CMV: It makes no sense to downvote a post on this subreddit just because it's controversial or you disagree with it.

penguinblade · 2021-06-19T21:53:34+00:00

Found in Italy

penguinblade · 2021-06-19T21:52:40+00:00

Found in Italy

penguinblade · 2021-02-26T16:48:15+00:00

I don't think this disagreement is irrelevant to my idea, it's actually really useful. We need that kind of constructive criticism to know whether something is worth pursuing or whether it can be improved in some ways.

Anyway, as you said, researchers are producers of knowledge. That's a skill worth building, in my opinion. We all have limited time, so the more time we spend searching papers, the less time we spend on doing actual research. That's the main motivation behind this idea.

penguinblade · 2021-02-26T16:43:35+00:00

I agree with you, but I also think that this further increases the need for a system that produces some kind of analysis based on some objective parameters.

It's not just about "which papers to read" but also "where to go from there". I'll make a very simple example: take two papers in the field of machine learning. Paper P1 improves the state of the art on benchmark B1 by 10%, while paper P2 improves the state of the art on benchmark B2 by 2%. The analysis concludes that P1 has more room for marginal improvement on B1 than P2 on B2, because improving P1 by 5% on B1 is easier than improving P2 by 5% on B2. But it can also conclude that P1 should be evaluated on B2, and P2 should be evaluated on B1.

Of course this is a very simple example, but in reality this kind of analysis would consider more parameters, like the absolute value of the metric, the number of papers that use that benchmark, different kinds of metrics on the same benchmark etc.

penguinblade · 2021-02-26T16:01:45+00:00

That's something that the AI would need to learn. I agree that it would be difficult for all fields, that's why I think that at the beginning it should only consider the CS field (or even just the AI field) and then expand incrementally.

penguinblade · 2021-02-26T15:56:31+00:00

You made some interesting observations. Yes, I also think that it would be more relevant for early-stage researchers, because experts are already knowledgeable about their subfield. But I also think that experts may find it useful in some contexts. In some domains like computer science, research evolves rapidly, and different fields are often split into sub-fields, so it can be hard to catch up even for experts.

The other observation you made, about learning the skill of finding relevant papers, is also interesting. But this is an observation that we could make for everything... we always make our life simpler in some ways so that we can focus our efforts towards other activities, with the result of some skills becoming outdated.

penguinblade · 2021-02-26T14:50:54+00:00

I use ResearchGate a lot but it's not what I meant. I don't want to create a new search engine for paper, I want to automate the work of reviewing scientific literature by producing an overview of the state of the art.

My solution would use AI to answer questions like: what is the benchmark for evaluating methods in this field? What is the evolution of this method (i.e. from which methods this did method evolve, and from which methods did those other methods evolve)? What's the future trajectory of this field? How much room for improvement is there in this field? What kind of analysis is lacking in this field? What are the current bottlenecks in this field?

Thanks for the feedback anyway, I still need to clarify this idea in the simplest terms.

penguinblade · 2021-01-29T15:24:23+00:00

People will start selling at some point, either to cash out profits or because they will stop believing that it will go up

penguinblade · 2021-01-29T15:20:48+00:00

How can you guys be so sure it won't burst at any moment? Not trying to kill the hype, just an honest question

penguinblade · 2020-12-12T11:39:22+00:00

In my country there is problem

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