- One Click Captcha (Wired) — Google’s new Captcha tech is just a checkbox: “I am not a robot”. Instead of depending upon the traditional distorted word test, Google’s “reCaptcha” examines cues every user unwittingly provides: IP addresses and cookies provide evidence that the user is the same friendly human Google remembers from elsewhere on the Web. And Shet says even the tiny movements a user’s mouse makes as it hovers and approaches a checkbox can help reveal an automated bot.
- The Responsive Enterprise: Embracing the Hacker Way (ACM) — Letting developers wander around without clear goals in the vastness of the software universe of all computable functions is one of the major reasons why projects fail, not because of lack of process or planning. I like all of this, although at times it can be a little like what I imagine it would be like if Cory Doctorow wrote a management textbook. (via Greg Linden)
- Pizza Hut Tests Ordering via Eye-Tracking — The digital menu shows diners a canvas of 20 toppings and builds their pizza, from one of 4,896 combinations, based on which toppings they looked at longest.
- How Browsers Get to Know You in Milliseconds (Andy Oram) — breaks down info exchange, data exchange, timing, even business relationships for ad auctions. Augment understanding of the user from third-party data (10 milliseconds). These third parties are the companies that accumulate information about our purchasing habits. The time allowed for them to return data is so short that they often can’t spare time for network transmission, and instead co-locate at the AppNexus server site. In fact, according to Magnusson, the founders of AppNexus created a cloud server before opening their exchange.
"machine learning" entries
Solutions to a number of problems must be found to unlock PAPI value.
In November, the first International Conference on Predictive APIs and Apps will take place in Barcelona, just ahead of Strata Barcelona. This event will bring together those who are building intelligent web services (sometimes called Machine Learning as a Service) with those who would like to use these services to build predictive apps, which, as defined by Forrester, deliver “the right functionality and content at the right time, for the right person, by continuously learning about them and predicting what they’ll need.”
This is a very exciting area. Machine learning of various sorts is revolutionizing many areas of business, and predictive services like the ones at the center of predictive APIs (PAPIs) have the potential to bring these capabilities to an even wider range of applications. I co-founded one of the first companies in this space (acquired by Salesforce in 2012), and I remain optimistic about the future of these efforts. But the field as a whole faces a number of challenges, for which the answers are neither easy nor obvious, that must be addressed before this value can be unlocked.
In the remainder of this post, I’ll enumerate what I see as the most pressing issues. I hope that the speakers and attendees at PAPIs will keep these in mind as they map out the road ahead. Read more…