Note: N^2 and NlogN scaling refer to runtime when considering values of N approaching infinity.

For finite N, it is entirely possible for algorithms with worse scaling behavior to complete faster.

I’ve used various flavors of Arch for years. I tried Nix and spent several hours failing to do anything - like table-stakes shit like installing packages.

I went back to Arch.

Nvidia has 90% of the discrete GPU market.

Kind of important that things work there.

Linux isn’t ready.

While many things will work ‘out of the box’, many won’t. Hell, for like 3 months HDR was causing system-wide crashes on Plasma for Nvidia cards, so the devs just disabled the HDR options until there was an upstream fix.

There are still a host of resume-from-sleep issues, Wayland support is still spotty, and most importantly - not every piece of software will run.

Linux is my daily driver, I have learned to live and love the jank. My wife uses windows and does not want to be confronted with a debugging challenge 5% of the time when she turns on her computer, and I think that is fair.

These kinds of posts paper over lots of real issues and can be counterproductive. If someone jumps into the ecosystem without understanding, these kinds of posts only set them up for frustration and disappointment.

The biggest factor is diet - a large portion of ingested water comes from food.

Someone who snacks on carrots is going to need to drink a very different amount of water to stay hydrated as someone who eats jerky and crackers.

There’s also obviously differences in kidney function, salt retention, even just body size. Current medical advice is to just drink when you are thirsty, which works for just about everyone.

I find it kind of bussin’, I find it kind of cap. The dreams in which I’m dying are the ones that kinda slap.

Dropping anything in orbit just means it is still in orbit.

You’d need a lot of fuel to deorbit that cube on a steep trajectory.

It depends on the type of fusion.

The easiest fusion reaction is deuterium/tritium - two isotopes of hydrogen. The vast majority of the energy of that reaction is released as neutrons, which are very difficult to contain and will irradiate the reactor’s containment vessel. The walls of the reactor will degrade, and will eventually need to be replaced and the originals treated as radioactive waste.

Lithium/deuterium fusion releases most of its energy in the form of alpha particles - making it much more practical to harness the energy for electrical generation - and releases something like 80% fewer high energy neutrons – much less radioactive waste. As a trade-off, the conditions required to sustain the reaction are even more extreme and difficult to maintain.

There are many many possible fusion reactions and multiple containment methods - some produce significant radioactive waste and some do not. In terms of energy output, the energy released per reaction event is much higher than in fission, but it is much harder to concentrate reaction events, so overall energy output is much lower until some significant advancement is made on the engineering challenges that have plagued fusion for 70+ years.

But if you could see them, they could see you …

The ideal answer is compost, regenerative agriculture, and (better treated) human-sources waste.

Organic crop yields will almost certainly reduce a bit without animal waste fertilizer, but that is fine since crop consumption will fall by a greater amount due to not needing to feed a bunch of extra animals.

You haven’t really described what you are imagining.

Proper “AI”. No more coding, you just tell the machine what to do and it will do it. I don’t think in the physical world but computers and every profession that is not physical will be much rarer. Either pivot to AI Management or be the arms that the AI “guides” through a task.

Telling a computer specifically what to do and how to do it without making mistakes is coding. Programming is a level above that, in designing the architecture of how to approach the business problem.

What the other commentator is saying, is that simple being able to tell some model ‘build an app that does XYZ’ requires AGI because that set of instructions is not complete - the machine requires outside knowledge and the ability to make judgement calls in order to complete it.

If that isn’t what you meant, it is at least what you said. The breakdown in communication here, between humans, should also serve as another reminder how difficult it is to convey an idea to another entity and how that problem will remain difficult for a very long time.

An inherent flaw in transformer architecture (what all LLMs use under the hood) is the quadratic memory cost to context. The model needs 4 times as much memory to remember its last 1000 output tokens as it needed to remember the last 500. When coding anything complex, the amount of code one has to consider quickly grows beyond these limits. At least, if you want it to work.

This is a fundamental flaw with transformer - based LLMs, an inherent limit on the complexity of task they can ‘understand’. It isn’t feasible to just keep throwing memory at the problem, a fundamental change in the underlying model structure is required. This is a subject of intense research, but nothing has emerged yet.

Transformers themselves were old hat and well studied long before these models broke into the mainstream with DallE and ChatGPT.

There is always a tension between security, privacy, and convenience. With how the Internet works, there isn’t really a way - with current technology - of reliably catching content like that without violating everyone’s privacy.

Of course, there is also a lack of trust here (and there should be given the leaks about mass surveillance) that the ‘stop child porn powers’ would only be used for that and not simply used for whatever the powers that be wish to do with them.

The world bank isn’t involved so much in printing money - that’s central banks like the US Federal Reserve or European Central Bank.

They do love to force developing nations to adopt US-style capitalism by withholding loans for needed development projects. They also focus far too much on increasing GDP at all costs and do not give really any weight to increasing living standards or reducing inequality. Basically, think loans to institute Reaganomics and you won’t be too far off.

The loans pay for large capital projects (power plants, large-scale irrigation, etc) that are built by the state and then mandated to he handed over to private entities that then charge rents and extract wealth. Not every loan and program is bad, but there’s plenty to give pause when they are involved in a project.