[iepathos]

It's not all that surprising that people were worried and believed this. The AI companies and infrastructure companies partnering with them have spent a lot of money and time trying to convince people this is the case year after year. The critical clue people miss is that everyone claiming that has very clear financial incentives to convince people that's the case even when they know it isn't. Anyone who was actually building with LLMs and judging for themselves based on its performance knew fully well that wasn't the case year after year.

[atomicnumber3]

I've said this before: if anthropic (et al) thought they genuinely had a shot at replacing even 30% of white collar work, they would ABSOLUTELY NOT warn ANYONE. They would do what oil, leaded gas, and cigarette companies did. Swear under oath this is completely safe, commit GRIEVOUS societal harm that you explicitly promised wouldn't happen, and then end up in history books instead of jail for reasons beyond my ability to fathom.

No. The very fact they are trying to "warn" us means it's all marketing.

This has been corroborated for me on the engineering front that I can't find a single IC I respect who actually thought there was any evidence AI was going to live up to the hype. I saw a lot of people I always thought were idiots/sycophants/brown nosers go insane with AI. Never saw anyone id trust to help me cross a street blindfolded say more that "I may be wrong, but I'm not seeing any evidence yet".

[ffsm8]

Fwiw , you're conflating multiple things and consequently drawing premature conclusions.

It can be massively over hyped for it's current capacity and decimate the white collar work.

A lot of the difference of opinion is down to their point of view. At my dayjob, LLMs will not live up to anything because the enterprise is not structured to take advantage of it's strength. That's unlikely to change within the foreseeable future.

I strongly suspect you mostly talked with people coming from just such a background, because it's hard to go beyond our own bubbles

[atomicnumber3]

Sure, naturally. And yet parent commenter is remarking that simultaneously no AI-true-believer startups have supplanted the old money, and simultaneously despite much talk the bigcos have not slashed headcount to tiny AI-powered teams.

[ffsm8]

Hmm, isn't that just down to the fact people always vastly underestimate the amount of work software takes?

It takes a lot of time to successfully deliver a product. Even at the more "extreme" end of expectation - like saying it's a X10 multiplier (I'd disagree on that, it's more like 0.5-3 - depending on the type of work you're working on) you'd still need multiple years to go from first line of code to displacing established players. Things just don't change that fast.

[1attice]

Depends on the bigco IMO. I'm not sure what kind of layoff numbers for Year Three of genAI would grab your attention, but I assure you, hundreds of thousands have mine.

[root_axis]

The layoffs started years before LLMs became practical coding tools.

[1attice]

So you're saying companies correctly estimated the need to cut staff to remain competitive and did so -- or at least, some state of affairs empirically indistinguishable from this. Not much of an argument, sorry to say

[fhe]

Yes, this... all the hype from the leading AI companies just pattern-matched so many past cases where things didn't pan out. really giving me the bad vibes..

[pydry]

>The critical clue people miss is that everyone claiming that has very clear financial incentives to convince people that's the case even when they know it isn't.

Social media is flooded with bots pushing this narrative - coding is dead, engineers are all cooked, the latest model is scarily good, "what am I for?", etc.

A good rule of thumb is that if it's a human being and not a bot, they'll use the word "slop" at some point.