There is a lot of buzz around online assistants in the past couple years. If you had asked most people five or six years ago about having a personal online assistant in their home, they would find it absurd. But now we have devices from Apple, Amazon, Google and other companies in many first world homes.
People have embraced technology such as the Echo from Amazon or Google Home. Why? Because these devices are designed to make our life easier. Want to know the weather? Ask Alexa. Want to set an alarm or set aside time for a meeting next week? Tell the online assistant and it will do the relevant bookings for you.
But what if online assistants could do so much more? And not just for people, but for companies and educational institutes too.
Most people have heard about the semantic web in passing, but not in any great deal. The concept of the semantic web is to create a web where information is easily accessible and understandable by machines.
Why is the semantic web an important concept? Because machines have a hard time understanding and interpreting information when it is written out for humans.
For instance, many of the sites that we use to gather information have words formatted around our way of understanding details. Amazon will have the title of a book and its price listed in a way that you can understand. But it does not necessarily mean that a machine could understand that information. Many times, machines cannot understand that information.
It is why online assistants are so limited in what they can do. Setting meetings and finding basic details are easy, repeatable tasks that online assistants are programmed to do. But it is still very hard for machines to gather complex information, determine its accuracy and interpret that information.
That is why so many experts believe the semantic web is a crucial concept.
Future of AI
In many ways, the future of AI will be determined by the success of establishing the semantic web. If there is a version of the web where machines are able to easily read, understand and interpret information, it can only benefit people, organizations and businesses.
It is complicated work to develop languages and concepts so that information we consume is processable by machines. But it is vital work that is going to shape the coming decade of innovation.