We are delighted to present the fourth issue of The Global IP Matrix magazine to you, our loyal readers.
We have had an amazing year and grown immensely in popularity since our launch of the GIP Matrix at INTA in Seattle in 2018.
When we first launched the Global IP Matrix our main goal was to produce an IP publication like no other to educate and captivate our audience with raw, undiluted news reported to you by world-renowned IP professionals from all over the globe (who are experts at knowing how the land lies in the global IP world) and we have achieved this!
Over the last year, we have continued to work with leading IP law firms and service providers to ensure our publication has something for everyone with an involvement in this very interesting industry.
We hope that you really enjoy this issue and many more to come.
Thank you all, for helping us in exceeding our expectations.
From all of us at & The Global IP Matrix & Northon’s Media, PR & Marketing Ltd
AI: PATENTS Is it changing patent prosecution? Invention submission AI has proven to be valuable to patent committees during the invention submission process. Patent committees typically receive an invention submission and want to do a high-level prior art analysis before even evaluating the submission to determine if it is worthy of patent protection. Committees want an easy method to understand if the invention is novel. With AI, they can take the text of the invention disclosure and put it into the system. They do not even need to know how to structure a Boolean search because, within moments, they will see highly predictive results. Some feel that artificial intelligence (AI) is revolutionizing the way patents are prosecuted, while others disagree. When we hear this term used in relation to patent prosecution, we immediately think of prior art searching. However, AI is being employed in several other ways. As Susan Krelitz, adjunct professor of Intellectual Asset Management at the Mitchell Hamlin School of Law said, “IP Law firms and departments will use AI if it makes their life easier, faster or less expensive. It is that simple.” Let us discuss each of the following areas, with specific examples, where AI has proven to be easier, faster or less expensive: • Prior art searching • Invention submission evaluation •Watching the competition and identifying new competitors •Directing R&D with white space landscaping •Opposition Invalidity Searching Prior art searching The most obvious use of AI within the IP industry is prior art searching. AI and machine learning are technologies that allow us to easily and quickly gain insight into massive amounts of patent data. The traditional method of conducting a prior art search is to have a researcher construct a query into a patent database. The query will identify published patents that meet the specific criteria in the query. The criteria may include class codes, keywords, exclusionary words, etc. The success of the prior art search is dependent on the skill of the searchers. Did they consider the right classes? Did they select the right keywords? Did they exclude keywords, without which the results will be overly inclusive? Did they use the correct Boolean operators? In other words, the search inquiry will return exactly what the researcher requested, nothing more and nothing less. The result of a traditional search is usually a long list of patents that the searcher must then sift through and prioritize. AI-based searching is different. It processes human language with flexible semantics. There is no need to learn Boolean search structures. AI allows the user to input any description of an invention directly into the system, which then automatically extracts the meaning of the text and identifies patents with a similar purpose or technical content. The system intelligently analyses the data and is not dependent on the specific quires selected by the searcher. Take Octimine, for example. An innovative start-up in the field of IP management and recognized as one of the leading AI platforms, Octimine takes semantic patent search, analytics, and machine learning to the next level. Founded in 2015 by former Max-Planck-Institute and LMU Munich researchers, the company was acquired by the Dennemeyer Group in October 2018 and can assist its users, through AI, in various aspects of patent prosecution. Octimine has a simple user interface but also uses a hybrid approach for more flexibility. The software solution allows a searcher to input natural language text in any format and refine the scope of the search by using specific filters. One example of a filter is a date range. Octimine users can restrict the search to prior art that existed on or before a particular date. dennemeyer.com Although the ease of entering a query is a definite advantage of AI, many see the way AI returns results as even more valuable. Traditional search engines return a long list of patents with little or no ranking and no visualization. Octimine ranks results by relevance and allows the searcher to quickly see the most relevant prior art. Modern IP search tools also use visualization to illustrate search results and help users to get an overview of the results in a split second. Although AI has substantial advantages over traditional search tools, it is not universally accepted. There are several reasons given by detractors for not using AI, the most common being that Boolean searching is proven and safe. Others complain that using AI involves a “Black Box.” The searcher does not know how the search was performed. Others complain that they already know how to do Boolean searching and they do not see the need for a simplified method. To help overcome these concerns, the experts suggest using AI searching alongside traditional methods. Many skeptical Octimine users have been surprised that AI has identified relevant prior art overlooked by conventional methods. Because AI is so easy to use, running an additional AI-based search to augment a traditional search is not time-consuming nor is it expensive. Several large IP departments use Octimine to do this type of first screening of the invention. If prior art is identified that is directly on point, they can decide to terminate the patent process before investing a lot of time. If the search identifies prior art, but the art is not definitive, the committee can ask the inventor to clarify any ambiguity. This can all be done without a professional searcher and can, depending on the results, save the committee from investing unnecessary time in the process. Watching, identifying and comparing competition AI is ideally suited both for comparing a company’s portfolio to its competitors’ and for identifying unknown competitors. There are traditional systems to monitor and compare competitive portfolios, but those systems require the company to identify the competitors first. AI allows a company to input a patent portfolio into the system and then ask the system to identify similar portfolios. If the company is using Octimine, it will identify the most similar portfolios, regardless of whether the competitor is even known to the company. Several analytics and visuals can be run to compare similar portfolios. Directing R&D with white space landscaping Several progressive companies are using AI to identify white space where they should direct their patent and R&D activities. AI reveals the patent activity of a technology, provides an overview of the state of the art and offers valuable insights to commercial and technology managers. As such, enough data is available to inform the R&D department as to where they should focus their activity and where the IP department should focus its filling strategy. Octimine, by way of example, has several graphical analytics to make it easier for the company to see the white space. Opposition / invalidity search When objecting to a competitor’s patent, the first option is to file an opposition (at the EPO), or a post-grant review (at the USPTO) and try to prove that there was non-cited prior art that invalidates the patent. AI is ideally suited for finding similar patent art. If using Octimine, all a user must do is insert the patent number and set a filter for the appropriate date. Octimine will identify prior art that is on point. Integration with IP management systems The most sophisticated AI systems offer APIs that allow integration of the AI system to their customers’ other systems. For example, Octimine has an API that allows search results to flow into other systems where they can be associated with the relevant matter. The Dennemeyer Group plans to integrate Octimine into DIAMS IQ, Dennemeyer’s IP management software system. One example of where this integration is valuable is in the invention submission and review process. Once Octimine is integrated, inventors and patent review committee members can review the search results in the same system they use to manage the invention submission. They will be able to make an AI-based novelty search a standard part of the review process. Other uses This article is not an exhaustive list of the ways AI is used by IP departments and firms today. Other uses include identifying licensees, patent valuation, patent proofreading, general landscaping, and clustering. The future of AIbased IP systems No one will question that AI is here to stay. The most progressive firms and departments are already using AI to make certain processes easier, faster and less expensive. As systems like Octimine become more pervasive, use will increase and detractors will melt away. About the Dennemeyer Group The Dennemeyer Group has more than 55 years of experience in delivering quality Intellectual Property services including patent annuities, trademark renewals, recordals, strategic IP consulting and intelligent software solutions for efficient IP management. These services are further expanded when coupled with Dennemeyer & Associates, the group’s law firm, to include EP validations, PCT nationalizations, trademark, and patent filing and prosecution. 30 www.gipmatrix.com www.gipmatrix.com 31