On May 7th, 2013, Ron Kaplan spoke at the CMU Silicon Valley Campus and claimed that now is the time for the “Conversational User Interface (CUI).” He claimed the Graphical User Interface (GUI) has “topped out” and showed an old cluttered and complex version of Expedia’s GUI to prove his point.
Forty years ago, Ron and colleagues at Xerox PARC published a paper about an early intelligent assistant called GUS (Genial Understanding System) that helped a user plan a flight from Palo Alto to San Diego. However it is only recently that the Conversational User Interface has become possible. Forty years ago, the quality of speech recognition was poor. Difficulties with ambiguity in natural language and with the sheer complexity of language slowed progress. The telegraphic nature of conversation and the fact that so much of what is communicated is unspoken also slowed progress. Ron argued that advances in speech recognition and in computational linguistics will soon make Conversational User Interfaces a reality.
Kevin Foster talked about Stream Computing in general and at IBM at the monthly meeting of the SVForum Business Intelligence Special Interest Group on December 4th, 2012. The slides are available at the BI SIG’s home page on SVForum’s website.
Stream computing is part of a paradigm shift from on-line transaction processing and analytical processing (OLTP and OLAP) to RTAP: Real Time Analytical Processing. IBM’s RTAP offering is called Infosphere Streams. It provides a programming environment that enables users to set up dataflow graphs. It takes advantage of eclipse and is part of IBM’s larger Big Data platform which also includes text analytics.
Tom Fawcett, Machine Learning Architect at Proofpoint, gave the San Francisco Bay Area ACM Data Mining SIG an insider’s view of email filtering on Monday, October 25th, 2010. Proofpoint has thousands of customers large and small and guarantees in their service level agreement that customers will get no more than one spam message per 350,000 emails. Tom pointed out that research on spam filtering has little to do with what companies do in practice in the “real world” and then he revealed a lot about how commercial spam filtering works.
Peter Farago and Sean Byrnes gave a juicy and surprising presentation about Flurry‘s mobile app analytics at the SDForum Business Intelligence Special Interest Group meeting on 10/19/2010 in Palo Alto. The title of their presentation was: ”Your Company’s Mobile App Blind Spot” and it provided both business and technical insights.
Flurry made a big splash in the news when Steve Jobs got pissed off at them and called them out by name in an interview because they outed Apple’s iPad when it was still a closely guarded secret. (See a short video outtake of the interview at VentureBeat.) Apple responded by changing legal agreements to exclude some third party analytics and some advertising.
Salesforce’s CRM analytics architect, Donovan Schneider, presented an overview at the SDForum BI SIG meeting on May 18th, 2010. Salesforce’s view of analytics is that it should deliver insight that is accessible to mere mortals, real-time, and trustworthy.
James Taylor, CEO of Decision Management Solutions, gave a talk on “Performance Management and Agility” at the monthly meeting of the SDForum BI SIG on Tuesday, April 20th. He argued that traditional BI and performance management result in dashboards that measure and monitor like instrument clusters in cars. But what is needed is something more like the cockpits in airplanes: there should be buttons and levers and so on that enable the “pilot” to act on the information presented by the dashboard. James argued for combining performance management with decision management (a term he pioneered) so that information supports decision-making that leads to action.
The first SDForum conference on analytics, “The Analytics Revolution,” was held in Mountain View on Friday, April 9th, 2010. The conference focused on recent advances in analytics, new opportunities afforded by these advances, and ways companies can take advantage of the analytics revolution in progress.
The “Competing on Analytics” panel at the SDForum Conference on “The Analytics Revolution” included people from companies using analytics to “compete at the highest level” according to the five stage maturity model in the book “Competing on Analytics: The New Science of Winning.” The panelists (Amr Awadallah, Cloudera; Joshua Klahr, Yahoo!; James Phillips, Northscale; Joydeep Sen Sarma, Facebook) represented a good mix from the relatively new Twitter to the larger, older, more established eBay. David Steier, PriceWaterhouseCoopers, moderated the panel.
The panel on “Analyzing Big Data” at the SDForum Analytics Conference on “The Analytics Revolution” included representatives of two companies that analyze data on a petabyte scale (Joydeep Sen Sarma, Facebook and Joshua Klahr, Yahoo!) and two software companies that stand behind open source infrastructure components that are often used to build analytics platforms (Amr Awadalla, Cloudera/Hadoop and James Phillips, Northscale/Memcached and Membase). The moderator, Owen Thomas of VentureBeat, started off by asking the panelists whether “big data” is a Silicon Valley phenomenon that will soon spread to the Fortune 500 and the rest of the world.
Ronny Kohavi (Microsoft) started out by telling a famous true story about Greg Linden’s experience moving a recommender to the shopping cart at Amazon. A Senior VP of Marketing vetoed Greg’s proposal fearing that it would distract customers from checking out and paying for the items already in their shopping basket reducing conversion. This is where the “HiPPO” in the title of Ronny’s presentation comes from. It stands for the “Highest Paid Person’s Opinion” and sometimes for the person (e.g., the VP) holding the opinion. The Amazon story had a happy ending because Jeff Bezos had established a corporate culture that allowed for experiments to be run so Greg was able to run an experiment to test the hypothesis of the HiPPO. It turned out that conversions did indeed drop but the increased revenue due to customers purchasing recommended items was substantially greater than the loss.