933 karma · joined April 12, 2016
The argument is that there is no infinite amount of _anything_. That is a fictional concept of 'too many parts to count'.
When you are trying to solve a crime, you only know that the murderer was a nurse, it's very important to assume a valid p(murderer|gender) as well as p(gender|nurse).
On the other hand, leaking p(gender|nurse) into a candidate scoring algorithm would be a no-no.
What people seem to ask for is very interesting actually. To both learn the underlying statistics AND learn not to use it explicitly in speech at the same time. Assuming next token prediction is the learned function, these two feel a bit contradictory.
It's completely valid to assume that in 'paralegal married a lawyer because she was pregnant' the lawyer is a man.
That's not a negative gender bias but rather a good educated guess, is it not?
It's not like the model would say that woman can not be lawyers.
I remember seeing that aired live on the national TV. Fun times.
https://www.nytimes.com/2008/01/24/arts/design/24abroad.html
On the other hand, why we use digital hardware precisely because it's robust against the noise present in the hardware analog circuits.
Closed apps running in background are like services. I do not need the window to be rendered in the background for messages or chat apps. I open them only when needed. Or having a large-ish apps I use on daily basis preloaded in compressed memory. It's just a sensible workflow.
- the first act was not so slow and boring, failing to actually introduce the characters - the finale was not so dumb...
At first I felt a little bored. At the end I was disappointed. Only the middle of the movie was kinda fun.
Maybe use a zoomed example on mobile?
I thought Musk got spoiled under the influence of his success. He might have been a bad apple all along. :(
https://mezha.media/en/2022/10/06/google-is-working-on-image...
Give it some time and SD will be able to do the same.
Heck, it could be even better, since your "mental" age based on your interests in movies could be more suitable for delivering ads then your actual age.
https://www.nytimes.com/2018/08/03/business/donor-advised-fu...
How cool it is to discuss these kind of issues? What do you think about the "erasing open source community" argument from the historical perspective? What does it have in common with industrial revolution?
Even though the real life implications are real, I find it fascinating and not so simple to unravel.
[1] https://en.wikibooks.org/wiki/Professionalism/The_Nestlé_Inf...