The Generative AI Con
We recorded 30 claims from this post. 13 were checked against evidence. 17 can’t be checked. 17 more are held. Read the post at its source.
Claims from this post (30)
In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.
Assessment: Can’t be checkedSaid
“It's been just over two years and two months since ChatGPT launched, and in that time we've seen Large Language Models (LLMs) blossom from a novel concept into one of the most craven cons of the 21st century — a cynical bubble inflated by OpenAI CEO Sam Altman built to sell into an economy run by people that have no concept of labor other than their desperation to exploit or replace it.”
What we tested: In the just over two years since ChatGPT launched, LLMs have gone from a novel concept to one of the most craven cons of the 21st century: a cynical bubble inflated by Sam Altman, built to sell into an economy run by people whose only idea of labor is a desperate wish to exploit or replace it.
Assessment: UnresolvedSaid
“In short, most of the coverage you read on artificial intelligence is led by companies that benefit financially from you thinking artificial intelligence is important and by default all of this coverage mentions OpenAI or ChatGPT.”
What we tested: Most of the AI coverage you read is led by companies that benefit financially from you thinking AI is important, and by default all of this coverage mentions OpenAI or ChatGPT.
Assessment: SupportedSaid
“User numbers alone tell you nothing about the sustainability or profitability of a business, or how those people use the product.”
What we tested: User numbers alone tell you nothing about a business's sustainability or profitability, or about how its users use the product.
What happened: The disclosed figure is an aggregate weekly activity count. The inference supporting the claim is limited: this count does not encode profit, retention, purposes, or the distribution of activity across days. (PYMNTS, )
Assessment: UnresolvedSaid
“There isn't a single god damn startup in the history of anything — other than perhaps Facebook — that has had this level of coverage at such an early stage.”
What we tested: Apart from perhaps Facebook, no startup has had as much media coverage so early as ChatGPT/OpenAI.
Assessment: Can’t be checkedSaid
“These numbers suggest that these products aren't very popular at all!”
What we tested: The January 2025 Similarweb monthly visitor numbers for Gemini, Copilot, Perplexity and Claude suggest that these products aren't very popular at all.
Assessment: Can’t be checkedSaid
“And even then, we still don't have a killer app! There is no product that everybody loves, and there is no iPhone moment!”
What we tested: Generative AI has no killer app or iPhone moment despite massive investment.
Assessment: UnresolvedSaid
“There is no "artificial intelligence" part of Microsoft's revenue or earnings. This is literally Microsoft taking anything with "AI" on it and saying "we made money!"”
What we tested: Microsoft's $13bn AI run-rate figure is not a distinct reported segment but a relabelling of anything with AI.
Assessment: Can’t be checkedSaid
“$3.25 billion a quarter is absolutely pathetic.”
What we tested: Microsoft's roughly $3.25 billion a quarter in AI revenue is absolutely pathetic.
Assessment: SupportedSaid
“OpenAI burned more than $5 billion last year.”
What we tested: OpenAI burned more than $5 billion in 2024.
What happened: The reported 2024 net loss exceeds the stated threshold. This supports the passage's inclusive loss interpretation, not a claim about cash consumption. (Ars Technica, )
Assessment: UnresolvedSaid
“To be clear, OpenAI burned approximately $5 billion on compute alone.”
What we tested: OpenAI spent about $5 billion on compute alone in 2024.
Assessment: Can’t be checkedSaid
“That may very likely mean Anthropic burned more money than OpenAI somehow last year! These companies are absolutely atrocious at business!”
What we tested: Anthropic very likely burned more money than OpenAI in 2024, and both are atrocious at business.
Assessment: Can’t be checkedSaid
“This is laughable on many levels, chief of which is that OpenAI, which made around twice as much revenue as Anthropic did in 2024, barely made a billion dollars from API calls in the same year.”
What we tested: Anthropic's projection that API revenue will hit $20 billion in 2027 is laughable on many levels, chiefly because OpenAI, which made about twice Anthropic's revenue in 2024, barely made a billion dollars from API calls that year.
Assessment: Can’t be checkedSaid
“Dario Amodei — much like Sam Altman — is a liar, a crook, a carnival barker and a charlatan, and the things he promises are equal parts ridiculous and offensive.”
What we tested: Dario Amodei, like Sam Altman, is a liar, a crook, a carnival barker and a charlatan, and the things he promises are equal parts ridiculous and offensive.
Assessment: UnresolvedSaid
“Anthropic is currently raising $2 billion at a $60 billion valuation primarily based off of this trumped-up marketing nonsense.”
What we tested: Anthropic's $60bn valuation fundraise rests primarily on inflated marketing claims.
Assessment: MixedSaid
“The one "big thing" that they've been able to do is to use "reasoning" to make the Large Language Models "think" (they do not have consciousness, they are not "thinking," this just means using more tokens to answer a particular question and having multiple models check the work), which mostly results in them being a bit more accurate when generating an answer, but at the expense of speed and cost.”
What we tested: The one big thing AI model companies have been able to do is 'reasoning', which means using more tokens and multiple models checking the work rather than actual thinking, and mostly results in models being a bit more accurate at the expense of speed and cost.
What held: The developer acknowledges cost and speed limitations in the o1 discussion. This supports that part of the claim, but does not establish a universal tradeoff or predominantly small accuracy gains. (OpenAI, )
What did not: Appendix A reports AIME pass@1 scores of 44.6 for o1-preview and 9.3 for GPT-4o, showing substantial gains on a demanding reasoning task. These selected evaluations challenge the modest-gain characterization, but cannot determine gains across all ordinary usage. (OpenAI, )
Assessment: Can’t be checkedSaid
“When you put aside the hype and anecdotes, generative AI has languished in the same place, even in my kindest estimations, for several months, though it's really been years.”
What we tested: Putting aside the hype and anecdotes, generative AI has languished in the same place for several months even by his kindest estimate, though really for years.
Assessment: Can’t be checkedSaid
“To break this down, Altman is describing his next model — GPT 4.5 — as launching in some indeterminate timeframe and doing something probably quite similar to the current GPT 4o model.”
What we tested: GPT-4.5 will probably do something quite similar to GPT-4o.
Assessment: Can’t be checkedSaid
“It’s quintessential LLM copy — soulless and almost, but not quite, right.”
What we tested: Deep Research's writing is quintessential LLM copy, soulless and almost, but not quite, right.
Assessment: Can’t be checkedSaid
“OpenAI's next big thing is the ability to generate a report that you would likely not be able to use in any meaningful way anywhere, because while it can browse the web and find things and write a report, it sources things based on what it thinks can confirm its arguments rather than making sure the source material is valid or respectable.”
What we tested: Deep Research generates reports you would likely not be able to use in any meaningful way anywhere, because it sources material based on what it thinks confirms its arguments rather than making sure sources are valid or respectable.
Assessment: Can’t be checkedSaid
“These models don't know anything, and thus everything they do — even "reading" and "browsing" the web — is limited by their training data and probabilistic models that can say "this is an article about a subject" and posit their relevance, but not truly understand their contents.”
What we tested: Generative AI models know nothing and cannot truly understand the content they read or browse.
Assessment: Can’t be checkedSaid
“Deep Research repeatedly citing SEO-bait as a primary source proves that these models, even when grinding their gears as hard as humanely possible, are exceedingly mediocre, deeply untrustworthy, and ultimately useless.”
What we tested: Deep Research repeatedly citing SEO-bait as a primary source proves that these models, even when working as hard as possible, are exceedingly mediocre, deeply untrustworthy and ultimately useless.
Assessment: UnresolvedSaid
“Furthermore, nothing about this product moves OpenAI toward profitability. In fact, I think they're doing the opposite.”
What we tested: Nothing about Deep Research moves OpenAI toward profitability, and he thinks it moves OpenAI in the opposite direction.
Assessment: UnresolvedSaid
“Deep Research uses OpenAI's o3 model which can cost as much as $1,000 a query, and while I imagine these prompts aren't that expensive, they are still significantly more so than a regular query from ChatGPT.”
What we tested: Deep Research queries cost significantly more than regular ChatGPT queries.
Assessment: Can’t be checkedSaid
“Deep Research is the AI slop of academia — low-quality research-slop built for people that don't really care about quality or substance, and it’s not immediately obvious who it’s for.”
What we tested: Deep Research produces low-quality research slop with no clear audience.
Assessment: Can’t be checkedSaid
“People like Marc Benioff claiming that "today's CEOs are the last to manage all-human workforces" are doing so to pump up their stocks rather than build anything approaching a real product.”
What we tested: Claims by CEOs like Benioff about AI replacing workforces are made to pump stocks, not reflecting real products.
Assessment: UnresolvedSaid
“The tech industry — and part of our economy — is accelerating at speed into a brick wall, driven by people like Sam Altman, Dario Amodei, Marc Benioff, and Larry Ellison, all men that are incentivized to have you value their companies based on something other than what their businesses actually sell.”
What we tested: The tech industry and part of the economy are heading for a crash driven by AI leaders' hype.
Assessment: Can’t be checkedSaid
“Generative AI is a financial, ecological and social time bomb, and I believe that it's fundamentally damaging the relationship between the tech industry and society, while also shining a glaring, blinding light on the disconnection between the powerful and regular people.”
What we tested: Generative AI is a financial, ecological and social time bomb damaging tech's relationship with society.
Assessment: Can’t be checkedSaid
“This entire bubble has been inflated by hype, and by outright lies by people like Sam Altman and Dario Amodei, their lies perpetuated by a tech media that's incapable of writing down what's happening in front of their faces.”
What we tested: The AI bubble has been inflated by hype and lies from Altman and Amodei, amplified by tech media.
Assessment: UnresolvedSaid
“The damage will be tens of thousands of people fired, long-term environmental and infrastructural chaos, and a profound depression in Silicon Valley that I believe will dwarf the dot-com bust.”
What we tested: The damage will be tens of thousands of people fired, long-term environmental and infrastructural chaos, and a profound depression in Silicon Valley that he believes will dwarf the dot-com bust.
Assessment: UnresolvedSaid
“And when this all falls apart — and I believe it will — there will be a very public reckoning for the tech industry.”
What we tested: The generative AI boom will fall apart, leading to a very public reckoning for the tech industry.
Held from this post (17)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The two reviews read the claim differently
- The criteria are ambiguous. Our reading, not assessed: Anthropic's burn has increased every single year, and so has OpenAI's.
- The two reviews read the claim differently
- The record does not meet the current rules. Our reading, not assessed: It would appear that Altman is saying GPT-5 won't be a model at all but some sort of combination of different mediocre products, including o3, which he would no longer let users use.
- Attribution is uncertain
- The record does not meet the current rules. Our reading, not assessed: If ChatGPT had 300 million monthly active users, that would mean a conversion rate to paying users of under 4%, which he calls pretty piss-poor, especially since subscription revenue makes up the majority of OpenAI's revenue.
- The two reviews read the claim differently
- The record does not meet the current rules. Our reading, not assessed: More than two years into the generative AI boom, OpenAI's biggest, sexiest products are Deep Research, which spends a lot of compute to produce a poorly-cited research paper, and Operator, a compute-intensive application that rarely completes, in minutes, a task that would otherwise have taken you seconds.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The criteria are ambiguous. Our reading, not assessed: None of these generative AI companies are profitable, and despite repeated claims that the cost of inference is coming down, that doesn't appear to be helping them.
- The record does not meet the current rules. Our reading, not assessed: Deep Research and Operator barely fulfil their intended purposes, yet the media praises them.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: Similarweb traffic data does not appear consistent with OpenAI's claim of 300 million weekly ChatGPT users.
- The two reviews read the claim differently