Microsoft to world: we’ve got open source machine learning too

Microsoft’s decided that it, too, wants to open source some of its machine learning space, publishing its Distributed Machine Learning Toolkit (DMTK) on Github. Google released some of its code last week. Redmond’s (co-incidental?) response is pretty basic: there’s a framework, and two algorithms, but Microsoft Research promises it will get extended in the future. The DMTK Framework is front-and-centre, since that’s where both extensions will happen. It’s a two-piece critter, consisting of a parameter server and a client SDK. The parameter server has “separate data structures for high- and low-frequency parameters”, Microsoft says, so as to balance memory capacity and access speed. It aggregates updates from local workers, and synchs different model mechanisms, including binary space partitions (BSP), answer set programming (ASP), and statistical signal processing (SSP) “in a…


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