Yeah, I probably plug DL4J too much. It's a hard habit to break, and I'm sure some people get tired of it. I try to only do it when I have something substantive to say about the post in question.
OpenAI and DL4J are equivalent in the sense that they both have active communities focused on parts of machine learning. The difference, of course, is that DL4J is a commercially backed OSS framework, while OpenAI is a not-for-profit think tank that is using other group's DL libs, while building its own sandbox and obviously conducting its own research.
I wouldn't say that DL4J is more serious because Java is enterprise. It's just tackling different problems. It does some things better (many integrations) and some things worse or not at all (automatic differentiation), which is simply a reflection of our priorities. Not research, just production solutions and apps. That said, we are making it easier to create custom layers with DL4J, so people will be able to implement a lot of the latest papers there soon.
OpenAI and DL4J are equivalent in the sense that they both have active communities focused on parts of machine learning. The difference, of course, is that DL4J is a commercially backed OSS framework, while OpenAI is a not-for-profit think tank that is using other group's DL libs, while building its own sandbox and obviously conducting its own research.
I wouldn't say that DL4J is more serious because Java is enterprise. It's just tackling different problems. It does some things better (many integrations) and some things worse or not at all (automatic differentiation), which is simply a reflection of our priorities. Not research, just production solutions and apps. That said, we are making it easier to create custom layers with DL4J, so people will be able to implement a lot of the latest papers there soon.
https://github.com/deeplearning4j/dl4j-examples/pull/224/com...