keegomatic

Personally, I’ve found that LLMs are best as discussion partners, to put it in the broadest terms possible. They do well for things you would use a human discussion partner for IRL.

• “I’ve written this thing. Criticize it as if you were the recipient/judge of that thing. How could it be improved?” (Then address its criticisms in your thing… it’s surprisingly good at revealing ways to make your “thing” better, in my experience)
• “I have this personal problem.” (Tell it to keep responses short. Have a natural conversation with it. This is best done spoken out loud if you are using ChatGPT; prevents you from overthinking responses, and forces you to keep the conversation moving. Takes fifteen minutes or more but you will end up with some good advice related to your situation nearly every time. I’ve used this to work out several things internally much better than just thinking on my own. A therapist would be better, but this is surprisingly good.)
• I’ve also had it be useful for various reasons to tell it to play a character as I describe, and then speak to the character in a pretend scenario to work out something related. Use your imagination for how this might be helpful to you. In this case, tell it to not ask you so many questions, and to only ask questions when the character would truly want to ask a question. Helps keep it more normal; otherwise (in the case of ChatGPT which I’m most familiar with) it will always end every response with a question. Often that’s useful, like in the previous example, but in this case it is not.
• etc.

For anything but criticism of something written, I find that the “spoken conversation” features are most useful. I use it a lot in the car during my commute.

For what it’s worth, in case this makes it sound like I’m a writer and my examples are only writing-related, I’m actually not a writer. I’m a software engineer. The first example can apply to writing an application or a proposal or whatever. Second is basically just therapy. Third is more abstract, and often about indirect self-improvement. There are plenty more things that are good for discussion partners, though. I’m sure anyone reading can come up with a few themselves.

May I ask how you’ve used LLMs so far? Because I hear that type of complaint from a lot of people who have tried to use them mainly to get answers to things, or maybe more broadly to replace their search engine, which is not what they’re best suited for, in my opinion.

Put simply, some states get more electors than other states to account for greater population, and each state decides how their electors are supposed to vote according to their statewide popular vote. Most states apply all of their electors to the winner of the popular vote in their state, while some apply them proportionally. Most do the former (“winner takes all”).

This leads to a discrepancy between the popular vote and the electoral vote, and it’s mathematically biased against states with higher populations. So, votes in the more populous states (which tend to vote Democrat) are worth “less” in the electoral college than those in less populous states, leading to Democrats winning the popular vote yet losing the actual election… which has happened in every election they’ve lost since Bush v. Gore, if I’m not mistaken. ~~I’ll double check that and edit if I’m wrong.~~

Edit: Sorry, it did not happen for Bush v. Kerry, Bush won the popular vote in that one by less than 1%. However, in the other two (Bush v. Gore and Trump v. Clinton) the popular votes were actually won handily by Gore and Clinton, not by Bush or Trump.

Edit 2: This is also notably NOT made worse by gerrymandering, because the number of electors you get is equal to the combined number of senators and congressmen your state gets. Since all states apply their electors based on the popular vote result, it doesn’t matter what party alignments your congresspeople have, so gerrymandering plays no role here.

The mathematical bias comes from the fact that every state gets two senators no matter what the population is, and only your congressperson count is proportional to population, but both count toward your number of electors. So, less populous states have proportionally somewhat more “electors per capita” than states with higher populations.

I never said I thought training AI with the copyrighted work of others causes harm to others. If anything, I think training is analogous enough to human learning that it’s a gray area. However, I think there are different ethical concerns with AI training data than there are with piracy, and those concerns mostly arise from the profit being made from the models.

It’s not hypocritical if you believe that theft is wrong because it hurts another person, rather than wrong because you don’t deserve the thing or that it offers you an unfair advantage. Your argument leans heavily on the latter but mine the former.

That’s not quite true, though, is it?

$50 earned is yours to spend on anything. A $50 discount is offered by a vendor to entice you to spend enough of your money on them to make the discount worthwhile.

Pirates don’t pirate because they’re trying to save money on something they would have bought otherwise… typically they pirate because the amount they consume would bankrupt them if they purchased it through legitimate means, so they would never have been a paying customer in the first place.

So, if they wouldn’t have bought it anyway, and they’re not reselling it, did they really harm the vendor? Whether they pirated it or not, it wouldn’t affect the vendor either way.

That’s not really the same thing, in my opinion.

If you were able to pay for everything handily but pirated anyway, or if you resold pirated content, then yeah you have something similar to theft going on. But that’s not really the norm; those people are doing something bad irrespective of the piracy itself, aren’t they?

I’m not the above poster, but I really appreciate your argument. I think many people overcorrect in their minds about whether or not these models learn the way we do, and they miss the fact that they do behave very similarly to parts of our own systems. I’ve generally found that that overcorrection leads to bad arguments about copyright violation and ethical concerns.

However, your point is very interesting (and it is thankfully independent of that overcorrection). We’ve never had to worry about nonhuman personhood in any amount of seriousness in the past, so it’s strangely not obvious despite how obvious it should be: it’s okay to treat real people as special, even in the face of the arguable personhood of a sufficiently advanced machine. One good reason the machine can be treated differently is because we made it for us, like everything else we make.

I think there still is one related but dangling ethical question. What about machines that are made for us but we decide for whatever reason that they are equivalent in sentience and consciousness to humans?

A human has rights and can take what they’ve learned and make works inspired by it for money, or for someone else to make money through them. They are well within their rights to do so. A machine that we’ve decided is equivalent in sentience to a human, though… can that nonhuman person go take what it’s learned and make works inspired by it so that another person can make money through them?

If they SHOULDN’T be allowed to do that, then it’s notable that this scenario is only separated from what we have now by a gap in technology.

If they SHOULD be allowed to do that (which we could make a good argument for, since we’ve agreed that it is a sentient being) then the technology gap is again notable.

I don’t think the size of the technology gap actually matters here, logically; I think you can hand-wave it away pretty easily and apply it to our current situation rather than a future one. My guess, though, is that the size of the gap is of intuitive importance to anyone thinking about it (I’m no different) and most people would answer one way or the other depending on how big they perceive the technology gap to be.

That is absolutely fascinating. I had the same assumption.

4K HDR

Normally I use kdenlive to edit video, which supports 4K AFAIK, but although that doesn’t support HDR it looks like DaVinci Resolve supports both.

Taxes

That’s surprising. Turbotax and Quickbooks have online options, and there are a few native apps like GnuCash, but I haven’t used them—TurboTax works for me.

GarageBand

Yeah that’s too bad. I hear good things about Ardour, though. Also, bandlab if you’re okay with a webapp.

Netflix

I only stream on an actual TV, not my computer, so I haven’t done this in a while, but I thought you could do this in Firefox with DRM enabled? If not, seems like there are addons which enable it. Might be outdated knowledge.

vector illustration

Fun is hard to come by

git client

Git clients all suck for me, CLI is the way to go. However, my co-workers that use git clients all use GitKraken (on macOS) and that is available on Linux, too.

screen recording was also painful

Won’t argue with you there. Don’t know why it doesn’t have first-class support in many distros. I hear OBS Studio works well for this if you want to do anything fancy with the recording, otherwise there are plenty of apps for this (Kazam might be a simpler choice).

barely meets my use cases

I think really (considering the above) your main issue is that you just have some strong software preferences. There are certainly ways to meet most if not all of the use cases you listed. It requires a big change in workflow, though.

For what it’s worth, I find that most of the issues with software alternatives in Linux is that everyone often recommends free/GPL replacements, which are invariably worse than the commercial/non-free software the user is used to. But there is paid software in Linux land, too, remember. In my case, I have often found that if I can pay for the software it will be better, and if there’s a webapp version of something non-free it will often be better than the native FOSS alternative. There are many notable exceptions to that rule, but money does solve the occasional headache.

The tea was then sold at a price of 2/- per pound, undercutting the price of smuggled Dutch tea, then priced at 2/1 per pound. This is secondary to the fact that the tea still was taxed at -/3 per pound, meaning the price was really 1/9 plus thruppence tax

Ahhh, it all makes sense now

worst fucking timeline

Again, your numbers are completely and totally wrong to begin with, proved by the very article you replied to—I’m just ALSO saying that even using your wildly incorrect numbers you’re still wrong in yet another way