1,090 karma · joined January 29, 2015
Email: zoltan dot vincze123 at gmail.com
LinkedIn: https://bit.ly/3Tkf7pS
The more you understand the real motivation of people the harder it gets to take business goals and decisions seriously.
And I think you are injecting the words "only", "there are" and "everything" here and there just to change the meaning of the sentences I quoted and I have written...
This resonates with my experience. I had the opportunity to work on a DS codebase written entirely in Scala with all the typing, parallelism, actor model, whatnot. Basically I joined the company because of this technical factor. It was fun until I figured out that DS was "typed IF-THEN-ELSE written by Java devs in Scala returning stuff the users complain about with high reliability within milliseconds". Now I am happy to be back to the single threaded untyped Python world. Still no bugs in production, because we validate all requests to death, have unit tests and integration tests running on real data not on mokups. Basically we follow the principle: if the integration test passes, our typing is just right, or at least good enough. Funnily all the typing errors we catch are caused by wrongly typed data, coming from the productive system written in a typed programming language... what a strange world.
A sentence, written by the author on, commented by me on and read by the HN community on devices, which exist only thanks to 80-90 years of rigorous, statistics based QA in engineering, especially in mechanical/hardware engineering.
Anyhow, after spending years on a team filled with social science PHDs, I would not waste my time on reading papers about statistical analysis done by social scientist.
This is based on the assumption that people want and can do their jobs well, or at all.
Lucky you, if this sounds strange to you.
The "only x room left with these conditions" false claim is used also in the EU.
This means that in the 5 households Nielsen used as a "representative sample of Seattle's population" one person got so overweight that he can't leave his flat any more and therefore he started buying his daily dose of soda online instead of buying it in his favourite store. Soda consumption drops by 20%. At least this is what Nielsen says. But hey, who am I to judge decades of financially successful quackery...
I wonder how a search engine could distinguish between "honest & professional" and "fake & amateur" headset reviews without having a head and two ears?
You should google up the story of the Swiss company Crypto AG Tl;dr; bought by the CIA and the BND (German counterpart) in 1970 and sold security software to governments all around the world. With built in backdoors for the CIA and BND. It was the main source of foreign intel for decades for the CIA.
An evil data scientist would put almost exclusively users on your screen who you are interested in but they are not interested in you to boost your spendings and would mix a small portion of good bidirectional matches just to make his purpose less obvious. Fortunately evil data scientists does not exist... I mean I definitely wasn't paid to do anything like that. Never.
I just imagine Moses saying "Who am I to question our being enslaved in Egypt, our society being organized this way, the order of things may reflect knowledge I may not have, hence I have to respect it. Let's just stay here, for ever."
Our society revolves around and is being organised by people challenging, bending or breaking social practices. If I have to choose, what to respect, I gonna respect this.
I always try to follow the rule-of-thumb of "if it can be done in the analytical DB, it should be done in the analytical DB". In my experience Oracle is pretty well suited for all of the "sorting, aggregation, discarding, merging, and splitting tasks". With proper indexing/partitioning processing 81M records shouldn't take 17 hours. Pulling all the data into python and then fighting the lack of (out-of-the-box) multi-threaded data processing capabilities seems to be part of the problem than of the solution.
In my current job if I have to do some analytical heavy lifting I just write the data to AWS S3 (parquet) and read the query-results back through AWS Athena (Presto) into python.
Nope, there are still some problems. It's not enough to be at the right space (=coordinates) at the right time, but you have to have both the right speed-vector and the right-acceleration vector, both compared to the universe (otherwise the milky way moves away from under your feet with galactic speed) and compared to your body (otherwise the speed/acceleration change will rip your body apart). And with right I mean 100% right, because we are talking about galactic speed and acceleration.