Semantic Technologies: The Next Step of AI

Then, just as suddenly as it starts, it recedes into the background, replaced by a new crop of technological, scientific or corporate jargon. But the trend does not die. It just disappears for a certain span of time and then comes back again, slightly changed in form and stronger than before. Something exactly like this is taking place with semantic technologies, previously known as the semantic web.

Talk about semantic technologies has been around for more than 40 years and lately, there has again been widespread interest with regard to such technologies. It is, in fact, the application of these technologies which make possible the Natural Language Processing (NLP) capabilities of IBM Watson, the ongoing refinement of Google search results, or the provision by DBpedia of a knowledge base from Wikipedia articles. Such technologies hold the key to the future of Artificial Intelligence (AI) as it is these technologies which will allow us to add knowledge and logic to AI as it exists today.

Before we get into how semantic technologies can change the world, it is necessary for us to understand what semantic technologies and machine learning are; for it is the combination of these two differing technologies which will lead to a quantum leap in the capabilities of AI in the near future. Semantic technologies basically use formal semantics to derive meaning from disparate sets of raw data. This is done by using tools, methods and techniques that help categorize and process data as well as define the relationships between different concepts and datasets. These relationships are described in a language that computers can understand and compute upon. Thus, semantic technologies allow computers to not just process strings of characters but to also to store, manage and retrieve information based on meaning and logic. [...]

 

To read the whole post and interact, please visit the SogetiLabs blog: Semantic Technologies: The Next Step of AI