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When ChatGPT broke the field of NLP: An oral history

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Re: When ChatGPT broke the field of NLP: An oral history

#141

Post by horsh1 »

simianwords wrote: post #139
larodi wrote: post #135

Earlier quoted context omitted.

Let's admit it - overnight it became much much harder to be a convincing professor, given each student can use GPTs of all sorts to contradict or otherwise intimidate you. Only a seasoned professor knows the feeling of being bullied by a smart-ass student. Which brings down the total value, the incentive, to teach, and also given the avoidance GPTs silently imprint in students. I mean - why write a program/paper/rese…

Not totally related but I have wondered how someone who thinks they are an expert in a field may deal with contradictions presented by GPT. For example, you may consider yourself an expert on some niche philosophy like say Orientalism. A student can now contradict any theories you can come up with using GPT and the scary thing is that they will be sensible contradictions. I feel like the bar to consider yourself an e…

Why in this story students use GPT and professors don't?

If you are an expert -- sit down and start working with GPT on your own. See what it can and what it can not do. See where it helps. See where it hands down lose.

Re: When ChatGPT broke the field of NLP: An oral history

#142

Post by simianwords »

horsh1 wrote: post #141
simianwords wrote: post #139

Earlier quoted context omitted.

Not totally related but I have wondered how someone who thinks they are an expert in a field may deal with contradictions presented by GPT. For example, you may consider yourself an expert on some niche philosophy like say Orientalism. A student can now contradict any theories you can come up with using GPT and the scary thing is that they will be sensible contradictions. I feel like the bar to consider yourself an e…

Why in this story students use GPT and professors don't? If you are an expert -- sit down and start working with GPT on your own. See what it can and what it can not do. See where it helps. See where it hands down lose.

You are right - this is a new activity professors have to pick up. A latent point in my previous comment was that maybe some professors have not as much expertise as may be required. Now that this expertise is sort of democratised there's more pressure on professors to get better.

Re: When ChatGPT broke the field of NLP: An oral history

#143

Post by charcircuit »

Al-Khwarizmi wrote: post #140
larodi wrote: post #135

Earlier quoted context omitted.

Let's admit it - overnight it became much much harder to be a convincing professor, given each student can use GPTs of all sorts to contradict or otherwise intimidate you. Only a seasoned professor knows the feeling of being bullied by a smart-ass student. Which brings down the total value, the incentive, to teach, and also given the avoidance GPTs silently imprint in students. I mean - why write a program/paper/rese…

Yes, my comment focused on NLP research but the importance of university teaching has also taken a hit - not that I fear bullying, but now students can have a dedicated custom teacher with infinite time and patience and that can answer questions at 3 AM, and obviously that reduces the relevance of the professor. While the human interaction in in-person teaching still provides some exclusive value, demand logically sh…

>but they wouldn't have been possible without the academics that kept working on neural networks while that field was actively scorned during the 90s-2000s AI winter

The bottleneck was on compute power. Industry would have also worked on neural networks once the compute power for it existed.

Re: When ChatGPT broke the field of NLP: An oral history

#144

Post by karel-3d »

Al-Khwarizmi wrote: post #132

As an NLP professor, yes, I think we're mostly screwed - saying LLMs are a dead end or not a big deal, like some of the interviewed say, is just wishful thinking. A lot of NLP tasks that were subject of active research for decades have just been wiped out. Ironically, the tasks that still aren't solved well by LLMs and can still have a few years of life in them are the most low-level ones, that had become unfashionab…

I used to study NLP but before transformers, and now I don't work with NLP/ML/LLMs at all. Can you explain to me this view?

LLMs are NLP? We have a model that works, and that works great for many people and many different usages, shouldn't NLP be at its top now? LLMs are not conceptionally that different to other models?

I worked with GIZA/MOSES statistical MT back in the day during my studies, it's at the end of the day just matrices that you don't really understand, same as with LLMs?

Re: When ChatGPT broke the field of NLP: An oral history

#145

Post by aitchnyu »

teruakohatu wrote: post #31

I am in academia and worked in NLP although I would describe myself as NLP adjacent. I can confirm LLMs have essentially confined a good chunk of historical research into the bin. I suspect there are probably still a few PhD students working on traditional methods knowing full well a layman can do better using the mobile ChatGPT app. That said traditional NLP has its uses. Using the VADER model for sentiment analysis…

Does it work for sarcasm and typos which real world people tend to do?

Re: When ChatGPT broke the field of NLP: An oral history

#146

Post by Al-Khwarizmi »

karel-3d wrote: post #144
Al-Khwarizmi wrote: post #132

As an NLP professor, yes, I think we're mostly screwed - saying LLMs are a dead end or not a big deal, like some of the interviewed say, is just wishful thinking. A lot of NLP tasks that were subject of active research for decades have just been wiped out. Ironically, the tasks that still aren't solved well by LLMs and can still have a few years of life in them are the most low-level ones, that had become unfashionab…

I used to study NLP but before transformers, and now I don't work with NLP/ML/LLMs at all. Can you explain to me this view? LLMs are NLP? We have a model that works, and that works great for many people and many different usages, shouldn't NLP be at its top now? LLMs are not conceptionally that different to other models? I worked with GIZA/MOSES statistical MT back in the day during my studies, it's at the end of the…

NLP is indeed at its top, NLP professors aren't :)

Imagine if you had stayed in academia and kept working in MT for the last two decades. First of all, now you would see how LLMs render all your work pretty much obsolete. That's already hard for many people. Not so much for me, as I consider myself to be rather adaptable, and maybe not for you either - you can embrace the new thing and start working on it yourself, right?

But the problem is that you can't. The main issue is not lack of explainability, but the sheer resources needed. In academia we can't run, let alone train, anything within even one or two orders of magnitude of ChatGPT. We can work with toy models, knowing that we won't get even remotely near the state of the art (many are now doing this, with the excuse of "green AI", sustainability and such, but that won't even hold much longer). Or we can work with the likes of ChatGPT as plain users, but then we are studying the responses of an "oracle" that we don't even have control of, and it starts looking more like religion than science.

Ten years ago an academic could beat the state of the art in MT and many other NLP tasks, now for many tasks that's just impossible (unless we count coming up with some clever prompt engineering, but again, religion). For those of us who were in this field because we liked it, not only to make a living, research has become quite unfulfilling.

Re: When ChatGPT broke the field of NLP: An oral history

#147

Post by justanotherjoe »

karel-3d wrote: post #144
Al-Khwarizmi wrote: post #132

As an NLP professor, yes, I think we're mostly screwed - saying LLMs are a dead end or not a big deal, like some of the interviewed say, is just wishful thinking. A lot of NLP tasks that were subject of active research for decades have just been wiped out. Ironically, the tasks that still aren't solved well by LLMs and can still have a few years of life in them are the most low-level ones, that had become unfashionab…

I used to study NLP but before transformers, and now I don't work with NLP/ML/LLMs at all. Can you explain to me this view? LLMs are NLP? We have a model that works, and that works great for many people and many different usages, shouldn't NLP be at its top now? LLMs are not conceptionally that different to other models? I worked with GIZA/MOSES statistical MT back in the day during my studies, it's at the end of the…

Its not the same at all. Llm is big yes and thats part of it. But llm is small compared to equivalent performance machine with something like ngram statistical models. You'd need the whole universe. Or something prohibitive like that. And itd still be worse. People don't like it but LLMs 'understand' texts in a very real meaning of the word. Because that's the most compressive way to do the task it's trained to. Is it the same as human understanding? Most likely not, but that complain is cheating.

Re: When ChatGPT broke the field of NLP: An oral history

#148

Post by moffkalast »

Cheer2171 wrote: post #38
teruakohatu wrote: post #31

I am in academia and worked in NLP although I would describe myself as NLP adjacent. I can confirm LLMs have essentially confined a good chunk of historical research into the bin. I suspect there are probably still a few PhD students working on traditional methods knowing full well a layman can do better using the mobile ChatGPT app. That said traditional NLP has its uses. Using the VADER model for sentiment analysis…

That's because VADER is just a dictionary mapping each word to a single sentiment weight and adding it up with some basic logic for negations and such. There's an ocean of smaller NLP ML between that naive approach and LLMs. LLMs are trained to do everything. If all you need is a model trained to do sentiment analysis, using VADER over something like DistilBERT is NLP malpractice in 2025.

> dictionary mapping each word to a single sentiment weight

That seems to me like it would flat out fail on sarcasm. How is that still considered a usable method today?

Re: When ChatGPT broke the field of NLP: An oral history

#149

Post by lupusreal »

meroes wrote: post #11
aidenn0 wrote: post #4

Earlier quoted context omitted.

Some people will never be convinced that a machine demonstrates intelligence. This is because for a lot of people, intelligence exists a subjective experience that they have and the belief that others have it too is only inasmuch as others appear to be like the self.

It doesn’t mean they tie intelligence to subjective experience. Take digestion. Can a computer simulate digestion, yes. But no computer can “digest” if it’s just silicon in the corner of an office. There are two hurdles. The leap from simulating intelligence to intelligence, and the leap from intelligence to subjective experience. If the computer gets attached to a mechanism that physically breaks down organic materi…

> And the claim other humans don’t have subjective experience is such non-starter.

There is no empirical test for the subjective experience of consciousness. You can't even prove to anybody else that you have it. We assume other people experience as we ourselves do as a basic decency we extend to other humans. This is a good thing, but it's essentially faith not science.

As for machines not having it, I'm fine with that assumption, but until there can be some sort of empirical test for it, it's not science. Thankfully, it's also not relevant to any engineering matter. Whether the machines have a subjective experience in any way comparable to our own doesn't touch any question about what demonstrable capabilities or limitations they have. We don't need to know if the computer has a ""soul"" to know if the computer can be a solution to any given engineering problem. Whether machines can have subjective experience shouldn't be considered an important question to engineers; let theologians waste their time fruitlessly debating that.

Re: When ChatGPT broke the field of NLP: An oral history

#150

Post by [deleted] »

Al-Khwarizmi wrote: post #146
karel-3d wrote: post #144

Earlier quoted context omitted.

I used to study NLP but before transformers, and now I don't work with NLP/ML/LLMs at all. Can you explain to me this view? LLMs are NLP? We have a model that works, and that works great for many people and many different usages, shouldn't NLP be at its top now? LLMs are not conceptionally that different to other models? I worked with GIZA/MOSES statistical MT back in the day during my studies, it's at the end of the…

NLP is indeed at its top, NLP professors aren't :) Imagine if you had stayed in academia and kept working in MT for the last two decades. First of all, now you would see how LLMs render all your work pretty much obsolete. That's already hard for many people. Not so much for me, as I consider myself to be rather adaptable, and maybe not for you either - you can embrace the new thing and start working on it yourself, r…

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