How accurate have Ed Zitron's AI skeptic predictions been?

You can do that, but then you’re no longer discussing his predictions. You’re discussing your predictions, and your own positioning.

Those differ from Dan’s essay, which engages with the literal text of Ed’s numerous predictions during 2024 and 2025 which are demonstrably invalidated by their measurable outcomes.

These tech giants need AI to continue to grow, and that growth at the moment seems to be coming from just two AI companies who are burning a record about of investments. OpenAI has raised nearly $200B, that is more money than Australia's tax revenue.. and they are getting further from being profitable as Chinese models are getting better and much cheaper.

The article linked seems right, but you have to take these morbid analogies in a very specific way, and assume that the only way to measure these companies is revenue/profits/money rather than their products.

I wish people would hold actual professional media economists to the same standards, along with journalists who just repeat press releases without actually challenging statements. His main argument has been the numbers don't make sense, and can't see how this won't end badly for a lot of people.

We have people telling us the next recession being imminent all the time. Others told us that NFTs were key to the future of art. That's the pundit way. If you want accuracy, you become like Charlie Munger, have maybe 2, 3 really good insights througout your career, and hope do to well using the insights yourself, not by being a pundit

That, and he has a nice way of speaking like everyone's gone mad but you and him ;) Have to admit I have enjoyed his rants, and there are certainly true things about them, here's another nice one for you lovers and haters alike! [0]

[0] https://www.linkedin.com/embed/feed/update/urn:li:ugcPost:74...

A frustrating thing about Ed Zitron is that he sometimes breaks news - gets hold of leaked numbers that nobody else has, for example - but he then wraps those numbers in his own extremely biased commentary. This makes it much harder to evaluate how credible the new information is.

Growth isn't a valid rebuttal, unless we can also sus out how much of that growth is tied up in circular financing of AI projects. We have a pretty good idea how much of Nvidia's valuation is tied up in the AI craze, it's a bit harder to tell with the megascalers....

Not challenging him was a mistake in hindsight, and I own it. Going forward I will no longer be helping writers/journalists with a clear anti-AI bias.

Lol, I appreciate the sprinkling of well timed humor in an article that is mostly straightforward facts and analysis.

P1. AI is useful powerful and (P1a) will continue to get more useful and powerful at the same rapid pace it's been improving

2. AI companies are very profitable, and (P2a) will be wildly profitable (eg $30T TAM) in the next few years

These are completely separate. But in practice people seem to be either proAI (both true) or anti AI (both false). P1 is clearly true and I find it hard to take anybody seriously who says otherwise. P1a... Who knows, gotta hit a wall sometime. P2 I'm way more uncertain about (especially P2a) but it seems like people like Zitron reason backwards from hating AI.

Regardless of whether you love LLM’s as technology, the financial realities of Anthropic and especially OpenAI really does not look good. They have a massive expenditure that they need to keep going in order to make profits, which at least in terms of OpenAI are horrendously behind. Zitron published these numbers together with Financial Times, so you gotta give him that at least. Meanwhile the CEO’s talk all kind of nonsense and give their own predictions to get more investors money to fund what might or might not be the biggest bubble in the history of finance. I certainly do not hope this happens, since the consequences would be horrific. But there is likely to be a some sort of correction in horizon, since the models will plateau and they will run out of money at some point.

Let me finish with my own prediction. I think a lot of people are going to lose a lot of money some time next couple of years.

In one of his posts a few months ago, he went on a weird tangent about the CEO of ServiceNow talking about sales planning and whether his teams are "on plan" or not. For people who haven't spent time in or around sales, this is an extremely common shorthand for quota tracking.

Ed's rant about how impossibly weird and inhuman the framing was revealed how little he knows, and cares to know, about the mechanics of the businesses he claims to profile. Yes, something like "on plan" is jargon, but a shred of reasonable journalistic curiosity (a Google search) would explain what it means and how it's a normal statement for a career-sales CEO.

If they were doing so well why the layoffs? Why the tightening both in salaries and perks and work life balance? Why so many choices disrupting morale for their employees?

https://danluu.com/futurist-predictions/

Yet, in this case, he takes the marketing numbers at face value, not being an expert in AI financing, while those who know more, can spot the sleight of hand, just like he can when it comes to semiconductors.

Whenever you'd look up anything pertaining to China's future, you'd inevitably find your screen plastered wall to wall with thumbnails of a photoshopped Xi Jinping, tears streaming down his face, next to large impact font text reading "CHINA WILL COLLAPSE IN X DAYS", with X varying from 1 to 30. Much like Ed Zitron's predictions, these events obviously never occur.

I think his contribution to the discourse is the bigger picture. These companies are going into potentially economy-wrecking debt over a speculative future that looks much foggier than the last two previous technological booms.

https://www.wheresyoured.at/measures/

Now ORCL is back to $140.

I found this in two minutes via a search engine, but the star blogger Dan Luu apparently cannot handle that. I'm not a regular Zitron reader, but incidentally this blog post that came up in the search is several levels above Luu's post.

Zitron gets the big picture right.

What I’ve stopped doing is reading him regularly. It feels hard to parse the factual from the obviously exaggerated.

I get he’s frustrated. We all are. But I’m not sure letting it out that much helps making the very urgent case he’s making.

The entire AI industry, especially the vested interests, are often full of shit, sure, but the sheer amount of misunderstanding that has surrounded the economy and its relation to AI has been mind boggling. There is much bologna being accepted as reasonable or even standard by HN comment sections.

I think something similar is happening with e.g. Amodei's predictions of mass unemployment due to AI. It won't happen in the immediate term, because deficit spending removes the economic incentive for firms to pare down their workforces.

All that said, I don't think these people are "wrong," per se. They're just early. When the sh*t hits the fan on all this, it's going to be a big problem. And, for example, companies whose primary business is collecting money for Internet ads will come face to face with the reality of how low value their products are. I have some insight into this, as I work for such a firm, and I know the true extent of the bot traffic out there.

1. Zitron claims model capability has peaked 2. Zitron claims AI lab growth (user and revenue) has stalled.

In the first case, TFA refutes by claiming 'wrong' repeatedly, which does not convince me of anything. If anything, Zitron is probably right in this regard, since the majority of progress in recent LLM tech has been setting up of guardrails to cajole the models using 'agents'.

In the second case, numbers are given showing growth, directly refuting Zitron. However, I'm giving Zitron the benefit of the doubt, given the old saying - market can remain irrational far longer than you can remain solvent. As long as people can be convinced that the sky is falling, rational predictions rarely pan out.

I use AI every day as I assume everyone else on Hacker News does. Will the S&P 500 drop 20%? I have no idea. If you know, please let me know so I can adjust by 401K.

I share this less to take a shot at Ed but more so that you all know to ask this if you ever hire a PR person.

> list 50 predictions by Ray Kurzweil that he made before 2005, the date he made the prediction, and whether to not his prediction was correct. If it was correct, give some proof.

Of the 50 that were listed, 43 were correct, 7 incorrect.

> Wrong (Zitron continues to write despite repeatedly being proven wrong)

Technically he didn't say he would stop if he was proven wrong.

I have heard multiple breathless press releases warning that the end of white collar work is "just 6 months away" and that people not using the latest Mythos/Fable/Whatever model will be hopelessly left behind.

To pick a specific piece of public information to support my claim: the previous SVP of ads quit immediately before the coup to start a subscription based search engine.

One nonpublic piece of information: basically every member of search leadership was pushed out within two years of his ascension.

But this article is not nearly as impartial as it claims to be. It interprets all Zitron's claims in a narrow and overly-literal way. Missing the point and refuting a technicality.

For example, looking at the last 3 year's revenue/profit growth. This tells us nothing without looking at a larger context. Has revenue growth slowed down? Have profit margins compressed? What makes up the income and has that changed? Etc.

I think anyone being intellectually honest understands that these tables alone don't refute Zitron's claims that big tech are "dying and thrashing around" which is something that could take many years and easily hide under these kind of top line / bottom line numbers. (Maybe further analysis would refute the claim, but that analysis is not present here.)

Or Zitron's claims that AI capabilities are "reaching the upper limits" back in 2024. I don't think even Zitron would disagree that AI capabilities have grown since then, but that doesn't refute his point. How long the "reaching" takes and how wide the "upper limits" are is completely up to a subjective interpretation, which this post makes no attempt to even explore.

By all means dunk on futurists. But at least steelman their positions or you look just as biased as them. (Although maybe I am off base and this bias is meant to be clear from the start by admitting to pro-AI predictions all the way back in 2015.)

Look at his incentives. It makes more sense.

I think the worst thing that happened to him was AI skepticism becoming a political position. This gave him a captive audience - as long as he says what they want to hear, which means that he can never ever concede that he might have been wrong or that AI might actually be progressing or having successes.

This is not conducive to good prediction long-term - rather it leads one to a state of cognitive dissonance where one's chosen enemies must be simultaneously terrifyingly powerful and incompetent dunces. The propagandist's disease.

I have seen some wild failure modes from people who are outsourcing their thinking to LLM. Amendments to clauses that don't make English sense. Multi-paragraph long replies in emails that say nothing specific to the issue at hand. Responding to questions with "AI says this" (but I asked you, not the LLM). Leadership wants us to embrace AI but there is no product for the layperson, it feels like everything is front end + generic prompts + $LLM_API_key. People want to make customer service bots that have access to personal data.

I feel like software devs are so lucky in that at least people in your field can see an LLM for what it is and harness (no pun intended) it appropriately. As a lay user, no such luck. Leadership and purse strings are far removed from IC work and don't understand why an AI product wouldn't work, they've heard otherwise in their circles, you had better make it work so that they can claim to have delivered an AI transformation this year.

Enter Zitron.

Zitron is a woo-pushing grifter (his product: his stance on AI). Even without examining his reasoning or the accuracy of his predictions, Zitron is hard to listen to. Mostly, he shouts out a constant barrage of bare assertions that his research is thorough and irrefutable and the doom is coming and ever "AI booster" who disagrees with him is an idiot, all the while without actually spending time arguing his point.

But Zitron feels like one of the few people actually pushing back against this craze.

I would very much like a better argument for a position that I support, please and thank you.

It's interesting how he has pivoted from denying that LLMs are useful to accusing frontier labs of Enron-scale fraud.

I suppose it's the natural pivot you have to make when your whole business is an anti-AI newsletter that costs $7 per month.

Was this hit piece prompted by Zitron being mentioned in the tech scene lately?

https://lwn.net/Articles/1091245/

I don't know. If you post walls of text and ramble on like Luu, perhaps you are sitting in a glass house?

Luu also fixates on Zitron mentioning Prabhakar Raghavan, but then proceeds to agree with Zitron's core point that Google has intentionally degraded it's search product to maximize revenue. Maybe Raghavan is not solely responsible, but it seems fair to hold him accountable for trends that accelerated under his leadership.

Zitron is saying that the hyperscalers had no genuine growth opportunities, so they're using the AI bubble to achieve growth. The fact that they've continued to grow for a few years doesn't contradict his point, and Meta's steadily decreasing profit margin certainly doesn't look healthy.

Shouldn't society have a clever name for people playing these roles by now? Something catchy, insulting and based on truth might help call this out easier. I would throw influencers in there too, they are writing/video-loggin/podcasting for the same money outcome.

- Hyperscalers like Goog, Meta, Msft invest cash in Anthropic, OpenAI, in exchange for equity

- The ongoing investment actually boosts the valuations in the Anthr/OpenAI (new raises are done at higher valuations), so the valuation of the Hyperscaler's existing investments in Anthr/OpenAI increases, which gets recorded as Other Income in quarterly earnings

- Much of that invested cash will itself come back (circularly) to the hyperscalers as revenue since Anthropic and OpenAI spend a lot of money via datacenters etc.

On Other Income phenomenon, see for example, https://www.ft.com/content/be97df0a-76b1-4cb0-9ba4-d1117d8d1...

Also, there's apparently lots of off-balance sheet debt. For example https://www.ft.com/content/a0a07cce-6d19-4b1e-a73b-9855a06ba...

What likely resonates is AI really does feel like a science experiment. There is clearly real value here. The problem is that the economic value has yet to catch up with the technological value. And yet the claims coming from AI companies have the unmistakable energy of a state-fair entrepreneur standing beside a suspicious knife yelling, “You have never seen anything like this before, it slices it dices...!”

I think Ed goes too far when he compares LLMs to garbage. He’s tried them, had a handful of bad experiences, and apparently decided the entire technology belongs in the round file. But much of what humans do is essentially trial and error with better PR: apply some logic, see what happens, adjust, try again, and continue until you eventually solve the problem.

If you can get an LLM to reliably do that, you can solve certain classes of problems dramatically faster.

I think it's really, really, really important to have a contrarian opinion out there, even it's a voice howling in the wilderness. Even if most of his predictions are wrong. Even if he swears a lot and gets a bit ranty at times.

Personally, I think he's going to be mostly right in the long term about the AI bubble, but mostly wrong in the long term about the effectiveness of AI (i.e. I think it will have a net-positive effect in the long term).

I always keep in mind the Gartner Hype Cycle [0] is true, and we're still on the initial slope up to the Peak Of Inflated Expectations.

[0] https://en.wikipedia.org/wiki/Gartner_hype_cycle

Ed Zitron mostly covers the costs of data centers, circular spending, and predictions of large the market for AI has to be to justify the data center expenditures.

I was disappointed this article didn’t really cover Zitron’s main arguments.

Maybe a paid article placement? I don’t know, but I was dissapointed: I read Zitron’s material and I wanted to see good counter arguments to his rants about costs of data centers, circular spending, and predictions of large the market for AI has to be to justify the data center expenditures arguments.

e.g.

>April 2025: "It also, at this point, is pretty obvious that generative AI isn't going to do much more than it does today." >>Wrong

Is generative AI really doing much more today relative to 1.5 years ago? Sure there have been sone improvements, but i feel like nothing fundamental has shifted in that time period. Nor would i really expect it to even if the statement was false, but it seems too early to tell.

In April 2025, Zitron wrote [1] "I am sick and tired of everybody pretending that generative AI is the next big thing." This was at the time when AI coding tools had already gone "mainstream" with devs, and pretty much everyone was using tools like GH Copilot, Cursor, or something similar.

So I replied with this observation, saying how, at least within software engineers, AI is being adopted faster than any technology before [2]. To stay objective, obviously I brought receipts: sharing how, based on an older survey I ran, ~75% of devs in that survey said they used AI coding tools. Zitron made fun of the small sample size (216 people), blocked, and pretended like AI had zero PMF anywhere in the world.

I stopped taking him seriously since then. And I'm wondering ever since: does he deliberately only look at numbers and facts that he can tell the AI doomer story around? Or is it more that he finds that there's not many people who are "informed sceptics", and decided to play this role?

[1] https://x.com/edzitron/status/1916903519594156407?s=20

[2] https://x.com/GergelyOrosz/status/1916906481686921483?s=20

For him, it's enough to be right once, even in 3 years from now.

AI is a big field. Hating on AI is like hating food because you don't like broccoli.

Robotics AI that replaces high risk labor and even low risk repetitive stress labor is nothing but a win for humanity.

It's just a question of what the entertainment is. Some people feel good about being told "we were being hoodwinked; there are lizard people" and others feel good about being told "you'll be 100x healthier and good looking if you take these supplements" and others feel good about being told "these people are evil demons who are stealing your water" and others feel good about being told "these idiot rich people are going to lose their shirts" and so on and so forth. It's like how I like slice of life shows and hate horror movies and my wife likes horror movies.

In a sense, the misinformation gambit of LLMs did not come fully to fruition in the West (as much as it has in 3rd world WhatsApp forward land) because the locals were already a fertile ground of poor epistemic hygiene and well served by human providers of misinformation. Hacker News itself only has some hundred thousand commenters or so and even this requires a practice of aggressive information curation to prevent unrepentant misinformation repetition nodes from polluting one's belief set.

Zitron is just, like Dan Luu says, wrong about everything and doesn't care anymore, he's in the business of extracting money from his engagement.

You don't say.

This is one of the most important learnings one can make from working in professional environments.

I'm not Ed's biggest fan, but he's been pointing out some very important things for quite some time now, regarding the ludicrous over-investments going on around so many companies that are completely and utterly devoid of profits and will likely never have any.

But from that point on they basically assumed this role of what financial punditry call perma-bears, people who constantly predict financial doom. It gets clicks and sells subscriptions, which is probably why they do it. But from that point on their predictions weren't very good. If you constantly predict doom then every now and then you'll look like you were a genius, but it's just survivorship bias. People discount all the other times you were wrong.

I don't know a whole lot about Zitron himself. Didn't he get big calling BS on cryptocurrency stuff that actually was BS?

The problem is that AI isn't cryptocurrency. This is very real.

I do suspect there's some bubbly stuff around it. I think data center construction looks very bubbly, especially the totally ludicrous amount of permitted planned data center construction. I bet no more than 20% of that ever comes online. I'm sure there's some AI companies that won't make it, and a bunch that are overvalued. But AI as a whole is real, not just hot air.

In 2004.

And he'd been talking about it before then.

People thought Max Keiser was a crank; instead he made detailed predictions based on his intuitions, limited insider feedback and cold hard facts. He couldn't say exactly when it would happen; he laid out some horsemen you could expect for the apocalypse and this was one.

The thing about a bubble is everything is fine until it isn't. And it's worth observing that key parts of what Zitron is discussing has been covered in the WSJ and FT.

It's all very well posting numbers to "disprove" him when what he is pointing out is that the AI hype train is delusional and the costs are buried.

But Zitron is directionally correct, I think, particularly with regards to Oracle, where things he has said have literally come true.

Frankly as a Brit I remain amused at how much Zitron winds Americans up just by being himself — sweary, vulgar, rude, catty. And since non-Brits can't read Brits, Luu has to engage in pretty immature character assassination about it.

> He found a niche in anti-tech grift, and is now exploiting the niche for all he can.

Or there's this one:

"I also have not taken the route you are "meant to take" to get here...I did not "earn my stripes" in the traditional sense, and those that have believe I did not earn my way here"

And maybe he lived in a van down by the river as well? I can't take this guy seriously, I just can't.

But I get that he speaks to an audience that needs to hear his take and that's their call. I don't have time and I won't make the time for podcasts and sitting through the worldview of anyone for hours at a time, 2 to 5 times weekly. No one is that interesting IMO.

*"I do a good photo shoot, I do a good interview, and I capitalize on events...I believe there are some that would like this level of attention or prestige, but they do not want to do the work to get it, and that chafes"

**"some men don't like me because emotional honesty and introspection are difficult for them."

I will say, the first part Mr. Luu says about big tech not being out of ideas is pure horse shit. Anyone who has worked in big tech knows that leadership at those companies can have no idea what they are doing and still be successful in earnings or the stock market. They are sometimes successful despite themselves.

But for the bloombergs and other podcasts I would have expected them to do a bit of research. I honestly think with the amount of doubling down he's been doing that he's a grifter.

Collapse of entire economies will result on a scale that will eclipse the great depression. And it wont be because AI revolutionized anything. AI will become a dirty word to never be uttered by anyone in the human race after.

the analogy to Ehrlich was strikingly apt

also statements can be interpreted many ways:

"Meta is dying" was countered by "Meta's revenue has increased since Zitron said that". OK, but 1) revenue/profit is only one measure of "not dying"; 2) what's the time scale? Nokia and Xerox were highly profitable companies that dominated their industries, and any prediction that they would go out of business at their height would have been laughed at, and yet, it wasn't too much later that they pretty much did.

> For example, with a style that could be described as the opposite of clickbait, Simon Willison has written what I suspect is the most widely read blog among programmers for the past 3-4 years (in the same way that, at various times in the past, Joel Spolsky or Jeff Atwood or Steve Yegge seemed to be the most widely read programmer among programmers). Among programmers and other serious users of AI, I would guess that Willison has a larger audience than Zitron.

I have no idea Simon Willison is the most widely read blog among programmers. I truly have no idea, and I've been programming for just a decade.

A lot of Simon's blogs posted here are when new LLM models are released, on how good are these LLM models create pelican riding a bike using SVGs. Nothing particularly interesting to me.

I truly have no idea why would people be interested in blogs about LLM creating pelican riding a bike svgs every single time a new model is released. Maybe its a proof of AGI/ASI for some?

I guess to me, Simon Willison will always be the "create-a-pelican-riding-a-bike-using-svg-dude".

Good critique of LLMs & the companies behind them is hard to find, and it is harder when people gravitate towards this sort of thinking.

Would love to see broken down counter example of public company.

So far Chegg and Duolingo have been devastated. Surely they could cut costs drastically with AI?

So from that standpoint, I guess it would make sense that a personality like that would now have ended up at the AI topic.

I would like to see a comparison with predictions of the pro-AI bubble and their hit rates though. This writing feels as selective as it tries to paint Zitron as.

US has 1.5x the money supply since Covid. This means everything has to go up 1.5x to reach the same parity from before. eg inflation. All corporate earnings are going to inflate as 1b yesterday is 1.5b today.

There is no whete for these mega corps to go. They dont know how to grow. meta becoming well meta with the vr crap is case and point. meta blowing billions on a few hyped AI people is the nail.

Other than cloud, microsft/google aimt doing anything. xbox? nope, hardware? nah. It is all attention economy or selling the pick axes for it.

the only mega corp that still seems to be moving the needle is apple which i think speaks volumes.

Eds point is that AI tam or expectations are insane full stop and he admits coding has a use just not as big of a tam. Gen ai in art, music, etc did not take off at all esp compared to code. this makes sense, no one pays an artist 500k/year. their time is worth little compared to coding.

Where he is wrong tho is that this is not new. there is always a hype cycle of nonsense that screws the little people. what is new is the level of polarization. it feels like ai psychosis right now in ways that remind me of crypto but worse because ai is actually useful so people are even more insufferable.

Can I try?

> But when people bring him up, they're of course not generally citing his anger

Wrong.

> Google has been increasing the relative priority of revenue over the user experience over time

Wrong.

> I'm curious what people do after being on the wrong side

Wrong.

Some of the claims categorized as "wrong" are also completely true, such as training hitting diminishing returns. New models are barely an improvement and most people I know stuck on Opus 4.6 over any newer one for example.

Exact same thing for the claim "the fact we're running out of high quality training data and we're hitting the walls of scaling laws, in the training paradigm, these models aren't getting better. What we're seeing today is pretty much what they're always gonna be like".

If anything, model performance has regressed in actual use (i.e. not benchmarks) for the past half a year.

that'll obviously never happen. it's wishful thinking and venting tbh. that's why i like listening to his stuff.

it's better than reading the wholly AI slop docs my CEO keeps sending out

One annoying side effect is that YouTube's algorithms will always try to force feed you more of the things you last searched, to amplify your biases and send you down the doomscroll rabbit hole. So if you search for Zitron, next time you visit you'll be flooded senselessly with naysayers, contrarians and skeptics from all courses of life.

He's created a huge following (and is presumably making a lot of money) from pushing a hardcore AI-skeptic narrative, and I can't blame him for seeing that opportunity and running with it. We're ultimately all responsible for recognising these people and weighting their advise as necessary.

Additionally, from a public reputational perspective making bad predictions simply doesn't matter. In finance we're all aware of perma-bears who will predict the sky is about to fall, and when it doesn't just argue that the disaster is still coming, but is taking longer than expected, or that some unforeseeable thing happened which has compounded the risk but has for now kicked the can down the road.

So ultimately, it will be very hard to say Zitron is wrong unless he starts time-boxing his predictions, which I don't believe Zitron has done for obvious reasons.

That said I don't listen to him much at all. I've tried to listen to him a few times, but it's become evident very quickly that he doesn't understand the technical details enough to be making the predictions he's making and seems way too emotionally invested in the arguments he's pushing without good reason. I have strong personal filters for low-quality sources like Zitron – if someone raises enough flags I avoid them like the plague.

Also consider that the economy isn't rational. Our economy should have tanked several times by now. AI should have fallen apart by now. Meta, Google, Microsoft should have declined. Instead it's record profits. So don't try to make predictions by being rational.

Think about the world before the 2017 "Attention Is All You Need" paper.

Did anyone predict that paper, what preceded and followed it?

Nope.

Same case now.

Maybe the word "prediction" is the problem; "guessing" would be better.

OK, what the heck. I'll make a prediction too:

You better buy SpaceX stock now. The way things are going in the US, the only way we build AI data centers at scale will be in space. Politicians have turned data centers into punching bags to be used to gain votes. We can't build power plants and people are being led to believe all kinds of things. Regardless of which, if any, are true or not, the rate of construction of AI data centers in the US is and will be seriously constrained by realities on the ground.

Hence my prediction: It's all going to space.

I knew that somewhere in the future, something has to give because you can't just go around saying anything without losing some credibility. You still have some ardent followers in his cult of a subreddit.

But just to be clear: Ed is part of a bigger problem in tech journalism which is characterised by extreme pessimism and excessive skepticism. It is not correct to view Ed in isolation rather to see it as a part of the culture in which he can thrive.

[1] https://news.ycombinator.com/item?id=48447549

[2] https://www.theargumentmag.com/p/ais-biggest-critic-has-lost...

And I say this as someone who started as a doomer, and is increasingly a pessimistic pragmatist (“LLMs have value as tools, but not nearly as much monetary value as the main players believe they do”).

I get it though: for those of us who grew up alongside the net and tech sector, who loudly decried M$ greed for ME/Vista/8/11 but celebrated them at XP/7/10, who remembered when Google’s “Don’t Be Evil” was spoken with serious reverence, the current era of tech feels toxic and nauseating. Current AI is a prime target for that discontent, as are the companies whose motives very clearly aren’t societal progress so much as reality authoring and authoritarianism. In that vein, Zitron is magnetic because his entire position is “you’re right to be mad and they’re all going to die from hubris without you having to actually do anything”, which itself panders to the human desire for personally preferential outcomes sans individual effort.

Properly picked apart though, and he has as much substance to offer as the ardent boosters: a handful of “trust me bros” with a smattering of distractions to wind you up, but never actually address your concerns or questions.

These companies are all heavily buoyed by their investments in AI which is essentially an oroboros of money.

Maybe he is well meaning, but it's pretty common these types are just milking an audience that they dialed in on with zero regard for integrity or honesty.

Zitron has a somewhat ranting style. Luu's passage on Google search for example just nitpicks on the person that Zitron allegedly named as responsible for the decline of Google search.

The real issue of course is that search quality clearly has gone down. What does Luu want? A "study"? Everyone can see that. The person is not the issue.

This is a highly selective analysis of Zitron's writings that focuses on a couple of mistakes. People need to understand that any normie will understand the difference between rants, numbers and speculation in Zitron's essays. They are not written for autists who talk of "priors" and "evidence".

You don’t have to spend effort proving him wrong. Just don’t read it and move on with your life. Regardless of which “side” of AI you’re on it’s kinda ridiculous how much effort gets spent on screaming gotcha at this one commentator.

I would reply the same regarding this article. Nearly all of these refutations are unconvincing.

The claim: "I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be."

The rebuttal: "Zitron's argument at the time was that hallucinations were as good as they were going to get, which meant that AI performance is capped at 2024 levels. Both the overall prediction and the mechanism were wrong. This one seemed wrong at the time, in that I noted here in 2024 that you can make AI code halfway decently by just putting it in a loop and having it run until the code compiles and tests pass"

Putting an LLM in a loop, burning tokens, and thrashing against a compiler and test suite is a ridiculous way to say that hallucinations have been "solved". Please. This is absurd.