Comment by walrus01
3 hours ago
> Probably too late for this, but I have argued before that language is a fundamentally lossy encoding of the human experience. We do our best to describe what we're seeing and experiencing using language, which is fantastically expressive, but it has its limits.
Yes, and sometimes this is very intentional. Take for example a short poem which if you sit and really think about it for a long time, you could go off on a mental tangent of imagining what sort of kingdom or empire created a statue that is now "two vast and trunkless legs of stone", for instance. Being terse and allowing for human interpretation is kind of the entire point of something being written like this.
I met a traveller from an antique land
Who said: Two vast and trunkless legs of stone
Stand in the desert. Near them, on the sand,
Half sunk, a shattered visage lies, whose frown,
And wrinkled lip, and sneer of cold command,
Tell that its sculptor well those passions read
Which yet survive, stamped on these lifeless things,
The hand that mocked them and the heart that fed:
And on the pedestal these words appear:
"My name is Ozymandias, king of kings:
Look on my works, ye Mighty, and despair!"
Nothing beside remains. Round the decay
Of that colossal wreck, boundless and bare
The lone and level sands stretch far away.
> Being terse and allowing for human interpretation is kind of the entire point of something being written like this.
It's also to a certain extent why LLMs work.
When IBM Watson was playing Jeopardy, one of the game prompts was:
> It was the anatomical oddity of U.S. gymnast George Eyser, who won a gold medal on the parallel bars in 1904
The man was missing a leg and used a prosthetic. Watson's output was, "What is leg?"
At first it was regarded as correct. If a human said that you could conclude that they knew the answer. But then the judges decided not to give Watson the point because its output didn't provide enough specificity to prove that it understood the context.
If you ask an LLM what kinds of things taste sweet it can give you examples like cotton candy or strawberries, but it has never actually tasted anything. All it knows is that the training data contains the association between those tokens. But the human reading the output knows what strawberries are, which is what allows the output to be meaningful.
Human language requires a human receiver, like art requires an audience.