As I understand it, it boils down to this: the current high tech focus is on using data to improve ad revenue via social media. Or as Jeff Hammerbacher (a former Facebook research scientist) says, “The best minds of my generation are thinking about how to make people click ads. That sucks.”
It sucks because the innovation process of massive social media companies focuses on ads, and so there has been only minimal transferable benefit for other industries that don’t make their money off of marketing. This is bad because transferable innovation makes for good economic growth and stability.
Here’s where Jeff Hammerbacher comes in. He’s developing software that will allow scientific researchers and other business sectors to apply the marco-level data management tools Google, Facebook and Amazon use to target ads.
Here’s a snippet:
After quitting Facebook in 2008, Hammerbacher surveyed the science and business landscape and saw that all types of organizations were running into similar problems faced by consumer Web companies. They were producing unprecedented amounts of information—DNA sequences, seismic data for energy companies, sales information—and struggling to find ways to pull insights out of the data. Hammerbacher and his fellow Cloudera founders figured they could redirect the analytical tools created by Web companies to a new pursuit, namely bringing researchers and businesses into the modern age.
Cloudera is essentially trying to build a type of operating system, à la Windows, for examining huge stockpiles of information. Where Windows manages the basic functions of a PC and its software, Cloudera’s technology helps companies break data into digestible chunks that can be spread across relatively cheap computers. Customers can then pose rapid-fire questions and receive answers. But instead of asking what a group of friends “like” the most on Facebook, the customers ask questions such as, “What gene do all these cancer patients share?”
Eric Schadt, the chief scientific officer at Pacific Biosciences, a maker of genome sequencing machines, says new-drug discovery and cancer cures depend on analytical tools. Companies using Pacific Bio’s machines will produce mountains of information every day as they sequence more and more people. Their goal: to map the complex interactions among genes, organs, and other body systems and raise questions about how the interactions result in certain illnesses—and cures. The scientists have struggled to build the analytical tools needed to perform this work and are looking to Silicon Valley for help. “It won’t be old school biologists that drive the next leaps in pharma,” says Schadt. “It will be guys like Jeff who understand what to do with big data.”[read the full article]