https://www.cbsnews.com/sanfrancisco/news/hawks-helping-keep-oakland-streets-safe-by-dispersing-crow-roosts/

while Baz insists he has nothing against crows, it’s the mess they leave behind that has people crying foul.

That’s what I’m secretly training the crows for.

I doubt the falconer would have any issue with me—I’m helping to keep them employed.

The Scouring of the Shire is probably the most explicit anti-industrialization section of the books—more so even than the destruction of Isengard.

I’m indifferent to squirrels… but my city has hired a falconer to scare the crows away with hawks, so now the crows symbolize the oppressed masses being persecuted by the state.

A crow-calling whistle and a small tin of peanuts.

Blood Meridian as an illustrated children’s book.

What’s the purpose—research? Tax evasion? Shits and giggles?

That… seems like what you’d expect, assuming that most districts aren’t sitting right on the 50% party preference line and fluctuating up and down every two years.

You know that there are two unrelated words, and you’ve seen two different spellings—it’s a natural assumption that the latter stems from the former.

Why so many people would pair them up the same (etymologically unsupported) way, I don’t know… maybe we’re used to correlating words relating to art with French, and assuming that words with “ou” come from French as well (and this case just happens to be an exception).

I use “mold” for both, and regard “mould” as the British spelling for both.

But the etymologies are interesting—the verb comes from French modle, while the fungus comes from late Middle English mould. So if anything, your assumed distinction is etymologically reversed.

One issue specific to the Fediverse is that each instance and each community might have its own standard for what it considers “credible”—and part of another user’s credibility score might come from users on instances with which yours isn’t federated and doesn’t share information.

Not using their turn signals if the only other traffic is pedestrians.

So many times I’ve been crossing an intersection to the opposite corner where I could cross either street first, so I pick the street that won’t block the car crossing the other way. They’re not signalling so I figure they’re going straight, and cross the other way so they won’t have to wait for me—but seemingly every time it turns out the car was really turning after all. So they’re stuck because they couldn’t conceive of pedestrians as traffic they need to communicate with.

A long family tradition.

How can an LLM tell a hawk from a handsaw when the wind is from the west, if both terms are just high-dimensional abstract vectors without cross-domain referents and it can’t even feel the west wind in its neural weights?

They also identify compounds in human sweat that increase biting behavior in mosquitoes as well as bitter compounds that suppress egg-laying and feeding behaviors…

Is that how anti-malarials like quinine work?

Stick with the gopher protocol, http is too poorly implemented.

The main shape is a Boteh.

There’s a part of our brain called the salience network, that continually models and predicts our environment and directs our conscious attention to things it can’t predict. When we talk to each other, most of the formal content is predictable, and the salience network filters it out; the unpredictable part that’s left is the actual meaningful part.

LLMs basically recreate the salience network. They continually model and predict the content of a text stream the same way we do—except instead of modeling someone else’s words so they can recognize the unpredictable/meaningful part, they model their own words so they can keep predicting the next ones.

This raises an obvious issue: when our salience networks process the stream of words coming out of such an LLM, it’s all predictable, so our brains tell us there’s no actual message. When AI developers ran into this, they added a feature called “temperature” that basically injects randomness into the generated text—enough to make it unpredictable, but not obvious nonsense—so our salience networks will get fooled into thinking there’s meaningful content.

The article describes a study in Autism without giving title, date, or authors. After searching that journal, I believe the source study is this: Non-autistic observers both detect and demonstrate the double empathy problem when evaluating interactions between autistic and non-autistic adults (Jones, D. R., Botha, M., Ackerman, R. A., King, K., & Sasson, N. J., Dec 2023).