The article has named sources for its quotes, whereas your comment relies entirely on "almost certainly" which sounds a lot less informed.

OP to me sounds more authentic and seems to have inside information.

After a quick search I found a publication actually mentioning about these tools:

Ford previously told Business Insider that it had developed two bespoke AI-enhanced scanning tools that helped validate that cars were properly assembled before rolling off the lot. The tools, called AiTriz and MAIVs, both debuted in 2024. https://autos.yahoo.com/policy-and-environment/articles/ford...

And after doing cursory research on these tools, it is clear they are rudimentary (as compared to SOTA LLMs), they were essentially smartphone mounted on stands and doing visual checks using the camera - so OP could be very right.

https://www.businessinsider.com/ford-uses-ai-cameras-in-fact...

A fine-tuned classifier purpose fit for a specific task can easily outperform a SOTA LLM on more modest hardware and often makes a lot more sense.

Calculator is a great analogy for that kind of specialized models. Way better than humans (and other things) at a specific task. Can't replace humans with it.

LLMs are not calculators.

If your data is sufficiently noisy or your relationship sufficiently simple a linear regression will outperform a SOTA LLM.

Nothing in the article contradicts their (IMHO accurate) claim. Three years ago boardrooms were not drinking the LLM Kool-aid yet, while ML-powered QC has been around for years. Remember Silicon Valley's hot dog vs not hot dog? That's pretty much all you need, only the hot dog is a car part.

Apparently it is not all you need, according to the article.

Yes, it seems like many are missing the crucial aspect of the timing. The mistake was realized 3 years ago and auto design and manufacturing process lead times are long. Plus the occasion for the story was 'Ford returning to the top of the JD Power Quality Survey rankings', so that's another 6-18 months of reporting lag. That puts the original layoff mistakes being made 5 to 8 years ago.

I don't know when the "MAIVIS and AiTriz pilots" you mention were implemented but another possibility is the Ford PR team saw that 'AI Backlash' stories are currently trending and opportunistically focused on that to explain a positive news event which likely had many causes. IMHO, we should view these 'AI Backlash' themed stories as no more valid than the 'AI Downsizing' themes they previously seized on to justify layoffs they wanted to do anyway.

>Yes, it seems like many are missing the crucial aspect of the timing.

First day on the internet propaganda-discourse machine?

If the article doesn't support your preconceived biases that's no problem, assume the title is true on it's face and comment reinforcing it. If neither of them support you then attack them. Welcome to internet comment sections.

Yeah, it looks like this wasn't AI related. I hope yours grows to be the top comment!

Submitted title was "Ford rehires 350 engineers after AI fails to preserve expertise or train juniors", which is not what the article says.

Submitters: "Please submit the original source. If a post reports on something found on another site, submit the latter." - https://news.ycombinator.com/newsguidelines.html

(We've reverted to the article's title now)

p.s. Article titles are sometimes rotated by the publications, in which case the submitter usually followed the guidelines but it takes time for us to catch up.

> This has nothing to do with LLMs and instead is almost certainly about their MAIVIS and AiTriz pilots

Where does this article say otherwise?

If you could read you'd know what I wrote there was nothing like what you're claiming