Dear all -- I've long promised (threatened?) to begin efforts to commercialize Apache Mahout. Given my line of work in VC, I see evidence for positive symbiosis between open source and commercial enterprise. We have evidence from the growth in user base and mailing list, as well as the Mahout in Action book, that this is becoming another successful Apache project. It's time to start bringing more of Mahout to the commercial world, and in turn bring those benefits back into the open-source project.
To that endm I've been working on a heavily product-ized, somewhat evolved, version of the recommender engine code available in Mahout. After about six months of work, it's ready to announce. Please meet a new startup company and software product, Myrrix (http://myrrix.com). Well, at least, it's ready for pre-launch of part of the product. The announcement (http://myrrix.com/myrrix-pre-launches/ ) tells part of the story, and the design doc (http://myrrix.com/design/ ) tells more, but I'll summarize key points here: - Aims to add packaging, documentation and support, to product-ize - Reuses Mahout APIs, some code, and certainly presented as a "Mahout-based" platform - Two-tier architecture: serving (or "speed") layer acting in real-time, coordinating with distributed Hadoop-based computation layer. Best of both worlds. - Leans heavily on a variant of the alternating least squares algorithm - Serving layer is free/open source and is a complete solution for small-to-medium recommender problems - Full distributed architecture, including hosted offering, is the commercialized (read: for-pay) part I would welcome community support in telling me what you like and don't like about this. All the better if anyone is in a position to actually run and test the Serving Layer: http://myrrix.com/download/ I intend this to bring more profile, attention, and work to the Mahout project, rather than subtract from it. I hope to see more Mahout-related commercializations, beyond the inclusions in distributions we're already seeing, in 2012, as it's key to the long-term project health. It's most certainly going to be the year of the application layer (analytics, machine learning) for Big Data. Thank you! Sean
