How accurate have Ed Zitron's AI skeptic predictions been?
![Feb 2024: "I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be."
Wrong4
March 2024: "Have We Reached Peak AI?"; another prediction that hallucinations mean that AI progress is limited to then-current levels
Wrong
April 2024: "As I previously warned, artificial intelligence companies are running out of data ..."; another prediction that models can't improve because there's no more data
Wrong
June 2024: OpenAI growth is stalling (with the implication it will continue to stall), which will lead to some kind of collapse of OpenAI
Wrong (it could be the case that OpenAI will collapse but, if so, it won't be due to any kind of growth stall from 2024)
July 2024: "Generative AI, as I said back in March, is peaking, if it hasn't already peaked. It cannot do much more than it is currently doing, other than doing more of it faster with some new inputs"
Wrong
July 2024: "Generative AI models aren’t getting more energy-efficient, nor are they getting more “powerful” in a way that would increase their functionality"
Wrong5
August 2024: "generative AI is a dead-end technology that has peaked”
Wrong
August 2024: re-iteration that the AI bubble has 3 quarters to prove itself (from March 2024) or there will be a collapse
Wrong6
September 2024: "o1 shows that OpenAI is both desperate and out of ideas", with a re-iteration of the idea that models can't improve due to lack of data
Wrong
Oct 2024: OpenAI's forecast of $3.7B revenue in 2024 and $11.6B in 2025 and $100B in 2029 are absurd, "a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud"
Wrong (2025 goal exceeded, 2029 TBD but not an egregious financial crime level of implausible)
Oct 2024: "[OpenAI revenue] growth is already slowing, and will slow dramatically as we enter the new year"
Wrong
Dec 2024: "I also warned you in March that generative AI had already peaked.”
Wrong (also, bizarrely, implying no progress since March 2024)
Jan 2025: "I believe we’re at peak AI"
Wrong
Jan 2025: "DeepSeek has commoditized the [LLM]"
Wrong
February 2025: Anthropic making $34.5B in revenue 2027 is "is laughable on many levels, chief of which is that OpenAI, which made around twice as much revenue as Anthropic did in 2024, barely made a billion dollars from API calls in the same year."
Wrong
February 2025: "Sundar Pichai wants Gemini to be 'used by 500 million people before the end of 2025, 'a number so unrealistic that someone at Google should have been fired, and that someone is Sundar Pichai."
Wrong (Gemini hit 750 M users)
February 2025: "Sam Altman deputizing Orion from GPT-5 to GPT-4.5 suggests that OpenAI has hit a wall with making its next model, requiring him to lower expectations";
Wrong (GPT-5 was a substantial improvement over GPT-4.5)
February 2025: "I will keep writing this stuff until I’m proven wrong."
Wrong (Zitron continues to write despite repeatedly being proven wrong)](https://files.mastodon.social/media_attachments/files/117/197/048/931/769/488/original/005310f2586b3d6d.webp)
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@danluu now do the ai company announcements over the same time
@danluu Excellent researched piece, thanks for writing it.
Could you add timestamps to your articles? When seeing phrases like "this year" it's harder to gauge which time period you're discussing.
(Unless it's written somewhere already and I've missed it?)
@danluu I wanted to believe everything he was saying but eventually I realized he's just another kind of grifter
@danluu I have several issues with this: 1) I think there is a corollary here to “the market can remain irrational longer than you can remain solvent”, the numbers were unhinged 2 years ago and they’re even more unhinged now, so even if specific predictions are wrong he could still be correct about the long term
@danluu 2) This assumes that the big player’s aren’t lying about usage numbers, I refuse to use AI and I’ve lost track of the number of times Google has pushed an on by default setting I have to disable, I’d bet good money that while that switch is on they’re counting me as a user,
@danluu 3) How are we defining model improvement? because from what I’ve seen in the literature the metrics are all easily gamed, OpenAI admitted (last year?) that they had basically trained the model on the answer key to a math benchmark so did it really improve at all?
@danluu 4) The fact that AI companies are buying up defunct companies to train on emails and chat histories, and Google is known to be training on private documents in drive is a pretty clear indicator to me that they’re run out of public data to mulch, I also haven’t heard them talk about how they’re using LLMs to generate training data in a while so I assume that went as badly as I thought it would.
