Lenguador

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.

Apparently Inflection AI have bought 22,000 H100 GPUs. The H100 has approximately 4x the compute for transformers as the A100. GPT4 is rumored to be 10x larger than GPT3. GPT3 takes approximately 34 days to train on 1024 A100 GPUs.

So with 22,000*4/1024=85.9375x more compute, they could easily do 10x GPT4 size in 1-2 months. Getting to 100x the size would be feasible but likely they're banking on the claimed speedup of 3x from FlashAttention-2, which would result in about 6 months of training.

It's crazy that these scales and timelines seem plausible.

This is an essay about the Barbie brand and its relationship to feminism and capitalism through history and the modern day. The Barbie movie is discussed but it's not the primary focus.

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.