Here’s What Google Search Will Look Like in 10 Years

From its meager beginnings as a student search engine project called BackRub at Stanford University, to the powerhouse search engine that is both a noun and a verb in one, Google’s path has been one of growth and constant adaptation with the times.
Examining the path of that history provides some interesting insights into what the world’s most popular search engine will probably look like in 10 years.
Why 10 years? Because 10 years encompasses nearly the entire lifetime of Google, from the moment of its first major algorithm update in 2003 called “Boston”. In 10 years, the search engine will probably look nothing like it does today, but it will serve a multitude of needs in everyday life well beyond those that exist on the family computer.

The History of Google Search

In 1995, when Larry Page and Sergey Brin first met and started collaborating on the search engine that would eventually become Google – then called BackRub – it’s doubtful they could have ever imagined the size and power of the company that would result from those efforts.


By 1999, the small company outgrew its garage-beginnings, and established its first real office in Palo Alto with eight employees. 2002 is when things got really interesting, with the Google Search Appliance, a major overhaul of AdWords, Google Labs, Google News and the first set of Google APIs for developers.
It isn’t surprising that the following year brought Google’s first algorithm update meant to thwart SEO folks who were – up to this point – quite successful at landing pages at the top of Google results through keyword stuffing and building huge backlink farming campaigns.
“Boston” curbed the backlink game a little bit, and so started the constant tug of war between those developing the Google algorithm for better results, and efforts of webmasters to land their websites and web pages as high in Google search results as possible.

The evolution of that algorithm – aside from attempting to thwart SEO gaming efforts – actually reveals a great deal about the future vision of Google Search planners, and where they have been steering the company up until this point. Here’s the breakdown of those major updates that offered that insight.
Brandy (2004) - Latent Semantic Indexing (LSI), which is using a mathematical technique to identify relationships within concepts inside of a collection of text.

Personalized Search (2005) – This update used the user’s search history to affect search results.
Google Local (2005) – Local business data gets integrated into Google maps.
Universal Search (2007) – News, video and local results are integrated with regular search results.
Real-Time Search (2009) – Social content like Twitter get integrated into a real-time feed.
Caffeine (2010) – Improves indexing of sites, improving the freshness of search results.
User Search (2012) – Google+ and authorship integrated into search results.
Venice (2012) – Better local results for broad queries.
Knowledge Graph (2012) – Information and image relevant to your search term show up next to regular results.

These were all of the updates that were not meant to thwart black-hat SEO efforts, but were instead intended to evolve the algorithm to produce a new generation of information in a brand new way, whether that involved integrating information about the user doing the searching, or trying to use something like the Knowledge Graph to predict what the user really intends to look for.
Predictive Search Results

The science of the search algorithm has applications well outside of the Internet search page itself. When you combine the multitude of mobile devices and the Internet of Things movement, the use of the search algorithm to feed everything with the right data becomes even more critical. Google may be best placed to do it, especially considering it has already established one of the most popular mobile platforms on the planet – Android.

Past efforts to incorporate user information and behavior into search results points to a future where artificial intelligence would be used to better predict what the user wants to know even before they ask it. Google Now is a good example of an early generation of this, and Google Glass is a clear example of an alternative delivery system for those search results. There is a growing movement toward augmented reality, and Google appears poised to take advantage of it.
In an interview with the BBC, Amit Singhal, Google’s head of search, explained it this way:

Read More