SlopppyEngineer

I usually say what unit of measurement we're counting in: days, weeks or months. For more detail, more specs are needed.

It' was a status thing. Those with manual labor jobs usually can't have long nails, so long nails means they're above manual labor. So the rich in the past did that, and now everybody wants to do that so and it becomes a beauty thing.

I'lp make it a point to discuss other car brands when in a Ford from now on

Nor is it the first battery powered train in the world or even first in Germany where this giga-train operates.

Optical computing won't change anything. The compiler takes care of it.

Even quantum computing basically works just like a GPU. You give it an algorithm and data to retrieve the result a bit later. Someone will make a quantum equivalent of CUDA before commercialization.

it could make our current computing technology exponentially more efficient, thus reducing the global power consumption of our data-driven society.

That's a bold lie. Jevons paradox will apply and the first thing that will happen is building more AI data centers and crypto mining.

It's going to kill poor folks. Rich people will have the better filter installations to keep micro plastics out.

It does remind me of that recent Joe Scott video about the split brain. One part of the brain would do something and the other part of the brain that didn't get the info because of the split just makes up some semi-plausible answer. It's like one part of the brain does work at least partially like an LLM.

It's more like our brain is like a corporation, with a spokesperson, a president and vice president and a number of departments that with semi-independently. Having an LLM is like having only the spokesperson and not the rest of the work force in that building that makes up an AGI.

they have to provide an answer

Indeed. That's the G in chatGPT. It stands for generative. It looks at all the previous words and "predicts" the most likely next word. You could see this very clearly with chatGPT-2. It just generated good looking nonsense based on a few words.

Then you have the P in chatGPT, pre-trained. If it happens to have received training data on what you're asking, that data is shown. It it's not trained on that data, it just uses what is more likely to appear and generates something that looks good enough for the prompt. It appears to hallucinate, lie, make stuff up.

It's just how the thing works. There is serious research to fix this and a recent paper claimed to have a solution so the LLM knows it doesn't know.

The tech sector is right now just running in hype and jumping from one hype to the next. It's a race to keep that investors throwing money at them with providing new targets to keep investors from realizing the stuff isn't that useful.

That's why they do regulatory capture to prevent that from happening. It all starts with money being equal to influence. This can temporarily be reset after a big crash of the system but sooner or later they start again.

The hight of the wage and the value to society are inversely proportional, with a few exceptions. Working for the greater good is seen as its own reward.