this post was submitted on 09 Mar 2024
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So-called "emergent" behavior in LLMs may not be the breakthrough that researchers think.

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[–] Norgur@fedia.io 27 points 8 months ago (3 children)

What always irks me about those "emergent behavior" articles: no one ever really defines what those amazing"skills" are supposed to be.

[–] General_Effort@lemmy.world 12 points 8 months ago

The term "emergent behavior" is used in a very narrow and unusual sense here. According to the common definition, pretty much everything that LLMs and similar AIs do is emergent. We can't figure out what a neural net does by studying its parts, just like we can't figure out what an animal does by studying its cells.

We know that bigger models perform better in tests. When we train bigger and bigger models of the same type, we can predict how good they will be, depending on their size. But some skills seem to appear suddenly.

Think about someone starting to exercise. Maybe they can't do a pull-up at first, but they try every day. Until one day they can. They were improving the whole time in the various exercises they did, but it could not be seen in this particular thing. The sudden, unpredictable emergence of this ability is, in a sense, an illusion.

For a literal answer, I will quote:

[Emergent abilities appear in an] arithmetic benchmark that tests 3-digit addition and subtraction, as well as 2-digit multiplication. GPT-3 and LaMDA (Thoppilan et al., 2022) have close-to-zero performance for several orders of magnitude of training compute, before performance jumps to sharply above random at [13B parameters] for GPT-3, [68B parameters] for LaMDA. Similar emergent behavior also occurs at around the same model scale for other tasks, such as transliterating from the International Phonetic Alphabet recovering a word from its scrambled letters, and Persian question-answering. Even more emergent abilities from BIG-Bench are given in Appendix E.

[–] anlumo@lemmy.world 11 points 8 months ago (2 children)

One of those things I remember reading was the ability of ChatGPT to translate texts. It was trained with texts in multiple languages, but never translation specifically. Still, it’s quite good at it.

[–] variaatio@sopuli.xyz 3 points 8 months ago (1 children)

That is just its core function doing its thing transforming inputs to outputs based on learned pattern matching.

It may not have been trained on translation explicitly, but it very much has been trained on these are matching stuff via its training material. Since you know what its training set most likely contained..... dictionaries. Which is as good as asking it to learn translation. Another stuff most likely in training data: language course books, with matching translated sentences in them. Again well you didnt explicitly tell it to learn to translate, but in practice the training data selection did it for you.

[–] anlumo@lemmy.world 6 points 8 months ago (1 children)

The data is there, but simpler models just couldn’t do it, even when trained with that data.

Bilingual human children also often can’t translate between their two (or more) native languages until they get older.

[–] bus_factor@lemmy.world 3 points 8 months ago

That's interesting. My trilingual kids definitely translate individual words, but I guess the real bar here is to translate sentences such that the structure is correct for the languages?

[–] bionicjoey@lemmy.ca 2 points 8 months ago

A lot of the training set was probably Wiktionary and Wikipedia which includes translations, grammar, syntax, semantics, cognates, etc.

[–] NounsAndWords@lemmy.world 11 points 8 months ago (1 children)

Emergent behavior is pretty much anything an old model couldn't do that a new model can. Simple reasoning, creating coherent sentences, "theory of mind", basic math, translation, I think are a few examples.

They aren't "amazing" in the sense that a human can't do them, but they are in the sense that a computer is doing it.

[–] admin@lemmy.my-box.dev 5 points 8 months ago

They aren't "amazing" in the sense that a human can't do them, but they are in the sense that a computer is doing it.

... without specifically being trained for it, to be precise.