The “reverse centaur” is a natural product of capitalism wanting workers to be as replaceable as possible in order to drive down wages. An ordinary “centaur” is counter to companies’ goals, they don’t want workers empowered.
But what about the damage along the way? Misallocation of capital? Too many data centers and not enough jobs? CO2? Expensive RAM? Endless articles on HN about AI saying there are too many articles on HN about AI?
The bubble is weirdly being kept alive by the promise it can replace software developers, which is ironic because all it has really achieved is a deluge of slop.
Social media has also gone utterly crazy. The last time I saw a gaslighting operation on this scale and volume (including accounts who "hate" AI "because its so scary good") was during the start of the Gaza war.
These accounts becoming easier to distinguish too, because whether they boost AI or feign criticism they all categorically refuse to use the s word.
I guess there is a few trillion riding on perpetuating this mass psychosis so it makes sense they'd try to use every trick to keep it going as long as possible.
Internet bubble was nothing like this. The scale is greater, the promises are more insane and the pop is going to be much more devastating.
> “The bubble doesn’t want cheap useful things,” Doctorow said. “It wants expensive ‘disruptive’ things
That about sums it up. I challenge anyone to name five things that have gotten cheaper or better in their life thanks to AI.
I can't think of anything that I consume that has gotten better, and the only thing that has gotten cheaper is the value of your skills to your employer, as it wants you to offload more of your work to a machine they own or rent. But perhaps someone here can find some tangible improvement.
It's allowed me to learn things more quickly. For example, I haven't written any C++ professionally for 20 years, and found myself in the position of needing to know it again. The existing material online for learning it is thick; sometimes I have a question that isn't answered directly or clearly in any way I can find with a standard search. I can grill the LLM much more quickly and pointedly.
However, this does not answer the usefulness-at-work question. Does anyone care if I know how the initializer list braces in constructor `Foo{1,2}` work? Today for hiring managers smitten with AI, seems like they don't.
Personally, I'm just trying to stay sharp on the off-chance that things crash out and people who know how to engineer *and* code become highly valuable. If not, I'll be doing something else, anyway.
While I agree with your sentiment and observatin by and large, ideally you could have added a few constraints as a lot of people here have had "Holy shit" moments with AI, but often it's most pronounced in a very specific personal context. Learning topics faster, fixing things without having to call a repair man, life-saving medical tips (somewhat more of a thing because of a handicapped health system, but that's another discussion).
Funnily enough though, the benefits don't seem to scale to the work environment as smoothly across the board. It's almost as if, to use pg's famous line, they built things that don't scale.
The moment you scale AI beyond the personal context, the noisiness and non-determinism of the technology starts wrecking havoc in ripples through the industry, damn the productivity. Managing the slop you've created, but more importantly (I would normally put an emdash here) managing the slop others created turns out to be a problem as big as the tech that created it.
What is the evidence of this? Isn't it strange no revolutionary product has yet
been created from the coding output of this technology? More to the point, the only thing that comes close is the Claw. So what we have as the first breakaway product is something to help orchestrate the slop generators, instead of say, a new Phone OS that rivals Android and iOS, or a Metaverse that is actually worthy of its name. Nothing to see here, just more shovels to shovel the shit essentially.
We are still in the grasp of the electric and information revolution. Peter Thiel said more than a decade ago that if you compare life in the 70s and now the only major visible difference would simply be more screens in various forms nowadays. This he presented as evidence that no new revolutionary technology has been created in the interim. At present, the same is more true of AI. It has made access to information faster than before. However, unlike other processes of learning, it has made it more difficult to ascertain the correctness of the information presented. It is doing this by actively removing the direct connection between the information it presents and the primary sources responsible for that information (think Google replacing its search field with an AI field).
The non-LLM AI stuff in the medical field is what I find most promising. Not the banal AI doctors and nurses replacing real doctors and nurses, but more the research end of things, where hallucinating and pattern matching to create new compounds to test seems promising. Of course, any technology that is able to routinely aid discoveries in applied maths and physics will also be welcome.
If this half decade saw an explosion of new bespoke hardware being built and sold aided by LLMs (think a tech shop of 10 employees being able to build and sell robust smartphones from scratch to a niche market sustainably etc), or jumpstarts an era of reverse engineering on crack that pierces through the tech oligopoly then that would be evidence of disruption on a macro scale... But no, alas, we are still waiting.
says " Peter Thiel said more than a decade ago that if you compare life in the 70s and now the only major visible difference would simply be more screens in various forms nowadays. "
You could extend Thiel's statement back even to the 1960's: beyond address and phone lookup, everything added by the WWW has been of little use to a wise consumer IMO.
I've been enjoying the industrial revolution parallels. Have the economics of bespoke products changed? Not really. But is it now easier to get a crude, but functional, approximation of an idea? Yes. The main issue appears to be users conflating B for A (and not realising their AI creation is fundamentally a mess).
I find the industrial revolution parallels interesting too. I figure we're in the steam age and this is a bit like the railway bubble. Or maybe a bit before that - I'm not sure current AI is as useful as railways.
"If that’s the case, AI will let them wire the toy steering wheel directly into the drivetrain. So you can have an amazing idea as a corporate visionary, and you don’t have to have any ego-shattering confrontations with people who know how to do things, who tell you you’re actually an idiot"
Usually when talking about bubbles bursting its about a stock market bubble. P/E ratios now are approaching/passing the P/E ratios during the dot com boom/bust. Another reference point with high P/E ratios was around 1929-1930 (there are others too).
The dot com boom can be thought of as ecommerce which enabled investing in a lot of silly ideas at the time. A key technology that underpinned it all and won out was search. Every ecommerce site felt like they needed search, there were search engine companies, lots of competition across google, yahoo, etc.
An interesting lens to put on AI and the current stock market is that the software will be commoditized, its an eventuality. Its trending towards being able to run LLMs locally and get decent output. Decent is subjective but output similar to Q4 of 2025 models is when we started seeing more consistently usable output.
I believe that will a potential the inflection point for a bubble bursting the stock market: local or DIY LLMs producing "good enough" output and companies publicly backing away from enterprise contracts, lowering their AI spend if they can find cheaper ways to do it.
Ironically I had a job figuring out what he meant by strike at its roots so I asked an LLM. Gemini seems to think he means labour bargaining/strikes, attacking the stock bubble with better accounting regulations and open source.
I'm not sure any of those will make much difference beyond what's already happening?
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[ 3.1 ms ] story [ 49.7 ms ] threadSocial media has also gone utterly crazy. The last time I saw a gaslighting operation on this scale and volume (including accounts who "hate" AI "because its so scary good") was during the start of the Gaza war.
These accounts becoming easier to distinguish too, because whether they boost AI or feign criticism they all categorically refuse to use the s word.
I guess there is a few trillion riding on perpetuating this mass psychosis so it makes sense they'd try to use every trick to keep it going as long as possible.
Internet bubble was nothing like this. The scale is greater, the promises are more insane and the pop is going to be much more devastating.
That about sums it up. I challenge anyone to name five things that have gotten cheaper or better in their life thanks to AI.
I can't think of anything that I consume that has gotten better, and the only thing that has gotten cheaper is the value of your skills to your employer, as it wants you to offload more of your work to a machine they own or rent. But perhaps someone here can find some tangible improvement.
However, this does not answer the usefulness-at-work question. Does anyone care if I know how the initializer list braces in constructor `Foo{1,2}` work? Today for hiring managers smitten with AI, seems like they don't.
Personally, I'm just trying to stay sharp on the off-chance that things crash out and people who know how to engineer *and* code become highly valuable. If not, I'll be doing something else, anyway.
Funnily enough though, the benefits don't seem to scale to the work environment as smoothly across the board. It's almost as if, to use pg's famous line, they built things that don't scale.
The moment you scale AI beyond the personal context, the noisiness and non-determinism of the technology starts wrecking havoc in ripples through the industry, damn the productivity. Managing the slop you've created, but more importantly (I would normally put an emdash here) managing the slop others created turns out to be a problem as big as the tech that created it.
What is the evidence of this? Isn't it strange no revolutionary product has yet been created from the coding output of this technology? More to the point, the only thing that comes close is the Claw. So what we have as the first breakaway product is something to help orchestrate the slop generators, instead of say, a new Phone OS that rivals Android and iOS, or a Metaverse that is actually worthy of its name. Nothing to see here, just more shovels to shovel the shit essentially.
We are still in the grasp of the electric and information revolution. Peter Thiel said more than a decade ago that if you compare life in the 70s and now the only major visible difference would simply be more screens in various forms nowadays. This he presented as evidence that no new revolutionary technology has been created in the interim. At present, the same is more true of AI. It has made access to information faster than before. However, unlike other processes of learning, it has made it more difficult to ascertain the correctness of the information presented. It is doing this by actively removing the direct connection between the information it presents and the primary sources responsible for that information (think Google replacing its search field with an AI field).
The non-LLM AI stuff in the medical field is what I find most promising. Not the banal AI doctors and nurses replacing real doctors and nurses, but more the research end of things, where hallucinating and pattern matching to create new compounds to test seems promising. Of course, any technology that is able to routinely aid discoveries in applied maths and physics will also be welcome.
If this half decade saw an explosion of new bespoke hardware being built and sold aided by LLMs (think a tech shop of 10 employees being able to build and sell robust smartphones from scratch to a niche market sustainably etc), or jumpstarts an era of reverse engineering on crack that pierces through the tech oligopoly then that would be evidence of disruption on a macro scale... But no, alas, we are still waiting.
You could extend Thiel's statement back even to the 1960's: beyond address and phone lookup, everything added by the WWW has been of little use to a wise consumer IMO.
Just beautiful.
The dot com boom can be thought of as ecommerce which enabled investing in a lot of silly ideas at the time. A key technology that underpinned it all and won out was search. Every ecommerce site felt like they needed search, there were search engine companies, lots of competition across google, yahoo, etc.
An interesting lens to put on AI and the current stock market is that the software will be commoditized, its an eventuality. Its trending towards being able to run LLMs locally and get decent output. Decent is subjective but output similar to Q4 of 2025 models is when we started seeing more consistently usable output.
I believe that will a potential the inflection point for a bubble bursting the stock market: local or DIY LLMs producing "good enough" output and companies publicly backing away from enterprise contracts, lowering their AI spend if they can find cheaper ways to do it.
I'm not sure any of those will make much difference beyond what's already happening?