@georgetakei especially when they are gpong to read #bannedbooks. They have made a pretty good list to start.

Some decades ago there was here a publisher who made a whole banned books series in cheap edition. That sold very well.

@Wileymiller fwiw, the wikipedia page doesn't mention Congress very much. they would normally cite the specific bill.

https://en.m.wikipedia.org/wiki/Denali%E2%80%93Mount_McKinley_naming_dispute

@Wileymiller "You're such a snowflake, it's just a joke bro" is something those rightoid armpits LOVE to yell like it's a great comeback, so it's deliciously ironic how here you are, ACTUALLY making a joke, and these same conservative chuds who are so very concerned about the state of humor just can't take it.

Pack 'em onto the next Starship and send them off to Mars.

@VeroniqueB99

LOL

looks like they got rid of the car by having the dog push it into a creek with his face...

@daringfireball yet another reason Plex is the only streaming service I use. Pirates get a better product for free than paying customers get for their endlessly-increasing monthly toll.

@daringfireball At least New York Times writes “…cost-cutting initiative that’s been called…” as a prefix to DOGE, not buying Musk’s narrative outright, as many outlets do.

@GossiTheDog

"There is zero artificial intelligence today. There could have been, but 50 years ago the decision was made by most scientists and companies to go with machine learning, which was quick and easy, instead of the difficult task of actually reverse engineering and then replicating the human brain.

So instead what we have today is machine learning combined with mass plagiarism which we call ‘generative AI’, essentially performing what is akin to a magic trick so that it appears, at times, to be intelligent.

While the topic of machine learning is complex in detail, it is simple in concept, which is all we have room for here. Essentially machine learning is simply presenting many thousands or millions of samples to a computer until the associative components ‘learn’ what it is, for example pictures of a daisy from all angles and incarnations.

Then companies scoured the internet in the greatest crime of mass plagiarism in history, and used the basic ability of machine learning to recognize nouns, verbs, etc. to chop up and recombine actual human writings and thoughts into ‘generative AI’.

So by recognizing basic grammar and hopefully deducing the basic ideas of a query, and then recombining human writings which appear to match that query, we get a very faulty appearance of intelligence - generative AI.

But the problem is, as I said in the beginning, there is no actual intelligence involved at all. These programs have no idea what a daisy, or love, or hate, or compassion, or a truck, or horse, or wagon, or anything else, actually is. They just have the ability to do a very faulty combinatorial trick to appear as if they do.

And while the human brain consumes around 20 watts, these massive pattern matching computers consume uncounted millions, and counting.

However there is hope that actual general intelligence can be created because, thankfully, a handful of scientists rejected machine learning and instead have been working on recreating the connectome of the human brain for 50 years, and they are within a few decades of achieving that goal and truly replicating the human brain, creating true general intelligence.

In the meantime it's important for our species to recognize the danger of relying on generative AI for anything, as it's akin to relying on a magician to conjure up a real, physical, living, bunny rabbit.

So relying on it to drive cars, or control any critical systems, will always result in massive errors, often leading to real destruction and death."
SearingTruth