The Age of Artificial Intelligence
Future-set science fiction books and movies no longer feature artificial intelligence (AI) as a major story aspect. Machines are progressively doing activities that once required human brains in many facets of our life.
A wide range of sectors have AI applications currently or in the future. For instance, search engines and online retailers have grown extraordinarily adept at anticipating what customers are interested in buying by continuously improving algorithms that monitor and learn about people based on their online behaviour.
AI meets IP
Research on patents and intellectual property is also being affected by AI. For decades, patent professionals have searched through vast amounts of literature utilising sophisticated syntaxes and human categorization methods, using Boolean and positional search for patent-related finding. This paradigm is evolving thanks to machine learning and AI, which increase retrieval accuracy and efficiency. Using machine learning techniques, modern searching can get past the inherent ambiguities that hinder traditional keyword search.
AI-enhanced semantic search, which enables the use of everyday language to find documents containing related concepts or meanings, is one technique to boost patent retrieval. For instance, the unique Semantic Gist® engine that powers our InnovationQ Plus® search software recognises that single terms like "vehicle" and "car" and pairs of terms like "vehicle" and "car" might have comparable meanings.
Another illustration is aviation, which is the most cautious and strictly controlled means of transportation in the world. Although parameter-driven autopilot systems have been available for a while, AI is becoming more and more important.
So how does this work?
One example is the extraction of concepts and meanings from patents and associated literature by a deep belief neural network. Because of how much they resemble the functions of the human brain, neural networks are so-called. Machine learning, in which a computer analyses a lot of data and extracts meaning from it, is made possible by neural networks.
In a neural network, complex concepts are encoded as mathematical vectors of the common ideas discovered by AI research. Similar to the human brain, the neural network is the mechanism that organises concepts inside large, complex data sets.