> US tech companies are about to be used as the biggest punching bag in history by the European Union. They’ll negotiate first, for sure, because that’s what the EU likes to do, but for sure the fines and reciprocal non-tariff barriers are going to only expand for US tech firms in the very near future if the Trump admin doesn’t want to negotiate.
For sure this will happen but there is a reason. The EU turned a blind eye on a lot of dark patterns used by the biggest players (such as lenient approach to scams that are omnipresent on Facebook, Instagram, Google platforms) and whatever these companies did they knew they might get a slap on the wrist maximum. Now that good relations are over, why would the EU tolerate this shit?
Its errors are interesting (averaging around one per paragraph). Semantically-correct, but wrong on precision (simple example, the English word "ardour" is transcripted as "ardor", and a foreign word like "palazzo" which is intended to remain so, is translated to "palace"). I'm still messing with temp/presence/frequency/top-p/top-k/prompting to see if I can squeeze some more precision out of it, but I'm running out of time.
Not sure if it matters but I exported a PDF page as a PNG with 200dpi resolution, and used that.
It seems like it's reading the text but getting the details wrong.
I would not be comfortable using this in an official capacity without more accuracy. I could see using this for words that another OCR system is uncertain about, though, as a fallback.
That's why in Europe there are strict laws regarding lax security of customer data and companies can be fined with a percentage of their turnover - which in the case of Oracle could hurt a bit.
Can someone explain it to me what the hackers actually meant and what the school is supposed to do? Mistreat these Asian kids with stern parents who force them to study until late night - because what? I believe it's barking up the wrong tree.
If you look at % breakdowns of elite universities now (though I sort of hesitate to include NYU in that bucket..), one of the biggest / fastest growing groups would be how many foreign nationals they admit now vs 10/20/30 years ago.
For a lot of these schools, foreign admissions are a big economic contributor because foreign nationals pay full freight (plus sometimes additional costs/fees). From wikipedia in 2022 the largest racial group at NYU was actually foreign nationals at 24%, with current estimates as high as 28%.
After that the remaining 76%, the biggest groups are - 23% White & 19% Asian anyway. If you decompose the foreign national numbers down, they are majority European & Asian country of origin. From some light googling, it would seem 15% of NYU students are Chinese & Indian nationals, above and beyond the 19% Asian American. So overall its hard to see admissions as being terribly discriminatory in this particular regard at NYU..
Give me one reason to use a closed-source Redis alternative rather than one of many open ones, starting with KeyDB. If I wanted a closed clone, I'd probably go with DragonflyDB (whose license is "feel free to run it in production unless you offer it as a managed redis service").
Why not both?
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