Pop Culture
We recorded 27 claims from this post. 15 were checked against evidence. 12 can’t be checked. 21 more are held. Read the post at its source.
Claims from this post (27)
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: ContradictedSaid
“And yes, that sound you hear is the slow deflation of the bubble I've been warning you about since March.”
What we tested: The generative AI bubble is slowly deflating as of July 2024.
What happened: Their account of PitchBook data reports record generative-AI investment in Q2. The same article describes weaker US seed activity and cooler enthusiasm, so the contradiction concerns broad financial contraction. (Aspiring for Intelligence — Sabrina Albert and Vivek Ramaswami, )
Assessment: SupportedSaid
“For Goldman to suddenly turn on the AI movement suggests that it’s extremely anxious about the future of generative AI, with almost everybody agreeing on one core point: that the longer this tech takes to make people money, the more money it's going to need to make.”
What we tested: The longer generative AI takes to make money, the more money it will need to make.
What happened: The investor's model illustrates the recurring recovery burden from continued AI infrastructure spending. Its numerical estimate is not treated as audited industry profit or as a figure claimed by Zitron. (Sequoia Capital — David Cahn, )
Assessment: Can’t be checkedSaid
“While one might argue that it'll mean faster generative processes, there really is no barometer for what "better" looks like, and perhaps that's why ChatGPT, Claude and other LLMs have yet to take a leap beyond being able to generate stuff.”
What we tested: ChatGPT, Claude and other LLMs have not progressed beyond generating content, possibly because there is no measure of what 'better' means.
Assessment: Can’t be checkedSaid
“The training data crisis is one that doesn’t get enough attention, but it’s sufficiently dire that it has the potential to halt (or dramatically slow) any AI development in the near future.”
What we tested: The training data shortage could halt or dramatically slow AI development in the near future.
Assessment: UnresolvedSaid
“Or, put another way, each additional step becomes increasingly (and exponentially) more expensive to take.”
What we tested: Each additional step of AI model improvement becomes exponentially more expensive.
Assessment: UnresolvedSaid
“All of this excitement, every second of breathless hype has been built on this idea that the artificial intelligence industry – led by generative AI – will somehow revolutionize everything from robotics to the supply chain, despite the fact that generative AI is not actually going to solve these problems because it isn't built to do so.”
What we tested: Generative AI will not solve problems in robotics, the supply chain and similar areas because it is not built to.
Assessment: Can’t be checkedSaid
“In essence, replacing humans with AI might break everything if you're one of those bosses that doesn't actually know what the fuck it is they're talking about.”
What we tested: Replacing human workers with AI may break operations when the managers doing it do not understand the work.
Assessment: UnresolvedSaid
“The reason I'm suddenly bringing up superintelligences — or AGI (artificial general intelligence) — is because throughout every defense of generative AI is a deliberate attempt to get around the problem that generative AI doesn't really automate many tasks.”
What we tested: Generative AI does not really automate many tasks.
Assessment: Can’t be checkedSaid
“These are not things that you can train in a dataset, because they're derived from experiences inside and outside of the creative process.”
What we tested: The adaptability, judgment and responsibility of human creative workers cannot be trained into AI via datasets.
Assessment: Can’t be checkedSaid
“And fully replacing any creative is so very unlikely if you're doing so based on copying a million pieces of someone else's homework.”
What we tested: Fully replacing any creative worker is very unlikely if it is done by copying a million pieces of someone else's work.
Assessment: UnresolvedSaid
“In essence, on top of generative AI not having any killer apps, not meaningfully increasing productivity or GDP, not generating any revenue, not creating new jobs or massively changing existing industries, it also requires America to totally rebuild its power grid, which Janous regrettably adds the US has kind of forgotten how to do.”
What we tested: Generative AI's growth requires the US to totally rebuild its power grid.
Assessment: Can’t be checkedSaid
“Perhaps Sam Altman's energy breakthrough could be these fucking AI companies being made to pay for new power infrastructure.”
What we tested: AI companies should be made to pay for new power infrastructure.
Assessment: UnresolvedSaid
“Yet, I have a counterpoint: no it doesn't.”
What we tested: OpenAI does not have a secret, unreleased breakthrough technology.
Assessment: UnresolvedSaid
“Generative AI, as I said back in March, is peaking, if it hasn't already peaked.”
What we tested: Generative AI is peaking or has already peaked.
Assessment: ContradictedSaid
“It cannot do much more than it is currently doing, other than doing more of it faster with some new inputs.”
What we tested: Generative AI cannot do much more than it currently does, beyond doing it faster with new inputs.
What happened: The public evaluation reported 97.8% success on basic Blocksworld and 52.8% on its obfuscated version, where earlier tested LLMs remained below 5%. These are substantive planning gains; the event date denotes publication of the demonstration, since exact test-run dates are not supplied. (Valmeekam, Stechly, Gundawar and Kambhampati / arXiv, )
Assessment: ContradictedSaid
“It isn’t getting much more efficient.”
What we tested: Generative AI is not getting much more efficient.
What happened: The paper reports stronger model performance with 93.3% less attention-cache memory than DeepSeek 67B. Its deployment tests report 5.76 times the generation throughput on an eight-H800 node using the earlier service's workload distribution, demonstrating substantial resource-efficiency gains. (DeepSeek-AI / arXiv, )
Assessment: Can’t be checkedSaid
“Generative AI at best processes information when it trains on data, but at no point does it "learn" or "understand," because everything it's doing is based on ingesting training data and developing answers based on a mathematical sense or probability rather than any appreciation or comprehension of the material itself.”
What we tested: Generative AI does not learn or understand; it produces answers probabilistically from training data.
Assessment: Can’t be checkedSaid
“LLMs are entirely different pieces of technology to that of "an artificial intelligence" in the sense that the AI bubble is hyping, and it's disgraceful that the AI industry has taken so much money and attention with such a flagrant, offensive lie.”
What we tested: LLMs are not 'artificial intelligence' as hyped, and the AI industry has raised money on a lie.
Assessment: UnresolvedSaid
“The jobs market isn't going to change because of generative AI, because generative AI can't actually do many jobs, and it's mediocre at the few things that it's capable of doing.”
What we tested: Generative AI will not change the jobs market because it can't do many jobs and is mediocre at what it can do.
Assessment: UnresolvedSaid
“While it's a useful efficiency tool, said efficiency is based off of a technology that is extremely expensive, and I believe that at some point AI companies like Anthropic and OpenAI will have to increase prices — or begin to collapse under the weight of a technology that has no path to profitability.”
What we tested: At some point AI companies like OpenAI and Anthropic will have to raise prices or begin to collapse, because the technology has no path to profitability.
Assessment: Can’t be checkedSaid
“Generative AI is not the future, but a regurgitation of the past, a useful-yet-not-groundbreaking way to quickly generate "new" data from old that costs far too much to make the compute and energy demands worth it.”
What we tested: Generative AI is not the future but a regurgitation of the past: a useful but not groundbreaking way to quickly generate 'new' data from old, which costs far too much to make its compute and energy demands worth it.
Assessment: UnresolvedSaid
“Basically, there's going to be a moment that spooks a venture capital firm into pushing one of its startups to sell, or the sudden, unexpected yet very obvious collapse of a major player.”
What we tested: There will be a moment that spooks a venture capital firm into pushing one of its startups to sell, or a sudden, unexpected yet very obvious collapse of a major player.
Assessment: UnresolvedSaid
“I see no situation where OpenAI and Anthropic continue to iterate on Large Language Models in perpetuity, as at some point Microsoft, Amazon and Google decide (or are forced to decide) that cloud compute welfare isn't a business model.”
What we tested: OpenAI and Anthropic will not be able to keep iterating on LLMs indefinitely because Microsoft, Amazon and Google will at some point stop subsidizing their compute.
Assessment: Can’t be checkedSaid
“Without a real, tangible breakthrough — one that would require them to leave the world of LLMs entirely, in my opinion — it's unclear how generative AI companies can survive.”
What we tested: Without a real, tangible breakthrough, which in the author's opinion would require leaving LLMs entirely, it is unclear how generative AI companies can survive.
Assessment: UnresolvedSaid
“It's been eighteen months since this bubble inflated, and since then very little has actually happened involving technology doing new stuff, just an iterative exploration of the very clear limits of what an AI model that generates answers can produce, with the answer being "something that is, at times, sort of good."”
What we tested: In the 18 months since the AI bubble inflated, generative AI has done very little new, only iterating within clear limits.
Assessment: Can’t be checkedSaid
“I understand that big tech desperately needs this to be the next hypergrowth market as they haven't got any others, but pursuing this quasi-useful environmental disaster-causing cloud efficiency boondoggle will send shockwaves through the industry.”
What we tested: Big tech's pursuit of generative AI will send shockwaves through the tech industry.
Assessment: Can’t be checkedSaid
“It's all a disgraceful waste.”
What we tested: The generative AI boom is a disgraceful waste.
Held from this post (21)
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 record does not meet the current rules. Our reading, not assessed: Generative AI is not making money for anyone because it does not generate extra revenue for companies using it.
- The record does not meet the current rules. Our reading, not assessed: Generative AI has no killer apps, does not meaningfully raise productivity or GDP, generates no revenue, and is not creating jobs or transforming industries.
- The criteria are ambiguous. Our reading, not assessed: Generative AI costs have not come down and there seems to be no path to them falling meaningfully.
- The two reviews read the claim differently
- The criteria are ambiguous. Our reading, not assessed: Generative AI has not created new jobs in the 18 months since the boom began.
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: Google's emissions grew 48% over the last five years while it chased a technology that made its search engine even worse, with little to show for it.
- 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: Despite the hype, media attention and investment, the supposed AI 'innovations', such as restaurant AI ordering systems, do not even seem capable of replacing the jobs they are meant to replace.
- The record does not meet the current rules. Our reading, not assessed: Generative AI costs far too much, isn't getting cheaper, uses too much power, and doesn't do enough to justify its existence.
- The two reviews reached different assessments. Our reading, not assessed: Generative AI is unprofitable and unsustainable, and it is fundamentally limited in what it can do because it generates answers probabilistically.
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: Copy editors and concept artists provide far more valuable work than any generative AI can, yet because managers don't appreciate or take part in labor, these jobs are under assault from LLMs, to the point that copywriters are now being paid to make LLM output sound more human.
- The criteria are ambiguous. Our reading, not assessed: Part of the AI bubble's collapse will be investors punishing a major provider, most likely Microsoft or Google, for heavy investment in a low-revenue industry.
- The record does not meet the current rules. Our reading, not assessed: Generative AI is not creating new jobs or new ways of working, is not making money, and has no clear path to higher revenue.
- The criteria are ambiguous. Our reading, not assessed: Generative AI companies are burning money with no clear path to making more money.
- The two reviews reached different assessments. Our reading, not assessed: Generative AI has no killer apps, and none are on the horizon.
- The record does not meet the current rules. Our reading, not assessed: The author thinks the AI bubble's collapse will be a succession of bad events crested by one large one, such as the collapse of a major AI company like Character.ai.