One example of this is “Sorry I was very drunk and went home and
crashed straight into bed” being summarized by Apple Intelligence as ”Drunk and crashed”.
I think the real problem with LLMs is we have deterministic expectations of non-deterministic tools. We’ve been trained to expect that the computer is correct.
Personally, I think the summaries of alerts is incredibly useful. But my expectation of accuracy for a 20 word summary of multiple 20-30 word summaries is tempered by the reality that’s there’s gonna be issues given the lack of context. The point of the summary is to help me determine if I should read the alerts.
LLMs break down when we try to make them independent agents instead of advanced power tools. Alot of people enjoy navel gazing and hand waving about ethics, “safety” and bias… then proceed to do things with obvious issues in those areas.
But the quality of Apple Intelligence shows us what happens when you use a tiny ultra-low-wattage LLM. There’s a whole subreddit dedicated to its notable fails: https://www.reddit.com/r/AppleIntelligenceFail/top/?t=all
One example of this is “Sorry I was very drunk and went home and crashed straight into bed” being summarized by Apple Intelligence as ”Drunk and crashed”.