5 ms·

Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario

99 points by Brajeshwar 4mo ago

openquery 4mo ago
https://archive.is/Pn7GU https://archive.is/Pn7GU
openquery 4mo ago
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.
- FloorEgg 4mo ago
  > 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.
  - openquery 4mo ago
    > 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). I don't see why that's the case when you have super-human researchers on tap. There are indeed physical (supply chain-y) issues to deal with but isn't the whole point that: 1. Super-human at AI research + scaling to millions of instances will probably result in super-intelligence in everything which is not AI research. (a subset of which is white-collar work) 2. Use that super-intelligence to solve any supply-chain issues you might be facing. > 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 hope so but whenever I do, I feel like I'm coping hard and not dealing with the facts. I'm not saying we're there yet - I'm saying the trend lines are clear.
    - BobbyJo 4mo ago
      > Use that super-intelligence to solve any supply-chain issues you might be facing. I think this is where a lot of people's thinking goes awry. Unlimited intelligence doesn't mean unlimited resources or instantaneous implementation.
      - openquery 4mo ago
        > Unlimited intelligence doesn't mean unlimited resources or instantaneous implementation. Of course you're right. At the end of the day you need to deal with the bedrock which is the laws of physics. I could be wrong but I struggle to believe we are close to the edge of what is possible in getting the most out of our limited resources or time. Without atomic physics, uranium would just be another shiny rock in the ground. Sand is just what covers beaches. With enough time and intelligence we've made the shiny rock power cities and persuaded the sand to solve long-standing mathematical conjectures.
    - grttw1 4mo ago
      “I don't see why that's the case when you have super-human researchers on tap. ” Hahahaa this is what AI psychosis looks like
    - FloorEgg 4mo ago
      > I hope so but whenever I do, I feel like I'm coping hard and not dealing with the facts. Maybe I'm being naive, but as someone who spent 2015-2025 fully bought into the idea AI would replace all human labor within ~20 years, my updated take that it won't has a different flavor than coping. A bit contributor to my perspective was studying the physics of the brain, and a deeper understanding of the very hard economic constraints in the current LLM supply chain. Re the brain, we compute information in a fundamental different way that is over 1,000,000 more energy efficient than an LLM. We are also around 1,000,000 times more sample efficient at learning. There is a lot of details in terms of specifics between complexity in human brain architecture (variety of synapses, diversity of neuron types, etc) that have no material equivalent yet. And on the other side, understanding how hard it has been to build out euv lithography infra, and to completely retool manufacturing for a new paradigm of computing will require so much coordination, a super AI could have all the answers but we also have to deal with getting a bunch of stubborn people to align. Some people are just coping yes, but if you really zoom into the details on both sides of the equations the gap between where we are and what it would take to dramatically surpass human intelligence is vast. At the same time I think people overestimate how hard some kinds of knowledge work is (in absolute terms, since it's new and we haven't evolved into it as much), and how economically impactful human augmentation with weaker narrower AI can still be. (Lots of automation and prosperity but without such extreme disruption) I think in the very long term all bets are off, but we will have plenty of time to evolve our economic systems before we get there.
- AlexandrB 4mo ago
  > 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.
- grey-area 4mo ago
  > 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).
  - QuercusMax 4mo ago
    As long as LLMs don't understand the different between regurgitating facts and making up stories, they're going to necessarily be limited.
    - fancyfredbot 4mo ago
      They are taught the difference through reinforcement learning with verifiable rewards. Pretending you've solved the task or making up a story about how you solved it won't do well in that training step.
  - openquery 4mo ago
    > LLMs show no sign of improving intelligence and instead providers are going down the ‘agentic’ rabbit hole. I'm not sure where you're getting this. I don't work at Anthropic but Fable (Mythos) seems demonstrably smarter than Opus for pretty much any definition of smarter and they claim that Opus was used heavily in Mythos development (yeah I know take this with a massive pinch of salt). Either way if the models are indeed helping development, even on the engineering, you can iterate on models faster and even if they're not contributing to core research yet you still have a baby exponential by improving the engineering.
    - bigstrat2003 4mo ago
      Anthropic's claims about their own products have almost zero value as evidence. They have lied to our faces about stuff before, and will again if it drives the hype cycle which delivers them money.
- Bukhmanizer 4mo ago
  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.
- munk-a 4mo ago
  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.
- dayvid 4mo ago
  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
- taurath 4mo ago
  > 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..
  - openquery 4mo ago
    The only thing the $1T model needs to do is find some algorithmic speedup which allows it to be trained at $100B. I'm not saying that's easy or that it will happen but I just don't see why not.
    - taurath 4mo ago
      I don't understand the logic here - a methodology to increase efficiency by 90% in training doesn't exist until it does - could you explain what you mean by "I don't see why it won't exist"? Are you seeing consistent gains by some process?
- expedition32 4mo ago
  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.
yardie 4mo ago
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.
- lifestyleguru 4mo ago
  Afer COVID and AI, the only buzzword left is WAR. Doesn't rhyme but we are well beyond funny.
- feoren 4mo ago
  > 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?
  - yardie 4mo ago
    It won't work because it's unnecessary. If these boneheads are right AI will drive the price of goods down. Price of labor goes down. It's deflationary. UBI is a backstop against inflation. And really just there so that rich people's money is worth something.
    - hn_acc1 4mo ago
      UBI can also be a backstop against deflation, can't it? If no one has income, it doesn't matter if bread costs $1 per loaf instead of $3-5 now - no one will be able to afford even $1 eventually, after they've sold their house at a loss, sold their car, sold their laptop, iphone, etc.
- hn_acc1 4mo ago
  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.
cliglot 4mo ago
Now let’s see if there will be any real consequences for such reckless stupidity: my bet, nah.
- uejfiweun 4mo ago
  Of course not. This coming crash will be where we learn that tech is "too big to fail" in the same way that the financial system is. They'll let one player fail (likely Anthropic, due to the constant fighting with the government) and bail out the rest.
  - SpicyLemonZest 4mo ago
    I guess I'm not sure why you'd expect it to be any different than the dotcom bubble, when this didn't really happen. "Too big to fail" is a thing in finance because of contagion factors that don't really apply to tech; there's no number of AI company bankruptcies that would force your bank to suspend withdrawals.
    - 1986 4mo ago
      https://en.wikipedia.org/wiki/Collapse_of_Silicon_Valley_Bank https://en.wikipedia.org/wiki/Collapse_of_Silicon_Valley_Ban...
      - SpicyLemonZest 4mo ago
        I'm not sure what you're trying to imply with this link? As the first line of this article says, Silicon Valley Bank failed. The shareholders were wiped out. (Some people got confused because the Twitter conversation was primarily driven by rich VCs and founders who were depositors of the bank, quite reasonably arguing that they should get their money back if at all possible.)
    - uejfiweun 4mo ago
      The reason is because AI is viewed by the powers that be as inexorably linked to national security. If you haven't noticed, every lab out there has the same excuse when pressed about the disruption caused by their technology - "we do it or else China does."
gortok 4mo ago
> 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?
- skybrian 4mo ago
  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.
  - gortok 4mo ago
    > 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. How do those chat bots discern that the ‘web searches’ they’re using are returning human generated information only that’s been vetted instead of LLM output?
    - skybrian 4mo ago
speak_plainly 4mo ago
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.
josefritzishere 4mo ago
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.
- munk-a 4mo ago
  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.
  - grttw1 4mo ago
    [dead]
  - unsnap_biceps 4mo ago
    What we're seeing is that AI is enabling us to reduce product headcount, but increase the scope of ownership for teams. We used to require each product keep at least 3 people on it to ensure that knowledge doesn't get lost with a departure, but now we're comfortable allowing an individual engineer drive it and allow AI to accelerate onboarding for a replacement when needed. This means that the teams can now handle 3x the products and our wish lists are getting shorter over time.
- profsummergig 4mo ago
  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.
  - lifestyleguru 4mo ago
    Dunno, the pencil sound effect as they let you speak to AI is quite calming. Now we need and efficient way to penalise claimants getting impatient or even rude at AI.
deagle50 4mo ago
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.
- deadbabe 4mo ago
  You do not need developers to spend tokens, regular people can spend tokens just as easily.
drivingmenuts 4mo ago
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.
- feoren 4mo ago
  > 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.
gigel82 4mo ago
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.
- skybrian 4mo ago
  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-killing-jobs https://econlab.substack.com/p/we-can-finally-say-ai-isnt-ki...
- Gagarin1917 4mo ago
  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.
cmiles8 4mo ago
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.
- ryandrake 4mo ago
  Can we just speed this up a little? I just want my $100 RAM prices back.
  - lifestyleguru 4mo ago
    Not so long ago I felt I outsmarted the system by using my 10 years old computers and laptops, but slowly I'm starting to squeak like a little mouse.
kerblang 4mo ago
In case anyone else read the "flipped on" as "flipped the switch on" rather than "reversed course on", no, it's the latter.
zuzululu 4mo ago
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.
- catigula 4mo ago
  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.
  - zuzululu 4mo ago
    I don't see the need and I don't think it has the impact you think it does enterprises thrive when they have the freedom to choose who to hire without government interference
    - e44858 4mo ago
      I don't want enterprises to thrive. I want me to thrive.
      - zuzululu 4mo ago
        but if enterprises dont thrive you dont thrive either
    - Madmallard 4mo ago
      they thrive the people in their own country struggle to survive not seeing a problem with this is very suspicious
hintymad 4mo ago
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?
- openquery 4mo ago
  IMO Demis has the most reasonable takes.
gaigalas 4mo ago
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.
cliglot 4mo ago
> 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.
- zuzululu 4mo 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
cgearhart 4mo ago
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.
al_borland 4mo ago
This just tells me they don't know anything and they should probably just stop talking, and everyone else should stop listening.
Macha 4mo ago
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.
1vuio0pswjnm7 4mo ago
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

99 points by Brajeshwar 4mo ago

https://archive.is/Pn7GU https://archive.is/Pn7GU

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.

FloorEgg 4mo ago
> 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.
- openquery 4mo ago
  > 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). I don't see why that's the case when you have super-human researchers on tap. There are indeed physical (supply chain-y) issues to deal with but isn't the whole point that: 1. Super-human at AI research + scaling to millions of instances will probably result in super-intelligence in everything which is not AI research. (a subset of which is white-collar work) 2. Use that super-intelligence to solve any supply-chain issues you might be facing. > 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 hope so but whenever I do, I feel like I'm coping hard and not dealing with the facts. I'm not saying we're there yet - I'm saying the trend lines are clear.
  - BobbyJo 4mo ago
    > Use that super-intelligence to solve any supply-chain issues you might be facing. I think this is where a lot of people's thinking goes awry. Unlimited intelligence doesn't mean unlimited resources or instantaneous implementation.
    - openquery 4mo ago
      > Unlimited intelligence doesn't mean unlimited resources or instantaneous implementation. Of course you're right. At the end of the day you need to deal with the bedrock which is the laws of physics. I could be wrong but I struggle to believe we are close to the edge of what is possible in getting the most out of our limited resources or time. Without atomic physics, uranium would just be another shiny rock in the ground. Sand is just what covers beaches. With enough time and intelligence we've made the shiny rock power cities and persuaded the sand to solve long-standing mathematical conjectures.
  - grttw1 4mo ago
    “I don't see why that's the case when you have super-human researchers on tap. ” Hahahaa this is what AI psychosis looks like
  - FloorEgg 4mo ago
    > I hope so but whenever I do, I feel like I'm coping hard and not dealing with the facts. Maybe I'm being naive, but as someone who spent 2015-2025 fully bought into the idea AI would replace all human labor within ~20 years, my updated take that it won't has a different flavor than coping. A bit contributor to my perspective was studying the physics of the brain, and a deeper understanding of the very hard economic constraints in the current LLM supply chain. Re the brain, we compute information in a fundamental different way that is over 1,000,000 more energy efficient than an LLM. We are also around 1,000,000 times more sample efficient at learning. There is a lot of details in terms of specifics between complexity in human brain architecture (variety of synapses, diversity of neuron types, etc) that have no material equivalent yet. And on the other side, understanding how hard it has been to build out euv lithography infra, and to completely retool manufacturing for a new paradigm of computing will require so much coordination, a super AI could have all the answers but we also have to deal with getting a bunch of stubborn people to align. Some people are just coping yes, but if you really zoom into the details on both sides of the equations the gap between where we are and what it would take to dramatically surpass human intelligence is vast. At the same time I think people overestimate how hard some kinds of knowledge work is (in absolute terms, since it's new and we haven't evolved into it as much), and how economically impactful human augmentation with weaker narrower AI can still be. (Lots of automation and prosperity but without such extreme disruption) I think in the very long term all bets are off, but we will have plenty of time to evolve our economic systems before we get there.
AlexandrB 4mo ago
> 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.
grey-area 4mo ago
> 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).
- QuercusMax 4mo ago
  As long as LLMs don't understand the different between regurgitating facts and making up stories, they're going to necessarily be limited.
  - fancyfredbot 4mo ago
    They are taught the difference through reinforcement learning with verifiable rewards. Pretending you've solved the task or making up a story about how you solved it won't do well in that training step.
- openquery 4mo ago
  > LLMs show no sign of improving intelligence and instead providers are going down the ‘agentic’ rabbit hole. I'm not sure where you're getting this. I don't work at Anthropic but Fable (Mythos) seems demonstrably smarter than Opus for pretty much any definition of smarter and they claim that Opus was used heavily in Mythos development (yeah I know take this with a massive pinch of salt). Either way if the models are indeed helping development, even on the engineering, you can iterate on models faster and even if they're not contributing to core research yet you still have a baby exponential by improving the engineering.
  - bigstrat2003 4mo ago
    Anthropic's claims about their own products have almost zero value as evidence. They have lied to our faces about stuff before, and will again if it drives the hype cycle which delivers them money.
Bukhmanizer 4mo ago
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.
munk-a 4mo ago
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.
dayvid 4mo ago
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
taurath 4mo ago
> 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..
- openquery 4mo ago
  The only thing the $1T model needs to do is find some algorithmic speedup which allows it to be trained at $100B. I'm not saying that's easy or that it will happen but I just don't see why not.
  - taurath 4mo ago
    I don't understand the logic here - a methodology to increase efficiency by 90% in training doesn't exist until it does - could you explain what you mean by "I don't see why it won't exist"? Are you seeing consistent gains by some process?
expedition32 4mo ago
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.

yardie 4mo ago

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.

lifestyleguru 4mo ago
Afer COVID and AI, the only buzzword left is WAR. Doesn't rhyme but we are well beyond funny.
feoren 4mo ago
> 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?
- yardie 4mo ago
  It won't work because it's unnecessary. If these boneheads are right AI will drive the price of goods down. Price of labor goes down. It's deflationary. UBI is a backstop against inflation. And really just there so that rich people's money is worth something.
  - hn_acc1 4mo ago
    UBI can also be a backstop against deflation, can't it? If no one has income, it doesn't matter if bread costs $1 per loaf instead of $3-5 now - no one will be able to afford even $1 eventually, after they've sold their house at a loss, sold their car, sold their laptop, iphone, etc.
hn_acc1 4mo ago
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.

cliglot 4mo ago

Now let’s see if there will be any real consequences for such reckless stupidity: my bet, nah.

uejfiweun 4mo ago
Of course not. This coming crash will be where we learn that tech is "too big to fail" in the same way that the financial system is. They'll let one player fail (likely Anthropic, due to the constant fighting with the government) and bail out the rest.
- SpicyLemonZest 4mo ago
  I guess I'm not sure why you'd expect it to be any different than the dotcom bubble, when this didn't really happen. "Too big to fail" is a thing in finance because of contagion factors that don't really apply to tech; there's no number of AI company bankruptcies that would force your bank to suspend withdrawals.
  - 1986 4mo ago
    https://en.wikipedia.org/wiki/Collapse_of_Silicon_Valley_Bank https://en.wikipedia.org/wiki/Collapse_of_Silicon_Valley_Ban...
    - SpicyLemonZest 4mo ago
      I'm not sure what you're trying to imply with this link? As the first line of this article says, Silicon Valley Bank failed. The shareholders were wiped out. (Some people got confused because the Twitter conversation was primarily driven by rich VCs and founders who were depositors of the bank, quite reasonably arguing that they should get their money back if at all possible.)
  - uejfiweun 4mo ago
    The reason is because AI is viewed by the powers that be as inexorably linked to national security. If you haven't noticed, every lab out there has the same excuse when pressed about the disruption caused by their technology - "we do it or else China does."

gortok 4mo ago

> 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?

skybrian 4mo ago
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.
- gortok 4mo ago
  > 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. How do those chat bots discern that the ‘web searches’ they’re using are returning human generated information only that’s been vetted instead of LLM output?
  - skybrian 4mo ago

speak_plainly 4mo ago

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.

josefritzishere 4mo ago

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.

munk-a 4mo ago
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.
- grttw1 4mo ago
  [dead]
- unsnap_biceps 4mo ago
  What we're seeing is that AI is enabling us to reduce product headcount, but increase the scope of ownership for teams. We used to require each product keep at least 3 people on it to ensure that knowledge doesn't get lost with a departure, but now we're comfortable allowing an individual engineer drive it and allow AI to accelerate onboarding for a replacement when needed. This means that the teams can now handle 3x the products and our wish lists are getting shorter over time.
profsummergig 4mo ago
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.
- lifestyleguru 4mo ago
  Dunno, the pencil sound effect as they let you speak to AI is quite calming. Now we need and efficient way to penalise claimants getting impatient or even rude at AI.

deagle50 4mo ago

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.

deadbabe 4mo ago
You do not need developers to spend tokens, regular people can spend tokens just as easily.

drivingmenuts 4mo ago

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.

feoren 4mo ago
> 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.

gigel82 4mo ago

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.

skybrian 4mo ago
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-killing-jobs https://econlab.substack.com/p/we-can-finally-say-ai-isnt-ki...
Gagarin1917 4mo ago
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.

cmiles8 4mo ago

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.

ryandrake 4mo ago
Can we just speed this up a little? I just want my $100 RAM prices back.
- lifestyleguru 4mo ago
  Not so long ago I felt I outsmarted the system by using my 10 years old computers and laptops, but slowly I'm starting to squeak like a little mouse.

kerblang 4mo ago

In case anyone else read the "flipped on" as "flipped the switch on" rather than "reversed course on", no, it's the latter.

zuzululu 4mo ago

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.

catigula 4mo ago
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.
- zuzululu 4mo ago
  I don't see the need and I don't think it has the impact you think it does enterprises thrive when they have the freedom to choose who to hire without government interference
  - e44858 4mo ago
    I don't want enterprises to thrive. I want me to thrive.
    - zuzululu 4mo ago
      but if enterprises dont thrive you dont thrive either
  - Madmallard 4mo ago
    they thrive the people in their own country struggle to survive not seeing a problem with this is very suspicious

hintymad 4mo ago

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?

openquery 4mo ago
IMO Demis has the most reasonable takes.

gaigalas 4mo ago

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.

cliglot 4mo ago

> 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.

zuzululu 4mo 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

cgearhart 4mo ago

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.

al_borland 4mo ago

This just tells me they don't know anything and they should probably just stop talking, and everyone else should stop listening.

Macha 4mo ago

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.

1vuio0pswjnm7 4mo ago

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