Pundit ClaimsAI claims by Gary Marcus and Ed Zitron, with the evidence

Claims checked against evidence, page 17 of 31

Claims by Gary Marcus and Ed Zitron. Deadlines are judged as of 2026-10-29.

Claims checked against evidence (3100)

Each of these claims was checked against dated evidence.

Page 17 of 31: claims 1601 to 1700 of 3100, ordered by the date first said, newest first. To find a claim by its words, use search.

  1. Assessment: SupportedSaid

    Ed Zitron

    “In effect, CoreWeave spends $1.43 to make $1.”

    What happened: The filing reports 2024 revenue of $1,915.426 million and net loss of $863.448 million, giving approximately $1.45 per revenue dollar. This supports the approximate loss-inclusive comparison, while correcting its arithmetic and leaving cash spending unmeasured. (CoreWeave, filing mirrored by Yahoo Finance, )

  2. Assessment: UnresolvedSaid

    Ed Zitron

    “Cloud GPUs are incredibly commoditized, and the core factors of differentiation between the various players are price, availability, and the exact hardware available.”

  3. Assessment: MixedSaid

    Ed Zitron

    “Converting cryptocurrency mining data centers to HPC data centers is effectively starting from scratch. There is no easy or logical way to repurpose a bitcoin miner for AI.”

    What held: The engineering discussion describes adding generators, chillers, batteries, UPS equipment, and GPU systems. It supports the claim that conversion requires substantial new equipment rather than simply putting existing Bitcoin machines to work on AI. (Core Scientific, transcript hosted by StockAnalysis, )

    What did not: The filing identifies existing infrastructure as an input to the HPC conversion, contradicting the implication that there is no practical reuse path. Separately, it describes the mining hardware as specialized SHA-256 ASICs, reinforcing the distinction between reusing a facility and reusing its mining chips. (Core Scientific, )

  4. Assessment: SupportedSaid

    Ed Zitron

    “Worse, despite making $1.9 billion in revenue during the 2024 financial year, the company lost $863 million in 2024, with its entire future riding on "explosive growth" that may not materialize, and even if it does, would require CoreWeave to spend unfathomable amounts of money on the necessary capex investments.”

    What happened: The overview reports the stated net loss and $1.9 billion revenue. The financial tables give revenue of $1,915.426 million and net loss of $863.448 million, which round to the claimed amounts. (CoreWeave, Inc.; filing mirrored by Yahoo Finance, )

  5. Assessment: ContradictedSaid

    Ed Zitron

    “If CoreWeave makes it to IPO — and it may do so as soon as next week — it will raise about $4 billion, which might give it enough runway to continue operations for a year, but by October 2025 it’ll face upwards of $500 million of loan payments a quarter, all while trying to scale up an operation that doesn't appear to have a path to profit.”

    What happened: The announcement specifies 36,590,000 issuer shares at $40, giving CoreWeave $1.4636 billion before fees; the $1.5 billion headline includes selling shareholders. Completion is independently confirmed by e1, and neither amount approaches $4 billion. (CoreWeave, )

  6. Assessment: UnresolvedSaid

    Ed Zitron

    “While it may sell by-the-hour compute to regular companies, it's clear that that market just doesn't exist at a meaningful revenue point.”

  7. Assessment: UnresolvedSaid

    Ed Zitron

    “CoreWeave's future is one that requires an industry that has yet to show any meaningful product-market fit to grow so significantly that compute companies turn into oil companies”

  8. Assessment: SupportedSaid

    Ed Zitron

    “Regardless of the reason, the company selling the literal fuel of the supposed AI revolution is losing hundreds of millions of dollars doing so.”

    What happened: Reuters reports the company's 2024 net loss as $863 million, which directly meets the claimed magnitude. This is a reported company result, not a Reuters estimate. (Reuters, republished by 93-5 The Lloyd, )

  9. Assessment: UnresolvedSaid

    Ed Zitron

    “In short, CoreWeave's position is one that at the very least competes with the hyperscalers, and is both a fascinating and disturbing window into the actual money that these companies do (or don't) make, and the answer is "not very much at all."”

  10. Assessment: UnresolvedSaid

    Ed Zitron

    “The problem is that, yes, GPUs are depreciating assets, a fact that will eventually become problematic for these companies.”

  11. Assessment: SupportedSaid

    Ed Zitron

    “CoreWeave’s S-1 tells the tale of a company that appears to be built for collapse, with over 60% of its revenue dependent on one customer, Microsoft.”

    What happened: The filing identifies Microsoft and reports a 62% share for fiscal 2024, exceeding the stated 60% threshold. This establishes concentration, not eventual collapse. (CoreWeave, Inc.; filing mirrored by Yahoo Finance, )

  12. Assessment: UnresolvedSaid

    Gary Marcus

    “For a man who allegedly believes human coders are basically done, Amodei sure has a lot of openings for coders.”

  13. Assessment: SupportedSaid

    Gary Marcus

    “I don’t want spoil all the fun, but … things didn’t go well:”

    What happened: Supports. (The Guardian, )

  14. Assessment: SupportedSaid

    Gary Marcus

    “To be sure, most or all trained coders will (if they are not already) soon use AI as a part of their workflow.”

    What happened: Daily use alone exceeds half of professional respondents. This avoids counting respondents who only plan to adopt AI. (Stack Overflow, )

  15. Assessment: UnresolvedSaid

    Gary Marcus

    “AI will be a tool to help people write code, just as spell-checkers are a tool to help authors write articles and novel, but AI will not soon replace people who understand how to conceive of, write, and debug code.”

  16. Assessment: MixedSaid

    Gary Marcus

    “As a fantastic, souped-up version of autocomplete, AI coding tools somewhat increase productivity.”

    What held: A randomized study of 96 Google engineers estimated about 21% less task time with completion, paste, and code-generation assistance. The task required passing tests, although the estimate had substantial uncertainty. (Google researchers / arXiv, )

    What did not: Sixteen experienced maintainers completed 246 randomized tasks more slowly when AI was allowed. The study covered February–June tools, primarily Cursor with Claude 3.5/3.7; it is adverse evidence for broad coding assistance, not an isolated test of autocomplete. (METR researchers / arXiv, )

  17. Assessment: UnresolvedSaid

    Gary Marcus

    “And they don’t magically resolve the challenges of maintaining complex code bases over time.”

  18. Assessment: UnresolvedSaid

    Gary Marcus

    “The idea that coders (and more generally, software architects) are on their way out is absurd.”

  19. Assessment: UnresolvedSaid

    Gary Marcus

    “A few days ago he triumphantly claimed (without evidence) that nearly all code would be written by AI within the next year:”

  20. Assessment: SupportedSaid

    Gary Marcus

    “Musk’s robotaxi promise hasn’t fared much better.”

    What happened: Tesla’s signed January disclosure still described launching the business and fully autonomous operation as future developments. This supports the inference that the million-robotaxi promise for 2020 remained substantially unfulfilled. (Tesla, Inc.; copy hosted by AnnualReports, )

  21. Assessment: UnresolvedSaid

    Gary Marcus

    “That is not going to magically change next year, at a time when AI still can’t reliably solving river-crossing problems.”

  22. Assessment: UnresolvedSaid

    Gary Marcus

    “That is not going to magically change next year, at a time when AI still can’t reliably solving river-crossing problems.”

  23. Assessment: SupportedSaid

    Gary Marcus

    “Even in the best work, like Google’s new AI co-scientist, humans scientists are still choosing the research goals.”

    What happened: Google's launch description makes scientist-supplied objectives the system's input and describes experts selecting its evaluation goals. AI-generated hypotheses and research plans therefore operated within human-chosen objectives. (Google Research, )

  24. Assessment: UnresolvedSaid

    Gary Marcus

    “Nobel-calibre science requires sound logic, reliable causal reasoning, and originality, and none of those are firmly in the grasp of current AI.”

  25. Assessment: SupportedSaid

    Gary Marcus

    “Hallucinations haven’t solved, despite constant assurances.”

    What happened: Table 4 reports a PersonQA hallucination rate of 0.19 for GPT-4.5, compared with 0.30 for GPT-4o and 0.20 for o1. These results show improvement alongside substantial remaining failures; they do not measure all everyday usage. (OpenAI, )

  26. Assessment: UnresolvedSaid

    Gary Marcus

    “• AGI should have a reliable ability to understand complex syntactic and semantic structure. (Failings here are also often reflected in quirky errors.”

  27. Assessment: UnresolvedSaid

    Gary Marcus

    “Especially when we just saw GPT-5 (ultimately relabeled as GPT 4.5) fail despite more than two years of hard and expensive work.”

  28. Assessment: SupportedSaid

    Gary Marcus

    “Hallucinations simply haven’t gone away, even in the latest models.”

    What happened: Table 4 reports PersonQA hallucination rates of 0.19 for GPT-4.5, 0.30 for GPT-4o, and 0.20 for o1. The release evaluation directly establishes persistence, while also showing improvement over the comparison models. (OpenAI, )

  29. Assessment: SupportedSaid

    Gary Marcus

    “• AGI should have reliable ability to reason over abstractions. (Ongoing unpredictable errors in LLMs reflect this.)”

    What happened: MIR-Bench tests fifteen models on deriving outputs from examples of underlying functions. Its controlled evaluations find substantial remaining failures, including in o1-family models, supporting the limited reliability claim. (Kai Yan and colleagues, arXiv, )

  30. Assessment: UnresolvedSaid

    Gary Marcus

    “But it is not just that I think Klein is wrong, or that he did a disservice to the other side of the argument, but that words like his are motivating a lot of dodgy bets being placed on the imminent AGI assumption — in ways that may not make sense.”

  31. Assessment: UnresolvedSaid

    Gary Marcus

    “What that means is that a quarter century has passed without a principled solution to even one of those problems.”

  32. Assessment: UnresolvedSaid

    Gary Marcus

    “(My view, as I explained in Taming Silicon Valley, is that industry has a vested interest in making people believe that AGI is imminent — how else to justify the lavish valuations - and that they have fooled a lot of people in government who aren’t technical experts into believing that AGI is closer than it really is).”

  33. Assessment: UnresolvedSaid

    Gary Marcus

    “The fact that Grok 3 was 15x the size of Grok 2, and also generally viewed as disappointing.”

  34. Assessment: SupportedSaid

    Gary Marcus

    “Most parts of the US still don’t have functioning driverless cars systems, for example, even after over a decade of lavish promises.”

    What happened: The article identifies existing Waymo service in Phoenix, San Francisco and Los Angeles, with Austin launching and other cities still planned. This supports geographically limited availability; national breadth is an inference from the deployment account. (Associated Press, syndicated by Tech Xplore, )

  35. Assessment: SupportedSaid

    Gary Marcus

    “But it is absolutely absurd to pretend “AGI imminent” hypothesis isn’t getting play in high places.”

    What happened: OpenAI's leader publicly expresses confidence in a path to AGI, alongside discussion of near-term agents and further advances. This establishes high-level attention, without proving any particular arrival date. (Sam Altman, )

  36. Assessment: SupportedSaid

    Gary Marcus

    “Every red cell in this graph (e.g, multiplying 20 digit numbers by 19 digit numbers2) is failure to generalize, even after immense amounts of training data:”

    What happened: The original experiment reports a clear limit to reliable multiplication as input length grows. The thread identifies o1-mini and reports similar accuracy for o1-preview, supporting the claim about the tested models. (Yuntian Deng, reproduced by Thread Reader, )

  37. Assessment: UnresolvedSaid

    Gary Marcus

    “The fact that GPT 4.5 received very mixed reviews — despite years of labor and billions investment — and could in no reasonable way be considered a major (rather than minor, incremental) step forwards towards AGI.”

  38. Assessment: UnresolvedSaid

    Gary Marcus

    “And these complex systems, built on the unreliable foundations of LLMs, are going to prove to be massively difficult to debug.”

  39. Assessment: UnresolvedSaid

    Gary Marcus

    “But there’s also no reason to think that any of them are logically insolvable in principle. So we will get there someday.”

  40. Assessment: UnresolvedSaid

    Gary Marcus

    “AI might replace average people in some tasks soon; replacing the best humans in a few years? Not going to happen.”

  41. Assessment: UnresolvedSaid

    Ed Zitron

    “OpenAI has no path to profitability, guaranteeing it will need more cash, and right now — at the time when it needs the most it’s ever needed — SoftBank, the only company willing to provide it, has proven that it will have to go to great lengths to do so.”

  42. Assessment: UnresolvedSaid

    Ed Zitron

    “Worse still, thanks to this agreement, OpenAI’s future — both in its ability to expand its infrastructure (which appears to be entirely contingent on the construction of Stargate) and its ability to raise funding — is entirely dependent on SoftBank, which in turn must borrow money to fund it.”

  43. Assessment: UnresolvedSaid

    Ed Zitron

    “It is time for investors and the general public to begin demanding tangible and direct numbers on the revenue and profits related to generative AI, as it is becoming increasingly obvious that the revenues are small and the profits are non-existent.”

  44. Assessment: UnresolvedSaid

    Ed Zitron

    “SoftBank has committed to over $40 billion of costs that it cannot currently afford, taking on as much as $24 billion in debt in the next year to help sustain one more funding round and the construction of data centers for OpenAI, a company that loses money on literally every single customer.”

  45. Assessment: UnresolvedSaid

    Gary Marcus

    “I can’t imagine that noncoders are really going to get those systems to work well enough for prime time (except perhaps in very very narrow use cases), let alone know what do when the back end internet calls break.”

  46. Assessment: UnresolvedSaid

    Gary Marcus

    “They never let you know that a significant number of real world coders are deeply frustrated with automated coding tools like Cursor.AI (which is in part powered by Anthropic’s Claude):”

  47. Assessment: UnresolvedSaid

    Gary Marcus

    “Nine years later and hundreds of startups later, my understanding is that not one radiologist has been replaced, and many parts of the world actually have a shortage of radiologists.”

  48. Assessment: UnresolvedSaid

    Gary Marcus

    “People are increasingly going to discourage American children from learning to code based on naive enthusiasm from people like Roose.”

  49. Assessment: UnresolvedSaid

    Gary Marcus

    “At least for another decade or two and probably more, big projects are always going to require software architects who know what they are doing.”

  50. Assessment: UnresolvedSaid

    Gary Marcus

    “it’s often easy to get a solution that is 80% correct, and extremely difficult to get the last 20%. Driverless cars have been like that for decades.”

  51. Assessment: SupportedSaid

    Gary Marcus

    “A new study of the latest system, GPT 4.5 showed that by on one standardized measure over 1/3 of the outputs are still hallucinations.”

    What happened: The report identifies a 37.1% hallucination rate for the February GPT-4.5 model on SimpleQA, exceeding one third. This is secondary reporting of OpenAI's result because the primary page's numeric chart values were absent from readable text. (Computerworld, )

  52. Assessment: SupportedSaid

    Gary Marcus

    “Already, of course, DeepSeek has shown that our once strong lead is diminishing.”

    What happened: The historical comparison reports a US-China Chatbot Arena rating gap narrowing from 9.3% in January 2024 to 1.7% in February 2025. The provider chart identifies DeepSeek at 1,362, close to Google at 1,385 and OpenAI at 1,366, linking the narrowing to DeepSeek. (Stanford Institute for Human-Centered Artificial Intelligence, AI Index, )

  53. Assessment: SupportedSaid

    Gary Marcus

    “Here Roose has displayed the cardinal sin of looking only at regurgitation rather than generalization. History has told us over and over that systems can be good at the former and still face enormous challenges at the latter.”

    What happened: StarCoderBase-15.5B achieved 72% accuracy on the most training-similar tenth of MBPP questions and 22% on the least similar tenth. The authors also investigated whether difficulty explained the association; these are familiarity comparisons, not proof of verbatim copying. (Martin Riddell, Ansong Ni and Arman Cohan, arXiv, )

  54. Assessment: SupportedSaid

    Gary Marcus

    “Many many top people have left (Sutskever, Murati, Schulman, recently, Amodei and Karpathy before, etc and many, many more).”

    What happened: The individual accounts document eight senior departures during 2024, including Karpathy, Sutskever, Schulman, and Murati; the Leike section also identifies Dario Amodei as a former OpenAI employee. The article explicitly distinguishes Brockman's temporary leave, which is excluded. (Observer, )

  55. Assessment: SupportedSaid

    Gary Marcus

    “Scaling hasn’t gotten them —or anyone else — to AGI.”

    What happened: The evaluator recognized a major advance but explicitly rejected treating the tested o3 as AGI. The discussion also identifies failures on tasks easy for humans. (ARC Prize, )

  56. Assessment: SupportedSaid

    Gary Marcus

    “And of course, there is still no GPT-5, even after two years, of hype, bullshit, and cryptic hints.”

    What happened: OpenAI's CEO explicitly places GPT-5's public availability in the future shortly before the post. The roadmap distinguishes it from the impending GPT-4.5 release. (Sam Altman / OpenAI, )

  57. Assessment: SupportedSaid

    Gary Marcus

    “Some have started serious competitors with similar IP.”

    What happened: The report identifies Dario and Daniela Amodei as Anthropic's co-founders and former OpenAI executives, and describes direct competition between the model families. (Reuters via Yahoo Finance, )

  58. Assessment: MixedSaid

    Gary Marcus

    “Whatever lead OpenAI had two years ago has been squandered.”

    What held: The developer reports a competitor matching o1 on reasoning tasks, supporting erosion of an uncontested technical lead. This does not establish parity on every capability. (DeepSeek-AI, via arXiv, )

    What did not: The report identifies ChatGPT as the leading app in its mobile usage comparison, alongside monetization. Its usage evidence contradicts the broad claim that OpenAI had lost its product lead. (Andreessen Horowitz, using Sensor Tower data, )

  59. Assessment: UnresolvedSaid

    Gary Marcus

    “DeepSeek led to a price war that cuts potential profits.”

  60. Assessment: UnresolvedSaid

    Gary Marcus

    “(And Elon is right that they don’t have all or most of the Stargate funding in hand).”

  61. Assessment: UnresolvedSaid

    Gary Marcus

    “Because OpenAI’s burn rate is so high (perhaps on the order of a couple billion dollars a month), they have limited runway, even after last year’s massive financing.”

  62. Assessment: SupportedSaid

    Gary Marcus

    “GPT 4.5 is hugely expensive.”

    What happened: The same paragraph lists standard input at $75 and output at $150 per million tokens. Against the contemporary Anthropic prices in e2, those are premiums of 25 times for input and 10 times for output. (OpenAI, )

  63. Assessment: UnresolvedSaid

    Gary Marcus

    “Even Altman himself was uncharacteristically tepid in his product announcement.”

  64. Assessment: SupportedSaid

    Gary Marcus

    “So now GPT 4.5 has dropped, and — breaking news — I was right. Hallucinations didn’t disappear today, and nor did stupid errors.”

    What happened: The launch card reports a 0.19 PersonQA hallucination rate and 0.74 accuracy on unambiguous BBQ questions, where the answer is supplied in the prompt. These establish persistent hallucinations and straightforward answer-selection mistakes, although PersonQA improved over GPT-4o. (OpenAI, )

  65. Assessment: UnresolvedSaid

    Gary Marcus

    “Gary Marcus was right all along that pure scaling would eventually hit a wall, or at least reach a point of massively diminishing returns.”

  66. Assessment: UnresolvedSaid

    Gary Marcus

    “Right now, the math for profitability doesn’t work, influence on productivity of GenAI has been minimal, and prospects for pure scaling aren’t looking great.”

  67. Assessment: UnresolvedSaid

    Gary Marcus

    “Right now, the math for profitability doesn’t work, influence on productivity of GenAI has been minimal, and prospects for pure scaling aren’t looking great.”

  68. Assessment: UnresolvedSaid

    Gary Marcus

    “It’s not just OpenAI either; it’s the whole field, as I discussed in my own recent Fortune article:”

  69. Assessment: SupportedSaid

    Gary Marcus

    “Actually, at any moment, we will finally get GPT 4.5, which most certainly wouldn’t live up to expectations around GPT-5 — hence its rather tentative name.”

    What happened: The release card reports a PersonQA hallucination rate of 0.19 for GPT-4.5. That is an improvement over the comparison models, but hallucinations clearly remain. (OpenAI, )

  70. Assessment: UnresolvedSaid

    Gary Marcus

    “The truth is that scaling just isn’t producing the fruit that it once did.”

  71. Assessment: UnresolvedSaid

    Gary Marcus

    “And for that matter people should be comparing GenAI revenue (on the order of low tens of billions per year, pre price wars) with GenAI expenditures (order half a trillion dollars to date), and doing the math, especially given the price wars induced by DeepSeek.”

  72. Assessment: SupportedSaid

    Gary Marcus

    “In “Deep learning is hitting a wall”, I warned that problems with reasoning and hallucination wouldn’t go away simply as a function of scaling, and they haven’t.”

    What happened: The January launch system card, in its February file version, reports a 14.8% PersonQA hallucination rate for o3-mini. Its comparison models also have nonzero rates, despite improvements. (OpenAI, )

  73. Assessment: UnresolvedSaid

    Gary Marcus

    “I personally noticed Musk’s shutting out of opposing views when he stopped answering my emails when I warned him in July – correctly - that throwing in with Trump would undermine the cause of AI safety (which for a decade, until a few weeks ago, seemed extremely important to Musk).”

  74. Assessment: UnresolvedSaid

    Ed Zitron

    “I must repeat that Microsoft will have spent over $200 billion in capital expenditures by the end of 2025.”

  75. Assessment: UnresolvedSaid

    Ed Zitron

    “As a result of the costs of running these services, a free user of ChatGPT is a cost burden on OpenAI, as is every free customer of Google's Gemini, Anthropic's Claude, Perplexity, or any other generative AI company.”

  76. Assessment: UnresolvedSaid

    Ed Zitron

    “And let’s be abundantly clear: OpenAI cannot exist any further without further venture capital investment. This company has absolutely no path to sustain itself, no moat, and loses so much money that it will need more than $50 billion to continue in its current form.”

  77. Assessment: UnresolvedSaid

    Ed Zitron

    “It doesn’t just cost more to run OpenAI than it makes — it costs the company a billion dollars more than the entirety of its revenue to run the software it sells before any other costs.”

  78. Assessment: UnresolvedSaid

    Ed Zitron

    “Anthropic, like OpenAI, has no moat.”

  79. Assessment: UnresolvedSaid

    Ed Zitron

    “Though Altman has promised that ChatGPT Plus and free users will eventually get access to a few Deep Research queries a month, this will only increase its cash burn further!”

  80. Assessment: UnresolvedSaid

    Ed Zitron

    “These realities — the lack of utility and product differentiation — also mean that OpenAI can’t raise its prices above the breakeven point, which would also likely make its generative AI unaffordable and unattractive to both business and personal customers.”

  81. Assessment: UnresolvedSaid

    Ed Zitron

    “OpenAI also spends an alarming amount of money on salaries — over $700 million in 2024 before you consider stock-based compensation, a number that will also have to increase because it’s “growing” which means “hiring as many people as possible,” and it’s paying through the nose.”

  82. Assessment: UnresolvedSaid

    Ed Zitron

    “OpenAI's products are not fundamentally differentiated or interesting enough to be sold separately. It has failed — as with the rest of the generative AI industry — to meaningfully productize its models due to their massive training and operational costs and a lack of any meaningful "killer app" use cases.”

  83. Assessment: UnresolvedSaid

    Ed Zitron

    “Its products do not scale like traditional software, in that the more users it gets, the more expensive its services are to run because its models are so compute-intensive.”

  84. Assessment: SupportedSaid

    Ed Zitron

    “People really do use them for coding, for searching defined libraries of documents, for generating draft materials, for brainstorming, and for summarizing and searching documents. These are useful, but they are not magical.”

    What happened: The survey of 9,047 workers documents actual reported use in three named categories and also reports time-saving benefits. It establishes existence, not universal effectiveness. (UiPath and Researchscape, )

  85. Assessment: UnresolvedSaid

    Ed Zitron

    “Yet it isn’t working. Consumers don’t want this shit. They’re intrigued by the idea, then mostly immediately bouncing off of it once they see what it can (or can’t) do.”

  86. Assessment: UnresolvedSaid

    Ed Zitron

    “Said costs are also so severe that even paying customers lose these companies money.”

  87. Assessment: UnresolvedSaid

    Ed Zitron

    “Nevertheless, OpenAI loses money on every single paying customer, just like with its free users. Increasing paid subscribers also, somehow, increases OpenAI's burn rate. This is not a real company.”

  88. Assessment: UnresolvedSaid

    Ed Zitron

    “Large Language Models — which are trained by feeding them massive amounts of training data and then reinforcing their understanding through further training runs — are hitting the point of diminishing returns.”

  89. Assessment: UnresolvedSaid

    Ed Zitron

    “Though every single person that visits ChatGPT.com might not become a user, it’s safe to assume that ChatGPT’s Monthly Active Users are somewhere in the region of 500-600 million.”

  90. Assessment: UnresolvedSaid

    Ed Zitron

    “And the reason why OpenAI hasn’t fixed the hallucination problem isn’t because it doesn’t want to, but because it can’t. They’re an inevitable side-effect of LLMs as a whole.”

  91. Assessment: SupportedSaid

    Gary Marcus

    “Hallucinations haven’t been magically solved, etc.”

    What happened: Karpathy directly reports fabricated URLs during early-access testing of Grok 3's DeepSearch. Such fabrication establishes that hallucinations persisted in the launch product. (Andrej Karpathy, )

  92. Assessment: SupportedSaid

    Gary Marcus

    “That wasn’t tested (presumably they don’t have access), and only a handful of benchmarks were actually reported.”

    What happened: This contemporaneous observation explicitly identifies the omission of full o3. It establishes the public chart's scope, not whether xAI privately tested o3 or had access. (Rex Asabor, OpenAI employee, )

  93. Assessment: SupportedSaid

    Gary Marcus

    “That said, OpenAI’s moat keeps diminishing, so price wars will continue and profits will continue to be elusive for everyone except Nvidia.”

    What happened: The benchmark operator announced that early Grok 3 led its user-preference leaderboard. This supports the inference that another rival had become a credible capability alternative, although preference rankings do not measure every OpenAI advantage. (LMArena, reproduced by Thread Reader, )

  94. Assessment: SupportedSaid

    Gary Marcus

    “That said, OpenAI’s moat keeps diminishing, so price wars will continue and profits will continue to be elusive for everyone except Nvidia.”

    What happened: Confirms a post-publication reduction on an existing OpenAI model. It does not independently establish the reason for the cut. (OpenAI, )

  95. Assessment: UnresolvedSaid

    Gary Marcus

    “Spoiler alert: it wasn’t.”

  96. Assessment: SupportedSaid

    Gary Marcus

    “Simply false, in view of the many basic aspects of geometry that AlphaGeometry2 does not cover, as discussed above.”

    What happened: The original report explicitly identifies classes of problems that cannot be expressed. Section 2 also lists three-dimensional geometry and nonlinear equations among its coverage gaps, supporting incomplete breadth rather than general mastery. (arXiv; Google DeepMind researchers, )

  97. Assessment: UnresolvedSaid

    Gary Marcus

    “Taking this into account, the fraction of problems where a composite AI system could solve the problem starting with its English language statement is at most 60%.”

  98. Assessment: UnresolvedSaid

    Gary Marcus

    “DeepMind didn’t make that claim, and it isn’t true.”

  99. Assessment: SupportedSaid

    Gary Marcus

    “Unlike DeepMind’s AlphaZero system which learned to play multiple board games, or OpenAI’s ChatGPT, AlphaGeometry2 is nowhere close to being a single general-purpose learning architecture.”

    What happened: This retrospectively documents the system introduced in the February report: a symbolic geometry engine works with language-model proposals on formalized geometry inputs. That supports the ordinary reading of a specialized composite system. (Google DeepMind, )

  100. Assessment: UnresolvedSaid

    Gary Marcus

    “Even if one were to glom together the best general AIs with AlphaGeometry2, the combination would fall far short of the geometric understanding and problem solving ability of high school math student with a talent for math.”