I get the feeling the author had a very simple and clear idea and then spent a lot of time fumbling about trying to present it clearly.
At one point I'm pretty sure there are six paragraphs shortly after each other that are all trying to restate the paragraphs before it. Since nothing seemed to become much clearer I kind of gave up at that point.
This seems to be the standard response to Ed’s work. He presents facts and figures that backup his theories in a painstaking manner and then detractors reply with something like this.
Following HNs guidelines, my most charitable interpretation of your response is that you don’t understand the arguments or numbers behind them and you aren’t just dismissing the arguments because you don’t like them. For that I’m saying you need to feed the article to the LLM of your choice and work back and forth until you get to an understanding of what’s being argued.
> Following HNs guidelines, my most charitable interpretation of your response is that you don’t understand the arguments or numbers behind them and you aren’t just dismissing the arguments because you don’t like them. For that I’m saying you need to feed the article to the LLM of your choice and work back and forth until you get to an understanding of what’s being argued.
That’s Zitron for ya. To be fair to him, he’s kind of forced into this position: he’s now famous for championing a cause (AI is dumb and will never work and the scientists are lying) that is becoming increasingly untenable by the day.
> AI is dumb and will never work and the scientists are lying
I don't see him making that claim, though.
Screwdrivers aren't useless. Screwdrivers have gotten a lot better over the decades. Everyone uses screwdrivers these days. Investing $500 billion into screwdrivers and expecting the screwdriver industry to grow to a double-digit percentage of GDP is still a really stupid idea. Let's face it: Universal Screwdriver[0] isn't going to happen.
Yeah, again this is the typical response from those who would rather stick their heads in the sand than face the reality that the spending is untenable.
They never refute his claims with anything substantial. They just call you “anti ai” or whatever (despite the argument having nothing to do with the technology, just a subset of companies).
Again, Zitron provides the numbers for his theories and they’re very compelling.
I’m still not seeing any equally compelling arguments as to why this is not the case. Only accusations of doomerism and links to him calling the bubble collapse early.
Nobody can rebut 10k words of rambling across half a dozen of separate arguments in a forum post. It'd be too long, and there is no readership for a point-by-point rebuttal for the dozens logic errors, misreprentations and various sleights of hand that the arguments (such as they are) are built on. And if you try to just rebut one thing, well, that wasn't actually the core argument but just incidental.
I've seen people talk about how compelling they find these articles, but literally never have they been able to point at a good argument. Like, in a paragraph, what's the most compelling and impactful argument in this article? What are a couple of numbers that make it so?
By 2029, according to their own projections:
OpenAI ≈ $184B/year
Anthropic ≈ $174B/year
Combined ≈ $358B/year
And remember, this is also in competition with open models that are increasingly encroaching on SOTA capabilities while costing less and allowing you to do more.
> I’m still not seeing any equally compelling arguments as to why this is not the case.
Zitron relies too heavily on how big the numbers are and not how workable the numbers are. Further, he seems to think that it will all just implode, which is pretty unlikely.
AI companies are making money. 1T in purchase negotiations is something that can be renegotiated if the numbers don't improve. And there's actually a pretty good chance that these AI companies sell the US federal government on AI being a strategic advantage which can ultimately gets a nice federal funding source.
Even in the worst case of what ed predicts, the more likely outcome is that the AI companies slow rollouts and purchases. The general market takes a hit, but it's ultimately not the end of the world.
But further, even with AI reducing their consumption, that doesn't mean chip manufacturers are hosed, we've already built up huge demand for things like RAM which are supremely supply constrained. That' has slowed the sale of consumer and enterprise electronics. Easing back on the AI market means those markets will likely pick up the slack again. Especially because I suspect businesses will be seriously thinking about things like "Why don't we deploy deepseek locally to save on compute cost?".
I suspect that prices for AI will ultimately increase before any of this happens and with those price increases that's where I can see there being more a demand to break ties with the bigger AI companies.
What Ed misses is that big business has much MUCH more flexibility when it comes to financing than even a midsize corperation. They have direct lines to bank presidents.
I agree the issue is not the scale but you're missing the reason the scale has allowed to inflate to these proportions is through purchase agreements that are enabled by other purchase agreements. Yes banks, other funders, and even the cash flow of the largest companies can provide lifelines, but why would they if the pullback begins? The problem with circular purchase agreements is the mechanism that allowed them to grow rapidly would also force them to shrink rapidly and most funders aren't going to want to catch that falling knife unless profit is near guaranteed, which it isn't. The numbers are still deeply in the world of speculative. Doesn't matter if you have a line to a bank president, they don't want to bail you out for free.
The point is that the numbers as they exist now require the industry to shoot the moon. It's not impossible, maybe the technology really is that revolutionary. But the margin for error is microscopic.
Let's say a kid's lemonade stand increases its revenue from $1/month to $100/month in three months. Clearly that 100x revenue increase per quarter is sustainable, so it predicts a $100M revenue a year from now, raises money at a $1B valuation, and signs a contract to buy $10M in industrial lemon squeezing machines. The squeezer manufacturer then predicts that it'll see a $500M revenue from all the other lemonade companies, raises money, and spends $1B on expanding its factories. Meanwhile, the kid is actually losing money because they are selling gold-leaf lemonade for $1 / glass while it costs $100 / glass to produce.
But the lemonade stand is making money! Worst-case scenario they'll just renegotiate the squeezer contract and slow down their growth, right? If the lemonade business goes bust they'll just sell hundreds of millions of dollars of squeezers to lime juice stands, right? The government will declare lemonade a "resource critical for national defense" and bail out the industry, right?
Yeah, sure, AI isn't 100% bullshit. There is indeed some money there, it won't be a complete collapse. But the numbers we are seeing are absolutely insane. We're already at "AI is bigger than the entire internet" levels of investments! Either we are collectively burning hundreds of billions of dollars on pure hype, or somehow every single company on the planet is hiding a secret 10x AI-boosted productivity increase.
Microsoft’s total depreciation and amortization in Q2 2027 was $11B - not clear how much of this is AI related. Apparently they had $34B in AI ARR as of May.
So let’s say their AI capex amortization and revenue are about equal. Not amazing, obviously they’re relying on continued growth, but doesn’t seem like the end of the world?
Compare that to Ed’s framing - Microsoft has $34B in revenue but spent $116B in capex last year to “make it”. They’re doomed!
But that capex spend is to make future revenue. Clearly he assumes demand won’t increase in the future, and that future projected revenue is “fake”. And sure, it definitely might not increase enough to make profitability.
But his whole analysis hinges on that one assumption. The entire article, all the numbers he gish gallops at you, could basically be replaced with “I don’t think AI demand and revenue will increase much beyond today.” Yeah, we know.
We see that companies are already balking at the cost and are increasingly looking at what the actual return of their current spend is, let alone when these prices have been increasing.
Where is the increase in demand going to be coming from?
Especially the increase needed to make this make sense?
My personal hunch is that the “diffusion curve” for AI is slower than most people in this space think. Most businesspeople I talk to have only tried a basic Copilot chat and/or free ChatGPT. Many still haven’t used anything “AI” at all. As more use cases become practicable and cost-effective, more software will include AI, and more people will use AI with or without knowing.
Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake. Of course they could be wrong, but they’re not made up.
> Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake.
I think Ed is wrong. But I have to push back. Wall street analysts are more likely to misrepresent precisely because they have money at stake. Much like ed has a pretty vested interest in saying the sky is falling (that's his brand at this point) the analysts have vested interests in saying everything is fine and keep investing.
We can see similar behaviors with analysts like zero hedge, which every week write a new "the bubble is about to pop" article.
A lot of this, IMO, is similar to a fact about the weather I'm probably misremember from stats. If you always predict "it will be sunny tomorrow" almost anywhere in the world you'll be right something like 80 to 90% of the time (citation needed).
Analysts who always say "things are great and stocks will go up" will be right most of the time. The tricky thing has always been predicting when and if a pop will happen.
Yes, fair point, analysts tend not to be too critical. But they are still developing more detailed models to understand and project things like revenue and profit, so there's some rigor - at least more than company leadership just giving takes or stating platitudes.
If you believe in the notion that the technology will improve to the point of being able to replace a human employee, the increase in demand is going to come from businesses that choose AI employees over human ones. Even if the AI employee costs more than human one, it's like a car vs a horse. The AI employee doesn't get sick, doesn't get into trouble with HR for sexual harassment, never comes into work hung over. You can hire 100 AI employees for a week and them fire them the next and not feel bad about it.
Whether this comes to pass is anyone's guess, but that's the theory.
I would say Ed makes three main claims in this post:
1) Companies are spending a ton on capex for future AI compute
2) Current levels of AI revenue are not enough to recoup that capex spend
3) Revenues won’t increase enough in the future to recoup that capex spend
Almost anyone, bubbler or not, would agree with points 1 and 2. But Ed cites dozens of numbers from different sources to repeat and reinforce them. It feels to me like an effort to overwhelm the reader with data to support his overall argument. That’s what I would call a gish gallop.
The third point is a prediction. He cites a lot of facts and numbers here too, but ultimately whether you believe his prediction is going to depend on your assumptions.
The thing is, I really would love to see a detailed analysis of capex spend and amortization. Capex spent on the future is a big unknown. But the big labs have claimed they are profitable on inference. How much capex was invested to create the capacity to serve current models? How much revenue is coming from serving those models? What does the full profitability picture look like? What does that imply for future demand needs?
On your last paragraph the simplest answer as to why we haven’t seen that is because they don’t want to show us because it wouldn’t paint a great picture for them.
Regarding Gish galloping, I don’t think you can Gish Gallup in writing. The point as you said is to rapidly overwhelm an opponent. That’s not possible in writing as the points can be argued one by one at the responders leisure.
Thank you, I will bear that in mind. I am mostly familiar with the term from online forums, where I’ve seen it used to refer to other forum posts, blog posts, etc.
> The other problem is the monstrous and abusive marketing campaign from the AI industry itself, and those who use AI on a regular basis. If you are against the consensus that AI will grow ever-larger every single quarter forever, you will be harassed and dogpiled across multiple social media platforms by everyone from AI influencers to actual journalists. The fact that it’s more professionally dangerous to critique the powerful than it is to align with them is disgusting, but I should be clear that these tactics only reinforce that I’m on the right track.
> As Nik Suresh noted in his recent piece, refusing to say that AI is giving you massive productivity benefits will lead to actual professional consequences, because so much is riding on the overall grift about what AI can do (which is much, much less than the boosters will promise). This runs antithetical to productivity or good sense, and everybody involved in it should be both eternally shamed and shunned from any sensible business.
> And while the AI industry and its fandom will claim that people like me are “skeptics” and “haters,” the outright hatred and vitriol that they spew for not falling in line behind a nakedly false narrative built on outright disinformation is disgraceful.
The most charitable way I can read those paragraphs is that he's vaguely alluding to a nebulous conspiracy by a cabal of elites, which evokes a specific ideology that cannot be discussed constructively.
Ed has repeatedly done the "why are people using LLMs?" bit but ignores what well-respected software engineers have actually said about them because he thinks they're AI boosters and they are just lying. At the least, it's an obvious blind spot to explain how the AI industry is what it is despite the numbers he reports arguing otherwise, and many of his industry trend predictions have been incorrect as a direct result.
You are reading way too much into it. The truth is far simpler: when someone's salary depends on AI being a success, you'll have a really hard time getting them to openly say anything negative about AI.
A huge portion of those "well-respected software engineers" work at companies which have pivoted to make AI an essential part of their strategy - because every company has. We're seeing companies where leadership explicitly says that anyone not enthusiastically making AI a core part of their workflow will get fired. It is literally forbidden to doubt AI. Want a promotion? Better start tokenmaxxing - your manager will be looking at your usage stats!
And it's going to be the same at the higher levels. A "CTO of $company says $100M AI investment was a massive waste" headline is obviously unacceptable. You've already burned the money, so why ruin your stock price by being "the only company too incompetent to properly use AI" rather than slowly and silently scaling it down while pretending everything is fine and parroting all the buzzwords your peers are using on LinkedIn?
The actual results are irrelevant. It does not matter if your AI results are mediocre, or "good in some edge cases", or "can speed up some easier work". The market has decided that AI is huge and a massive success, so anyone not adopting it and having extreme successes with it is a failure and will be punished.
There's no need to invent a conspiracy here. Simple self-preservation will do.
Ah, yes. Because someone owns NVDA in their retirement account, they're going to intellectually bankrupt themselves and totally lie about being able to use an LLM to generate code feels faster than writing it manually. No conspiracy at all!
I get the feeling the author had a very simple and clear idea and then spent a lot of time fumbling about trying to present it clearly.
At one point I'm pretty sure there are six paragraphs shortly after each other that are all trying to restate the paragraphs before it. Since nothing seemed to become much clearer I kind of gave up at that point.
This seems to be the standard response to Ed’s work. He presents facts and figures that backup his theories in a painstaking manner and then detractors reply with something like this.
Following HNs guidelines, my most charitable interpretation of your response is that you don’t understand the arguments or numbers behind them and you aren’t just dismissing the arguments because you don’t like them. For that I’m saying you need to feed the article to the LLM of your choice and work back and forth until you get to an understanding of what’s being argued.
> Following HNs guidelines, my most charitable interpretation of your response is that you don’t understand the arguments or numbers behind them and you aren’t just dismissing the arguments because you don’t like them. For that I’m saying you need to feed the article to the LLM of your choice and work back and forth until you get to an understanding of what’s being argued.
That definitely does not follow HN guidelines.
A simpler answer to why people always accuse him of being a bad writer is that he’s a bad writer, not that they’re too dumb for his genius.
> For that I’m saying you need to feed the article to the LLM of your choice
Ahh, the daily cry of the AntiAI crusader. Pretty fun to see it over here, tho! Usually it’s confined to reddit and bsky.
That’s Zitron for ya. To be fair to him, he’s kind of forced into this position: he’s now famous for championing a cause (AI is dumb and will never work and the scientists are lying) that is becoming increasingly untenable by the day.
> AI is dumb and will never work and the scientists are lying
I don't see him making that claim, though.
Screwdrivers aren't useless. Screwdrivers have gotten a lot better over the decades. Everyone uses screwdrivers these days. Investing $500 billion into screwdrivers and expecting the screwdriver industry to grow to a double-digit percentage of GDP is still a really stupid idea. Let's face it: Universal Screwdriver[0] isn't going to happen.
[0]: https://en.wikipedia.org/wiki/Universal_Paperclips
Yeah, again this is the typical response from those who would rather stick their heads in the sand than face the reality that the spending is untenable.
They never refute his claims with anything substantial. They just call you “anti ai” or whatever (despite the argument having nothing to do with the technology, just a subset of companies).
On the contrary, he's more obviously right every day passing.
Again, Zitron provides the numbers for his theories and they’re very compelling.
I’m still not seeing any equally compelling arguments as to why this is not the case. Only accusations of doomerism and links to him calling the bubble collapse early.
Nobody can rebut 10k words of rambling across half a dozen of separate arguments in a forum post. It'd be too long, and there is no readership for a point-by-point rebuttal for the dozens logic errors, misreprentations and various sleights of hand that the arguments (such as they are) are built on. And if you try to just rebut one thing, well, that wasn't actually the core argument but just incidental.
I've seen people talk about how compelling they find these articles, but literally never have they been able to point at a good argument. Like, in a paragraph, what's the most compelling and impactful argument in this article? What are a couple of numbers that make it so?
Juho, you have a well known blog and enough people would read it, so please go ahead and write a rebuttal.
Here, if this is just misrepresentations and logical fallacies than it should be easy to explain the main point away:
How are OAI and Anthropic reasonably and reliably going to make the profits they need to to hit these targets?
By Q1 2028: OpenAI ≳ $10B/month Anthropic ≳ $10B/month Combined ≳ $20B/month / $240B ARR
By 2029, according to their own projections: OpenAI ≈ $184B/year Anthropic ≈ $174B/year Combined ≈ $358B/year
And remember, this is also in competition with open models that are increasingly encroaching on SOTA capabilities while costing less and allowing you to do more.
> I’m still not seeing any equally compelling arguments as to why this is not the case.
Zitron relies too heavily on how big the numbers are and not how workable the numbers are. Further, he seems to think that it will all just implode, which is pretty unlikely.
AI companies are making money. 1T in purchase negotiations is something that can be renegotiated if the numbers don't improve. And there's actually a pretty good chance that these AI companies sell the US federal government on AI being a strategic advantage which can ultimately gets a nice federal funding source.
Even in the worst case of what ed predicts, the more likely outcome is that the AI companies slow rollouts and purchases. The general market takes a hit, but it's ultimately not the end of the world.
But further, even with AI reducing their consumption, that doesn't mean chip manufacturers are hosed, we've already built up huge demand for things like RAM which are supremely supply constrained. That' has slowed the sale of consumer and enterprise electronics. Easing back on the AI market means those markets will likely pick up the slack again. Especially because I suspect businesses will be seriously thinking about things like "Why don't we deploy deepseek locally to save on compute cost?".
I suspect that prices for AI will ultimately increase before any of this happens and with those price increases that's where I can see there being more a demand to break ties with the bigger AI companies.
What Ed misses is that big business has much MUCH more flexibility when it comes to financing than even a midsize corperation. They have direct lines to bank presidents.
I agree the issue is not the scale but you're missing the reason the scale has allowed to inflate to these proportions is through purchase agreements that are enabled by other purchase agreements. Yes banks, other funders, and even the cash flow of the largest companies can provide lifelines, but why would they if the pullback begins? The problem with circular purchase agreements is the mechanism that allowed them to grow rapidly would also force them to shrink rapidly and most funders aren't going to want to catch that falling knife unless profit is near guaranteed, which it isn't. The numbers are still deeply in the world of speculative. Doesn't matter if you have a line to a bank president, they don't want to bail you out for free.
The point is that the numbers as they exist now require the industry to shoot the moon. It's not impossible, maybe the technology really is that revolutionary. But the margin for error is microscopic.
Well, how workable are they?
Let's say a kid's lemonade stand increases its revenue from $1/month to $100/month in three months. Clearly that 100x revenue increase per quarter is sustainable, so it predicts a $100M revenue a year from now, raises money at a $1B valuation, and signs a contract to buy $10M in industrial lemon squeezing machines. The squeezer manufacturer then predicts that it'll see a $500M revenue from all the other lemonade companies, raises money, and spends $1B on expanding its factories. Meanwhile, the kid is actually losing money because they are selling gold-leaf lemonade for $1 / glass while it costs $100 / glass to produce.
But the lemonade stand is making money! Worst-case scenario they'll just renegotiate the squeezer contract and slow down their growth, right? If the lemonade business goes bust they'll just sell hundreds of millions of dollars of squeezers to lime juice stands, right? The government will declare lemonade a "resource critical for national defense" and bail out the industry, right?
Yeah, sure, AI isn't 100% bullshit. There is indeed some money there, it won't be a complete collapse. But the numbers we are seeing are absolutely insane. We're already at "AI is bigger than the entire internet" levels of investments! Either we are collectively burning hundreds of billions of dollars on pure hype, or somehow every single company on the planet is hiding a secret 10x AI-boosted productivity increase.
Ctrl-F “amortiz”: Not Found
Microsoft’s total depreciation and amortization in Q2 2027 was $11B - not clear how much of this is AI related. Apparently they had $34B in AI ARR as of May.
So let’s say their AI capex amortization and revenue are about equal. Not amazing, obviously they’re relying on continued growth, but doesn’t seem like the end of the world?
Compare that to Ed’s framing - Microsoft has $34B in revenue but spent $116B in capex last year to “make it”. They’re doomed!
But that capex spend is to make future revenue. Clearly he assumes demand won’t increase in the future, and that future projected revenue is “fake”. And sure, it definitely might not increase enough to make profitability.
But his whole analysis hinges on that one assumption. The entire article, all the numbers he gish gallops at you, could basically be replaced with “I don’t think AI demand and revenue will increase much beyond today.” Yeah, we know.
So where would this increased demand come from?
We see that these companies have no moat.
We see that companies are already balking at the cost and are increasingly looking at what the actual return of their current spend is, let alone when these prices have been increasing.
Where is the increase in demand going to be coming from? Especially the increase needed to make this make sense?
My personal hunch is that the “diffusion curve” for AI is slower than most people in this space think. Most businesspeople I talk to have only tried a basic Copilot chat and/or free ChatGPT. Many still haven’t used anything “AI” at all. As more use cases become practicable and cost-effective, more software will include AI, and more people will use AI with or without knowing.
Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake. Of course they could be wrong, but they’re not made up.
> Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake.
I think Ed is wrong. But I have to push back. Wall street analysts are more likely to misrepresent precisely because they have money at stake. Much like ed has a pretty vested interest in saying the sky is falling (that's his brand at this point) the analysts have vested interests in saying everything is fine and keep investing.
We can see similar behaviors with analysts like zero hedge, which every week write a new "the bubble is about to pop" article.
A lot of this, IMO, is similar to a fact about the weather I'm probably misremember from stats. If you always predict "it will be sunny tomorrow" almost anywhere in the world you'll be right something like 80 to 90% of the time (citation needed).
Analysts who always say "things are great and stocks will go up" will be right most of the time. The tricky thing has always been predicting when and if a pop will happen.
Yes, fair point, analysts tend not to be too critical. But they are still developing more detailed models to understand and project things like revenue and profit, so there's some rigor - at least more than company leadership just giving takes or stating platitudes.
Here's from a VC: https://x.com/bryce/status/2080766415716692385
"Have lost count of the number of CEOs I’ve talked to this week that are planning to be moved off OAI and Anthropic entirely by years end."
Interesting. I wonder what they will move to, and where it would be hosted.
If you believe in the notion that the technology will improve to the point of being able to replace a human employee, the increase in demand is going to come from businesses that choose AI employees over human ones. Even if the AI employee costs more than human one, it's like a car vs a horse. The AI employee doesn't get sick, doesn't get into trouble with HR for sexual harassment, never comes into work hung over. You can hire 100 AI employees for a week and them fire them the next and not feel bad about it.
Whether this comes to pass is anyone's guess, but that's the theory.
> gish gallops
this is a funny way of spelling "cites sources" and "does basic math"
> The Gish gallop is a debate tactic where one person overwhelms an opponent with a massive, rapid-fire stream of many minor, weak, or false arguments
https://en.wikipedia.org/wiki/Gish_gallop
yes, thank you, I also have access to Google
What data here is false? How do you gish gallop in writing?
I would say Ed makes three main claims in this post:
1) Companies are spending a ton on capex for future AI compute
2) Current levels of AI revenue are not enough to recoup that capex spend
3) Revenues won’t increase enough in the future to recoup that capex spend
Almost anyone, bubbler or not, would agree with points 1 and 2. But Ed cites dozens of numbers from different sources to repeat and reinforce them. It feels to me like an effort to overwhelm the reader with data to support his overall argument. That’s what I would call a gish gallop.
The third point is a prediction. He cites a lot of facts and numbers here too, but ultimately whether you believe his prediction is going to depend on your assumptions.
The thing is, I really would love to see a detailed analysis of capex spend and amortization. Capex spent on the future is a big unknown. But the big labs have claimed they are profitable on inference. How much capex was invested to create the capacity to serve current models? How much revenue is coming from serving those models? What does the full profitability picture look like? What does that imply for future demand needs?
On your last paragraph the simplest answer as to why we haven’t seen that is because they don’t want to show us because it wouldn’t paint a great picture for them.
Regarding Gish galloping, I don’t think you can Gish Gallup in writing. The point as you said is to rapidly overwhelm an opponent. That’s not possible in writing as the points can be argued one by one at the responders leisure.
Thank you, I will bear that in mind. I am mostly familiar with the term from online forums, where I’ve seen it used to refer to other forum posts, blog posts, etc.
> The other problem is the monstrous and abusive marketing campaign from the AI industry itself, and those who use AI on a regular basis. If you are against the consensus that AI will grow ever-larger every single quarter forever, you will be harassed and dogpiled across multiple social media platforms by everyone from AI influencers to actual journalists. The fact that it’s more professionally dangerous to critique the powerful than it is to align with them is disgusting, but I should be clear that these tactics only reinforce that I’m on the right track.
> As Nik Suresh noted in his recent piece, refusing to say that AI is giving you massive productivity benefits will lead to actual professional consequences, because so much is riding on the overall grift about what AI can do (which is much, much less than the boosters will promise). This runs antithetical to productivity or good sense, and everybody involved in it should be both eternally shamed and shunned from any sensible business.
> And while the AI industry and its fandom will claim that people like me are “skeptics” and “haters,” the outright hatred and vitriol that they spew for not falling in line behind a nakedly false narrative built on outright disinformation is disgraceful.
sigh
Whether wrong or profound, it probably deserves a bit of actual discourse.
The most charitable way I can read those paragraphs is that he's vaguely alluding to a nebulous conspiracy by a cabal of elites, which evokes a specific ideology that cannot be discussed constructively.
Ed has repeatedly done the "why are people using LLMs?" bit but ignores what well-respected software engineers have actually said about them because he thinks they're AI boosters and they are just lying. At the least, it's an obvious blind spot to explain how the AI industry is what it is despite the numbers he reports arguing otherwise, and many of his industry trend predictions have been incorrect as a direct result.
> a nebulous conspiracy by a cabal of elites
You are reading way too much into it. The truth is far simpler: when someone's salary depends on AI being a success, you'll have a really hard time getting them to openly say anything negative about AI.
A huge portion of those "well-respected software engineers" work at companies which have pivoted to make AI an essential part of their strategy - because every company has. We're seeing companies where leadership explicitly says that anyone not enthusiastically making AI a core part of their workflow will get fired. It is literally forbidden to doubt AI. Want a promotion? Better start tokenmaxxing - your manager will be looking at your usage stats!
And it's going to be the same at the higher levels. A "CTO of $company says $100M AI investment was a massive waste" headline is obviously unacceptable. You've already burned the money, so why ruin your stock price by being "the only company too incompetent to properly use AI" rather than slowly and silently scaling it down while pretending everything is fine and parroting all the buzzwords your peers are using on LinkedIn?
The actual results are irrelevant. It does not matter if your AI results are mediocre, or "good in some edge cases", or "can speed up some easier work". The market has decided that AI is huge and a massive success, so anyone not adopting it and having extreme successes with it is a failure and will be punished.
There's no need to invent a conspiracy here. Simple self-preservation will do.
Ah, yes. Because someone owns NVDA in their retirement account, they're going to intellectually bankrupt themselves and totally lie about being able to use an LLM to generate code feels faster than writing it manually. No conspiracy at all!
This isn't a conspiracy, which requires coordination between the co-conspirators: it's just old-fashioned common interest in propping up a bubble.
The use of this phrase by the science denial side of this debate is, so infuriating that I must simply end my comment here.
Look up, Ed. I know you know.