Nah, people put together stuff randomly all the time. Things that most people are aware of tend to be filtered to stuff that works together.

It is no more creative than putting pieces of paper with things on them and pulling them randomly out of a hat. AI can't creatively come up with something new to write on one of those pieces of paper.

Except LLMs are the worst of both worlds in that respect. In order to work in a robot factory, its output needs to be reliable and repeatable, ideally across as wide a range of inputs as possible. LLMs .... are very much not that. They're also only as 'skilled' as their training data, which thanks to the morally bankrupt scraping of every source the AI companies can get their grubby hands on, is of enormously variable quality - and because of the nature of LLMs, it will never be better than its training data. The average quality of its output will, in fact, be the average of its training data.

It's possible for LLMs to be creative - in the sense that it can output novel sentences - except that as you increase its 'creativity' (temperature) beyond the default that most of the chatbots out there have, the quality plummets. It still can't solve complex problems though, because even if it does have an internal model of how certain things function, it can't come close to the complexity of what humans can hold in their brains - or perhaps cannot abstract portions of their model in the same way - as evidenced by their utter failure to work through any problem that has more than five or so layers. This is a problem that sees diminishing returns with increased parameter count - the primary metric that is driving the enormous data centers being built.

LLMs are a solution looking for a problem, and aside from 'bs for people who don't want to make any decisions in their day-to-day life' and 'scam generator', there doesn't seem to be very many niches that they are actually good at filling.

Everytime someone says to a worker in a factory "figure it out" it involves creativity in some way.

OpenAI and others have had data centers training models for 10 years. Chatgpt was released in 2022. A data center was churning for years before release to create that model.

Huh that's odd, then how come DeepMind was founded checks notes in 2010?

This meme implies that AI data centers have been around for a long time. They have not.

This response implies that you actually understand the point being made. You don't. If you think this is only about AI datacenters, I have to assume you're letting the AI 'think' for you. Otherwise, that says a lot about you, and none of it is positive.

AI have been running in datacenters for over a decade, it didn't just spring up overnight while the companies are building datacenters that cost billions in hardware that will be replaced in less than 5-10 years. They might as well be setting the cash on fire, it would harm the planet less than the result of pissing away billions of dollars on datacenters that may be bankrupt in under a decade when the AI companies start actually charging for cost and hardware that will need replaced before then.

intelligence /ĭn-tĕl′ə-jəns/
noun

The ability to acquire, understand, and use knowledge.

Much like you, AI is incapable of understanding anything, they just regurgitate what they hear.

AI aren't intelligent, they're stochastic parrots that can process words as math to generate a facsimile of intelligence to make the ignorant think it's smart.