In this post, our founder and CTO, Adam Gibson is being interviewed by one of our open-source contributors, Francois Garillot, on recent changes to DeepLearning4j's parameter server.
Hi Adam, thanks for agreeing to chat with me. I heard some parts of Deeplearning4j are now using Aeron, as of release 0.7.0. and I wanted to ask you a few questions about it. But first, remind me and our audience, what is Deeplearning4j?
In this context, it is actually a whole ecosystem of libraries, one that has everything for deep learning: you have data transforms, you have a UI, you have distributed systems, you have reinforcement learning, you have various kinds of streaming integrations. It's literally a whole ecosystem of libraries for building deep learning applications. The main emphasis is not necessarily on research but actually connecting a deep learning model to production systems, connecting it to a local database, running on your Hadoop cluster — in the same library! We're able to build comprehensive pipelines connecting production systems to new systems, deploying models as microservices, among other things. Deeplearning4j is actually a sub-library now: it is just the name of the library that started all this. It now contains mostly a deep learning DSL.