Skymind is providing commercial support and services for an open source project called deeplearning4j. It’s a collection of of approaches to deep learning that mimic those developed by leading researchers, but tuned for enterprise adoption.
A San Francisco-based startup called Skymind launched on Monday to offer support and services for deeplearning4j, an open source deep learning project it has created. It’s early to tell how much traction deep learning will gain among mainstream companies or even web companies, but the technology does hold a lot of promise. The existence of open source libraries backed by professional services could certainly help spur adoption – especially for a field of data analysis previously relegated to top universities and research labs at companies such as Google, Microsoft, Facebook and Baidu.
Skymind founder Adam Gibson calls what he’s pushing “enterprise distributed deep learning,” and he predicts more companies will be apt to give it a try if it’s packaged in a consumable manner. The deeplearning4j (or DL4j) models are tuned to run easily out of the box, and on standard CPU architectures (although the company might soon offer cloud-based GPU training environments), and are written in Java.
“We just want to make deep learning applicable to everybody else,” he said.