I’m working on https://www.dragondictionary.com, a Chinese-English dictionary aimed at Chinese learners. I am building it because there’s no good desktop alternative to Pleco at the moment.
The article doesn't explain what is actually going on to produce the second chart, but here is a guess. Assume people have a true ability x, an estimated ability y which is x + some unbiased noise, and a test score z which is also x + some unbiased noise. If you take a sample and collect the lowest quartile of test scores z, then the average of the estimated abilities y in that group is higher than z because the y are produced centered at x rather than centered at z. By collecting the lowest quartile of test scores, you didn't just get the dumbest people, you also got the people who happened to perform badly on the test that day. These people may be estimating their ability accurately, in which case the estimate would be higher than their randomly bad performance that day.
This seems like too obvious a mistake to not have been noticed for this long though.
Lowest test scores come from low ability plus bad luck and as such are lower than just low ability and highest test scores come from high ability and great luck and as such are higher than just high ability.
However, from my reading of the article they were asked to estimate their performance after they had already taken the test, not their inherent ability.
ML is a shiny object with often no discernible ROI but occasionally very large ROI, and companies are understandably nervous about missing out. Spending a small amount to hedge their bets isn't necessarily irrational.
"Awesome" and "Aweful" have similar etymologoies: both mean, "Inspiring or creating awe". But one has morphed into, "really good", and the other into "really bad".
This. It can be used more colloquially than the equivalent meaning of "terrible," where it's closer to something like "awesome." It can also generally used as a marker of intensity. In no case does it mean "bad at something."
The idea is that it gives a standard for semantic markup that can be read as plain text. Lists, highlighted text, block quotes, etc. that is all plain text but easily parsed by humans.
HTML emails are a blessing. Receiving them allows me the ability to quickly glance at an email from an unexpected sender and immediately recognize it as a marketing email or cold sales, and send it to the spam folder without needing to read a single word.
+1 I do this when doing 1-to-1 or 1-to-many calls. I look at the lens at the top of my laptop or the one in the meeting room when I am talking.
It means I can't see what others are doing and feels kinda weird just staring at a lens when talking, but in a world of people who don't make eye contact like this on video calls, I think it has a good amount of impact/gravitas.
Start offering a $99 course on how to profit from FB Libra. Doesn't matter if you don't know anything about it, because the people who buy shovels during a gold rush usually know even less.
Getting involved is risky - even if you are right (and I think you are), the price could still increase by a large amount for a long time before sense reasserts itself.
As Keynes apparently did not say: "The market can stay irrational a lot longer than you can stay solvent."
If you hit your trading / credit limits you could lose a lot of money despite being right in the long run.
And as Keynes definitely did say, "In the long run, we are all dead."
Ironically it may be to buy something like bitcoin and sell when it goes up. Reasoning: a) there are obviously hype believers who will buy and push the price up when optimistic and b) they tend not to sell being believers whereas as a skeptic you can.
