Comment by awakeasleep
3 hours ago
Read a little more of what he's written before you praise him, so you don't end up looking as dumb as I did.
Ed may be right about some of his claims, but he is 100% a crank, and he makes so many incoherent claims I'd say that if he's right, it's in the nature of a broken clock.
If you want to dismiss him for being hyperbolic or under estimating the usefulness of AI go for it.
If you are making the case that he is full of shit, please provide some actual evidence of his main thesis that AI companies are not going about this in any sustainable way
> his main thesis that AI companies are not going about this in any sustainable way
The point isn't that his thesis is fucked, just that his analysis tends to be free with details in a way that shouldn't inspire confidence, e.g. mixing up EBIT and EBITDA.
Someone elsewhere in this thread referenced this guy [1]. His takes properly summarise the lack of care Zitron appears to display for getting detailed arguments right.
If you're deeply familiar with financial jargon, I think he's fine. But if you're not, it's easy to get whisked into woo-woo nonsense that's falsely precise due to mis-using (and in some cases, very clearly mis-understanding) core financial and economic concepts.
[1] https://bsky.app/profile/peark.es/post/3mmhtcib3622i
Ed's not a crank, but you need to pay close attention to the topic of his proclamations to separate the wheat from the chaff.
He's right about some things -- off the top of my head: <ul>
<li>OAI's perpetual fundraising, due to their losses</li>
<li>Coreweave</li>
<li>Circular financing</li>
<li>Revenue/capex imbalance</li> </ul>
-- all forensic economics analyses.
He's often wrong when on the topic of capabilities and adoption -- he mistakes a snapshot for a trajectory, and treats current limitations as permanent:
<ul> <li>Hallucination/unreliability an unsolvable problem</li>
<li>OpenAI failing</li>
<li>AI capabilities have plateaued / models will stop getting better</li>
<li>Saying Microsoft's cancelled leases meant the bubble was popping</li>
<li>Agents a marketing fad</li>
<li>Gross miscalculation of OAI 2025 revenue</li>
<li>Lack of adoption</li>
<li>AI not getting more efficient (compared to 10-40x reduction in inference costs YoY)</li>
<li>Repeating "95% of pilots fail" but ignoring massive bottoms-up adoption</li> </ul>
Christensen got this right when he had the insight to judge a technology by its rate of improvement relative to what a market needs, not by whether it's good enough today.
Put Zitron back at the early days of the integrated circuit and imagine what he would have written about the technology.
Some open predictions:
<ul> <li>Bubble is going to burst -- I tend to agree with the thesis that "there is some marginal capacity being planned/built today that will never pay back its capex"</li>
<li>Losses mean there's no viable business here -- the recent moves by all of the players to some form of usage based pricing show there's price discovery occurring. I don't know of anyone who is stopping using LLMs because of the pricing changes...it's just changing their behavior.</li> </ul>
Can you provide evidence of where he's been wrong?
An example of him in July 2024: https://www.wheresyoured.at/pop-culture/
>And yes, that sound you hear is the slow deflation of the bubble I've been warning you about since March...
>How does GPT – a transformer-based model that generates answers probabilistically (as in what the next part of the generation is most likely to be the correct one) based entirely on training data – do anything more than generate paragraphs of occasionally-accurate text?
etc.
Basically the essence is he's skeptical of AI / LLMs being any good so thinks all the investment is down the drain. Meanwhile AI progresses such that Fable can probably beat most humans and IQ tests, maths and the like. And the 'bubble' didn't deflate yet.
My take is that as a PR guy, used to people hyping stuff and not that up on comp-sci he fundamentally doesn't get what's going on. He assumes it's all hype rather than the steady progress in computing reaching brain equivalent levels and beyond.
He's not wrong about the numbers, and you may be seeing what you want to see a little, here.
Fable scoring OK on some benchmarks does not the mean the investment has financially paid off, because that's not how ROI works.
You're right that no bubble has deflated, but I think we can all see that a) there seems to be a bubble - I'm old enough to remember the dot-com era bubble, and this definitely feels like that, b) the only company clearly making a profit on AI right now is NVIDIA, and c) the net economic value of the sector as a whole (i.e. money out > money in), is still unproven
It's not even obvious to me as somebody who is up on comp-sci, that this isn't all hype, that the progress is/will be steady, and that reaching brain equivalent levels and beyond using these architectures will be economically viable.
I can create a perfectly good human brain in 9 months, train it in ~20 years, and have it pay off economically in a more proven way than [waves hands] all of this.
For some reason we've decided paying a hyperscaler the equivalent of a year's salary to do a job in a a day that a similarly paid and skilled human could do in a month is value for money.
You could probably give everyone in the US free healthcare for life and a free ride through college for less money than has been pumped into AI in the last 5 years, and have a more proven economic model.
Sure, time value is a thing, but given the error rates, the energy issues... this direction is not exactly a slam dunk as a net benefit, and I think that's all he's called out in any of the writing I've seen of his.
I also happen to agree with his take on Oracle, as it happens - they're only going to survive if it turns out they're a part of critical national infrastructure deep in the bowels of the US government. They look totally over-leveraged otherwise.
Here's some criticism: https://bsky.app/profile/peark.es/post/3mmhtcib3622i (see the full thread)
I'm not qualified enough myself to judge Zitron's reporting, nor this criticism. But George Pearkes is a reasonably respected financial analyst.
I think both sides might be cherry picking the pieces that make their arguments the strongest - Pearkes has pulled out a few paragraphs, but there is a lot in Zitron's writing, so it's easy to select 6 bits you don't like/agree with or find fault with, but I'm not sure it undermines the rest.
I actually think Zitron would be better off focusing on those deals where there is clearly something weird going on (SpaceX IPO, Oracle/OpenAI/NVIDIA triangle, the neoclouds, and so on), than picking a fight with the one company that actually seems to be trying to play it straight in this sector (Anthropic), and I can see how he's covering the whole field with the same cynicism which might not be appropriate.
That said, I'm not entirely convinced that some of Pearkes' analysis deserves us all to align to the rosy bullish view he takes either.
Time will tell, it always does, but at least you've put forward some data unlike anyone else, so thank you for that.
Let me guess, you disagree with his views on the utility of Ai (which he's pretty bad about) and you use that as cover and/or to negate his real journalism that is based in facts (Ai being an unprecedented & unrecoupable bubble littered with unprofitable companies thats likely to crash our economy unless these Ai conglomerates cozy up lawmakers to situate themselves for a bail out)
My disagreement is that every time he turns out to be completely wrong he silently moves the goalposts instead of acknowledging it.
For years he was all-in on "AI is useless, it has no business value at all" claims, and then when that was decisively disproven by Claude Code, he didn't spend one second on self-reflection on why he was wrong and whether this might mean he is wrong about other things. He just smoothly pivoted to "AI companies will never be profitable, tokens are hugely subsidized". And now that that's about to be disproven (word on the street is that Anthropic will soon report profitability, and both Anthropic and OAI have repeatedly said inference is profitable), he's pivoting again to "tokens are too expensive and the ROI isn't there for business". No correction, no reflection, just "we're at war with Eurasia, we've always been at war with Eurasia".
Even if he’s sometimes right, there are better analysts out there who are also right and have the honesty, humility and integrity that Zitron lacks.
> For years he was all-in on "AI is useless, it has no business value at all" claims, and then when that was decisively disproven by Claude Code...
No such disproval has happened. Claude Code does not provide business value, it provides the illusion of value. Just like everything else LLMs do.
Can you elaborate on what happened that made you look dumb?
[flagged]
> Show us on the doll where Zitron touched you
Comment read sensibly until this bit.