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Statistical mimicry is to language what a plastic toy picturing a bus is to public transportation innovation. It may look right, but it can't perform its function. A horse-drawn cart would be cruder, but could actually move people from A to B. It's cargo-cult AI.
I'm looking forward to seeing AI agents that: - Have a model of the world - Assume others do too - Use some form of language to update models on each side ... As well as many others things you use language for. It doesn't matter if their syntax is terrible.
Much like an airplane, language has a function. No matter how realistic you make your image of a plane, if it misses the function, you still haven't mastered human flight.pic.twitter.com/UX8LDecrvS
indeed, but how to model the world is the big question i think and retrieve that information rationally, with meaning...
not only retrieve but update the world model as well off course...
would it be more straightforward to try AI implementations with minimal vocabularies to start with, let them acquire more vocabulary after they learn to parse a small but sufficient set of words? how about bicameral AIs who run models of each other as well as the external world?
Would such a model require some sort of causal inference based learning or just inductive learning suffice?
How can you get there?
ive been building this the last year or so online 
I think Luc Steels has done a lot of great work coming from exactly that point of view.
.@shugenja you were way way ahead of your time w your MMORPG design (wrt world models and the updates) in the early 1990s 
@fchollet I was trying to create autonomous agents walking around MUDs creating a vibrant and realistic economy. It was klunky but possible to have them all have maps of the rooms and items they saw, at O(n) cost. They also had to develop expectations of where to find things.
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