[bartread]

This trope of proclaiming some critical flaw in the functioning of LLMs with the implication that they therefore should not be used is getting boring.

LLMs are far from perfect but they can be a very useful tool that, used well, can add significant value in spite of their flaws. Large numbers of people and businesses are extracting huge value from the use of LLMs every single day. Some people are building what will become wildly successful businesses around LLM technology.

Yet in the face of this we still see a population of naysayers who appear intent on rubbishing LLMs at any cost. To me that seems like a pretty bad faith dialogue.

I’m aware that a lot of the positive rhetoric, particularly early on after the first public release of ChatGPT was overstated - sometimes heavily so - but taking one set of shitty arguments and rhetoric and responding to it with polar opposite, but equally shitty, arguments and rhetoric for the most part only serves to double the quantity of shitty arguments and rhetoric (and, adding insult to injury, often does so in the name of “balance”).

[pier25]

It's probably the other way around actually.

The average person assumes LLMs are intelligent and all this AI thing will end up replacing them. This has created a distorted perception of the tech which has had multiple consequences. It's necessary to change this perception so that it better adjusts with reality.

[whiplash451]

You are unlikely to reach the average person by posting an analysis of GSM-NoOp on substack.

[SpicyLemonZest]

But I don’t think this result is relevant to that question at all. There’s quite a lot of people in the world who can’t consistently apply formal mathematical reasoning to word problems or reliably multiply large numbers.

[lewhoo]

> Yet in the face of this we still see a population of naysayers who appear intent on rubbishing LLMs at any cost.

What was the cost in this case ? It's just an experiment and I think your reaction is way too emotional for some reason.

[bartread]

It's not emotional: it's bored. This is boring me and therefore I'm becoming irritated with it.

[castigatio]

Well said.

I can understand the incentive for researchers to make provocative claims about the abilities or disabilities of LLM's at a moment in time when there's a lot of attention, money and froth circling a new technology.

I'm a little more stumped on the incentive for people (especially in tech?) to have strong negative opinions about the capabilities of LLM's. It's as if folks feel the need to hold some imaginary line around the sanctity of "true reasoning".

I'd love to see someone rigorously test human intelligence with the same kinds of approaches. You'd end up finding that humans in fact suck at reasoning, hallucinate frequently and show all kind of erratic behaviour in our processing of information. Yet somehow - we find other humans incredibly useful in our day to day lives.

[bbor]

To be fair, and in case it isn’t obvious: this is kinda this guy’s whole schtick. And has been for decades:

  The inability of standard neural network architectures to reliably extrapolate — and reason formally — has been the central theme of my own work back to 1998 and 2001, and has been a theme in all of my challenges to deep learning, going back to 2012, and LLMs in 2019.

Basically he sees his role in human development as a Diogenes-esque figure, a cynic whose job is to loudly and frequently point out flaws in the rising tide of connectionist AI research — to throw a plucked chicken at Socrates to disprove his description of humans as featherless bipeds, so to speak. Except now, for better or worse, the poultry-tossing has been replaced by polemics on Twitter and Substack.

The point isn’t to contribute to expert-level discourse with incremental clarifications (like most academics do), but rather to keep the overall zeitgeist around the technology in check. I absolutely agree that he’s not a useful figure for engineers trying to employ the tools available to them; I think his audience is more like “voters” or “university donors” or “department heads” — in other words, people fretting over long term directions.

When he started connectionism was the underdog camp, and he’s lived to see it take over AI to such an extreme extent that most laypeople would honestly say that AI didn’t exist until, like, 5 years ago. I think we can all relate to how frustrating that must feel!

Plus he’s fun. He’s not quite at guru levels of dishonesty, but he’s still got that guru flair for the dramatic. He’s worth a substack sub just to get the flip side of every big event, IMO!

[bartread]

Thank you: this is really helpful context that, in the case of this author, I wasn't aware of. To be honest I didn't even look at his name, I just skimmed the piece and had that sort of, "oh, it's this all over again," reaction.

> When he started connectionism was the underdog camp, and he’s lived to see it take over AI to such an extreme extent that most laypeople would honestly say that AI didn’t exist until, like, 5 years ago. I think we can all relate to how frustrating that must feel!

I absolutely agree.

In some sense the definition of AI has always evolved with time - think of how much of what was considered AI research at places like MIT in the 1950s is now thought of as being just algorithms and data structures, for example - but it has infuriated me how quickly the majority of people have equated AI with, really, just LLMs, leaving much of the rest of the field out in the cold, as it were.

It can be kind of frustrating as well when using an LLM isn't going to be the best approach - where for example ML might be a better approach with large numeric datasets, but it doesn't even get a look in in the conversation, and isn't seen as cutting edge. In some sense, that's fair, a lot of what people do with ML nowadays isn't cutting edge, but in business, it doesn't have to be cutting edge, it just has to be useful and deliver value.

Definitely annoying.

[bbor]

Yup, well said. If you think we engineers have it tough, think of the poor AI professors — the go-to book for AI survey courses (Russel and Norvig) is maybe 75% symbolic approaches, and students are surely up in arms about that now that everyone’s talking about LLMs.

I spend a lot of time “defending” AI, and I do enjoy pointing out that basically any computer program of any kind is AI, including websites. We don’t even have a good definition of intelligence for people, it’s pure hubris to try to put a solid one onto computers!

Of course, the old (90s?) adage holds true, and should be plastered on billboards across SV, IMO: “AI is whatever hasn't been done yet.” - Larry Tesler https://en.wikipedia.org/wiki/AI_effect

[apwell23]

> Large numbers of people and businesses are extracting huge value from the use of LLMs every single day

No they aren't. If they really did we would see those number in qtrly reports.

[bartread]

The impact of LLMs for many sectors is deflationary, which means you specifically won't see those numbers in quarterly reports. Doesn't mean that value isn't being extracted with LLMs but rather that it's being eroded elsewhere. What you'll see is companies that don't leverage the benefits gradually being left behind.

[apwell23]

Not sure what this comment means. There would be losers but no winners ? You mean there would be a loss of gdp from llms ?