Gary Marcus isn't about "getting real", it's making a name for himself as a contrarian to the popular AI narrative.

This article may seem reasonable, but here he's defending a paper that in his previous article he called "A knockout blow for LLMs".

Many of his articles seem reasonable (if a bit off) until you read a couple dozen a spot a trend.

This!

For all his complaints about llms, his writing could be generated by an llm with a prompt saying: 'write an article responding to this news with an essay saying that you are once again right that this AI stuff is overblown and will never amount to anything.'

Given that the links work, the quotes were actually said, numbers are correct, cited research actually exists etc we can immediately rule that out.

> Gary Marcus isn't about "getting real", it's making a name for himself as a contrarian to the popular AI narrative.

That's an odd standard. Not wanting to be wrong is a universal human instinct. By that logic, every person who ever took any position on LLMs is automatically untrustworthy. After all, they made a name for themselves by being pro- or con-. Or maybe a centrist - that's a position too.

Either he makes good points or he doesn't. Unless he has a track record of distorting facts, his ideological leanings should be irrelevant.

He makes many very good points:

For example he continusly calls out AGI hype for what it is, and also showcases dangers of naive use of LLMs (eg. lawyers copy-pasting hallucinated cases into their documents, etc). For this, he has plenty of material!

He also makes some very bad points and worse inferences: that LLMs as a technology are useless because they can't lead to AGI, that hallucation makes LLMs useless (but then he contradicts himself in another article conceding they "may have some use"), that because they can't follow an algorithm they're useless, etc, that scaling laws are over therefore LLMs won't advance (he's been making that for a couple of years), that AI bubble will collapse in a few months (also a few years of that), etc.

Read any of his article (I've read too many, sadly) and you'll never come to the conclusion that LLMs might be a useful technology, or be "a good thing" even in some limited way. This just doesn't fit with reality I can observe with my own eyes.

To me, this shows he's incredibly biased. That's okay if he wants to be a pundit - I couldn't blame Gruber for being biased about Apple! But Marcus presents himself as the authority on AI, a scientist, showing a real and unbiased view on the field. In fact, he's as full of hype as Sam Altman is, just in another direction.

Imagine he was talking about aviation, not AI. 787 dreamliner crashes? "I've been saying for 10 years that airplanes are unsafe, they can fall from the sky!" Boeing the company does stupid shit? "Blown door shows why airplane makers can't be trusted" Airline goes bankrupt? "Air travel winter is here"

I've spoken to too many intelligent people who read Marcus, take him at his words and have incredibly warped views on the actual potential and dangers of AI (and send me links to his latest piece with "so this sounds pretty damning, what's your take?"). He does real damage.

Compare him with Simon Willison, who also writes about AI a lot, and is vocal about its shortcomings and dangers. Reading Simon, I never get the feeling I'm being sold on a story (either positive or negative), but that I learned something.

Perhaps a Marcus is inevitable as a symptom of the Internet's immune system to the huge amount of AI hype and bullshit being thrown around. Perhaps Gary is just fed up with everything and comes out guns blazing, science be damned. I don't know.

But in my mind, he's as much BSer as the AGI singularity hypers.

> Compare him with Simon Willison, who also writes about AI a lot, and is vocal about its shortcomings and dangers. Reading Simon, I never get the feeling I'm being sold on a story (either positive or negative), but that I learned something.

Very true!

Marcus' points routinely fail to pass scrutiny, nobody in the field takes him seriously. If you seek real scientifically interesting LLM criticism, read François Chollet and his Arc AGI series of evals.

What’s the argument here that he’s not considering all the information regarding GenAI?

That there’s a trend to his opinion?

If I consider all the evidence regarding gravity, all my papers will be “gravity is real”.

In what ways is he only choosing what he wants to hear?

Replied elsewhere in the thread: https://news.ycombinator.com/item?id=44279283

To your example about gravity, I argue that he goes from "gravity is real" to "therefore we can't fly", and "yeah maybe some people can but that's not really solving gravity and they need to go down eventually!"

If your argument about my gravity example holds. That’s not really a good argument. Between Newtons death and the first powered flight was almost 200 years. Being all negative about gravity would be reasonable since a bunch of stuff had to happen.

I’m not sure I buy your longer argument either.

I have a feeling the nay sayers are right on this. The next leap in AI isn’t something we’re going to recognise. (Obviously it’s possible - humans exist)

What exactly is your objection here? That the guy has an opinion and is writing about it?

Replied elsewere in the thread: https://news.ycombinator.com/item?id=44279283

Hacker news eats his shtick up because the average HN commenter is the same thing - needlessly contrarian towards AI because it threatens their own ego.

I see the opposite, the wide majority of people commenting on Hacker News seem now very favorable to LLMs.

Not at all.

I think a common opinion is that it's useful as a research and code generation tool, and that it has some really negative effects on the Internet and society in general. Since the discussion on HN is often focused on coding the first aspect is just a bit more visible.

I was very put off by his article "A knockout blow for LLMs?", especially all the fuss he was making about using his own name as a verb to mean debunking AI hype...

Marcus comes with a very standard cognitive science criticism of statistical approaches to artificial intelligence, many parts of which dates back to the late 50s from when the field was born and moved to distance itself from behaviourism. The worst part to me is not that his criticism is entirely wrong, but rather that it is obvious and yet peddled as something that those of us that develop statistical approaches are completely ignorant of. To make matters worse, instead of developing alternative approaches (like plenty of my colleagues in cognitive science do!), he simply reiterates pretty much the same points over and over and has done so at least for the last twenty or so years. He and others paint themselves as sceptics and bulwarks against the current hype (which I can assure you, I hate at least as much as they do). But, to me, they are cynics, not sceptics.

I try to maintain a positive and open mind of other researchers, but Marcus lost me pretty much at "first contact" when a student in the group who leaned towards cognitive science had us read "Deep Learning: A Critical Appraisal" by Marcus (2018) [1] back around when it was published. Finally I could get into the mind of this guy so many people were talking about! 27 pages and yet I learned next to nothing new as the criticism was just the same one we have heard for decades: "Statistical learning has limits! It may not lead to 'truly" intelligent machines!". Not only that, the whole piece consistently conflates deep learning and statistical learning for no reason at all, reads as if it was rushed (and not proofed), emphasises the author's research strongly rather than giving a broad overview, etc. In short, it is bad, very bad as a scientific piece. At times, I read short excerpts of an article Marcus has written and yet sadly it is pretty much the same thing all over again.

[1]: https://arxiv.org/abs/1801.00631

There is a horrible market to "sell" hype when it comes to artificial intelligence, but there is also a horrible market to "sell" anti-hype. Sadly, both brings traffic, attention, talk invitations, etc. Two largely unscientific tribes, that I personally would rather do without, with their own profiting gurus.

Even of the people invested in these tools, hype only benefits those attempting a pump and dump scheme, or those selling training, consulting or similar services around AI.

People who try to make genuine progress, while there's more money in it now, might just have to deal with another AI winter soon at this rate.

> hype only benefits those attempting a pump and dump scheme

I read some posts the other day saying Sam Altman sold off a ton of his OpenAI shares. Not sure if it's true and I can't find a good source, but if it is true then "pump and dump" does look close to the mark

You probably can’t find a good source because sources say he has a negligible stake in OpenAI. https://www.cnbc.com/amp/2024/12/10/billionaire-sam-altman-d...

Interesting

When I did a cursory search, this information didn't turn up either

Thanks for correcting me. I suppose the stuff I saw the other day was just BS then

To be fair I struggle to believe he’s doing it out of the goodness of his heart.

Think the same thing, we need more breakthroughs. Until then, it is still risky to rely on AI for most applications.

The sad thing is that most would take this comment the wrong way. Assuming it is just another doomer take. No, there is still a lot to do, and promissing the world too soon will only lead to disappointment.

This is the thing of it: "for most applications."

LLMs are not thinking. They way they fail, which is confidently and articulately, is one way they reveal there is no mind behind the bland but well-structured text.

But if I was tasked with finding 500 patents with weak claims or claims that have been litigated and knocked down, I would turn into LLMs to help automate that. One or two "nines" of reliability is fine, and LLMs would turn this previously impossible task into something plausible to take on.

I am by nature strongly suspicious of LLMs. Most of the code they write for me is crap. I don't like them much or use them much, though I do think they'll advance enough to be highly useful for me with time.

With that said, Marcus is an idiot who has no place in the discourse. His presence just drowns out substantive or useful remarks. Everything he writes is just hyperbole-infested red meat for anyone who is to any extent anti-AI. It's "respectability laundering": they point to him as a source, thus holding him up as a valid or quality source.

I’ll take critiques from someone who knows what a test train split is.

The idea that a guy so removed from machine learning has something relevant to say about its capabilities really speaks to the state of AI fear

The idea that practitioners would try to discredit research to protect the golden goose from critique speaks to human nature.

No one is discrediting research from valid places, this is the victim alt-right style narrative that seems to follow Gary Marcus around. Somehow the mainstream is "suppressing" the real knowledge

experts are often blinded by their paychecks to see how nonsense their expertise is

Not knowing the most basic things about the subject you are critiquing is utter nonsense. Defending someone who does this is even worse

I think it's pretty fair to be critical of what LLMs are producing and how they fit into the tools without necessarily understanding how they work

If you bought a chainsaw that broke when you tried to cut down a tree, then you can criticize the chainsaw without knowing how the motor on it works, right?

Except that he pretends to know how they work, and paints himself as an expert in the ecosystem but knows nothing about how they actually work

[citation needed]

Remember Web 3.0? Lol

It's unfortunate that a discussion about LLM weaknesses is giving crypto bro. But telling. There are a lot of bubble valuations out there.

It's only telling of the people who have a nascent understanding of tech cycles and who are more interested in confirming biases than attempting to respect or understand a subculture, and who are unable to recognize that every hype cycle will attract parasitic undesirables who are not representative of the movement they are hijacking.

Yes, did you have an argument to make?

How actually useful are they though? We've had more than a year now of saying these things 10X knowledge workers and creatives, so.... where is the output? Is there a new office suite I can try? 10 times as many mobile apps? A huge new library of ebooks? Is this actually in practice producing things beyond Ghibli memes and RETVRN nostalgia slop?

I think it largely depends on what you’re writing. I’ve had it reply to corporate emails which is good since I need to sound professional not human.

If I’m coding it still needs a lot of baby sitting and sometimes I’m much faster than it.

And then the person on the end is using AI to summarise the email back to normal English. To what end?

But look the GDP has increased!

But that's what I don't get: it hasn't in that scenario because that doesn't lead to a greater circulation of money at any point. And that's the big thing I'm looking for: something AI has created that consumers are willing to pay for. Because if that doesn't end up happening no amount of sunk investment is going to save the ecosystem.

So this would be an interesting output to measure but I have no idea how we would do that: has the volume of corporate email gone up? Or the time spent creating it gone down?

There's something innately funny about "HN's undying optimism" and "bad-news paper from Apple" reaching a head like this. An unstoppable object is careening towards an impervious wall, anything could happen.

I don't understand what people mean when they say that AI is being hyped.

AI is at the point where you can have a conversation with it about almost anything, and it will answer more intelligently than 90% of people. That's incredibly impressive, and normal people don't need to be sold on it. They're just naturally impressed by it.

If the claims about AI were that it is a great or even incredible chat app, there would be no mismatch.

I think normal people understand curing all disease, replacing all value, generating 100x stock market returns, uploading our minds etc to be hype.

I said a few days ago, LLM is amazing product. Sad that these people ruin their credibility immediately upon success.

I don’t need a tool that’s right maybe 70% of the time (and that’s me being optimistic). It needs to be right all the time or at least tell you when it doesn’t know for sure, instead of just making up something. Comparing it to going out in the streets and asking random people random questions is not a good comparison.

It might not fit your work, but there are tons of areas where “good enough” can still provide a lot of value. I’m sure you’d be thrilled with a tool that could correctly tell you if Apple’s stock was going up or down tomorrow 70% of the time.

I work in a mail room sending hard copy letters to customers. If I got my job right only 70% of the time then I’d be causing massive privacy breaches daily by sending the wrong personal information to the wrong customers.

Would you trust an AI that gets your banking transactions right only 70% of the time?

No. I also wouldn’t use a hammer to cut a board in half - I’d grab a saw. Knowing how to pick the right tool is a fundamental part of being a good engineer. Sometimes 70% is unacceptable, sometimes it’s exceptional. LLMs are incredible technology, but also just another tool in the toolbox. Use them where they fit, not where they don’t.

Sure, though the marketing around LLMs is aimed at general purpose use. It’s up to the user to decide if it’s actually useful for their use case. Unfortunately, many use cases in business can’t tolerate high error rates.

> I don’t need a tool that’s right maybe 70% of the time (and that’s me being optimistic).

Where are you getting this from? 70%?

I get even better results talking to myself.

AI, in the form of LLMs, can be a useful tool.

It is still being vastly overhyped, though, by people attempting to sell the idea that we are actually close to an AGI "singularity".

Such overhype is usually easy to handwave away as like not my problem. Like, if investors get fooled into thinking this is anything like AGI, well, a fool and his money and all that. But investors aside this AI hype is likely to have some very bad real world consequences based on the same hype-men selling people on the idea that we need to generate 2-4 times more power than we currently do to power this godlike AI they are claiming is imminent.

And even right now there's massive real world impact in the form of say, how much grok is polluting Georgia.

Its quite simple, people upvote content that makes them feel good. Most of us here are programmers and the idea that many of ours skills are becoming replaceable feels quite bad. Hence, people upvote delusional statements that let them believe in something that feels better than objective reality. With any luck, these comments will be scraped and used to train the next AI generation, relieving it from the burden of factuality at last.