That reminds me of a joke.

A museum guide is talking to a group about the dinosaur fossils on exhibit.
“This one,” he says, “Is 6 million and 2 years old.”
“Wow,” says a patron, “How do you know the age so accurately?”
“Well,” says the guide, “It was 6 million years old when I started here 2 years ago.”

From Wikipedia: this is only a 1-sigma result compared to theory using lattice calculations. It would have been 5.1-sigma if the calculation method had not been improved.
Many calculations in the standard model are mathematically intractable with current methods, so improving approximate solutions is not trivial and not surprising that we’ve found improvements.

This seems like more of an achievement for the Barbie brand than for the individual director.

NGC 1277 is unusual among galaxies because it has had little interaction with other surrounding galaxies.

I wonder if interactions between galaxies somehow converts regular matter to dark matter.

Claude 2 would have a much better chance at this because of the longer context window.
Though there are plenty of alternate/theorised/critiqued endings for Game of Thrones online, so current chatbots should have a better shot at doing a good job vs other writers who haven’t finished their series in over a decade.

This looks amazing, if true. The paper is claiming state of the art across literally every metric. Even in their ablation study the model outperforms all others.

I’m a bit suspicious that they don’t extend their perplexity numbers to the 13B model, or provide the hyper parameters, but they reference it in text and in their scaling table.

Code will be released in a week https://github.com/microsoft/unilm/tree/master/retnet

Why do you say they have no representation? There are a lot of specific bodies operating in the government, advisory and otherwise, with the sole focus of indigenous affairs. And of course, currently, indigenous Australians are over represented in terms of parliamentarian race (more than 4% if parliamentarians are of indigenous descent).

While in general, I’d agree, look at the damage a single false paper on vaccination had. There were a lot of follow up studies showing that the paper is wrong, and yet we still have an antivax movement going on.

Clearly, scientists need to be able to publish without fear of reprisal. But to have no recourse when damage is done by a person acting in bad faith is also a problem.

Though I’d argue we have the same issue with the media, where they need to be able to operate freely, but are able to cause a lot of harm.

Perhaps there could be some set of rules which absolve scientists of legal liability. And hopefully those rules are what would ordinarily be followed anyway, and this be no burden to your average researcher.

See this comment on another thread about this for some more details.

Taking 89.3% men from your source at face value, and selecting 12 people at random, that gives a 12.2% chance (1 in 8) that the company of that size would be all male.
Add in network effects, risk tolerance for startups, and the hiring practices of larger companies, and that number likely gets even larger.

What’s the p-value for a news story? Unless this is some trend from other companies run by Musk, there doesn’t seem to be anything newsworthy here.

So, taking the average bicep volume as 1000cm3, this muscle could: exert 1 tonne of force, contact 8% (1.6cm for a 20cm long bicep), and require 400kV and must be above 29 degrees Celcius.

Maybe someone with access to the paper can double check the math and get the conversion efficiency from electrical to mechanical.

I expect there’s a good trade-off to be made to lower the force but increase the contraction and lower the voltage. Possibly some kind of ratcheting mechanism with tiny cells could be used to overcome the crazy high voltage requirement.

DALL-E was the first development which shocked me. AlphaGo was very impressive on a technical level, and much earlier than anticipated, but it didn’t feel different.
GANs existed, but they never seemed to have the creativity, nor understanding of prompts, which was demonstrated by DALL-E. Of all things, the image of an avocado-themed chair is still baked into my mind. I remember being gobsmacked by the imagery, and when I’d recovered from that, just how “simple” the step from what we had before to DALL-E was.
The other thing which surprised me was the step from image diffusion models to 3D and video. We certainly haven’t gotten anywhere near the quality in those domains yet, but they felt so far from the image domain that we’d need some major revolution in the way we approached the problem. The thing which surprised me the most was just how fast the transition from images to video happened.

I find the link valuable. Despite the proliferation of AI in pop culture, actual discussion of machine learning research is still niche. The community on Reddit is quite valuable and took a long time to form.

If this is a real question, this talk explains the fundamental concepts of atomic operations in a couple of minutes.

The talk itself is over an hour long, as the use of atomic operations has a large number of pitfalls. The joke in the meme leans on a specific type of memory ordering guarantee, known as “relaxed” in C++ parlance, which can be a lot faster, but which is much more likely to violate the default assumptions a programmer may make about order of operations and visibility across threads.

The greatest fix to all your pointer issues are to use references.

I wonder what specifically they’re interested in vs long deployments in Antarctica (people do 12 months rotations in some stations there).

I found this article discussing the psychology of placements in Australian antarctic stations: https://psychology.org.au/for-members/publications/inpsych/2021/february-march-issue-1/life-in-the-australian-antarctic-program.

The differences as I see them are:

1. Smaller crew
2. No unsuited outdoor time
3. Smaller space
4. Communication latency / outages
5. Personal belongings weight/volume limits
6. Dietary restrictions

Haha, thanks for the correction. If you have to use your degree in ethics, perhaps you could add your perspective to the thread?

In the last 12 months, 3M’s profits were $14.4B (source), so this fine represents 8.5 months of profits.

How large should the fine have been?

If you can get past the weird framing device, the Plinkett reviews of the Star Wars prequels are an excellent deep dive into the issues with those films: https://www.youtube.com/watch?v=FxKtZmQgxrI&list=PL5919C8DE6F720A2D

Jenny Nicholson’s videos are great, but her documentary on “The Last Bronycon” is special, as the realization dawns on you while watching that she has more connection to Brony culture than you might have guessed: https://www.youtube.com/watch?v=4fVOF2PiHnc

According to consequentialism:

1. Imagining sexual fantasies in one’s own mind is fine.
2. Any action which affects no-one but the actor, such as manifesting those fantasies, is also fine.
3. Distributing non-consensual pornography publicly is not fine.
4. Distributing tools for the purpose of non-consensual pornography is a grey area (enables (2), which is permissible, and (3), which is not).

From this perspective, the only issue one could have with deep fakes is the distribution of pornography which should only be used privately. The author dismisses this take as “few people see his failure to close the tab as the main problem”. I guess I am one of the few.

Another perspective is to consider the pornography itself to be impermissible. Which, as the author notes, implies that (1) is also impermissible. Most would agree (1) is morally fine (some may consider it disgusting, but that doesn’t make it immoral).

In the author’s example of Ross teasing Rachel, the author concludes that the imagining is the moral quandry, as opposed to the teasing itself. Drinking water isn’t amoral. Sending a video of drinking water isn’t amoral. But sending that video to someone dying of thirst is.

The author’s conclusion is also odd:

Today, it is clear that deepfakes, unlike sexual fantasies, are part of a systemic technological degrading of women that is highly gendered (almost all pornographic deepfakes involve women) […] Fantasies, on the other hand, are not gendered […]

1. Could you not also equally claim that women are being worshipped instead of degraded? Only by knowing the mind of both the consumer and the model can you determine which is happening. And of course each could have different perspectives.
2. If there were equal amounts of deep fakes of men as women, the conclusion implies that deep fakes would be fine (as that is the only distinction drawn), which is probably not the author’s intention.
3. I take issue with the use of systemic. The purpose of deep fakes is for sexual gratification of the user, not degradation. Only if you consider being the object of focus for sexual gratification to be degradation could the claim that there is anything systemic. If it was about degradation, wouldn’t consumers be trying to notify targeted people of their deep fake videos and make them as public as possible?
4. Singling out “women” as a group is somewhat disingenuous. Women are over-represented in all pornography because the majority of consumers are men and the majority of men are only attracted to women. This is quite clear as ugly women aren’t likely to be targeted. It’s not about “being a woman”, it’s about “being attractive to pornography consumers”. I think to claim “degradation of women” with the caveat that “half of women won’t be affected, and also a bunch of attractive males will be” makes the claim vacuous.