I'm the post author and would be happy to answer any questions and discuss academia CS and startups.
My immediate first impression was that this was another app that would waste my time. I want less of those, not more. The absolute best news feed app I've used is Flipboard for the iPad, and even then I don't use it too much as I feel too much like I'm wasting time with it (like HN!).
Secondarily, the homepage doesn't grab you enough. The text in the graphics is too blurry and the pictures are generic. The homepage below the icons doesn't have the production values to explain why it's cool.
I'm not trying to be negative here. Some of the points in your article really hit home (email summarization would be awesome and paradigm shifting). So I wonder if you might focus more on making something that will save people time and solve a pain point vs. "another web-based time-wasting thing" (that may not be fair, but that was a first impression).
For example, can you scrape an inbox and list of Facebook/Github/Tumblr/RSS/Twitter feeds to get a single high-sensitivity greatest hits from all monitored news feeds? This way you can check a single page in five minutes on your phone and feel reasonably content that you saw the top headlines for that week. Kind of like news.ycombinator.com/best.
Just some thoughts, FWIW.
You've missed the point already. The web is vast, on the whole filled with 99.99% crap. But .01% of something large is still very big. You cannot list the interesting things a priori with a few feeds. Prismatic is about learning about what you actually like to read and giving it to you. It's got the smooth/sleak usability of Google reader (read title, keep smashing J when something isn't worth reading, essentially letting you skim/reject more than 10 uninteresting articles/minute), but without the low recall "enumerate every site I think I am interested in" subscription model.
It's compelling and awesome.
j/k: Jump to next/previous article up/down: Scroll to next/previous article with animation space: Scroll to next article s: open share box for active article o: open active article in new tab b: bookmark active article in new tab f: Go to search field and find new interests. r: to recommend active story gh: go to home feed gd: go to your feed of saved stories gr: go to your feed of recommended stories gg: go to top news 'global' feed
But wouldn't it be better to use NLP to emancipate people from the attention economy altogether, to help identify not what people want, but what they need to he happier, and more engaged in the real world doing real things for real people?
I work on ads recommendations, and yes, it would be "better" if I stop recommending KFC to the 36% of obese Americans & instead recommend Crossfit or Yoga or Gold Gym or Myoplex. If I do that, they will quit the site en-masse and the negative engagement rates will go through the roof, I'll be out of a job, will end up eating at McDonalds to save money, and then become obese, and then click on the same KFC coupon recommended by another data scientist hired to replace me :)
Yes, it would be "better" if people read the Economist instead of Cosmo, or went to grad school instead of building crud web apps, or watched Frontline PBS instead of Jerry Springer, but then, it would also be much "better" for the environment if we got rid of the 1000s of walmarts & safeways selling groceries & Uncle Sam shipped you healthy lettuce and spinach weekly via USPS....communism 101 :)
The problem with your comment is that you present a false choice.
I believe that there is strong - very strong - demand for real, lasting happiness. Indeed I think that is the strongest demand there is. NLP and technologies like it can be at the core of the tools that help people choose who they want to be and help (not coerce) them to act consistency with those choices.
Am not being flippant...I actually share your concerns very much, just that data mining in the real world has made me uber-cynical for the future of mankind.
Btw I think "subreddits on steroids" is an incredible testimonial catchphrase - it would have been enough for me to buy your app, but I don't own a smartphone.
The core NLP behind Prismatic is topic modeling; we don't use anything off the shelf, but something crafted pretty specifically to our needs.
We do model user similarity based upon interest overlap and social graph analysis. So we know how likely you are to care about what someone in your extended network shares.
The latter would be perfectly understandable, so not meant to be a hostile question, more curiosity out of personal interest of how you handle that aspect of private-sector research. Worries about that are part of what keeps me personally from jumping from academia. I'd like to do less paper-writing and more applied work, which fits nicely, but I'd still want to do some paper-writing and be able to discuss techniques publicly, which seems to fit more awkwardly. I assume it's possible to pull off both, but all the people I know who've left academia for startups have stopped publishing completely, and many of them doing ML/big-data stuff are quite secretive about their techniques.
In terms of industry research on the whole and publishing. It is true that you can't publish everything, but look at Google. Arguably some of the influential systems papers of the last decade or so have come out of Google. Google doesn't publish all the details of their search algorithms, but it turns out that because they address real-world problems they've done enough great stuff that some of it can safely be shared without endangering their moat.
Another aspect to consider is that while industry publishes less, we do tend to churn out useful open-sourced (Prismatic will definitely be doing that soon) that is of at least comprable utility to people out there as most papers.
- What would happen if viability of academic research was tied to one being a successful business person? (Asking in light of your comment elsewhere in this page re. "tenure system".)
One point you only lightly touched on, but which I think is worth restating is this: in academia theres this frustrating sense of "if you're not narrow, you can't be deep", whereas I see a lot of the more sophisticated bits of industry really valuing folks who strive for broad depth.
Would you agree with that assessment?
(admission: i'm presently having a go at building some tech products/tools that tie into a whole range of my researchy interests)
http://cdn.getprismatic.com/cdn/img/people/aria-bio__60cac85...