[ArtWomb]

Conversational AI is much closer than we think. Neural sequence-to-sequence models are successful in domain specific domains. But in the context of chit-chat based dialogue systems, the responses lack humanity. Undoubtedly due to the fact they don't comprehend our world. Transfer learning alleviates some of that awkwardness.

If anyone's interested in further experiments on their own. There is now a unified Python framework for dialogue models ;)

https://parl.ai/about/

[abhishek0318]

Really? Most of the chatbots in production are rule based systems.

[blurbleblurble]

The transformer can also be used at different levels of abstraction, e.g. to do interesting stuff with knowledge graphs. I think the transformer architecture is about to make things very, very interesting.

https://arxiv.org/pdf/1904.02342.pdf

[p1esk]

We don’t even know how many breakthroughs it will take to get to the level of 3yo’s conversational abilities. And I’m talking major level breakthroughs, like LSTM or Transformer, probably trained on much more data.