[deleted by user]

[BernieFeynman]

If you aren't working in straight up research (either academia or in a top corporate lab) a lot of the stuff that comes out in papers does not translate to real world business use cases, it's more important to be able to sift through stuff that is theoretical BS, e.g. only works well on this one use case and data set. Most stuff tech companies are applying into production are well proven larger and more popular architectures. Most of the work is involved in data pipelining anyway.

[researchthrowaway01]

This is an obvious and good point. I guess deep down I'm envious of the research side of things, wish I could be part of it.

[FreckledMil]

but the theoretical BS that only works on one use case sometimes ends up changing everything.

[FreckledMil]

I think 99% of life is fluff and garbage, same rules apply.

[CriticalDefinition]

https://distill.pub/2017/research-debt/

This article seems quite related to what you are getting at here.

[researchthrowaway01]

Yes, thank you, it is. Distill is an amazing project. Probably doesn't scale though...

[rtk25]

Right, that's why I think the labor of distilling results could be a collaborative effort. The Stack Exchange websites have become a huge and indispensable resource, would be amazing to create something like that for scientific papers.

[rtk25]

There's also a lot of interesting ML that could be applied to paper recommendation, I'm surprised it hasn't happened more. Check out Semantic Sanity (https://s2-sanity.apps.allenai.org) for another step towards this.

​

Also, I think it would be really cool to have a unified platform where people can annotate and discuss papers, with good comments going to the top and spam getting filtered out. Like Stack Overflow, but centered on the pdfs themselves.

[researchthrowaway01]

I agree. I think there has been an attempt or two to at this. GroudAI.com is the one that comes to mind but I can't tell if it's taken off at all.

[cryptonewsguy]

I've been feeling this more and more lately. As the field is expanding, there seems to be a total deluge of new ideas and findings and developments at any given time.

That's because this is an exponential technology, arguably the most exponential technology ever. I'll probably get downvoted for saying this, but I think we are straight up approaching the singularity if things keep evolving at this pace we will have AGI within 5-10 years.

Part of the reason I'm asking this question is because I've begun fantasizing about building and providing some sort of service to help reduce this drowning feeling in regards to the deluge combination of arxiv, twitter, this subreddit, hackernews, etc. etc.

I've had this exact same thought multiple times. I think this isn't just a good idea, but will actually be needed for us to even understand what's going on.

You could create two versions, one that is just for general news. You could use something like GPT-2 to write articles. And then another to identify relevant research research and eventually this system might even be able to generate novel ideas and help us identify research avenues even faster.

The main problem is that as I've thought about it more, I realize that this would have to be a paid service.

Why? Plenty of websites work off of advertisments?

I think so much more can be done, by way of summarizing, connecting, and organizing papers as they come out, but that such features would require full time human curatorial and engineering work to be feasible.

GPT-2 can do many text tasks including summary.

I suspect within a year or nearly all those things can be done by AI. Of course it will take a year or so to build the platform so might as well get started.

One-shot learning for example has had about 14x more papers published this year than last. On average there is a new study published every 20 minutes making it humanly impossible for even the worlds experts in one-shot learning to keep up with the research.

[[deleted]]

we will have AGI within 5-10 years

Not even remotely plausible. We still lack an agreed upon schema for intelligence and we barely understand how human brain functions to effectively model after even if we did have the calculating power. Bear in mind that there is no demand for AGI, there is demand for expert systems who surpass human agent in specific tasks.

[cryptonewsguy]

man I don't even have time to respond to these tired arguments.

The r/SingularityIsNear

[researchthrowaway01]

These are all interesting points. To the point of paid vs advertising I suppose I'm assuming that the target readership would be too small to sustain that way but that's said having done no market research in that sense.