Do LLM’s “understand” language? A thought experiment:

Understanding Language: Do Large Language Models Truly Comprehend Meaning?

Exploring the Capabilities of AI in Deciphering Unfamiliar Languages

Imagine uncovering a completely unfamiliar language—perhaps one originating from alien intelligences—but lacking any understanding of its vocabulary, grammar, or context. All we have are vast collections of symbols that seem to form an alphabet, yet their meanings remain entirely obscure. We might notice patterns, such as recurring sequences or symbols that tend to follow each other, but deciphering a message or grasping the language’s structure would be a daunting challenge.

Now, consider training a large language model (LLM) on this alien dialect. Assuming an abundance of data and consistent patterns in the language, the LLM could learn to predict and generate sequences of symbols that mirror the original text. In theory, if aliens attempted communication with such a model, it might even hold seemingly coherent conversations.

However, the crucial question arises: Does the LLM truly understand the language? Given that it has no awareness of what the individual symbols represent, can it genuinely grasp the meaning? It knows how symbols are related to each other and can produce plausible continuations, but is this equivalent to understanding?

Interestingly, this scenario mirrors human language learning in many ways. Human speakers often learn a language as infants—by recognizing patterns, intonation, and contextual cues—without initially understanding every concept or vocabulary. To an LLM, human languages are, in a sense, similar to an alien language: a complex system of symbols and rules that can be modeled without necessarily knowing what each part represents.

Furthermore, if we could develop a perfect translation between the hypothetical alien language and our own, it suggests that an LLM trained on the alien language might appear extraordinarily intelligent—perhaps even surpassing current AI models like ChatGPT—simply because it was trained on communications from more advanced or different intelligences.

In summary, while large language models can mimic language patterns remarkably well, whether this equates to true understanding remains a profound and philosophical question. It challenges us to reconsider what it means for a machine—or any entity—to truly comprehend language and meaning.