1,663 karma · joined July 18, 2013
This is not an apt description of the system that insists the doctor is the mother of the boy involved in a car accident when elementary understanding of English and very little logic show that answer to be obviously wrong.
It reduced life expectancy for people who were alive in 2019. Those statistics say nothing about the life expectancy of people who are currently alive.
This is not what I’d describe as “fighting your insurance”.
What's up with Portuguese and Poland? (Millennium, Biedronka, what else?)
The word "craque" in Portuguese was borrowed from English with the "exceptional" definition and is commonly used. Given how many Brazilian players there are in the top leagues, I wouldn't be surprised if it was commonly used by football players in general.
I understood how to do arithmetic for numbers with multiple digits before I was taught a "procedure". Also, I am not even sure what you mean by "memorization is how you learned fractions". What is there to memorize?
I mean, not totally unthinkable, thankfully. That's the only reason we have the Carlos Ghosn Hollywood-esque escape story.
100k+ has been close to the floor for entry level for a while now. Did you do the math on how much you'd earn over 10 years?
Inventing merge sort is not a particularly impressive intellectual achievement.
MATLAB is a proprietary computing platform with its own language that was very widely used (and probably still the standard in some fields of engineering). The fact that it is proprietary and the language is not great as a general programming language were significant drawbacks to wide adoption.
As far as ML is concerned, the deep learning revolution happened when Python was the dominant language for scientific computing (mostly due to NumPy and SciPy), so naturally a lot of the ecosystem was built to have Python as the main (scripting) language. The rest is history.
As far as "attempts to recreate similar ecosystem":
PyTorch (currently the most popular deep learning framework), was originally Torch (initial release: 2002 - long before "Deep Learning" was a thing) with Lua as the scripting language. Python's momentum in 2010's meant that eventually it was rewritten in Python thus becoming PyTorch.
Julia language is a famous somewhat recent example (first release 2012, stable 1.0 in 2018) of a language that was built partially to address some of Python's shortcomings and to "replace" it as the default for scientific computing. It didn't succeed - it's hard to move people away from an ecosystem with so much head start and momentum as Python had in the 2010s.
I've never worked with any of these, but that's what I would expect as well. API documentation that describes how to solve each kind of mathematical optimization problem.
Do you have an example of an optimization solver with API documentation for business SMEs?
Why?
Some people, yes. Not all. I would say this attitude does not correlate with intelligence/wisdom.
> And that was when reality slapped me really hard for the first time on my face.
These two consecutive paragraphs seem contradictory.
I am sorry to say, this is just not true.
> but having a few dozen solutions already memorized should let you do some pattern recognition
Chess opening memorization is pure "remember the moves, play the moves" that's it. No thinking or pattern recognition involved.
If this is about being able to solve problems by generalizing from having seen a few dozen solutions, then I don't think "memorizing" is the appropriate term here, at all.
The comment I replied to claimed that "LLMs would do pretty well at leetcode interviews". OpenAIs own report [0] shows how GPT-4 fails miserably at medium/hard leetcode problems that are not in the training data.
Hearing some people, you'd think they ask you to memorize chess openings or something.