I remember when compression was popularized, like mp3 and jpg, people would run experiments where they would convert lossy to lossy to lossy to lossy over and over and then share the final image, which was this overcooked nightmare
I wonder if a similar dynamic applies to the scenario presented in the comic with AI summarization and expansion of topics. Start with a few bullet points have it expand that to a paragraph or so, have it summarize it back down to bullet points, repeat 4-5 times, then see how far off you get from the original point.
Summarizing requires understanding what’s important, and LLMs don’t “understand” anything.
They can reduce word counts, and they have some statistical models that can tell them which words are fillers. But, the hilarious state of Apple Intelligence shows how frequently that breaks.
I remember when compression was popularized, like mp3 and jpg, people would run experiments where they would convert lossy to lossy to lossy to lossy over and over and then share the final image, which was this overcooked nightmare
I wonder if a similar dynamic applies to the scenario presented in the comic with AI summarization and expansion of topics. Start with a few bullet points have it expand that to a paragraph or so, have it summarize it back down to bullet points, repeat 4-5 times, then see how far off you get from the original point.
In my experience, LLMs aren’t really that good at summarizing
It’s more like they can “rewrite more concisely” which is a bit different
Summarizing requires understanding what’s important, and LLMs don’t “understand” anything.
They can reduce word counts, and they have some statistical models that can tell them which words are fillers. But, the hilarious state of Apple Intelligence shows how frequently that breaks.
I used to play this game with Google translate when it was newish