Forget taking over my job. AI is headed straight for the C suite.

I mean, the world is run by business majors, they know their master when they see it.

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Linus was ahead of the game on this one. Nvidia should start building data centers next to public pools. Cool the systems and warm the pools.

That was a solved problem 20 years ago lol. We made working systems for this in our lab at Uni, it was one of our course group projects. It used combinations of sensors and microcontrollers.

It's not really the kind of problem that requires AI. You can do it with AI and image recognition or live traffic data but that's more fitting for complex tasks like adjusting the entire grid live based on traffic conditions. It's massively overkill for dead time switches.

Even for grid optimization you shouldn't jump into AI head first. It's much better long term to analyze the underlying causes of grid congestion and come up with holistic solutions that address those problems, which often translate into low-tech or zero-tech solutions. I've seen intersections massively improved by a couple of signs, some markings and a handful of plastic poles.

Throwing AI at problems is sort of a "spray and pray" approach that often goes about as badly as you can expect.

The trouble with phrases like 'neural structures' and 'language parsing' is that these descriptions still play into the "AI" narrative that's been used to oversell large language models.

Fundamentally, these are statistical weights randomly wired up to other statistical weights, tested and pruned against a huge database. That isn't language parsing, it's still just brute-force calculation. The understanding comes from us, from people assigning linguistic meaning to patterns in binary.

I'm... honestly kinda okay with it crashing. It'd suck because AI has a lot of potential outside of generative tasks; like science and medicine. However, we don't really have the corporate ethics or morals for it, nor do we have the economic structure for it.

AI at our current stage is guaranteed to cause problems even when used responsibly, because its entire goal is to do human tasks better than a human can. No matter how hard you try to avoid it, even if you do your best to think carefully and hire humans whenever possible, AI will end up replacing human jobs. What's the point in hiring a bunch of people with a hyper-specialized understanding of a specific scientific field if an AI can do their work faster and better? If I'm not mistaken, normally having some form of hyper-specialization would be advantageous for the scientist because it means they can demand more for their expertise (so long as it's paired with a general understanding of other fields).

However, if you have to choose between 5 hyper-specialized and potentially expensive human scientists, or an AI designed to do the hyper-specialized task with 2~3 human generalists to design the input and interpret the output, which do you go with?

So long as the output is the same or similar, the no-brainer would be to go with the 2~3 generalists and AI; it would require less funding and possibly less equipment - and that's ignoring that, from what I've seen, AI tends to be better than human scientists in hyper-specialized tasks (though you still need scientists to design the input and parse the output). As such, you're basically guaranteed to replace humans with AI.

We just don't have the society for that. We should be moving in that direction, but we're not even close to being there yet. So, again, as much potential as AI has, I'm kinda okay if it crashes. There aren't enough people who possess a brain capable of handling an AI-dominated world yet. There are too many people who see things like money, government, economics, etc as some kind of magical force of nature and not as human-made systems which only exist because we let them.

The sheer waste of energy and mass production of garbage clogging up search results alone is enough to make me hope the bubble will pop reeeeal soon. Sucks for research but honestly the bad far outweighs the good right now, it has to die.