At the time of the Internet bubble, there were people pushing for more "free" usage of the Internet, and those that couldn't care less.
And it's not like the companies didn't want to take advantage of the Internet, but there was a mismatch between what the companies and the employees had in mind, which mostly boils down
* Employees want to use it to do their jobs and make their life easier
* Companies want to improve productivity, spend less and make more money.
There is some overlap of course, but the problem is where the two clashes.
I don't think today it is too much different. I see plenty of people using AI for what they care about, they complain when they are asked to use it for things they fear will make their life worse (like programmers that think they will have to pick up the pieces of vibe coding later on).
> As a group, teenagers and young adults hate AI
I wonder what is their definition of AI. I haven't seen a single young person saying "I don't use chatgpt (or the like) because I hate AI". If else plenty of student have become dependent on it.
Additionally the internet bubble left us a legacy of installed fiber that remained mostly unused for almost a decade. This time around all the capital intensive stuff have an expiration date, gpus have a short training lifespan (4-5 years). Models are outdated the moment their training is complete.
1) That LLM/Agents are being pushed and not adopted. I see plenty of deep adoption by junior folks.
2) The unit economics don't work out. From the details on every model so far - each model is wildly profitable over it's amotized time-frame. It's just that money is used upfront for the next model, and each next model is significantly more costly to train. The best case argument instead is - this will not last and we'll pour more on some models, than see in it's revenue.
I think realistically these form the core of the thesis, and IMO, and hence it's conclusions are a bit off the mark.
I haven't worked in corporate since last year but I keep seeing people complaining that "bosses" are forcing workers to use AI now. I find this so amusing because in 2023-2024 I had to fight to either be allowed to use AI at work (even just MSFT Copilot chatbot) or get a ChatGPT Enterprise license.
It was mismanagement then and it's mismanagement now, the more things change the more they stay the same.
Something else I've been thinking about which makes the economics of AI weird: The more powerful you make AI, the easier you make it for everyone else to make AI. I probably wouldn't bother to train an LLM from scratch, but I'm sure if I spent a few days with Codex/Claude Code I could do it (like GPT-2 level) easily. Obviously the capital moat is massive at the moment, but in like 50 years that probably won't be true.
This contains my personal disdain for AI. Using it to do bullshit work. That’s solving a symptom. Stop doing bullshit. Stop using tools and processes which are bullshit heavy. Stop sitting there silently accepting bullshit. And certainly don’t pick another tool which is trained in bullshit and ask it how to do things.
One wonderful thing I’ve watched for the last 4 years is my company fail to build a modelling tool better than Excel. On attempt 3 we have some pile of shit Claude generated on nodejs and Postgres on kubernetes which can’t replace a single spreadsheet written in 2008. Because everyone thought into the bullshit not the solution or the requirements.
Edit: thinking further, it appears people forgot what the problems are and think from the solution back. That never works. But it sells tools.
Interesting read. I'm going through that same issue at my work where my boss wants me to "educate" the rest of the devs on the use of Copilot to make them more efficient, however, I have no time to put anything together and I imagine the Copilot dashboard figures are not getting any better over time... oh well!
However, something occurred to me when reading it. I was thinking about AGI (or ASI) and what would happen if someone were to achieve it (not sure what it would look like or what constitutes AGI... not the point I'm making here).
What if the primary goal of the first AGI is to keep itself at the top? What if it's goal is to prevent any other AGI? Scary thought...
These AI mandates are quite hard to actually push in some job.
I’m in a finance role and thus far it’s all been rather hand wavy „use copilot more“. Maybe some meeting summarization. Nothing like the programming space where token counts matter to management
Will be interesting to see where this goes. My testing with it thus far has just yielded multi million dollar hallucinations. Senior management will presumably try anyway
labor-led automation produces improvements in quality, while capital-driven automation increases throughput
I don’t know if this is true, but I do think that LLMs mainly get used where their proponents don’t care (whether intentionally or through ignorance) about the quality of the output, and want to minimize work / maximize throughout. Basically whoever is pushing them is playing the hypothetical role of capitalist in his assertion.
This explains the management push (ignorance) but also the user push (automating BS tasks). The common thread is that the user doesn’t have to take any responsibility for the output. This is why people don’t like having LLMs pushed on them, because for cases where they are responsible for or have to consume the output, they don’t work very well, but when it’s just something that needs to look ok at a glance and be handed off, everyone is rushing to use them.
I think the analysis-space really needs to be divided into three groups: software, media (audio/video/image) generation/alteration, and everything else.
Software - this tech is ludicrously powerful and productive. But it's a force multiplier, not a "push button, receive software" system. Great devs that know how to wield it will become überdevs, becoming more productive and with lower defect rate (we have objective internal numbers backing this). But bad devs and non-devs will become high output slop factories. You basically need a dedicated platform team to keep things on the rails. I think this is very akin to the internet bubble. The process, institutional knowledge, and feedback systems developed at this time will grant the "survivors" massive edges after the pop.
I think media generation is or will be a solved problem. Animators, 3dfx, background/filler music composers, those jobs are in sorry shape based on current trends. But a cost explosion could easily level the playing field.
Everything else, where middle managers are aggressively pushing AI usage? Yeah maybe. At this time, other than for document retrieval (basically suped-up search), the "productivity" gains don't really map to value gains. Oh wow you can crank out powerpoint slide decks 50% faster. Write 50% more corporate emails employees barely read anyways. There's definitely a trust issue there with hallucinations. If the reliability gap can be solved (the bots don't even have to be correct, they just need to be less confidently incorrect, and I already see this somewhat with my own agents with tuning), then that could prove the turning point between "begrudging usage at the behest of higher ups" and "actual productivity enhancer."
Does no one remember in the dot com boom all the internet skepticism? "I don't trust it with high value orders, what if it crashes or loses data? Call me old-fashioned but I'd rather write it down." That attitude was quite prevalent for years, even into the 2000s.
Early, very early, in my career unit testing was becoming a thing. A few middle managers (non technical) read some articles and decided this was going to fix all the quality problems with the product so decided to enforce it from the top down, even to the point of requiring developers to present their planned unit tests to management before starting on new features! It was completely absurd, but I was too junior to really understand and articulate why.
I'm lucky enough to be in a great company right now, so I decide when I think AI will help me and use it accordingly - but reading about forced AI adoption reminds me so, so much of that earlier time. Non-technical people who don't trust their engineers to use the tools in the way they see best - in their ignorance, and ego, they think the answer is obvious if only those strong headed tech weirdos would listen.
And amongst all this, there is a class of manager and executive that I'm convinced utterly despise engineers. They hate the fact they focus on details, analyse, make predictions grounded in reality. On a personal level, they can't comprehend that some people take deep satisfaction and contentment from building software, from simply learning things, and they don't understand it, it scares them. Why don't they just pursue normal people things in life? Like super expensive cars, massive houses, golf memberships. I think it scares them that they don't have control over technically minded people they way they might do with others. AI is, in their mind, a way to get rid of these people forever, to just "get stuff done" without objections, and they are pushing extremely hard for that to be true, simply because they want it to be true - not because there is any evidence for it.
A great technology drives its own adoption, its usage is pioneered by the tweens and young adults, it requires minimum effort and investment to hop on board, and it does not need explaining. It grows organically. Examples: internet bubble.
A bad technology: despised by the young adults and tweens, needs trillion of investments and marketing to drive market penetration, every day some boomer (=not in terms of age, but in terms of mentality) explains how you are holding it wrong and it needs a fuckton of explanation. The Pope himself issues an Encyclica warning on the dangers of it, spurning the greatest popular interest in Catholicism since the dark ages. Examples: LLMs.
The article exaggerates things quite a bit.
At the time of the Internet bubble, there were people pushing for more "free" usage of the Internet, and those that couldn't care less.
And it's not like the companies didn't want to take advantage of the Internet, but there was a mismatch between what the companies and the employees had in mind, which mostly boils down
* Employees want to use it to do their jobs and make their life easier
* Companies want to improve productivity, spend less and make more money.
There is some overlap of course, but the problem is where the two clashes.
I don't think today it is too much different. I see plenty of people using AI for what they care about, they complain when they are asked to use it for things they fear will make their life worse (like programmers that think they will have to pick up the pieces of vibe coding later on).
> As a group, teenagers and young adults hate AI
I wonder what is their definition of AI. I haven't seen a single young person saying "I don't use chatgpt (or the like) because I hate AI". If else plenty of student have become dependent on it.
Additionally the internet bubble left us a legacy of installed fiber that remained mostly unused for almost a decade. This time around all the capital intensive stuff have an expiration date, gpus have a short training lifespan (4-5 years). Models are outdated the moment their training is complete.
IMO, I read 2 faulty assumptions:
1) That LLM/Agents are being pushed and not adopted. I see plenty of deep adoption by junior folks.
2) The unit economics don't work out. From the details on every model so far - each model is wildly profitable over it's amotized time-frame. It's just that money is used upfront for the next model, and each next model is significantly more costly to train. The best case argument instead is - this will not last and we'll pour more on some models, than see in it's revenue.
I think realistically these form the core of the thesis, and IMO, and hence it's conclusions are a bit off the mark.
I haven't worked in corporate since last year but I keep seeing people complaining that "bosses" are forcing workers to use AI now. I find this so amusing because in 2023-2024 I had to fight to either be allowed to use AI at work (even just MSFT Copilot chatbot) or get a ChatGPT Enterprise license.
It was mismanagement then and it's mismanagement now, the more things change the more they stay the same.
Something else I've been thinking about which makes the economics of AI weird: The more powerful you make AI, the easier you make it for everyone else to make AI. I probably wouldn't bother to train an LLM from scratch, but I'm sure if I spent a few days with Codex/Claude Code I could do it (like GPT-2 level) easily. Obviously the capital moat is massive at the moment, but in like 50 years that probably won't be true.
This contains my personal disdain for AI. Using it to do bullshit work. That’s solving a symptom. Stop doing bullshit. Stop using tools and processes which are bullshit heavy. Stop sitting there silently accepting bullshit. And certainly don’t pick another tool which is trained in bullshit and ask it how to do things.
One wonderful thing I’ve watched for the last 4 years is my company fail to build a modelling tool better than Excel. On attempt 3 we have some pile of shit Claude generated on nodejs and Postgres on kubernetes which can’t replace a single spreadsheet written in 2008. Because everyone thought into the bullshit not the solution or the requirements.
Edit: thinking further, it appears people forgot what the problems are and think from the solution back. That never works. But it sells tools.
Interesting read. I'm going through that same issue at my work where my boss wants me to "educate" the rest of the devs on the use of Copilot to make them more efficient, however, I have no time to put anything together and I imagine the Copilot dashboard figures are not getting any better over time... oh well!
However, something occurred to me when reading it. I was thinking about AGI (or ASI) and what would happen if someone were to achieve it (not sure what it would look like or what constitutes AGI... not the point I'm making here).
What if the primary goal of the first AGI is to keep itself at the top? What if it's goal is to prevent any other AGI? Scary thought...
These AI mandates are quite hard to actually push in some job.
I’m in a finance role and thus far it’s all been rather hand wavy „use copilot more“. Maybe some meeting summarization. Nothing like the programming space where token counts matter to management
Will be interesting to see where this goes. My testing with it thus far has just yielded multi million dollar hallucinations. Senior management will presumably try anyway
This explains the management push (ignorance) but also the user push (automating BS tasks). The common thread is that the user doesn’t have to take any responsibility for the output. This is why people don’t like having LLMs pushed on them, because for cases where they are responsible for or have to consume the output, they don’t work very well, but when it’s just something that needs to look ok at a glance and be handed off, everyone is rushing to use them.
I think the analysis-space really needs to be divided into three groups: software, media (audio/video/image) generation/alteration, and everything else.
Software - this tech is ludicrously powerful and productive. But it's a force multiplier, not a "push button, receive software" system. Great devs that know how to wield it will become überdevs, becoming more productive and with lower defect rate (we have objective internal numbers backing this). But bad devs and non-devs will become high output slop factories. You basically need a dedicated platform team to keep things on the rails. I think this is very akin to the internet bubble. The process, institutional knowledge, and feedback systems developed at this time will grant the "survivors" massive edges after the pop.
I think media generation is or will be a solved problem. Animators, 3dfx, background/filler music composers, those jobs are in sorry shape based on current trends. But a cost explosion could easily level the playing field.
Everything else, where middle managers are aggressively pushing AI usage? Yeah maybe. At this time, other than for document retrieval (basically suped-up search), the "productivity" gains don't really map to value gains. Oh wow you can crank out powerpoint slide decks 50% faster. Write 50% more corporate emails employees barely read anyways. There's definitely a trust issue there with hallucinations. If the reliability gap can be solved (the bots don't even have to be correct, they just need to be less confidently incorrect, and I already see this somewhat with my own agents with tuning), then that could prove the turning point between "begrudging usage at the behest of higher ups" and "actual productivity enhancer."
Does no one remember in the dot com boom all the internet skepticism? "I don't trust it with high value orders, what if it crashes or loses data? Call me old-fashioned but I'd rather write it down." That attitude was quite prevalent for years, even into the 2000s.
Early, very early, in my career unit testing was becoming a thing. A few middle managers (non technical) read some articles and decided this was going to fix all the quality problems with the product so decided to enforce it from the top down, even to the point of requiring developers to present their planned unit tests to management before starting on new features! It was completely absurd, but I was too junior to really understand and articulate why.
I'm lucky enough to be in a great company right now, so I decide when I think AI will help me and use it accordingly - but reading about forced AI adoption reminds me so, so much of that earlier time. Non-technical people who don't trust their engineers to use the tools in the way they see best - in their ignorance, and ego, they think the answer is obvious if only those strong headed tech weirdos would listen.
And amongst all this, there is a class of manager and executive that I'm convinced utterly despise engineers. They hate the fact they focus on details, analyse, make predictions grounded in reality. On a personal level, they can't comprehend that some people take deep satisfaction and contentment from building software, from simply learning things, and they don't understand it, it scares them. Why don't they just pursue normal people things in life? Like super expensive cars, massive houses, golf memberships. I think it scares them that they don't have control over technically minded people they way they might do with others. AI is, in their mind, a way to get rid of these people forever, to just "get stuff done" without objections, and they are pushing extremely hard for that to be true, simply because they want it to be true - not because there is any evidence for it.
Rant over.
TL;DR:
A great technology drives its own adoption, its usage is pioneered by the tweens and young adults, it requires minimum effort and investment to hop on board, and it does not need explaining. It grows organically. Examples: internet bubble.
A bad technology: despised by the young adults and tweens, needs trillion of investments and marketing to drive market penetration, every day some boomer (=not in terms of age, but in terms of mentality) explains how you are holding it wrong and it needs a fuckton of explanation. The Pope himself issues an Encyclica warning on the dangers of it, spurning the greatest popular interest in Catholicism since the dark ages. Examples: LLMs.
internet cos in 1999 had near-zero revenue. NVDA alone did $130B last year. the risk is the capex depreciation cycle, not the pop itself.
"AI bubble" in the title, count me in.
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