Comment by vonnik | Hacker News Reader

Comment by vonnik | Hacker News Reader

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You would need to join a community of people who can show you how to contribute to these projects. There are a lot of very active open-source communities, including OpenAI and Deeplearning4j, to name but two.[0][1]

People in those communities can't point you in the right direction, if you show you're willing to read the docs and do the work of learning. One thing you will find is that AI requires a lot of non-AI components to work. That is, you may be able to help an open-source project develop its UI, or improve its datapipeline, or any number of other useful things. By working on the edges of such a project, you'll learn the lingo and grasp some of the basic ideas. From there, you can start working on the math, etc.

Bottom line, there are a lot of ways to get involved with AI.

[0] https://gitter.im/openai/gym

[1] https://gitter.im/deeplearning4j/deeplearning4j

[2] http://deeplearning4j.org/deeplearningforbeginners.html

Why is this comment downvoted? Is this bad advice?

Because vonnick has a habit of plugging deeplearning4j in every deep learning-related thread. IMHO, that's somewhat to be expected/laudable here on HN - particularly since deeplearning4j has an open-source framework, and has published interesting and informative blog posts. OTOH, they're ours-is-more-serious because java-is-enterprise thing is a little out of mainstream, so having OpenAI and deeplearning4j being highlighted in a way that seems to equate them isn't as helpful as it appears.

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.

https://github.com/deeplearning4j/dl4j-examples/pull/224/com...

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