back
103 comments
> The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential. Everything else is transient

As long as the term “AI” means by-and-large LLMs with additional features sprinkled on top, the answer is no. More likely (without careful vetting by the folks aggregating these models) is that the quality will go down as more and more AI-generated output gets subsumed into these models.

Even without that particular problem, LLMs-as-AI can only give us probabilistic outputs based on inputs; and by definition they’re reliant on humans to provide the training data for their model. Without specialized knowledge or training on that knowledge (And even with it, viz. Meta’s engineering), we don’t have to worry about AI itself. We do have to worry what investors who are looking for outsized returns will do to get those returns, job market be damned.

The problem for us isn’t that AI will take our jobs; it’s that snake-oil salesmen can sell the idea that AI will take our jobs, investors buy into it, companies try it, fire their folks, the snake-oil salesmen IPOs, the companies that bought into this idea implode in some form or fashion, and the salesmen have already taken the money and ran. Of course, we still lose our jobs, but maybe (!) we get them back when this all fails?

> More likely (without careful vetting by the folks aggregating these models) is that the quality will go down as more and more AI-generated output gets subsumed into these models.

This assumes that there aren't algorithmic breakthroughs which reduce training/inference costs by several OOMs.

How much do these models need to do before people throw their hands in the air and say, ok this is happening. The Erdos unit distance problem, which as far as I understand was approached by multiple competent mathematicians was solved by a frontier model. Sure people argue there was no novelty there (I cannot comment as a non-mathematician) but it feels like they can draw lines laterally from deep knowledge in different fields (in this case combinatorics and algebraic number theory I believe) and solve problems.

Now if you have millions of instances running in parallel, all "probabilistic", working on frontier AI research I really don't see the blocker (and believe me I wish I did).

The only thing that matters is the economy of it all.

Open AI et al are hemorrhaging absurd amounts of money. It's not clear whether there will ever be a good balance between cost, value, and price.

Lots of companies are already questioning the value they get from LLMs at current prices which are obviously not enough to generate profits.

It’s no longer true that AI tools primarily get knowledge from their pre-training input data. That gives them a baseline, but nowadays AI chatbots and coding agents routinely assume they need to get up-to-date information in other ways, via web searches and other tool calling.

So I don’t see accuracy declining at least for programming.

>LLMs-as-AI can only give us probabilistic outputs based on inputs

I am not completely sure what you are saying here, but it sounds like a variation of the "it's just a stochastic parrot" argument, which is reductionist. The human brain is also just a bunch neurons firing.

Is model collapse still an unsolved topic? Once saw a method that determines if a training input is high quality.
> The problem for us isn’t that AI will take our jobs; it’s that snake-oil salesmen can sell the idea that AI will take our jobs, investors buy into it, companies try it, fire their folks, the snake-oil salesmen IPOs, the companies that bought into this idea implode in some form or fashion, and the salesmen have already taken the money and ran.

Or, it eventually becomes clear to enough people that the AI companies aren't going to make enough money to justify their valuations, so the asset bubble bursts, the economy crashes, and we lose our jobs.

>As long as the term “AI” means by-and-large LLMs with additional features sprinkled on top, the answer is no. More likely (without careful vetting by the folks aggregating these models) is that the quality will go down as more and more AI-generated output gets subsumed into these models.

Nope. This isn't how it works.

AI progress has largely been synthetic and has produced leaps and bounds capabilities increases in the last couple of years.

Sorry.

This is all noise. The leaders of these companies are flip-flopping to whatever sounds best for their current agenda - hiring, fundraising, pre-IPO, etc.

The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential. Everything else is transient noise.

> The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential.

I think we know the answer to that already - LLMs show no sign of improving intelligence and instead providers are going down the ‘agentic’ rabbit hole.

There are too many things missing, like a world model, understanding, and taste (in the sense of knowing what is good and what is not good).

> The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential

I agree with your sentiment (about the noise), however I think this over simplifies it a bit. We may get AI that is super-human at frontier research and dramatically accelerates the pace, and still have to wait decades before it disrupts the job market (or maybe never displaces all work).

For one, the answer may depend on material science and chip manufacturing that can take a very long to build out a supply chain for even with super AI help.

And we may just find that the human mind is way more capable than we thought and even with accelerating research it's just a harder problem than anyone expected, even algorithmically.

I expect it to be a bit of both, and from ~2015 - 2025 I was in the "AI is coming for all our jobs" camp. My perspective changed last year after doing a deep dive into latest science on the human brain. (I've kept a very close eye on AI dev progress for 12+ years.

It's important not to miss the fact that AI productivity was a useful excuse for companies looking to conduct layoffs. Did some companies buy the hype? Sure - but the biggest companies would have wanted that sweet stock price layoff bump anyways and AI was a readily available justification to get it.
> The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential.

What if the answer is flatly: no? All that other stuff starts to matter a lot then.

Predicating your business decisions on a potential breakthrough that may never come is frankly insane. Imagine if at the dawn of the car industry Ford decided that it's actually a race to build the first flying car and nothing else matters.

Sure, but let’s not pretend that people treated the statements of these ceos as strategic messaging. People very clearly treated what Altman, Zuck, Amodei etc have been saying as predictions, and it hasn’t been until they’ve been proven wrong that people have started with the counter-narrative.
> LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential

The cost is already outrunning the benefit to a massive amount, and the predicted expotential is not here yet. I predict it'll always be around the corner, a $1T model won't get there, but it will "look promising", but we'll sadly run out of money for the $10T or $100T model..

We have two worlds:

1. Cutting edge LLMs developing ASI/AGI. 2. AIs doing general knowledge work

The second world will be achieved far before the first world is achieved. And as the first path gets develolped, the second path becomes cheaper and cheaper to run inference on along with being democratized which reduces the margins for the cutting edge companies. It seems like a mad dash to go as far as possible until 90% of general work can be automated with more cheaply available tech

The leaders of these companies have no stake in it. They are beyond worldly concerns.

Napoleon got sent to Elba. Hitler ate a bullet. Your average tech CEO will still have more money than they can spend.

https://archive.is/Pn7GU
My read has been that a lot of leaders were trying to drive “being early” as the catalyst for future success. At the complexity scale of big orgs you’re mostly fiddling with the incentives that the system self-aligns toward. Firing a bunch of people does create an incentive to use AI, if you think it’ll help.

The more pernicious effect I’ve been seeing is that we’re living in the golden age of LLMs, but eventually that’ll fade. Tokens are subsidized and cheap, model capabilities leap forward regularly, and there’s competition driving it all. But even now there’s stories about frontier models suddenly becoming less capable, or providers switching to usage-based billing, and new model releases feel a bit more sluggish and less dramatic. (Fable/Mythos notwithstanding.)

Eventually the models are going to settle into a rut of being just “good enough” to earn a living rather than all this hoopla. A lot of people will be re-hired. And we’ll do it all again for the next wave.

I kind of wish there was a way to flip the script on the companies that gave up on humans and tried to switch to AI. Make them suffer for their idiocy in the same way that workers suffered or continue to suffer.

If that makes me a bad person, fine. If a few CEO's wind up working at 7-11 to make rent money, all the better.

> If a few CEO's wind up working at 7-11 to make rent money, all the better.

There are CEOs who have only ever failed abysmally their entire careers, and they generally only ever make more money. Accountability is for losers.

In case anyone else read the "flipped on" as "flipped the switch on" rather than "reversed course on", no, it's the latter.
Text-only, no Javascript, no ads/tracking:

  curl http://assets.msn.com/content/view/v2/Detail/en-in/AA27hbnR \
  |grep -o "<p>.*</p>" \
  |tr -d '\134' \
  |sed '1s/^/<meta charset=utf-8>/' > 1.htm

  firefox ./1.htm
  #links 1.htm
Honestly, this is just the inverse of them all getting hyped on AI replacing all the jobs. Between both of these positions, RTO, crypto, VR, it's really shown just how much they're trend chasers.

Only a Tech CEO speaks in absolutes, it seems.

The ultimate irony here is that the biggest jobs wipeout most likely to happen now is when all these “AI exploration lab” type teams that every company quickly created are blown up.

Most, if not nearly all, of these teams have little to show ROI wise and the music on the AI bubble is slowing dramatically. They went from seemingly unlimited budgets and headcount when CEOs said “get me some of that AI” to some really uncomfortable scenes playing out know as the same CEOs realize this has cost a fortune with little to show for it.

Can we just speed this up a little? I just want my $100 RAM prices back.
Yet layoffs excused by AI (expenses or claimed productivity gains) are continuing by the thousands each day, so... not sure what this is based on.
This is just based on Ramp’s data about their customers, but it seems that some companies are hiring more people after adopting AI?

https://econlab.substack.com/p/we-can-finally-say-ai-isnt-ki...

Individual firms can cut jobs while the overall economy sees more of that job pop up. That’s what happens when individuals become more efficient, new projects become more economical and more companies end up requiring these jobs.
It will affect jobs because the investment strategy works to degenerate the economy, but not because of the tech. Like a dog that barks at a truck and thinks he scared it away.
After watching the AI roll out for a couple years now I'm much more confident that it's just a scam. There is no net positive ROI on AI. It's not good enough, and the "mass job destruction" scenario offsets any marginal gains by eliminating the market for basically all products. That doesn't mean that mediocre C-suites won't try but it only takes 1-2 quarters to feel the burn and back track.
I recently tried to get customer service. I think it was from the DMV for my state. The website asked me to use the AI bot first. Completely useless. It took a phone call with a human to somewhat resolve the issue.
It's a rather useful tool... and it absolutely has been overhyped repeatedly and sold as a panacea.

If you believe AI will 10x you're developers you've drunk the kool-aid, if you believe AI will have no impact on your developers then you're being stubbornly ignorant.

Sorry, but you aren't familiar with frontier models if you think it's not "good enough". The latest models are quite a bit more capable than most people in many regards already.
Dumbasses the lot of them.

Took that nonsense to Capitol Hill, trying to tell a bunch of politicians who knew damn well they are only there as long as they can keep their voters employed. They could have asked their own AI what happens when employment reaches 40-50%. Hint: it's never good. They were going to become another problem the government had to solve.

Also, UBI is non-starter no matter what Sam Altman believes.

Sam Altman doesn't BELIEVE in UBI - but he knows it's the only way to SELL his product, therefore he pretends he believes in it. None of these guys want one cent going to anyone but themselves.
> UBI is non-starter no matter what Sam Altman believes.

Do you mean it's a non-starter in the current political climate? Or that you personally just don't think it will work?

Afer COVID and AI, the only buzzword left is WAR. Doesn't rhyme but we are well beyond funny.
Of course they have. Fewer developers means fewer tokens sold.

Until AI no longer needs human supervision, it's more profitable to tax as many employees as possible.

You do not need developers to spend tokens, regular people can spend tokens just as easily.
This just tells me they don't know anything and they should probably just stop talking, and everyone else should stop listening.
Remember it was reported that OpenAI didn't think that ChatGPT would be successful? OpenAI thought that ChatGPT was yet another toy before its launch. Yet once ChatGPT became an overnight success, Altman started to talk about how AI would be dangerous, how it would displace or even replace jobs. In contrast, Amodei seemed to always believe in what he said. So, can we say that Altman is a opportunistic businessman, and Amodei is a cult leader?
IMO Demis has the most reasonable takes.
article misses an important point that these big tech companies are all listed on the public market, any narrative about their decisions should weigh that reality and why suddenly its being disseminated.

personally, I am collecting 3 salaries working remotely. For one of the jobs, I am tasked with hiring other devs but i dont put the effort in as i dont see a point. i just say i can't find a decent engineer and why should i when a frontier models can do most of their work? in our job postings we see thousands of applicants in a very short period of time, i just do these multi stage interviews with a rotation of candidates to basically buy time while i work on another job

i see that things are getting very desperate and i feel for those that are still struggling to find SWE jobs, AI is absolutely doing a number and the gap is going to increase not decrease.

Any need to address the huge numbers of foreign workers in America putting direct, nonnegotiable pressure on those jobs?

It's time for the program to end.

The damage is done. The truly jarring realization isn't that AI companies made these predictions, but how eagerly countless corporations were willing to sacrifice their own people in pursuit of profit – even at the cost of economic collapse.
> there is an oversupply of SWE and a dwindling supply of jobs which pushes wages down

Which is exactly what every one on HN with a working brain predicted a decade+ ago.

decade+ ago AI agents were not a thing, it was only last year when it started picking up and there's less pressure to hire as frontier models improve massively
Now let’s see if there will be any real consequences for such reckless stupidity: my bet, nah.