Wikipedia is dominated by fairly left-wing people who try to portray any research about race differences in IQ as fringe. I would not regard their articles on these matters as reliable.
cubefox
Karma: 2,561
“Race realism” is a completely mainstream idea. People in the US routinely classify people by race, statistics do the same, medicine routinely also does so (while often using the synonym “ethnicity”) when it is medically relevant, approximately nobody doubts that “East Asian” people exist and are different from “Europeans” etc.
I don’t know what you mean exactly with HBD, but opinions on race differences in intelligence are in fact quite mainstream, in fact more so than many other fairly common beliefs, e.g. that eating meat is wrong.
Most people don’t donate to anyone, so this is not informative. We know that there is a heavy imbalance between left/right faculty in academia. For example, [29% of Harvard faculty say they are “very liberal”, while only 1% say they are “very conservative”](https://www.foxnews.com/media/fewer-harvard-faculty-members-identifying-liberal-although-staff-still-strongly-left-leaning-survey). [Many departments employ zero registered Republicans or show heavy imbalance in registered Democrat/Republican ratio.](https://www.ff.org/nearly-four-in-five-college-departments-dont-employ-a-single-conservative/) [Journalists also heavily lean left.](https://www.mediaite.com/media/news/study-finds-that-just-3-4-of-american-journalists-are-republicans/)
Richard’s views, whether you agree with them or not, are very controversial
They are very controversial only for certain subgroups like academics, who are far more left-wing than the general population, but not for the general population itself.
Without going into the object level, per your own number, “the 35% most extreme members of the ideological camp you disagree with are being outright reprehensible” doesn’t seem like an insane thing to believe at all?
If we assume the camps (left/right) are split 50⁄50, then it would follow that 35% (35% of 50%, the 17.5% most left-wing plus most right-wing fraction) of the population “are being outright reprehensible”, i.e. more than a third of the entire population. That seems to be a rather extreme view.
For example, most academics and journalists are far more left-wing than the general population, so most of them would fall into the 17.5% (35% of 50%) of the most left-wing fraction of the population. Therefore, most academics would be “outright reprehensible” according to your view.
Taking out soft contact lenses can be a lot harder for very short slighted people because the lenses are thicker and less flexible.
An unrelated point: these pictures seem obviously bad. They look like children’s drawings, or drawings of a random amateur. The artist is blind, so this is understandable, but it doesn’t make the end result any better. It seems that the museum is more interested in promoting certain artists who are deemed deserving of attention than in promoting good art.
The whole thing looks like a “The Emperor’s New Clothes” situation: High-brow curators and visitors looking respectfully at the stuff in front of them until some random kid (no doubt dragged in against its will) just says “this looks like shit and also weirdly perverted”.
Speculation: Are we perhaps already seeing the indirect effect of diffusion model art here? When photography was invented, artists pivoted to unrealistic art. Now with text-to-image models getting better and better, even technical drawing prowess for unrealistic art is becoming unimpressive. So artists and curators have to find the interesting aspects of art elsewhere, like in the unusual personality or circumstances of the artist.
Other examples: A Covid-19 pandemic also seemed intuitively highly implausible in early 2020 despite strong evidence that it could no longer be contained. Similarly with Russia being about to invade Ukraine in late 2021 / early 2022. There should be a term for this: *normal world bias*
A counterexample is a variant of the typical mind fallacy: if you perfectly understand something, it feels so obvious that you tend to forget what was not obvious before. So professors are regularly worse at explaining a difficult concept than teaching assistants: because the latter still know what makes it hard to understand.
This Twitter user is known for having an undisclosed method for accessing the CoT of OpenAI models. He sometimes posts snippets. Recent examples.
Well, if RL “really worked”, yes it seems like it should almost certainly invent and reason in an alien language.
What would be the advantage? Inventing new languages at least doesn’t seem to increase our reasoning ability compared to using existing ones. For example, it seems unlikely that people can reason better with any artificial languages like Esperanto or Interlingua (or Python, UML, etc) than with English. I would expect that if it were possible to artificially create a language that is substantially better for thinking than existing languages, we would have already created such a language.
Of course humans can also reason to a significant degree in latent space, without language, but latent reasoning (Neuralese) is different from reasoning in an artificial language (Thinkish).
From hovering I can see there are just three accuracy votes (for a total of −11) so far, so someone apparently used strong downvotes.
I didn’t mean to suggest otherwise. Probably bad wording.
The issues might already be present during SFT (instruction tuning), before any RLHF or RLVR is applied. Base models, being pure token predictors, don’t have a problem with faithfully extrapolating style, but they don’t reason and therefore can’t plan ahead very far, so any complex plots are out of reach.
Damn, you beat me to it by seven years.
I’m impressed that you managed to put a hyperlink inside your LaTeX.
A nice definition of “paradox”.
David Lewis famously observed that one man’s modus ponens is another man’s modus tollens. The first man argues:
While the second man argues:
But Lewis forgot about the third man:
each major government
Particularly the US government. Other governments will consider themselves lucky when they manage to convince the US government to get access to frontier models.
It was previously called a “zero-day exploit”. It referred to the time after a vulnerability was published for a corresponding exploit to appear. A zero-day exploit is one that appears together with the security vulnerability, leaving the software maintainer zero days to fix the vulnerability before anyone can exploit it.
Later people started to call security vulnerabilities for which a zero-day exploit exists “zero-day vulnerability” or just “zero day”.