Firstly, the term “globalists” is an anti-Semitic dogwhistle. Beyond that usage, it’s meaningless.
Secondly, YouTube is riddled with disinformation. This is primarily due to the algorithm which drives receptive users to extremist videos (and skeptical users who might refute those videos away from them). It’s also because it’s a lot more difficult to fact-check spoken language than written language.
To my knowledge, Reddit is owned by private companies and investors. Blackrock and Vanguard have no ownership stake, or a very small and very indirect ownership stake.
For what it’s worth, a significant percentage of every (reasonably liquid) public company on Earth is owned by Vanguard and Blackrock, because those companies manage trillions of dollars in assets (many of which are middle-class people’s retirement investments). They aren’t a conspiracy. They’re asset managers, and mostly passive managers at that.
For now, we’re special.
LLMs are far more training data-intensive, hardware-intensive, and energy-intensive than a human brain. They’re still very much a brute-force method of getting computers to work with language.
Also, how you know it read the book, and not a summary of it, of which there are loads on the internet?
In the case of ChatGPT, it’s hard to tell. OpenAI won’t even reveal what their training dataset was.
Researchers have done some tests to tease this out, and they’re pretty confident that it has read quite a few books and memorized them verbatim. See one of my favorite papers in a while, Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4.
AIs are trained for the equivalent of thousands of human lifetimes (if not more). There’s no precedent for anything like this.
There are a few reasons why music models haven’t exploded the way that large-language models and generative image models have. Maybe the strength of the copyright-holders is part of it, but I think that the technical issues are a bigger obstacle right now.
Generative models are extremely data-inefficient. The Internet is loaded with text and images, but there isn’t as much music.
Language and vision are the two problems that machine learning researchers have been obsessed with for decades. They built up “good” datasets for these problems and “good” benchmarks for models. They also did a lot of work on figuring out how to encode these types of data to make them easier for machine learning models. (I’m particularly thinking of all of the research done on word embeddings, which are still pivotal to large language models.)
Even still, there are fairly impressive models for generative music.
Not OP, but I do like coffee.
I like to have one or two monthly “roaster’s choice” subscriptions. This way, I get to try something a little different every few weeks.
I’ve enjoyed Black and White, Intelligentsia, and Sey so far.
That’s one of the reasons why I joined this instance instead of any of the others.
The idea has definitely come up that there’s an association between the “globalist” pejorative and anti-Semitism (globalism -> conspiracy that secretly controls the world -> Jewish conspiracy), but it’s not as cut and dry as I thought.
Relevant Wikipedia entry about new anti-Semitism