AI News, Data Science and Technology Monthly - December 2015

Data Science and Technology Monthly - December 2015

In November, Google open-sourced their machine learning technologycalled TensorFlow that powers a bunch of their products like Google Photos Search, Smart Reply, speech recognition and more.  TensorFlow was a successor to their DistBelief technology that remained dependent on Google infrastructure, and hence wasn’t ready to be open-sourced.

As pointed out in this Forbes article, Google is probably open sourcing TensorFlow to help it become the gold standard in machine learning.

In a few years, as the artificial intelligence and machine learning market becomes more popular, a robust open source platform will become attractive to new users.

However, Facebook jumped on this bandwagon and announced that it is open sourcing the hardware design for the servers it uses to train deep learning algorithms.

With companies racing each other to open source their algorithms and hardware designs and their APIs, what all this really signifies is not the triumph of open-source, but the triumph of data.

The human mind as opposed to machines have a faster learning process even with smaller amounts of data.

 Meanwhile, researchers from NYU, Univ of Toronto and MIT published this seminal paper in Science called “Human-level concept learning through probabilistic program induction”. They describe a model that learns as quickly as humans, with just one training example and the results produced were stunning, because they achieved better than human performance.

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