tonarinokanasan

Forgive me for not reading all 2500 documents, but I haven't heard anything to suggest there was a bunch of sinister stuff in there -- and there's nothing implicitly evil about having docs leaked.

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Exactly the same here. Since I swipe type, I have to imagine that would be a nightmare on Dvorak with all the vowels clustered together.

I use Dvorak, but it has nothing to do with statistics for me. When I switched to Dvorak, it felt more comfortable on my hands. My typing speed is essentially the exact same, for example, and I don't think you could find a measurable difference depending on which I use. But qualitatively -- it feels more comfortable.

While the conversion is appreciated, there's no reason to be an ass about it. OP labeled it, so it's not like it was confusing or making unnecessary assumptions about the audience. So really you're the one who just comes across as completely culturally insensitive.

I think the trouble is, what baby are we throwing out with the bathwater in this case? We can't prevent LLMs from hallucinating (but we can mitigate it somewhat with carefully constructed prompts). So, use cases where we're okay with that are fair game, but any use case (or in this case, law?) that would require the LLM never hallucinates aren't attainable, and to get back earlier, this particular problem has nothing to do with capitalism.

This is a thing that is true of all LLMs, but it seems like you're misunderstanding the core issue. It CAN give outputs like that sometimes. What we CAN'T do is force it to give outputs like that ALL the time.

It will answer "I don't know" if its predictive text model guesses that the most common response to this would be "I don't know". To do that, to simplify a little, you could imagine that it reads your question, compares that to all the text in its training data, and tries to find the conversation that looks most like the question you asked, then answers whatever the person in the training data answered. But your exact question wasn't in its training data, so if you took that mental model, and instead had it compare to 1000 similar looking things in its training model and average them, then it would hopefully do a better job of coming up with something at least close to what you actually asked. Now take it to a million, or a billion.

When we're asking questions about the real world, we would prefer for it to answer based on knowledge about the real world. But what if it "matches" data from a work of fiction? Or just someone who doesn't know what they're talking about? Or true information, but about a different subject?

It doesn't know anything. It doesn't understand anything you say. It just looks at patterns that it learned from the training data and tries to guess what words are most likely to be said in that case. In other words, "here's one case where it didn't hallucinate" and "it will never hallucinate" are not the same thing at all.

Edit: To clarify, it doesn't search its training data to answer your question, so asking "was this in the training data" is impossible. By the time you interact with it, the data is long gone. It was just used for training.

I think the bigger factor is, someone who already thinks they're great probably isn't working on noticing and improving their weaknesses. Someone who thinks they still have a lot to learn is putting a lot of effort into improving.

So, especially if they've felt that way for any significant length of time, it's no wonder which person will end up being better.

Surely there's a breakpoint with plants though, right? You could transport a few plants, but probably not a whole garden, or a flower bed, or a tree old enough to have deep roots, etc

My point wasn't that the status quo is good or right. There's a fundamental problem if the person most motivated to improve the property - the tenant actually living there - isn't the one who the system rewards for doing so.

Pretending the system we have today is different than it is is just denying reality, and isn't an effective way to realize change. The reality that we live in is that by improving your own home while renting, you're a sucker who is being taken advantage of by the system.

There's a fundamental difference between furniture and an improvement to the underlying property itself. For example, if you repaint a fence, you can't take the paint with you, and the value of the paint itself was far lower than the labor cost to apply it to the fence.

One problem it has is that it can be REALLY slow sometimes. Like any turn based strategy game, map size has an exponential effect on how long a game takes, but the mechanics of wesnoth lean a lot more towards larger maps.

I'm mostly talking about multiplayer though. For singleplayer there's about a hundred million campaigns to play so you could probably play it forever.