Inside an AI 'brain' - What does machine learning look like?

Inside an AI brain - What does machine learning look like?
5/5 based on 1 votes.
One aspect all recent machine learning frameworks have in common - TensorFlow, MxNet, Caffe, Theano, Torch and others - is that they use the concept of a computational graph as a powerful abstraction. A graph is simply the best way to describe the models you create in a machine learning system. These computational graphs are made up of vertices (think neurons) for the compute elements, connected by edges (think synapses), which describe the communication paths between vertices.

Unlike a scalar CPU or a vector GPU, the Graphcore Intelligent Processing Unit (IPU) is a graph processor. A computer that is designed to manipulate graphs is the ideal target for the computational graph models that are created by machine learning frameworks.

We’ve found one of the easiest ways to describe this is to visualize it. Our software team has developed an amazing set of images of the computational graphs mapped to our IPU. These images are striking because they look so much like a human brain scan once the complexity of the connections is revealed – and they are incredibly beautiful too.
Submitted by elementlist on Feb 16, 2017
35 views. Averaging 0 views per day.

Comments on Inside an AI 'brain' - What does machine learning look like?

Post Reply

Please login or register if you wish to leave a comment.

Quick Search


3,013 listings in 21 categories, with 1,064,739 clicks. Directory last updated May 16, 2017. Welcome nainesh shah, the newest member.