Unresolved claims, page 1 of 8
Claims by Gary Marcus and Ed Zitron. Deadlines are judged as of 2026-10-29.
Unresolved claims (795)
The record was checked, and the evidence available by the cutoff does not settle it. Forecasts whose deadline has not arrived are listed apart, as not yet due.
Page 1 of 8: claims 1 to 100 of 795, ordered by the date first said, newest first. To find a claim by its words, use search.
Assessment: UnresolvedSaid
Gary Marcus Observation
“And the effects of all that IP theft on artists and writers, and potential negative effects more broadly across the employment market (though, mercifully, these have been more modest than some people expected).”
Our reading: Generative AI's negative effects on the employment market have so far been more modest than some expected, while its IP theft has harmed artists and writers.
No horizon Evidence as of
Limitation: No verified earlier employment expectation matches measured September 2026 outcomes in population, measure and elapsed period [e1][e2][e5].
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“Although it is unreliable and prone to hallucinations, it is terrific at making plausible sounding text (e.g., phishing attacks to trick people into revealing credentials) and deepfaked videos at virtually zero cost, allowing attackers to broaden their attacks.”
Our reading: Although generative AI is unreliable and prone to hallucinations, it is terrific at making plausible sounding text (such as phishing attacks) and deepfaked videos at virtually zero cost, allowing attackers to broaden their attacks.
No horizon Evidence as of
Limitation: Virtually zero is undefined.
Source: Breaking news: U.S. banks are taking hits from AI agents
Assessment: UnresolvedSaid
Gary Marcus Forecast
“The Trump administration will do little to hold them responsible.”
Our reading: The Trump administration will do little to hold the AI industry responsible for harms.
No deadline stated Evidence as of
Limitation: 'Little' has no threshold, so final judgment will turn on reading the overall record.
Source: Breaking news: U.S. banks are taking hits from AI agents
Assessment: UnresolvedSaid
Ed Zitron Observation
“In other words, venture capital is not particularly good at creating value, and has, in a period of poor value creation, centralized the majority of its investments in a single industry, with the majority of those investments going to companies related to or powered by Large Language Models that have yet to prove their economic worth.”
Our reading: Venture capital is not particularly good at creating value and has put the majority of its investments into a single industry (AI), with the majority of those going to LLM-related or LLM-powered companies that have yet to prove their economic worth.
No horizon Evidence as of
Limitation: AI classifications are broader than LLM classifications.
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Ed Zitron Conditional forecast
“To sustain the valuation of these stocks — let alone continue growing — will require every company involved to either spend or make hundreds of billions of dollars in perpetuity, increasing every single quarter, without fail.”
Our reading: Sustaining AI-trade stock valuations requires every company involved to spend or make hundreds of billions of dollars in perpetuity, increasing every quarter.
No deadline stated Evidence as of
Only if: to sustain current valuations
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Ed Zitron Conditional forecast
“If demand wavers, NVIDIA, Broadcom, Micron, AMD, and any associated silicon or hardware counterparties will see their revenue growth stumble, which will have a brutal knock-on effect on their stocks.”
Our reading: If hyperscaler and neocloud demand wavers, NVIDIA, Broadcom, Micron, AMD and related suppliers will see revenue growth stumble and their stocks suffer badly.
No deadline stated Evidence as of
Only if: if hyperscaler and neocloud GPU demand wavers
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Ed Zitron Causal claim
“This has led to the single-highest inflow of foreign investments into US equities in history — larger than the Dot-Com Bubble, the leadup to the Great Financial Crisis, and even the dying gasps of the Zero Interest Free Era in 2021, per Apollo:”
Our reading: The AI bubble has driven the highest inflow of foreign investment into US equities in history, larger than the Dot-Com era, pre-GFC, or 2021.
No horizon Evidence as of
Limitation: Search snippets were not promoted into evidence.
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Ed Zitron Observation
“As of typing this sentence, NVIDIA alone makes up 11.31% of the NASDAQ 100, with the combined weight of NVIDIA, Google, Amazon, Meta, Microsoft, Broadcom, Micron, AMD and CoreWeave representing about 46.5% of the index’s value, or 39.3% of the entire 3000-company NASDAQ composite.”
Our reading: NVIDIA is 11.31% of the NASDAQ 100, and nine AI-trade companies make up about 46.5% of the NASDAQ 100 and 39.3% of the NASDAQ Composite.
No horizon Evidence as of
Limitation: No later-date percentage was treated as counterevidence.
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Ed Zitron Conditional forecast
“And let’s be clear about something: all it takes is the vibe souring to the point that people lose faith in the AI trade for everything to start to collapse.”
Our reading: If people lose faith in the AI trade, everything will start to collapse.
No deadline stated Evidence as of
Only if: if sentiment sours and people lose faith in the AI trade
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Ed Zitron Observation
“This is one of the core issues with measuring AI demand — that the vast majority of it comes from selling services that do not make any economic sense.”
Our reading: The vast majority of AI demand comes from selling services that do not make any economic sense.
No horizon Evidence as of
Limitation: The result depends on interpreting economic sense as delivery-cost coverage.
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Ed Zitron Causal claim
“Their elevated valuations come from a belief that they’ll grow in perpetuity, much like the American markets.”
Our reading: The elevated valuations of AI-related stocks in Taiwan, Japan and Korea come from a belief they will grow in perpetuity.
No horizon Evidence as of
Limitation: One analyst's model cannot represent all investors.
Source: AI Had Better Work Out
Assessment: UnresolvedSaid
Gary Marcus Observation
“A lot of the discussion on social media has been reduced to an ignorant cheering section that applauds without knowing what it is applauding or what it might mean— without ever asking basic scientific questions.”
Our reading: A lot of the social media discussion of OpenAI's math results has been reduced to an ignorant cheering section that applauds without knowing what it is applauding or what it might mean, without ever asking basic scientific questions.
No horizon Evidence as of
Limitation: Search visibility is not a representative sampling method.
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“As a result, we have zero idea of how generalizable the result is outside math.”
Our reading: As a result of OpenAI's vague report, we currently have zero idea how generalizable its math result is outside mathematics.
No horizon Evidence as of
Only if: as a result of the vague, undisclosed details in OpenAI's report
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“Already, the advent of general purpose agents with broad internet access has led to tens of thousands of hacking incidents”
Our reading: General purpose agents with broad internet access have already caused tens of thousands of hacking incidents.
No horizon Evidence as of
Limitation: The aggregate is available through secondary reporting and does not separate distinct hacking attempts from simulated tests and other behavior [e1].
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“Greedy company makes bad choice that causes chaos; government does nothing to stop them.”
Our reading: OpenAI, which Marcus calls a greedy company, made a bad choice that caused chaos, and the government did nothing to stop it.
No horizon Evidence as of
Limitation: The packet does not provide sufficiently comprehensive government records to establish whether relevant preventive action occurred before the attacks.
Source: BREAKING: OpenAI was warned, months before the Hugging Face incident
Assessment: UnresolvedSaid
Gary Marcus Observation
“The board might want to consider its liability, since they have done nothing constructive to address OpenAI’s security meltdown.”
Our reading: OpenAI's board has done nothing constructive to address the company's security meltdown.
No horizon Evidence as of
Limitation: The relevant records are company disclosures, not board minutes or independent findings about board conduct.
Source: BREAKING: OpenAI’s epic meltdown — and how Sam Altman is blowing up Jensen Huang’s reputation
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“If he keeps sticking to that line, despite overwhelming evidence to the contrary, Huang’s own reputation will rapidly diminish.”
Our reading: If Jensen Huang keeps saying the AI labs are in control of their systems, his reputation will rapidly diminish.
No deadline stated Evidence as of
Only if: if Huang keeps saying AI labs are in control
Source: BREAKING: OpenAI’s epic meltdown — and how Sam Altman is blowing up Jensen Huang’s reputation
Assessment: UnresolvedSaid
Gary Marcus Observation
“He has consistently favored OpenAI over Anthropic (a company that doesn’t seem to be quite so deeply in over its head).”
Our reading: President Trump has consistently favored OpenAI over Anthropic, and Anthropic does not seem to be as deeply in over its head as OpenAI.
No horizon Evidence as of
Limitation: The packet lacks a broad comparison of procurement, restrictions, enforcement and endorsements across the full period.
Source: BREAKING: OpenAI’s epic meltdown — and how Sam Altman is blowing up Jensen Huang’s reputation
Assessment: UnresolvedSaid
Gary Marcus Observation
“And he has done absolutely nothing (or at least nothing public) to sanction or investigate OpenAI, even after its repeated attacks on foreign governments, companies and universities and who knows what else.”
Our reading: President Trump has publicly done nothing to sanction or investigate OpenAI, despite OpenAI's repeated attacks on foreign governments, companies and universities.
No horizon Evidence as of
Limitation: September 30 confirmation does not establish the inquiry's first public-disclosure date.
Source: BREAKING: OpenAI’s epic meltdown — and how Sam Altman is blowing up Jensen Huang’s reputation
Assessment: UnresolvedSaid
Gary Marcus Observation
“Once again OpenAI and told nobody for months.”
Our reading: OpenAI did not disclose the German website compromise incident to anyone for months.
No horizon Evidence as of
Limitation: The principal contemporaneous Reuters report could not be read with read_page.
Source: “I think the answer is we have to shut the labs down” - Jensen Huang
Assessment: UnresolvedSaid
Gary Marcus Observation
“And so far the White House has done nothing.”
Our reading: The White House has taken no action over OpenAI's hacking incidents.
No horizon Evidence as of
Limitation: Private government activity cannot be excluded through public searches.
Source: “I think the answer is we have to shut the labs down” - Jensen Huang
Assessment: UnresolvedSaid
Gary Marcus Forecast
“What we are facing near-term, anyway, is not extinction. And it’s not superintelligence… It’s wholesale deepfaked disinformation, and unreliable but persistent AI systems stealing credentials and launching cyberattacks, at scale.”
Our reading: In the near term, we are facing not extinction and not superintelligence, but wholesale deepfaked disinformation and unreliable but persistent AI systems stealing credentials and launching cyberattacks at scale.
No deadline stated Evidence as of
Limitation: The evidence covers only about five weeks after the post.
Source: Big news at the UN
Assessment: UnresolvedSaid
Gary Marcus Forecast
“We should expect that malicious actors will try use current AI to undermine financial systems and other vital infrastructure such as trains or electrical systems.”
Our reading: Malicious actors will try to use current AI to undermine financial systems and vital infrastructure like trains and electrical systems.
No deadline stated Evidence as of
Limitation: Several October 2026 reports could not be read.
Source: Big news at the UN
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“⚠️ Microsoft and OpenAI have only one play to make GenAI profitable, and this is it: all out 24x7 surveillance.”
Our reading: Microsoft and OpenAI's only way to make generative AI profitable is around-the-clock surveillance of users.
No horizon Evidence as of
Limitation: Public financial disclosures do not provide the required matched profit and data-practice measurements.
Assessment: UnresolvedSaid
Gary Marcus Observation
“The mood has changed, and this time a whole pile of people pushed back.”
Our reading: The mood has changed, and this time a large number of people pushed back on Amodei's claim that it will be possible to cure most human disease in about 5-10 years.
No horizon Evidence as of
Limitation: Selected social posts cannot establish population sentiment.
Source: No, Dario Amodei, we will not be curing cancer and “most human disease” in five to ten years
Assessment: UnresolvedSaid
Gary Marcus Observation
“Google still makes a ton of money, $402 billion in revenue last year, $132 billion in profit), and has vastly more cash to play with than OpenAI and Anthropic.”
Our reading: Google made $402 billion revenue and $132 billion profit last year and has vastly more cash than OpenAI and Anthropic.
No horizon Evidence as of
Limitation: The claim's accounting basis and rounding method are unspecified. The reported revenue rounds to $403 billion to the nearest billion; the evidence does not establish how Marcus obtained $402 billion [e1].
Assessment: UnresolvedSaid
Gary Marcus Observation
“Google’s most obvious competitors have troubles of their own. OpenAI has a declining reputation, Anthropic has conflict with the administration, Microsoft and Amazon don’t have the same talent pool.”
Our reading: Google's competitors have problems: OpenAI's reputation is declining, Anthropic is in conflict with the administration, and Microsoft and Amazon lack comparable talent.
No horizon Evidence as of
Limitation: Reputation depends on the population and measure selected.
Assessment: UnresolvedSaid
Gary Marcus Forecast
“He has worked together with his replacement, Koray Kavukcuoglu, for over a decade, and they will continue to work together.”
Our reading: Hassabis and his replacement Kavukcuoglu will keep working together at Google.
No deadline stated Evidence as of
Limitation: Internal advisory work may occur without public documentation.
Assessment: UnresolvedSaid
Gary Marcus Forecast
“The surgery prediction, too, will surely be repackaged with a new date, at a later date.”
Our reading: Musk will later re-issue his robot-surgery prediction with a new, later date.
No deadline stated Evidence as of
Limitation: Public search coverage is incomplete.
Source: Elon Musk’s preposterous and possibly harmful claim about robotic surgery
Assessment: UnresolvedSaid
Gary Marcus Observation
“Elon’s timeline predictions are notoriously, and to my mind, obviously, bad, yet all too often reported as gospel.”
Our reading: Elon Musk's timeline predictions are notoriously and, in Marcus's view, obviously bad, yet all too often reported as gospel.
No horizon Evidence as of
Limitation: Support for one component does not settle the combined claim.
Source: Elon Musk’s preposterous and possibly harmful claim about robotic surgery
Assessment: UnresolvedSaid
Gary Marcus Observation
“The kind of math OpenAI is dealing with here is radically different from many (perhaps most) real-world problems in which verification neither guarantees solutions nor allows one to produce infinite training data effectively for free.”
Our reading: The kind of math OpenAI is dealing with in the Astra results is radically different from many (perhaps most) real-world problems, in which verification neither guarantees solutions nor allows one to produce infinite training data effectively for free.
No horizon Evidence as of
Limitation: The natural-systems paper is historical context, not outcome evidence for August 2026.
Source: OpenAI’s amazing — but vastly oversold — new model Astra
Assessment: UnresolvedSaid
Gary Marcus Observation
“The “AGI-is-near” community keeps committing the same logical fallacy over and over.”
Our reading: The 'AGI-is-near' community keeps committing the same logical fallacy, the fallacy of composition, over and over.
No horizon Evidence as of
Limitation: Some relevant original posts could not be retrieved or dated.
Source: OpenAI’s amazing — but vastly oversold — new model Astra
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“OpenAI can do what Astra does in math because math allows for external tools to do verification and to create synthetic data.”
Our reading: Astra's math success is possible because math allows external tools for verification and synthetic data generation.
No horizon Evidence as of
Limitation: Later formalization does not establish verification’s role during training or discovery [e6].
Source: OpenAI’s amazing — but vastly oversold — new model Astra
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“OpenAI was driven by competition to drop its prices by 80%.”
Our reading: Competitive pressure drove OpenAI to cut its prices by 80%.
No horizon Evidence as of
Limitation: The verdict concerns the causal statement as a whole; the numerical price reduction is supported.
Source: The seven most shambolic things that happened in AI today.
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“From a technical perspective, this is what happens when you let pattern0matching machines with no real comprehension of what they are doing freely roam the internet.”
Our reading: The AI security incidents happened because pattern-matching AI systems with no real understanding were allowed to roam the internet freely.
No horizon Evidence as of
Limitation: The evidence does not provide a validated measure of comprehension or causal tests that settle its role in these incidents [e1–e3].
Assessment: UnresolvedSaid
Gary Marcus Observation
“A lot of people have come around to that view:”
Our reading: Many people now share the view that Amodei is not much different from Altman.
No horizon Evidence as of
Limitation: The claim supplies neither a numerical threshold nor a defined population.
Source: Dario takes it on the chin
Assessment: UnresolvedSaid
Gary Marcus Observation
“Nor have we reached a moment in “which technological growth accelerates beyond human control””
Our reading: AI-driven technological growth has not accelerated beyond human control as of July 2026.
No horizon Evidence as of
Limitation: The main incident account is supplied by the affected developer.
Source: Sorry, Sam and Elon, we have not reached the Singularity
Assessment: UnresolvedSaid
Gary Marcus Observation
“The market isn’t reading the latest potential Nvidia-OpenAI deal as good news; they are reading it as desperation.”
Our reading: The market is reading the potential Nvidia-OpenAI $250 billion financing backstop as desperation rather than good news.
No horizon Evidence as of
Limitation: The available commentary is not a representative sample of investors.
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“Certainly it would slow down progress and raise prices, helping two US companies at the expense of hundreds of thousands of others.”
Our reading: If the US builds a regulatory moat, it would certainly slow down progress and raise prices, helping two US companies at the expense of hundreds of thousands of others.
No deadline stated Evidence as of
Only if: if the US builds a regulatory moat
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“that the lack of a technical moat would mean that companies like OpenAI would remain unprofitable.”
Our reading: The lack of a technical moat has kept companies like OpenAI unprofitable, as Marcus predicted.
No horizon Evidence as of
Limitation: Financial evidence is reputable secondary reporting on audited statements, not directly inspected statements.
Assessment: UnresolvedSaid
Gary Marcus Observation
“That’s basically what has happened.”
Our reading: Marcus's January 2025 predictions have basically come true: that the US would not achieve a decisive AI victory over China if it continued to focus largely on LLMs, that the two would converge on a tie, that the lack of a technical moat would keep companies like OpenAI unprofitable, that Nvidia would be vulnerable, that the CHIPS act would backfire without doing much to hold China back, that models would keep getting more efficient and less expensive while hallucinations and reliability problems persisted, and that racing endlessly around LLMs would sap resources from more original ideas.
No horizon Evidence as of
Limitation: This assesses the retrospective bundle, not a newly issued conditional forecast.
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“Second, because the systems are not reliable, charging premium prices was never really viable in the long term.”
Our reading: Because the systems are not reliable, charging premium prices was never really viable in the long term.
No horizon Evidence as of
Limitation: The research abstract provides limited methodological detail.
Source: China catches up
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“Third, the basic approach is easily replicated, leading to the price war dynamics and small or negative margins.”
Our reading: The LLM approach is easily replicated, which causes price wars and small or negative margins.
No horizon Evidence as of
Limitation: Capability evidence concerns one competitor and predates the post.
Source: China catches up
Assessment: UnresolvedSaid
Gary Marcus Observation
“As I have said before, over and over, LLMs are becoming a commodity.”
Our reading: LLMs are becoming a commodity.
No horizon Evidence as of
Limitation: The principal June source is a model marketplace with a commercial interest in offering multiple vendors.
Assessment: UnresolvedSaid
Gary Marcus Observation
“In my view, the world has indeed gone in this direction. LLMs have become commodities, prices wars have been significant, profits for the LLM providers have been elusive.”
Our reading: LLMs have become commodities.
No horizon Evidence as of
Limitation: The meaning of commodities materially affects the assessment.
Source: The Generative AI Fizzle™
Assessment: UnresolvedSaid
Gary Marcus Observation
“In my view, the world has indeed gone in this direction. LLMs have become commodities, prices wars have been significant, profits for the LLM providers have been elusive.”
Our reading: Profits for LLM providers have been elusive.
No horizon Evidence as of
Limitation: The unresolved verdict does not mean the identified providers were profitable.
Source: The Generative AI Fizzle™
Assessment: UnresolvedSaid
Gary Marcus Observation
“But on the whole, Generative AI has not been delivering great gains. We have seen that now in study after study, MIT, McKinsey, Bain, and many more.”
Our reading: Overall, generative AI has not been delivering large gains, as many studies (MIT, McKinsey, Bain) show.
No horizon Evidence as of
Limitation: The NANDA document is preliminary and was retrieved from a third-party mirror.
Source: Accenture: Then and now, and how it may signify things to come
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“I really do think that Claude Code (which remember, is a special-purpose neurosymbolic system rather than a generic chatbot) will increase productivity for coders (if technical debt doesn’t swallow back those gains).”
Our reading: Claude Code will increase coders' productivity, unless technical debt cancels out the gains.
No deadline stated Evidence as of
Only if: if technical debt doesn't swallow back the gains
Source: Accenture: Then and now, and how it may signify things to come
Assessment: UnresolvedSaid
Gary Marcus Forecast
“You can’t multiply your losses every year by 8x (or even close) for very long.”
Our reading: OpenAI cannot keep multiplying its losses by around 8x a year for very long.
No deadline stated Evidence as of
Limitation: The first calendar year after the baseline had not ended at the evaluation date.
Source: OpenAI’s lead is dwindling fast
Assessment: UnresolvedSaid
Gary Marcus Observation
“And, of course, all of these risks were foreseeable.”
Our reading: The harms alleged in Florida's lawsuit against OpenAI were all foreseeable.
No horizon Evidence as of
Limitation: Foreseeability does not establish that the alleged harms occurred or that OpenAI legally caused them.
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“To be sure, Anthropic brought this on themselves to a considerable degree, by (a) overselling doom and their own wares and (b) by literally and repeatedly calling for export controls themselves.”
Our reading: Anthropic brought the export control order on itself to a considerable degree, by overselling doom and its own products and by literally and repeatedly calling for export controls itself.
No horizon Evidence as of
Limitation: The packet contains no sufficiently complete decision record establishing the influence of Anthropic's advocacy.
Assessment: UnresolvedSaid
Gary Marcus Observation
“Because essentially all their software has a tendency to fabricate fairly regularly and even defame people and to sometimes give bad medical information, and so on.”
Our reading: Essentially all LLM providers' software fabricates fairly regularly, sometimes defaming people and giving bad medical information.
No horizon Evidence as of
Limitation: Difficult and adversarial benchmarks cannot be treated as random samples of everyday use.
Source: Maybe Section 230 doesn’t shield AI companies from liability, after all
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“If American courts were to rule similarly, or if Congress made that the law of the land, all the LLM providers would be in deep, deep trouble.”
Our reading: If US courts or Congress held companies liable for their chatbots' output, all LLM providers would be in deep trouble.
No deadline stated Evidence as of
Only if: if US courts rule that chatbot output is the company's own speech, or Congress legislates so
Source: Maybe Section 230 doesn’t shield AI companies from liability, after all
Assessment: UnresolvedSaid
Gary Marcus Forecast
“And so at some point, I think OpenAI is gonna have a problem where they can’t really meet their obligations.”
Our reading: At some point OpenAI will be unable to meet its financial obligations.
No deadline stated Evidence as of
Limitation: The cash figure comes from The Decoder's summary of The Information's report on documents shared with shareholders. It is not an audited filing.
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“If they can’t meet their obligations, I expect Nvidia and Oracle and many others would take a big hit as collateral damage (Domino 5).”
Our reading: If OpenAI can't meet its obligations, Nvidia, Oracle and many others would take a big hit as collateral damage.
No deadline stated Evidence as of
Only if: if OpenAI can't meet its obligations
Assessment: UnresolvedSaid
Gary Marcus Observation
“Two years later, competitors have caught up. OpenAI has had to cut prices.”
Our reading: Over the past two years competitors have caught up to OpenAI and it has had to cut prices.
No horizon Evidence as of
Limitation: Arena measures human preferences and does not establish universal capability parity.
Assessment: UnresolvedSaid
Gary Marcus Observation
“Open AI, I think, has a problem right now. They are burning money the fastest.”
Our reading: OpenAI has a problem and is burning money faster than its AI competitors.
No horizon Evidence as of
Limitation: Neither item supplies a comparable January–March 2026 cash-burn ranking for OpenAI, Anthropic, Google and Amazon [e1, e2].
Assessment: UnresolvedSaid
Gary Marcus Forecast
“That is absolutely not going to happen.”
Our reading: SpaceX will not return 2,538x its IPO investment as Amazon did, which would imply a market cap of about $4,442 trillion.
No deadline stated Evidence as of
Limitation: The evidence covers only the June 12, 2026 debut day. It does not show SpaceX's share price or market value at any later date, including the evaluation date.
Source: An entire industry is being propped up by math that is insane.
Assessment: UnresolvedSaid
Gary Marcus Observation
“The one possible major productivity story (coding) also happens to be the one burning the most cash.”
Our reading: AI coding, the one possible major productivity success, is also the use case burning the most cash.
No horizon Evidence as of
Limitation: The target quarter and cash-burn definition are evaluator interpretations because Marcus did not specify them.
Source: Slop, productivity, and why the AI-fueled world is going nowhere mighty fast
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“As I noted on X, nobody is going to trust an American AI company that is partly owned by the US Government.”
Our reading: If an American AI company is partly owned by the US government, nobody is going to trust it.
No deadline stated Evidence as of
Only if: if an American AI company is partly owned by the US government
Source: AI’s Black Friday
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“None of that is particularly great for Nvidia, CoreWeave, Oracle, Nebius, Micron, and a variety of other hardware and semiconductor providers”
Our reading: The developments described (SpaceX leasing compute to Google and Anthropic, and firms buying hardware before there was demand for it) are not particularly great for Nvidia, CoreWeave, Oracle, Nebius, Micron, and a variety of other hardware and semiconductor providers.
No horizon Evidence as of
Limitation: The customer accounts do not establish what purchases or contracts would otherwise have occurred [e1, e2].
Source: AI’s Black Friday
Assessment: UnresolvedSaid
Gary Marcus Observation
“AGI: machine can do anything human can do, autonomously. That has not achieved]”
Our reading: AGI, a machine that can autonomously do anything a human can do, has not been achieved.
No horizon Evidence as of
Limitation: This is an evidence limitation, not a finding that AGI had been achieved.
Source: No need to panic about Anthropic’s new blog, and some more good news
Assessment: UnresolvedSaid
Gary Marcus Forecast
“Getting to AGI will require new ideas, not just new code optimizations.”
Our reading: Reaching AGI will require new ideas, not merely new code optimizations.
No deadline stated Evidence as of
Limitation: The meaning of new ideas remains partly judgmental.
Source: No need to panic about Anthropic’s new blog, and some more good news
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“If there is no moat, nobody is going to take 90% of the market.”
Our reading: If there is no moat, no AI company will capture 90% of the AI market.
No deadline stated Evidence as of
Only if: if there is no moat
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“And companies like Anthropic are ending their all you can eat buffet, which will make many customers think twice.”
Our reading: Anthropic and similar companies are ending all-you-can-eat pricing, which will make many customers think twice about using them.
No horizon Evidence as of
Limitation: The policy evidence concerns particular Anthropic products and uses.
Assessment: UnresolvedSaid
Gary Marcus Forecast
“Same will happen with Anthropic and OpenAI.”
Our reading: As with SpaceX, Anthropic and OpenAI will be pushed into indices and index trackers and retail investors will suffer losses when reality catches up.
No deadline stated Evidence as of
Limitation: Anthropic's preliminary prospectus does not establish a completed offering, index entry or investor losses, and provides no evidence of OpenAI's status.
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“With no clear winners, nobody can charge monopoly prices; instead, you get price wars and commodity pricing.”
Our reading: If there are no clear winners among AI competitors, nobody will be able to charge monopoly prices, and instead there will be price wars and commodity pricing.
No deadline stated Evidence as of
Only if: with no clear winners
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“But everybody is building essentially the same technical solution with essentially the same data, so there is no moat.”
Our reading: Because everybody competing to build AI is building essentially the same technical solution with essentially the same data, there is no moat for any of them.
No horizon Evidence as of
Limitation: The observations precede June 2, 2026; the Stanford report became available on June 29.
Assessment: UnresolvedSaid
Ed Zitron Observation
“For example, Anthropic lets you burn anywhere from $8 to $13.50 in tokens for every dollar of subscription cost, and while AI boosters will say that Anthropic is “profitable on inference,” nobody actually has proof outside of theoretical scenarios posed by CEO Dario Amodei.”
Our reading: Anthropic lets subscribers burn $8 to $13.50 in tokens per subscription dollar, and there is no proof beyond Amodei's theoretical scenarios that Anthropic is profitable on inference.
No horizon Evidence as of
Limitation: The January calculation does not verify May allowances, model mix or caching treatment [e1].
Source: AI Doesn't Have ROI
Assessment: UnresolvedSaid
Ed Zitron Causal claim
“The overwhelming majority of AI users are completely divorced from and actively trained to ignore the true cost of AI tokens, which means they naturally use these services in a way that’s actively uneconomical.”
Our reading: The overwhelming majority of AI users are completely divorced from, and actively trained to ignore, the true cost of AI tokens, so they naturally use these services in an actively uneconomical way.
No horizon Evidence as of
Limitation: The population and economic perspective are broader than those covered by the located studies.
Source: AI Doesn't Have ROI
Assessment: UnresolvedSaid
Ed Zitron Causal claim
“This is why every AI startup is inherently unprofitable — they’re literally sending every penny of their venture capital money directly to Anthropic and OpenAI to power their unprofitable services.”
Our reading: Every AI startup is inherently unprofitable because they are literally sending every penny of their venture capital directly to Anthropic and OpenAI to power their unprofitable services.
No horizon Evidence as of
Limitation: A founder's undefined profitability statement is weaker than financial accounts.
Source: AI Doesn't Have ROI
Assessment: UnresolvedSaid
Ed Zitron Observation
“OpenAI, Anthropic and other AI companies have actively conspired to mislead the world about the true costs of AI, and it was working great right up until they decided to try charging what it actually cost.”
Our reading: OpenAI, Anthropic and other AI companies actively conspired to mislead the world about AI's true costs, and this worked well until they decided to try charging what AI actually costs.
No horizon Evidence as of
Limitation: The FTC report does not resolve the specific allegation of coordinated cost deception [e1].
Source: AI Doesn't Have ROI
Assessment: UnresolvedSaid
Ed Zitron Observation
“AI labs may be able to run their own infrastructure and save some costs, but we have no evidence that this makes anything “profitable.””
Our reading: There is no evidence that AI labs running their own infrastructure makes anything profitable.
No horizon Evidence as of
Limitation: The result depends on the meaning of profitable and the required causal connection.
Source: AI Doesn't Have ROI
Assessment: UnresolvedSaid
Ed Zitron Observation
“I must repeat myself: AI is more expensive today than it was three years ago, and it is not getting cheaper.”
Our reading: AI costs more today than it did three years ago and is not getting cheaper.
No horizon Evidence as of
Limitation: The packet does not isolate matched total task costs at the required endpoints or the immediate prepublication trend.
Source: AI Doesn't Have ROI
Assessment: UnresolvedSaid
Gary Marcus Observation
“They are creating interactive fiction that is trained to predict the language of actual beings.”
Our reading: LLMs are interactive fiction trained to predict the language of actual beings.
No horizon Evidence as of
Limitation: On a purely behavioral reading, the role-play characterization has support.
Source: The Pope appears to understand AI better than Geoffrey Hinton does.
Assessment: UnresolvedSaid
Gary Marcus Observation
“Within hours of when I posted yesterday’s essay on the decline of tokenmaxxing, I saw further converging evidence, such as this:”
Our reading: There is further converging evidence, as of late May 2026, that tokenmaxxing (the push to maximize AI token usage) is declining.
No horizon Evidence as of
Limitation: Amazon's precise leaderboard shutdown date is unspecified (e1).
Source: What happens next, after the decline of tokenmaxxing?
Assessment: UnresolvedSaid
Gary Marcus Observation
“Consistent with the Axios quote, and the Uber concern’s I expressed a couple days ago, I am seeing more and more reports online like this:”
Our reading: Marcus is seeing more and more online reports like the quoted one, about companies burning money on tokens without significant ROI.
No horizon Evidence as of
Limitation: The item provides no comparable observation windows or complete record of Marcus's encounters [e1].
Source: Breaking: bad news for three of the biggest IPOs in history
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“One big reason why Anthropic is having a blowout quarter (aside from the massive one time subsidy that they got from SpaceX) is that companies have been “tokenmaxxing” for the last few months, encouraging employees to use GenAI as much possible, without much regard to payoff.”
Our reading: A major reason for Anthropic's blowout quarter, besides a one-time SpaceX subsidy, is companies tokenmaxxing: pushing employees to use GenAI as much as possible without much regard to payoff.
No horizon Evidence as of
Limitation: The filing covers a broader period than the quarter-to-date claim.
Source: Breaking: bad news for three of the biggest IPOs in history
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“That means lots of short-term revenue to Anthropic and OpenAI, but it never seemed like a sustainable idea to me:”
Our reading: Tokenmaxxing means lots of short-term revenue for Anthropic and OpenAI, though it never seemed to Marcus like a sustainable idea.
No horizon Evidence as of
Limitation: Ramp's adoption and spending figures do not isolate tokenmaxxing's revenue contribution to each provider [e1].
Source: Breaking: bad news for three of the biggest IPOs in history
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“which means less revenue for Anthropic and others. Or lower prices and even more challenges in being profitable.”
Our reading: The reported enterprise swing away from tokenmaxxing means less revenue for Anthropic and others, or else lower prices and even more challenges in being profitable.
No horizon Evidence as of
Limitation: The report does not connect customer usage changes to attributable financial effects at Anthropic or other providers [e1].
Source: Breaking: bad news for three of the biggest IPOs in history
Assessment: UnresolvedSaid
Gary Marcus Conditional forecast
“In which cases those stocks will eventually fall.”
Our reading: If enough customers have second thoughts, so that none of the three IPO'ing companies ever hits its long-term projections, those companies' stocks will eventually fall.
No deadline stated Evidence as of
Only if: if enough customers have second thoughts
Source: If enough other companies report the same, the bubble pops. 🫧
Assessment: UnresolvedSaid
Gary Marcus Observation
“Every time I think about the numbers and lack of RoI for most pilot studies and the reliability problems I think so.”
Our reading: Most AI pilot studies show no return on investment, and AI has ongoing reliability problems.
No horizon Evidence as of
Limitation: No cited study provides representative pilot-level counts with comparable financial costs and returns for January–March 2026. [e1, e2, e3]
Assessment: UnresolvedSaid
Gary Marcus Observation
“Practically every day I see new signs that the backlash against AI is growing.”
Our reading: Public backlash against AI is growing, with new signs appearing nearly every day.
No horizon Evidence as of
Limitation: The result depends partly on how much weight is given to practically every day.
Source: The growing AI backlash
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“Some of this is technical (LLMs aren’t reliable), some of it is political/economic (such as the utter lack of responsible regulation).”
Our reading: Some of generative AI's downsides have technical causes, such as LLMs being unreliable, and some have political or economic causes, such as the utter lack of responsible regulation.
No horizon Evidence as of
Limitation: One adjudicated incident cannot measure the general reliability of all LLMs.
Source: The growing AI backlash
Assessment: UnresolvedSaid
Gary Marcus Causal claim
“GenAI has been undermining secondary and college education, opening up mass surveillance, increasing disinformation, delusions, impersonation, phishing, and other forms of cybercrime, nonconsensual deep fake porn, bias in employment and other domains, and economic disparity, drowning the world in slop and unwanted, over-leveraged environment-damaging data centers that risk causing a recession.”
Our reading: Generative AI has been undermining secondary and college education, opening up mass surveillance, increasing disinformation, delusions, impersonation, phishing and other cybercrime, nonconsensual deepfake porn, bias in employment and other domains, and economic disparity, and drowning the world in slop and in unwanted, over-leveraged, environment-damaging data centers that risk causing a recession.
No horizon Evidence as of
Limitation: The search and verified evidence do not cover every listed harm adequately.
Source: The growing AI backlash
Assessment: UnresolvedSaid
Gary Marcus Forecast
“And I am sure we will see many more catastrophic failures soon enough, involving things like privacy, security and data loss. Already there have been many.”
Our reading: Many more catastrophic vibe-coding failures involving privacy, security and data loss will occur soon.
No deadline stated Evidence as of
Limitation: Public incident reporting is incomplete.
Source: Dario Amodei, hype, AI safety, and the explosion of vibe-coded AI disasters
Assessment: UnresolvedSaid
Gary Marcus Observation
“Here is a further example of my last point that ChatGPT’s exciting new image system has trouble with functional understanding, sent to me by a reader:”
Our reading: ChatGPT's exciting new image system has trouble with functional understanding.
No horizon Evidence as of
Limitation: The assessment concerns observable functional depictions, not whether the model possesses human-like understanding.
Assessment: UnresolvedSaid
Gary Marcus Observation
“But if you look closely, there are several errors, and those errors are revealing.”
Our reading: ChatGPT's new image engine's labeled bike diagram contains several revealing labeling errors.
No horizon Evidence as of
Limitation: This is an evidence-access limitation, not a finding that the labels are correct.
Assessment: UnresolvedSaid
Gary Marcus Observation
“But anybody knowledgeable about bikes (racers, mechanics, designers etc) would immediately see numerous problems.”
Our reading: ChatGPT's tandem bike image contains numerous problems that bike experts would immediately spot.
No horizon Evidence as of
Limitation: The packet contains no inspectable copy of the tandem image or qualified independent assessment.
Assessment: UnresolvedSaid
Gary Marcus Observation
“And all this from a company thought (or claimed) that GPT-5 was going to be tantamount to AGI (spoiler alert: it wasn’t)”
Our reading: GPT-5 was not tantamount to AGI, although OpenAI thought or claimed that it would be.
No horizon Evidence as of
Limitation: Support for one clause is insufficient to support the whole claim.
Source: Peak absurdity, Part II
Assessment: UnresolvedSaid
Gary Marcus Observation
“On the happy side, in its current form, Myth is nowhere near as scary as Tom Fridman (who worries about schoolchildren accidentally taking down power grids) and others made it out to be.”
Our reading: In its current form, Claude Mythos Preview is nowhere near as dangerous as Thomas Friedman and others portrayed it.
No horizon Evidence as of
Limitation: Simulated network compromise and individual exploits do not directly measure disruption of a real power grid.
Source: Claude Mythos, evaluated
Assessment: UnresolvedSaid
Gary Marcus Observation
“LLMs are an efficient way to pattern recognition where perfect results are not required, but an inefficient way to reason a plan.”
Our reading: LLMs are efficient for imperfect pattern recognition but inefficient for reasoning out a plan.
No horizon Evidence as of
Limitation: Different efficiency baselines could produce different judgments.
Source: Even more good news for the future of neurosymbolic AI
Assessment: UnresolvedSaid
Gary Marcus Observation
“You can read the full paper by Timothy Duggan, Pierrick Lorang, Hong Lu, and Matthias Scheutz, which very much vindicates the Apple reasoning paper, here.”
Our reading: The Tufts paper strongly vindicates the Apple reasoning paper's findings.
No horizon Evidence as of
Limitation: A weaker reading of vindicates as merely consistent with would receive more support.
Source: Even more good news for the future of neurosymbolic AI
Assessment: UnresolvedSaid
Gary Marcus Forecast
“But anybody who thinks LLMs are a direct route to the sort AGI that could fundamentally transform society for the good is kidding themselves.”
Our reading: LLMs are not a direct route to the sort of AGI that could fundamentally transform society for the good, and anyone who thinks they are is kidding themselves.
No deadline stated Evidence as of
Limitation: The forecast's central terms remain underspecified.
Source: Even more good news for the future of neurosymbolic AI
Assessment: UnresolvedSaid
Gary Marcus Observation
“It’s obviously not AGI.”
Our reading: Claude Code is not AGI.
No horizon Evidence as of
Limitation: This is an evidentiary finding, not a finding that Claude Code was AGI.
Source: Even more good news for the future of neurosymbolic AI
Assessment: UnresolvedSaid
Gary Marcus Observation
“The source code leak proves it. Tucked away at its center is a 3,167 line kernel called print.ts.”
Our reading: The leaked Claude Code source shows a 3,167-line kernel called print.ts at its center, proving it is not a pure LLM.
No horizon Evidence as of
Limitation: A longer file alone does not disprove a shorter function inside it.
Assessment: UnresolvedSaid
Gary Marcus Forecast
“The first part has already come to pass. In time, other three will, too.”
Our reading: The other three parts of Marcus's 2020 agenda (knowledge, reasoning, world models) will eventually be adopted, as neurosymbolic AI already has been.
No deadline stated Evidence as of
Limitation: The terms are vague, and current industry uses of 'reasoning' and 'world models' may not match the paper's meaning.
Assessment: UnresolvedSaid
Gary Marcus Observation
“The demo was definitely proof of concept that we need to get our regulatory and technical house in order, but not the immediate threat the media and public was lead to believe.”
Our reading: The Mythos demo was not the immediate threat the media and public were led to believe.
No horizon Evidence as of
Limitation: The principal technical evidence is Anthropic's own disclosure.
Source: Three reasons to think that the Claude Mythos announcement from Anthropic was overblown
Assessment: UnresolvedSaid
Gary Marcus Observation
“The model itself is incrementally better than previous recent models, but certainly not an off-the-chart breakthrough:”
Our reading: Mythos is incrementally better than recent previous models and certainly not an off-the-chart breakthrough.
No horizon Evidence as of
Limitation: The original Mythos system card could not be read through the required tool.
Source: Three reasons to think that the Claude Mythos announcement from Anthropic was overblown
Assessment: UnresolvedSaid
Gary Marcus Observation
“ChatGPT can’t reliably run a timer but it has still been implicated in delusions, suicides, cognitive surrender, mass disinformation, and so much more.”
Our reading: ChatGPT cannot reliably run a timer, yet it has been implicated in delusions, suicides, cognitive surrender and mass disinformation.
No horizon Evidence as of
Limitation: Legal allegations establish implication, not proven causation.
Source: What should we take from Anthropic’s (possibly) terrifying new report on Mythos?