This is accurate and the parent commenter here seems to be echoing a common misconception. Either they are confused or they need to elaborate more to demonstrate that they have a valid complaint.
For instance, this would have been a valid complaint:
"Users who don't need free threading will now suffer a performance penalty for their single-threaded code."
That is true. But if you are currently using multiple threads, code that was correct before will still be correct in the free threaded build, and code that was incorrect before will still be incorrect.
On the other hand, the authors make plenty of other great points -- about the fact that LLMs can produce bullshit, can be inaccurate, can be used for deception and other harms, are now a huge challenge for education.
The fact that they make many good points makes it all the more disappointing that they would taint their credibility with sloppy assertions!
The author makes this assertion about LLMs rather casually:
>They don’t engage in logical reasoning.
This is still a hotly debated question, but at this point the burden of proof is on the detractors. (To put it mildly, the famous "stochastic parrot" paper has not aged well.)
The claim above is certainly not something that should be stated as fact to a naive audience (i.e. the authors' intended audience in this case). Simply asserting it as they have done -- without acknowledging that many experts disagree -- undermines the authors' credibility to those who are less naive.
Gotta love the word “just” in that first paragraph.
The majority of the research money behind most (if not all) drugs, is spent well after academia’s contribution. Clinical trials are very costly, they usually fail, and yet they’re quite important!
If someone without the necessary expertise chimes in with an unhelpful answer within minutes of a question being asked, then everyone who comes after must check their answer before deciding if the user still needs help.
But even worse, I think potential responders on StackOverflow may not read the question at all because it will be listed as already having an answer. It won’t be an accepted answer, sure. But it still disincentivizes attention to the question. (I know it certainly disincentivizes me when I go looking for SO questions to answer.)
If a question has gone unanswered for hours or days, then sure — offer whatever advice you’ve got. But before then, you’re just adding noise, and actually reducing the chances that the OP will get what they were looking for.
It think the parent's point here could be rephrased like this:
Copyright law treats "involved a human" vs. "involved a machine" as fundamentally different just because humans are special-cased, not due to any deeper reason. Just by fiat.
The law gives special consideration to humans "just because". Therefore, if one situation involves a human in a particular role and another situation involves a machine, then there is no useful analogy to be drawn -- as far as the law is concerned. Even if the analogy makes perfect sense to you and me, the law treats humans and machines as fundamentally different, so all bets are off.
There are at least two potential issues pertaining to copyright law here, and it's not clear which one you're asking about. That's why the responses you're getting here seem to be answering different questions.
1. Are the AI systems violating the copyright protections of the images they were trained on? If so, are users of such AI systems also in violation of those copyrights when they create works derived from those training images?
Answer: That's not yet settled.
2. If you make an image with an AI system, is your new image eligible for copyright protection, or is it ineligible due to the "human authorship requirement"?
Answer: The US Copyright Office recently wrote[1] that your work is eligible for copyright if you altered it afterwards in a meaningful way. Here's a quote:
>When an AI technology determines the expressive elements of its output, the generated material is not the product of human authorship. As a result, that material is not protected by copyright and must be disclaimed in a registration application.
>In other cases, however, a work containing AI-generated material will also contain sufficient human authorship to support a copyright claim. For example, a human may select or arrange AI-generated material in a sufficiently creative way that “the resulting work as a whole constitutes an original work of authorship.” Or an artist may modify material originally generated by AI technology to such a degree that the modifications meet the standard for copyright protection.
You might already be advanced beyond high-level introductory material, but this short book chapter by Chris Lattner himself was a good read for me (a casual reader, not a compiler expert).
The answer is that once you’re able to definitively recognize it in at least one form, you’ll start to recognize similar, not quite identical forms.
The sapling form is not quite the same as the vine form, which is not quite the same as the very thick hairy vine that it eventually transforms into. But once you know one, you can start to recognize the others due to at least some parts of the plant matching what you already know. And then the other parts of the plant, which you hadn’t previously recognized as being how poison ivy can look, are added to your personal visual memory, too.
I don’t know, it’s hard to explain. It’s like if you saw a chihuahua and a Great Dane, you might not recognize them as being the same species. But if you see enough dogs in between, eventually you’ll see that they have something in common.
I'm afraid you have it exactly backwards. The problem isn't that it doesn't work -- the problem is that it does work. And to the extent that it isn't perfect, well, it's still improving all the time. You cited a 3-year-old article reporting on data from up to eleven(!) years ago -- an eternity in this field. Not even worth reading at this point.
The racial bias issue is still important for now, but it's fast becoming irrelevant. We should be asking ourselves where our priorities lie even if bias weren't a concern.
Some people like granular comments, and some people only want high-level comments. I’ve long suspected that both camps are correct, because they’re using different languages.
A single line of Python data analysis code is often worth 20 lines of C++. If you would be willing to add one comment per 20 lines in C++, then nearly every line of your pandas gobbledygook is worth commenting.
Terse code is good, but that doesn’t necessarily mean the comments should be terse (or absent).
According to Dmitry Kobak, some details in these figures are merely convergence artifacts, and no longer produced when using more recent versions of UMAP.
Many people will respond with the opposite answer they intend to convey. This is especially likely for non-native Engish speakers, but will also affect native speakers.
For instance, this would have been a valid complaint:
"Users who don't need free threading will now suffer a performance penalty for their single-threaded code."
That is true. But if you are currently using multiple threads, code that was correct before will still be correct in the free threaded build, and code that was incorrect before will still be incorrect.