In the short term, Distill's editorial assistance will help authors produce outstanding papers, although they need to be willing to work as well.
In the longer-term, I'd like to explore match making between data visualization people who would like to get into machine learning and machine learning researchers publishing papers.
And in the very long term, I think the right solution is to add a new component to the research ecosystem. Just like we we have people who specialize as research engineers, theoreticians, and experimentalists, I'd like to have a respected "research distiller" specialization. Eventually, I'd like to try and start special grants for research groups to have someone focused on this.
Two Minute Papers on YouTube:
I have actually been meaning to write a paper on my findings and have been looking for journals to write for. However it doesn't quite "fit" with most journals. Distill looks like it's more catered to "professional" machine learning people, at least for now. Is there any way that somebody with my background (design+data viz+development+interest and curiosity to learn ML) could be involved with Distill?
Absolutely. We know a number of leading ML researchers who would love to publish papers as Distill articles but don't have the design/data vis skills. We'd like to facilitate collaborations which would lead to data vis people co-authoring cutting edge research papers.
Or would said facilitation be done by the admins / editors / steering committee? If so, then how do you plan on finding dataviz people? I'm asking this in particular because I would imagine that people who have ML findings to talk about would probably contact you ("I researched such and such, and found such and such. Now I would love to publish in Distill"). But I wonder if data visualization specialists would do the same thing. Contacting with "hey, I love data viz, would love to collaborate with somebody looking for one" feels a little inappropriate to me.
Thoughts?
As a data viz person, I would be absolutely thrilled to work on this, I'm trying to scratch time here and there to position myself better in that respect, learning more and trying to bridge that gap.
And I rarely cover recent work.
> In the longer-term, I'd like to explore match making
> between data visualization people who would like to
> get into machine learning and machine learning
> researchers publishing papers.
I'm a junior faculty working in ML with no personal knowledge of web development, d3, etc. While the papers currently on Distill are absolutely gorgeous and will be an invaluable tool for learning advanced ML concepts, I simply cannot see myself or my students putting the time to actually create something like that.
Unless a student is especially adept at the specific tools needed to create these and especially enthusiastic at using them, I will actively discourage them from doing it. The time needed is simply not worth it right now.
I would be happy and grateful if tools for creating these articles become easier to learn and use eventually, such that even the lower-budget, time-constrained researchers could afford to create them.
I won't deny the time commitment needed for a distill article is not trivial - it is far more work than a technical blog. But in terms of a pure tradeoff of time per publication, the calculus makes sense. Most of the work of research distillation and synthesis is already part of the research process, and writing a distill article is just a matter of putting it all of down on paper. Doing research is a far more time consuming and less predictable process.
This applies especially if you write the distillation targeted at the lab you want to hire you.
Hey let's be honest, most academics (that I know) still don't even use LaTeX (or refuse to do so). This is really cool, but requires way too many skills (in js/css3/html5/distill-extensions and node.js).
Personally, my team and I had really great experience with sharelatex.com, whom only I had knowledge about LaTeX. I liked that it's also opensource with a permissive license. I would rather host that on sandstorm.io the next time, or just pay for the comfort offered by overleaf.com (I've never seen such a beautiful colloborative LaTeX Editor).
• What about vendor lock-in?
• Can you export to LaTeX, Word or PDF?
• Can you selfhost it for your team or company?
What field? TeX is pretty much de rigueur in Math/CS/Physics graduate schools in the U.S.
I clearly don't expect people to do that much. I can only do that because i'm coming from web development, and very nice tools started to appear recently.
People in research needs a design framework like a set of templates for keynotes/PPT/JS/CSS (think about how much traction got bootstrap). Distill is doing an awesome jobs at showing the example of what you could do.
Maybe Distill could open-source the templates they use to build those blog post?
On the other hand, being able to write well and to create good interactive illustrations are valuable skills. Maybe we could incorporate these things into seminars or otherwise crowdsource the creation of e.g. individual figures?
So, I guess this will get distill get traction.
- Little incentive for researchers to do this beyond their own good will.
- Most ML researchers are bad writers, and it's unlikely that the editing team will do the work needed (which is often a larger reorganization of a paper and ideas) to improve clarity.
- Producing great writing and clear, interactive figures, and managing an ongoing github repo require nontrivial amounts of extra time, and researchers already have strained time budgets.
- It requires you to learn git, front-end web design, random javascript libraries (I for one think d3 is a nuisance), exacerbating the time suck on tangents to research.
Maybe you could convince researchers to contribute with prizes that aligned with their university's goals. Just spitballing here, but maybe for each "top paper" award, get a team together to further clarify the ideas for a public audience, collaborate with the university and their department and some pop-science writers, and get some serious publicity beyond academic circles. If that doesn't convince a university administration that the work is worth the lower publication count, what will?
In the worst case it'll be the miserable graduate students' jobs to implement all these publication efforts, and they won't be able to spend time learning how to do research.