What Is Skymind?● Skymind is Red Hat for AI.● The Skymind Intelligence Layer (SKIL) is RHEL:

An enterprise distribution backed by commercial support.

● SKIL bundles libraries that Skymind built:○ Deeplearning4j: Neural net configuration○ ND4J: Scientific computing engine○ DataVec: ETL tool for machine learning○ Deep-learning model server w/REST API

● SKIL helps you train neural nets quickly and get the maximum value from your hardware

Founded 2014Funding $6.3MSales $1M+ in Q1 2017

$4-6M projected in 2017Clients 12 enterprise clients

10,000+ open-source developers160,000+ DL4J downloads/mo.

Staff 25

Company Overview

Reference Architecture

DL4J Build, train, and deploy neural networks on the JVM

RL4JReinforcement learning algorithms on the JVM

ND4J High-performance tensor library for scientific computing

Skymind’s Open-Source ToolsArbiter Hyperparameter optimization for neural networks

DataVec Data ingestion, normalization, and vectorization (ETL for ML)

Model ImportImport and deploy neural networks trained from Keras, TensorFlow & Theano

ParallelWrapper● Single node parameter Averaging

● Use a datasetiterator but run multigpu

or just use all cores

● Also useful for testing parameter averaging on a single

node before going distributed

https://github.com/deeplearning4j/dl4j-examples/blob/master/dl4j-cuda-specific-examples/src/main/java/org/deeplearning4j/examples/multigpu/MultiGpuLenetMnistExample.java#L40

Datavec TransformProcess● Persistable data pipelines● Mainly useful for csv and log data right now● Also comes with a transform process server for encasing

data transform as a service● https://github.com/deeplearning4j/dl4j-examples/blob/mas

ter/datavec-examples/src/main/java/org/datavec/transform/join/JoinExample.java

Nd4j indexing● Use the static methods in NDArrayIndex● Allows slicing of an array any way you could in numpy● Boolean indexing also supports masking● https://github.com/deeplearning4j/dl4j-examples/blob/mas

ter/nd4j-examples/src/main/java/org/nd4j/examples/Nd4jEx6_BooleanIndexing.java

Arbiter● Define a search space● Supports Grid and Random search

● Comes with a GUI for looking at an overall search space

● https://github.com/deeplearning4j/dl4j-examples/tree/master/arbiter-examples

Nearest neighbors!● We have VPTrees, QuadTrees,KDTrees,SPTrees● Used in BarnesHutTsne and our nearest neighbors server● Combined with an autoencoder variant it’s also a great way

of leveraging unsupervised algorithms (run nearest neighbors on the representations from the neural net

Libnd4j● Self contained c++ library● Actually contains cuda kernels and openmp loopsfor various types of algorithms (reductions,scans,..)

● Also contains bindings for blas and lapack

● https://github.com/deeplearning4j/libnd4j

Cudnn● Dl4j actually comes with cudnn● All you have to do is include it as a dependency● We support lstms and the cnns● It’s actually possible to use this on flink (just tricky to

setup)

ParallelInferece● Thread pool oriented model serving● Supports keras and dl4j models● Useful for saturating your server also gets aroundmodels not being thread safe ● Works similar to parallelwrapper

Nd4j Workspaces● Our new cyclic memory management engine● Allows you to turn off garbage collection● We have seen a 3 to 5x speed improvement using it● http://deeplearning4j.org/workspaces

Upcoming features● Jumpy (our python interface) -

https://github.com/deeplearning4j/jumpy● Autodiff● Integration of our aeron based parameter server● proper keras backend

Dl4j streaming● Integrate with kafka and setup streaming jobs● Needs some work and promotion but is a great way of

leveraging kafka for production● Also supports spark streaming● Flink contributions welcome

Transfer Learning● Take pretrained models from keras and load them in to

dl4j and write a “fine tune configuration” ● Use this to build new image models quickly● Use our model zoo and refine existing models

Nd4j Workspaces● Our new cyclic memory management engine● Allows you to turn off garbage collection● We have seen a 3 to 5x speed improvement using it● http://deeplearning4j.org/workspaces

Community showcase● Apache opennlp is integrating arbiter and our LSTMS● Apache Tika recently merged our ● Apache Flink wants to merge us for GPU support ● Tons of traction with the spring boot community