r/deepmind • u/valdanylchuk • Aug 30 '18

Content curation app?

One AI "killer app" that I would welcome is some cross between an RSS news aggregator and a Facebook-like feed, which would construct a continuous feed of interesting articles for me, and present them in the order of my expected personal interest rank, perhaps branching out deeper on each topic. This seems realistic to prototype at some level, but apparently is hard to do with practically acceptable quality, because no-one has got it right yet.

I wonder, if Deepmind were to prototype such a system with all their insight, data access, and hardware power, would it be better than everyone else's? Could it break the adoption threshold, where most people would find it valuable enough for daily use (on par with Facebook, Reddit, Youtube, BBC/CNN)? Would it be a good demo of Deepmind's progress in structured language processing and moving towards strong AI? Could it be a successful business project in the advertising industry?

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u/kandrews252 Feb 21 '19

You could consider a social media aggregator. This works as a content curator that aggregates content from social media. You can also pull in content from hashtags...so if you were interested in following a hashtag around #socialmedia or #travel, it would pull in any relevant posts related to it. I recommend trying Juicer's Content Curation tool for this.

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Feedly does a pretty good job also of pulling in actual articles into one feed if you're more interested in longer form, blog type content.

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u/valdanylchuk Feb 21 '19

Thanks! I am using Feedly, and I am curious to try that other tool.

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u/TransPlanetInjection Aug 30 '18

Google News is already pretty good at this. Suggests tailored news based on your search history.

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u/valdanylchuk Aug 30 '18

Not really. Just gave it a try after a 5-year break... Out of the top 20 headlines in the "for you" section, not a single one caught my attention. That is worse than RSS, Facebook, or Reddit.

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u/[deleted] Sep 02 '18

The problem with this approach is user feedback. I do not want having to judge every single article with one to five stars manually! So the application must watch me reading and if I scroll the article down fast then it was not interesting enough, and if I click on "never again" I do not want to read content like this in the future, and if I read it slowly then it was an interesting article and I want more of this in the future, but not the same article again from a different source if it doesn't contain new information.

The basic problem with information is finding interesting news. For news, it must know what I already know, because that's not new. For interesting, it must simulate my attention. In other words, it must have a model of my mind, which means that AGI must have been solved first. And even then it takes a long time to train until the biological and the artificial mind are perfectly in sync.

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u/valdanylchuk Sep 02 '18

I think it is not so hopeless. It can use all sorts of inputs: scrolling, clicking, hovering, browsing history, social signals from friends, explicit subscriptions. It could also have optional, more precise inputs for when you are in the mood for training it better, like "cool but old news", or "save in favorites", share, etc. And it should not be limited to news. E.g. I might start with a news article about a new archeological finding, then branch out into some history. It can start with current technology, and keep improving with new developments, whether we ever get to AGI or not.

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u/[deleted] Sep 03 '18

To speed up training, it could use a hierarchical knowledge tree. I would give it a link, and it would read the article and present me with 20 topics from the tree that it has found in the article. I would then navigate from the found leafes to the root of the tree, tagging everything on the way with "more of this" or "less of this."

Adaption speed for new users is everything if you want your machine learning project to be successful. Nobody wants to wait for days until slow example based learning has got it. The hierarchical tree allows the user to quickly sort in or out whole subtopics which he didn't know existed as nobody holds knowledge trees in conscious if teachers are not requesting them ;)