Neural Networks and Artificial Intelligence Advances will need to benefit from the Intellectual Property Laws
Neural networks and real world applications of artificial intelligence will require the protection of the intellectual property law in order to benefit the companies and programmers creating the new innovations. In the coming weeks and months I will be attempting to apply concepts of deep learning and neural networks to copyright law and patent law. Most of you know my name is Robert Z. Cashman, and I am a patent attorney and the owner of the Cashman Law Firm, PLLC located in Houston, Texas. While most of my time is spent defending clients who are accused of misusing bittorrent networks, I did start my law firm with the intention of protecting ideas and furthering technology. And, in today’s fast paced world, what better technology is there to discuss other than artificial intelligence (A.I.), neural networks, and deep learning.
Are Artificial Intelligence applications of neural networks patentable?
For the budding attorney, the best way to understand neural networks is that it is code, likely copyrightable and patentable (if it accomplishes a useful goal). Obviously you can’t patent an idea, nor can you patent an algorithm (see the Metabolite v. Labcorp paper I wrote almost twelve years ago), nor can you patent the correlation between two sets of data and the interpretation thereof (a “thinking step” linking the two together). Thus, the mechanics of a neural network and how it works might not be patentable, but how that neural network is applied in the context of creating a useful result IS likely patentable (especially if it is tied to a machine).
Thus, as you can see, a neural network and the way it is programmed and applied to achieve an end result IS protectable, IS likely patentable, and thus can be understood as being PROPERTY. Thus, it can be protected with a patent, it can be sold or assigned to another individual or entity, and it can be copied or stolen in violation of the copyright laws.
I am getting ahead of myself. Let’s start off with some basic definitions so that any non-scientific person will understand how and why a neural network or deep learning in general could be useful to them.
What is a neural network and how can artificial intelligence make use of AI to provide a useful result?
A neural network is a program that uses data fed into it in order to output a result.
For example, as explained by Andrew Ng, the founder of deeplearning.ai, if someone has a set of data (e.g., a list of homes in a particular zip code, along with various houses that have been sold and for what prices), and they also have other sets of data (such as how many bedrooms a family of a particular size requires, and the walking distance of each house in a neighborhood to the local school), a neural network can crunch the data to determine which house is most appropriate for which family (e.g., which house has the correct number of bedrooms), which house best meets that family’s needs based on the ages of their children (e.g., which house is closest to the school), and the predicted price of that house based on past sales, an artifical intelligence neural network would be able to help that family choose the best home for the least amount of money that satisfies that family’s needs.
Size of the neural network matters.
In the artifical intelligence world, the size and type of the neural network required to achieve a particular result will become a relevant consideration. For example, if a local real estate broker is looking to provide an artificial intelligence service that can help place families into the best homes for their needs, and he is only looking to do so in a small area (e.g., a small dataset), he would need the use of only a small neural network.
However, if that real estate broker was looking to scale up and expand the scope of that service to the entire state, or even all of the real estate in the US, he would require a significantly larger neural network.
SUMMARY: AI applications of neural networks are likely copyrightable and patentable.
In sum, the takeaway from this article is that artificial intelligence runs its code using neural networks, and the code itself is likely copyrightable, and the application of that code is patentable. The code itself is protected from others stealing, copying, or using the code without authorization, and doing so can be either considered copyright infringement or patent infringement, depending on how the neural networks are coded.
[CONTACT AN ATTORNEY: If you have a question for an attorney about neural networks, deep learning, or artificial intelligence applications in general (or how to protect something you have created), you can e-mail us at info[at]cashmanlawfirm.com, you can set up a free and confidential phone consultation to speak to us about your AI application, or you can SMS or call us at 713-364-3476 (this is our Cashman Law Firm, PLLC’s number)].
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