Their video player is also garbage, especially on mobile. I'll have to open and close a video multiple times to get it to play, the quality will take a nosedive midway through and just stay that way for the rest of the video, and they take forever to load.
I had this same issue in Redshift and ended up populating a table with values 1 to the maximum number of commas found (e.g. using max(regexp_count(...)) or something), then cross joining on the table with the csv column and calling split_part on the corresponding column and index (with the index coming from the numbers table). The cross join ensures that you index every value of the csv column.
What does "X for white people" look like though? The only reason that "X for black people" exists is that black people are a minority group and aren't sufficiently catered to by X, which is already more or less "X for white people" by default, at least in the US and much of Europe. As such, any product that that markets itself explicitly to white people (again, only referencing the US and Europe here) is much more likely to have less socially acceptable intent behind it
"X for white people" makes more sense in a population where caucasians are the minority, for instance in China.
> What does "X for white people" look like though?
Totally hypothetical example... "NBA for white people" - basically majority-white professional basketball teams playing each other. I'm sure that would ignite a firestorm if someone tried to do that.
But what would the justification be for setting up such a league? "Netflix for black people" is a representation of cultural differences and seeing those differences reflected on screen. "NBA for white people" would just be... excluding non-white people. White and black basketball players aren't different physically (on average) nor do they typically have different playing styles. There isn't really a lot of justification in such a division, hence why it would result in a firestorm.
Fair point. How about "Rap for white people" - a record label that only features white rappers for people that want to hear more suburban white-America culture expressed through rap? Still might ignite a firestorm, all it takes is one media outlet framing it as racist.
It might ignite a firestorm but this might too on more right wing channels (e.g. Breitbart), it's just that those channels aren't as represented in "mainstream" media
You deny reality --"White and black basketball players aren't different physically"
seriously? The only reason blacks dominate bball is bc they are different physically.
The same for why we have women's sports that exclude men.
The reason why blacks need to create X for blacks is often because they can't compete without it, which just means yes groups on avg are different.
Whites can't compete with black bball players.
Groups on average are different.
So yes, I can see why there is a reason and market for a NBA for whites.
Given the cost of developing a single drug can be in the billions of dollars, what financial incentive is there for companies to spend so much on R&D and clinical development if there is no commercial exclusivity rights at the end of the pipeline? You could nationalise drug development but that is a lot of risk to burden the taxpayer with.
What financial incentive is there for drug companies to ever cure anything when instead they can just develop drugs that alleviate symptoms, which you must then purchase in-perpetuity?
This is the best retort. I'm going to start using this, thanks.
The one I usually go with is "It actually costs $1T to develop a drug. $999B in basic research paid by US taxpayers and $1B in just enough frivolous novelty for the bigpharma company to get a patent racket going".
At least in the UK, sandwiches are the most that pharma reps can use to bribe doctors with... Which is not to say they aren't effective (you'll get butts in chairs at least, no guarantee they will pay any attention to you though).
Damned bribery and corruption act. I could really do with some free holidays and lavish parties. Now it's all branded mugs and that's your lot. Someone offered us free beer and we had to refuse. Oh, the humanity!
I think an important distinction to make is your use of the word "language", and how we think of language as it concerns human minds, and as it concerns GPT-3.
In our heads, language is a combination of words and concepts, and knowledge can be encoded by making connections between concepts, not simply words. If there is no concept or idea backing up the words, it can hardly be called knowledge. Consider the case of the man who did not speak French, yet memorised a French dictionary, and subsequently went on to win a Scrabble competition. Just because he knows the words, would you say he knows the language?
A language model such as GPT-3 operates only on words, not concepts. It can make connections between words on the basis of statistical correlations, but has no capacity for encoding concepts, and therefore cannot "know" anything.
> In our heads, language is a combination of words and concepts, and knowledge can be encoded by making connections between concepts, not simply words. If there is no concept or idea backing up the words, it can hardly be called knowledge.
Great point.
> A language model such as GPT-3 operates only on words, not concepts. It can make connections between words on the basis of statistical correlations, but has no capacity for encoding concepts, and therefore cannot "know" anything.
Are you sure? Aren't "concepts" encoded in how language is used, at least to some degree?
LeCun does say that models that explicitly attempt represent knowledge perform better than GPT-3 in terms of answering questions. I'm no expert but I believe him.
>Aren’t “concepts” encoded in how language is used, at least to some degree?
Good point and I think this shows up to the extent different languages might affect how we express particular concepts.
However I think it is more accurate to say that language solidifies and gives form to how we express concepts and the “concepts” themselves are independent of languages. Only our “expression” of these “concepts” depends on language.
For anyone interested in art and art history, this distinction was the central focus of the French surrealist painter Rene Magritte.
Language is how we store our knowledge, and language is a system of words. If a language model contains all the possible sentences you can say, it will complete any of your sentences, don't you think it knows what you know? The input is sequence of characters, so you can say it may or may not operate on words. It can operate on subwords, words or phrases where it see fit.
I like to think intelligence as clouds. If you dig deep down, they are just droplets, there are so many of them, they can appear to be so many different shapes. And they look complete different. Maybe intelligence is the same.
The "handwriting" data for this model is basically the coordinates of a pen. The length of the string representation of the text is very different from the length of the coordinate representation of the text, therefore the model "learns" a window corresponding to when it is drawing the current letter, and when to start the next letter. For these letters, as the model doesn't learn how long this window should be, nor how to transition from it to the next letter, it gets stuck and outputs nonsense.
The problem is that the prior appears to be placed over the school, rather than the individual -- ie if your school had a low proportion of high achievers in previous years, students are finding their grades marked down, almost regardless of their performance. This results in particularly high grade disparity between independent and state schools. So it is not so much the case that good students get good marks, bad students get bad marks, but rather good schools get good marks, "bad" schools get bad marks.
Because mark inflation is a thing, and schools are different. There are schools that will give out A+ and others a B, for the same academic performance. School reputations don't change from year to year. So a school that inflates marks one year, will more than likely inflate them the next year. Are you suggesting that this should not be taken into consideration? That you should simply trust the relative weight of grade (relative to all the other schools) at face-value?
>"bad" schools get bad marks.
Why the quotes? There are schools that are at the bottom of academic rankings. That's a fact of reality.
>students are finding their grades marked down, almost regardless of their performance.
What numbers are we talking about here? No matter what algorithm or heuristic they chose, some unfairness was going to happen and my argument is that these cases are overstated. I'm sure they exist because we're talking about hundreds of thousands of students all in different circumstances. Having said that, in cases of egregious outcome, an appeals process would make sense. Also I'm sure many universities will take the pandemic into consideration and the fact that this was a best attempt at replicating standardizing test result without a test actually being taken.
Right. A levels were not written so a statistical model was created to approximate A level results based on prior performance of applicants correlated with their school and course marks. Yeah, I get all that. It changes nothing about my argument.
