Other comments are wrong, its complicated residual structures on tv/movies.
blargerer
joined 2 years ago
‘My whole library is wiped out’: what it means to own movies and TV in the age of streaming services
You can probably throw together a pretty simple wordpress website without much knowledge. Just keep it mostly out of the box, maybe change the theme.
Nintendo president: “Game development will become even longer, more complex, and more sophisticated”
Have you ever worked on a game?
I don't think this is really viable. Maybe some sort of minimum lifetime.
He wants the resources being spent on graphics to be redirected to engineers and game designers. There is a reasonable top end budget to put towards any given game, so it is at least mostly 0 sum.
On a free service sure, on something you are paying for? fuck off.
This is a bit inaccurate. Some of his videos contained plagiarism, but they weren't written by James and were taken down as soon as it was pointed out. The source of the plagiarism was also not other youtubers, it was written movie articles. The writer in question no longer works for him. This was all made clear in the Hbomberguy video.
old school youtuber, one of the early big names. Got famous trashing on shitty old video games, but also occasionally did movie reviews, especially Monster Madness, in October where he'd review a bunch of horror movies. This is referencing how he said he wouldn't be reviewing the 2016 ghostbusters movie when it was announced. The media didn't really go nuts over him not reviewing it though.
We have almost no idea what the sequel looks like. Wait to see what risks it takes before judging.
Spewing bullshit as consistently as he does while still being believed by your core base is a rare skill set.
So, they are likely very poorly managed but, R&D is a common slushfund to keep your profit negative so you don't have to pay taxes.
I haven't read this article, but the one place machine learning is really really good, is narrowing down a really big solution space where false negatives and false positives are cheap. Frankly, I'm not sure how you'd go about training an AI to solve math problems, but if you could figure that out, it sounds roughly like it would fit the bill. You just need human verification as the final step, with the understanding that humans will rule out like 90% of the tries, but if you only need one success that's fine. As a real world example machine learning is routinely used in astronomy to narrow down candidate stars or galaxies from potentially millions of options to like 200 that can then undergo human review.