[MachineElf]

Umm.. fourthed? I just couldn't help but jump in and also recommend Greg Egan's "Permutation City". That book is just wonderful... think simulation, cellular automata as a model for computation, artificial life and all that other good stuff :).

Also, about the LEVAN thing... given the amount of data available online, both in various structured formats and unstructured formats, don't be surprised if deep learning will yield better and better results moving forward. To me though, they mostly seem evolutionary rather than revolutionary. I mean if you look back at the AI field, during the days before the "AI winter" came, huge amounts of data is one thing researchers back then didn't have available. This is not to say that there haven't been advances in learning algorithms at all recently. ..

[arethuza]

As well as adding my own strong recommedatios for Egan's "Permutation City" and "Diaspora" I would also recommend "Quarantine" - which has a rather splendid idea for mobile apps - "neural mods" that actually augment the brains own congnitive capabilities (including augmenting sensory data for the ultimate in VR).

And there is what one group chooses to do with a very special neural mod...

[agibsonccc]

This is happening now in deep learning. Deep autoencoders[1] are allowing for computer representations of "similar" concepts. I recently gave a talk on this very concept to assist in QA systems.

[1] http://www.slideshare.net/agibsonccc/ir-34811120