When the chess computer Deep Blue defeated Garry Kasparov, a world champion, in 1997, many gasped in fear of the machines triumphing over mankind. In the intervening years, artificial intelligence has done some amazing things, but none have managed to capture the public’s imagination in quite the same way. Now, however, the awe of the Deep Blue moment is back, as computers are taking on something humans consider their defining ability: language.
or are they? Definitely, large language model (LLM), the most famous of which is ChatGPT, which resembles flawless human writing. But a debate has begun about what the machines are actually doing internally, what it is that humans do when they speak in turn—and inside academia, about the principles of the world. most famous linguistNoam Chomsky.
Although Professor Chomsky’s views have changed significantly since his rise to prominence in the 1950s, many elements have remained largely constant. He and his followers argue that human language differs in type (not just degree of expressiveness) from all other forms of communication. All human languages are more similar to each other than whale song or computer code. Professor Chomsky has repeatedly stated that a Martian traveler would conclude that all humans speak the same language with surface differences.
Perhaps most notably, Chomskyan theories hold that children learn their native languages with surprising speed and ease despite their “poverty of stimuli”: they slurred and sometimes heard the language in childhood. The only explanation for this could be that some kind of instinct language is built into the human brain.
Chomskyan ideas have dominated the linguistic field of syntax since their birth. But many linguists are fiercely opposed to Chomsky. And some are now seizing on the LLM’s abilities to launch a renewed attack on Chomskyan theories.
Grammars have a hierarchical, nested structure consisting of units within other units. Words make phrases, which make clauses, which make sentences, and so on. Chomskyan theory posits a mental operation, “merge”, which consists of joining smaller units together to form larger ones that can then be operated on further (and so on). In a recent New York Times op-ed, the man himself (now 94) and two co-authors said “we know” that computers don’t use language like humans, implicitly referring to this kind of sensation. Do or don’t do. LLMs, in effect, simply predict the next word in a series of words.
Yet, for a number of reasons, it is difficult to fathom what the LLM “think”. programming details and training information Commercially owned like ChatGPT. And even programmers don’t know what’s going on inside.
However, linguists have found clever ways to test the implicit knowledge of LLMs, in effect cheating them with probing tests. And indeed, LLMs seem to learn nested, hierarchical grammatical structures even when they are only exposed to linear input, ie strings of text. They can handle new words and understand parts of speech. Tell ChatGPT that “dax” is a verb that means to fold and eat a slice of pizza, and the system deploys it easily: “After a long day at work, I like to relax while looking at my favorite pizza and Like to dax on a slice of pizza. TV show.” (The fake element can be seen in “Daxes On”, which ChatGPT probably patterned on the likes of “Chew” or “Plague On”.)
What about “poverty of stimuli”? after all, GPT-3 (LLM underlying ChatGPT until the recent release of GPT-4) is estimated to be trained on approximately 1,000 times the data a ten year old human is exposed to. This leaves open the possibility that children have an innate instinct for grammar, making them far more proficient than any LL.M. In a paper appearing in Linguistic Inquiry, researchers claim to have trained an LLM on no more than a text a human child is exposed to, discovering that it can also use rare bits of grammar. Can do. But other researchers have attempted to train LLMs only on databases of child-directed language (i.e., transcripts of caregivers talking to children). LLM fares much worse here. Perhaps the brain really is made for language, as Professor Chomsky says.
It’s hard to judge. Both sides of the argument are preparing to make their case for the LLM. The unnamed founder of his School of Linguistics has offered only a ferocious retort. to live up to their principles this challengeTheir camp will have to put up a strong defense.
© 2023, The Economist Newspaper Limited. All rights reserved. From The Economist, published under license. Original content can be found at www.economist.com
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