aria

Sorry about that, we'll roll announcements into a single email next time.

We need read access to auto-complete emails for sharing and for invitations. Unfortunately, there didn't seem to be a separate read from write permission for that. Hope that helps.

In general, LSH is great for detecting near-duplicates which are very close, but we have two issues: (1) The stories we're looking for have a greater distance than LSH is great at detecting efficiently and (2) Because our feature vector has structure (named entities, n-grams, etc.) we have problem-specific 'coarse' feature-vector, which is good at detecting possible related candidates cheaply.

I'm not quite sure you got the gist of the post. The library isn't about scalability. It's about having a consistent way to describe how data sources accumulate/aggregate new values to do something useful with them.

We don't have a batch MapReduce problem and so Hadoop isn't really an option and, having used it in the past, not sure it's even a great choice.

Also, most of the data we're working with comes from content being shared and not number of users, so for our case in particular, dealing with a lot of data is an issue from day one.

Lastly, " solve the problem first and abstract out the framework later" I think is one of the core misconceptions in computer science and engineering. Abstraction lets you build faster if done correctly.

Again, if we only needed a simple key-value store and only had to deal with managing user data/events, we have built this kind of library out. Many of the reasons we built this library is because of the kinds of data aggregation we encounter in relevance ranking and machine learning.

fixed.thanks for noticing.

Yes. We don't have a definite date, but soon.

I'll put that up right now. Sorry it's a very new blog. Here's a direct link http://blog.getprismatic.com/blog/rss.xml

A lot of this advice is also applicable for managing your team of magical pixie fairies.

Any reason for that conclusion? I personally have known the instructor of the course for the better part of a decade and he's one of the finest CS educators out there and has numerous awards to show for it.

I've talked with him about this choice and he has a lot of sound reasons for making this move backed by his years of experience teaching in various languages.

What's your line of thought? I use Clojure many hours every day and while I think that LISP languages are awesome, I don't think they're a good choice for a 1st programming course either.

Really shocked they would place numbers in a table like that when the 'Scala Pro' version is doing something algorithmically smarter.

They note in the paper this distinction, but it should be marked in the table, because I'm sure 99% of people don't see that. Sloppy!

Thanks so much. Any insight from your startup we could benefit from?

Thanks so much. I'm really happy with the team too.

The code from the paper is available at http://groups.csail.mit.edu/rbg/code/content_structure/code....

You can see a demo of the site at condensr.com. There will be substantial changes to the site including predicting the best dish at a restaurant on the site soon. An academic paper should follow shortly.

Does this mean the Clojure Conj videos are all up?