Tag Archives: mobile devices

Nov. 16, 2010 SDF Green Data Centers

On Tuesday November 16, 2010 in San Francisco at Nixon Peabody, SDForum held a Clean Tech Breakfast on “Greening Your Data Center.” Mavis Yee of Nixon Peabody moderated panelists Rick Chateauvert of EMC, Mike Dauber of Battery Ventures, Andrew Feldman of SeaMicro and Mukesh Khattar of Oracle.

All that data floating in the cloud is really stored in brick and mortar data centers around the world. These server farms currently use huge amounts of electricity generating waste heat. We are reaching the physical and engineering limits of current technology to cool these buildings. Incremental improvements are not enough. Companies must rethink everything from HVAC to the power consumed by the smallest semiconductor.

Ultimately the millions of mobile devices demanding all this data may provide a solution. The semiconductors, flash memory and power management software used by smart phones could dramatically the increase the efficiency of future data centers. There would be a great opportunity for someone to develop a data center app for that.

Copyright 2010 DJ Cline All rights reserved.

Oct. 13, 2010 SDF IQ Engines

On October 13, 2010 in Palo Alto at Pillsbury Winthrop, the SDForum Emerging Technology SIG hosted Gerry Pesavento, CEO and Co-Founder of IQ Engines and Pierre Garrigues, Director of Research and Development. They talked about “Trends in Visual Intelligence.”

They explained how their image recognition engine takes advantage of human crowd sourcing from the millions of mobile devices taking billions of pictures everyday around the world. If someone takes a picture and they do not tag it with identifying data about the content, the camera merely assigns the images a number, which does not help much.

Pesavento said “The mobile camera is evolving to an ‘intelligent visual sensor’ to power mobile visual search, vision for the blind, photo labeling and augmented reality.” IQ Engines is sorting through images from mobile devices is a user driven strategy of working from images that people are already interested in rather large libraries of stock images. Putting human recognition in a real-time loop to assist machine learning dramatically speeds up the accuracy of recognizing images. The better a person identifies the image, the higher their ranking. The key is their scalable any-image recognition engine. All this easier with the growth of the cloud, new database and analytics tools.

The most interesting development to me will be the new high definition three-dimensional digital cameras. Soon many mobile devices will have two cameras to give the kind images reminiscent of stereo-optic images from the 1800s or Viewmaster images from the 1900s. Until then I will have to take two pictures of the same stationary object a few inches apart and process them together later. (Now you know why I do that funny move when I take your picture. Always thinking ahead.)

Copyright 2010 DJ Cline All rights reserved.