Google Duplex & Why A.I. Is Harder Than You Think, latest by @garymarcus and Ernest Davis @NYTimes https://nyti.ms/2IS3mDz
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agreed. one thing i wish we had more space for: we need a synthesis of knowledge engineering and ML; neither on its own is sufficient. but currently the two approaches don’t mix well. major problem for research.
I would claim that Markov logic goes a long way toward solving this problem.
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I’d agree with
@pmddomingos More generally, I see probabilistic dependency graphs as the holy grail—these capture causal relationships, quantify uncertainty, blend knowledge with data driven knowledge and can incorporate rich nonlinear functions. Hard to argue against it.Kiitos. Käytämme tätä aikajanasi parantamiseen. KumoaKumoa
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Markov Logic is an elegant idea! OTOH as articulated by
@danieldennett here: (https://m.youtube.com/watch?feature=youtu.be&v=arEvPIhOLyQ&t=6m22s … ) I wonder if we will ultimately need a “softer” definition of logical propositions, as much or more than a softer method of inferring their truth values. -
How about a "everyone nominates their favourite (attempt at a) solution" round with
@GaryMarcus as judge, and without self-nominations (i.e., one may not just throw in one's own formalism).@pmddomingos,@etzioni,@AvilaGarcez, and all others -- any takers? ;) - Näytä vastaukset
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