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Such failures are interesting, in the physicist's sense. That it struggles with composition sometimes but not other times might indicate model has learned a pa
by Vetch 4y ago
Such failures are interesting, in the physicist's sense.
That it struggles with composition sometimes but not other times might indicate model has learned a particular distribution factorization which is good much of the time but makes it unable to properly account for conditional dependencies in certain queries. The issue of losing track of lots of details may also be related.
Its struggles with negation is also fascinating because that has been a thorn since the early days of GOFAI. Negation is trickier and more involved than what one might naively assume.
For those taking relief from such weaknesses, it's worth remembering that this is as bad as it is going to be and probably not for long. Model size is surprisingly small when compared to recent behemoths. That it can already do all that it does is certainly cause for concern.
- SemanticStrengh 4y agoNatural language has some major complexities that people don't realize. One of the most surprising one is that plurality does not means more than one.
- YeGoblynQueenne 4y ago>> Its struggles with negation is also fascinating because that has been a thorn since the early days of GOFAI. Well, ish. Negation (specifically, negation-as-failure, i.e. failure to prove) in logic programming introduces non-monotonicity, but reasoning remains sound and even completeness is guaranteed under conditions. John McCarthy (father of AI and also LISP) was very enthusiastic about nonmonotonic reasoning because he considered it the obvious way to represent common sense which was, for him, the one thing missing from AI systems. In plain words, nonmonotonic reasoning means that you can change your mind as new information becomes available. But, you have a point that DALL-E's (and other similar systems') inability to deal with negation is reminiscent of older issues with expressing negation. In particular, it reminds me of datalog, a subset of Prolog that does not allow negation as failure. The motivation for that is to guarantee termination. This guarantee comes at the cost of completeness, so there are programs that cannot be expressed in datalog (but can in Prolog). There might be something similar going on with DALL-E, or maybe it's just a simpler case of not being able to derive negation from correlations, as I point out in another comment.