(Fixed first bit)
I was unsure of the wording on the second two points. By "instant" I mean without needing to reprogram the system or invoke new training. For example, playing a video game, a human can apply previous knowledge to new levels of the game, allowing them to get by the level the first time they encounter it. The AI's so far don't really achieve this -- they can't reapply previous knowledge well, they don't make abstractions and logical judgements.
This applies to novel situations as well. A human can encounter a room full of completely new objects, and based on affordances and constraints, determine what they might do. A statistics programmed machine, as seen so far, would not be able to do this, and would not be able to figure out these novel items.
I don't know if it's the same thing you're getting at, but one thing that I think is missing from well-known machine learning approaches is "meta-cognition." As human beings, we have the awareness that we don't know something, and we can takes steps ourselves to learn more about any given subject. I don't know how much progress there's been in this area for AI. I suspect there is a pretty wide divide between current approaches and this kind of learning though.
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