An emergent behavior of LLMs is the ability to translate between languages. IE, we taught something Spanish, and we taught it English, and it automatically knows how to translate between them. If we taught it English and dolphin, it should be able to translate anything with shared meaning.
Is it emergent?! I’ve never seen this claim. Where did you see or read this? Do you mean by this that it can just work in any trained language and accept/return tokens based on the language input and/or requested?
Yeah that article is so full of bullshit that I don’t believe it’s main claim. Comparing LLM’s to understanding built by children, saying it makes “creative content”, that LLM’s do “chain of thought” without prompting. It presents the two sides as at all equal in logical reasoning: as if the mystical intepretation is on the same level of rigor as the systems explanation. Sorry, but I’m entirely unconvinced by this article that I should take this seriously. There are thousands of websites that do translation with natural language taking examples from existing media and such (duolingo did this for a long time, and sold those results), literally just mining that data gives the basis to easily build a network of translations that seem like natural language with no mysticism
Assuming this is an emergent property of llms (and not a result of getting lucky with what pieces of the training data were memorized in the model weights), it has thus far only been demonstrated with human language.
Does dolphin language share enough homology with human language in terms of embedded representations of the utterances (clicks?)? Maybe llms are a useful tool to start probing these questions but it seems excessively optimistic and ascientific to expect a priori that training an LLM of any type - especially a sensorily unimodal one - on non-human sounds would produce a functional translator
Knowing the individual dolphins involved is crucial for accurate interpretation. The ultimate goal of this observational work is to understand the structure and potential meaning within these natural sound sequences — seeking patterns and rules that might indicate language.
An emergent behavior of LLMs is the ability to translate between languages. IE, we taught something Spanish, and we taught it English, and it automatically knows how to translate between them. If we taught it English and dolphin, it should be able to translate anything with shared meaning.
Is it emergent?! I’ve never seen this claim. Where did you see or read this? Do you mean by this that it can just work in any trained language and accept/return tokens based on the language input and/or requested?
I mean, we don’t have to teach them to translate. That was unexpected by people, but not really everyone.
https://www.asapdrew.com/p/ai-emergence-emergent-behaviors-artificial-intelligence
Yeah that article is so full of bullshit that I don’t believe it’s main claim. Comparing LLM’s to understanding built by children, saying it makes “creative content”, that LLM’s do “chain of thought” without prompting. It presents the two sides as at all equal in logical reasoning: as if the mystical intepretation is on the same level of rigor as the systems explanation. Sorry, but I’m entirely unconvinced by this article that I should take this seriously. There are thousands of websites that do translation with natural language taking examples from existing media and such (duolingo did this for a long time, and sold those results), literally just mining that data gives the basis to easily build a network of translations that seem like natural language with no mysticism
It can translate because the languages have already been translated. No amount of scraping websites can translate human language to dolphin.
Assuming this is an emergent property of llms (and not a result of getting lucky with what pieces of the training data were memorized in the model weights), it has thus far only been demonstrated with human language.
Does dolphin language share enough homology with human language in terms of embedded representations of the utterances (clicks?)? Maybe llms are a useful tool to start probing these questions but it seems excessively optimistic and ascientific to expect a priori that training an LLM of any type - especially a sensorily unimodal one - on non-human sounds would produce a functional translator
Moreover, from deepmind’s writeup on the topic:
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