[zachthewf]

Before you spend 20 minutes reading this article, it's worth understanding that the writer has been posting popular but consistently wrong takes for 2+ years (e.g. https://www.wheresyoured.at/peakai/ from March 2024) arguing that AI is failing, is a waste of money, is bad, will never work, etc.

[asveikau]

Not sure where I heard this, but I'm reminded of a story about someone predicting the dotcom crash early, circa 1998. For 2 years they were demonstrably crazy, and missed out on massive stock market gains. Then they were right. (And yes, tech slowly bounced back after that.)

Predicting the timing of such a thing is notoriously difficult. I don't think being wrong about timing 2 years ago means there won't be a correction.

[nostrademons]

I'm also reminded of all the HN posts from 2007-2009 that predicted that the adoption of social networking would be a terrible thing for privacy, that it would destroy society, that people would lose their jobs over crazy shit they said on the Internet, that it would lead to the decline of trust and in-person interactions, that people would forget how to socialize, etc.

They were right about all of that but it took 15-20 years and the companies involved grew 100x in that timefold, eventually reaching trillion-dollar valuations that would've seemed insane in 2007.

There is a tremendous amount of money to be made in destroying society.

[mike_hearn]

Eh, you can find HN posts predicting that literally everything will destroy privacy/society/trust/etc. Predicting doom is a popular pasttime.

What I remember from that time period is people predicting that we were in a tech bubble driven by social media, that obviously Facebook and LinkedIn were overvalued because social media was a trivial fad, and so on. Example article pulled at random:

https://theconversation.com/linkedin-is-floating-on-air-or-i...

And yet there was no bubble, these companies did fine and Meta became a financial Godzilla.

[nostrademons]

They weren't wrong. We were in a tech bubble driven by social media. Digg, StumbleUpon, Kongregate, MySpace, Orkut, Slide, Meebo, Mahalo, Bebo, Justin.TV, etc. aren't exactly around anymore. Facebook and YouTube are the winners.

Anyone remember this video?

https://www.youtube.com/watch?v=I6IQ_FOCE6I

How many of the logos that scroll by there still exist?

[asveikau]

I was definitely around when that video was current, but I don't remember it. It's pretty amusing.

Ironically I feel like it captures the spirit of the then-coming 2010s boom more than the climate in 2007, though some of the language it's using is decidedly pre-mobile and more "web 2.0"-ish.

[mike_hearn]

The fact that some companies fail isn't evidence there was a bubble. Companies are always failing.

[abaymado]

Not related to AI but, I recently rewatched "The Big Short" and your comment reminded me of it. I can't testify the accuracy of the movie, but for over year, Michael Burry was viewed as in the same manner for shorting the market, while the economy was was in a hype cycle.

[deaton]

Burry of course has famously predicted 40 of the last 5 crashes, so maybe not the best example.

[loeg]

And lost his shirt doing it. (Or, well, his investors' money. I'm sure he's fine.) https://www.reuters.com/sustainability/sustainable-finance-r...

[asveikau]

This is like the old quote, "the market can stay irrational longer than you can stay solvent"

[red75prime]

> Predicting the timing of such a thing is notoriously difficult.

So, it stands to reason that it wasn't a prediction, but a lucky guess (unless the alleged predictor has a history of correct predictions).

[FromTheFirstIn]

That actually doesn’t stand to reason at all!

[padjo]

If I just continually predict that it will rain tomorrow I'll be right eventually. That doesn't mean that I know anything about the weather.

[zachthewf]

I'm open-minded to arguments about AI being a financial bubble and a bad business.

I'm not open-minded to arguments about utility, given that I personally witnessed LLMs evolve from interesting but useless toys to insanely helpful tools I use every day.

[asveikau]

I guess one of Zitron's arguments is that the utility you see today is based on subsidized costs, that if you had to pay more it might not be worth the tradeoff to you.

So the claim is the cost isn't coming down enough to make it make sense for a lot of uses in the long term. When I hear that next to the most wild claims, some by influential people, that the entire white collar workforce is going to be replaced very shortly, it's a bit of a useful reality check.

[degamad]

Exactly. The question is not "are people using it to do stuff?" because we know right now they are. Given free or heavily-subsidised access to powerful tools, people will use them.

If I had someone giving me free access to cranes and excavators, I'd be raving about how easy it was to build houses now. But tomorrow when I have to pay full price for them, I'm going to be making very different calculations about return on investment.

The question we need to be asking is "what is the likely full-price cost we'll have to pay for these tools, and is that cost likely to be worth paying?"

What Ed's pointing to is that the full-price cost will have to cover the capital expenditures that have been invested, or the companies which risked that capital will go bust. That gives us a floor for what the full price cost will be, and that floor seems higher than the value being offered by the tools.

[zuzululu]

you cant operate setup cranes or excavators alone

[Aerolfos]

What does that have to do with anything?

Is reading comprehension really this bad nowadays?

[root_axis]

Can you point to anything specific from the article that you'd describe as consistently wrong? Not disagreeing with you, but nothing popped out to me after skimming the article.

[zachthewf]

I didn't read the posted article (I don't read this author anymore because I think it's basically anti-AI ideological propaganda).

But from the article I linked back in March 2024:

"Generative AI models are expensive and compute-intensive without providing obvious, tangible mass-market use cases. Murati and Altman's futures depend heavily on keeping the world believing that development and improvement of their models' capabilities will continue a rapacious pace of progress that has unquestionably slowed, with OpenAI admitting that GPT-4 may be worse on some tasks.

As I've written before, hallucinations are a feature not a bug. These models do not "know" anything. They are mathematical behemoths generating a best guess based on training data and labeling, and thus do not "know" what you are asking it to do. You simply cannot fix them. Hallucinations are not going away."

Since then:

- hallucinations are dramatically less of a problem

- several mass market use cases have emerged, most notably coding

- rate of progress has increased

[root_axis]

I think the points you raise are reasonable signals to consider, but I don't think they show the author being "consistently wrong". The overall thesis still remains plausible even though we have seen LLMs continue to improve.

> - hallucinations are dramatically less of a problem

Sure, but it remains a big enough problem that human intervention and review is still necessary for any serious work across all use cases and industries.

> - several mass market use cases have emerged, most notably coding

Coding seems to be the only one, but there are still a lot of open questions about how the market can sustain the costs, and that's without considering the market dynamics that could emerge once costs are lowered enough that open source models start to become an attractive option.

> - rate of progress has increased

Debatable.

[SlinkyOnStairs]

> Sure, but it remains a big enough problem that human intervention and review is still necessary for any serious work across all use cases and industries.

Another important consideration: Hallucinations getting less common/severe but not (as-good-as) solved makes them worse.

LLMs used to very obviously get things wrong. And people wouldn't trust them. Now they're good enough that people blindly trust them.

Now people just directly PR AI output with little to no manual review. We even have clowns calling for the complete abolition of directly human-authored code.

Whatever gains were had in better AI code output over the past two years I lose in having to review much more thoroughly.

[Capricorn2481]

> several mass market use cases have emerged, most notably coding

Most notably? This is not a mass market use case in the way the author is describing. They are asserting that the amount of spend they need to get this off the ground necessitates the entire world coming in on it, and I would say that opinion has aged pretty well. There are a lot of coders, but there are more people scratching their heads as AI is shoved into every part of their lives.

[mashlol]

Has rate of progress increased? How does one measure that? Genuinely curious - would be very interesting to map out the "effectiveness" of each AI model vs how long it took to train/release.

From my perspective, the model gains are mostly incremental now and a lot of the gains are just from things like improving the agent harnesses. I could be wrong though.

[_aavaa_]

On the front page right now is the newest announcement from Xiaomi serving large model at over 1,000 tok/s on standard server gpus.

Every facet of the field is being pushed on and advanced at the same time.

[raziel2701]

Hallucinations are still a problem. I recently asked one to give me a quote from a book, figuring that since these AI companies have pirated all books in existence surely it can just recite a specific passage no? It hallucinated the quote, I had even told it what chapter it was in. Had I not read the book recently maybe I would've believed the hallucinated quote.

And it got me thinking, they sell these AIs as assistants, but it couldn't even look up a passage from a book. This is basic, elementary stuff, it should get it right. I would have fired this assistant right away if it were a person. Not only did it get it totally wrong, it came to me with utmost confidence that this is the quote from the book. Unreliable assistants? That's the product they're trying to sell? Get out of here with that trash. I can't trust it.

[bigstrat2003]

> hallucinations are dramatically less of a problem

No they aren't. The models still hallucinate just like they always did. You cannot trust them, ever, to get something right.

> several mass market use cases have emerged, most notably coding

They aren't really useful for coding based upon the above. Since you can't trust them, you have to carefully review everything they make, which in turn destroys any productivity they could've given you.

> rate of progress has increased

I have yet to see any progress. Opus 4.8 that you get today is no more effective than GPT-3.5 was. Much less would I agree that the rate of progress has increased. Only hype has increased, but there has yet to be a drop of substance.

[lowbloodsugar]

His point is that coding is only a “market” because it is being sold at a loss. Businesses have to pay per-token prices and are saying that the cost is not justified.

Nevertheless, it all misses the point if we get to AI post-scarcity utopia. But thats a big if.

[sumeno]

It doesn't miss the point because if we get to some AI post-scarcity utopia then the companies pouring trillions into it now are never going to make their money back on that investment.

The only way they make their money back is if everyone pays them tons of money for it.

[simianwords]

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

[azakai]

Not the person you are responding to, but here:

> I believe that artificial intelligence has three quarters to prove itself before the apocalypse comes, and when it does, it will be that much worse, savaging the revenues of the biggest companies in tech. Once usage drops, so will the remarkable amounts of revenue that have flowed into big tech, and so will acres of data centers sit unused, the cloud equivalent of the massive overhiring we saw in post-lockdown Silicon Valley.

We have seen 8 quarters since. Has any of that come to pass?

[phkahler]

Even if you see a real bubble or catastrophy in the making, predicting when it will pop is a fools game.

[simianwords]

if you can't predict when it will pop then you should really not predict anything. I can also predict that Google will pop. I won't tell you when but I'll tell you that it will. I'll remain thoroughly unfalsifiable and I'll keep pushing the dates.

[__alexs]

The quality of AI doomerism takes is matched only by the quality of AI boosterism takes. Ed's kind of interesting as a temperature sensor but I don't feel like you can really take anything he writes seriously.

[freejazz]

And its been 3 years of AI boosters telling me that my job as a litigating attorney will not exist in 2 months. Yet here I am, gainfully employed.

[mrkeen]

From your link:

  When asked whether it will be possible to fix Sora's videos after they've been generated, Murati said "eventually," and then couched that by saying "that's what we're trying to figure out...how to use this technology as a tool that people can edit and create with." She promised that there would "eventually" be "more steerability, control and accuracy...and reflecting of intent of what you want." 

  You'll "eventually" be able to add audio to Sora videos, and when asked when Sora's generative videos will be available to the public, she once again said "eventually," and when pushed said that Sora's launch would "definitely be this year, but could be a few months."

  Murati, living in a world of "eventuallies," provided no technical insights, no specifics, and very few details.

And, take a look at https://openai.com/index/sora-is-here/

Please speculate on why OpenAI wouldn't just leave it up (whether or not they were able to improve it).

[supern0va]

I highly recommend folks read Wired's profile on him: https://www.wired.com/story/ai-pr-ed-zitron-profile/

Tim Lee also pointed out that when Ed has posted details on some of his analysis, they have had some....oddities: https://x.com/binarybits/status/2034377838883700953

[gdcbe]

What if you phrase the question from "will AI ever be useful" (a term as utterly vague as "IT") to "will it ever be able to promise the financial gains these companies are hoping? Especially with local models eating their lunch :shrug:

[ericmcer]

Yeah they seem clickable because anything Anti-AI is a bit soothing right now, but he is constantly wrong and usually is pushing the angle of "these businesses aren't even profitable!"

Instantly close the tab as soon as the popup to subscribe to his newsletter pops up.

[Danox]

They ain’t profitable yet. Most of the model maker’s will be gone soon. It’s unsustainable unless you’re Google who has other income coming in to support their hobby, and the Chinese model makers are spending a fraction to be six months behind and many of them will be there for the long-term because they have backup support (government) who is in the race for the long-term.

One other thing that’s working against the model makers is the hardware is getting better and the models are getting smaller and more capable. I don’t think we’re going back to the mainframe days. Local will be the endgame.

Is Ed right? Probably because in the end it’s unsustainable the companies left will be the companies that have income coming from somewhere else and there’s one large tech company that isn’t even participating in the boondoggle unless you count $1 billion dollars a year as participating ultimately there is no moat in AI model making.

Nvidia and Microsoft trying to introduce another Arm processor in a laptop of all things won’t change the tide either.

[jimmaswell]

Why is anti-AI soothing?

[simonw]

Because there are still a huge number of people who would be very relieved if the whole AI thing just went away.

[recursive]

For some of us it is, I suppose as an alternate view to AI booster-ism, particularly if you think the long term effects would be mostly negative.

[raziel2701]

It's seen as an existential threat to young people. If you can't get a job you starve.

[Jtarii]

Gen AI is strictly bad for society.

[jimmaswell]

Can't really agree. It's improved my life more than any other single innovation made in my lifetime.

[Jtarii]

The positives: Some tech nerds got a cool new toy

The negatives: Culture is destroyed, truth is destroyed, democracy is destroyed.

I guess its a wash at the end of the day.

[jimmaswell]

> Culture is destroyed, truth is destroyed, democracy is destroyed.

Just because those things happened in Dune doesn't mean they'll come true. It should be obvious what massive potential the thinking machines have for humanity as a whole.

[lelanthran]

> Can't really agree. It's improved my life more than any other single innovation made in my lifetime.

So? Something can be bad for society while improving your individual lot in life.

[GolfPopper]

From the linked article, "Sora is not going to generate movies." How's Sora doing these days?

[themafia]

> Before you spend 20 minutes reading this article, it's worth understanding that the writer has been posting popular but consistently wrong

So, judge the book by it's cover?

> arguing that AI is failing, is a waste of money, is bad, will never work, etc.

Then the opposite should be easy to prove. AI is succeeding, is efficient, is universally good, and is working everywhere it's tried. Are those true?

[gilbetron]

> So, judge the book by it's cover?

It is literally judging the book by it's author, which is an extremely rationale judgement to make.

[themafia]

> It is literally judging the book by it's author

How is that better?

> which is an extremely rationale judgement to make.

So it's "rational" to take bias into reading? Why even read? If you know what you think and refuse to accept new information then what purpose is there in consuming anything?

You should just read the comments and get a warm fuzzy that the crowd, for the time being, agrees with your intentionally static ideology.

Comments like these obviously hope they can sway the crowd before they can take an unbiased reading of the article. If the author is that wrong then the crowd here should be able to discover that on their own. If the author convinces the crowd then I'd think you'd want to present a better argument than "well, he was wrong _before_." Post hoc, ergo propter hoc, in action.

[bigstrat2003]

That's the exact opposite of rational. It is, in fact, a formal logical fallacy (ad hominem). His argument can be correct even if he himself is not typically correct.

[supern0va]

On the surface, that's quite fair. However, there's one problem: it is much easier to make statements than to verify them, and that asymmetry is part of why the internet has been slowly eroding society.

It's useful/necessary to use past writing/arguments from an author to say whether they should actually receive any further critical evaluation, or be dismissed. We shouldn't say definitively "they're always wrong, so they're wrong now". However, it's reasonable to say: the author has a demonstrated lack of credibility, so we can probably assume they're wrong here, particularly if they have been wrong in this domain so many times before. Or if they happen to be correct, it's probably not strongly demonstrated by their work.

[adampunk]

What's the point of reading someone's writings on a subject where you know they're not typically correct? How would we know what we 'learn' from Ed is right?

[Kye]

He also does PR for AI companies and only really acknowledges this in interviews. As far as I know he never discloses it in his rants.

[syawin]

[flagged]

[tomhow]

Please don't comment like this on HN. We can disagree with people whilst still affording people basic decency; it's a condition of participating here.

If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.