1. Technical interview prep companies give structured learning and practice to people that aren't good with structure.
2. Algorithm technical interviews provide a structure for companies to compare skill levels of different candidates against each other
3. Neither is the best scenario for either party but in a chaotic world without structure, each one is trying the best they can towards filling a job role by meeting with someone in a span of 45 minutes.
Personally as a founder of an interview prep company for data scientist (https://www.interviewquery.com/), I find that we try to just teach candidates concepts through bite-sized problems and repetition. Some people might hate it, but we're essentially playing the game that the companies are holding up. So you might as well learn to get good at it.
Exactly. Let's say that MarketRank grows in market share to be the dominant search engine. What's to stop someone from then gaming Reddit / HackerNews posts and comments with bots and fake accounts because the operator understands that these websites now have "community verified rank importance"?
They're already gamed or easily gamed. You can buy Reddit accounts with high amounts of karma which are sold to people who are trying to do "astroturf" promotions.
Is there a way to calculate exactly how much this affects the every day person? Specifically what I'm looking for is a table breaking down the costs by category.
For example - I don't really drive that much on a day to day basis compared to the average American, and so if it's a huge 50% increase in gas prices yoy, that over indexes the inflation number for me because I might drive 80% less than the average American. So I would assume that inflation is really <7.9% for me.
Inflation rates tend to be calculated from the average on many different things. So it can be tricky to understand how much it's really affecting. Imagine it like this: if it only was measuring for the prices of potatoes and gas, and potatoes went up by 2.5% and gas did the same by 7.5%, then the inflation would be like 5% but it's not clear
Source: In my country, the government forces some product prices to be limited so they can trick us in to believing that the problem is smaller than it actually is
I think U.S. News Ranking only really has merit because it's been around for a long time and has also done a good job of transferring its brand into good SEO.
It's incredibly easy to be a niche influencer nowadays. If I write a blog post on a niche subject that I know a lot about, I can easily take that blog post, re-word it a bit, and record it for Youtube with some light edits -> example data science account: https://www.youtube.com/channel/UCcQx1UnmorvmSEZef4X7-6g
Youtube recommendation algorithm is so good at rewarding continuous creators. The difficulty is that the effort in making videos is surprisingly high and scaling is hard.
The garbage in garbage out cascading failure generally seems to crash pretty fast. Given the U.S. is a capitalistic society the companies / institutions that do this and don't achieve their goals through data science should be apparent and then fail accordingly.
The trail of devastation left by this process, in financial and human terms, when medical systems go awry or vendors to state judicial systems wrongly convict innocent people.
I agree about your latter example, but about your first example: isn't it the case that these faulty AI systems for medical diagnosis have been rejected? Doctors don't like them because they don't want to be replaced or one-upped, and because they just don't trust them (rightly so, as it turns out). So the systems, which were put out for use on a trial basis, don't get used.
Best optimization of weather conditions has to be seasonal. Seattle and Portland may be horrible 8 months out of the year but the summer months are quite perfect.
What I want to know are which cities are great seasonal cities in which I could potentially buy a condo for the high seasons, and then leave in the non-high seasons for a potential rental at a still competitive price.
For example: SF sucks in the summer, but maybe the tourists don't know that.
SF has microclimates and for my preferences the southeastern part of the city (the Mission, Potrero Hill, Dogpatch) have perfect summers. Highs of 65-75, and then at night the fog comes and cools things down for perfect sleep temperatures. On the western side of the city it’s just fog all day.
Plus it’s always an impressive sight to see the fog come over the hills every day.
> For example: SF sucks in the summer, but maybe the tourists don't know that.
Actual SF, or surrounding areas? I would think SF is fairly nice in the summer with the ocean breeze. Sonoma county gets pretty warm in the summer as well, but SF proper always felt cooler to me. I can imagine San Jose being just as bad or worse though.
You do have the probably apocryphal Mark Twain "The coldest winter I ever spent was a summer in San Francisco." And you can really get the cold, grey city vibe. But, honestly for the most part, it's hard to find a lot of fault (for me) in SF climate most of the year. And I've spent a lot of time there even if I've never lived there.
ADDED: And I wouldn't think most people would think anything in NoCal generally (or most of CA even more generally) "sucked" in the summer
> I wouldn't think most people would think anything in NoCal generally (or most of CA even more generally) "sucked" in the summer
Eh, week or longer periods of temperatures in the high 90's and low 100's when you're not at the coast isn't always pleasant, I could see how some people think it sucks, depending on how much you're required to be outside. It gets hotter the farther north and more inland you go for a while (even if you don't have to go inland much).
In the end a lot is just what you're used to, I think.
The excessive summer sun is actually a bug not a feature, especially if you factor in the diminished air quality with increased forest fires. Last summer everybody I know chaired when the rains finally came and cleared the air from all the particulates.
Actually IMO the PNW would have a pretty sweet overall weather if only it would rain just a little more in the summer (say once a week / every two weeks).
Being able to test this and change on the fly when you get the data also makes a huge impact in terms of how much revenue you're able to generate during these critical periods.
2. Algorithm technical interviews provide a structure for companies to compare skill levels of different candidates against each other
3. Neither is the best scenario for either party but in a chaotic world without structure, each one is trying the best they can towards filling a job role by meeting with someone in a span of 45 minutes.
Personally as a founder of an interview prep company for data scientist (https://www.interviewquery.com/), I find that we try to just teach candidates concepts through bite-sized problems and repetition. Some people might hate it, but we're essentially playing the game that the companies are holding up. So you might as well learn to get good at it.