You’re completely right, if the goal is good customer support and decent working conditions for the operators.

It’s not. The goal is like 1rre said - make people get fed up and stop trying to get their stuff fixed, just buy a new one. Oh, and they could fire half the operators too, since less people would be willing to wade through the pile of shit to talk to them.

Money and profit, screw the rest.

And an excuse to fire half of the support staff.

This article and discussion is specifically about massively upscaling LLMs. Go follow the links and read OpenAI’s CEO literally proposing data centers which require multiple, dedicated grid-scale nuclear reactors.

I’m not sure what your definition of optimization and efficiency is, but that sure as heck does not fit mine.

Don’t look for statistical precision in analogies. That’s why it’s called an analogy, not a calculation.

No, this is the equivalent of writing off calculators if they required as much power as a city block. There are some applications for LLMs, but if they cost this much power, they’re doing far more harm than good.

https://arstechnica.com/health/2023/11/ai-with-90-error-rate-forces-elderly-out-of-rehab-nursing-homes-suit-claims/

Exactly this, and rightly so. The school’s administration has a moral and legal obligation to do what it can for the safety of its students, and allowing this to continue unchecked violates both of those obligations.

You are making it far simpler than it actually is. Recognizing what a thing is is the essential first problem. Is that a child, a ball, a goose, a pothole, or a shadow that the cameras see? It would be absurd and an absolute show stopper if the car stopped for dark shadows.

We take for granted the vast amount that the human brain does in this problem space. The system has to identify and categorize what it’s seeing, otherwise it’s useless.

That leads to my actual opinion on the technology, which is that it’s going to be nearly impossible to have fully autonomous cars on roads as we know them. It’s fine if everything is normal, which is most of the time. But software can’t recognize and correctly react to the thousands of novel situations that can happen.

They should be automating trains instead. (Oh wait, we pretty much did that already.)

Even talking about it this way is misleading. An LLM doesn’t “guess” or “catch” anything, because it is not capable of comprehending the meaning of words. It’s a statistical sentence generator; no more, no less.

This. Satire would be writing the article in the voice of the most vapid executive saying they need to abandon fundamentals and turn exclusively to AI.

However, that would be indistinguishable from our current reality, which would make it poor satire.

What part of “we paid these guys and they said we’re fine” do you not? Why would they choose and pay and release the results from a company they didn’t trust to clear them?

I’m not saying it’s rotten, but the fact that the third party was unilaterally chosen by and paid for LMG makes all the results pretty questionable.