The great information revolution of the last twenty years or so started with the advent of the Internet and browsers in 1994. Early attempts were amazing in how much new stuff was being invented but the real breakthrough of scale came with Google in 1998.
They unveiled to the new a spanking new light and fast search engine with a quirky name. It was based on the first great graph of our times, the Web graph. It had 100 million links when they started, which seemed huge at the time.
Google showed from the start huge advantages of scale. They took the leadership position and never relinquished it. The scale of the Web is in hundreds of billions of pages for the current Google index and many trillions for all the pages they got.
After Web, the next great graph turned out to be the Social Graph. Facebook was the one taking it to greatness, but they were not the first. Friendster and Myspace, two early social network pioneers failed, because of their own mistakes in inflexibility and short-term thinking.
Social Graph is much smaller, with about two billion nodes and hundreds of billions of edges. Its power comes from the nature of its nodes are edges, which are people and their profiles and their friendships. Facebook has done a masterful job riding a huge advertising wave on profiles from the Social Graph.
This brief overview sets the ground for the next graph of our times, the Reasoning Graph. It is an AI graph, which offers tantalizing possibilities in terms of what it can be used for.
Reasoning is at the core of all AI, yet it has been almost completely neglected because of all the buzz and hype revolving around concepts such as computer vision processing and self-driving cars, conversational assistants and computers playing games. And it is not that all the commotion is undeserved as all the progress has been remarkable.
But all that still leaves us no closer to the true goal of AI, which is true machine intelligence. In the following posts we are going to embark on this journey.