3 cars.
Then, 19th century middle-class, in an attempt to look wealthier and having no personality whatsoever, replicated the trend on their tiny lots, even though they owned much less land, and keeping a lawn is a financial burden.
Nowadays, there's so much profit in this space (equipment, herbicides, etc) that there's an immense marketing budget to keep the status quo.
That's why it's important to learn your history. Good to see this trend reversing.
The important thing is not having money go missing.