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.
Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
21–30 of 106 posts
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#22> 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 s…
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.
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#23The 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.
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#24After 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.
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.
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#25Yet 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...
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#26> 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 s…
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.
> 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?
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#27Earlier quoted context omitted.
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.
> 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?
It’s true that they are only as good as their input data, but the same is true if you do your own web searches.
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#28> 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 s…
> 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).
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#29In case anyone else read the "flipped on" as "flipped the switch on" rather than "reversed course on", no, it's the latter.
Re: Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario
#30Earlier quoted context omitted.
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.
> 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?
Every lab is already training on synthetic data and has been for years now.