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

Claims checked against evidence by Gary Marcus, page 11 of 19

Deadlines are judged as of 2026-10-29. About Gary Marcus and the sources covered.

Claims checked against evidence by Gary Marcus (1870)

Each of these claims was checked against dated evidence.

Page 11 of 19: claims 1001 to 1100 of 1870, ordered by the date first said, newest first. To find a claim by its words, use search.

  1. Assessment: SupportedSaid

    “The data are coming in – and it’s not.”

    What happened: The published study reported no significant improvement in pull-request cycle time or throughput. Its results support the claim about the contemporary research record, although they cannot establish a universal absence of benefits. (Uplevel, )

  2. Assessment: SupportedSaid

    “many lawsuits pending”

    What happened: The order addresses six actions: three consolidated author actions, the Times action, Daily News, and the Center for Investigative Reporting. Ongoing discovery and future deadlines establish pending status; grouping the author actions and the newly consolidated newspaper actions leaves three proceedings. (U.S. District Court, Southern District of New York; copy hosted by Chat GPT Is Eating the World, )

  3. Assessment: UnresolvedSaid

    “the company had an operating loss of $5b last year”

  4. Assessment: SupportedSaid

    “From left to right that’s Ilya Sutskever (now gone, less than a year later), Greg Brockman (on leave, at least until the end of the year), CTO Mira Murati (departure just announced) and Sam Altman (fired, and then rehired).”

    What happened: OpenAI announced Sutskever's departure in May, less than a year after the September 2023 reference point. (OpenAI, )

  5. Assessment: SupportedSaid

    “Co-founders John Schulman also left, so did Andrej Karpathy and Jan Leike, and perhaps a dozen others.”

    What happened: The report establishes Schulman's departure before the post and identifies him as a co-founder. (TechCrunch, )

  6. Assessment: UnresolvedSaid

    “Altman had, much to my surprise, just echoed my longstanding position that current techniques alone would not be enough to get to AGI”

  7. Assessment: SupportedSaid

    “I rushed out a hot take on X, my usual cautions about how LLMs aren’t really AGI:”

    What happened: The launch-era card documents failures in computer-mediated tasks normally performed by human lab assistants; its METR section also reports difficulties using tools and environmental feedback. These are substantive capability gaps supporting the ordinary human-level reading, rather than evidence based merely on occasional errors. (OpenAI, )

  8. Assessment: SupportedSaid

    “Almost exactly what I predicted we would see with GPT-4, back on Christmas Day 2022.”

    What happened: Altman's original statement contains all three elements of the comparison: continuing flaws, continuing limitations, and a stronger first impression than sustained use supports. (Sam Altman / X, )

  9. Assessment: SupportedSaid

    “You should be watching to see what the candidates plan to do about fraud and disinformation, as AI contributes to escalation in both.”

    What happened: This primary agency release connects AI to greater attack scale and describes increasing use of cloned voices and videos to induce fraudulent transactions. It provides a mechanism and an operational assessment, but no estimate of AI-attributable losses. (Federal Bureau of Investigation, San Francisco, )

  10. Assessment: SupportedSaid

    “And you should be watching to see what they plan to do about the growing problem of nonconsensual deep fake porn, and especially how that might affect the already vulnerable population of teenage girls, who have been hard by social media.”

    What happened: The Korean passage says the threat from sexual deepfakes of acquaintances and celebrities is substantially increasing. The accompanying police series records 297 cases through July 2024, compared with 180 in all of 2023, directly supporting growth in recorded cases. (Korean National Police Agency; copy hosted by the National Youth Policy Institute, )

  11. Assessment: UnresolvedSaid

    “Because the candidates – in the House, the Senate, and for President – certainly aren’t going to bother to talk about AI policy if we don’t let them know that it matters, to all of us.”

  12. Assessment: UnresolvedSaid

    “No such governance board ever materialized; if it does, you can bet it won’t have any teeth, unless there is a government mandate that it does.”

  13. Assessment: UnresolvedSaid

    “I stressed the same in my Senate testimony, but nothing thus far in existing US law addresses this need.”

  14. Assessment: SupportedSaid

    “California’s pending AI bill SB-1047 was supposed to be a tiny step in that direction, and even that has gotten watered down.”

    What happened: The author's official amendment announcement explicitly describes replacing criminal penalties with civil penalties. That is a concrete reduction in enforcement severity before publication, while preserving civil enforcement. (Office of California Senator Scott Wiener, )

  15. Assessment: SupportedSaid

    “When Sam Altman stood next to me in the Senate, he told the Senate that he strongly favored AI regulation. But behind the scenes his team fought to water down the EU AI Act.”

    What happened: Altman enthusiastically endorsed a proposed oversight agency and also endorsed licensing. The same exchange includes Marcus, establishing their participation in the hearing. (U.S. Senate Committee on the Judiciary / Government Publishing Office, )

  16. Assessment: UnresolvedSaid

    “Companies like OpenAI that have talked big about investing in safety research and then stinted on their promises”

  17. Assessment: SupportedSaid

    “It also provides important whistleblower protections, which as many ex OpenAI employees have made clear, are critical.”

    What happened: The official analysis confirms whistleblower protections in the relevant version. Its major provisions cover disclosures about noncompliance and unreasonably dangerous models to the Attorney General or Labor Commissioner. (California Legislature, Senate Third Reading analysis, )

  18. Assessment: ContradictedSaid

    “In the new form, SB 1047 can basically only be used only after something really bad happens, as a tool to hold companies liable. It can no longer protect us against obvious negligence that might likely lead to great harm.”

    What happened: The sponsor's official description expressly retains enforcement before harm where public safety faces an imminent threat. It also confirms the narrower point that enforcement was restricted. (Office of California Senator Scott Wiener, )

  19. Assessment: UnresolvedSaid

    “If the bill doesn’t pass, the view will be that Big Tech always wins; nobody will bother. Future state and federal efforts will suffer.”

  20. Assessment: SupportedSaid

    “Most or all of the major big tech companies joined a lobbying organization that fought SB-1047, tooth and nail, despite broad public support for the bill.”

    What happened: The report names four of the five companies in the stated ordinary Big Tech grouping. Contemporary reporting supplements the earlier primary partnership disclosure; affiliation does not establish that each company directed this particular campaign. (The Register, )

  21. Assessment: SupportedSaid

    “California’s SB-1047, not yet signed into law, but on its way to being one of the first really substantive AI bills in the US, primarily addressed to liability around catastrophic risks, was significantly weakened in last-minute negotiations.”

    What happened: The author's firsthand amendment summary confirms that civil penalties replaced criminal perjury penalties. It also identifies a reduced attestation standard and narrower access to civil penalties before harm, supporting a material reduction in safeguards. (Office of California Senator Scott Wiener, )

  22. Assessment: SupportedSaid

    “As I emphasized last year in front of the Senate, there is not one risk but many: bias, disinformation, defamation, toxicity, invasion of privacy, and so much more, to say nothing of risks to employment, intellectual property, and the environment, precisely because recent techniques can be applied in so many ways, still poorly understood.”

    What happened: The report identifies bias, harmful content, disinformation, privacy, intellectual-property and environmental risks, and discusses labor-market effects. It links estimation difficulties to diverse applications, limited training-data visibility, and immature safety measurement. (National Institute of Standards and Technology, )

  23. Assessment: UnresolvedSaid

    “And no, GPT-5 did not drop this week as many had hoped.”

  24. Assessment: SupportedSaid

    “Even then developers are required only to implement "reasonable safeguards" against these severe risks--not to fully mitigate them.”

    What happened: The July 3 analysis describes reasonable safeguards and a prohibition on release where unreasonable critical-harm risk remains. Together these support risk reduction without a zero-risk guarantee. (Foley & Lardner LLP, )

  25. Assessment: SupportedSaid

    “Lastly, asking for standards is not unique to AI; it's common across many industries to ask that companies evaluate the safety of their products according to set standards: just look at the pharmaceutical industry, or aviation, automobiles, etc.”

    What happened: FDA describes manufacturers testing drugs and submitting evidence against a defined safety-and-effectiveness requirement. The event date denotes this standing regulatory practice at the post date, not the document's publication. (U.S. Food and Drug Administration, )

  26. Assessment: SupportedSaid

    “And much of what would be required is already something companies committed to voluntarily, in discussions at the White House and in Seoul.”

    What happened: The announcement records pre-release testing, cybersecurity safeguards and sharing risk information. These overlap with central safety functions identified in the bill analysis. (The White House, announcing participating companies' commitments, )

  27. Assessment: SupportedSaid

    “But you don't make clear that much of the bill's requirements are limited to models with training runs of $100 million+. Companies that can afford that, presumably valued in the billions, are not exactly "little-tech."”

    What happened: The article expressly discusses the July 3 amendment and confirms that the $100 million training-cost threshold remained central. Its current page also contains a later veto notice, which is not used here. (Foley & Lardner LLP, )

  28. Assessment: SupportedSaid

    “OpenAI recently put Paul Nakasone (ex NSA) on the board”

    What happened: OpenAI directly announces Nakasone's appointment within the period described. Its concluding biography also identifies his former leadership of the NSA. (OpenAI, )

  29. Assessment: UnresolvedSaid

    “Sam Altman has acknowledged wanting to train on everyone's personal documents (Word files, email etc)”

  30. Assessment: UnresolvedSaid

    “OpenAI just put in money in a $60M fundraise with a Webcam company and is planning hardware joint venture with them.”

  31. Assessment: SupportedSaid

    “An awful lot of key players have left the island. Most voluntarily.”

    What happened: Sutskever presents the departure as his decision. This supports classifying it as voluntary on the public record. (Ilya Sutskever, via X, )

  32. Assessment: UnresolvedSaid

    “LLMs are not AGI, and (on their own) never will be; scaling alone was never going to be enough.”

  33. Assessment: UnresolvedSaid

    “LLMs are not AGI, and (on their own) never will be; scaling alone was never going to be enough.”

  34. Assessment: SupportedSaid

    “Nvidia dropped 6%, 20% over the last month”

    What happened: The table's Close column gives $125.83 on July 5, $107.27 on August 2 and $100.45 on August 5. These produce declines of 20.17% over the month and 6.36% for the day; the separate Adj Close column is not used. (Yahoo Finance, )

  35. Assessment: SupportedSaid

    “OpenAI tempered expectations for its next event, and said we wouldn’t see GPT-5 then.”

    What happened: The direct spokesperson statement supports the claimed expectation-setting. (TechCrunch, )

  36. Assessment: SupportedSaid

    “Over a quarter century later, handling outliers is still the Achilles’ Heel of neural networks.”

    What happened: The evaluation reports failures across several unfamiliar visual domains, supporting a recurring weakness in contemporary generative neural systems. It also finds improvements from in-context learning, while reporting that this approach remains vulnerable to distribution shifts. (arXiv; Zhang and colleagues, )

  37. Assessment: MixedSaid

    “Symbolic systems have always been good for outliers; neural networks have always struggled with them. For 30 years, this has been a constant.”

    What held: The gSCAN experiments report substantial failures when neural models must apply compositional rules to unfamiliar combinations. This supports the recurring neural-difficulty part of the claim, but does not establish symbolic superiority across the entire period. (arXiv; Ruis and colleagues, )

    What did not: In a comparison of seven models, the meta-trained neural approach combined systematicity and flexibility that the symbolic and ordinary neural comparators did not jointly achieve. This contradicts a stable categorical division between successful symbolic generalization and unsuccessful neural generalization. (Nature, )

  38. Assessment: UnresolvedSaid

    “An entire industry has been built - and will collapse - because people aren’t getting it.”

  39. Assessment: UnresolvedSaid

    “The AI world pretty much divides into two groups: those who understand why current machine learning techniques suck at outliers, and therefore struggle at things like driverless cars and high-level reasoning in unusual circumstances — and those who don’t.”

  40. Assessment: UnresolvedSaid

    “The bubble has begun to burst.”

  41. Assessment: UnresolvedSaid

    “I have long argued that Generative AI might be a dud; I just didn’t expect it to fade so fast.”

  42. Assessment: SupportedSaid

    “Another GenAI monetization scheme bites the dust.”

    What happened: The report establishes discontinuation of the celebrity-persona offering. It also contains direct confirmation from Meta, making this stronger than an unconfirmed report of a cancellation. (The Verge, )

  43. Assessment: UnresolvedSaid

    “Users have lost faith, clients have lost faith, VC’s have lost faith.”

  44. Assessment: UnresolvedSaid

    “PS Microsoft Bing completely flubbed, 4/4, “people going yuck towards Generative AI”.”

  45. Assessment: SupportedSaid

    “Consequently, any “reasoning” or “planning” in LLMs is hit or miss, viable if the particulars of a given situation are close enough to what is in the training set, but highly vulnerable if they are not.”

    What happened: Reasoning accuracy falls substantially and consistently on unfamiliar variants of the same tasks. Performance is still nontrivial, which fits 'hit or miss' rather than total failure. (Wu et al., MIT/Boston University (arXiv; NAACL 2024), )

  46. Assessment: UnresolvedSaid

    “People are starting to realize all of the above.”

  47. Assessment: SupportedSaid

    “Much as I admire the new pair of systems, they do have a serious shortcoming and one that is not unfamiliar. The systems both rely on a kind of cheat on the input: trained human coders translate all the Olympiad's input sentences into mathematical form.”

    What happened: The primary paper explicitly confirms expert manual formalization of AlphaProof's competition inputs. Its publication is later, but the reported event is the July 2024 evaluation. (Nature, )

  48. Assessment: UnresolvedSaid

    “That said, I am certain that the impending collapse won’t lead to the absolute death of AI. There is too much at stake.”

  49. Assessment: ContradictedSaid

    “I fully expect that the generative AI bubble will begin to burst within the next 12 months, for many reasons:”

    What happened: EY reports $49.2 billion of first-half generative AI VC investment versus $44.2 billion for all of 2024. It also reports nearly 25% fewer transactions than in the preceding half-year, a material sign of concentration that qualifies the expansion. (EY Ireland, )

  50. Assessment: UnresolvedSaid

    “There can be no path to AGI without neurosymbolic AI.”

  51. Assessment: UnresolvedSaid

    “Nobody has a moat”

  52. Assessment: SupportedSaid

    “Nonetheless, GDM's new work is powerful proof of concept (pun intended!). Neural networks and symbol systems can be profitably combined, contra Hinton and LeCun.”

    What happened: The developer's account connects the actual IMO proofs to a transformer that proposes Lean tactics, search over proof states and automatic formal verification. It explicitly identifies the described work as ending in July 2024. (Julian Schrittwieser, AlphaProof coauthor, )

  53. Assessment: UnresolvedSaid

    “The neural network approach known as generative AI — especially its poster chatbot ChatGPT – has captured the world’s imagination, but will soon flame out.”

  54. Assessment: SupportedSaid

    “Hallucinations and boneheaded errors of reasoning and what I like to call discomprehensions are, as far as I can tell, an inevitable byproduct of LLMs; certainly they have yet to disappear, despite many promises to the contrary.”

    What happened: In mid-2024, LLM products whose providers claimed they 'avoid' hallucinations still hallucinated on 17% to 34% or more of test queries. (Stanford HAI / RegLab, )

  55. Assessment: ContradictedSaid

    “The current approach has reached a plateau”

    What happened: User comparisons collected June 10–25 show newer frontier models outperforming preceding models on image-containing conversations. Preference measurements are imperfect, but this is independent evidence of improvement within the target quarter. (LMSYS Org, )

  56. Assessment: UnresolvedSaid

    “So for the most part, we’ve been stuck in a world in which all the major tech companies are building exactly the same thing (bigger and bigger LLMs based on more data), achieving almost exactly the same results (a passel of GPT-4 level models, hardly different from each other, all struggling with hallucinations and boneheaded errors), and hardly any investment in anything else.”

  57. Assessment: UnresolvedSaid

    “There is no killer app”

  58. Assessment: UnresolvedSaid

    “The biggest intrinsic failings of generative AI have to do with reliability, in a way that I believe can never be solved, given their inherent nature.”

  59. Assessment: UnresolvedSaid

    “Long-term adoption (vs mere experimentation) has been modest, there is no significantly better tech now than there was in January; GPT-5 is still a no show.”

  60. Assessment: SupportedSaid

    “Long-term adoption (vs mere experimentation) has been modest, there is no significantly better tech now than there was in January; GPT-5 is still a no show.”

    What happened: The official July release history records GPT-4o mini, not GPT-5. This supports the chronology alongside explicit reporting that GPT-5 remained forthcoming; this entry alone would not prove nonrelease. (OpenAI, )

  61. Assessment: UnresolvedSaid

    “Customers can easily switch to other providers, almost anytime they want, and for month there had been more and more alternatives, including Anthropic and Google, at more and more attractive prices, forcing OpenAI itself to cut prices just a few days ago.”

  62. Assessment: UnresolvedSaid

    “LLMs have just became exactly the commodity I predicted they would become, at the lowest possible price.”

  63. Assessment: UnresolvedSaid

    “Obviously, their only hope is to raise more cash, and they will certainly try.”

  64. Assessment: UnresolvedSaid

    “And leaving more and more code writing to generative AI, which grasps syntax but not meaning, as a new benchmark from Stephen Wolfram shows, is not the answer, either.”

  65. Assessment: SupportedSaid

    “As Ernie Davis and I pointed out in Rebooting AI, five years ago, part of the reason we are struggling with AI in complex AI systems is that we still lack adequate techniques for engineering complex systems. That hasn’t really changed.”

    What happened: The researchers explain that model scale and structure make established software testing and verification methods difficult to apply. They connect that methodological limitation to the difficulty of ensuring deployment robustness. (DeepMind, )

  66. Assessment: UnresolvedSaid

    “Neurosymbolic AI has long been an underdog; in the end I expect it to come from behind and be essential.”

  67. Assessment: UnresolvedSaid

    “The markers that our next President puts down—about how much liability and responsibility companies will have, and about how the government keeps up with a rapidly changing technology— will have lasting impact.”

  68. Assessment: UnresolvedSaid

    “Returns are starting to diminish.”

  69. Assessment: UnresolvedSaid

    “With the truth that LLMs can’t be trusted now becoming more widely known, the big AI leaders have switched their focus to long term promises that are impossible to verify and even more grandiose than “we can help your business in unprecedented ways” (which has turned out to be mostly untrue).”

  70. Assessment: SupportedSaid

    “As of today, I am more confident than ever that GPT-5 won’t land this year.”

    What happened: OpenAI introduced GPT-5 on August 7, 2025. A model first introduced in August 2025 was not released in 2024. (OpenAI, )

  71. Assessment: SupportedSaid

    “As of today, I am more confident than ever that GPT-5 won’t land this year.”

    What happened: OpenAI's initial GPT-5 announcement is dated August 7, 2025, and describes rollout beginning that day. This places its public arrival after the forecast's 2024 deadline. (OpenAI, )

  72. Assessment: UnresolvedSaid

    “In case you haven’t noticed, GPT-5 has come to seem to be a little like that. People keep on trying project its arrival, and its arrival keeps on slippin’ into the future.”

  73. Assessment: UnresolvedSaid

    “Nobody to my knowledge has kept systematic track of the predictions, but I took a quick and somewhat random look at X and had no trouble finding many predictions, going back to 2023, almost always optimistic.”

  74. Assessment: UnresolvedSaid

    “Others are bailing now, too. Or at least trying to subtly alter their positions, committing less to the unrealistic.”

  75. Assessment: SupportedSaid

    “Exhibit A: OpenAI’s CTO Mira Murati just publicly acknowledged what I long suspected: there is no mind blowing GPT-5 behind the scenes as of yet.”

    What happened: The contemporaneous report attributes a modest internal capability lead to OpenAI's CTO. This supports the ordinary qualitative reading, although it does not independently measure private models or identify one as GPT-5. (The Decoder, )

  76. Assessment: UnresolvedSaid

    “LLMs are not AGI, and (on their own) never will be; scaling alone was never going to be enough.”

  77. Assessment: SupportedSaid

    “In many ways, it is much weaker than what Altman and I talked about at the Senate last year.”

    What happened: Marcus proposed FDA-like review before deployment. The same transcript records Altman's proposed licensing agency, license revocation, safety standards, and independent audits; it establishes the comparison rather than proving Marcus's later assessment by repetition. (U.S. Senate / Government Publishing Office, )

  78. Assessment: UnresolvedSaid

    “Anyone who can afford that can easily fill out some paperwork and run a few tests, just like I can pay a few bucks to get a driver’s license. It’s the least they can do.”

  79. Assessment: ContradictedSaid

    “He doesn’t specify which actual restrictions in the proposal bill would “stifle AI models”.”

    What happened: Ng explicitly names safety assessments and shutdown capabilities. In the next paragraph, he focuses on the hazardous-capability designation and potential downstream liability, then connects that burden to inhibited model development, especially open source. (DeepLearning.AI, )

  80. Assessment: SupportedSaid

    “Two weeks later, it has already come out that the database that indexes the whole thing is in plain text (except on systems that are explicitly set to encrypt everything). That’s bananas. Keystone Kops level security.”

    What happened: The preserved June documentation describes the unencrypted database and demonstrates extracting and searching its screenshot-derived text. Its June 6 example falls within the target period; June 8 is the documentation's stated FAQ update date. (Alexander Hagenah, )

  81. Assessment: UnresolvedSaid

    “Every company that would be subject to the stronger set of regulations is valued in the billions.”

  82. Assessment: UnresolvedSaid

    “It can do some things better, some worse, very few reliably.”

  83. Assessment: UnresolvedSaid

    “The double Y-axis makes no sense, and presupposes its own conclusion.”

  84. Assessment: MixedSaid

    “The graph assumes that all continued progress will be same — ignoring qualitatively unsolved problems (hallucinations, planning, reasoning etc), the fact that synthetic data may not be as useful as natural data, limits on then-possible energy distribution and compute, etc.”

    What held: Supports the trend-continuation component, not the alleged omission of obstacles. (Leopold Aschenbrenner, Situational Awareness, )

    What did not: The surrounding discussion explicitly allows data constraints to halt progress without new methods. (Leopold Aschenbrenner, Situational Awareness, )

  85. Assessment: SupportedSaid

    “For one thing, the bad press about Sam Altman and OpenAI, who once seemingly could do no wrong, just keeps coming.”

    What happened: This critical newsletter discusses the voice dispute, safety-team departures, and restrictive employee agreements. The event being assessed is publication of critical coverage; available_at conservatively uses the displayed modification date. (The Guardian, )

  86. Assessment: UnresolvedSaid

    “In 2019 I pointed out through a series of examples on Twitter with GPT-2 that LLMs were subject to essentially the same critique: greedy with respect to data, uninterpretable, unreliable as reasoners, subject to hallucinations, etc, that they lacked world models (“they don't develop robust representations of *how events unfold over time*), and that they would be inadequate on their own.”

  87. Assessment: UnresolvedSaid

    “Nowadays we both (unlike many other people) stress the absolutely essential nature of common sense, physical reasoning and world models, and the failure of current architectures to handle those well.”

  88. Assessment: UnresolvedSaid

    “Worse, we are no closer to a solution to the alignment problem now than we were then.”

  89. Assessment: SupportedSaid

    “For all the daily claims of “exponential progress”, and for all the tens of billions that have been invested since, reliability is still a dream, and of course toxicity and hallucinations are still with us.”

    What happened: The May evaluation documents invented constraints and false claims of task completion, directly supporting continuing hallucinations and unreliable autonomous execution. The report also records successful shorter tasks and strong scientific-question performance, so the failures do not imply universal incompetence. (UK AI Safety Institute, )

  90. Assessment: SupportedSaid

    “The ridicule is of me; the failure is of the lords of deep learning to resolve what ails their AI.”

    What happened: The leading lab says its flagship model, released within the period, still hallucinates and is not fully reliable. (OpenAI, )

  91. Assessment: UnresolvedSaid

    “But OpenAI has been and continues to be a California-registered 501(3)(c) nonprofit, pledged not to profits, but to humanity – and still getting tax-exempt status on the basis of their promise to deploy AI safely:”

  92. Assessment: UnresolvedSaid

    “The 3.5 API (geared towards programmers as a backend tool) was available beforehand, but that’s not of course the consumer-directed product with gimmicks like word-by-word typing to give a false impression of humanness that ultimately went viral.”

  93. Assessment: UnresolvedSaid

    “Fundamentally, the essay attacks a strawman, viz. that the firing of Altman was somehow precipitated by an immediate safety concern), thereby diverting from the board’s actual, stated concern (candor).”

  94. Assessment: UnresolvedSaid

    “And oops, Grok’s basic understanding of time is shaky, too:”

  95. Assessment: UnresolvedSaid

    “Musk is just building bigger and bigger LLMs, and Meta is mostly (despite LeCun’s reservations) mostly doing the same.”

  96. Assessment: UnresolvedSaid

    “Regulatory capture is the default, as Karla Ortiz recently noted,::”

  97. Assessment: SupportedSaid

    “OpenAI called itself open, and traded on the notion of being open, but even as early as May 2016 knew that the name was misleading.”

    What happened: The report describes Amodei telling Altman and Brockman that people expected OpenAI to release its source code. Altman acknowledged that this exceeded its plans and discouraged correcting the impression; this is firsthand reporting, not an internal email. (The New Yorker, )

  98. Assessment: UnresolvedSaid

    “OpenAI promised to devote 20% of its efforts to AI safety, but never delivered, according to a recent report by Jeremy Kahn at Fortune.”

  99. Assessment: SupportedSaid

    “Altman once (in 2016) promised that outsiders would play an important role in the company’s governance; that key promise has not been kept.”

    What happened: The adjacent line 7a explanation assigns director elections to these members. The filing therefore describes an internally selected board, not an electorate drawn from the public. (OpenAI Inc., copy hosted by Gwern, )

  100. Assessment: UnresolvedSaid

    “But lately, he and they have made a lot of mistakes, and broken a lot of promises.”