“Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks.”

– Stephen Hawking

Despite its wide-spread adoption and further sub-technologies being developed over the years, the field of AI has remained murky to outsiders. For generations, Artificial Intelligence or AI has been depicted to the general public as a threat to our existence or as a superior being which deems our species unworthy of the planet. There exists a definite lack of precise definition of the field and there is little, to no information regarding where the world nations are at with respect to developing the technology.

In pursuit of enhancing the clarity on this topic, EconSight – a leading Switzerland-based Business Research and Consulting firm, partnered with PatentSight and the Swiss Federal Institute of Intellectual Property to conduct a deep-dive into the technology field of Artificial Intelligence. Kai Gramke, who is the CEO at EconSight, presented the findings from the study at the PatentSight Summit 2019.

AI2

In reality, the field of Artificial Intelligence has more to do with software or networks that are capable of learning to solve complex problems on their own. Although still in the nascent stages of development, AI has seen widespread implementation by businesses and industries to help them solve complex and labor-intensive problems. Yet there lacks a precise definition of the field, which clearly identifies its various applications and sub technologies.

 

Defining the technology field of Artificial Intelligence using patent data

Patent data contains a hoard of information that, when extracted and analyzed using scientific methods, can generate valuable insights into the landscape of a specific technology. Using citation data and information regarding the country in which a patent is filed in, it is possible to develop a clear understanding about which firm leads in number of patents filed under a particular technology and in which countries they have a strong hold. Different business sectors, along with corresponding key players within it that areadopting this technology, have also been studied and ranked based on the number of world-class patents owned by each of them. For the purposes of this study, EconSight considers that a world-class patent belongs to the top 10% of the patent families in a technology field. 

 

Combining World-Class Research with best-in-class Patent Data and Analytics

EconSight uses sophisticated approaches, comprehensive analysis methods and design scenarios in their quest to rethink economics or business from a global, more holistic perspective. As a leader in business research, they realize the importance of high-quality and reliable data for accuracy of results. This is precisely why they trust in PatentSight, as the quality of our database has already been endorsed by the use of our services in the European Commission’s landmark merger case.

At PatentSight, we understand the importance of high-quality data in providing actionable insights. To ensure a continued influx of accurate and curated data into our software, we have a dedicated team in place that works day-in and day-out to comb through the data that is published for analysis on the LexisNexis PatentSight Business Intelligence software.

Collaboration nu-1

The study was further supported by various analysis tools and preset comparison charts and graphs, available in the PatentSight software, from where relevant insights and analyses can be extracted. These presets and tools, help to delve deep into the patent database. For instance in this study, to identify the different technological classifications and companies that are active within it, that pertain to the broader field of AI. The synergy that was developed by combining EconSight’s research prowess and PatentSight’s robust tools and high-quality data, ensured that the study delivered, both in terms of value of content and accuracy of findings.

 

Results of the study

The published study has invaluable insights into the, hitherto elusive, field of Artificial Intelligence. The different sub-technologies that are classified under the broad spectrum of Artificial Intelligence are identified and defined.

AI and its Sub-Technologies

As concluded by the study, the field of AI is divided into 3 sub-technologies, the development of which has been exponential in the past three years, can be seen in the graph below. The sub-technologies were further defined as follows:

  • Deep learning – a machine learning technique that performs learning in more than two hidden layers. It performs feature extraction and transformation. Each successive layer uses the output from the previous layer as input.

  • Neural Networks – a machine learning algorithm inspired by the working of the human brain enabling a system to learn from observational data. A simple neural network consists of an input layer, a single hidden layer and an output layer.

  • Machine Learning – research field in computer science that tries to apply algorithms to a set of data samples to discover patterns of interest.

AI patent development over years-3                                                   Source: EconSight, IGE, LexisNexis PatentSight, 2019

Artificial Intelligence: Countries and Fields of Application 

Detailed analysis of different industries, where AI has been already implemented, were also performed as part of the study. This information was looked at, from the perspective of countries, to identify leading nations in the respective industrial application of AI.USA, Germany, Switzerland, China, France, Japan and South Korea were found to be leading innovations in the field of AI.  When diving deeper into company/industry level, industries like Healthcare, Energy, Industry (Manufacturing), Data Security, Fintech and Marketing were found to be developing this technology to better their processes or to bring advanced technology to their end-customer. Among these sectors, Healthcare was found to be the one witnessing the largest number of patents filed under thetechnological scope of AI in recent years. The graph below shows the global development of patent portfolios in these individual industries over the past two decades.

AI patent development in industries-1

                                                                                       Source: EconSight, IGE, LexisNexis PatentSight, 2019

In his presentation at the PatentSight Summit, Kai showcased various other interesting graphics, as well, that displayed the current state of innovation in AI among major countries around the world. USA was seen to be the front runner in this field of research for the past few years and seemed to target a strong hold in major foreign markets as well. Recent trends, though, show a different picture, where China is also gaining traction and rapidly increasing the number of patents being filed under the scope of AI. Although, this number is still incomparable to the US, when considering only world-class patents. Apart from in Germany and inChina, when compared to domestic companies, American companies hold the strongest patent portfolios in all other foreign markets, and they have been doing so consistently over the years.  This could very well indicate that although widespread implementation of the technology has only begun, firms see the need to protect their innovations more broadly in anticipation of opportunity loss.

  

“AI is everywhere. It’s not that big, scary thing in the future. AI is here with us.” 

– Fei-Fei Li

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