Follow up on AI Intuition.
The Large Language Model has a key word in the middle – Language. Language is the main means of human communication and what makes humans differentiate from animals. But language is not just a way of communication, it is also the primary way we accumulate and codify knowledge pretty much about everything that eventually gets passed from one generation to another.
Language is also an actuator of our inner voice that facilitates our thinking process. When we deliberately reason we use inner voice and think using different language constructs. Some literature about LLMs, especially early ones, emphasized limitations of large language models by equalizing their capabilities to language fluency. Certain AI luminaries were insisting that LLMs are merely parroting human’s language skills. What critics failed to recognize is LLM’s potent use of language paradigm as a reasoning mechanism like humans do: not simply fluent expression of thoughts in grammatically and syntactically correct way, there is more, much more into it.
Fig. Language as communication means and thinking/reasoning vehicle
LLM prominence in AI landscape
There is an ongoing debate that LLM based AI, while being a fractional space of AI applicability to real life situations, disproportionately captivates so many researchers’ valuable time and regulators’ attention. I would argue that among many subfields of AI LLM and Generative AI justly steal the bulk of attention because massive human civilization knowledge has been codified in linguistic artifacts.
Millennia worth human civilization experience has been captured in the form of billions of written documents. Just pause and think about it: the written knowledge is a result of reverse engineering of what and how humans think about pretty much everything. Drama, recipes, philosophical and casual dialogues, fiction, textbooks on psychology, math, physics, and so on spread out throughout thousands of years.
Language is how we learn, update our current knowledge and pass it along. What could be a better and most attractive way of improving this eons worth storage of immense human wisdom? What could be better ways of retrieving, transferring and enacting it? Well, LLMs are aimed at that.
Fig. Generative AI and LLM in AI space
In the early days of AI the hope was that First Order Logic (FOL) – the logic language – would be the best way of capturing the essence and representing our views of the world in order for computers to successfully reason. Unfortunately, FOL despite its effective formalization of logic and reasoning doesn’t scale as well when capturing almost infinite and constantly changing knowledge of the world as LLMs amazingly manage to do it today.
Read on to untangle this magic…
Leave a Reply