hissing meerkat

Dogs love pumpkin. Dogs love cinnamon.

10s of thousands of nothing. Hundreds of thousands isn’t even enough that “economic growth” at the expense of increased costs and greater inequity would be a net benefit.

A complete Greenland slide-off would be an average sea level rise of about 7m, and is possible in our lifetimes as an extreme event (something like a fraction of a percent chance before 2100). If it happened it would be multiple events really, spread out across years or decades. Antarctic ice moving so its weight is no longer supported by the continent was too unlikely to include in models a few years ago, but the West Antarctic has been so active that I’d expect it to start showing up in estimates.

That’s because you’re the victim of a crime: extortion

No, terrible record keeping is exactly what caused this, according to the anonymous whistleblower: warranty work on the door was performed without any records being created for it due to boeing keeping two record keeping systems, one that was the system of record and one that was used as visibility for management.

No, the NTSB said that Boeing hadn’t provided them with the records, not that orders for the reinstallation hadn’t been made. Boeing is now trying to blame the lack of records to follow-up on on employees, even though none of the work should have been possible without the records existing in the first place.

Boeing absolutely shouldn’t be trying to get out ahead of the NTSB investigation with their own deflecting interpretation of what the NTSB has uncovered and shared with Boeing, which is probably along the lines of the anonymous whistleblower from a few months ago who detailed failings in the record keeping process before the senate hearings revealed that Boeing hadn’t provided the NTSB with the records (which according to the anonymous whistleblower didn’t exist because they were never created)

New?! This is the original area in which China excelled at producing electric vehicles. London’s early electric buses were European licensed production of BYD buses (or more likely BYD licensed powertrains)

Is China even allowing electric buses to be exported yet? The last time I looked it was still going to take over a decade to replace all the buses in China, but a chunk of a decade has passed since then.

There’s an old report from New York City putting the value of an electric bus at about $1.2 million, mostly the health benefits from no emissions not fuel savings. At the time there was no way for New York City to buy them because there’s no way to fund transit out of healthcare when the state pays for one but not the other, there were no non-Chinese manufacturers, and then shortly after they couldn’t compete with London that valued an electric bus at £1.7 million if I remember correctly, and the UK could justify funding buses based on healthcare. I think those first buses were about €600k. At the same time kneeling electric transit buses in China were about $90k, and small electric buses were $30-$40k.

Whether or not you use downvotes doesn’t really matter.

If what you like is well represented by the Boba drinkers and the Boba drinkers disproportionally don’t like Cofee then Cofee will be disproportionally excluded from the top of your results. Unless you explore deeper the Cofee results will be pushed to the bottom of your results. And any that happen to come to the top will have arrived there from broad appeal and will have very little contribution to thinking you like Cofee.

If you don’t let the math effectively push things away that are disliked by the people who like similar things as you then everything will saturate at maximum appeal and the whole system does nothing.

There’s two problems. The first is that those other things you might like will be rated lower than things you appear to certainly like. That’s the “easy” problem and has solutions where a learning agent is forced to prefer exploring new options over sticking to preferences to some degree, but becomes difficult when you no longer know what is explored or unexplored due to some abstraction like dimension reduction or some practical limitation like a human can’t explore all of Lemmy like a robot in a maze.

The second is that you might have preferences that other people who like the same things you’ve already indicated a taste for tend to dislike. For example there may be other people who like both Boba and Cofee but people who like one or the other tend to dislike the other. If you happen to encounter Boba first then Cofee will be predicted to be disliked based on the overall preferences of people who agree with your Boba preference.

No, not as simply as that. That’s the basic idea of recommendation systems that were common in the 1990s. The algorithm requires a tremendous amount of dimensionality reduction to work at scale. In that simple description it would need a trillion weights to compare the preferences of a million users to a million other users. If you reduce it to some standard 100-1000ish dimensions of preference it becomes feasible, but at the low end only contains about as much information as your own choices about subscribed to or blocked communities (obviously it has a much lower barrier of entry).

There’s another important aspect of learning that the simple description leaves out, which is exploration. It will quickly start showing you things you reliably like, but won’t experiment with things it doesn’t know you’d like or not to find out.

Carbon Catch and Release