Role of Knowledge Graph and Artificial intelligence in future Robotics and Google's Semantic search
Google is spreading its wide hand in the area of web search amazingly and land-marking itself in the history of internet search. In this respect, Google is experimenting on various components of Semantic search technology which is being considered as the future of web searching world.
Semantic search is a future search engine technology where meaning and context of search words will be used to refine search results. In other words Google will answer questions rather than just look for words, in near future.
As Google's semantic search technology is an upcoming technology with integration of Artificial Intelligence and based on Knowledge Graph Repositories so, here I am discussing some facts about these two important components of Semantic search technology.
What is knowledge Graph?
Google wants to make its search engine intelligent enough to understand the relation between different entities in the world. The idea is to build a huge knowledge graph of interconnected entities and their attributes.
As per Amit Singhal, Senior Vice President of Google: "Google is building a huge in-house understanding of what an entity is and a repository of what entities are in the world and what should you know about those entities".
The knowledge graph is an advance and refined technology with great power and multiple complexities. For making a giant knowledge graph, Google is building the infrastructure for providing instant results for more algorithmically complex search tasks. Right now, Google's Knowledge graph has 200 million entities. With improvements in infrastructure Google is upgrading its knowledge graph more and more and this is the Google's strategy to stay ahead of rivals in future.
"The knowledge graph will work as an encyclopedia that will hold and gather structured information from the web. This will enable Google search engine to better understand searcher's query and respond with more relevant results for complex queries."
History of Knowledge Graph
The concept of knowledge graph come in light with purchase of American company Metaweb (developer of Freebase) by Google on July 16, 2010. It was an American software company that would maintain an open database of things in the world. Freebase was a community-built knowledge base pack with some 12 million canonical entities.
Freebase was a huge knowledge base consisting of metadata. It was a collection of structured data to provide a global resource to people for information like movies, books, TV shows, celebrities, locations, companies and more.
"The aim behind Freebase was to enable the web to understand the relationship between real-world entities to deliver relevant information more quickly."
Freebase was just like a small baby who has now grown up to a young knowledge base having a huge in-house of 200 million interconnected entities.
How Knowledge Graph will enhance Google's search engine capability?
Knowledge graph is the foundation of Semantic search engine. Knowledge graph will make the search engine capable to respond itself with more contextual information to a query rather than relying on other websites for providing information; as a conglomerate of information will already be available there that shall be aimed to answer possible queries that people will be searching for.
”The relationships between entities will be available in repositories of knowledge graph that will make Google search engine intelligent enough to find relationship between search query words as contents will rule the web world in future.” This changing scenario of Google semantic search engine will definitely make an impact on future SEO techniques.
Role of Artificial Intelligence in Google's Semantic search technology:
Google wants to make its search engine act like a human brain.
"In real life a human brain transforms the real word objects and images into entities and understands the relations between their attributes to find out the accurate information about surrounding activities of objects."
But while talking about Google search engine:
"The idea is to transform words of a page into entities that really mean something and have related attributes, just like a human brain does naturally". This ability of a computer is termed as Artificial intelligence.
To understand the real intention of a searcher Google applying artificial intelligence for Semantic Search technology to work like a dictionary that understands the meaning of the query rather than parsing through keywords.
Role of Knowledge graph and Artificial intelligence in future Robotics:
Robotics is the perfect combination of mechanical engineering and computing. A mechanical engineer built a robot while a computer makes it operational. But the purpose is not only to make a robot just a working machine but making it as intelligent as to take some meaningful decisions also.
Here is where the Knowledge graph information and artificial intelligence encounter very closely to result a better and intelligent output. The main problem for robotics is its language capabilities. The knowledge graph repositories will work as the foundation for how robotics would incorporate into future of robot-human interaction. Access to Knowledge graph huge in-house (interconnected entities and relationship of their attributes) will make a robot accomplished in linguistics.
As per Senior Vice President of Google: Future robots with access to Google's entity-based search engine might be able to understand that the "tiny baby" (an entity in knowledge graph) they are caring for is small, fragile and always hungry, and includes attributes like "no solids."
We are going to see various applications of artificial intelligence in near future. Emerging technologies will widely use artificial intelligence and conglomerate of information like knowledge graph to show their intelligence.
Google has already started using such technologies to regularly update its services like search engine and mail services. Semantic search and 3D Graphic Calculator for search engine are instance for the same.
Robotics is an emerging technology that has a bright future. Though robotics is completely based on Artificial intelligence yet Knowledge graph will be most useful for refining this technology and let us to see most intelligent robots serving around us, in near future.