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The fundamental feature of Web 3.0 that is going improve data connection is the creation of the semantic web. Right now, albeit intelligent, machines only have a somewhat limited ability to “understand” what humans ask them to do. For example, search engines use keywords and numbers to project query results, with no real grasp of the true “meaning” of terms. Content is identified but rarely understood, since even the smartest AI lacks the skill to interpret reality as humans do.
For example, when using facial recognition software, we can assign two different values to “male” and “female” actors, but the AI is not able to understand the meaning of “gender” or “sex.” This level of understanding requires an explanation — the name of this “thing” (gender) must have a “meaning” beyond the terms “male” and “female” which is defined as semantic metadata. By creating a metadata registry, we can provide the machines with a mechanism to interpret things beyond their names by means of classification, identification and formation of definitions. Semantic metadata is deeply interlinked and interconnected and creates a rich context around each piece of content.
Web 3.0 leverages the computing power of advanced AI to harness the full potential of the semantic web. Natural language processing and integration of information are used to provide machines with all the necessary context needed to obtain a more “human” understanding of the world and improved interconnectivity. As AngelList partner and venture investor Lee Jacobs explained, “It has been said that there is approx. 2.5 quintillion bytes of data created each day, machines are getting smarter and smarter, and algorithms have better predictive power; the rate at which we will learn about the world around us will continue to accelerate.”
The semantic web improves the ability of both users and machines to share and connect content since search and analysis will be based on a deeper understanding of the content itself as well as its definition. All information available, such as images, links, terms and videos will be correlated to understand the context leading to a much higher level of connectivity between data.
