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Contents
Artificial intelligence (AI) continues to grow more pervasive each day and is being used in nearly every industry, from cybersecurity and robotics to healthcare and fintech. Due to its broad application, more industry-specific AI startups are joining the market all the time and, as a result, AI spending has greatly increased. In fact, according to IDC Research, worldwide spending on artificial intelligence systems was $5.3 billion in 2015 and is projected to reach $19.3 billion in 2018 and $46.8 billion by 2020. And from 2000 through 2016, annual VC investment in AI startups grew 6-fold to nearly $3.5 billion (2017 Artificial Intelligence Index Report). In an industry growing this quickly and experiencing such a brisk pace of innovation, protecting your company’s inventions is vital for long-term success.
Why Patenting AI is Important
The rapid pace of innovation and the influx of artificial intelligence companies make protecting intellectual property of the utmost importance. Organizations that understand their inventions are at stake, and thus develop strong patent portfolios, will prevail. Those that fail to protect their technology leave themselves vulnerable to competitors and copycats as well as lawsuits.
In addition to protecting a company’s technology, obtaining artificial intelligence patents provides other benefits as well, such as faster growth and higher valuations. For startups, patenting their technology increases the likelihood of first round funding by 53 percent, and second round funding increases by 67 percent. Additionally, the probability of a successful exit skyrockets, with the chances of an IPO increasing by 153 percent and an acquisition increasing by 83 percent (Office of Chief Economist Report).
Challenges to Patenting AI
There are some special considerations when patenting AI inventions. To better understand what they are, consider the figure to the right, which shows three types of deep learning invention types.
Type I uses deep learning, such as a deep neural network, to read signals output from some physical device like sensors on an industrial process, machinery, a chemical reaction, or a digital image. This is a common use for deep learning – improving some process or thing by applying deep learning to its form or operation.
We call Type I inventions “closed loop” because they use deep learning to provide feedback into the system or thing being analyzed, to improve upon it. The United States Patent and Trademark Office (USPTO) favors Type I inventions and will grant patents for them as long as they pass the other requirements, such as being sufficiently inventive.
Type II inventions are what we call “open loop.” This describes when deep learning on one system or thing is applied to improve or change a different system or thing. The USPTO also favors this type of invention.
Type III inventions can be problematic to patent. Not only is the invention open loop, but the results of the learning are merely displayed, or stored in files. The USPTO considers the mere display or storage (or communication) of learning results as simply moving data around and not doing anything technologically useful with it. Thus, it’s much more challenging to obtain patents for Type III inventions than Type I or II inventions.
Why TurboPatent is the best choice for AI patents
TurboPatent possesses deep domain expertise in artificial intelligence. We use AI technology (semantic search, Natural Language Processing) to improve the efficiency of the patent drafting process, and to provide analytics on the patentability of an invention. These tools ensure that the patents our clients pursue are more likely to be awarded, and help ensure patent applications our artificial intelligence domain experts produce are accurate and consistent. Not only do we possess deep knowledge of AI, it is an integral part of TurboPatent’s identity. This technical knowledge and knowhow ensure your artificial intelligence patents will be in the most capable hands.
*Content Provided by FSP LLC, a patent law firm.