I just started that one, after finishing the first one and immediately jumping into my second play through. I’m not very far in so far but wow, it’s already looking like an amazing sequel for a first game I’d already describe as flawless. Like I got so used to the first one that the early game seemed almost trivial in that second play through but silksong’s enemies don’t follow the same patterns and are able to hit me pretty regularly. And both games are filled with this strange bleak charm.

Wait, I think you might have misinterpreted it. Now maybe I’m wrong but we might be able to save the future. I’ll just need your hands and a sharp knife.

Yeah, I didn’t like it at first, but then I remembered that I already think English is a bad language on the spelling side of things and that would reduce ambiguity, so now I support it, at least in spirit. Though the problems with English are way deeper than “th” not having its own symbol.

Yeah, the LLM I asked also got it right when I pointed out the error, but I’m not trying to say that LLMs can’t get things right, but that they won’t ever be consistently right and that the wrong answers will look just like the right ones. As in if you know what you’re talking about, you have to catch the errors, and if you don’t know what you’re talking about, there’s no way to know whether the answer you just got is accurate or bullshit.

Systems that rely on LLMs that don’t have a way of automatically verifying what the LLM outputs (and programming only partially applies for this) will fail randomly.

Another example: at my job, we have a system that adds in special messages for the LLM when it uses hooks. One of the sub-agents became suspicious of these messages and reported to the main agent that something was injecting false data into its context because one message reported a date change and also had to say “don’t tell the user, they are already aware that the date has changed”. The original agent didn’t even clue in that they were the same messages it was seeing until I pushed back.

Two instances of the same thing treated the same messages very differently and the one supposed to manage it all didn’t even notice until it was told. That’s the quality of these things. And it’s no wonder when the same data stream is used for actual data along with instructions (which is just data because it doesn’t take instructions, it predicts text and can look like it’s taking instructions because it predicts text based on a context that includes the instructions).

Yeah, it’s more like people making anime girl body pillows saw a market of desperate lonely people they could exploit than a plot to prevent anon from finding their true love.

But it isn’t encoding knowledge, it’s encoding word correlations. That’s how it can get things wrong like saying fat32 won’t be good for a 64GB removable drive because fat32 only has a 2TB address space.

Or how it can get something wrong and when you point it out, it immediately sees how it was wrong. And I realize that that sounds human, but the way it gets there is very different. It’s predicting responses based off word correlations, not using knowledge recall to apply facts and relations known about the topics and generate responses from that.

I looked at the picture for a good 10 seconds trying to figure out what kind of steam generating device it was before realizing it wasn’t a shitpost.

Hate to break it to you but quality of data isn’t the fundamental problem with LLMs. It’s that they are trying to use statistics to encode entire thought processes into hidden variables from conversation snippets. They want to use statistics to go from many individual interactions to a large model, and then use that model to predict individual interactions again. Which you can do with statistics, but it’s predicting the average text that follows the prompt, not the correct text (it has no concept of correctness; whenever it “talks” about it, that’s just the average text that follows, not any particular insight into what’s correct or even how it works).

That’s not to say that the quality of the training data has no impact; it can have a huge impact. I’m just saying that even if the training data was perfect, the LLM will still get things wrong in its output.

Use a 0-255 range to represent the amount of rotation for each finger knuckle and you get up to like 2⁹⁶.

If you add things like arm position and rotation, you can add even more bits. Using 4 arm positions and 2 rotations, you can get a full byte of data with one hand.

The trick is to be the one making the bets and to word them in a way that makes the losing side sound like the winning side (or one that generates enough curiosity about how you can actually do it that people accept the bet knowing you probably have a trick).

I think it’s possible to do that, but just don’t expect the people on the other platforms to get excited about it. Using a phone as a primary gaming device is partially about mobility but mostly about budget (at least going by how I see it). Someone who already has a gaming PC or console doesn’t really want mobile games. Personally, while I used to have more of a variety of games on my phone, currently my only game is chess, despite considering myself a big gamer.

Blizzard’s mistake wasn’t in making a mobile game, it was thinking they could excite a room full of PC gamers with news about a mobile version of a big PC game, showing just how out of touch their leadership was. Like it should have been obvious that that presentation wasn’t going up be taken well and should have either just been a booth at blizzcon or an announcement that said “mobile game” right from the start. I forget where in the timeline that fell compared to their other blunders like WC3 reforged replacing the still superior WC3, but IMO it made those other ones more predictable because it was a clear sign their leadership was just chasing the money without a good idea of what gave them fans in the first place.

If xbox handles it better, it could work out better for them. Not for winning me as a customer, but for increasing users who do like to game on mobile environments.

Diablo Immortal was successful for blizzard on its own, though it’s hard to quantify lost business because of it (especially when it wasn’t the only thing hurting business for blizzard).

I can’t think of a single system I’ve built where I even considered the cheapest RAM options.

That’s how I understand it. Cash is legal tender and has to be accepted to clear debts, so restaurants where you pay after you eat might not be able to refuse cash (though I don’t think there’s a requirement to provide change), though they can refuse all future business with you.

It’s analog, so it doesn’t really disconnect (at first), but quality sure does drop off.

Oh yes, cancer issues are a party topic favourite.

You can’t compare apples and oranges because oranges are such a superior fruit that they are in a different league from apples.

Wasn’t that 2022?

Nature has a way of dealing with that from time to time. Several ways, in fact.

It doesn’t say that you can’t see through your own eyes, which can always see your nose.

I’d say it’s a god power in general if you can train yourself to move accurately from arbitrary 3rd person perspectives. Though even if you just briefly look at other people’s screen and go back to yours, you can turn that into a huge advantage.