IBM's BLU

I'm very excited to see that IBM has finally announced BLU, an architecture-aware compressed columnar engine in DB2. My old friends at Almaden Research worked super hard on this project, and were waiting until the product was released before they could brag about the stellar performance results that BLU achieved internally. I'm looking forward to seeing the BLU papers finally getting out to the research community.  Here's Curt Monash's summary of the product announcement.

Edit:
Here's a great video describing Blink from Guy @ Almaden.

Javascript Applications

In a previous blog post, I talked about how Javascript is already the language in which so many mobile and web applications are being built. It is not a huge stretch to expect at least some of the back-end code to move to Javscript. Node.js and backbone.js are already making this easier. What I've recently been amazed by is how much of the native desktop experience can be re-created on the browser.
Check out Epic/Mozilla's port of the Unreal 3D engine to HTML5 here. I remember a time growing up when my desktop was too slow to run Unreal, and today, we can run it in the browser! Given this kind of performance,  applications like photo-editing or even light-weight video editing could be delivered over the web with snappy interfaces that don't require round-trips to the back-end for everything. Pushing some of the processing to the cloud will certainly make certain kinds of editing that were too demanding for an average desktop processor possible with a cluster of GPU-based servers on the cloud. It will also likely make new kinds of workflows and actions possible.

As for the less sexy back-end logic, having that be in Javascript, and running efficiently will certainly open up new possibilities. This isn't a new idea -- Netscape tried this in the mid-nineties and it didn't really take off. However, Google's V8 engine has made running Javascript applications so much more efficient, that replacing a Python/Django or Ruby On Rails stack with Javascript seems entirely reasonable. Consider the kinds of things you could do with this -- You could build a full web application in a single language (Javascript), and optimize it differently for a desktop browser, or a tablet, or a phone. As your application evolves, you might find it easier to move some functionality back and forth between the server and the client. I expect we'll see application servers provide a good environment for Javscript apps much like we have for Java (Tomcat, Weblogic, Websphere etc.).

I expect we'll see ever more interesting and sophisticated apps delivered on the desktop browser, and watch them quickly flow down to browsers on tablets, and eventually phones.

Interesting Papers

Here's an assortment of interesting papers from some of my colleagues in the recommendation/machine learning space that I've recently read.

• BPR: Bayesian Personalized Ranking from Implicit Feedback, Rendle et. al.
• Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior, Kanagal et. al. in PVLDB 2012
• Latent factor models with additive and hierarchically-smoothed user preferences, Ahmed et. al. in WSDM 2013
• Matrix Approximation under Local Low-Rank Assumption, Joonseok Lee et. al. ICLR
• Sibyl: A system for large scale supervised machine learning