Fair enough. Not endorsing the idea of Cicada but it does open up an interesting conversation about the future of the internet. Can we really say "nope, the internet is good enough." That like saying "nope the horse and buggy works fine. why change it?" Not putting words in your mouth, just making a point about the general trend of trite comments here being hostile to new ideas. I think we should discuss the viability of the internet in the near future.
Good points. I'm not opposed to new ideas, but what I like most about the internet is just how simple it is. Whatever comes next, I don't believe we should lose that.
Looking at this it appears the github large avatar for the-laughing-monkey user doesn't match the thumbnail image. Maybe it was recently changed. The large version is an illustration, but the small version gets hits on TinEye for Dan Jeffries (the author of the book mentioned as inspiration).
A search for Dan Jeffries cicada turns up some related material. Seems strange that the link to the book on the iamcicada page doesn't explicitly spell out the author's relationship to the project.
Maybe somewhere along the way, he decided to go pseudonymous? I'm sure he's an HNer, maybe he'll weigh in.
I'm putting together a monthly newsletter featuring stories of the trials and triumphs of technological innovation in complex, regulated industries.
Why? Because hard problems are not easily solved, but they’re worth doing. The first issue goes out March 31.
Some of the industries covered will be government, healthcare, finance, and defense. Each issue will contain a mix of original and curated articles that focus on quality and substantive insight.
We were all drawn to applying the statistical, experimental, and algorithmic approaches we learned in graduate school (and in our spare time) to a range of problems in industry. Every project has a big learning component that keeps things exciting and fresh.
Our first handful of clients all came from our professional network. I've been a developer and consultant for a long time (shockingly, over half my life!) and so, despite selling my companies and heading to graduate school, I had a bit of a network of other founders who knew me and were supportive of the new venture.
A few lessons learned, in brief: (1) Try really, really hard to be specific about what you offer (even when in reality you offer a lot of different things), (2) Write great proposals -- they become the project bible and really help streamline client conversations, and (3) Understanding a client's data and business always takes longer than you'd think.
Haven't had a chance to play with it yet but clicked around and it looks interesting. I like the idea of users posting their own coding challenges. The one thing I noticed this suffers from is a lack of a community base. Just clicking through the challenges on the front page I saw no discussions. But with that said I think this could be a neat application for new programmers. I know someone who is going through freecodecamp now. I'll ask them to take a look at this and see what they think.
Please do! And if you can, let me know what their experience is like: matt@edabit.com
As for the lack of community, the site has been live for about a week now and it's already got 1000 registered users. In a few months I think it will be very active!
Discourse has devolved so much it is going to be tough getting people to debate respectfully around different viewpoints. It might be better to recruit a handful of people who can set the tone for these debates and then eventually open it up for a larger community.
I agree with your sentiment about publications just rehashing the same story. That's a large reason why I started http://emergentdata.co. It's not political focused rather focuses on technological acceleration and large global issues like water scarcity and mass migration. I try to curate content around a few principles:
-Try to get to the most original source
-Stick to real events, avoid speculation and hearsay
-Avoid sensationalist headlines
Alchemy is doing all the NLP. Each article is extracted for concepts and entities (as defined by Alchemy in their documentation). I normalize each term that is extracted in order to prevent duplicates (there are some duplicates that still sneak through so it still requires a little bit of data maintenance). So the way this looks is that their is one node for a term say "Machine Learning." In one article "Machine Learning" is a concept with a negative sentiment and high relevance and another article it is an entity with low relevance but positive sentiment. The relationships house the sentiment and relevance properties: (machine_learning)-[relevance,sentiment]-(article).
The suggested readings sections pulls the most relevant concept of that article and finds connected articles with the same concept at a high relevance. This way suggested articles are more than just key word hits. It's all about relevance. I'm still continuing to tweak this query and there's a lot more that can be done with it such as matching sentiment and emotion. As the dataset grows I'll look to add a feature that pulls a list of articles based on a cluster of highly associated entities.
As for Alchemy, I've tried a number of different NLP APIs and, in my opinion, none of them have come close to matching Alchemy's accuracy. It does make mistakes but at a low enough level that it's easy to manually correct.
Thanks for the background. I'm working on a similar project but currently parsing news articles using a collection of specific rss feeds and calling Google's NLP API with the text. It sounds like AlchemyAPI seems be a better fit in this case.
How are you finding Neo4J is handling the scale of reading and writing all these stories? I've had a positive experience so far but I'm only in the few thousands range.
Neo4j handles read/write seamlessly I have found, but I'm only around 10,000 nodes and 20,000+ edges. I've heard use cases for Neo4j in the range of 50M+ nodes. My position on this is not whether Neo4j can handle it but whether your code and infrastructure can.
Hi HN: I built a curative news feed covering advancements in technology and global issues. I'm utilizing Neo4j and AlchemyAPI, as well as some custom code, to create a knowledge graph in the background. Have a few ideas of additional features for the dataset but would love to hear some feedback.
FWIW- I do agree they overthought everything.