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

Claims checked against evidence by Ed Zitron, page 10 of 13

Deadlines are judged as of 2026-10-29. About Ed Zitron and the sources covered.

Claims checked against evidence by Ed Zitron (1230)

Each of these claims was checked against dated evidence.

Page 10 of 13: claims 901 to 1000 of 1230, ordered by the date first said, newest first. To find a claim by its words, use search.

  1. Assessment: UnresolvedSaid

    “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.”

  2. Assessment: UnresolvedSaid

    “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.”

  3. Assessment: UnresolvedSaid

    “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.”

  4. Assessment: UnresolvedSaid

    “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.”

  5. Assessment: SupportedSaid

    “OpenAI burned more than $5 billion last year.”

    What happened: The reported 2024 net loss exceeds the stated threshold. This supports the passage's inclusive loss interpretation, not a claim about cash consumption. (Ars Technica, )

  6. Assessment: UnresolvedSaid

    “In short, most of the coverage you read on artificial intelligence is led by companies that benefit financially from you thinking artificial intelligence is important and by default all of this coverage mentions OpenAI or ChatGPT.”

  7. Assessment: UnresolvedSaid

    “Furthermore, nothing about this product moves OpenAI toward profitability. In fact, I think they're doing the opposite.”

  8. Assessment: UnresolvedSaid

    “Anthropic is currently raising $2 billion at a $60 billion valuation primarily based off of this trumped-up marketing nonsense.”

  9. Assessment: UnresolvedSaid

    “To be clear, OpenAI burned approximately $5 billion on compute alone.”

  10. Assessment: MixedSaid

    “The one "big thing" that they've been able to do is to use "reasoning" to make the Large Language Models "think" (they do not have consciousness, they are not "thinking," this just means using more tokens to answer a particular question and having multiple models check the work), which mostly results in them being a bit more accurate when generating an answer, but at the expense of speed and cost.”

    What held: The developer acknowledges cost and speed limitations in the o1 discussion. This supports that part of the claim, but does not establish a universal tradeoff or predominantly small accuracy gains. (OpenAI, )

    What did not: Appendix A reports AIME pass@1 scores of 44.6 for o1-preview and 9.3 for GPT-4o, showing substantial gains on a demanding reasoning task. These selected evaluations challenge the modest-gain characterization, but cannot determine gains across all ordinary usage. (OpenAI, )

  11. Assessment: UnresolvedSaid

    “The tech industry — and part of our economy — is accelerating at speed into a brick wall, driven by people like Sam Altman, Dario Amodei, Marc Benioff, and Larry Ellison, all men that are incentivized to have you value their companies based on something other than what their businesses actually sell.”

  12. Assessment: SupportedSaid

    “User numbers alone tell you nothing about the sustainability or profitability of a business, or how those people use the product.”

    What happened: The disclosed figure is an aggregate weekly activity count. The inference supporting the claim is limited: this count does not encode profit, retention, purposes, or the distribution of activity across days. (PYMNTS, )

  13. Assessment: UnresolvedSaid

    “Deep Research uses OpenAI's o3 model which can cost as much as $1,000 a query, and while I imagine these prompts aren't that expensive, they are still significantly more so than a regular query from ChatGPT.”

  14. Assessment: UnresolvedSaid

    “There is no "artificial intelligence" part of Microsoft's revenue or earnings. This is literally Microsoft taking anything with "AI" on it and saying "we made money!"”

  15. Assessment: UnresolvedSaid

    “And when this all falls apart — and I believe it will — there will be a very public reckoning for the tech industry.”

  16. Assessment: UnresolvedSaid

    “The damage will be tens of thousands of people fired, long-term environmental and infrastructural chaos, and a profound depression in Silicon Valley that I believe will dwarf the dot-com bust.”

  17. Assessment: UnresolvedSaid

    “There isn't a single god damn startup in the history of anything — other than perhaps Facebook — that has had this level of coverage at such an early stage.”

  18. Assessment: SupportedSaid

    “There were multiple other companies doing exactly what GPT-3 did months before ChatGPT launched.”

    What happened: The announcement offers Jurassic-1 through an open-beta API and web environment and describes text generation, question answering, and classification. It establishes one other company's comparable functional offering well before the cutoff. (AI21 Labs, )

  19. Assessment: UnresolvedSaid

    “It only caught fire because the media insisted it did so.”

  20. Assessment: SupportedSaid

    “DeepSeek's models don't require massive new data centers (they run on the GPUs currently used to run services like ChatGPT, and can even work on more austere hardware), nor do they require an endless supply of bigger, faster NVIDIA GPUs every year to progress.”

    What happened: The report identifies the hardware actually used and describes training-efficiency improvements and deployment on H800s. It supports the existing-hardware route, although it is a company report and does not document the construction history of the facility. (DeepSeek-AI, )

  21. Assessment: UnresolvedSaid

    “Right now, I do not believe that there are companies that are stymied by the pricing that OpenAI and their ilk offer, nor do I think there are many companies or use cases that don’t exist because Large Language Models are too expensive.”

  22. Assessment: UnresolvedSaid

    “He ended with “look forward to bringing you all AGI and beyond” — something which, I add, has always been close on the horizon in Altman’s world, although curiously has yet to materialize, or even come close to materializing.”

  23. Assessment: UnresolvedSaid

    “OpenAI only makes 27% of its revenue from selling access to its models — around a billion dollars in annual recurring revenue — with the rest ($2.7 billion or so) coming from subscriptions to ChatGPT.”

  24. Assessment: UnresolvedSaid

    “There really isn’t anything special about any of these companies anymore — they have no moat, their infrastructural advantage is moot, and their hordes of talent irrelevant.”

  25. Assessment: UnresolvedSaid

    “We also know that OpenAI’s training and inference costs in 2024 were around $7 billion, meaning that either refining current models or building new ones is quite costly.”

  26. Assessment: UnresolvedSaid

    “Once these models are hosted elsewhere, and once DeepSeek's methods (which I'll get to shortly) are recreated (which won't take long), I believe we'll see that these prices are indicative of how cheap these models are to run.”

  27. Assessment: UnresolvedSaid

    “OpenAI and Anthropic no longer have moats to raise capital with.”

  28. Assessment: UnresolvedSaid

    “This isn’t a particularly exciting pitch to investors or the public markets, because there’s no product, innovation or business model to point to, and if they’d actually try and productize it and turn it into a business, it’s quite obvious at this point that there really isn’t a multi-trillion dollar industry for generative AI.”

  29. Assessment: SupportedSaid

    “One thing we do know is that OpenAI and Anthropic will now have to either drop the price of accessing their models, and potentially even the cost of their subscriptions.”

    What happened: The announcement says the reduction is in effect and applies to the same o3 model. This establishes OpenAI's part of the prediction. (OpenAI, )

  30. Assessment: UnresolvedSaid

    “As a result, I don’t really see anything changing, beyond the eventual collapse of the API market for companies like Anthropic and OpenAI.”

  31. Assessment: UnresolvedSaid

    “After all, OpenAI loses money on every transaction — even its $200-a-month "ChatGPT Pro" subscription.”

  32. Assessment: UnresolvedSaid

    “While NVIDIA will find other ways to make money — Jensen Huang always does — it's going to be a hard sell for any hyperscaler to justify spending billions more on GPUs to markets that now know that near-identical models can be built for a fraction of the cost with older hardware.”

  33. Assessment: UnresolvedSaid

    “As I've written about many, many, many times, the Large Language Models run by companies like OpenAI, Anthropic, Google and Meta are unprofitable and unsustainable, and the transformer-based architecture they run on has peaked.”

  34. Assessment: UnresolvedSaid

    “As I've written about many, many, many times, the Large Language Models run by companies like OpenAI, Anthropic, Google and Meta are unprofitable and unsustainable, and the transformer-based architecture they run on has peaked.”

  35. Assessment: UnresolvedSaid

    “In any case, the massive expense of running generative models hasn’t been the limiter on their deployment or success — you can blame that on the fact that they, as a piece of technology, are neither artificial intelligence nor capable of providing the kind of meaningful outcomes that would make them the next Smartphone.”

  36. Assessment: UnresolvedSaid

    “And, as I noted at the time, it was not particularly reliable, failing to accurately count the number of times the letter ‘r’ appeared in the word “strawberry.””

  37. Assessment: UnresolvedSaid

    ““AGI” isn’t coming.”

  38. Assessment: MixedSaid

    “The launch of its "Operator" "agent" was a joke — a barely-functional product that is allegedly meant to control your computer and take distinct actions, but doesn't seem to work.”

    What held: The tester reports five failures involving web research and online tools. These show real launch limitations, but the small, relatively demanding task set is not a representative consumer success-rate estimate. (Zengyi Qin / Hugging Face Community, )

    What did not: Newton describes successful browser research producing walking-tour links and a completed lesson-plan task. His same review documents substantial shopping friction, so these successes limit the broad dismissal without establishing reliable autonomy. (Platformer / Casey Newton, )

  39. Assessment: UnresolvedSaid

    “I do not believe that the companies making foundation models (such as OpenAI and Anthropic) have been incentivized to do more with less, and because their chummy relationships with hyperscalers were focused almost entirely on "make the biggest, most hugest models possible, using the biggest, most hugest chips," and because the absence of profitability didn’t stop them from raising more money, efficiency was never a major problem for them.”

  40. Assessment: ContradictedSaid

    “Large Language Models (and reasoning models) are niche.”

    What happened: The November survey estimated broad public participation, with search, explanation and writing leading uses. Material qualifications in this same source are possible online-panel selection bias and light usage: its conservative weekly-use estimate was about 29%, and most adults did not use LLMs in a typical week. (Rethink Priorities, )

  41. Assessment: UnresolvedSaid

    “And if OpenAI cuts its prices to compete with DeepSeek, its losses will only deepen.”

  42. Assessment: UnresolvedSaid

    “After all, OpenAI lost $5 billion (after $3.7 billion in revenue, too!), and Anthropic just under $3 billion in 2024.”

  43. Assessment: UnresolvedSaid

    “And this, in turn, will make any investor think twice about writing the company a blank check — which, as I’ve said ad nauseum, is potentially fatal, as OpenAI needs to continually raise more money than any startup ever has in history, and it has no path to breaking even.”

  44. Assessment: SupportedSaid

    “Whether or not someone chooses to pay DeepSeek is largely irrelevant — someone else will take what it’s created and build their own, or people will start running their own DeepSeek instances renting GPUs from one of the various cloud computing firms.”

    What happened: Skywork records the release of its final OR1 models on May 13 and explicitly identifies DeepSeek's distilled models as their starting points. This is an actual third-party derivative release after the forecast. (Skywork AI, )

  45. Assessment: MixedSaid

    “They're running out of training data, and the actual capabilities of these models were peaking as far back as March 2024.”

    What held: The estimate supports an approaching constraint on usable human-generated public text under continuing scaling trends. It does not show that data was already exhausted, and the discussion identifies other data sources and ways progress could continue. (Epoch AI, )

    What did not: Using its baseline testing framework, ARC Prize reports public-evaluation scores of 21.2% for o1-preview and 9% for GPT-4o. This is post-March capability progress, although the evaluator also reports substantially greater inference time. (ARC Prize, )

  46. Assessment: ContradictedSaid

    “The current models developed by both the hyperscalers (Gemini, Llama, et. al) and multi-billion-dollar "startups" like OpenAI and Anthropic are horribly inefficient, I had just made the mistake of assuming that they'd actually tried to make them more efficient.”

    What happened: Meta describes concrete changes to parallelization, reliability, storage and training infrastructure, alongside inference optimizations. This is substantive efficiency engineering, although the improvement magnitude is company-reported. (Meta, )

  47. Assessment: UnresolvedSaid

    “Suggesting one is "taking detailed notes on bloggers" is an attempt to intimidate people that are seriously evaluating the fact that OpenAI burns $5 billion a year and has no path to profitability.”

  48. Assessment: UnresolvedSaid

    “I am 100% sure that these chatbots will return, because it's fairly obvious that Meta intends to fill your feeds with content either entirely generated or summarized by generative AI, be it with fake profiles or content itself.”

  49. Assessment: UnresolvedSaid

    “Meta will push as much AI slop as it wants, both created by its generative models and their users, and massively ramp up content that riles up users with little regard for the consequences.”

  50. Assessment: UnresolvedSaid

    “AI-generated slop already dominates the platform, and as discussed earlier, the quality of the platform has fallen into utter disrepair, mostly because Meta's only concern is keeping you on the platform to show you ads or content it’s been paid to show you, even if the reason you're seeing it is because you can't find the stuff you actually want to find.”

  51. Assessment: UnresolvedSaid

    “There will be measurable damage to the stock market, but more importantly tens of thousands of people will lose their jobs and a depression will begin in the tech industry.”

  52. Assessment: UnresolvedSaid

    “There will be measurable damage to the stock market, but more importantly tens of thousands of people will lose their jobs and a depression will begin in the tech industry.”

  53. Assessment: UnresolvedSaid

    “There will be measurable damage to the stock market, but more importantly tens of thousands of people will lose their jobs and a depression will begin in the tech industry.”

  54. Assessment: UnresolvedSaid

    “bizarre AI slop is dominating feeds with Mark Zuckerberg promising that there’s more to come”

  55. Assessment: UnresolvedSaid

    “AI-generated images and machine-generated text is everywhere, and it’s impossible to avoid, as there is no reliable way to determine the provenance of a piece of content — with one exception, namely the considered scrutiny of a human.”

  56. Assessment: SupportedSaid

    “Be the person who tells people that Sam Altman burns $5 billion a year on unsustainable software that destroys the environment and is built upon the large-scale larceny of creative works because he's desperate for power.”

    What happened: The filed memorandum quotes an internal admission connecting pirated material to GPT-3 training. This is documentary evidence presented by plaintiffs, not a judicial determination that the training infringed copyright. (Class plaintiffs in In re OpenAI Copyright Infringement Litigation, )

  57. Assessment: UnresolvedSaid

    “Generative AI is incredibly unprofitable.”

  58. Assessment: ContradictedSaid

    “The products aren't coming.”

    What happened: The disclosure dates general availability to May 2025 and reports continued growth in weekly users and business subscriptions in February 2026. Its reported commercial scale supplies evidence that adoption extended beyond an experimental launch. (Anthropic, )

  59. Assessment: ContradictedSaid

    “I also want to be clear that none of these companies ever had a plan.”

    What happened: Microsoft specified concrete generative AI functions inside Word and other work applications. That is a product and deployment strategy beyond purchasing GPUs, regardless of whether the promised benefits were achieved. (Microsoft, )

  60. Assessment: SupportedSaid

    “OpenAI currently spends $2.35 to make $1, and Microsoft CFO Amy Hood said that OpenAI would cut into Microsoft's profits this October, losing it a remarkable $1.5 billion, "mainly because of an expected loss from OpenAI" according to CNBC.”

    What happened: These estimates imply $8.7 billion of expenses and a ratio rounding to $2.35. CNBC also reports exclusions, including equity-based compensation, so this supports the cited estimate rather than comprehensive accounting expenses. (CNBC, )

  61. Assessment: UnresolvedSaid

    “"Orion," OpenAI's next model, will underwhelm, as will its competitors' models, and at some point somebody is going to blink in one of the hyperscalers, and the AI era will be over.”

  62. Assessment: UnresolvedSaid

    “If we're truly at the diminishing returns stage of transformer-based models, it will be extremely difficult to justify buying further iterations of NVIDIA GPUs past Blackwell.”

  63. Assessment: UnresolvedSaid

    “Once the AI bubble pops, there are no other hyper-growth markets left, which will in turn lead to a bloodbath in big tech stocks as they realize that they’re out of big ideas to convince the street that they’re going to grow forever.”

  64. Assessment: UnresolvedSaid

    “The constant refrain I hear from VCs and AI fantasists is that "chips will bring down the cost of inference," yet I don't see any proof of that happening, nor do I think it'll happen quickly enough for these companies to turn things around.”

  65. Assessment: UnresolvedSaid

    “Remember, the capital expenditures on generative AI and the associated infrastructure have gone over $200 billion in the last year.”

  66. Assessment: UnresolvedSaid

    “And before then, you’re going to get a lot of desperate stories about how “AI gains can be found outside of training new models” to try and keep the party going, despite reality flicking the lights on and off and threatening to call the police.”

  67. Assessment: UnresolvedSaid

    “I believe all of this is going nowhere, and that at some point Google, Microsoft, or Meta is going to blink and pull back on their capital expenditures.”

  68. Assessment: UnresolvedSaid

    “There is no iPhone moment coming, I'm afraid.”

  69. Assessment: ContradictedSaid

    “The entire tech industry has become oriented around a dead-end technology that requires burning billions of dollars to provide inessential products that cost them more money to serve than anybody would ever pay.”

    What happened: The preceding sentence identifies 2024 revenue of $4 billion and inference compute and hosting costs of $2.4 billion. This reported positive serving margin supplies a counterexample to the categorical assertion, without establishing company-wide profitability. (Epoch AI, )

  70. Assessment: UnresolvedSaid

    “Instead, big tech has found itself peddling increasingly-more-expensive iterations of near-identical Large Language Models — a direct result of them all having to use the same training data, which it’s now running out of.”

  71. Assessment: UnresolvedSaid

    “Putting that aside, OpenAI is also a terrible business that has to burn $5 billion to make $3.4 billion, with no proof that it’s capable of bringing down costs.”

  72. Assessment: UnresolvedSaid

    “Even if OpenAI listens to its better angels, the reality still stands: ads won’t dam the rising tide of red ink that promises to eventually drown the company.”

  73. Assessment: UnresolvedSaid

    “If NVIDIA doesn’t solve its cooling problem — and solve it well — its customers will undoubtedly encounter thermal throttling, where the chip reduces speed in order to avoid causing permanent damage.”

  74. Assessment: UnresolvedSaid

    “The revenue isn't coming.”

  75. Assessment: UnresolvedSaid

    “Throughout these pieces I have repeatedly made the point that — separate to any lack of a core value proposition, training data drought, or unsustainable economics — generative AI is a dead end due to the limitations of probabilistic models that hallucinate, where they authoritatively state things that aren't true.”

  76. Assessment: ContradictedSaid

    “Generative AI's products have effectively been trapped in amber for over a year.”

    What happened: Developers could use the API to have Claude inspect screens, move a cursor, click and type. This materially extends possible workflows, although Anthropic describes the release as experimental and error-prone. (Anthropic, )

  77. Assessment: UnresolvedSaid

    “OpenAI, the biggest player in the industry, is on course to lose more than $5 billion this year, with competitor Anthropic (which also makes its own transformer-based model, Claude) on course to lose more than $2.7 billion this year.”

  78. Assessment: MixedSaid

    “The hallucination problem is one that is nowhere closer to being solved — and, at least with the current technology — may never go away, and it makes it a non-starter for a great many business tasks, where you need a high level of reliability.”

    What held: Testing on May 23–27 found frequent hallucinations in a specialized legal research product. This supports the barrier to unverified, high-reliability legal work under the stated interpretation, but does not establish the number of business tasks excluded. (arXiv, )

    What did not: Table 2 reports SimpleQA hallucination rates of 0.61 for GPT-4o and 0.44 for o1-preview, with improvements on the other listed tests. The same paragraph reports contrary anecdotal feedback and cautions against generalizing beyond these evaluations. (OpenAI, )

  79. Assessment: ContradictedSaid

    “The models aren't going to get better.”

    What happened: The report identifies MAI-Thinking-1's base-model training on 8K GB200 GPUs and reports 84.2% GPQA Diamond pass@1, exceeding the pre-post results in e3. It uses the same 198-question Diamond subset; its large output budget and grading procedure limit exact comparability. (Microsoft AI, )

  80. Assessment: UnresolvedSaid

    “At some point, these ugly messes will collapse as it becomes clear that their entire infrastructure is written upon increasingly-automated levels of crap, rife with hallucinations and devoid of any human touch.”

  81. Assessment: UnresolvedSaid

    “Google is exactly the monster that Sundar Pichai and Prabhakar Raghavan wanted it to be — a lumbering private equity vehicle that uses its crooked money machine to demolish smaller players, except there are no more hyper-growth markets left for it to throw billions at, leaving it with Generative AI, a technology that lacks mass-market utility and burns cash with every prompt.”

  82. Assessment: SupportedSaid

    “It isn’t. You saw a prototype and heard a speech.”

    What happened: Explicitly identifies the unveiled Cybercab as a prototype. The article's headline uses arrival language, but its description supports Zitron's distinction. (The Verge, )

  83. Assessment: UnresolvedSaid

    “Generative AI's destructive, larcenous growth exists in large part because people buy Sam Altman's shit, and because they believe that he's somebody special, a genius operator that can do the impossible, which in turn helps them platform his half-truths and outright lies.”

  84. Assessment: UnresolvedSaid

    “Sam Altman's rise to power came, in part, from members of the media propping him up as a genius”

  85. Assessment: UnresolvedSaid

    “Yet the media still takes the idea that he’d launch a robotaxi network seriously, even though Musk has been lying about this shit since 2019.”

  86. Assessment: MixedSaid

    “far too many simply ran exactly what Musk said and acted as if he’d proven that these were actual robots walking around and doing things on their own accord, as opposed to what was blatantly obvious: that they were controlled remotely by human operators.”

    What held: Reports a bartender robot's acknowledgment of assistance, alongside accounts of teleoperated guest interactions. (Ars Technica, )

    What did not: Contradicts including walking in a blanket account of remote control. The reported operation combined autonomous locomotion with human-assisted interactions. (Ars Technica, )

  87. Assessment: UnresolvedSaid

    “Even a $2 price increase (the first expected price hike for ChatGPT Plus, as the company reportedly works towards charging $44 per month) and similar price hikes on the Teams and Enterprise plans won’t do much to stem the flow of red ink on its balance sheet.”

  88. Assessment: ContradictedSaid

    “That product is extremely commoditized. The free version of ChatGPT is effectively identical to the free version of Anthropic's Claude, Meta's AI assistant, Microsoft's Copilot, and even Twitter's "Grok."”

    What happened: The launch announcement places access in premium subscription tiers during the target quarter. The explicit premium-only history in e2 corroborates that this was not an ordinary free consumer offering. (xAI, )

  89. Assessment: UnresolvedSaid

    “At the current cost of revenue, it will cost OpenAI more than $27 billion to hit that revenue target.”

  90. Assessment: UnresolvedSaid

    “Unlike Facebook and Google, ChatGPT’s most frequent free users actually become less valuable over time, and become a burden on a system that already burns money.”

  91. Assessment: UnresolvedSaid

    “Yet, once you get past these problems, you run head-first into the largest one: that generative AI is deeply unprofitable to run.”

  92. Assessment: UnresolvedSaid

    “As I've said before, OpenAI is unprofitable, unsustainable and untenable in its current form”

  93. Assessment: UnresolvedSaid

    “Because access to its APIs isn’t a particularly big business, OpenAI’s hopes of hitting its revenue goals is almost entirely contingent on ChatGPT Plus continuing to grow.”

  94. Assessment: SupportedSaid

    “All of this is happening at a time when an astronomical amount of talent is leaving the company — the talent that OpenAI desperately needs to build products that people will actually pay for.”

    What happened: The simultaneous departure announcements cover the chief technology officer, chief research officer and a research vice president. Those roles support the ordinary reading of a substantial concentration of relevant leadership departures. (The Register, )

  95. Assessment: ContradictedSaid

    “To hit a revenue target of $11.6 billion in 2025, OpenAI would need to increase revenue from ChatGPT customers by 310%.”

    What happened: The derived counterexample reaches the target with a 213.5% increase in the stipulated ChatGPT baseline, assuming the stated mix and a full year at the resulting rate. This is a calculation from reported premises, not a measured revenue outcome. (CNBC, )

  96. Assessment: SupportedSaid

    “To be abundantly clear, as it stands, OpenAI currently spends $2.35 to make $1.”

    What happened: The reported estimates imply $8.7 billion of expenses on their loss basis and an expense-to-revenue ratio of 2.35135. This supports the arithmetic reading, not a claim about realized expenditure. (CNBC, )

  97. Assessment: UnresolvedSaid

    “Also, at some point, OpenAI will have to work out a way to go public, because otherwise there is absolutely no reason to invest in this company, unless you are doing so with the belief that you will be able to offload your shares in a future secondary sale.”

  98. Assessment: SupportedSaid

    “OpenAI's products are increasingly-commoditized, with Google, Meta, Amazon and even Microsoft building generative AI models to compete.”

    What happened: The retrospective comparison identifies capability convergence by Llama 3.1, released during the target quarter. It supports increasing model substitutability while also documenting historical lags behind closed models. (Epoch AI, )

  99. Assessment: UnresolvedSaid

    “Cutting prices, therefore, only serves to slash whatever meager margins exist on those customers, or to turn those potentially-profitable customers into a loss center.”

  100. Assessment: UnresolvedSaid

    “OpenAI lives and dies on the revenue gained from ChatGPT, a product that hasn't meaningfully changed since it launched beyond adding new models that do, for most users, exactly the same thing.”