4 ms·
The problem will always remain that it cannot answer 'why', only 'what'. And oftentimes you need things like intent and purpose and not just a lossy translation
by ljm 1y ago
The problem will always remain that it cannot answer 'why', only 'what'. And oftentimes you need things like intent and purpose and not just a lossy translation from programming instructions to prose.
I'd see it like transcribing a piece of music where an LLM, or an uninformed human, would write down "this is a sequence of notes that follow a repetitive pattern across multiple distinct blocks. The first block has the lyrics X, Y ...", but a human would say "this is a pop song about Z, you might listen to it when you're feeling upset."
- amelius 1y agoThat's a bad example, because an LLM is perfectly capable of saying when something is a song or not.
- ljm 1y agoAnd how does it do that? By looking at the words and seeing that they rhyme? An LLM is not capable of subtext or reading between the lines or understanding intention or capability or sarcasm or other linguistic traits that apply a layer of unspoken context to what is actually spoken. Unless it matches a pattern. It has one set of words, provided by you, and another set of words, provided by its model. You will get the bang average response every single time and mentally fill in the gaps yourself to make it work.