'The Big Sunday Show' highlights Elon Musk's upcoming interview with Tucker Carlson warning about the dangers of A.I.. The U.S. Patent and Trademark Office has launched a process that could determine whether artificial intelligence systems can get full or partial credit as inventors of new ideas that win patent protection. USPTO on Monday announced it would hold a "listening session" on this question in early May, and is accepting public comment on whether AI has now become so advanced that it should somehow be credited as an inventor when it produces an idea that has yet to be conceived by mankind. The question of whether and how to credit AI for new inventions is one that has emerged over the last few years. In 2019, USPTO asked for public comment on whether AI is now so advanced that federal laws need to be rewritten in order to protect inventions from "entities other than natural persons."

When Michelle K. Lee, '88, SM '89, was sworn in as the director of the U.S. Patent and Trademark Agency in 2015, she saw an opportunity. The agency was a bit behind on digital transformation and adopting things like cloud computing and artificial intelligence, but the organization had mountains of data -- like more than 10 million patents the office has issued since opening in 1802, and 600,000 patent applications received each year. Lee led a project to use data and analytics to modernize the agency, such as implementing AI solutions to improve patent searches and the speed and quality of patents issued. By gathering data about how patent examiners make decisions, and determining outlying behavior, the office could also pinpoint areas in which examiners would benefit from targeted training. "If the U.S. Patent and Trademark Office, a 200-plus-year-old governmental agency, has a machine learning opportunity, so too does every organization," Lee said during a presentation at EmTech Digital, hosted by MIT Technology Review.

In a new report released on October 27 by the United States Patent and Trademark Office (USPTO), more than 42% of all technology areas in 2018 incorporate Artificial Intelligence (AI) in their new inventions. The majority of these improvements come in knowledge processing and planning/control, which involve analyzing information to gain new insights and using those insights to manage a business process. CIOs continue to talk about how vital AI technologies are, but this new report confirms that if companies aren't already putting that talk into action, they are behind the curve. The danger of falling behind is even greater for companies that haven't started adoption since the statistics only cover till the end of 2018. In the last 18 months, the percentage of technologies that include AI has undoubtedly continued to increase. The report also confirms an increased interest by the office in this technology and a higher willingness to consider new applications that include them.

MIT SMR Connections is the custom content creation unit within MIT Sloan Management Review. In this Q&A, Michelle K. Lee, vice president of the Amazon Web Services (AWS) Machine Learning Solutions Lab, shares real-world examples of machine learning in action, describes four key implementation challenges, and offers other advice. This conversation has been condensed and edited for clarity, length, and editorial style. Q: Can you provide an overview of how artificial intelligence (AI) and machine learning (ML) are driving digital transformation? Lee: AI and machine learning went from being aspirational technology to mainstream extremely fast.

The average time it took from filing to issuance was 850 days. The patent that took the longest time to issue was U.S. Patent No. 10410308, System, method, and device for personal medical care, intelligent analysis, and diagnosis.

The United States Patent and Trademark Office (USPTO) published a notice in the Federal Register last month saying it's seeking comments, as spotted by TorrentFreak. "Should authors be recognized for this type of use of their works?" asks the office. Earlier this year, the office similarly asked for public opinion on AI and patents. None of these questions have concrete answers in US law, but people have been debating the potential outcomes for years. The situation might be a little clearer when you're looking at something like an AI-based app where a user has to make a lot of decisions to shape the end result.

The U.S. Department of Commerce's Patent and Trademark Office (USPTO) is asking for the help of experts and the broader public to determine the impact AI will have on intellectual property and "whether new forms of intellectual property protection are needed." A call for public comment was published in the Federal Registrar by the USPTO today in search of answers about such issues as how AI is reshaping perceptions of inventions or whether additional information should be required to claim a deep learning system as an invention since they can have a large number of hidden layers and weights that evolve. To help solicit responses, the notice in the federal registrar comes along with a series of questions such as "what is an AI invention and what does it contain?" "What are the different ways that a natural person can contribute to conception of an AI invention and be eligible to be a named inventor? Structuring data in order to train a model?

The U.S. Department of Commerce's Patent and Trademark Office (USPTO) is asking for the help of experts and the broader public to determine the impact AI will have on intellectual property and "whether new forms of intellectual property protection are needed." A call for public comment was published in the Federal Registrar by the USPTO today in search of answers about such issues as how AI is reshaping perceptions of inventions or whether additional information should be required to claim a deep learning system as an invention since they can have a large number of hidden layers and weights that evolve. To help solicit responses, the notice in the federal registrar comes along with a series of questions such as "what is an AI invention and what does it contain?" "What are the different ways that a natural person can contribute to conception of an AI invention and be eligible to be a named inventor? Structuring data in order to train a model?

In this time-lapse, Intel breaks its own Guinness World Record for the most drones flown simultaneously, and they look pretty cool while doing it. IBM has been granted a patent for a coffee drone. These diagrams are part of the application the company filed with the U.S. Patent and Trademark Office. The barista handing you your cup of coffee might one day be a drone. IBM has secured a patent for a coffee drone that not only flies around public spaces to deliver cups of brew but also predicts which people need caffeine pick-me-ups.

The U.S. Patent and Trademark Office published a patent application filed by Microsoft that describes a method of cheat detection for games on a platform level using machine learning. The idea is to bring cheat detection outside the game itself given platforms like Xbox Live and PlayStation Network can't detect any wrongdoings within the game. To do this, Microsoft proposes using artificial intelligence. "A platform that hosts third-party games may not be able to detect cheating that occurs in third-party games, even where achievements in third-party games are managed at the platform level," the patent states. "When the third-party game notifies the game platform of the improperly awarded achievement, the game platform may award the player an item in response to the achievement, thereby rewarding the cheating behavior."