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Has LLM killed traditional NLP?

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31–40 of 159 posts

Re: Has LLM killed traditional NLP?

#31
post #6

No, it has not and will not in the foreseeable future. This is one of my responsibilities at work. LLMs are not feasible when you have a dataset of 10 million items that you need to classify relatively fast and at a reasonable cost. LLMs are great at mid-level complexity tasks given a reasonable volume of data - they can take away the tedious job of figuring out what you are looking at or even come up with some basic…

That’s sort of like asking a horse and buggy driver whether automobiles are going to put them out of business. I think for the most part, casual nlp is dead because of LLMs. And LLM costs are going to plummet soon, so large scale nlp that you’re talking about is probably dead within 5 years or less. The fact that you can replace programmers with prompts is huge in my opinion so no one needs to learn an nlm API anymor…

> The fact that you can replace programmers with prompts

No, you can't. The only thing LLM's replace is internet commentators.

Re: Has LLM killed traditional NLP?

#32
post #6

No, it has not and will not in the foreseeable future. This is one of my responsibilities at work. LLMs are not feasible when you have a dataset of 10 million items that you need to classify relatively fast and at a reasonable cost. LLMs are great at mid-level complexity tasks given a reasonable volume of data - they can take away the tedious job of figuring out what you are looking at or even come up with some basic…

[deleted]

Re: Has LLM killed traditional NLP?

#33

Earlier quoted context omitted.

I think your intuition on this might be lagging a fair bit behind the current state of LLMs. System message: answer with just "service" or "product" User message (variable): 20 bottles of ferric chloride Response: product Model: OpenAI GPT-4o-mini $0.075/1Mt batch input * 27 input tokens * 10M jobs = $20.25 $0.300/1Mt batch output * 1 output token * 10M jobs = $3.00 It's a sub-$25 job. You'd need to be doing 20 times…

>You'd need to be doing 20 times that volume every single day to even start to justify hiring an NLP engineer instead. How much for the “prompt engineer”? Who is going to be doing the work and validating the output?

Prompt engineering is less and less of an issue the simpler the job is and the more powerful the model is. You also don't need someone with deep nlp knowledge to measure and understand the output.

Re: Has LLM killed traditional NLP?

#34

Earlier quoted context omitted.

I think your intuition on this might be lagging a fair bit behind the current state of LLMs. System message: answer with just "service" or "product" User message (variable): 20 bottles of ferric chloride Response: product Model: OpenAI GPT-4o-mini $0.075/1Mt batch input * 27 input tokens * 10M jobs = $20.25 $0.300/1Mt batch output * 1 output token * 10M jobs = $3.00 It's a sub-$25 job. You'd need to be doing 20 times…

>You'd need to be doing 20 times that volume every single day to even start to justify hiring an NLP engineer instead. How much for the “prompt engineer”? Who is going to be doing the work and validating the output?

You do not need a prompt engineer to create: “answer with just "service" or "product"”

Most classification prompts can be extremely easy and intuitive. The idea you have to hire a completely different prompt engineer is kind of funny. In fact you might be able to get the llm itself to help revise the prompt.

Re: Has LLM killed traditional NLP?

#35

Earlier quoted context omitted.

>You'd need to be doing 20 times that volume every single day to even start to justify hiring an NLP engineer instead. How much for the “prompt engineer”? Who is going to be doing the work and validating the output?

All software engineers are (or can be) prompt engineers, at least to the level of trivial jobs like this. It's just an API call and a one-liner instruction. Odds are very good at most companies that they have someone on staff who can knock this out in short order. No specialized hiring required.

> ..and validating the output?

You glossed over the meat of the question.

Re: Has LLM killed traditional NLP?

#36
post #3

This article seems to be paywalled unfortunately. While LLMs are very useful when the tasks are complex and/or there is not a lot of training data, I still think traditional NLP pipelines have a very important role to play, including when: - Depending on the complexity of the task and the required results, SVMs or BERT can be enough in many cases and take much lower resources, especially if there is a lot of training…

https://archive.is/J53CE

Re: Has LLM killed traditional NLP?

#37
post #26

Earlier quoted context omitted.

> LLM costs Inference costs, not training costs. > The fact that you can replace programmers You can’t… not for any real project. For quick mockups they’re serviceable > That’s sort of like asking a horse and buggy driver whether automobiles Kind of an insult to OP, no? Horse and buggy drivers were not highly educated experts in their field. Maybe take the word of domain experts rather than AI company marketing teams…

> Maybe take the word of domain experts rather than AI company marketing teams. Appeal to authority is a well known logical fallacy. I know how dead NLP is personally because I’ve never been able to get NLP working but once ChatGPT came around, I was able to classify texts extremely easily. It’s transformational. I was able to get ChatGPT to classify posts based on how political it was from a scale of 1 to 10 and whi…

“I couldn’t be bothered learning something, and now I don’t have to! Checkmate!”

While LLM’s can have their uses, let’s not get carried away.

Re: Has LLM killed traditional NLP?

#38

Earlier quoted context omitted.

That’s sort of like asking a horse and buggy driver whether automobiles are going to put them out of business. I think for the most part, casual nlp is dead because of LLMs. And LLM costs are going to plummet soon, so large scale nlp that you’re talking about is probably dead within 5 years or less. The fact that you can replace programmers with prompts is huge in my opinion so no one needs to learn an nlm API anymor…

> The fact that you can replace programmers with prompts No, you can't. The only thing LLM's replace is internet commentators.

As I explained below, I avoided having to learn anything about ML, PyTorch or any other APIs when trying to classify posts based on how political they were and which affiliation they were. That was holding me back and it was easily replaced by an llm and a prompt. Literally took me minutes what would have taken days or weeks and the results are more than good enough.

Re: Has LLM killed traditional NLP?

#39
post #26

Earlier quoted context omitted.

> LLM costs Inference costs, not training costs. > The fact that you can replace programmers You can’t… not for any real project. For quick mockups they’re serviceable > That’s sort of like asking a horse and buggy driver whether automobiles Kind of an insult to OP, no? Horse and buggy drivers were not highly educated experts in their field. Maybe take the word of domain experts rather than AI company marketing teams…

> Maybe take the word of domain experts rather than AI company marketing teams. Appeal to authority is a well known logical fallacy. I know how dead NLP is personally because I’ve never been able to get NLP working but once ChatGPT came around, I was able to classify texts extremely easily. It’s transformational. I was able to get ChatGPT to classify posts based on how political it was from a scale of 1 to 10 and whi…

> Appeal to authority is a well known logical fallacy.

I did not make an appeal to authority. I made an appeal to expertise.

It’s why you’d trust a doctor’s medical opinion over a child’s.

I’m not saying “listen to this guy because their captain of NLP” I’m saying listen because experts have spent years of hands on experience with things like getting NLP working at all.

> I know how dead NLP is personally because I’ve never been able to get NLP working

So you’re not an expert in the field. Barely know anything about it, but you’re okay hand waving away expertise bc you got a toy NLP Demo working…

That’s great, dude.

> I was able to get ChatGPT to classify posts based on how political it was from a scale of 1 to 10

And I know you didn’t compare the results against classic NLP to see if there was any improvements because you don’t know how…

Re: Has LLM killed traditional NLP?

#40

Earlier quoted context omitted.

That’s sort of like asking a horse and buggy driver whether automobiles are going to put them out of business. I think for the most part, casual nlp is dead because of LLMs. And LLM costs are going to plummet soon, so large scale nlp that you’re talking about is probably dead within 5 years or less. The fact that you can replace programmers with prompts is huge in my opinion so no one needs to learn an nlm API anymor…

> The fact that you can replace programmers with prompts No, you can't. The only thing LLM's replace is internet commentators.

No you can’t; LLMs are dog shit at internet banter, too neutered
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