I just returned from the Google Faculty Summit, a gathering of ~100 professors (mostly computer scientists) in Mountain View from universities across North America, and a few from South America as well. Google holds this event annually, as part of their university relations effort, fostering recruiting channels and research collaborations between the company and academia.
One of the highlights of the 1.5-day program was an informal talk by Larry Page, Google co-founder (and U.Michigan alumnus). Larry discussed a wide range of topics, devoting surprising attention to the topic of artificial intelligence, which he argued was being under-emphasized in computer science research these days. He expressed his opinion that much current AI research lacks the ambition to tackle the really fundamental problem, which he suggested would ultimately be solved with simple ideas and a huge engineering effort to bring to scale. (I suspect that most AI researchers would broadly agree with this, though they might quarrel with sweeping characterizations of the field.) Larry also asserted that Google’s algorithms for placing ads on content pages (a fundamental operation of their AdSense service) came out of their early efforts on more general AI text understanding problems. Thus, he credited AI research with half of Google’s current revenue.
Visiting innovative companies is of course a most worthwhile way for even the busiest academics to spend their time. In addition to learning about emerging technologies and making valuable connections, we get a glimpse of what problems these companies think are important, and where the real technical challenges are. Reflecting on all the impressive work from Google we saw presented at this meeting (Google Earth, Flu Trends, Book Search, Statistical Machine Translation, Wave, just to name a few), however, it occurred to me that once Google recognizes that a problem is important and ripe for innovation, they are probably well on their way to producing great solutions. Perhaps a better strategy for academic researchers like myself is to try to diagnose where Google (and other companies) may have a blind spot–problems that are important and solvable but the industry players just don’t see that yet, or perhaps do not see how the advances would benefit the company. Regardless, it’s clearly advantageous to be aware of what the capable people at Google and other cutting-edge technology companies are up to.