Redex

Ok that’s really cool. It looks like it’s really new? Like 3 months old?

If you’re working on a large project/product then sure, but VS Code is just so damn good, it’s so much fucking faster than IntelliJ, has so many more options and is typically just more intuitive to me. Whenever I can I typically use it.

Possible, but I wouldn’t really see this as evidence of that in particular. Israel has been conducting subversive actions against Hamas and the Houthis for a long time and something like that pager attack was likely being planned far ahead.

Ok yeah the second part makes sense, but for the first part I was calculating it based on hand washing, dishwashers would be way less since you have to split the usage per person in the household, which holds for hand washing as well. Idk for other people but when I’m alone I use the dishwasher probably every 3-4th day and for handwashing I’d say 20L is realistic, double it maybe but still isn’t that much.

Yeah but it says “at home” and gives recommendations how you personally can reduce water consumption (like more efficient taps or showerheads), which makes me believe that it’s not your entire direct and indirect water consumption (which realistically isn’t even relevant for the argument since the water used for crops isn’t gonna be getting treated anyway)

How the hell do people use that much water? Are they including water consumption needed for the products we use or? Let’s say a flush is 8L and the average person flushes 5 times a day, that’s 40L. The average person needs about 2L of water a day. Let’s say an average shower is 100L. Cleaning dishes at worst is probably like 20L per person without a dishwasher. That’s like 160L of water per day and I feel like most of those were over-estimates. How did they get to that number?

My thoughts are the same, as long as it’s not so bad you can’t not notice it, I think it’s fine.

The main problem in my mind with purely vision based FSD is that it just isn’t as smart as a real human. A real human can reason about what they see, detect inconsistencies that are too abstract for current ML algorithms to see, and act appropriately in never before seen circumstances. A real human wouldn’t drive full speed through very low visibility areas. They can use context to reason about a situation. Current ML algorithms can’t do any of that, they can’t reason. As such they are inherently incapable of using the same sensors (cameras/eyes) to the same effect. Lidar is extremely useful because it helps get a bit better of a picture that cameras can’t reliably provide. I’m still not sure that even with lidar you can make a fully safe FSD car, but it definitely will help.

Money

Personaly those shortcuts are a feature I literally never use so much so I don’t even register their existence anymore.

I too am relatively envious of the UK’s outlet design, I only hate how bulky and foot destroying they are.

Ok sure, what do you want them to do instead then? 80% of their income is reliant on a tech giant’s grace and is seemingly more and more likely to be cutoff soon. They need to survive somehow, and every monetised service they tried flopped thusfar.

I don’t know much apart from the basics of YAML, what makes it complicated for computers to parse?

I mean if you make a gmail account just for your Google account, you’ll either have to log into your Gmail account to check emails or miss potential important emails related to your account, which you would get if they were sent to your main email.

I mean regular people don’t know how to read it, except if you randomly decided you wanted to. It’s pretty big culturally, e.g. the Baška tablet is a very important piece of history written in glagolitic that everyone knows about, and I’ve seen the alphabet randomly displayed in a few places, but nobody actually uses it today.

Damn, wild Glagolitic script found. I didn’t even realise it was in the Unicode standard.

Yeah but then you look at China and it’s at 4%. Maybe they got into the game early enough to get enough adress space for it to be serviceable?

Interesting that India has such a high percentage. I’m guessing it’s because most of their network infrastructure is probably relatively new and so they can include support right off the bat, instead of having to retrofit stuff?

Didn’t know about the outbound traffic thing, that’s really cool.

Well on one hand yes, when you’re training it your telling it to try and mimic the input as close as possible. But the result is still weights that aren’t gonna reproducte everything exactly the same as it just isn’t possible to store everything in the limited amount of entropy weights provide.

In the end, human brains aren’t that dissimilar, we also just have some weights and parameters (neurons, how sensitive they are and how many inputs they have) that then output something.

I’m not convinced that in principle this is that far from how human brains could work (they have a lot of minute differences but the end result is the same), I think that a sufficiently large, well trained and configured model would be able to work like a human brain.