The deep learning algorithms of artificial intelligence can identify patterns that help inventors think laterally, make connections between nonobvious ideas, pinpoint hidden invention features, and exploit new science and technology-based opportunities. "To invent, you need a good imagination and a pile of junk." So said Thomas Edison, America's most prolific inventor. Yet the march of technology is now changing the great man's inventive equation: powerful algorithmic advisory systems are now giving inventors far more fertile imaginations, even if they don't have very much of one themselves. After being fed vast datasets of information on a field of inventive endeavor, deep learning algorithms identify patterns that help inventors think laterally, make connections between nonobvious ideas, pinpoint hidden invention features that rivals have missed, and exploit new science and technology-based opportunities from, say, patents and journals.
To patent machine learning, you will need to correctly claim and describe your invention while making sure that you comply with current laws related to this type of intellectual property. Machine learning plays an important role in much of today's technology. For example, without machine learning, effective internet searches would not be possible. The problem with machine learning, however, is that it can be hard to file patents for inventions in this growing field. It is not always immediately clear what software inventions are eligible for patent protections.
Who are the inventors of patents? Since George Washington signed the first patent in 1790, the United States has issued patents to people of various ages, ethnicities, and genders, with some patent inventors being as young as two when they filed. The varied backgrounds of these inventors stems from the United States Patent and Trademark Office's ("USPTO") broad definition of an inventor, laying out an inventor to "mean the individual or, if a joint invention, the individuals collectively who invented or discovered the subject matter the invention." But what happens when the inventor is a machine? This is the exact issue Dr. Stephen Thaler sought to resolve with the USPTO as well as other worldwide patent offices.
While Intellectual Property (IP) law is already quite complicated, especially when international boundaries are concerned, with the advent of Artificial Intelligence (AI), IP law promises to become even more complex. For example, when AI is involved in an inventive or creative process, who holds the IP rights to that work? Can AI hold a copyright (AI is already creating art, writing books, and taking photographs)? Can AI hold a patent? Recently, two UK academics attempted to file patents on behalf of an AI system known as DABUS, which invented a robot-friendly system of interlocking food containers without human involvement.
Patents are used to grant exclusive property rights to an inventor and prevent their discovery from being copied by others. The main requirements for a patent are that the invention must be novel, non-obvious and be useful or have an industrial application. Patents are a central part of how pharma does business. Pharma products require longer and more complex research and development (R&D) cycles than products in other industries. Consequently, companies invest significant amounts of money into their new products early on in their development.