Claims that can’t be checked, page 29 of 37
Claims by Gary Marcus and Ed Zitron. Deadlines are judged as of 2026-10-29.
Claims that can’t be checked (3643)
Public evidence cannot settle these claims, so they are recorded and attributed, not scored. Most were screened out: both AI providers read the claim on its own and found it a value judgment, rhetoric, hedged, too vague to test, or about something no public evidence could show. The rest were found to be recommendations or too open to test in a full review.
Page 29 of 37: claims 2801 to 2900 of 3643, ordered by the date first said, newest first. To find a claim by its words, use search.
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Things just got worse.”
Our reading: OpenAI's challenges got worse over the two weeks before late February 2024.
No horizon
Qualifier: in the last two weeks
Source: The last two weeks at OpenAI
Assessment: Can’t be checkedSaid
Ed Zitron Causal claim
“I think the tech industry's (and venture capital’s) obsession with artificial intelligence is a symptom of rot, where products are created based on analytics and guesswork rather than actually thinking about what a customer might want.”
Our reading: The tech industry's and venture capital's obsession with AI is a symptom of the Rot Economy rather than of customer-driven product thinking.
No horizon
Source: Software Has Eaten The Media
Assessment: Can’t be checkedSaid
Ed Zitron Causal claim
“And I think it's because Microsoft isn't actually interested in users liking or using the product, but in showing the markets a new button that computer manufacturers can put on laptops that suggests that it is still innovative.”
Our reading: Microsoft promotes Copilot to signal innovation to markets rather than because it cares about users liking or using it.
No horizon
Source: Software Has Eaten The Media
Assessment: Can’t be checkedSaid
Ed Zitron Causal claim
“This decision is one made to satisfy investors — a way of showing that Google is integrating artificial intelligence to "push the boundaries of where we need to go" according to Sundar Pichai, who I do not believe ever uses Google Assistant.”
Our reading: Google's decision to replace Google Assistant with Gemini was made to satisfy investors, as a way of showing that Google is integrating artificial intelligence.
No horizon
Source: Software Has Eaten The Media
Assessment: Can’t be checkedSaid
Ed Zitron Rhetoric
“In a logical tech economy, one would be terrified that so many bets have been made on such shaky ground, but we're in the Rot Economy, where an unsustainable product with few clear use cases can burn billions of dollars and fuel our climate crisis because the tech industry has run out of fucking ideas.”
Our reading: In the Rot Economy, unlike a logical tech economy where so many bets on shaky ground would be terrifying, an unsustainable product with few clear use cases (generative AI) can burn billions of dollars and fuel the climate crisis because the tech industry has run out of ideas.
No horizon
Scope: we're in the Rot Economy
Source: Software Has Eaten The Media
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“Waiting on RAG to fix what ails LLM is just waiting on another miracle.”
Our reading: Expecting RAG to fix LLMs' problems is like waiting for a miracle.
No horizon
Source: No, RAG is probably not going to rescue the current situation
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Some great-grandchild of RAG, perhaps extended, revised, and elaborated, might even help — if people seriously embrace neurosymbolic AI in coming years.”
Our reading: Some great-grandchild of RAG, perhaps extended, revised, and elaborated, might help AI work reliably if people seriously embrace neurosymbolic AI in coming years.
No horizon
Only if: if people seriously embrace neurosymbolic AI in coming years
Source: No, RAG is probably not going to rescue the current situation
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Honestly, every LLM, with RAG or without, probably ought to have on of those old movie disclaimers after every response:”
Our reading: Every LLM, with or without RAG, should probably carry a disclaimer after each response.
No horizon
Qualifier: with RAG or without
Source: No, RAG is probably not going to rescue the current situation
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Making it work is very likely going to require a whole new technology, one that is unlikely to arrive until the tech industry gets over its infatuation with LLMs and quick fixes.”
Our reading: Reliable AI will very likely require a whole new technology, which is unlikely to arrive until the tech industry moves past its infatuation with LLMs and quick fixes.
No horizon
Only if: new technology unlikely until industry gets over LLM infatuation and quick fixes
Source: No, RAG is probably not going to rescue the current situation
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“Today’s issue may well be fixed quickly, but I hope it will be seen as the wakeup call that it is.”
Our reading: The ChatGPT malfunction of February 2024 may well be fixed quickly.
No horizon
Source: ChatGPT has gone berserk
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Today’s issue may well be fixed quickly, but I hope it will be seen as the wakeup call that it is.”
Our reading: The ChatGPT malfunction is a genuine wakeup call about the instability of generative AI and should be treated as one.
No horizon
Source: ChatGPT has gone berserk
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“But I will quote something I said two weeks ago: “Please, developers and military personnel, don’t let your chatbots grow up to generals.””
Our reading: Developers and military personnel should not let their chatbots grow up to be generals.
No horizon
Source: ChatGPT has gone berserk
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“We are still living in the age of machine learning alchemy that xkcd captured so well in a cartoon several years ago:”
Our reading: We are still living in the age of machine learning alchemy that an xkcd cartoon captured several years ago.
No horizon
Qualifier: still
Source: ChatGPT has gone berserk
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“In the end, Generative AI is a kind of alchemy.”
Our reading: In the end, generative AI is a kind of alchemy.
No horizon
Qualifier: in the end
Source: ChatGPT has gone berserk
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“The need for altogether different technologies that are less opaque, more interpretable, more maintanable, and more debuggable — and hence more tractable—remains paramount.”
Our reading: It is of paramount importance to develop altogether different AI technologies that are less opaque, more interpretable, maintainable, and debuggable than generative AI.
No horizon
Source: ChatGPT has gone berserk
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“Gary Marcus keeps hoping that he will live to see an AI that is deeper than mere stochastic mimicry plus Band-Aids. He has, however, learned not to hold his breath.”
Our reading: Repeating a 2019 passage he wrote with Ernest Davis, Marcus says he keeps hoping to live to see an AI deeper than mere stochastic mimicry plus Band-Aids but has learned not to hold his breath.
No horizon
Qualifier: quoted from Rebooting AI (2019), co-written with Ernest Davis, and reaffirmed
Source: Has Google gone too woke? Why even the biggest models still struggle with guardrails
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Some things have scaled exponentially, and some haven’t. The capacity to endow machines with the commonsense understanding of history, culture, and human values that would be required to make sensible guardrails has not.”
Our reading: Some things have scaled exponentially, but the capacity to give machines the commonsense understanding of history, culture, and human values needed to make sensible guardrails has not scaled exponentially.
No horizon
Qualifier: exponentially
Source: Has Google gone too woke? Why even the biggest models still struggle with guardrails
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“At the same time, the system seemed yesterday (I imagine it will be partly patched soon) wildly too restrictive on some other queries:”
Our reading: Gemini's overly restrictive responses to some queries will likely be partly patched soon.
No horizon
Source: Has Google gone too woke? Why even the biggest models still struggle with guardrails
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“In fact, I would go as far as to say that I actually think that it is good that Google is trying here (albeit clearly ineptly).”
Our reading: It is good that Google is trying to counter minority underrepresentation in generated images, though it is doing so ineptly.
No horizon
Qualifier: albeit ineptly
Source: Has Google gone too woke? Why even the biggest models still struggle with guardrails
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Increased transparency is essential.”
Our reading: Increased transparency about LLM training data and hidden system prompts is essential.
No horizon
Qualifier: about training data and hidden prompts
Source: Has Google gone too woke? Why even the biggest models still struggle with guardrails
Assessment: Can’t be checkedSaid
Ed Zitron Forecast
“These things are not "learning," or "understanding," or even "intelligent" — they're giant math machines that, while impressive at first, can never assail the limits of a technology that doesn't actually know anything.”
Our reading: Generative AI models are not learning, understanding or intelligent and can never overcome the limits of a technology without knowledge.
No horizon
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“As I discussed in my last newsletter, media entities are increasingly normalizing their content to please search engine algorithms, and the jobs that involve pooling affiliate links and answering where you can watch the Super Bowl are very much at risk.”
Our reading: Media jobs producing SEO-driven generic content, like affiliate-link pooling, are very much at risk from generative AI.
No horizon
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Recommendation or value judgment
“I'd argue that a generative AI's inability to reliably generate stuff is an existential threat that should have smothered these companies early in their lives.”
Our reading: Zitron argues that generative AI's inability to reliably generate output is an existential threat that should have smothered AI companies like OpenAI and Anthropic early in their lives.
No horizon
Qualifier: I'd argue
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“I consider myself relatively tuned into the tech ecosystem, and I read every single tech publication regularly, yet I'm struggling to point to anything that generative AI has done other than reignite the flames of venture capital.”
Our reading: Zitron, who says he reads every tech publication regularly, is struggling to point to anything generative AI has done other than reignite venture capital.
No horizon
Qualifier: in his own assessment
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“Yet even with thousands of headlines, billions of dollars of investment, and trillions of tokens run through various large language models, there are no essential artificial intelligence use cases, and no killer apps outside of non-generative assistants like Alexa that are now having generative AI forced into them for no apparent reason.”
Our reading: Despite thousands of headlines, billions of dollars of investment and trillions of tokens, there are no essential AI use cases and no killer apps apart from non-generative assistants like Alexa.
No horizon
Scope: outside of non-generative assistants like Alexa
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Forecast
“I don't argue it will, at least not in such a way that anybody's lives will be improved.”
Our reading: Zitron doubts that generative AI, a product that can only sort-of-kind-of do something, will create trillions of dollars of economic value, at least not in a way that improves anybody's lives.
No horizon
Qualifier: at least not in such a way that anybody's lives will be improved
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“Google's investment in Anthropic was made in the hopes that it’d see a similar revenue multiplier, and I'd argue Amazon's was made in the same vein — though it was too late to force Anthropic to use AWS as their preferred vendor.”
Our reading: Google's investment in Anthropic was made hoping for a revenue multiplier like Microsoft's, and Zitron argues Amazon's was made in the same vein, though too late to force Anthropic to use AWS as its preferred vendor.
No horizon
Qualifier: I'd argue (as to Amazon)
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“Sora's outputs can mimic real-life objects in a genuinely chilling way, but its outputs — like DALL-E, like ChatGPT — are marred by the fact that these models do not actually know anything.”
Our reading: Generative models like Sora, DALL-E and ChatGPT do not actually know anything.
No horizon
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“I believe artificial intelligence companies deeply underestimate how perfect the things around us are, and how deeply we base our understanding and acceptance of the world on knowledge and context.”
Our reading: Zitron believes AI companies deeply underestimate how perfect the things around us are and how deeply we base our understanding and acceptance of the world on knowledge and context.
No horizon
Qualifier: I believe
Source: Subprime Intelligence
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“We are in for a wild ride.”
Our reading: Society faces turbulent times from AI-generated video.
No horizon
Source: Absolutely amazing ant video augurs intellectual mayhem
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“A major educational resource will likely be spoiled practically overnight.”
Our reading: YouTube is likely to be ruined as a major educational resource almost overnight by AI-generated fake videos.
No horizon
Qualifier: due to AI-generated fake videos
Source: Absolutely amazing ant video augurs intellectual mayhem
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If other judges rule the same way, and hold companies responsible for the nonsense their chatbots say, one of the biggest alleged use cases for large language models could dry up, fast.”
Our reading: If other judges rule the same way and hold companies responsible for the nonsense their chatbots say, one of the biggest alleged use cases for large language models could dry up fast.
No horizon
Only if: other judges rule the same way
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“In the tech industry, this should be the top story.”
Our reading: The Air Canada chatbot ruling should be the top story in the tech industry.
No horizon
Qualifier: in the tech industry
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Nor should he have.”
Our reading: The tribunal judge was right not to accept Air Canada's argument that its chatbot was a separate legal entity responsible for its own actions.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“It’s probably not fair to blame the weird board on a lack of data.”
Our reading: Sora's erroneous chessboard is probably not due to a lack of training data.
No horizon
Source: Sora Can’t Handle the Truth
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“From AGI perspective, however, this is an immense warning sign.”
Our reading: From an AGI perspective, Sora's fixation on the local at the expense of a deep representation of the global is an immense warning sign.
No horizon
Scope: from an AGI perspective
Source: Sora Can’t Handle the Truth
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“The sooner the AI industry -- and the world at large — recognizes this, the better.”
Our reading: The AI industry and the world should recognize soon that generative AI shares a persistent factuality and comprehension problem.
No horizon
Source: Sora Can’t Handle the Truth
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Artists are presumably getting really screwed here.”
Our reading: Artists are probably being badly harmed by the way Sora was trained.
No horizon
Source: Sora’s Surreal Physics
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“As a solution to artificial general intelligence, though, I see it as a distraction.”
Our reading: In Marcus's view, Sora is a distraction as a solution to artificial general intelligence.
No horizon
Qualifier: I see it as
Source: Sora’s Surreal Physics
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Sora is fantastic, but it is akin to morphing and splicing, rather than a path to the physical reasoning we would need for AGI. It is a model of how images change over time, not a model of what entities do in the world.”
Our reading: Sora is akin to morphing and splicing of images, not a path to the physical reasoning needed for AGI.
No horizon
Source: Sora’s Surreal Physics
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“If a system can’t at all handle with the permanence of objects, I am not sure we should even call it a world model at all.”
Our reading: If a system can't handle the permanence of objects at all, Marcus is not sure it should even be called a world model.
No horizon
Only if: if a system can't at all handle the permanence of objects
Source: Sora’s Surreal Physics
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“I would not at all be surprised if there also had been lots of training on YouTube visited, and various copyrighted materials.”
Our reading: Sora may well have been trained on lots of YouTube video and various copyrighted materials.
No horizon
Source: Sora’s Surreal Physics
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“In my view, these claims — about AGI and world models — are hyperbolic, and unlikely to be true.”
Our reading: Claims that Sora amounts to AGI, vindicates scaling laws, or constitutes a world model are hyperbolic and unlikely to be true.
No horizon
Source: Sora’s Surreal Physics
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“As a technology for video artists that’s fine, if they choose to use it; the occasional surrealism may even be an advantage for some purposes (like music videos).”
Our reading: As a technology for video artists Sora is fine if they choose to use it, and its occasional surrealism may even be an advantage for some purposes such as music videos.
No horizon
Qualifier: if they choose to use it
Source: Sora’s Surreal Physics
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“In the new regime, caveat emptor.”
Our reading: People programming via LLMs in English should beware of the risks.
No horizon
Source: The hottest new programming language is English! Or maybe not.
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“DALL-E 2 is, I dare say, not as smart as it seems.”
Our reading: DALL-E 2 is not as smart as it appears.
No horizon
Source: Horse rides Astronaut, redux
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“The problem with “Foundation Models” (a common term for Generative AI) is that they have never provided the firm, reliable foundation that their name implies.”
Our reading: Foundation models (generative AI) have never provided the firm, reliable foundation their name implies.
No horizon
Source: Statistics versus Understanding: The Essence of What Ails Generative AI
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Generative AI systems have always tried to use statistics as a proxy for deeper understanding, and it’s never entirely worked.”
Our reading: Generative AI systems have always tried to use statistics as a proxy for deeper understanding, and it has never entirely worked.
No horizon
Qualifier: always
Source: Statistics versus Understanding: The Essence of What Ails Generative AI
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“GPT-3 has no idea what grape juice is, or what cranberry juice is, or what pouring, sniffing, smelling, or drinking are, or what it means to be dead.”
Our reading: GPT-3 has no idea what grape juice or cranberry juice is, what pouring, sniffing, smelling or drinking are, or what it means to be dead.
No horizon
Scope: GPT-3, in the grape-juice example
Source: Statistics versus Understanding: The Essence of What Ails Generative AI
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Taking a real chance at wrecking both society and the environment on little more than vague speculation makes no sense.”
Our reading: Taking a real chance at wrecking both society and the environment on little more than vague speculation makes no sense.
No horizon
Qualifier: on little more than vague speculation
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If the battles over resources became acute enough, actual war could ensue.”
Our reading: If competition over resources for AI chips became acute enough, actual war could follow.
No horizon
Only if: if battles over resources for AI chips became acute enough
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Even if AI doesn’t kill all or many of us directly, as some people fear, the collapse of a $7 trillion project could trigger a devastating, worldwide financial depression, far worse than the subprime mortgage crisis of 2007-2008.”
Our reading: The collapse of a $7 trillion AI project could trigger a worldwide financial depression worse than the 2007-2008 crisis.
No horizon
Only if: if the $7 trillion project collapses
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“My guess is that is actually a very conservative estimate going forward, particularly if models continue the trend of becoming bigger and more costly to train.”
Our reading: GenAI's future energy needs will probably exceed the power consumption of Germany, especially if models keep growing.
No horizon
Qualifier: particularly if models keep getting bigger and costlier to train
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“We should all say “No” to reckless AI expansionism — unless and until tech leaders can show persuasively that the technology is mature enough that such expansion would demonstrably yield enormous net benefit.”
Our reading: We should all say no to reckless AI expansionism unless and until tech leaders can show persuasively that the technology is mature enough that such expansion would demonstrably yield enormous net benefit.
No horizon
Qualifier: unless and until tech leaders can show persuasively that the technology is mature enough that expansion would demonstrably yield enormous net benefit
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Let’s not by any means abandon research in AI, altogether—I do still see great hope if we can get to more trustworthy forms of AI—butfor now we should be focusing primarily on safety and innovative new approaches, rather than rushing to scale up existing and problematic architectures to unfathomable and unpredictable consequences.”
Our reading: AI research should not be abandoned altogether, but for now the focus should be primarily on safety and innovative new approaches rather than rushing to scale up existing, problematic architectures.
No horizon
Qualifier: for now
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“So far GenAI has been mostly promise, rather then delivery. There is no argument yet that it is actually worth tearing up the globe.”
Our reading: So far GenAI has been mostly promise rather than delivery, and there is no argument yet that it is actually worth tearing up the globe.
No horizon
Qualifier: so far
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“It is bad enough that large language models are making this kind of stuff easy now; worse that companies like OpenAI seem content to let society bear all the costs, like some careless industrial plant belching out toxic chemicals back in the day.”
Our reading: Large language models are now making scams like fake books easy, and companies like OpenAI seem content to let society bear all the costs.
No horizon
Qualifier: seem
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“A project that costs $7 trillion is inevitably going to be seen as too too big to fail. Any bailout could easily shatter the world’s economy.”
Our reading: A project that costs $7 trillion will inevitably be seen as too big to fail, and any bailout could easily shatter the world's economy.
No horizon
Only if: a project that costs $7 trillion
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If you want go to fast, fine; if you want to go insanely fast, you risk screwing the pooch, and possibly the entire field of AI along with it.”
Our reading: Scaling AI insanely fast risks failure that could damage the whole field of AI.
No horizon
Only if: if AI expansion goes insanely fast
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“In asking for $7 trillion, it is pretty obvious to most that Sam Altman has jumped the shark.”
Our reading: Sam Altman's request for $7 trillion shows he has jumped the shark.
No horizon
Source: Seven reasons why the world should say No to Sam Altman
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“My guess is that Altman never gets the money, even in ten yearly $700B tranches.”
Our reading: Altman will probably never raise the $7 trillion, even in ten yearly $700B tranches.
No horizon
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Without massive technical advances, chains of LLMs are unlikely to give us that.”
Our reading: Without massive technical advances, chains of LLMs are unlikely to provide a stable and secure basis for agents.
No horizon
Only if: without massive technical advances
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“To begin with, it’s just not clear that anywhere near that much capital is available.”
Our reading: It is not clear that anywhere near $7 trillion of capital is available for Altman's project.
No horizon
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“But they need to be built on a stable and secure basis.”
Our reading: AI agents need to be built on a stable and secure foundation.
No horizon
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Whatever number the investors might run, I am not remotely convinced that we are particularly close to AGI.”
Our reading: Whatever numbers investors might run, Marcus is not remotely convinced that we are particularly close to AGI.
No horizon
Qualifier: whatever number the investors might run
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“Combine that with worries about security, and it’s all a colossal accident waiting to happen.”
Our reading: Marcus calls device-controlling LLM agents, given their privacy problems combined with worries about security, 'a colossal accident waiting to happen'.
No horizon
Qualifier: privacy access combined with security worries
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Nor am I confident that Altmann or anyone else has any idea in the near term about how to make AGI safe.”
Our reading: Marcus is not confident that Altman or anyone else has any idea, in the near term, of how to make AGI safe.
No horizon
Qualifier: in the near term
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“I won’t say that this can’t happen. But it is deeply speculative.”
Our reading: Marcus will not rule out the upside scenario in which Altman, OpenAI and their partners achieve AGI that conquers sickness and climate change and Altman uses his cut to subsidize everyone else, but he calls that scenario deeply speculative.
No horizon
Qualifier: declines to say it can't happen
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“One screwup (and we all know LLMs are prone to screwups) and a LOT of people could die.”
Our reading: If LLM agents ran on Defense Department computers, a single LLM error could kill many people.
No horizon
Only if: if such agents run on Department of Defense computers
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Rogue employees could take over your devices, and bad actors will have tremendous incentive to hack OpenAI’s security.”
Our reading: If OpenAI's software can take over user devices, rogue employees could take over devices and attackers will have strong incentive to hack OpenAI.
No horizon
Only if: if OpenAI's software can take over user devices
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Nor am I convinced that the proceeds (if they did succeed) would be redistributed remotely equitably.”
Our reading: Marcus is not convinced that, if Altman's $7 trillion project succeeded, its proceeds would be redistributed remotely equitably.
No horizon
Only if: if the project succeeded
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“In short, I am putting LLM-based agents distributed to millions of customers at the top of my list of most dangerous ideas of 2024.”
Our reading: Marcus puts LLM-based agents distributed to millions of customers at the top of his own list of the most dangerous ideas of 2024.
No horizon
Qualifier: distributed to millions of customers
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“The best realistic case is that LLM-based agents never see widespread release. If we are lucky, their likely problems with reliability and all the associated risks will cause them to die on the vine.”
Our reading: The best realistic outcome is that LLM-based agents never see widespread release, dying because of their likely reliability problems.
No horizon
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“First, in The Information earlier this week was a hint that OpenAI might not be knocking it out of the park economically.”
Our reading: There are signs OpenAI may not be doing very well economically.
No horizon
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“I doubt we will have the maturity we need in the next several years.”
Our reading: AI agent technology is unlikely to reach the needed maturity for reliable use in the next several years.
No horizon
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“In the very best case, LLM-based agents will change the world for the better. But I don’t see that happening, certainly not this decade.”
Our reading: Marcus does not see LLM-based agents changing the world for the better, which he calls the very best case, and certainly not this decade.
No horizon
Qualifier: in the very best case
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Even if the $7 trillion bet succeeded (on its own terms), it might tear apart society through radically increased unemployment and social inequality or redrawn geopolitics that are hard even to fathom.”
Our reading: Even if the $7 trillion bet succeeded, it might tear apart society through unemployment, inequality or upheaval in geopolitics.
No horizon
Only if: if the $7 trillion bet succeeded on its own terms
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Giving the keys to the castle to an LLM, at our current level of technological readiness, seems to me to be batshit insane.”
Our reading: At current technological readiness, giving LLMs full control of users' systems is reckless and should not be done.
No horizon
Qualifier: at current level of technological readiness
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If they throw LLM-based agents over the fence, we are all in grave danger.”
Our reading: If OpenAI releases LLM-based agents carelessly, everyone will be in grave danger.
No horizon
Only if: if OpenAI releases LLM-based agents without responsibility
Source: What Could Possibly Go Wrong with Sam Altman’s New Ambitions?
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“These systems don’t deeply understand their inputs, contra Dr. Hinton, and as pointed out here regularly.”
Our reading: Large language models do not deeply understand their inputs.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“We really should consider trying some other approaches to AI.”
Our reading: The AI field should consider approaches to AI other than scaling large language models.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“You shouldn’t count on these systems.”
Our reading: People should not rely on large language model systems.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“And they continue to be unstable in virtually everything they do.”
Our reading: Generative AI systems continue to be unstable in virtually everything they do.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“There are many legitimate near-term fears about the misuse of AI, ranging from mis- and disinformation to voice cloning scams to bias to deepfake scams and deepfake porn.”
Our reading: There are many legitimate near-term fears about the misuse of AI, ranging from misinformation and disinformation to voice cloning scams, bias, deepfake scams and deepfake porn.
No horizon
Qualifier: near-term
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Please, developers and military personnel, don’t let your chatbots grow up to generals.”
Our reading: Developers and military personnel should not let chatbots take on the role of military generals.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Letting them run a war would be malpractice.”
Our reading: Generative AI systems should not be allowed to run a war; doing so would be malpractice.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“One might conceivably attribute some shallow level of understanding to LLMs, but there are many reasons to doubt that current neural networks have deep understanding.”
Our reading: There are many reasons to doubt that current neural networks have deep understanding, although one might conceivably attribute some shallow level of understanding to LLMs.
No horizon
Scope: current neural networks
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“By not even acknowledging the growing literature on memorization (let alone challenging it), Hinton made himself look to be seriously out of touch.”
Our reading: By not even acknowledging, let alone challenging, the growing literature on memorization, Hinton made himself look seriously out of touch.
No horizon
Qualifier: by not even acknowledging (let alone challenging) the growing literature on memorization
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Now it’s AI developers who are expecting to do what they do scot-free, while society picks up the tab.”
Our reading: AI developers expect to operate without paying for the harms they cause, leaving society to bear the costs, much as polluting factories once did.
No horizon
Source: Deepfaked Shit is Getting Real
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“That needs to change.”
Our reading: The situation in which AI developers do what they do scot-free while society picks up the tab for the consequences needs to change.
No horizon
Source: Deepfaked Shit is Getting Real
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“Black Mirror has arrived, ahead of schedule.”
Our reading: Dystopian, Black Mirror-style AI harms such as deepfake fraud have already arrived, sooner than expected.
No horizon
Source: Deepfaked Shit is Getting Real
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“but the media and the public need to realize that company white papers are not peer-reviewed articles. Particularly when it comes to safety-critical questions, peer-review is essential.”
Our reading: The media and public must recognize that company white papers are not peer-reviewed, and peer review is essential for safety-critical questions.
No horizon
Qualifier: safety-critical questions
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“Unfortunately, in the specific domain in which we are talking about, bioweapons risk, even a tiny effect could literally be world-changing, in a deeply negative way.”
Our reading: In the bioweapons domain, even a tiny effect of LLMs on capability could be world-changing in a deeply negative way.
No horizon
Qualifier: in the bioweapons domain
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Unfortunately footnote [C] is extremely dubious.”
Our reading: Footnote C of OpenAI's paper, which says the results are not statistically significant, is extremely dubious.
No horizon
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“If an LLM equips even one team of lunatics with the ability to build, weaponize and distribute even one pathogen as deadly as covid-19, it will be really, really big deal.”
Our reading: If an LLM equips even one team of lunatics with the ability to build, weaponize and distribute even one pathogen as deadly as covid-19, that will be a really, really big deal.
No horizon
Only if: if an LLM equips even one team of lunatics to build, weaponize and distribute even one pathogen as deadly as covid-19
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“The threshold itself is arbitrary, and it is rarely good practice to use thresholds in statistical analysis, because doing so throw away information”
Our reading: The 8-of-10 threshold OpenAI used is arbitrary, and using thresholds in statistical analysis is rarely good practice because doing so throws away information.
No horizon
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Statistical significance is in part a function of sample size; with a bigger sample size, I doubt there would be any question about significance at all.”
Our reading: With a bigger sample size, the author doubts there would be any question that the effect of LLM access is statistically significant.
No horizon
Only if: if the sample size were bigger
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“What the results really seem to be showing is that (a) the nonexperts aren’t so much to be worried about, because few get over the hump, but (b) experts really do seem to be helped, in every aspect of development.”
Our reading: The study results seem to show that nonexperts are not much of a worry because few clear the threshold, but experts do seem to be helped in every aspect of bioweapon development.
No horizon
Qualifier: as interpretation of the study results
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“It should go without saying that any risk-benefit analyses that with respect to the tradeoffs involved in AI needs to reflect studies that are not just methodologically sound but also interpreted accurately.”
Our reading: AI risk-benefit analyses need to be based on studies that are both methodologically sound and accurately interpreted.
No horizon
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“Indeed, in a domain like this, thresholds can be deeply misleading, because we don’t really know the relation between a threshold in the experiment and what would matter in the real world.”
Our reading: In the bioweapons domain, experimental thresholds can be deeply misleading because the relation between an experimental threshold and real-world significance is unknown.
No horizon
Qualifier: in the bioweapons domain
Source: Diving deep into OpenAI’s new study on LLM’s and bioweapons