When I look at LLMs as an interface, I'm reminded of back when speech-to-text first became mainstream. So many promises about how this is the interface for how we'll talk to computers forevermore.
Here we are a few decades later, and we don't see business units using Word's built-in dictation feature to write documents, right? Funny how that tech seems to have barely improved in all that time. And, despite dictation being far faster than typing, it's not used all that often because.. the error rate is still too high for it to be useful, because errors in speech-to-text are fundamentally an unsolvable problem (you can only get so far with background noise filtering and accounting for accents etc).
I see the parallel in how LLM hallucinations are fundamentally an unsolvable component of transformers-based models, and I suspect LLM usage in 20 years will be around the level of speech-to-text today: ubiquitously in the background, you use it here and there to set a timer or talk to a device, but ultimately not useful for any serious work.
Here we are a few decades later, and we don't see business units using Word's built-in dictation feature to write documents, right? Funny how that tech seems to have barely improved in all that time. And, despite dictation being far faster than typing, it's not used all that often because.. the error rate is still too high for it to be useful, because errors in speech-to-text are fundamentally an unsolvable problem (you can only get so far with background noise filtering and accounting for accents etc).
I see the parallel in how LLM hallucinations are fundamentally an unsolvable component of transformers-based models, and I suspect LLM usage in 20 years will be around the level of speech-to-text today: ubiquitously in the background, you use it here and there to set a timer or talk to a device, but ultimately not useful for any serious work.