I remember reading a comment sometime ago on this site where people on HN seem to have a positive bias towards topics on machine learning and would always upvote it. ML seems to be such a tech buzzword these days. This blog post is at the top of this site, yet there is not a single comment of discussion. I am not trying to sound negative, but rather was wondering if other people shared the same opinion.

Regarding the post: This seems like a useful resource. When I read many of these papers, a code supplement makes understanding it so much better. I do a lot of research with RNNs with respect to language modeling and implementing various models when I started researching this field was very useful to get a better understanding. I got great feedback on my implementations where people said it helped them understand.

I have a hunch that learning resources get a significant bump from people using upvotes as bookmarks.

I think the ML results and demo posts are mostly getting upvotes because the results are fascinating and the posts are often excellently written. Image manipulation in particular lends itself towards posts that are appealing both to people casually skimming articles and to people looking for some technical depth.

Another reason may be that this is a pure "resource" post that doesn't make an argument or represents personal opinions that people could easily comment on. It's not a good basis to start a discussion, unlike many other HN posts.

However, I'd appreciate more comments of course ;)

I guess you raise a good point since it is only a "resource" post. My comment was geared toward all ML related posts in general.

I do research in ML so I love seeing these posts, but the fact that words like neural networks has become such a buzzword is somewhat disappointing. I remember all the buzz when Swiftkey released their "neural network" keyboard simply because of the name.

More than a few times I've seen a resource post like this that has garnered discussion on the usefulness of what was being done. In a few extreme cases, HN has exposed people copy/pasting the work of others and linked to the originals.

Yes, and I don't think it's just people using upvoting as bookmarks (most people I know don't do that).

I think it has to do with the fact that HN is a very diverse mix of folks (technical, non-technical, working at startup, working at big co, web devs, mobile devs, infra dev, etc). There isn't a concentration of ML-technical folks like you might find on /r/machinelearning (decent technical ML discussion). Instead you have here a mix of futurology speculation and tutorial discussion - lots of introductory material of highly varying quality (since the people upvoting don't really know if it's good), science fiction passed off as credible opinion, highly technical ML posts that get upvoted a lot but no comments, etc.

My guess (based on my own upvote) is that people want to know about it but don't currently know enough to contribute.

Heh. Only if you are talking about the sexy machine learning bits - reinforcement learning's this year's hot sexy one. A few years ago, it's convolutional neural networks, followed by recurrent nets.

Nobody thinks SVM is cool anymore :S

Part of this is due to, I think the immense amount of marketing pushed by Big Corp on their recent AI successes.

I admit to upvoting solely as a means to bookmark it.

Agree people blindly upvote ml topic. That explain why there is never a c++ or java programming topics on top news.

Regarding your second point, posts about C++ or Java seem to be lacking simply because the languages evolve over a multi year phase. I do remember seeing posts about C++17 on HN and there being discussion about it. People will occasionally post libraries they made in that language. I don't do a lot of Java development, but I am interested in C++ and if you are too I would check out r/cpp if you haven't. Many of the posters are people doing a lot of work on C++ - compiler developers, people working on the standard, etc.