DeepMind wants to reconcile Deep Learning and classical computer science algorithms with Neural Algorithmic Reasoning. Featuring DeepMind's Petar Veličković and Charles Blundell, MILA's Andreea Deac

Will Deep Learning really be able to do everything? We don't really know. 

But if it's going to, it will have to assimilate how classical computer science algorithms work. This is what DeepMind is working on, and its success is important to the eventual uptake of neural networks in wider commercial applications.

This work goes by the name of Neural Algorithmic Reasoning. Join us as we discuss roots and first principles, the defining characteristics, similarities and differences of algorithms and Deep Learning models with the people who came up with this. 

We also cover the details of how Neural Algorithmic Reasoning works, as well as future directions and applications in areas such as path finding for Google Maps

Could this be the one algorithm to rule them all?

Article published on VentureBeat.

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