In 2006, Strands, my previous company, organized and sponsored a Late Summer School on Recommender Systems in Bilbao. With a little help from our friends and a grant from the Basque Country Government, we invited a number of experts and promising Ph.D. students to a series of workshops to discuss the Present and Future of Recommender Systems. Before the workshops were over, a few of the attendees, including Professor John Riedl, were already talking about building an international conference on the wonderful interactions we were experiencing (some pictures here). One year later, the First ACM Recommender Systems conference (RecSys), was held in Minneapolis. In a few weeks, RecSys will get to its 8th edition. It’s incredibly rewarding to see how companies like Netflix, Linkedin, Google, Yahoo!, Baidu, IBM, Comcast, and Facebook picked up the baton and they currently sponsor what we started 8 years ago. Today, we announce that we’re launching a similar endeavor to create a new community on Predictive APIs and Applications.
Early this year, I electronically met Louis Dorard and Ali Syed. It turned out that we were all on the same mission to democratize machine learning with our respective companies. We also shared the vision that a predictive world will be a much better world. Louis and I later met in San Francisco. Shortly thereafter, we started discussing the need for a world-wide practical community that gathers annually to discuss the latest technical advancements and challenges on Predictive APIs and Applications. So I am thus very happy to announce that PAPIs 2014 – The First International Conference on Predictive Application and APIs will be held in Barcelona on November 17-18. We even have plans for repeating the conference in Sydney right before KDD next year and afterwards bringing it to the US in 2016 or wherever the community takes it to.
Over the last few weeks, we’ve been busy building up a highly technical and diverse Program Committee that will help select the first presenters at PAPIs 2014:
Erick Alphonse (Deloitte), Sébastien Arnaud (OpinionLab), Richard Benjamins (Telefonica), Misha Bilenko (Microsoft), Jason Brownlee (Machine Learning Mastery), Natalino Busa (ING), Eric Chen (NTT Innovation), Mike Cossy (IBM), Beau Cronin (Salesforce), Ricard Gavaldà (UPC), Andrés González (CleverTask), Matthew Grover (Walmart), Harlan Harris (Education Advisory Board), Jeroen Janssens (YPlan), Benedikt Koehler (dcore.de), Maite López (UB), Gideon Mann (Bloomberg), Jordi Nin (Barcelona Supercomputing Center), Mark Reid (ANU), Juan Antonio Rodriguez (IIIA), Marc Torrens (Strands), Jordi Torres (Barcelona Supercomputing Center), and Zygmunt Zając (FastML).
A first group of companies like BigML, CleverTask, Codole, Dataiku, GCS Agile, Persontyle, Strands, and Taiger, and much larger ones like Microsoft and IBM are helping us impulse PAPI’s and create the community. If your company is interested in helping us in this endeavor please contact us here.
We want PAPIs to become an open forum for technologists and researchers on distributed, large-scale machine learning services and developers of real-world predictive applications. We aim at seeding highly technical discussions on the way common and uncommon predictive problems are being solved. However, we want PAPIs to be an eminently hands-on conference.
One of the features that characterized the RecSys community was its original mix of researchers and practitioners. However, it had a clear imbalance on the academic side. In the 2009 edition in New York City, I gave a provocative opening keynote arguing that too much emphasis was given to new algorithms rather than to other under-represented topics like data, evaluations, and interfaces that were essential to build real-world recommender systems. I still remember the (positive and negative) reactions of many attendees. In my opinion, an incredible group of talented scientists were not paying that much attention to the crucial problems. A couple of years ago, Domonkos Tikk sent me a note that said:
I often cite your provocative statement on the 5% contrib of algorithms to the success of recsys. 3y ago I completely disagreed. Now I see that it might be 10 or 15%, but there are other major factors too. Well, we are also more in the industry than in academia…
In this first edition, we will focus on the pragmatic issues and challenges that companies on the trenches must face to make predictive APIs and applications a reality, and add academic tracks on future editions, once we understand them better.
So if you are working on an interesting Predictive API or Application and want to show the rest of the world your new advancements or discuss the challenges that you are facing please send us your proposal.
Predictive APIs and Applications cover a wider area of application than Recommender Systems. Therefore, their impact in our everyday’s life will be orders of magnitude higher and affect more industries than we can now imagine. So please don’t miss the opportunity to join this nascent community early on.
See you all at PAPIs in Barcelona!!!