I wasn't very clear when I said this. I wasn't talking about "natural intelligence". I was referring to the fact that GPT-3 tends to produce sentences that don't really make sense in the wider context of the passages that it writes. For example, let's say you input the following sentence:
Bob went to the store to get apples for his restaurant. He needed to cook food for an important dish. Bob came back home, and cut the apples using a ________
Most human readers would think of the word "knife". However, GPT-3 might fill in the blank with the word "machete" or "sword". While these words grammatically make sense, they don't make sense in the wider context of the sentence. Admittedly, my example is a bit contrived, but if you read through enough text, you can find this type of strange writing from GPT-3. That is what I meant by incoherent.
Also, by "explainability" I'm referring to the ability of engineers to understand why a model decided to choose a particular word or phrase versus another (in my apocryphal example, this would mean understanding why the model chose "sword" instead of "knife").