With the advent of Artificial Intelligence in every imaginable sphere that matters, it is hardly surprising that innovators are now in a rush to build their Intellectual Property portfolio in AI. The popularity of Artificial Intelligence, machine learning, neural networks and all other things related to Intelligent machines has been on the rise for quite some time now. A similarly whopping growth has been observed in the number of machine learning or AI related patents/applications which have been filed in the recent years. A recently published article revealed that patent applications based on machine learning have nearly quadrupled in the last few years, owing to the widespread use of the same in all major technological fields. Since the formal conception of Artificial Intelligence and machine learning, way back in the 50s, more than 300,000 patent applications and over a million scientific journals have been published.
Further, within the elaborate world of AI, machine learning has always been a defining aspect which attracted significant attention from the very beginning. WIPO has stated that over one-third of the published patents/applications in the AI domain are related to Machine Learning. It has been estimated that the average annual growth in patents related to machine-learning is somewhere between 25-30 percent. Machine learning techniques such as deep learning, reinforcement learning, neural networks have seen unprecedented growth in terms of patent filings in the last few years. So, here’s a question – What does this flourish of activity reveal about the future of artificial intelligence in the world of Intellectual Property? The answer, as it turns out, is many-fold.
AI has often been compared to the “Electricity of the new era”. If so, Machine learning can surely be considered to be the wire which conducts it. WIPO has recently taken upon itself to develop a framework for the field of AI, including the applications of machine learning such as processing of speech and digital signal processing. The vital areas which would be completely transformed by AI were also identified, such as Transport and Communication. However, other sectors such as Law, Banking, Medicine, Entertainment, Agriculture are not far behind either in utilizing machine learning and AI, and building their respective patent portfolios as well. Bearing these facts in mind, it is not hard to see the growing interest of inventors in patenting their AI end applications.
If this does not seem convincing enough, global leaders and tech giants such as Microsoft, IBM and the like have been working tirelessly to build a hefty patent portfolio in the field of AI applications. The recent patent activity of IBM and Microsoft clearly suggest that these companies want to make their mark as pioneers in AI and machine learning as well. Toshiba, NEC and Samsung are major players in this race too, however, it will be a while before they can catch up to either IBM or Microsoft. A particular focus in recent times seems to be on machine learning techniques which are based on biologically inspired methods and supporting vector machines using supervised learning.
It would be safe to predict that with the current rise of AI and machine learning, the time is not very far off when machine learning would be recognized as a distinct technology in its own right. A strong case can be made in favor of this argument, as seemingly abstract technologies such as cloud computing, cryptocurrency have been acknowledged in the same way. Assigning the same acceptance to machine learning would go a long way, especially keeping in mind the growing industrial and commercial importance of these fields.
An important point to keep in mind in this scenario is also the vast amount of scientific journals and magazines already available pertaining to basic techniques in machine learning. This may make patenting of the core concepts of machine learning difficult, owing to the significant amount of information already available in the public domain. Thus, a certain modification of the existing patent laws may be in order, so that the kinds of AI applications which may be patented are clearly defined. In light of the exponential development this field has seen in recent times, this day may not be very far at all.
Amit Aggarwal is the Co-Founder and Director of Effectual Services which provides end-to-end intellectual property and business and market research support. His responsibilities include directly leading the business development and support functions of the company. He is also responsible for the overall functioning of the company and for creating its growth strategy. He has extensive experience within the IP domain and has worked with leading multi-national and regional corporations in the areas of patent strategy, business planning, operations, patent infringement, prior art searches, patent litigation, and enforcement support services.