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> You have to go read it yourself afterwards ^ this is important. Otherwise you may very well be missing anything really surprising or novel. See for example
by internet_points 7mo ago
> You have to go read it yourself afterwards
^ this is important.
Otherwise you may very well be missing anything really surprising or novel.
See for example https://www.programmablemutter.com/p/after-software-eats-the-world-what#:~:text=the%20errors%20systematically%20pointed%20in%20a%20particular%20direction https://www.programmablemutter.com/p/after-software-eats-the... , an experience report of NotebookLM where
> It was remarkable to see how many errors could be stuffed into 5 minutes of vacuous conversation. What was even more striking was that the errors systematically pointed in a particular direction. In every instance, the model took an argument that was at least notionally surprising, and yanked it hard in the direction of banality.
- WarmWash 7mo agoOn one hand 2024 in AI time was a decade ago. On the other, Google might not have done much to upgrade the podcast feature since them.
- mathattack 7mo agoIt’s gotten somewhat better over time though clearly not their top priority.
- internet_points 7mo agoThis regression towards the mean is still very much a feature of the newer models, in my experience. I don't see how a model that predicts the most likely word based on previous context + corpus data could possibly not have some bias towards non-novelty / banality.