Artificial intelligence is rapidly evolving, and large language models (LLMs) like ChatGPT are one of the more exciting examples. Their generative capabilities have implications for our patent system, some of which are underappreciated and nonintuitive.
Under U.S. patent law, an inventor may not obtain a patent if the claimed invention would have been obvious to an artisan of ordinary skill, in view of the prior art. (See 35 U.S.C. § 103.)
Though we recently touched on the U.S. Court of Appeals for the Federal Circuit ruling that only natural beings, which do not include artificial intelligence, can be an inventor under the U.S. Patents Act, the decision merits additional discussion.
Defining artificial intelligence (AI) can be a challenging task due to the expansiveness of its reach and evolving nature if its application. At its core, AI is the use of computer systems to perform tasks which historically have required human intelligence. Thus, AI can interpret and learn from data, creating alone, using what it has learned from this data, without additional human input. Such machine learning is further refined into deep learning, in which artificial neural networks—algorithms which copy how the human brain works—learn in a manner that mimics how humans do but by processing vast amounts of data. This neural networks approach of having computers “learn” as the human brain does differs from the more traditional rules-based computer programming, in which a computer is programmed with the explicit rules it will follow. Even as AI-powered computers begin to mimic human thinking, going beyond following predetermined tasks and routines, it’s not surprising that while AI is good at rules-based thinking, it cannot mimic certain functions of the human brain yet.
The U.S. Court of Appeals for the Federal Circuit has agreed with the U.S. Patent Trademark Office (PTO) in holding that artificial intelligence (AI) cannot be considered an “inventor” for purposes of obtaining patents.
Many companies are increasingly looking to the federal government during COVID-19 for liquidity or other financial assistance. Colleague Drew Schulte recently spoke with host Joel Simon on Pillsbury’s Industry Insights podcast and highlighted a variety of strategies available to companies with intellectual property assets (and particularly patents or patentable assets) to reduce costs and to generate revenue by monetizing their IP assets.
As the COVID-19 outbreak continues its spread across the globe—resulting in more than four million infections worldwide and thousands dying of the virus every day—a growing community of scientists, software developers, health organizations, public consortia, private companies, and federal agencies (e.g., NIH) have been collaborating and sharing their patented technologies and IP rights with the shared goal of understanding and responding to COVID-19.We briefly look at some of the mechanisms, including open source software, patent pool, and open patent pledge, that are helping facilitate this open innovation paradigm.
Innovation has become seemingly synonymous with operating a successful business as the projected success of a company is measured by both its ability to innovate and its track record of innovation. Patent law is an area of law tasked by the U.S. Constitution to promote innovation. Patents and innovation should therefore ostensibly have some correlation for business.
While companies in every industry are working hard to figure out the best response to this global pandemic, those in the pharmaceutical and medical device industries have been faced with some unique challenges related to the balancing of intellectual property rights with serving the public good. One particular question that such companies might face is whether parts of their patent portfolio are connected to federal funding and if so, how the Bayh-Dole Act may come into play as the government faces increasing pressure to meet public health needs.
As the world collectively struggles to adapt to the “new normal,” it is clear that one of many challenges facing businesses and individuals is how to best adapt to supply chain disruptions. A key example of where these shortages are being reported is in the health care sector, which is experiencing a limited (or non-existent) supply of personal protective equipment (PPE) for health care workers and ventilators for patients. Not only have these shortages placed a strain on those treating patients who have fallen ill from COVID-19, but it has also frustrated efforts to fully identify who may or may not be infected. As one example, in a recent interview conducted by The Indicator podcast, it was reported that limited supplies of PPE to protect workers during patient sample collections were in turn limiting the ability of the University of Washington’s health center to test patients for coronavirus.
With great power comes great responsibility. 5G is the next generation of 3GPP technology. Along with having the potential to facilitate the next leap in connectivity, 5G technology supremacy also has the power to define the geopolitics of the next century. As the global battle for 5G dominance plays out, companies are driving hard to secure coveted Standard Essential Patents (SEPs) encompassing 5G technology. The victor will secure substantial revenue and money flow in the form of patent royalties.
Be you a founder, would-be investor or acquirer, correctly valuing the intellectual property of a company is rarely a simple task, but it can be even more challenging when that IP involves artificial intelligence or machine learning. See what our colleague Josh Tucker has to say about the challenges and importance of protecting underlying IP on 7 Mile Advisors’ Deal Talk podcast, “How Patents, AI and Machine Learning Affect Value.”
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